Abstract: Droughts in the Amazon region are expected to increase in frequency and intensity, which would negatively affect the tropical forest, leading to a positive climate-forest feedback loop that could potentially result in the collapse of this ecosystem. In this study, extreme drought conditions were identified in the Peruvian Amazon region for the period 2000-2024, using the maximum cumulative water deficit (MCWD) index, which is related to the tropical forest water stress. The ERA5, CHIRPS and MSWEP datasets were used to estimate precipitation, while ERA5 data were used for evapotranspiration. This study focuses on the specificities of droughts and the differences across study areas. Six study areas were specified, three of them located in the Loreto department (northern Peruvian Amazon), another centered in the Moyobamba city (western Peruvian Amazon), another in Ucayali, in the central Peruvian Amazon and the other in Madre de Dios (southern Peruvian Amazon). It was found that the drought events are more frequent and intense in the central and southern region of the basin. Based on the combined effect of the regional severity of the drought and its spatial extent we identified the hydrological years of 2023-24, 2022-23, 2009-10 and 2004-05 as extreme droughts.

Abstract: How much rain can we expect in Toulouse on Wednesday next week? It is impossible to provide a precise and definitive answer to this question due to the limited predictability of the atmosphere. So ideally, a forecast would be probabilistic, that is expressed in the form of a probability of, say, having at least some rain. However, for some forecast users and applications, an answer expressed in mm of rain per 24h would be needed. A so-called point-forecast can be the output of a single deterministic model. But with ensemble forecasts at hand, how to summarize optimally the ensemble information into a single outcome? The ensemble mean or quantile forecasts are commonly used and proved useful in certain circumstances. Here, we suggest a new type of point-forecasts, the crossing-point quantile, and argue that it could be better suited for precipitation forecasting than existing approaches, at least for some users. More precisely, the crossing-point quantile is the optimal forecast in terms of Peirce skill score (and equivalently in terms of area under the ROC curve) for any event of interest. Along a theoretical proof, we present an application to daily precipitation forecasting over France and discuss the necessary conditions for optimality.

Abstract: The Southeastern European territory is under severe climatic pressure owing to accelerating dry-thermal trends. The present survey illustrates the spatial and temporal evolution of the climate regime over the natural and agricultural landcover of South-eastern Europe and individual countries (Albania, Bosnia Herzegovina, Bulgaria, Croatia, Greece, N. Macedonia, Montenegro, Romania, Serbia, and Slovenia). For this purpose, an high spatial resolution of the Johansson Continentality index, Kerner Oceanity index and Pinna Combinative index was estimated for the first time over two climatic periods (1964–1993; 1994–2023). The Johansson index depicts increasing continentality over the southern and eastern regions, majorly by the spatiotemporal expansion of the Continental climate over the agricultural and natural areas of Bulgaria (respectively, from 49.9% to 73.7% and from 13.3% to 36.8%) followed by Serbia, Romania, and Greece. The Kerner index illustrates increasing continentality over most of the study area owing to the spatiotemporal increase of the Sub-Continental climate type over the agricultural and natural areas of Bosnia Herzegovina (from 68.6% to 84% and from 41.4% to 63.2%), N. Macedonia, Slovenia and the natural areas of Croatia and Serbia. The extension of the Continental over the agricultural and natural areas of Romania is also shown. The Pinna index exhibits an increasing aridity trend, which is more intense in the central and eastern regions. This trend is demonstrated by the higher distribution of the Semi-Dry in the second period mostly over the agricultural and natural areas of Bulgaria (2.4% to 23.1% and 0.7% to 5.8%), and a remarkable expansion of the Moderate Wet climate over both area types of Romania (from 3.3% to 44.8% and from 5.6% to 15.2%) and Bosnia Herzegovina (from 13.7% to 33.5% and from 3.5% to 13.2%). This study’s results highlight the necessity for intensifying adaptation plans and actions aiming at the feasibility of agricultural practices and the conservation of natural areas.

Abstract: This study examines how climate change affects maximum aviation payload capacity across China's diverse airport network. Analyzing projections from 30 CMIP6 models under the SSP5-8.5 scenario, specifically we quantify temperature and pressure effects on Maximum take-off weight (MTOW) at 184 Chinese airports. Results reveal that while all airports experience MTOW reductions by 2081-2100, high-plateau airports (>2,438m) face more moderate decreases (-1.25%) than plain airports (< 1,500m) (-1.72%). This counterintuitive pattern stems from elevation-dependent pressure compensation: high-altitude regions benefit from significant pressure increases (4.6 hPa) that partially offset temperature-induced density reductions, while lowland areas receive minimal pressure compensation (0.9 hPa). For commercial aircraft, these changes translate to 1.3-2.9 tons payload reduction for narrow-body aircraft at plain airports. Our findings demonstrate how topography modulates climate impacts on aviation operations, highlighting the need for regionally-tailored adaptation strategies with focus on economically vital lowland hubs.

Abstract: Accurate estimations of ETo is critical for hydrologic studies, efficient crop irrigation, water resources management and sustainable development. The evaluation of an empirical method for estimating hourly ETo, utilizing the incoming solar radiation and a relation between a function of relative humidity and vapor pressure deficit as an aerodynamic term was calibrated under semi arid conditions, and assessed against the ASCE PM (2005) method for hyper arid to sub humid climatic regimes in the State of California. For hyper arid climatic conditions, the empirical method underestimated and had R2 values from 0.88 to 0.95 and RMSE values from 0.062 to 0.115 mm h-1. Hyper arid climatic conditions, correspond to lower R2 and different relations between the VPD and the inverse of the natural logarithm of relative humidity (1/lnRH). For arid semi arid and sub humid climatic conditions the empirical method performed satisfactorily. The RMSE was calculated for various intervals of the range of the observed wind speed values and it was satisfactory for &gt;99% of all data. The RMSE was also calculated for various intervals of the observed values of VPD and was satisfactory for &gt;97% of all data except for hyper arid stations (59% of u2 and 60% of VPD data).

Abstract: This study aimed to assess the influence of recent climatic conditions and cultivar on the timing of key phenological stages in grapevines. For this purpose, five table grape varieties with different ripening periods, grown at the Murfatlar viticultural center and vineyard in Romania, were studied. This vineyard is challenged by current cli-matic changes. At the local level, data have been recorded showing constant climatic changes, with changing temperature and humidity regimes. These data will lead to management problems that other vineyards are already facing. The study covered the period from 2000 to 2019 and tracked the timing of the onset of vegetative phases, as recorded in the number of days from January 1 to that point, according to the BBCH phenological scale. The results showed that the length of the vegetation period depends not only on the variety but also on the viticultural year, due to annual climatic variability. Changes in the duration of the vegetative phases were evidenced, with a trend towards advancing ripening.

Abstract: The evaluation of raindrop-size distribution (DSD) is a crucial subject in radar meteorology, as it determines the relationship between radar reflectivity (Z) and rainfall rate (R). The coefficients (a and b) of the Z-R relationship vary significantly due to several factors (e.g., climate and rainfall intensity), rendering the characterisation of local DSD essential for improving radar quantitative precipitation estimation. This study used a unique network of 21 disdrometers with high spatio-temporal resolution in Mexico City to investigate changes in the local drop size distribution (DSD) resulting from seasonal fluctuations, rain rates, and topographical regions (flat urban, and mountainous). The results indicate that the DSD modelling utilizing the normalized gamma distribution provides an adequate fit in Mexico City, regardless of geographical location and season. Regional variation in DSD's slope, shape, and parameters was detected in flat urban and mountainous areas, indicating that distinct precipitation mechanisms govern rainfall in each season. Severe rain intensities (R > 20 mm/h) exhibited a more uniform and flatter DSD shape, accompanied by increased dispersion of DSD parameter values among disdrometer locations, particularly for intensities exceeding R > 60 mm/h. The coefficients a and b of the Z-R relationship, exhibit significant geographic variability, dependent on the city's topographic gradient, underscoring the necessity for regionalisation of both coefficients within the metropolis.

Abstract: Since pre-industrial times, anthropogenic methane emissions have increased and are partly responsible for a changing global climate. Natural gas and oil extraction activities are one significant source of anthropogenic methane. While methods have been developed and refined to quantify onshore methane emissions, the ability of methods to directly quantify emissions from offshore production facilities remains largely unknown. Here, we review recent studies that have directly measured emissions from offshore production facilities and critically evaluate the suitability of these measurement strategies for emission quantification in a marine environment. The average methane emission from production platforms measured using downwind dispersion methods were 32 kg h-1 from 188 platforms; 118 kg h-1 from 104 platforms using mass balance methods; 284 kg h-1 from 151 platforms using aircraft remote sensing; and 19,088 kg h-1 from 10 platforms using satellite remote sensing. Upon review of the methods, we suggest the unusually large emissions, or zero emissions observed could be caused by the effects of a decoupling of the marine boundary layer (MBL). Decoupling can happen when the MBL becomes too deep or when there is cloud cover and results in a stratified MBL with air layers of different depth moving at different speeds. Decoupling could cause: some aircraft remote sensing observations to be biased high (lower wind speed at the height of the plume); the mass balance measurements to be biased high (narrow plume being extrapolated too far vertically) or low (transects miss the plume); and the downwind dispersion measurements much lower than the other methods or zero (plume lofting in a decoupled section of the boundary layer). To date, there has been little research on the marine boundary layer, and guidance on when decoupling happens is not currently available. We suggest an offshore controlled release program could provide a better understanding of these results by explaining how and when stratification happens in the MBL and how this affects quantifications methodologies.

Abstract: Accurate hyperspectral simulations are critical for the vicarious calibration of next-generation space-based sensors and for ensuring the long-term consistency of climate data records. This study presents a refined methodology to generate simulated radiometric calibration references (RCRs) over bright desert pseudo-invariant calibration sites (PICS), specifically designed to meet the stringent accuracy requirements of hyperspectral observations. Building on metrology principles, and in the absence of SI-traceable references, the approach leverages simulated reflectance over stable desert targets as a community-accepted calibration reference. Key advancements include improved surface reflectance modelling using the RPV model and CISAR algorithm, enhanced atmospheric property characterization from multiple state-of-the-art datasets, and the use of the Eradiate Monte Carlo-based radiative transfer model. These refinements reduce uncertainty in simulated top-of-atmosphere reflectance, achieving an accuracy within ±3% in high-transmittance spectral regions. Validation against both multispectral and hyperspectral satellite data (i.e., EMIT, EnMAP and PRISMA) confirms the robustness of the methodology. This work establishes a reliable framework for hyperspectral sensor calibration and intercalibration, addressing the pressing need for traceable, high-fidelity reference data in Earth observation.

Abstract: As a sensitive indicator of climate change, vegetation ecological quality on the Tibetan Plateau (TP) plays a crucial role in indicating environmental change. Based on the meteorological and ecological data on the TP from 2001 to 2020, we analyze the variations of different vegetation types and their relationship with atmospheric circulations. The results suggest that the overall ecological quality of vegetation on the TP shows an improvement trend. The ecological quality index (EQI) of sparse shrubs increases dramatically, while it of evergreen coniferous forests shows a decreasing trend. Warming is an important factor contributing to the EQI increase in the northeastern TP. Precipitation increase is not favorable to the EQI increase in the southwest of grasslands. Furthermore, the strengthening of the East Asian and South Asian summer monsoons is beneficial for the EQI increase of coniferous forests and evergreen broad-leaved forests. The remarkable warming and humidifying in deciduous broad-leaved forests, mixed forests, partial shrubs and evergreen broad-leaved forests, and the meridional water vapor transport in the central-southern TP, is conducive to EQI increase. Although the strengthening of the TP summer monsoon and westerly remarkably favors the EQI increase in grasslands and shrubs, the variations in meridional water vapor flux transport in the northeast area and the zonal water vapor flux transport in the west, results in the marked EQI decrease. Thus, the northeastern and western parts are the main areas of ecological quality degradation. The results can provide a basis for ecological restoration and protection, the development and utilization of climate resources on the TP.

Abstract: Evaluating the impact on roadside environments of NH3 from vehicle emissions is important for protecting the ecosystem from air pollution by fine particulate matter and nitrogen deposition. This study used passive samplers to measure NH3 and NOX at multiple points near a major road to observe the distribution of these gases in the area. The impact of NH3 emitted from vehicles on a major road on the environmental concentration of NH3 at different distances from the roadside was found to be similar to that of NOX and NO2. The concentration of NH3 rapidly decreased due to dilution and diffusion within approximately 50 m of the road, and after 100 m the concentration remained almost the same or decreased slowly. Furthermore, CO2 observations taken in the same period along the roadside and in the background yielded a vehicular emission factor of 4–50 mg/km for NH3, which is comparable with previous research. This emission factor level contributes 4–11 ppb to the NH3 concentrations in roadside air through the dilution and diffusion process. A correlation was found between the emission factors of NH3 and NOX that is different from the trade-off relationship seen when single-vehicle exhaust is measured

Abstract: Climate forecasting models typically assume homogeneous information processing across all stakeholders, neglecting critical real-world retrieval asymmetries. We introduce Observer-Dependent Entropy Retrieval (ODER), a mathematically rigorous framework that redefines climate forecasting not solely as a predictive exercise but as an observer-dependent retrieval process, reframing uncertainty and risk as functions of latency, hierarchy, and actor-specific access. Using a Bayesian–Markovian formulation, ODER provides a structure for incorpo- rating observer-specific entropy retrieval into forecasting. This paper presents a foundational framework with conceptual demonstrations and proposed validation pathways. We outline a benchmarking methodology and define proxies for empirical calibration that could connect theory to practice. ODER transforms climate forecasting by making retrievability—not just predictive accuracy—central to early warning and decision-making.

Abstract: Extreme temperature or heat wave events cause significant damage to socioeconomic activities and ecological systems. Over the past few decades, heatwave events in Pakistan have caused several health issues and increased mortality rates. This study analyzes the relationship and impact of temperature extremes of the northern Indian Ocean’s (IO) sea surface temperature (SST) and atmospheric temperature over land (ATL) for Pakistan. For this purpose, daily and monthly average atmospheric temperature over land (T2m) and SST were taken into account, and anomalies were calculated. It also analyzes the relationship between the Nino3.4 Index and northern IO’s SST and ATL. The seasonal (spring and summer) and monthly ( March-August) temperature extremes for Pakistan and the northern IO region have been analyzed over 5, 7, and 10-day stretch from 1979 to 2015. Results show that SST has a higher frequency of extreme temperature anomalies over different stretches of days than ATL. Temperature extreme anomalies were observed in northern IO’s SST during El Niño years. ATL was significantly prompted by SST when observed on a seasonal basis; however, an insignificant relationship was observed on a monthly basis. T2m and SST have shown a significant relationship with the Nino3.4 Index for sea and land. The results of this study would address the sustainable development goals (SDGs) focusing on hunger, good health and well-being, and climate action. It will further provide insight to policymakers for devising mitigation strategies against temperature extremes.

Abstract: Urban environments increasingly suffer from extreme heat due to climate change and urban heat island effects. This study compares the summer temperature reduction ef-fects of two contrasting cooling infrastructures: a ground fountain located in Dongtan Yeoul Park—a newly developed smart city district experiencing rapid urbanization, and a natural stream in Chilrangi Valley in Sangdong-eup, the coolest rural location in South Korea during summer. Using on-site IoT-based weather stations, thermal imag-ing, and microclimate monitoring, we analyzed air temperature, surface temperature, Mean Radiant Temperature (MRT), and Universal Thermal Climate Index (UTCI) at various distances from each water source. The ground fountain showed a maximum air temperature reduction of 2.26°C within a 5-meter radius, with MRT and UTCI re-ductions of up to 3°C compared to adjacent dry zones. However, cooling effects di-minished rapidly with distance. In contrast, the natural stream maintained an average air temperature of 25.5°C—approximately 10°C lower than the urban site—along with more stable MRT (~40°C) and UTCI (~45°C) throughout the day. These findings indi-cate that while ground fountains provide localized, short-term relief, natural systems deliver broader and more sustainable cooling. This study highlights the importance of integrating both artificial and natural water-based infrastructures to enhance thermal comfort and support climate-resilient urban planning.

Abstract: The roughness of the Earth’s surface dictates the nature of air flow across it. During some parts of the year, a large portion of the Earth’s surface is snow covered, and the roughness of the snow surface varies over the snow season and over space. Detailed meteorological data that are necessary to access the aerodynamic roughness (z0) are not widely collected and as such the geometry of a surface can be used to estimate z0. Here we present a formulation and the corresponding computer code to compute z0 based on the Lettau (1969) geometric approach. We apply it to three snow surface datasets, each at different phases of the snowpack (and each at two resolutions): fresh snow accumulation (1 m2 at 1 and 10 mm), peak accumulation (1 km2 at 1 and 10 m) and ablation sun cups (25 m2 at 5 and 50 mm). The new code produces a mean z0, as well as a histogram of all z0 values for each individual roughness element (10s of thousand for the 1000 x 1000 grids), as well as directional z0 diagrams, which can be matches with the wind rose for the location. The formulation includes two parameters that may optionally be applied to smooth the surface before calculating z0. By calculating z0 as a function of these two parameters, we demonstrate the sensitivity of the z0 value to these parameter choices.

Abstract: This work discusses the theory of PM2.5 source apportionment and presents an integrated modeling approach, which combined receptor models based on PM2.5 component measurement data and CTM air quality models using emission inventory. This approach obtains refined source apportionment results through a three-step modeling process. Firstly, this approach takes advantage of the CMB receptor model's ability to resolve the contributing source sectors of the primary PM2.5 components. This approach also used relatively accurate PM2.5 component measurement data, especially for secondary components and dust of PM2.5, which present high uncertainty for the CTM model due to the challenges with model mechanisms, emission inventory, and model resolution. Secondly, this approach utilizes CTM’s source apportionment tools to estimate the contributions of specific emission sources by simulating atmospheric physical and chemical processes and tracking the emission sources groups of specific spatial locations for complete components of PM2.5. Finally, the CMB receptor model source apportionment results for primary PM2.5 components, along with the measured secondary components PM2.5 concentrations, and the source apportionment results including local and long-range contributions estimated by the CTM model are used to obtain the refined integrated source apportionment. The integrated approach developed in this work was applied to conduct source apportionment in the 2+26 Cities Region during the autumn and winter of 2017-2018. This work provided refined source apportionment results for all PM2.5 components, including the local contributions and mutual contributions among different cities and regions, which are crucial for policy and action plans. This work directly supported the PM2.5 pollution control action plans in the region.

Abstract: Recent observations have increasingly challenged the conventional understanding of atmospheric NH3 and its potential sources in remote environments. Laboratory studies suggest that microdroplet redox generation of NH3 could offer an alternative explanation. However, key questions remain: 1) Can microdroplet redox generation of NH3 occur in ambient air? 2) Is it restricted by the presence of specific catalysts? 3) What factors determine the efficiency of ambient NH3 generation via microdroplet redox reactions? We investigate these questions based on adiabatic-expansion-induced perturbation observations performed in various atmospheres over the last decade. Our results indicate the adiabatic-expansion-induced generation of NH3+HNO3 at ultrafast formation rates, with campaign-dependent stable stoichiometric ratio of HNO3 to NH3, as well as highly variable occurrence frequencies and efficiencies. These findings suggest that microdroplet redox reactions are more likely responsible for the generation of NH3+HNO3 than conventional atmospheric NH3 chemistry. Moreover, our analysis suggests that the line speed of microdroplets may be one of the key factors in determining the occurrence, stoichiometric ratio and efficiency of the redox reaction. Additionally, the presence of sea-salt aerosols and low ambient temperature, rather than the specific catalysts, may significantly influence these processes. However, the current observational data do not allow us to derive a functional relationship between the redox reaction rate and these parameters, nor to fully detail the underlying chemistry. Comprehensive and controlled laboratory experiments, similar to our adiabatic-expansion-induced observations but utilizing state-of-the-art highly sensitive analyzers, would be necessary, though such experiments are beyond our current capabilities.

Abstract: In this study, multi-model simulations are performed in fully-coupled configurations for investigating the effect of desert dust on spatial-temporal variation of precipitation. Dust-based processes of formation/removal of ice nuclei (IN) and cloud condensation nuclei (CCN) are investigated by using both on-line access model WRF-CHIMERE and online integrated model WRF-Chem. The comparisons of models’ predictions with measured (GRISO: Spatial Interpolation Generator from Rainfall Observations) precipitations over Italian Peninsula, point out the models’ skills in reproducing at least the severe orographic precipitations occurred over the alpine areas. To quantify the impact of the mineral dust transport concomitant to the Atmospheric River (AR) on cloud formation, a sensitivity study is performed by using WRF-CHIMERE model (i) by zeroing dust concentrations, and (ii) by modifying the Thompson Aerosol-Aware microphysics scheme setting (i.e. DeMott 2015). Our findings show that, although important instantaneous changes are modelled at local scale for precipitation and for temperature, not significant total changes in precipitation and air temperature averaged over the whole domain are pointed out by sensitivity test. On the other hand, the WRF/Chem simulation differs from WRF-CHIMERE in temporal-spatial variability of dust concentrations and precipitations.

Abstract: Eulerian observations of chemical species at fixed positions in a flow field are known to violate conservation laws, while the observations tracking moving air parcels are practically unfeasible. Eulerian observations often cause positive correlations between reactants and products in the atmosphere, which are frequently misinterpreted as evidence of the related chemical conversion. This dilemma has motivated innovative trials. The perturbation technique, widely used in mathematical and physical studies, offers a potential solution. Combining Eulerian observations with perturbation techniques may compensate the weakness, making this approach particularly valuable for studying the gas-aerosol partitioning of semi-volatile particulate species in ambient air. As an example, we examined this combination through an adiabatic-expansion-induced perturbation study on the gas-aerosol partitioning of dimethylamine (DMA) and trimethylamine (TMA) in ambient air. Eulerian observations of chemical species in size-segregated atmospheric particles ranging from 10 μm to 0.056 μm, coupled with downstream adiabatic-expansion-induced perturbation observations, were performed in coastal and marine atmospheres using a commercial sampler (Nano MOUDI-II, MSP, US), followed by offline chemical analysis. The results revealed that particulate DMA generally tended to evaporate in ambient air during the observational periods, while enhanced adiabatic-expansion-induced perturbations occasionally led to the co-formation of DMAHNO3 and NH4NO3. However, gaseous TMA apparently underwent gas-particle condensation to reach equilibrium in ambient air, with adiabatic-expansion-induced perturbation resulting in the formation of non-ionized TMA particulates. Thermodynamic analysis further supported that the observed particulate TMA was primarily determined by the equilibrium of gaseous TMA with non-ionized particulate TMA, rather than ionic TMAH+.

Abstract: Objectives of measuring radon concentrations are radioprotection, as high concentrations in the atmosphere are hazardous agents, and scientific applications, mainly related to radon as an environmental tracer. For radon screening and surveying, usually relatively simple monitors are used such as track-etch or SSNTD detectors, while for scientific research, mostly more sophisticated and expensive equipment is employed. For some years, a new generation of instruments is available that were conceived as consumer grade monitors; however their performance is such that also their scientific usage appeared interesting for certain purposes. This requires particular QA/QC, including understanding their behaviour and knowing their limitations. One instrument in this hybrid consumer / science grade segment is the RadonEye, an ionization chamber with relatively high sensitivity. It has already been subjected to studies of its performance which suggest that it can be used also in certain scientific applications. This paper reports experiences with the RadonEye acquired during about two years, mainly for recording time series of radon concentration indoors and outdoors. Specific topics are calibration uncertainty, response to thoron and some so far unresolved questions related to measurement statistics.