In the case of indigenous grapevine varieties, the aim of clonal selection is twofold: to improve their technological cultivation problem while preserving the varietal character. As the sensitivity of perennial crops to climate change becomes more pronounced, clonal selection, which is already very time-consuming for perennial woody crops, may take even longer. In Badacsony, clonal selection breeding of the ‘Kéknyelű’ and ‘Juhfark’ varieties was started in the early 2000s. The problem mentioned above in cultivation technology is the poor fertility of ‘Kéknyelű’ (functionally female-flowered variety), while in the case of ‘Juhfark’ the high susceptibility to grey rot (Botrytis). Based on 11 years of data significant difference in yield between clone B.2. and the base variety was found. In this comparison the year clusters also gave different values, as in years belonging to cluster 1 the ’Kéknyelű’ yielded more than in another year. Both clones of ‘Kéknyelű’ matured with significantly lower pH compared to the base variety. ‘Kéknyelű' is renowned for the distinctive variety character of its wine, which is said to be acidic. Given the acidic nature of ‘Kéknyelű’ wine and the expected increase in must degrees and pH due to climate change, these distinctions may be beneficial in the future. Daily meteorological parameters were also recorded in the years under study, and different indexes were calculated for both of varieties for different phenological periods. The years were classified into 3 clusters and the harvest data were analyzed within each cluster. In the case of 'Kéknyelű' our results revealed significant differences in yield between vintage clusters for clone B.2. However, clone B.1 demonstrated distinct KMW and pH values. Both 'Kéknyelű’ clones have produced a substantially higher incidence of Botrytis infection in cluster 2 years than in cluster 3 years. Botrytis infection only showed statistically significant differences between year clusters for ‘Juhfark’. It is intriguing that in most years, the rotting rate was lower in both clones, especially in year clusters 1 and 3 when the overall rate of Botrytis infection was quite low. Our results highlighted the year-round sensitivity of the two varieties studied and the difficulties of clonal selection.

Flooding, exacerbated by climate change, poses a significant threat to certain areas, increasing in frequency and severity. In response, the construction of supplementary dams has emerged as a reliable solution for flood management. This study employs a Remote Sensing (RS) approach integrated with GIS to assess the feasibility of constructing a supplementary dam near Linville, Brisbane, Australia, with the aim of mit-igating floods and preventing overtopping failure at the Wivenhoe Dam. Using QGIS software and a 25-meter resolution DEM from the Queensland Spatial Catalogue ‘QSpatial’ website, four potential dam sites were analysed, considering cross-sections, watershed characteristics, and water volume calculations. Systematic selection criteria were applied to identify the most optimal option based on dam wall di-mensions, volume-to-area, and volume-to-cost ratios. The selected option was further assessed against predefined criteria, yielding one optimal choice. The study provides insights into the feasibility and ef-fectiveness of supplementary dam construction for flood mitigation in the region, with recommendations for future research and implementation.

Organizational climate is the ascribed psychological meanings and significance associated with the procedures, policies and practices that are recognized and rewarded in the workplace, and hence mediates the effects of environmental stimuli on individuals’ response. Safety climate is a specific organizational climate, i.e., organizational climate for safety. Previous research claimed that organizational climate provides foundation for safety climate, but without elaboration on the foundational mechanisms. This paper attempts to fill up this knowledge gap. As organizational climate is a multi-dimensional phenomenon, this paper chooses two dimensions, i.e., perceived organizational support (POS) and participative decision-making (PaDM), for illustrative purposes. Drawing on an interactive approach to forming climate perceptions, this paper introduces two interactive constructs, i.e., leader-member exchange (LMX) and team member exchange (TMX), and establishes a multiple mediation model depicting the foundational effect of organizational climate on safety climate. A random sample of Hong Kong based construction personnel is used to validate the model. The results show that both POS and PaDM are positively associated with perceived safety climate, both LMX and TMX fully mediate the effect of PaDM on safety climate, and only LMX partially mediates the effect of POS on safety climate. This study sheds light on the foundational effects of organizational climate on safety climate. POS can improve the quality of reciprocal exchange about safety matters between construction personnel and their supervisors, and hence raise construction personnel’s awareness of the priority of safety. PaDM can improve the quality of reciprocal exchange about safety matters vertically and horizontally, and hence have construction personnel aware the importance of safety. In practice, this paper suggests that project managers timely recognize and reward construction personnel’s contribution, genuinely cares about their well-being, and take their suggestions seriously in making decisions. In this way, the quality of both vertical and horizontal exchange about safety matters improves, and a sound and positive safety climate ensues.

Globally, the intensity and irregularity of weather and climate extremes are increasing due to climate change. In Ethiopia, the occurrence of extreme events has been increasing, reporting severe impacts on environment which led to losses of lives and livelihood of societies. In this study, Heat Wave Magnitude Index daily (HWMId) was used to analysis heat wave magnitude in the Middle Awash Basin of Ethiopia. Gauge data obtained from Ethiopian Meteorological Institution (EMI) for 1981-2022 period and the future projection was taken from Coupled Model Intercomparison Project Phase 6 (CMIP6) under two socioeconomic pathways (SSP 2 and SSP 5) scenarios. The findings clearly showed that the area aggregated annual temperature anomaly increasing each year, 2015 was one of the warmest year on record with an anomaly of +1.8 °C. Severe to extreme heat wave recorded particularly during the last 10 years. For the future projection, under SSP 2-4.5 forcing scenario, the annual average air temperature projected to be warmer, which increasing 1.7 ℃ to 1.8 ℃ during mid-century and 2.3 ℃ to 2.4 ℃ end of century. Meanwhile, for SSP 5-8.5 forcing, the projection indicated an increment of 2.2 ℃ to 2.5 ℃ under mid-century and 4.4 ℃ to 4.8 ℃ end of century. Concerning the severity of heat wave, extreme to very extreme heat wave projected under SSP 2-4.5 forcing scenario and supper extreme heat wave projected under SSP 5-8.5 forcing scenario, respectively. The increase in extreme events may have a negative impact on health, water availability and food security. Therefore, the result of this study are essential for making wise decisions and for developing suitable strategies for climate change adaptation and mitigation that could minimize the risk of unusually extreme weather events.

Climate change is a phenomenon that makes the climate system of a given region to be more unpredictable and increases the risk of water-related problems. GCMs under the new CMIP6 framework holds several climate models with many improvements as compared to past similar efforts. The improvements are mainly in the number of scenarios formulated, setup, parametrization, and resolution. In this study, 10 downscaled climate models from CMIP6 are evaluated by applying statistical and data mining tools and are ranked based on their capability to describe the historical observed series. The result of the analysis showed that the outputs of the MPI-ESM1-2-HR model have a good overall ranking among those 10 models. The output of this top-ranked model is used to understand future climate over UASB after properly bias-corrected using the QM method. Results of the bias correction step show that average annual precipitation has shown an increment of 6.5\% in the middle (SSP2-4.5) and 10.3\% in the worst (SSP5-8.5) case scenarios for the mid-century (2040 - 2069). Similarly, for the end of the century (2070 - 2099) an increment of 4.7\% and 17.5\% was predicted for the two scenarios respectively. Whereas average annual maximum temperature series showed an increment of 1.5 $\degree C$ for middle and 2.6 $\degree C$ for the worst case in the mid-century. At the same time, an increment of 2.2 $\degree C$ and 3.5 $\degree C$ were predicted for the end of the century similarly for those scenarios. Furthermore, it was predicted that the average annual minimum temperature series will have an increment of 2.6 $\degree C$ and 3.1 $\degree C$ for mid-century and 3.1 $\degree C$ and 4.7 $\degree C$ for the end century for the two scenarios respectively. An increase in precipitation with increased land degradation problems in the sub-basin increases the risk of flood events in the future.

Introduction. Environmental Health in a Global World at New York University was re-designed as a class participatory effort, challenging undergraduate students to understand environmental hazards and the resultant adverse health outcomes by embracing the inherent complexity of environmental risks and proposing solutions. Methods. Following introductory lectures, students are placed into teams and assigned a specific perspective, or avatar, which includes learning to see the challenge from the perspective of a technical expert such as a biologist, an engineer, or an anthropologist. The teams then design specific systems maps to visualize the complex interactions that lead to adverse health outcomes after a given environmental exposure. The maps highlight potential leverage points, where relatively minor interventions can provide a disproportionate benefit in health outcomes. The teams then explore potential interventions and identify the potential unintended consequences of those actions, develop and advocate for innovative new strategies to mitigate risk and improve outcomes. Results and Discussion. Over the past 5 years we have taught this methodology to over 680 students with strong, student-oriented results. The teams created and presented more than 100 strategies, addressing a diverse set of environmental challenges that include water contamination, gun violence, air pollution, environmental justice, health security, and climate change. Developing the strategies helped the students understand environmental threats in a more holistic way, provided them with some agency in finding solutions, and offered an opportunity for them to improve their presentation skills. The responses in course evaluations have been enthusiastic, with many students reporting a deep impact on their college experience.

This study assessed farmers’ perception of climate change, estimated the determinants of, and evaluated the relationship among adaptation practices using the multivariate probit model. A survey in 300 agricultural households was carried out covering 10 sample districts considering five agro-ecological zones and a vulnerability index. Four adaptation choices (change in planting date, crop variety, crop type and investment in irrigation) were deemed as outcome variables and socioeconomic, demographic, institutional, farm-level and perceptions variables were deployed as explanatory variables. Their marginal effects were determined for three climatic variables—temperature, precipitation and drought. Age, gender and education of head of household, credit access, farm area, rain-fed farming and tenure, are found to be more influential compared to other factors. All four adaptation-options are found to be complimentary to each other. Importantly, the intensity of impact of dependent variables in different models, and for available adaptation-options, are found to be unequal. Therefore, policy options and support facilities should be devised according to climatic variables and adaptation options to achieve superior results.

The way humans use natural resources and especially freshwater, reflects their relationship with nature. It also influences the conceptual Water Resources Management (WRM) model. A historical review shows that the interplay between Humans and Nature is diachronically in constant change between two opposites: conflict and cooperation. Lessons from the past 20.000 years indicate that the WRM model is a function of two main parameters: (1) socio-economics, and (2) climate conditions. Three different Eras of the Humans-Nature relationship have been distinguished: (1) Naturalistic: Nature dominating Humans during the Last Glacial Period (100-10) kyr BC, (2) Dualistic: Nature-Humans cooperation and competition from 10 kyr BC to 1800 AD, and (3) Anthropocentric: Humans dominating Nature from 1800 AD to now. Since 2000, the Integrated WRM (IWRM) model is promoted as state-of-the-art and remains anthropocentric producing huge externalities. Its assessment during the last 20 years has given mixed results and needs to be reformulated. The new model we suggest is based on the dialectical tool for conflict resolution. It unifies Humans and Nature and enhances the social dimension of WRM. After identifying conflicts between stakeholders and the natural laws (eristic part), opposite objectives are unified to harmonize Humans with Nature (dialectical resolution). A case study of flood mitigation illustrates the eristic-dialectical methodology.

Low carbon cities are increasingly forming a distinct strand of sustainability literature. Models have been developed to measure the performance of low carbon cities. The purpose of this paper is to formulate a strategy-based model to evaluate current performance and predict future conditions of low carbon cities. It examines the dynamic interrelationships between key performance indicators (KPIs), induces changes to city plan targets and then instantly predicts the outcome of these changes. Designed generic and flexible, the proposed model shows how low carbon targets could be used to guide the transformation of low carbon cities under four strategies: (1) passive intervention, (2) problem solving, (3) trend modifying and (4) opportunity seeking. Further, the model has been applied to 17 cities and then tested on 5 cities: London, New York, Barcelona, Dubai and Istanbul. The paper concludes with policy implications to realign city plans and support low carbon innovation.

Several sun models suggest the radioactive balance where the concentration of greenhouse gases and the albedo effect are related to the Earth's surface temperature. There is a considerable increment of greenhouse gases due to anthropogenic activities. Climate change correlates with this alteration in the atmosphere and an increase in surface temperature. Efficient forecasting of climate change and its impacts of 1.5°C global warming above pre-industrial levels could be helpful to respond to the threat of c.c. and develop sustainably. Many studies have predicted the temperature change in the coming years. The global community has to create a model that can realize good predictions to ensure the best way to deal with the warming. Thus, we propose a finite-time thermodynamic (FTT) approach in the present work. The FTT can solve problems such as the faint young sun paradox. In addition, we use different machine learning models to evaluate our method and compare the experimental prediction and results.

Climate justice as a commons is conceived as the intertemporal climate equity and equal- ity exchange amongst generations. Sustainability, intended as the interplay amongst the economy, the society, the environment, and the governance, is essential to forge the climate justice theoretical framework. On this base, the study attempts to model intertemporal choice amongst generations in these four domains, making use of an over- lapping generations (OLG) model. The proxies detected are GDP growth (economy), environmental quality (environment), and labor growth, and environmental investment (society) as assumptions. The governance dimension is captured by the di¤erence in wealth between young and old generations. The work aims at replying to the follow- ing research question: Which are the conditions for sustainable development such that climate justice holds? The intra-intergenerational exchange is de…ned in two periods, while the individual provides their preferred economic and environmental choice mix as consumption-saving. This study shows that sustainable growth is achievable only with increased young e¤ort and less leisure and consumption.

In the last decades droughts, deforestation and wildfires have become recurring phenomena that have affected both human activities and natural ecosystems in Amazonia. The time an ecosystem requires to recover from carbon losses is a crucial metric to evaluate disturbance impacts on forests. However, the factors influencing and controlling the recovery time and its spatiotemporal patterns at the regional scale are still poorly understood. In this study, we combined forest growth model, remote sensing and field plots, to map Amazonia-wide (300-ha resolution) impact and recovery time of aboveground biomass (AGB) after drought, fire and a combination of logging and fire. Our simulated results indicate that AGB decreases by 4%, 19% and 46% in forests disturbed by drought, fire and logging + fire, respectively, with an average AGB recovery time of 27 years for drought, 44 years for burned and 63 years for logged + burned areas and with maximum values reaching 184 years in areas of high fire intensity. Our findings provide two major insights in the spatial and temporal patterns of drought and wildfire in the Amazon: 1) the recovery time of the forests takes longer in the southeastern part of the basin, and, 2) as droughts and wildfires become more frequent – since the intervals between the disturbances is getting shorter than forest regeneration – potentially causing a long-lasting damage in these fragile ecosystems and a permanent degradation.

We use the third version of the Canadian Local Climate Model as a diagnostic tool to study the climatology of observed CG lightning activity at Maniwaki (latitude: 46,23°N; Longitude: 75,58°W). We examine the dependence between the hourly lightning activity and the related atmospheric variables during the warm season of sixteen years (between 1984 and 2004). The goal of this research is: a) to evaluate the atmospheric static state evolution and its moisture contents for conditions having generated lightning occurrence, b) to develop a CG lightning parameterization, and c) to verify this CG lightning parameterization on other Canadian areas. The freezing level altitude and the precipitable water content are used to estimate the static air instability and its moisture content respectively. These two parameters are served to develop the CG lightning parameterization. A comparison between the observations and simulations CG lightning occurrence and frequency at Maniwaki showed a mean absolute error rate of 27% and 55% respectively. We apply this parameterization at four Canadian regions, distributed from west to east. The simulated CG lightning results are comparable to observed CG lightning at Maniwaki and tested regions. The application of the CG lightning parameterization to the daily data enabled us to find the monthly results. This application represents a preliminary stage for validation this parameterization in regional numerical models in Canada during the historic period.

Several chemistry-climate models (CCM) underestimate the total column ozone (TCO) over the polar region in the Southern Hemisphere during wintertime. To evaluate potential causes of the problem, we exploit CCM SOCOLv3 to study the TCO over Antarctica sensitivity to the: (1) photo-dissociation rates of ozone for large solar zenith angles; (2) rates of the stratospheric heterogeneous reactions, and (3) intensity of the meridional flux into the polar regions due to sub-grid scale mixing processes in the model. Comparisons of the model results with the satellite-based IASI (Infrared Atmospheric Sounder Interferometer) sensor measurements showed that the most important processes for the improvement of the polar ozone simulation results are photolysis and horizontal mixing. The reasonable tuning of these factors has allowed us to improve the model representation of the ozone annual cycle over the southern polar region. The proposed increase of the horizontal mixing can be recommended for the CCMs with relatively low horizontal resolution.

In this paper, Rice water requirement and irrigation water requirement in Amol agro meteorological Station in 2016-2045 are forecasted based on the projected meteorological data of Hadcm3 under A2 scenario. Rice water requirements are estimated by using crop coefficient approach. Reference evapotranspiration are calculated by FAO Penman-Monteith method. Moreover, the irrigation water requirements are simulated by calibrated CROPWAT model using the meteorological parameters. The results show that both crop water requirement and irrigation water requirement present downward trend in the future. In 2016-2045, the rice water requirement and irrigation water requirement decrease by more than 9.9% under A2 scenario, respectively. Furthermore, the precipitation rise may be the main reason for the decrease in crop water requirement, while significant decrease of irrigation water requirement should be attributed to combined action of rising precipitation and a slight increase in temperature.

In-cloud ice mass accretion on wind turbines is a common challenge faced by energy companies operating in cold climates. On-shore wind farms in Scandinavia are often located in regions near patches of forest, the heterogeneity length scales of which are often less than the resolution of many numerical weather prediction (NWP) models. The representation of these forests--including the cloud water response to surface roughness and albedo effects related to them--must therefore be parameterized in NWP models used as meteorological input in ice prediction systems, resulting in an uncertainty that is poorly understood and to present date not quantified. The sensitivity of ice accretion forecasts to the subgrid representation of forests is examined in this study. A single column version of the HARMONIE-AROME 3D NWP model is used to determine the sensitivity of the forecast of ice accretion on wind turbines to the subgrid forest fraction. Single column simulations of a variety of icing cases at a location in northern Sweden were examined in order to investigate the impact of vegetation cover on ice accretion in varying levels of solar insulation and wind magnitudes. In mid-winter cases, the wind speed response to surface roughness was the primary driver of the vegetation effect on ice accretion. In early season cases, the cloud water response to surface albedo effects plays a secondary role in the impact of in-cloud ice accretion, with the wind response to surface roughness remaining the primary driver for the surface vegetation impact on icing. Two different surface boundary layer (SBL) forest canopy subgrid parameterizations were tested in this study that feature different methods for calculating near-surface profiles of wind, temperature, and moisture, with the ice mass accretion again following the wind response to surface vegetation between both of these schemes.

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

The following paper describes an economical, multiple model predictive control (EMMPC) for an air conditioning system of a confectionery manufacturer in Germany. The application consists of a packaging hall for chocolate bars, in which a new local conveyor belt air conditioning system is used and thus the temperature and humidity limits in the hall can be significantly extended. The EMMPC calculates the optimum energy or cost humidity and temperature set points in the hall. For this purpose, time-discrete state space models and an economic objective function with which it is possible to react to flexible electricity prices in a cost-optimised manner are created. A possible future electricity price model for Germany with a flexible EEG levy was used as a flexible electricity price. The flexibility potential is determined by variable temperature and humidity limits in the hall, which are oriented towards the comfort field for easily working persons, and the building mass. The building mass of the created room model is used as a thermal energy store. Considering electricity price and weather forecasts as well as internal, production plan-dependent load forecasts, the model predictive controller directly controls the heating and cooling register and the humidifier of the air conditioning system.

The construction industry is one of the most fatal industries, so it is important to pay more attention to safety solutions. Even though work-related accidents are known as major waste in construction projects, little attention has been paid so far to incorporating safety into the lean construction framework. In this research, lean construction theory is reviewed through the lens of safety. That being so, the identified challenges in previous research on improving safety in construction projects are categorized and those related to the concept of lean project delivery are introduced. Then, the principles of the lean construction framework are explained and the relevant changes for incorporating safety into the framework are introduced and discussed. It is expected that this hybrid model would further enrich the lean construction framework. The careful attention of project executives to this model may improve the safety situation in construction projects.

Land surface temperature (LST) is a critical parameter for land surface and atmospheric interactions. However, the applicability of current land surface temperature estimates for field-level hydrological, agricultural, and ecological operations is still challenging due to their coarse spatiotemporal resolution. In the current article, we have downscaled 100 m LST to 10 m by using high-resolution Sentinel-1,2 optical-microwave data and three different models- 1) Thermal Sharpening (TsHARP); 2) Thin Plate Spline (TPS); and 3) Random Forest (RF). The extensive analysis was performed at agricultural farms in the semi-arid (IARI) region of India during the winter and summer seasons of 2020-21 and 2021-22, arid (CAZRI) and per-humid (UBKV) region (2021-2022). The calibration accuracy of the RF model was shown to better agreement with the coefficient of determination (R2) of 0.982, root means square error (RMSE) 0.181 and normalized root means square error (RMSE) 0.061 with their lower values of standard errors over three diverse agro-climatic zones. The findings demonstrate that the validation accuracy of models' varied according to the agroclimatic zones, although RF and TPS consistently outperformed as compared to the TsHARP models.

The snow melt from the High Atlas is a critical water resource in Morocco. In spite of its importance, monitoring the spatio-temporal evolution of key snow cover properties like the snow water equivalent remains challenging due to the lack of in situ measurements at high elevation. Since 2015, the Sentinel-2 mission provides high spatial resolution images with a 5 day revisit time, which offers new opportunities to characterize snow cover distribution in mountain regions. Here we present a new data assimilation scheme to estimate the state of the snowpack without in situ data. The model was forced using MERRA-2 data and a particle filter was developed to dynamically reduce the biases in temperature and precipitation using Sentinel-2 observations of the snow cover area. The assimilation scheme was implemented using SnowModel, a distributed energy-balance snowpack model and tested in a pilot catchment in the High Atlas. The study period covers 2015-2016 snow season which corresponds to the first operational year of Sentinel-2A, therefore the full revisit capacity was not yet achieved. Yet, we show that the data assimilation led to a better agreement with independent observations of the snow height at an automatic weather station and the snow cover extent from MODIS. The performance of the data assimilation scheme should benefit from the continuous improvements in MERRA-2 reanalyses and the full revisit capacity of Sentinel-2.

The representation of aerosols in climate-chemistry models is important for air quality and climate change research, but it can require significant computational resources. To overcome this, simpler modules such as modal aerosol modules with three lognormal modes (MAM3) can be used. In this study, the coupling of the Carbon Bond Mechanism, version Z (CBMZ), and MAM3 chemistry modules in WRF-CAM5 was improved by adding biomass-burning emissions to both gas- and particle-phase chemistry and incorporating a conversion mechanism between volatile organic compounds (VOCs) and secondary organic carbons (SOCs). The study conducted six simulations over the western U.S. and northeastern Pacific region and compared the model’s performance with observational benchmarks such as reanalysis, ground-based, and satellite data. The results showed that the model with enhanced chemistry capabilities had a 31% and 58% reduction in root-mean-square errors (RMSE) for black carbon (BC) and organic carbon (OC) surface concentrations, respectively. The earlier release of the WRF-CAM5 version had two deficiencies that were addressed in this study. This research highlights the importance of accurate aerosol representation in climate-chemistry models for improving accuracy and reducing errors in simulations.

Frequent employee resistance to innovation is one of the main barriers of change failure in a health care organization and one of the negative stimuli of employment relationships. Identifying the reasons of resistance is a topical issue for every organization, as the speed of change can affect their competitiveness. Consequently, it is helpful not only to know the causes of potential resistance but also to be ready to control any implicit opposition. The organizational climate and the attitude of the staff play an important role in understanding and accepting innovation. Purpose of the study is to develop a model, which would facilitate the choice of an appropriate strategy necessary to enable the health care organization to eliminate or at least to reduce resistance to often essential innovative changes. The article analyses the root causes of resistance and identifies strategies that help to mitigate or eliminate staff resistance for innovation. Use of suggested model can make easier reducing staff resistance to change processes and thus speed up the implementation of innovations. This methodology can be used to eliminate the reasons for staff resistance to change in health care institutions of different countries, but it was tested in Lithuania and achieved good enough results.

Species have shown their habital variations in responding to climate change, especially during the spring and summer spawning seasons. The species distribution model (SDM) is considered the most favorable tool to study the potential effects of climate change on species distribution. Therefore, we developed the ensemble SDM to predict the changes in species distribution of Portunus trituberculatus among different seasons in 2050 and 2100 under the climate scenarios RCP4.5 and RCP8.5. The results of SDM indicate that the distribution of this species will move northward and have obviouse seasonal variations. Meanwhile, the suitable habitat for the species will be significantly reduced in summer, with loses rates ranging from 45.23% (RCP4.5) to 88.26% (RCP.8.5) by 2100s. Habitat reduction will mainly occur in the East China Sea and southern part of the Yellow Sea, while there will be a small increase in the northern Bohai Sea. These findings will be important to manage the ecosystem and fishery, provide an information forecast of this species in the future, and maintain species diversity if the seawater temperature rises.

Delineating chilling and forcing periods is one of the challenging topics in understanding how temperatures drive the timing of budburst and bloom in fruit tree species. Here, we investigated this question on olive trees, using flowering data collected over six years on 331 cultivars in the worldwide collection of Marrakech, Morocco. Using a Partial Least Squares approach on a long-term phenology (29 years) of ‘Picholine Marocaine’ cultivar, we showed that the relevance of delineating the chilling and forcing periods depends more on the variability of inter-annual temperatures than on the long-term datasets. In fact, chilling and forcing periods are similar between those delineated by using datasets of 29 years and those of only 6 years (2014–2019). We demonstrated that the variability of inter-annual temperatures is the main factor explaining this pattern. We then used the datasets of six years to assess the chill and heat requirements of 285 cultivars. We classified Mediterranean olive cultivars into four groups according to their chill requirements. Our results, using the Kriging interpolation method, indicated that flowering dates of most of these cultivars (92%) were governed by both chilling and forcing temperatures. Our investigations provided first insights to select adapted cultivars to global warming.

The virtual airport hub business model is an innovative solution supported by digital technologies, the implementation of which in continental air transport may lead to a reduction in energy consumption and to a reduction in greenhouse gas emissions. The prerequisites for the implementation of the described solution are: striving to implement the GHG emission reduction strategy laid out in the Paris Agreement (2015) and the European Green Deal (2019) as well as the EU digitalization strategy (2020). The use of predictive analitics to identify the mobility needs of population and operational capabilities of the sector, gives an opportunity to plan travel flows and to create an appropriate set of direct connections among regional airports every day. The results of the analysis of data from 2019 on the amount of energy consumption and GHG emissions indicate that in Europe, it would be possible to achieve reduce GHG emissions by 5% without reducing the number of passengers using air transport. The study was prepared after conducting literature studies, data analysis and using the method of formulating scenarios. The proposed solution has the features of an innovative business model, the implementation of which allows for obtaining more favorable effects using already available resources.

Achieving and sustaining stability for economic growth remain the greatest and most immediate development challenge for Ethiopia. For natural resource-based economies especially maintaining stability and growth depends fundamentally upon climate change adaptation and mitigation. The close links between climate and Ethiopia’s economy are reflected by the strong relationship between GDP growth rate and rainfall variability. A study by the World Bank projects that unless steps to build resilience are effective, climate change will reduce Ethiopia’s GDP growth by between 0.5 and 2.5% each year. Along with the challenges posed by climate change, a number of development opportunities are emerging in response to climate change which includes access to international climate finance. The international response to climate change in the form of external development finance plays a key role to support developing countries in their transition to a low-carbon, climate-resilient and sustainable development pathway. Therefore, this study was conducted to assess the flow and the overall contribution of climate finance to sustainable development in Ethiopia. Specifically, focused on outlining how climate finance is currently reconciled in the existing Ethiopian climate change governance and its contribution to sustainable development. In order to achieve these objectives, data were collected from different sources. The Rio Marker methodology applied to review climate financial flow over the 5 year period. The result reveals that, climate change is central to development agendas despite its recent emergence in the mainstream, with various initiatives under way to combat or reduce its impacts in Ethiopia. In addition, the amount of climate finance from the developed countries to Ethiopia shows some fluctuation for the past five years. In general, the overall flow of climate finance mostly targeted climate adaptation actions which spur and enable the transition towards climate-resilient growth and sustainable development.

This study assessed stakeholders’ perception on the prospects and challenges of practising Climate–Smart Agroforestry in the Asunafo North Municipal Assembly in the Ahafo Region in Ghana. Interviewer administered questionnaires were used to collect cross-sectional data from 250 cocoa, food and cash crop farmers drawn from four (4) communities using simple random sampling. And nine (9) in-depth interviews were also conducted to elicit key stakeholder perspectives. Stakeholders also held the view that Climate-Smart Agroforestry encourages the use of stress-tolerant crop varieties, increase income, improve soil productivity, diversify farm produce, urges the reduction of input supply and recommends the timely usage of the inputs, ensures better market system for farm produce, cost of production decreases during the practice of Agroforestry, agro-ecological functions and Climate-Smart Agroforestry can best help adapt to the threats of climate change in the agriculture sector. The challenges included insecure tree ownership right, fast-declining soil fertility and long maturity period of Agroforestry trees, land tenure issues, illegal tree logging (chainsaw operators) on farms, lack of practical understanding of the approach, inadequate knowledge and information and inadequate supportive facilities in the study area. The study recommends further studies on the existing forest policy and legislations and its implications on the practice and adoption of Climate-Smart Agroforestry in respond to climate change in the area.

An existing simplified simulation model of global climate, population, economy, and governance is extended, through statistical and other data analysis, to include several measures of human well-being and population displacement. The revised model is used to explore (in testing to the year 2060) vicious cycles and causal cascades that, some have warned, could lead to acceleration of climate change in the coming decades. Model scenario testing addresses two uncertainties, namely the strength of the effect of climate change on governance erosion, and the strength of the “heat trap” effect from physical tipping points such as ice loss and permafrost thaw. This testing indicates that a strong heat trap effect could very well accelerate climate change, but that even a strong governance erosion effect is unlikely to do so. Governance erosion would hurt human well-being but is probably not much of a climate threat per se. These results are tentative but point to the possibility of formally modeling causal cascades beyond what the larger climate models have done to date.

Rapid climate change requires more powerful and precise modeling methods to forecast future climate variability. The GSTARIMA Model is efficient, combining space-time analysis with the Autoregressive Moving Average (ARIMA) Model. The integration of heteroscedasticity error and the Kriging method can strengthen the Model's ability to handle the problem of non-constant error variance in the GSTARIMA Model and forecast at unobserved locations of climate observations. This paper's Systematics Literature Review (SLR) is presented comprehensively with the principal aim of developing a thorough understanding of applying the GSTARIMA Model with heteroskedasticity error and the Kriging Method in climate forecasting following the Data Analytics Lifecycle methodology. The Systematic Literature Review (SLR) process consists of three main stages. We sourced the articles from databases such as Scopus, Dimensions, and EBSCO-Host The subsequent stage involved conducting a comprehensive literature review using the PRISMA method to ensure rigor and depth. Additionally, we performed bibliometric analysis to enhance rigor. Lastly, we conducted a gap analysis session to scrutinize existing research on the GSTARIMA Model and identify new opportunities. This literature review reveals that integrating GSTARIMA Model with heteroscedasticity errors and the Kriging method is suitable for climate forecasting. This research inspires researchers to contribute to the improvement and refinement of the Model, making it a more potent and valuable tool in climate forecasting.

In this paper we illustrate a new, simple and complementary ground-based methodology to retrieve the vertically resolved atmospheric precipitation intensity through a synergy between measurements from the National Aeronautics and Space Administration (NASA) Micropulse Lidar network (MPLNET), an analytical model solution and ground-based disdrometer measurements. The presented results are obtained at two mid-latitude MPLNET permanent observational sites, located respectively at NASA Goddard Space Flight Center, USA, and at the Universitat Politècnica de Catalunya, Barcelona, Spain. The methodology is suitable to be applied to existing and/or future lidar/ceilometer networks with the main objective of either providing near-real time (3h latency) rainfall intensity measurements and/or to validate satellite missions, especially for critical light precipitation (<3 mm hr⁻¹).

The World Meteorological Organization (WMO) recommends that the most recent 30-year period, i.e. 1991-2020, shall be used to compute climate normals of geophysical variables. A unique aspect this recent 30-year period is that the satellite-based observations of many different essential climate variables are available during this period, thus opening up new possibilities to provide a robust, global basis for the 30-year reference period in order to allow climate monitoring and climate change studies. Here, using the satellite-based climate data record of cloud and radiation properties, CLARA-A3, for the month of January between 1981 to 2020, we illustrate the difference between climate normal, as defined by guidelines from WMO on calculations of 30-yr climate normals, and climatology. It is shown that this difference is strongly dependent on the climate variable in question. We discuss the impacts of the nature and availability of satellite observations, variable definition, retrieval algorithm and programmatic configuration. It is shown that the satellite-based climate data records show enormous promise in providing climate normal for the recent 30-year period (1991-2020) globally. We finally argue that the holistic perspectives from the global satellite community should be increasingly considered while formulating the future WMO guidelines on computing climate normals.

Assessment of extreme events and climate change on reservoir inflow is important for water and power stressed countries. Projected climate is subject to uncertainties related to climate change scenarios and Global Circulation Models (GCMs’). Extreme climatic events will increase with the rise in temperature as mentioned in the AR5 of the IPCC. This paper discusses the consequences of climate change that include extreme events on discharge. Historical climatic and gauging data were collected from different stations within a watershed. The observed flow data was used for calibration and validation of SWAT model. Downscaling was performed on future GCMs’ temperature and precipitation data, and plausible extreme events were generated. Corrected climatic data was applied to project the influence of climate change. Results showed a large uncertainty in discharge using different GCMs’ and different emissions scenarios. The annual tendency of the GCMs’ is bi-vocal: six GCMs’ projected a rise in annual flow, while one GCM projected a decrease in flow. The change in average seasonal flow is more as compared to annual variations. Changes in winter and spring discharge are mostly positive, even with the decrease in precipitation. The changes in flows are generally negative for summer and autumn due to early snowmelt from an increase in temperature. The change in average seasonal flows under RCPs’ 4.5 and 8.5 are projected to vary from -29.1 to 130.7% and -49.4 to 171%, respectively. In the medium range (RCP 4.5) impact scenario, the uncertainty range of average runoff is relatively low. While in the high range (RCP 8.5) impact scenario, this range is significantly larger. RCP 8.5 covered a wide range of uncertainties, while RCP 4.5 covered a short range of possibilities. These outcomes suggest that it is important to consider the influence of climate change on water resources to frame appropriate guidelines for planning and management.

As recent history has shown, changing climate not only threatens to increase the spread of known disease, but also the emergence of new and dangerous phenotypes. This occurred most recently with West Nile virus: a virus previously known for mild febrile illness rapidly emerged to become a major cause of mortality and long-term disability throughout the world. As we move forward, into increasingly uncertain times, public health research must begin to incorporate a broader understanding of the determinants of disease emergence – what, how, why, and when. The increasing mainstream availability of high-quality open data and high-powered analytical methods presents promising new opportunities. Up to now, quantitative models of disease outbreak risk have been largely based on just a few key drivers, namely climate and large-scale climatic effects. Such limited assessments, however, often overlook key interacting processes and downstream determinants more likely to drive local manifestation of disease. Such pivotal determinants may include local host abundance, human behavioral variability, and population susceptibility dynamics. The results of such analyses can therefore be misleading in cases where necessary downstream requirements are not fulfilled. It is therefore important to develop models that include climate and higher-level climatic effects alongside the downstream non-climatic factors that ultimately determine individual disease manifestation. Today, few models attempt to comprehensively address such dynamics: up until very recently, the technology simply hasn’t been available. Herein, we present an updated overview of current perspectives on the varying drivers and levels of interactions that drive disease spread. We review the predominant analytical paradigms, discuss their strengths and weaknesses, and highlight promising new analytical solutions. Our focus is on the prediction of arboviruses, particularly West Nile virus, as these diseases represent the pinnacle of epidemiological complexity – solution to which would serve as an effective “gatekeeper”. We present the current state-of-the-art with respect to known drivers of arbovirus outbreak risk and severity, differentially highlighting the impact of climate and non-climatic drivers. The reality of multiple classes of drivers interacting at different geospatial and temporal scales requires advanced new methodologies. We therefore close out by presenting and discussing some promising new applications of AI. Given the reality of accelerating disease risks due to climate change, public health and other related fields must begin the process of updating their research programs to incorporate these much needed, new capabilities.

Climate change effect on human-living in verities of way such as health and food security. This study presents predicting crop yields, and production risk in the near future (2020-2029) in northern Thailand using coupling 1 km resolution of regional climate model which is downscaled using a conservative remapping method and the Decision Support System for the Transfer of Agrotechnology (DSSAT) modeling system. The accuracy of the climate and agricultural model was appropriate compared to the observations with Index of Agreement (IOA) in ranges of 0.65 - 0.89. The DSSAT modeling system predicts that rice, and maize production will decrease by 5% and 4% in northern Thailand. In addition, a short-term risk analysis of rice and maize production has shown that, in the context of climate change, maize production appears to be at a high risk of low production in the near future, while rice cultivation might be a low risk.

Land use/land cover (LULC) and climate changes are two main factors directly affecting hydrologic conditions. However, very few studies in Vietnam have investigated changes in hydrological process under the impact of climate and land use changes on a basin scale. The objective of this study is to assess the individual and combined impacts of land use and climate changes on hydrological processes for the Nam Rom river basin, Northwestern Viet Nam using Remote Sensing (RS) and Soil and Water Assessment Tools (SWAT) model. SWAT model was used for hydrological process simulation. Results indicated that SWAT proved to be a powerful tool in simulating the impacts of land use and climate change on catchment hydrology. The change in historical land use between 1992 and 2015 strongly contributed to increasing hydrological processes (ET, percolation, ground water, and water yield), whereas, climate change led to significant decrease of all hydrological components. The combination of land use and climate changes significantly reduced surface runoff (-16.9%), ground water (-5.7%), water yield (-9.2%), and sediment load (-4.9%). Overall climatic changes had more significant effect on hydrological components than land use changes in the Nam Rom river basin during the 1992–2015. Under impacts of projected land use and climate change scenarios in 2030 on hydrological process of the upper Nam Rom river basin indicate that ET and surface flow are more sensitive to the changes in land use and climate in the future. In conclusion, the findings of this study will basic knowledge of the effects of climate and land-use changes on the hydrology for future development of integrated land use and water management practices in Nam Rom river basin.

Storm Ophelia made landfall over Ireland as an extra-tropical storm on the morning of the 16th of October 2017. The storm caused major power outages, lifted roofs, caused coastal flooding in Ireland, and resulted in the loss of three lives. A model’s capability to forecast extreme weather events such as Storm Ophelia is of utmost importance and now with a changing climate, it becomes more important to improve and enhance model forecasting capability. The Weather Research and Forecasting (WRF) model V3.9 has been configured for the Irish domain and this study presents a preliminary evaluation of the Model during Storm Ophelia. Simulated wind speed and direction were compared with hourly remote sensing (lidar) and in-situ (wind speed and wind direction at 10m) observations at the coastal site of Mace Head Atmospheric Research Station on the West coast of Ireland (53.33◦ N, 9.90 49 ◦ W). The model simulation has generally small biases in the simulated wind speed and wind direction during this case study. The model also realistically simulated the magnitude and geographical distribution of the wind speed and wind direction observed during Ophelia.

We revisit the notion of climate, along with its historical evolution, tracing the origin of the modern concerns about climate. The notion (and the scientific term) of climate has been established during the Greek antiquity in a geographical context and it acquired its statistical content (average weather) in modern times, after meteorological measurements had become common. Yet the modern definitions of climate are seriously affected by the wrong perception of the previous two centuries that climate should regularly be constant, unless an external agent acted. Therefore, we attempt to give a more rigorous definition of climate, consistent with the modern body of stochastics. We illustrate the definition by real-world data, which also exemplify the large climatic variability. Given this variability, the term “climate change” turns out to be scientifically unjustified. Specifically, it is a pleonasm as climate, like weather, has been ever changing. Indeed, a historical investigation reveals that the aim in using that term is not scientific but political. Within the political aims, water issues have been greatly promoted by projecting future catastrophes while reversing the true roles and causality directions. For this reason, we provide arguments that water is the main element that drives climate and not the opposite.

Even though Greece is considered a vulnerable region in terms of climate hazards, public perception and attitude do not always identify climate change as an important environmental area of concern, especially when compared to socio-economic issues. The key issue of this paper is to investigate and analyse public perception in Greece as regards to climate change risk. Through a questionnaire survey this paper analyses trends that exist, peoples’ opinion and awareness with regards to climate risk and how willing they are to change current lifestyle, to pay or to act to minimize or to prevent the risk. Conventional wisdom of this paper is to highlight factors that influence individual perception and point out drivers of behavior change that can support efficiently future adaptation plans.

The main objective of this paper is to assess pro-environmental behavior, climate change perception, anxiety, hope and despair in different political orientations. Specific aims included to validate all the instruments; to assess whether the factor structure of the scales were valid across political orientations; to evaluate their reliability; to assess differences concerning age, gender and political orientation; to know the variables that explain pro-environment behavior; and to evaluate the moderating role of climate change perception, despair and hope in the relationship between climate change anxiety and pro-environmental behavior. Confirmatory factor analysis (CFAs), multi-group CFAs (to measurement invariance), multiple linear regressions and moderations were performed. Results showed that pro-environment behavior and climate change hope achieved the four levels of invariance across different political orientations; climate change anxiety achieved the three first levels of invariance; climate change perception and climate change despair achieved configural invariance. Climate change anxiety personal experience, climate change perception total, reality and consequences present higher values in left political orientation that in right or center. Climate change anxiety variables contribute most to explaining pro-environmental behaviors. Hope, despair and climate change perception consequences moderate de relationship between climate change anxiety and pro-environment behavior. These results open up new avenues of investigation, namely, to understand why high levels of anxiety lead to more pro-environment al behaviors.

In the decarbonization of the steel, cement, and chemical industry in Germany, green hydrogen is expected to play a crucial role. The utilization of green hydrogen in the production processes of said industries requires organizations to modify their business model, requiring sustainable business model innovation (SBMI). Numerous tools and frameworks that support organizations in the process of SBMI have been proposed in the literature in recent years. However, the applicability of these tools and frameworks for steel, cement, and chemical companies that intend to utilize green hydrogen to produce their goods remains unexplored. By conducting a systematic literature review on tools and frameworks for SBMI, a literature and practice review to identify and analyze existing green hydrogen projects of steel, cement, and chemical companies, and an evaluation of the identified tools and frameworks in an evaluation matrix, this paper aims to assess the suitability of SBMI tools and frameworks for steel, cement, and chemical companies that plan to use green hydrogen to produce their goods. Based on the evaluation, the Cambridge Business Model Innovation Process (CBMIP) was identified as the most suitable SBMI framework.

Whereas many carbon cycle models track CO₂ perturbations relative to a pre-industrial equilibrium, this paper uses absolute quantities to describe atmospheric CO₂ sinks, source and flow rates. This method, when combined with the notion of source and sink resistance, and a finite biospheric reservoir, accurately describes ¹⁴C levels between 1820 and 2020 using only five external parameters. The inputs are:- global records of fossil-fuel emissions, records of CO₂ mixing-ratio and listings of atmospheric atomic weapons tests. Over the same period ¹³C flows are also accurately described given a ð¹³C value for fossil fuel and a ð¹³C value for the initial background. This top-down approach differs from complex climate models since it circumvents the necessity to catalogue individual processes. The paper proceeds to use the method to examine the anthropogenic fossil-fuel emissions contributions during the period 1750 to 2020, deducing that around 24% remains in the atmosphere, while 76% has been absorbed in the land, terrestrial biosphere and surface ocean. During the same period 13% of the total CO₂ atmospheric concentration is due to fossil fuels. However, regarding the increase, fossil fuels contributed to 38% of the rise during this period.

Climate change poses a significant threat to global food security, necessitating a thorough examination across multiple dimensions. Establishing appropriate food security evaluation indicators that align with the evolving concept of food security is imperative. This study enhances food security evaluation by refining a multi-dimensional framework and analyzing the impact of climate change across various regions from 2002 to 2021. By constructing an Food Security Index system composed of a three-tier indicator system and employing the entropy method for weighting, we assess the impacts of climate change on food security using a climate-economic model. Regression analysis reveals a negative linear relationship between mean temperatures and food security (p&lt;0.01), while precipitation impacts food security non-linearly, particularly exhibiting inverse U-shaped patterns in major grain-producing and grain-consuming areas. Extreme high temperatures consistently reduce food security, whereas extreme precipitation displays a complex, statistically significant inverse U-shaped association. In regions where production and consumption are balanced, mean temperatures have a negative effect on food security, while precipitation exhibits a positive correlation, but excessive precipitation can have adverse effects. These findings highlight the intricate interplay between climate change, regional disparities, and food security in China, emphasizing the need to consider multi-dimensional factors and regional variations in addressing food security challenges. These insights are invaluable for policy-making and planning aimed at enhancing food security in China.

Abstract: Climate change is one of the main barriers for agricultural production and productivity globally. Hence, understanding farmers’ adoption level of CSA practices and determinants is of highly important for policy decisions. Consequently, the study's purpose was to assess adoption level of multiple CSA practices and determinants of climate-smart agriculture practices in the study area. The study was conducted in Welmera Woreda, Oromia Region, Ethiopia. From the Woreda, three kebeles were identified, and 306 respondent farmers were selected. A cross-sectional household survey, focus group discussion, and key informant interviews were used. Multivariate probit model was used to examine adoption determinants of multiple climate-smart agriculture practices. According to the result, Conservation agriculture, integrated soil fertility management, and crop diversification are the most commonly practiced CSA techniques in the study area. Demographic factors result indicated that being male as compared with female farmers, has positive and significant effect on crop diversification and improved livestock feed and feeding practices. Age of farmers significantly and negatively affecting the probability of adoption of improved soil fertility management practices and crop diversification. However, it affects the adoption of agroforestry practices positively and significantly. Based on the result of economic factors, having relatively large farm land size significantly increases the adoption of conservation agriculture, improved soil fertility management, crop diversification, improved livestock feed and feeding practices, and postharvest technology practice. Better farm income increases the likelihood of uptake of improved livestock feed and feeding. Having a large number of livestock positively influences adoption of conservation agriculture and having access to credit services positively influences the implementation of agroforestry, crop diversification, and postharvest technology. In addition, institutional factors such as access to agricultural extension service and training found that significantly and positively influences the adoption of crop diversification; access to participation on farmers’ field day similarly significantly and positively influence the adoption of both conservation agriculture and improved soil fertility management practice. Awareness creation for farmers and experts about climate change and including location specific CSA practices in to agricultural program is crucial.

In the recent century, the tourism industry and within it the tourism economy are one of the most important and fundamental sectors of engaged business. E-tourism can be used as a dynamic tool in up to date areas of informative information and tourism marketing will be considered as a suitable field for the tourism industry. The aim of this study was to investigate the relationship between climate change and the amount of revenues from the tourism industry relying on a tool called e-tourism, and informing and providing services through this way so that Iran can achieve a greater share of export of a single-product oil economy combined with economic growth and sustainable development goals. The method of this research is descriptive-analytical.

This study assessed the impact of climate change on water availability and variability in two subbasins in the Upper Blue Nile Basin of Ethiopia. Downscaled future climate data from HadCM3 of A2 (medium-high) and B2 (medium-low) emission scenarios were compared to the observed climate data for a baseline period (1961 to 1990). The emission scenario representing the baseline period was used to predict future climate and as input to a hydrologic model to estimate the impact of future climate on the streamflow at three future time horizons 2020 - 2045, 2045 - 2070 and 2070 - 2100. Results suggest that medium-high emission scenario best represents the local rainfall and temperature pattern. With A2 scenario, daily maximum/minimum temperature will increase throughout the future time horizons. The minimum and maximum temperature will increase by 3.6^oC and 2.4^oC, respectively, towards the end of the 21st century. Consequently, potential evapotranspiration is expected to increase by 7.8%, though trends in annual rainfall do not show statistically meaningful trends between years. A notable seasonality was found in the rainfall pattern such that dry season rainfall amounts are likely to increase and wet season rainfall to decrease. The hydrological model indicated that the local hydrology of the study watersheds will be significantly influenced by climate change. Overall, at the end of the century, streamflow will increase in both rivers by up to 64% in dry seasons and decrease by 19% in wet seasons.

The government of Nepal (GoN) has developed and implemented climate policies, plans and frameworks such as NAPA, National Climate Change Policy, LAPA and currently in the process of developing National Adaptation Plans (NAPs). These policies and plans are in different states of its implementation with diverse opinions and perceptions of the stakeholders. The paper has explored these opinions and experiences of climate experts in Nepal on state of climate policies, inter-linkages, roles and responsibilities of ministries/departments, important factors and subjective indicators for effective implementation of the policies. Altogether 30 experts responded the questionnaire sent via the email, LinkedIn and Skype Interview in the 1^st phase of Delphi research technique. The experiences of these experts range from 2-30 years representing government, non-government sectors, media and independent experts. As per most of the experts interviewed, the policies and plans are progressing in strategic direction with national and local priorities. The LAPA is the pioneer framework to address the local climatic issues, originated in Nepal. However, lack of clarity on roles/responsibilities and coordination among the ministries/departments; clear mechanisms for implementation of these policies; lack of sensitization, decentralization and delegation of finance and technologies; capacity of the stakeholders are the major challenges identified.

This article presents and discusses analytical data on the scientific publication record from 1910 to 2020 on two topics: "climate" and "climate change/global warming/climate emergency". The goal is to visualize how the publication record on these two topics has evolved over time, from different classification perspectives (year, country, source and organization). Three hypotheses are tested using data collected from Web of Science and various graphical representations of the data. It is found that research output related to the Earth’s contemporary changing climate overtook that of general climate research in 2011, and the publication ratio has been expanding in the last decade. There are significant differences in the publication countries and sources between the two topics, and conversely less significant differences in terms of organizations publishing these works. Differentiation factors that affect the level of research output and engagement on the climate challenge include: island versus landlocked nations, specialized versus general scientific journals, academic versus institutional organizations. The future of the publication records is discussed, such as the emergence of new terms to refer to the climate challenge, such as “climate emergency”.

The German Constitutional Court’s climate verdict provides a re-interpretation of liberal- democratic core concepts and is highly relevant for liberal constitutional law in general – including EU and international law. The verdict accepts human rights as intertemporal and globally applicable; it applies the precautionary principle to these rights and frees them from the misleading causality debate. However, the court fails to address the most important violations of human rights, and it categorised climate policy as a greater threat to freedom than climate change. And the court does not make it clear that the Paris 1.5-degree limit implies a radically smaller carbon budget. Furthermore, little attention has so far been paid to the fact that the ruling implies an obligation for more EU climate protection, especially since most emissions are regulated supranationally. To be effective, the EU emissions trading system demands a reform, which should go well beyond the existing EU proposals to enable societal transformation to sustainability.

The 20th century, global temperatures underwent significant changes, impacting agricultural climate zones worldwide. Xinjiang, China, a key player in machine-picked cotton production, was influenced by various heat-related indicators(sum of active temperature ≥ 10℃、mean temperature in July、climatological growing season length, April-May sum active temperature、Last spring frost, and Defoliator spray time). Using meteorological data from 58 weather stations in Xinjiang, we examined the spatio-temporal trends of these indicators during the period of 1981-2020. Additionally, we considered the effects of climate warming and plastic mulching on the sowing area and zoning area of machine-picked cotton in different suitable zones. Overall, Xinjiang experienced an trend in heat resources, with a pattern of "more in the southern part than the northern part, and more in plains and basins than in mountainous areas." Under climate warming conditions, the sowing area of the most suitable cotton zone and the suitable cotton zone has increased, while the sowing area of the moderately suitable cotton zone and unsuitable cotton zone has decreased. Under the plastic mulching mechanism, a comparison of the zoning area and sowing area from 1991 to 2020 revealed that there was no difference in the zoning area of the most suitable zone compared to the sowing area, while the zoning area of the suitable zone increased by 15.7% (2.15×103km2) compared to the sowing area. The zoning area of the moderately suitable zone decreased by 14.5% (0.26×103km2), and the unsuitable zone decreased by 7.8% (0.17×103km2) compared to their respective sowing areas. These results indicate that climate warming and plastic mulching have increased the cultivable area of machine-picked cotton in Xinjiang, but there are also instances of unreasonable zoning. It is necessary to allocate land resources reasonably based on climatic conditions to ensure the healthy development of the cotton industry in Xinjiang.

For achieving climate targets, public engagement is key. Climate communication can play an important role here. Telling regional stories of successful climate action seems a promising form of climate communication: It may convey a feeling of ‘So this is what climate action looks like – and it is people like you and me who are starting to take action.’ This transformative research project (1) formulates hypotheses on what could make such local climate stories effective, (2) then identifies, produces and disseminates stories in the region of Konstanz, Germany, following a rapid prototyping approach, and (3) analyzes the effect of the stories by using focus groups. So far, two prototyping series of filmic story production have been completed in 2022/2023 and some initial insights were derived: Potential protagonists seem willing to tell their stories, and the stories have a potential to inspire people. Technical film quality is relevant. The stories must be selected and told carefully (who is portrayed, which actions are interpreted as success, through which channels are the stories shared), in order to create resonance with different target groups. Next steps are continuation of film production prototyping, a broader sharing of stories, and thorough impact research by focus groups.

Climate change mainly affects production and consumption systems, such as: food, livelihoods, production (e.g., reduced milk production), water, and land use. The role of local knowledge has been recognized as important for decision-making under changing circumstances. This study was conducted in the northern part of the Ecuadorian Andes using a sample of 170 dairy-cattle-producing households. The objectives were: i) to characterize the rural livelihoods of dairy cattle farmers, ii) to evaluate access to climate information and perceptions of climate change, and iii) to determine the relationship between livelihoods and perceptions of climate change. Significant differences were identified between the groups evaluated in relation to the dairy farmers’ livelihoods. In addition, 85.29% of the respondents mentioned that climate information is important, but 67.83% do not trust the sources of information. It was found that there is a significant relationship between the level of education and age with the variables of climate change perceptions. This combined knowledge allows people to promote agri-environmental and educational policies to achieve climate literacy at a rural level.

The paper presents the open source tool climdex-kit which includes utilities to compute, analyze and visualize climate indices based on the input data, target domain and temporal extent defined by the user. It is intended to support researchers as well as practitioners and decision makers to derive, handle and interpret meaningful information for climate change studies and sectoral applications. It currently includes the computation of 30 indices based on temperature and precipitation, describing both mean and extreme climate conditions, and it is designed to work with climate model projections. The tool is written in Python and integrates utilities from the well-established Climate Data Operators (CDO) and NetCDF Operators (NCO) libraries. The specific utilities for selecting, aggregating and visualizing data are thought to help users to produce tailored results improving understanding and communication of future climate change. In order to show the functionalities of the package as well as its potential integration in regional climate services, climdex-kit was applied to an ensemble of downscaled climate model projections up to 2100 for the region Trentino – South Tyrol (north-eastern Italian Alps). The projections for a selection of indices accounting for extreme temperature and precipitation conditions were derived and different visualization choices discussed. The package climdex-kit is developed in a way that allows users to implement additional routines for calculating other indices as well as for easily adapting the routines to handle with different data types and spatio-temporal targets defined by the specific application. Effective climate services can in fact be developed only if flexible tools and customizable climate information are integrated with a clear understanding of data features and limitations.

Despite the impact that climate change is having on our planet and considering its consequences for future generations, much of the academic literature focuses on adolescent and adult percep-tions, giving little relevance to children's perceptions. Children's voices have the potential to in-fluence public opinion, which may in turn determine the direction of a new policy on the cli-mate crisis. In this context, it is urgent that we understand how children perceive this problem. This quantitative study was based on the application of 245 questionnaires to children aged be-tween 9 and 13 years old from five schools in north-eastern Portugal, more specifically in the region of Trás-os-Montes. To collect the data, we used a questionnaire with 26 questions, being 24 of closed response, Likert type, one of them open response, and one multiple choices. The da-ta were statistically treated using SPSS software. The results show that most of the children ex-press concern about the study's potential problem. However, they show some doubts and a lack of knowledge about some of the themes. We found differences between the two study cycles, with children in the 6th grade having a higher average in the understanding of the phenomenon, as well as the level of education of the parents being positively correlated with a more ecocen-tric posture. The female students also showed a slightly more ecological posture, i.e., an eco-friendlier posture. From the results obtained, we can open new paths for future research and contribute to the definition of policies and educational practices since the school has the respon-sibility to cooperate in the production of values, attitudes, and pro-environmental behaviours.

As climate is not only a valuable tourism resource but also a factor influencing travel experience, estimating climate change can provide implications to sustainable development of the tourism industry. This study develops Climate Volatility Index (CVI) using GARCH model and estimates the relationship between CVI and Japanese tourism demand for Korea using a tourism demand model, based on data from January 2000 to December 2013. Time lag is applied based on a decision making process regarding travel destinations. The result shows that an increase in volatility of climate change leads to a decrease in tourism demand.

Climate variability and change has been found to be one of the factors that affect economies leading to food insecurity in various parts of the world. Kenya is no exception. This study looks at how climate variability has contributed to food insecurity in Kisii County, Kenya. The objectives of this study is therefore to, (i) to examine the rainfall and temperature trends in Kisii County for a period of approximately 30 years, (ii) to examine the effect of climate variability on food production and (iii) to assess the perception of local farmers on weather and climate information, (iv) to evaluate the coping strategies adopted at to bridge the gap on food deficit at different household level and (v) to assess the nutritional status of children and the elderly. The study was conducted in two sub-counties of Kisii County; Marani and Bomachoge Chache. The data used was mainly rainfall and temperature data from meteorological stations and sample data gathered from selected groups. The study population comprised of children between 6 months and 59 months, household heads, elderly people and agricultural officers. Purposive sampling was used to select agricultural officers while multistage sampling was used to select respondents at household level. Data was collected by use of a pre-tested questionnaire. The MUAC tape was used to collect nutritional status of children while BMI data was obtained from elderly people. Mann Kendall statistic was used to determine whether the trend of rainfall and temperature observed is significant while Chi-square test was used to determine whether the coping strategies observed varied significantly at household level. From the analysis, rainfall has not shown any significant change in Kisii County while temperature trend has been significantly increasing over the years at 95% confidence level. This could explain the observed reduction in river levels. Analysis of crop production and price trends of major food crops in Kisii County showed a decreasing trend of food production leading to increase in price over the years. This meant that farmers could not produce enough to take them to the next harvesting season making farmers to adopt different coping strategies at household level which differed significantly according to Chi-Square test. Malnutrition status of both elderly people above 59 years and children between 6-59 months were similar with 23% of both children/elderly being severely malnourished/malnourished. This study has only looked at climatic factors such as rainfall and temperature. Other aspects such as depth of underground water, ph level of soil and the effects of land fragmentation also need to be looked at. This study is important to both farmers in choosing the right crop to plant, and policy makers and planners in formulating the best mitigation and intervention strategies for Kisii County food insecurity problem. This will further contribute to national efforts towards achievement of vision 2030.

Arctic feedbacks will accelerate climate change and could jeopardise mitigation efforts. The permafrost carbon feedback releases carbon to the atmosphere from thawing permafrost and the sea ice albedo feedback increases solar absorption in the Arctic Ocean. A constant positive albedo feedback and zero permafrost feedback have been used in nearly all climate policy studies to date, while observations and models show that the permafrost feedback is significant and that both feedbacks are nonlinear. Using novel dynamic emulators in the integrated assessment model PAGE-ICE, we investigate nonlinear interactions of the two feedbacks with the climate and economy under a range of climate scenarios consistent with the Paris Agreement. The permafrost feedback interacts with the land and ocean carbon uptake processes, and the albedo feedback evolves through a sequence of nonlinear transitions associated with the loss of Arctic sea ice in different months of the year. The US’s withdrawal from the current national pledges could increase the total discounted economic impact of the two Arctic feedbacks until 2300 by $25 trillion, reaching nearly $120 trillion, while meeting the 1.5 °C and 2 °C targets will reduce the impact by an order of magnitude.

The effects of climate change health impacts on urban health care systems and vulnerable populations are a researched topic with foundations on urban risk management, urban health methodologies, and sustainable urbanization. As climate change is a dynamic and transformative global issue the gap between adaptation and mitigation efforts and urban planning relies, among other things, in the limitations of previous studies of risk management structures tailored to the existing strategy to calculate the uncertainties and predict their influence on urban systems and subsystems. Moreover, as climate and health is a well-researched issue, it is also complex as the methodologies and strategic approach to minimize health risks of climate change is intrinsically contingent to risk methodologies and policy-making processes that are efficient with support of knowledge-based information. This paper emphasis the need for focusing on urban health risk management methods that serves to identify potential opportunities, and then manage and take action to prevent adverse health effects. It also emphasizes the probability of events and their consequences, which are measurable both qualitatively and quantitatively.

Concerns of food and environmental security have increased enormously in recent years due to the vagaries of climate change and variability. Efforts to promote food security and environmental sustainability often reinforce each other and enable farmers to adapt to and mitigate the impact of climate change and other stresses. Some of these efforts are based on appropriate technologies and practices that restore natural ecosystems and improve the resilience of farming systems, thus enhancing food security. Climate smart agriculture (CSA) principles, for example, translate into a number of locally-devised and applied practices that work simultaneously through contextualised crop-soil-water-nutrient-pest-ecosystem management at a variety of scales. The purpose of this paper is to review concisely the current state-of-the-art literature and ascertain the potential of the Pfumvudza concept to enhance household food security, climate change mitigation and adaptation as it is promoted in Zimbabwe. The study relied heavily on data from print and electronic media. Datasets pertaining to carbon, nitrous oxide and methane storage in soils and crop yield under zero tillage and conventional tillage were compiled. Findings show that, compared to conventional farming, Pfumvudza has great potential to contribute towards household food security and reducing carbon emissions if implemented following the stipulated recommendations. These include among others, adequate land preparation and timely planting and acquiring inputs. However, nitrous oxide emissions tend to increase with reduced tillage and, the use of artificial fertilizers, pesticides and herbicides is environmentally unfriendly.

Lichens are traditionally divided into short “crustose”, intermediate “foliose” and tall “fruticose” types, a practice that hides a growth continuum. Substrate, temperature and water are thought to affect vertical growth, but such factors are difficult to measure, because, for example, the water actually available to lichens does not match rainfall patterns or even ground water levels. To reliably assess the effect of those factors, I recorded temperature, moisture, and substrate in and under individual terricolous lichen colonies in 60 fixed quadrats on April, August, October, and December of 2015 (Cerro de la Muerte, Costa Rica, 9°33′N; 83°45′W). The measurements were taken inside the colonies themselves (rather than on the general environment), covering an annual cycle of the relatively simple páramo habitat, where animals and vegetation have less impact than in lower ecosystems. The hypotheses were that lichens would grow taller on softer, warmer, and moister ground; on the Caribbean versant; and on the rainy season. Results matched the hypotheses, with one exception: lichens on soft ground were not taller than those on rock. Caribbean colonies were, on the average, 7 cm taller than those on the drier Pacific versant. Physiologically available water seems to be the main determinant of lichen vertical growth: more water means taller lichens and greater protection from climatic change for both the lichens and their microcommunities.

This academic paper explores the synergistic potential of Agroforestry systems and Climate-Smart Agriculture (CSA) in enhancing climate change adaptation strategies. Focusing on Australia and Pacific Island Countries, the study delves into the pivotal role of these approaches in mitigating the impacts of changing climate variables on agricultural production. By analysing important climate variables, their potential alterations, and their subsequent effects on crop production, the paper advocates for a holistic and forward-thinking approach to sustainable agriculture in the face of climate change.

40 years of cloud observations are available globally from satellites allowing derivation of climate data records (CDRs) for climate change studies. The aim of this study is to investigate how stable these cloud CDRs are and whether they qualify stability requirements recommended by the WMO’s Global Climate Observing System (GCOS). We also investigate robust trends in global total cloud amount (CA) and cloud top temperature (CTT) that are significant and common across all CDRs. The latest versions of four global cloud CDRs, namely CLARA-A3, ESA Cloud CCI, PATMOS-x and ISCCP-HGM, are analysed. This assessment finds that all three AVHRR based cloud CDRs satisfy even the strictest GCOS stability requirements for CA and CTT when averaged globally. While CLARA-A3 is most stable in global averages, PATMOS-x offers the most stable CDR spatially. While we find these results highly encouraging, there however remain large spatial differences in the stability of and across the CDRs. All four CDRs continue to agree on the statistically significant decrease in global cloud amount over the last four decades, although this decrease is now weaker compared to the previous assessments. This decreasing trend is stabilizing or even reversing in the last two decades; the latter is seen also in MODIS-Aqua and CALIPSO GEWEX datasets. Statistically significant trends in CTT are observed in global averages in the AVHRR-based CDRs, but the spatial agreement in the sign and the magnitude of the trends is weaker compared to those in CA. We also present maps of Common Stability Coverage and Common Trend Coverage that could provide a valuable metric to carry out an ensemble-based analysis of the CDRs.

This paper identifies the characteristics of the farmer that affect the degree of farmer’s perceived-impact of climate change (CC). We use data from the Indonesian Rice Farm Household survey consisting of 87,330 farmers. An ordered probit regression model was used to estimate the effect of each variable on the degree of perceived-impact of CC. The results of this study confirm the previous empirical studies. Several variables that have been identified as having a positive effect on farmer adaptation practices such as farmer education, land tenure, irrigation infrastructure, cropping system, chemical fertilizer application, access to extension services and participation in farmer group affect the degree of CC perceived-impact negatively. However, a different result was found in the estimation of the gender variable. We found that female farmer has a higher resilience toward CC than the male farmer does. Furthermore, the female farmer has a more positive perception about future farming conditions than the male does. Finally, we suggest that the implementation of national adaptation policy should prioritize more to the farmer with insecure land tenure and utilize and expand the channel of agricultural extension services to deliver the planned adaptation policy.

Atmospheric lightning is an outcome of extreme complex physical processes occurring in the atmosphere. Cloud-to-ground (CG) lightning is considered as a natural disaster. Understanding the importance of CG lightning and implication of the lightning phenomena, Global Climate Observing System (GCOS), world meteorological organization, in its report in the year 2016, introduced the lightning as an Essential Climate Variable (ECV). The present report uses the Lightning Detection Sensor Network (LDSN) established by the National Remote Sensing Centre, Indian Space Research Organization over India to generate the Lightning ECV. A use case of these ECVs are also showcased for an event in Bihar, India, when 42 deaths were reported at locations with large number of CG occurrences.

The understanding of weather and climate extremes provides academics, decision makers, international development agencies, nongovernmental organizations and civil society the necessary information for monitoring and giving early warning to prevent or minimize the risks associated with weather related hazards. Different researches were carried out to provide vital information that will further enhance the assessment of vulnerability and its impacts. Lack of proper understanding of weather and climate extremes was realized to be responsible for the huge and devastating losses that could have being averted or minimized over the past decades. Different countries and institutions have put in place a number of ways to increase sensitization and awareness of weather extremes. This became necessary in order to reduce the losses associated with these extremes both on local and regional scales.

The impact of climate extremes on the society has been of great concern to environmental scientist and policy makers. The destructive consequence attributed to natural hazards associated with climates extremes has been estimated to billions of dollars across the globe. To carry out a robust and effective researches that help to minimize or prevent the loss, detailed datasets of the past, present and future are needed. This will help to give an accurate prediction and early warning which is necessary for the policy making.

Xinjiang, as a climate-sensitive region in northwest China, holds significant importance in studying extreme weather events for agricultural production and socioeconomic development. Based on data from 52 meteorological stations and 23 extreme climate indicators in Xinjiang from 1960 to 2021, the 5a moving average, linear trend estimation, climate tendency rate, and GIS spatial analysis methods are used to analyze the distribution and change characteristics of extreme climate. The results revealed that from 1960 to 2021, TXx, TNx, TXn, TNn, FD, ID, TN10p, TX10p, and WSDI showed a significant upward trend, while SU, TR, TN90p, TX90p, and CSDI showed a significant downward trend. What is more, the range of changes in the extreme temperature indexes from 1990 to 2021 is higher than that of 1960 to 1989. The high-value areas of extreme indexes are primarily concentrated in the northern part, while the high-value areas of cold event indexes are mainly distributed in the southern part. The upward/downward trends all accounting for over 80.00% of the entire region. The Rx1day, Rx5day, PRCPTOT, R95p, R99p, R10, R20, and R25 showed a significant growth trend from 1960 to 2021, and the range of change in the extreme precipitation indexes from 1990 to 2021 was lower than that from 1960 to 1989. Moreover, their high-value areas and high climate tendency areas are mainly concentrated in the northern and western parts of Xinjiang, with upward trends all accounting for over 71.00% of the entire region. The research results provide theoretical foundations for formulating climate risk strategies in the northwest region of China.

There is a range of local weather and climate-related factors that contribute to the degradation of cultural heritage buildings, structures and sites over time. Some of these factors are influenced by changes in climate and some of these changes manifest themselves though a speeding up of the rate of degradation. It is the intention of this paper to review this situation with special reference to the Nordic Countries, where typical trends resulting from climate change are shorter winters and increased precipitation all year round. An attempt is made to initially draw up a classification of materials and structures relevant to cultural heritage that are affected, with a proposed numeric scale for the urgency to act. The intention is to provide information on where best to concentrate cultural heritage site preservation resources in the future.

A scenario-based approach to the impacts of land use and climate change can help in identifying future policy directions. This study models the impacts of different land use and climate change scenarios on the forest ecosystems of South Korea to identify national-scale forest policy options. Climatically suitable forest areas for 1,031 climate vulnerable plant species were identified for current time and for 2050. We calculated change in species richness under four climate projections. We built forest conversion models and created four 2050 forest scenarios: (1) forest loss continues at current rates; (2) similar loss, but with conservation in areas with suitable future climates; (3) a reduction of loss by 50%; and (4) a combination of preservation and overall reduction of loss by 50%. We then crossed the forest conversion models with the climate-driven change in species richness, and categorized current forest areas into four classes to offer forest policy alternatives. By deploying the scenarios which preserve climatically suitable forests, the average species richness where forests converting to other land uses reduced significantly. We suggest conserving forests with suitable climates for biodiversity conservation and the establishment of forest plantations targeted to areas where species richness will decline based on our results.

Keywords: Climate change, stress factors, Vitis spp., extreme climate events, sustainable agriculture

Climate change represents a prevalent challenge confronted by humanity, and with cities being one of the regions most heavily impacted by such change, enhancing their climate resilience is paramount in adapting to and mitigating the associated risks and losses. This article evaluates the climate resilience of 270 major cities in China by creating an urban climate resilience indicator system centered on exposure, vulnerability, and resilience. The article analyses the spatial and temporal evolution trend of climate resilience in Chinese cities, as well as the source of regional differences using Kernel density analysis and the Dagum Gini coefficient decomposition. The article then explores the influence of financial investments on urban climate resilience, considering the moderating effect of urbanization rate.

According to the World Food Programme (WFP), the projected increase in the human population stands at 2 billion people by 2050. At the same time, world food production is witnessing a declining trend over recent years, and 690 million (8.9%) of the world's population are already in severe starvation. Climate variability and climate change impacts on food security are very eminent today. For this reason, this study explored the real effects of climate variability and change on food security in Africa by applying the system Generalized Method of Moments (GMM) and the Panel Corrected Standard Errors (PCSEs) estimators on data from 2001–2018 for 38 selected African countries. The findings reveal that higher amounts of precipitation positively influence food security along two dimensions (food availability and utilization). Hotter temperatures negatively impact food availability and utilization. However, it aids food accessibility in Africa. Similarly, carbon dioxide emissions improve food availability and are harmful to food accessibility and food utilization in Africa. Consequently, the effects of climate variability and change on food security in Africa are undesirable, thereby putting the continent at risk of food insecurity over the long run. Given these findings, the study made appropriate recommendations for policy change to address the negative effects of climate variability and change on food security in Africa.

Many pilot-based initiatives have been developed to promote awareness and use of climate information services among vulnerable smallholder farmers in Africa through million-dollar investments. However, despite their experimental nature, these pilot projects have been successful in raising participating farmers’ awareness and use of climate information services and they can inform transferrable good practices. Through a systematic literature review approach, this review sought to understand ways in which these past pilot projects have contributed to climate risk management in the context of smallholder farming and the factors that led to their success. Results showed that climate information services main contribution to climate risk management has been through facilitating farm level decision making. Factors that led to success of the pilots include: use of downscaled information; building institutional partnerships to add value to climate information; involving farmers through the co-designing and co-developing process; face-to-face way of communication; embedding pre-seasonal workshops in the activities of local institutions for sustainability; using diversity of communication channels to enhance reach among others. These factors can be borrowed as good practices to inform future efforts focused on increasing adoption of climate information services among a wider population beyond pilot project reach.

Earth's global surface temperature shows variability on an extended range of temporal scales and satisfies an emergent scaling symmetry. Recent studies indicate that scale invariance is not only a feature of the observed temperature fluctuations, but an inherent property of the temperature response to radiative forcing, and a principle that links the fast and slow climate responses. It provides a bridge between the decadal- and centennial-scale fluctuations in the instrumental temperature record, and the millennial-scale equilibration following perturbations in the radiative balance. In particular, the emergent scale invariance makes it possible to infer equilibrium climate sensitivity (ECS) from the observed relation between radiative forcing and global temperature in the instrumental era. This is verified in ensembles of Earth system models (ESMs), where the inferred values of ECS correlate strongly to estimates from idealized model runs. For the range of forcing data explored in this paper, the method gives best estimates of ECS between 2.3 and 3.4 K.

Drainage systems are usually dimensioned for design storms based on intensity-duration-frequency (IDF) curves of extreme precipitation. For each location, different IDF curves are established based on local hydrological conditions. Recent research shows that these curves also vary with time, and should be updated with recent data. The purpose of this study is to evaluate IDF curves obtained from precipitation simulations from the Eta RCM, comparing them with IDF curves obtained from data of a rainfall station. Climate models can be a useful tool for assessing the impacts of climate changes on drainage systems, referring precipitation forecasts. In this study, the Eta RCM was forced by two global climate models: HadGEM2-ES and MIROC5. The bias of the precipitation data, generated by RCM models, was corrected using a Gamma distribution. The Juqueriquerê River Basin, in the cities of Caraguatatuba and São Sebastião, São Paulo State, Brazil, was chosen as a case study. The results show a good correlation between the IDF curves of simulated and observed rainfall for the control period (1960-2005), indicating the strong possibility of using the Eta RCM precipitation forecasts for 2007 - 2099 to establish future IDFs thereby, taking into account climate changes in urban drainage design.

The atmospheric lightning is one of the natural disasters which need to be considered in the sustainable development. The National Remote Sensing Centre (NRSC) has installed 46 lightning detection sensors (LDS) across the country. These sensors work in radio frequencies having their detection range up to 1000 km with more than 98% detection efficiency within 300 km range. The network is put in a way that sensors have about 50% sensor-to-sensor overlap in their detection ranges to enable high geolocation accuracy and maintain redundancy. The NRSC-LDS network (LDSN) estimates the current associated with each cloud to ground (CG) lightning flash which can be utilized for the risk assessment. The current estimates from one network to the other need to be inter-calibrated and harmonized. Present study compares the LDSN current estimates with Lightning Location Network (LLN) estimates and results are discussed with their impact on the estimation of vulnerable zones. A case study of lightning-induced fire event is presented to showcase the importance of the currents associated with lightning for future planning.

The international literature shows a polarised debate on the impacts of climate change on migration. Some studies find a positive linkage, whereas others find a negative one. It is, without a doubt, a complex process better considered case-specific. There is no available information on the relationship between climate change and migration in Colombia, despite past research exploring each of these subjects independently. This study intends explicitly to investigate this linkage gap. Consequently, this paper's essential contribution is that it builds a bridge between climate change scenarios and migratory science for the first time in Colombia. Despite their limitations, the theoretical and methodological framework suggested by IOM (2009b pp. 86, Section B, Chapter II) is demonstrated in this study to be very valid since it provides a methodology to predict where future flows will occur (based on past evidence). The methodological approaches of SLA and NELM explained in section A in the IV Chapter are also valuable for analysing and approaching this study's conclusions. The primary conclusions of this study indicate that the "Coffee Region," Valle, and Atlantic (or Caribbean Coast) provinces that mainly send emigrants to Spain and the US are the key internal regions responsible for most of the international migration from Colombians. The same areas are especially vulnerable to the impacts of upcoming climate change in the A1B scenario produced by the IDEAM (2010) for 2040 and 2100. Thus, future flows of migrants are expected from these regions (2040-2100). However, issues such as visa requirements or the costs associated with migration constitute international barriers to this flow. The sensitivity of these regions can also be associated with internal migration flows, more armed conflict, and forced displacement in a cyclical process. Theoretically, a resurgence of Colombia's armed conflict and displacement due to climate change can be expected. However, the need for empirical studies in Colombia to support this analysis is imperative and is the most crucial recommendation arising from this study.

The paper will analyze the pressures and vulnerabilities of the consolidated city from two perspectives: technical and social. Some design and pragmatic experiences conducted by the author in his teaching and research experience first at the Department of Urbanism of TUDelft in the Netherlands and currently at the PDTA Department of La Sapienza University of Rome will be introduced and analyzed. In the first research activity, whose case study is Rotterdam, all urban vulnerabilities related to climate change will be analyzed while in the second one, conducted in Viterbo, the vulnerability related to the hull of social inclusion, poor accessibility and psycho-social stress that plague our established cities will be treated. The two areas of study, different in size and spatial governance tools, are comparable because they allow deciphering the city's risks through lines of intervention that could serve as best practices and serve the urban planning disciplinary update also allowing to define a reflection on morphology and fabrics and on the shape of the city itself. Both teaching and research activities in which the author is involved allow the topic of urban vulnerability to be addressed with a broad exploratory scope that, in the final stage, hypothesizes design intervention on the neighborhood scale, identified as the most appropriate to provide plausible climate and social adaptation and mitigation responses.

The impact of warming on the phenology of grapevine (Vitis vinifera L.) in conditions of Central Europe was evaluated at the locality of Dolné Plachtince in the Slovakian wine region. In Welschriesling and Pinot Blanc model varieties there was observed onset of phenophases as defined in BBCH scale over 1985–2018 period. Based on the data obtained there was evaluated the influence of average and average maximum temperature and GDD on the onset of phenophases. The results observed indicate earlier budburst by 5–7 days, earlier beginning of flowering by 7–10 days, and earlier berry softening by 18 days, and harvest dates advanced by 8–10 days on average. In both varieties there was found the highest influence of the average monthly temperature in March on budburst, the highest influence of the average monthly temperature and the average maximum temperature in May on the beginning of flowering, and the highest, statistically significant influence of the average maximum temperature in June on grape veraison. The warming observed in moderate climate conditions of northern wine regions in Central Europe (Slovakia) has not caused yet the changes in the grapevine phenology stable enough to require serious adaptation measures.

We have modelled the energy consumption of prototype and real buildings under present and future climatic conditions with the EnergyPlus model to develop a better understanding of the relationship between changing climate conditions and energy demand. We have produced detailed meteorological information with 50 meters of spatial resolution through dynamical downscaling process combining regional, urban and computational fluid dynamics models which include the effects of the buildings on urban wind patterns. The city of Madrid has been chosen for our experiment. The impact on energy demand and their respective economic cost are calculated for year 2100 versus 2011 based on two IPCC climate scenarios, RCP 4.5 (stabilization of emissions) and RCP 8.5 (not reduction of emissions). Findings show that climate change will have a significant impact on the energy demand for buildings. Space heating demand will be increased by the RCP 4.5 and cooling demand will be increased for the RCP 8.5 in the analysed buildings.

This literature review paper delves into the synergies between Climate-Smart Agriculture (CSA) and the effective management of food losses. With the escalating challenges posed by climate change and the pressing need to address food security concerns, the intersection of these two critical domains becomes paramount for sustainable agricultural practices. The review explores existing research on the implementation of climate-smart agricultural techniques and their impact on mitigating food losses throughout the agricultural value chain. The paper synthesizes findings related to climate-resilient crop varieties, precision farming, water-use efficiency, and sustainable soil management, highlighting their contributions to reducing post-harvest losses and enhancing overall food security. In addition to summarizing current knowledge, this paper identifies gaps in the literature and proposes avenues for future research. This review serves as a foundation for researchers, policymakers, and practitioners seeking to contribute to the advancement of climate-smart agriculture and the reduction of food losses, paving the way for a more sustainable and resilient global food system.

The study aimed to investigate the effect of climate change exposure on affect and pro-environmental behavioural intentions in a randomised controlled trial. An online survey was completed by 100 adult participants and included measures of affect and pro-environmental behavioural intentions pre- and post-exposure. Participants were randomly allocated to a group that saw a climate change video (n=55) or a group that saw a non-climate change video (n=45). The findings showed were that participants in the climate change group showed a significant increase in negative affect and pro-environmental behavioural intention scores post-video exposure compared to the non-climate change video group. This suggests that climate change video exposure negatively influences affect but also potentially increases the intention to act pro-environmentally. These findings have the potential to support policies and societal change, however further investigation into the type of contents, actual behaviour change, and impacts on diverse populations (e.g., minority groups) is needed that influences pro-environmental behaviours is required. Furthermore, to achieve a greater impact, future research should be conducted measuring actual pro-environmental behaviour change, including with those from diverse populations.

Introduction The climate crisis is essentially a public health crisis. Response is imperative to prevent economic and social crises associated with the growing burden of climate impacts on human health and the health care sector. Green Podiatry Pillars By adopting the three pillars of Exercise, Evidence, and Everyday changes, podiatrists can contribute to more sustainable health and health care. Discussion Educating our patients to use their feet for low carbon active transport, eliminating interventions not supported by evidence, and reducing fossil fuel driven supply chains and energy use, are three impactful measures that all podiatrists, and indeed, all health and medical personnel, need to adopt. The avoidable suffering, enormous and costly use of resources for diabetic foot disease, is a scourge that must realise its preventable potential. It is too late, too costly, too polluting, and too sad, to continue to direct health care and research efforts and budgets, to an expensive modifiable diabetes disease process, potentiated by poor food and physical inactivity. Affected patients require skilled support, to avert such chronic disease processes, often not of their making. Conclusions Healthcare contributes 5 to 8% of green house gases (GHG), and non-communicable diseases (NCD) are increasing, so healthcare must lead on primary health. As citizens and health professionals, we must advocate for better community health, and educate our patients. Future Directions All health and medical personnel need to consider planetary health and sustainable healthcare within their daily work. Healthcare must act to address climate change, and realise benefits for people and planet.

There has been an increase in the inefficiencies of urban infrastructure services in Indian cities as a result of rapid and unplanned urbanization (UNDP, 2017). Indian cities have grown multidimensional as a result of massive industrializa-tion and technological spread backed by globalization impacting the early 2000. It has transformed the city fabric and the associated challenges. Therefore, an Urban Climate Vulnerability Assessment (UCVA) is needed to identify, target and recognize climate vulnerable urban cities, sectors, or populations. The UCVA framework consists of seven broad thematic indicators — physical, hazard, social, demographic, financial provisioning, infrastructure and admin-istration vulnerabilities, and their sub indicators to represent the climate vul-nerability of Indian cities. This assessment is for seven Indian cities namely Delhi, Mumbai, Chennai, Bengaluru, Srinagar, Shillong, and Ahmedabad which were selected based on their geographical location, population, ecosystem types and hazards/ hazard trends to understand and assess the respective vul-nerabilities. The Assessment is done through a comprehensive approach using a robust and predictive qualitative framework. It helps in determining respec-tive risks and in improving community resilience to the climate hazards by in-tegrated planning and improved preparedness. UCVA can support as a deci-sion support mechanism for devising suitable mitigation and adaptation strategies for building urban climate resilience.

Nature-based solutions (NbS) - working with and enhancing nature to address societal challenges - are increasingly being featured in climate change adaptation policy and plans. While there is growing evidence that NbS can reduce vulnerability to climate change impacts in general, there is a lack of understanding on the mechanisms through which this can be achieved, particularly in the Global South. To address this, we analyse 85 nature-based interventions in rural areas across the Global South, and factors mediating their effectiveness, based on a systematic map of peer-reviewed studies encompassing a wide diversity of ecosystems, climate impacts, and intervention types. We develop and apply an analytical framework of people’s social-ecological vulnerability to climate change, in terms of six pathways of vulnerability reduction: social and ecological exposure, sensitivity, and adaptive capacity. Most cases (95%) report a reduction in vulnerability, primarily by lowering ecosystem sensitivity to climate impacts (73% of interventions), followed by reducing social sensitivity (52%), reducing ecological exposure (36%), increasing social adaptive capacity (31%), increasing ecological adaptive capacity (19%) and/or reducing social exposure (14%). An analysis of mediating factors shows that social dimensions are equally important as technical factors in NbS to achieving equitable and effective outcomes. Attention to the distinct social and ecological pathways through which vulnerability is reduced helps to harness the multiple benefits of working with nature in a warming world.

Leaders are failing to respond to the climate and environmental urgency the world is facing. A growing action gap, clearly visible during the recent CoP25, has been fueled by leaders' inability to respond efficiently to the mounting threats scientists—and increasingly society—are concerned about. Bridging this gap and tackling the growing polarization within society calls for leaders to accept the full complexity of the issues the world is facing. This will require them to question their understanding of these geopolitical affairs and embrace the dynamics at play, and avoid falling back on simplistic cognitive models. We propose a heuristic to convey the pathways available to decision-makers to make their way out of the current inaction impasse. By breaking free of this deadlock, a social transition will have the potential to take place, helping us to avoid crossing the climate system tipping points.

We evaluate the complexity of Colombian climate from extreme behavior of gauge temperature and precipitation, using the the novel Tsallis' non-extensive entropy principle based on physical information through the q-index. We find the spatial structure of non additive universal categories (q-index) and compare with some complex systems with the potential to have some degree of dynamical affinity. Our results evidence the great dynamical variability of regional climate expressed in the large range of values of $q$-index, and the high degree of non-extensitivity for both temperature and precipitation.

This study focusses on identifying a set of representative future climate projections for the Upper Indus Basin (UIB). Although a large number of GCM’s predictor sets are nowadays available in the CMIP5 archive, the issue of their reliability for specific regions must still be confronted. This situation makes it imperative to sort out the most appropriate, single or small-ensemble set of GCMs for the assessment of climate change impacts in a region. Here a set of different approaches is adopted and applied for a step-wise shortlist and selection of appropriate climate models for the UIB under two RCPs: RCP 4.5 and RCP 8.5, based on, a) range of projected mean changes, b) range of projected extreme changes, and c) skill in reproducing the past climate. Furthermore, because of higher uncertainties in climate projection for high mountainous regions like the UIB, a wider range of future GCM climate projections is considered by using all possible future extreme scenarios (wet-warm, wet-cold, dry-warm, dry-cold). Based on this two-fold procedure, a limited number of climate models is pre-selected, out of which the final selection is done by assigning ranks to the weighted score for each of the mentioned selection criteria. The dynamically downscaled climate projections from the Coordinated Regional Downscaling Experiment (CORDEX) available for the top-ranked GCMs are further statistically downscaled (bias-corrected) over the UIB. The downscaled projections up to year 2100 indicate temperature increases ranging between 2.3 °C and 9.0 °C and precipitation changes that range, from a slight annual increase of 2.2% under the drier scenarios, to as high as 15.9% for the wet scenarios. Moreover, for all scenarios, the future precipitation will be more extreme, as the probability of wet days will decrease, while, at the same time, the precipitation intensities will increase. The spatial distribution of the downscaled predictors across the UIB also shows similar patterns for all scenarios, with a distinct precipitation decrease over the south-eastern parts of the basin, but an increase in the northeastern parts. These two features are particularly intense for the “Dry-Warm” and the “Median” scenarios over the late 21st century.

Building more energy efficient and sustainable urban areas that will both mitigate the effect of climate change and adapt for the future climate, requires the development new tools and methods that can help urban planners, architect and communities achieve this goal. In the current study, we designed a workflow that links different methodologies developed separately, to derive the energy consumption of a university school campus for the future. Three different scenarios for typical future years (2039, 2069, 2099) were run as well as a renovation scenario (Minergie-P). We analyse the impact of climate change on the heating and cooling demand of the buildings and determined the relevance of the accounting of the local climate in this particular context. The results from the simulations showed that in the future there will a constant decrease in the heating demand while for the cooling demand there will be a significant increase. It was further demonstrated that when the local climate was taken into account there was an even higher rise in the cooling demand but also that the proposed renovations were not sufficient to design resilient buildings. We then discuss the implication of this work on the simulation of building energy consumption at the neighbourhood scale and the impact of future local climate on energy system design. We finally give a few perspective regarding improved urban design and possible pathways for the future urban areas.

Land surface albedo determines the splitting of downwelling solar radiation into components which are either reflected back to the atmosphere or absorbed by the surface. Land surface albedo is an important variable for the climate community and therefore was defined by the Global Climate Observing System (GCOS) as an Essential Climate Variable (ECV). Within the scope of the Satellite Application Facility for Land Surface Analysis (LSA SAF) of EUMETSAT, a near-real time (NRT) daily albedo product was developed in the last decade from observations provided by the SEVIRI instrument on board the geostationary satellites of the Meteosat Second Generation (MSG) series. In this study we present a new collection of albedo satellite products based on the same satellite data. The MSG Ten-day ALbedo (MTAL) product incorporates MSG observations over 31 days with a frequency of NRT production of 10 days. The MTAL collection is more dedicated to climate analysis studies compared to the daily albedo that was initially designed for the weather prediction community. For this reason, a homogeneous reprocessing of MTAL was done in 2018 to generate a Climate Data Record (CDR). The resulting product is called MTAL-R and has been made available to the community in addition to the NRT version of the MTAL product which has been available for several years. The retrieval algorithm behind the MTAL products comprises three distinct modules: one for atmospheric correction, one for daily inversion of a semi-empirical model of the bidirectional reflectance distribution function, and one for monthly composition that also determines surface albedo values. In this study the MTAL-R CDR is compared to ground surface measurements and concomitant albedo products collected by sensors on-board polar-orbiting satellites (SPOT-VGT and MODIS). We show that MTAL-R meets the quality requirements if MODIS or SPOT-VGT are considered as reference. This work leads to 14 years of production of geostationary land surface albedo products with a guaranteed continuity in the LSA SAF for the future years with the forthcoming third generation of European geostationary satellites.

Individuals with low health literacy (HL) are known to have poorer health outcomes and to have higher mortality rates compared to individuals with higher HL: hence, the improvement of HL is a key outcome in modern healthcare systems. Healthcare providers are therefore asked to support patients’ literacy skills by encouraging the implementation of autonomy-supportive patient centered communication (PCC), which in turn requires the enhancement of patient engagement. Our main hypothesis is that the well-known relationship between autonomy-supportive PCC and HL is mediated by patient engagement which is known to play a role in HL promotion and that is related to PCC as well. The purpose of this study was to formulate a hypothetical structural equation model (SEM) linking PCC to patient engagement and HL. A cross-sectional survey design was employed involving 1007 Italian chronic patients. The hypothetical model was tested using SEM to verify the hypothesized mediation of patient engagement between PCC and HL. Results show that the theoretical model has a good fit indexes and that patient engagement fully mediates the relationship between PCC and HL. This finding suggests healthcare systems to implement a new paradigm where patients are supported to play an autonomous role in their own healthcare.

The objective of this research was to study the dynamics of moisture and nutrition at the root zone and to quantify the variables linked to efficient water management in avocado orchards of mid and high-lands of Michoacán, México, in typical Andisols of low fertility with (A)C(w2) and C(w2) climates, respectively. Using the FDR (Frequency Domain Reflectometry) technology, the dynamics of soil moisture and salinity were recorded daily at four depths: 0-15, 15-30, 30-45, and 45-60 cm. The soil moisture balance model was used to determine actual evapotranspiration (ETr), crop coefficient (Kc), and water use efficiency (WUE). Results indicated that ETr is 66-73% of the total water at 0-30 cm depth; the fertilizer absorption is limited to 0-30 cm, being negligible at deeper layers. The water use efficiency is 4.4 to 5.6 kg of fruit m-3 of applied water, and the ratio of the water use index (ETr/irrigation sheet applied, ISA) is 0.65-0.70; while the annual avocado Kc is 0.72 in Cutzato and 0.78 in Tiamba. We concluded that avocado has a low water requirement, it does not cause leaching of nutrients and/or water, the absorption of water and nutrients mostly occurs at 30 cm depth, and from a hydrological point of view, the crop is environmentally friendly.

The study explores the value of indigenous knowledge in mitigating and adapting to the effects of climate change in rural communities of Uganda. It provides an overview of how rural farmers use traditional and indigenous knowledge to predict weather changes to inform their adaptation and mitigation plans. The study intended to investigate how climate change effects were managed by the rural communities of Bakiga using indigenous knowledge and practices. Specifically, it sought to establish how local farmers’ innovations and practices were used to mitigate the effects of climate change and enhance food security. A case study research design with triangulation of data sources was employed. The study was conducted in Rukiga District, southwestern Uganda, where rural farmers were interviewed to explore their practices for reducing the effects of climate change to enhance food security. Thematic data analysis was used to get participants’ experiences and views regarding indigenous knowledge and effects of climate change mitigation. The findings indicate that rural farmers have indigenous practices of mitigating the effects climate change and contributing to the Sustainable Development Goals (SDGs).

The brief paper utilises Zimbabwe as a case study to discuss the effects of El Nino in Southern Africa. It offers potential adaptation and mitigation measures for farmers to prepare for the forecasted El Nino-influenced rainy season 2023/24 and the future. To reduce climate and weather hazards connected with El Nino, the brief report suggests anticipatory action methods be applied in southern Africa, using Zimbabwe as a case study. To protect farmers' livelihoods and enhance drought readiness for the forthcoming agricultural seasons, the paper suggests a degree of strategic, tactical, and operational decision-making that the agriculture industry should adhere to. It emphasised the significance of providing farmers with knowledge and advice regarding drought and heat stress, including cultivating crop varieties and livestock and sufficient fire safety precautions. The brief paper calls to advocate for anticipatory action to avert El Nino in Southern Africa.

This study contextualises the background of Japan’s “carbon neutrality and net-zero” (CNN) policy announced in October 2020, thereby identifying important changes in the country’s climate policy between 1990 and 2020. Using four research questions, four main findings were extracted from a narrative technique-based analysis of Japan’s policy documents related to CNN. The following are the findings: [i] the framing of climate change as a “climate crisis” by influential Japanese climate stakeholders was a key motivation for Japan to formally announce its CNN policy in October 2020, [ii] pressure from the international community and the political leadership of the Yoshihide Suga administration are essential factors that led the Japanese government to change its stance and announced this policy, [iii] Japan unintentionally delayed announcement of the policy until 2020 due to the concern among Japanese climate stakeholders about the problem of fairness in Kyoto Protocol’s emission reduction targets, and [iv] this delay was also due to Keidanren’s (or business sector) consistent opposition to the introduction of regulatory schemes. These results emerge for the first time in a study of Japan’s CNN politics, particularly in terms of the broader context of climate politics. Finally, we offer a possible explanation for Suga’s deliberate announcement of the CNN policy. This opens up space for future research to complement our study by providing important indicators on the trajectory of this important policy.

The prefabricated houses supply in Chile was analyzed from web platforms, public market, social media, and Internal Revenue Service, using indicators according to regulatory compliance, complexity, and sustainability attributes, which are essential in advancing to industrialization, and climate change adaptability. The 80% is concentrated in construction, and manufacturing companies, 83% of them are legally registered,with the capacity of meeting technical requirements. To delve deeper into this, 54% has low level, 35% medium level, and 11% high level. The sustainability was measured in 5 levels: 2.7% (1), 37,5% (2), 58,6% (3), 1,1% (4) and 0% (5), which is the highest one. This attribute was determined as the weakest one. The proposed evaluation, based on indicators by attribute, is objective and relevant to consideration since there is still a lack of capacity to supply the housing deficit, and there is not attributes associated to security in habitability to address the climate change, and environment threats, with a lack of action by the state to promote this productive sector, therefore focusing more in provide products, than taking responsibility of the site, not advancing to become a real state agency, which could be improved if management, and regulation were incorporated.

Based on the daily observation data of 2254 meteorological stations in China from 1961 to 2021 after homogenization and correction, the extreme value analysis method that combines relative threshold and absolute threshold was used to identify extreme climate events in the mainland of China, namely extreme high temperature, extreme low temperature, extreme drought, extreme precipitation and extreme typhoon events. The frequency and linear variation trends of individual extreme events in the past 60 years were investigated. On this basis, the multi extreme events composite risk grade index (MXCI) was constructed, which can objectively reflect the comprehensive characteristics of multi extreme climate events in different regions. The results show that the high value areas of MXCI were mainly located in Southeast China and Southwest China. The MXCI presented a decreasing trend in most of the western and southeastern regions of China, while an increasing trend from Southwest China to the south of Northeast China, due to the frequent occurrence of extreme high temperature, extreme drought and other extreme events in these regions.

This essay review explores the concept of climate-smart forestry as an approach to mitigating and adapting to climate change. It highlights the need for a holistic approach to forestry that considers regional differences and synergies between ecosystem services. The essay discusses various management strategies at different scales, including species selection, mixed species cultivation, and the promotion of the bioeconomy. It also examines the trade-offs and synergies between different forest uses and the effects of forest management on ecosystem services. Furthermore, the review addresses major abiotic and biotic damage risks to forests, such as wildfires, windstorms, and bark beetle attacks, and proposes risk management strategies. Lastly, the review delves into the management of peatland forests, discussing the role of drainage, the impact of ditch network maintenance, and the challenges of peat ash fertilization. Overall, the review provides valuable insights into climate-smart forestry and its potential to contribute to climate change mitigation and adaptation.

Students are often portrayed as future leaders. Their participation in climate change mitigation would improve when they access climate information and gain a high level of climate change awareness. This study was initiated to assess the Congolese students’ awareness of climate change by focusing on their sources of information on climate change, knowledge about the causes and impacts of climate change and activities that can raise awareness on climate change. Using a convenience sampling technique, we collected data through individual interviews conducted among 1,278 students from 13 universities across the Democratic Republic of Congo (DRC). The interview results showed that all students irrespective of their disciplines were concerned about climate change, a phenomenon strongly driven by human activities, such as deforestation (78%), urbanisation (30%), agriculture activities (30%) and transport services (26%). The students’ perceptions of climate change impacts included increase in temperature (82%), decrease in the number of rainy days (66%), proliferation of pests (60%) and increase in the number of malaria patients (39%). The primary sources of information that significantly affected students’ awareness of climate change included environment-related university courses and television broadcasts. The awareness-raising and mitigation actions related to climate change recommended by the students included educating people about good waste management (56%), planting trees (65%) and using the taxes paid by mining companies for the restoration of degraded ecosystems. The students believed that in DRC, all layers of the society (educational institutions, civil society organisations, community members and businesses) are important in building resilience to climate change. This study can guide teachers to focus their educational efforts on shaping pro-environmental behaviour in students.

There is a growing consensus that to effectively adapt to climate change, cities need user-friendly tools and reliable high-resolution biophysical and socio-economic data for analysis, mapping, modeling, and visualization. This study examines availability of various types of information used in climate adaptation plans of 40 municipalities with population less than 300,000 people in the United and in France, probing into the choice and usage of relevant information by small municipalities. We argue that non-climatic spatial data, such as population demographic and socio-economic patterns, urban infrastructure, and environmental data must be integrated with climate tools and datasets to inform effective vulnerability assessment and equitable climate adaptation planning goals. Climate adaptation plans frequently fail to address the existing structural inequalities and environmental injustices in urban infrastructure and land use. Adaptation methodological approaches should be reassessed in the context of much needed societal transformation. Lessons learned from our studies offer valuable insights for potential development of the national and state-level climate adaptation information services for cities.