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.

In this analysis, we assess the performance of GSMaP-GNRT6 data in capturing precipitation climatology and climate variability across China from 2001 to 2020. The evaluation involves comparing four precipitation indices of accumulated precipitation, the number of rainy days, rainstorm days, and precipitation maximum with the daily precipitation data from 2419 stations in China. The findings reveal that the GSMaP data effectively captures the overall spatial distribution of annual, summer, and monthly precipitation. However, it exhibits minor limitations in accurately depicting the spatial distribution of the number of rainy days from July to September and the precipitation maximum during wintertime in eastern China. While the GSMaP data depicts a coherent annual cycle consistent with the station observations, a general underestimation is observed. Notably, the GSMaP data presents a much smoother annual cycle in precipitation maximum. Regarding accumulated precipitation, the number of rainstorm days, and precipitation maximum, the GSMaP data shows an almost consistent interannual variation and increasing trends, aligning with station observations. However, it is noteworthy that the magnitude of the increasing trend based on the GSMaP data is greater, especially entering the early 21st century. Conversely, a significant discrepancy in the annual variation and an almost opposite changing trend are noticed in the number of rainy days between the GSMaP data and station observations.

Based on the ERA5 reanalysis dataset of the European Centre for Medium-Range Weather Forecasts (ECMWF), the climatology of the planetary boundary layer height (PBLH) in Jiangsu, China, is studied. The PBLH based on ERA5 is verified by using radiosonde data, and the results show that the PBLH based on ERA5 fits very well with the PBLH diagnosed by the radiosonde data. Overall, the daytime average PBLH is between 700-1200 m, which is higher in the north and lower in the south. It is between 100 and 400 m at night, and it is lower in the north and higher in the south. PBLH exhibits complex spatiotemporal variation. In the daytime, the PBLH in inland areas is highest in spring, followed by fall and summer, and lowest in winter. At night, the seasonal variation in the PBLH is less obvious. The seasonal variation in the PBLH in coastal areas is higher in fall and winter and lower in spring and summer. PBLH shows an obvious diurnal cycle, usually reaching its peak at 14:00 (LST) or 15:00 (LST). The diurnal cycle of the PBLH is significantly positively correlated with the near-surface temperature and wind speed and significantly negatively correlated with the relative humidity and lower tropospheric stability. The daytime PBLH increases significantly in most areas. The increase in PBLH can be attributed to the increase in near-surface temperature and the decrease in near-surface relative humidity and lower tropospheric stability.

New data on the climate in southern Spain from 1792 to 1808 are analyzed in this work. The data source is the newspaper Correo Mercantil de España y sus Indias, where summaries of the weather conditions in Spain were published at weekly resolution. The study is focused on southern provinces, providing 2788 new records, some of them corresponding to areas without data previously recorded. The analysis indicates the predominance of cold-dry winters, cold-wet springs, warm-dry summers, and variable conditions in autumn, from west (cold-wet) to east (warm-dry). Some examples of these situations are presented.

Aerosols play an important role in Earth’s climate system, thus long time ground based measurements of aerosol optical properties are useful in understanding this role. 10 years of quality-assured measurements between 2010 and 2020 are used to investigate the aerosol climatology in the Cluj-Napoca area, in North-Western Romania. In this study, we analyze the Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA) and Ångström exponent obtained by CIMEL sun photometer, part of the Aerosol Robotic Network (AERONET) to extract the seasonality of aerosols in the region and investigate the aerosol climatology of the area. Higher aerosol loads are found during July and August. Ångström exponent has the lowest values in April and May and the highest in August. The classification of aerosols using AERONET data is performed to separate dust, biomass burning, polluted urban, marine and continental dominant aerosol mixtures. In addition, the study presents the validation efforts of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) dataset against AERONET AOD over 10 years period.

The varved sediments of the Pyrenean Lake Montcortès (Pallars Sobirà, Lleida) embody a unique continuous high-resolution (annual) paleoarchive of the last 3000 years for the circum-Mediterranean region. A variety of paleoclimatic and paleoecological records have been retrieved from these uncommon sediments that have turned the lake into a regional reference. Present-day geographical, geological, ecological and limnological features of the lake and its surroundings are reasonably well known but the lack of a local weather station has prevented characterization of current climate, which is important to develop modern-analog studies for paleoclimatic reconstruction and to forecast the potential impacts of future global warming. Here, the local climate of the Montcortès area for the period 1955-2020 is characterized using a network of nearby stations situated along an elevational transect in the same river basin of the lake. The finding of statistically significant elevational gradients for annual and monthly average temperature and precipitation has enabled to estimate these parameters and their seasonal regime for the lake site. A representative climograph has been shaped with these data that can serve as a synthetic descriptive and comparative climatic tool. The same analysis has provided climatic data for modern-analog studies useful to improve the interpretation of sedimentary records in climatic and ecological terms. In addition, the seasonal slope shifting of the climatic elevational gradients has been useful to gain insights about possible future climatic trends under a warming scenario.

Stretching along the border of North Dakota and Minnesota, The Red River Valley (RRV) of the North has the highest frequency of reported blizzards within the contiguous United States. Despite the numerous impacts these events have, few systematic studies exist discussing the meteorological properties of blizzards. As a result, forecasting these events and lesser blowing snow events is an ongoing forecast challenge. This study presents a climatology of atmospheric patterns associated with RRV blizzards for the winter seasons of 1979-1980 to 2017-2018. Patterns were identified using subjective and objective techniques using meteorological fields from the North American Regional Reanalysis (NARR). The RRV experiences on average, 2.6 events per year. Blizzard frequency is bimodal with peaks occurring in December and March. The events can largely be typed into four meteorological categories dependent on the forcing that drives the blizzard: Alberta Clippers, Arctic Fronts, Colorado Lows, and Hybrids. Objective classification of these blizzards using a competitive neural network known as the Self-Organizing Map (SOM) demonstrates that gross segregation of the events can be achieved with a small (8-class) map. This implies that objective analysis techniques can be used to identify these events in weather and climate model output that may aid future forecasting and risk assessment projects.

Soil temperature reflects the impact of local factors，such as vegetation，soil and the atmosphere of a region. Therefore, it is important to understand the regional variation of soil temperature. However, lack of observations with adequate spatial and/or temporal coverage, it would be difficult to use the observation data to study the regional variation. Based on the observation data from Nanchang and Ganzhou stations and ERA-Interim/Land reanalysis data, this study analyzed the temporal-spatial distribution characteristics of soil temperature over Poyang Lake Basin. The results showed close correlations between observation data and reanalysis data at different depths. Reanalysis data could mainly reproduce the temporal-spatial distributions of soil temperature over the Poyang Lake Basin, but generally underestimate their magnitudes. Temporally, there is an obvious warming trend in the basin. Seasonally, the temperature raised fastest in spring and slowest in summer, except for the ST4, which rising fastest in spring and slowest in winter. In terms of depths, the temperature of ST1 rises fastest. For the other layers, the warming trend is almost similar. An abrupt change of annual soil temperature at all depths occurred in 1997, and annual soil temperatures at all depths were abnormally low in 1984. Spatially, annual soil temperature decreased with latitude, except for the summer ST1. Because of the high temperature and precipitation in summer, the ST1 are higher around the lake and the river. The climatic trend of soil temperature presents the general increase trend from south to north, opposite to the distribution of soil temperature. The findings provide a basis for understanding and assessing the variation of the soil temperature over the Poyang Lake Basin.

Precipitation is a crucial driver for many environmental processes and weather radars are capable of providing precipitation information with high spatial and temporal resolution. However, radar-based quantitative precipitation estimates (QPE) are also subject to various potential uncertainties. This study explores the development, uncertainties and potentials of the hourly operational German radar-based and gauge-adjusted QPE called RADOLAN and its reanalysed radar climatology dataset named RADKLIM in comparison to ground-truth rain gauge data. The precipitation datasets are statistically analysed across various time scales ranging from annual and seasonal aggregations to hourly rainfall intensities in regard to their capability to map long-term precipitation distribution, to detect low intensity rainfall and to capture heavy rainfall. Moreover, the impacts of season, orography and distance from the radar on long-term precipitation sums are examined in order to evaluate dataset performance and to describe inherent biases. Results revealed that both radar products tend to underestimate total precipitation sums and particularly high intensity rainfall. But our analyses also showed significant improvements throughout the RADOLAN time series as well as major advances through the climatologic reanalysis regarding the correction of typical radar artefacts, orographic and winter precipitation as well as range-dependent attenuation.

Knowledge of wave climate is essential for efficient management of the world's coastal areas. Senegal is a relevant case given its high coastal vulnerability to energetic wave conditions. This study investigates wave climates along the coastal zone of Senegal based on a new high-resolution hindcast covering the period 1980-2021. This study evaluates the average, seasonal and extreme values for the wave significant heights (Hs), periods (Tm02/Tp) and mean directions (DIR). In boreal Winter, the wave climate is dominated by swells coming from the North-Atlantic lows, while in boreal Summer, the Southern Coast (from Dakar to Casamance) is exposed to swells generated in the South-Atlantic Ocean. Throughout their refraction around Dakar Peninsula, NW swells rotate by ~100° from NW to SW, while their Hs is roughly halved when reaching the Southern Coast of Senegal. Over the studied period, trends in Hs are weak (~0.6 cm.decade-1) on the Northern Coast, double on the Southern coast (~1.2 cm.decade-1), mostly due to an increase during boreal Summer (2 cm.decade-1). The wave periods show weak trends (~0.05 s.decade-1) and DIRs show weak counterclockwise rotation (-1°.decade-1). These trends are explained by the main climate modes of the Atlantic Ocean (NAO/EA during Winter, SAM during Summer) and are important for future research and long-term monitoring of the Senegalese Coast.

The North American Monsoon (NAM) in southern Arizona continues to be a topic of interest to ecologists, climatologists, and citizens as well as the triggers and characteristics of plant growth and reproduction in relation to the onset of the monsoon. In researching the onset of the North American Monsoon (NAM) in south-central Arizona relative to the phenology of Saguaro cactus (Carnegiea gigantea) and other Sonoran Desert species we identified interesting and previously unreported features in the NAM rainfall data. We present preliminary descriptive analyses of (1) monsoon onset as measured by the first day after June 1 with precipitation ≥10 mm (1990-2022), (2) first day of year warming of Sea Surface temperatures (SST) in the Gulf of California to ≥29º C measured across five open-sea blocks (mean 9452 km2), and (3) El Niño Southern Oscillation (ENSO) anomaly with a threshold of +/- 0.5º C for the Oceanic Niño Index (ONI) in the Niño 3.4 region (5ºN-5ºS, 120º-170ºW). Three patterns emerge from our analyses: (1) The day of the year of monsoon onset occurs approximately 12 days earlier in the year from 1990-2022 in south-central Arizona. (2) There appears to be a signal in the rainfall onset data very roughly approximating cycles of ENSO Oceanic Niño Index (ONI) anomalies in Niño region 3.4. (3) Gulf of California sea surface temperature (SST) and monsoon onset data support an expected link between the timing of SST warming and monsoon rainfall onset.

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.