Regional Climate Characteristics Research Articles

Quantitative Classification of Spring Discharge Patterns: A Cluster Analysis Approach

ABSTRACTSprings provide critical water resources that are sensitive to changing climate and catchment processes. In many regions, understanding the temporal variability and spatial distribution of spring discharge is therefore crucial for sustainable water management. Knowledge of these discharge characteristics, organised in a coherent framework, is essential for protecting spring water and preventing shortages. To establish such a framework, we conducted a comparative analysis of long‐term discharge records from 96 springs across Austria. Based on discharge seasonality and autocorrelation, we derived a broad‐scale classification through cluster analysis and explored associations between individual clusters. The identified similarities in discharge patterns were grouped into four distinct spring categories, each demonstrating common behaviour. To determine the main factors influencing discharge across these four groups, we compared their spatial and temporal patterns with regional climate and catchment characteristics. They align with physical drivers of spring discharge, including precipitation frequency and intensity, snow cover duration, and dominant aquifer type. As these factors were not included in the classification procedure, their alignment supports the validity of our statistical approach. We conclude that the quantitative information derived from this analysis provides a valuable complement to traditional spring classification schemes, which are often based on qualitative knowledge. Our proposed strategy refines these classification approaches, enhances objectivity and reproducibility, and promotes conformity across hydrological disciplines.

Multiple “spaces”: Using wildlife surveillance, climatic variables, and spatial statistics to identify and map a climatic niche for endemic plague in California, U.S.A.

Regional climatic features in endemic areas can help inform surveillance for plague, a bacterial disease typically transmitted by fleas and maintained in mammals. We use 7,954 coyotes (Canis latrans), a sentinel species for plague, screened for plague exposure by the California Department of Public Health - Vector-Borne Disease Section (CDPH-VBDS; 1983-2015) to identify and map plague-suitable local climates within California to empirically inform ongoing sampling and surveillance plans. Using spatial point processes, we compare the distributions of seropositive and seronegative coyotes within the “space” defined by the first two principal components of PRISM Climate Group 30-year average climate variables (primarily temperature and moisture). The approach identifies both regions consistent with CDPH-VBDS mapping of plague-positive rodent and other carnivore samples over the same period and additional plague-suitable areas with climate profiles similar to seropositive samples elsewhere but little or no historical sampling, providing new data-informed insight for prioritizing limited surveillance resources.

Evaluation and refinement of ERA5-land 2 m atmospheric temperature in GNSS precipitable water vapor

Since the land 2 m air temperature from European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5-land) is vulnerable to interference by regional climate characteristics and local topography, how to objectively and accurately evaluate its accuracy and then establish a refined model is the key to improve its multifaceted and deep-level applications. This study proposed a systematic and complete refinement method for ERA5-land air temperature based on the densely distributed weather stations in Shandong Province in eastern China, including the compensation of elevation matching bias (EMB) caused by ASTER GDEM and the overall refinement using the remove-and-restore model (RRM). Taking the hottest July and the coldest December in this area, surface air temperature, atmospheric weighted mean temperature (Tm) and GNSS precipitable water vapor (PWV) were used to verify the feasibility of this method. The results show that: (1) Whether the temperature is high in July or low in December, the accuracy can be improved by about 42.2 % when the refinement method was used. Especially for high altitude areas (the summit of Mount Tai, 1553 m above sea level), the accuracy can be improved by 74.5 %. (2) In contrast to only the temperature lapse rate (TLR) correction, the average root mean square (RMS) can be reduced by 7.4 % and 60.4 % in July and 7.0 % and 59.5 % in December for the met stations less than 150 m in altitude and the peak station of Mount Tai, respectively, when the new method was used. (3) Compared with the Tm and PWV computed by interpolated temperature without any correction, the accuracy of Tm can be improved by 31.2 % and 34.1 % in July and December for weather station in the altitude of 100 ∼ 350 m after the TLR correction, EMB compensation and RRM refinement successively. Meanwhile, the accuracy of PWV can be improved by 47.8 % in July and 42.0 % in December, respectively, and especially for PWV high-value moments. Besides, after correction by RRM, both Tm and PWV in low altitude areas achieve at least 20 % accuracy improvement. In summary, the systematic and complete refinement method proposed in this study are important to significantly improve the ERA5-land 2 m temperature availability and GNSS PWV accuracy, and the compensation of EMB is mainly effective for high altitude areas.

Adaptive silviculture for climate change in the Great Lakes- St. Lawrence Forest Region of Canada: Background and design of a long-term experiment

We present the implementation of the Adaptive Silviculture for Climate Change (ASCC) initiative at the Petawawa Research Forest (PRF) in Ontario, Canada. The study addresses the urgent need for adaptive forest management strategies in response to climate change by examining silvicultural treatments aimed at mitigating its impacts on forest ecosystems. It addresses the complex interplay between climate change projections, regional climate characteristics, and forest management practices for pine dominated forests in the Great Lakes-St. Lawrence Forest region of Canada, underscoring the importance of adaptive approaches in sustaining forest ecosystems. We outline the design and objectives of five distinct treatments—control, business-as-usual, resistance, resilience, and transition—implemented over 4 replicate blocks on a 212-ha area at the PRF. We provide detailed descriptions of each treatment’s management objectives, desired future conditions, and silvicultural strategies. We conclude by summarizing planned research efforts, including seedling survival assessments, phenological monitoring, and measuring treatment impact on fuel loads. By addressing the challenges and opportunities of climate change as part of an international research network, this research will contribute to a deeper understanding of forest ecosystem responses to climate change and inform adaptive management strategies for sustainable forest management.

Analysis of the summer thermal comfort indices in İstanbul

Thermal indices and thermal comfort maps have great importance in developing health-minded climate action strategies and livable urban layouts. Especially in cities where vulnerability to heatwaves is high, it is necessary to detect the most appropriate indicators for the regional characteristics and action planning with respect to thermal comfort. The aim of the study is to examine thermal indices as indicators of regional climate characteristics by relating to meteorological parameters and spatial features. Atmospheric variables including air temperature, wind speed, cloud cover, and relative humidity data were obtained from 30 meteorological stations located in districts having different climatic features. Heat stress levels for apparent temperature (AT), heat index (HI), wet bulb globe temperature (WBGT), physiological equivalent temperature (PET), universal thermal climate index (UTCI), and perceived temperature (PT) indices were calculated and associated with meteorological parameters. Thermal comfort maps have been created with the daily mean and maximum values of all indices. As a result, the meteorological parameters with the strongest correlation with all thermal indices are air temperature (Ta) with r = 0.89 ± 0.01 and mean radiant temperature (Tmrt) with r = 0.75 ± 0.16. The differences in thermal stress levels over the city have been distinctively observed in the ATmax, PETmax, and PTmax maps, which are generated by the daily maximum values of the indices. Çatalca, where forests cover large areas compared to highly urbanized districts, has the lowest heat stress defined by all indices.

The new record of drought and warmth in the Amazon in 2023 related to regional and global climatic features

In 2023 Amazonia experienced both historical drought and warm conditions. On October 26th 2023 the water levels at the port of Manaus reached its lowest record since 1902 (12.70 m). In this region, October monthly maximum and minimum temperature anomalies also surpassed previous record values registered in 2015 (+ 3 °C above the normal considering the 1981–2020 average). Here we show that this historical dry and warm situation in Amazonia is associated with two main atmospheric mechanisms: (i) the November 2022–February 2023 southern anomaly of vertical integrated moisture flux (VIMF), related to VIMF divergence and extreme rainfall deficit over southwestern Amazonia, and (ii) the June–August 2023 downward motion over northern Amazonia related to extreme rainfall deficit and warm conditions over this region. Anomalies of both atmospheric mechanisms reached record values during this event. The first mechanism is significantly correlated to negative sea surface temperature (SST) anomalies in the equatorial Pacific (November–February La Niña events). The second mechanism is significantly correlated to positive SST anomalies in the equatorial Pacific, related to the impacts of June–September El Niño on the Walker Circulation. While previous extreme droughts were linked to El Niño (warmer North Tropical Atlantic SST) during the austral summer (winter and spring), the transition from La Niña 2022–23 to El Niño 2023 appears to be a key climatic driver in this record-breaking dry and warm situation, combined to a widespread anomalous warming over the worldwide ocean.

The Role of Climatic, Environmental and Socioeconomic Factors in the Natural Movement of Urban Populations in Kazakhstan, 2012-2020: An Analysis from a Middle-Income Country in Central Asia.

This study addresses the importance of identifying key characteristics influencing demographic indicators for urban populations, emphasizing the need to consider regional climatic features and ecological factors. The research utilized data from ten main regional cities across the Republic of Kazakhstan. This study involved a retrospective analysis based on secondary data from official sources spanning 2012-2020. We employed correlation analysis and multidimensional regression models. Noteworthy predictors for crude birth rate included the influence of effective temperature (β = 0.842, p < 0.0001), marriage rate (β = 0.780, p < 0.0001), Gini coefficient (β = -27.342, p = 0.020) and divorce rate (β = -2.060, p < 0.0001), with overall strong model performance (R2 = 0.940). The degree of atmospheric pollution (β = -0.949, p = 0.044), effective temperature (β = -0.294, p < 0.0001) and Gini coefficient (β = 19.923, p = 0.015) were the predictors for crude mortality rate, with a high model fit (R2 = 0.796). The study unveils significant relationships between demographic indicators (crude birth rate, mortality rate) and variables like effective temperature, marriage rate, divorce rate, Gini coefficient, physician density and others. This analysis of climatic, environmental, and socioeconomic factors influencing demographic indicators may help in promoting specific measures to address public health issues in Kazakhstan.

Dominance of net autotrophy in arid landscape low relief polar lakes, Nunavut, Canada.

The Arctic is the fastest warming biome on the planet, and environmental changes are having striking effects on freshwater ecosystems that may impact the regional carbon cycle. The metabolic state of Arctic lakes is often considered net heterotrophic, due to an assumed supply of allochthonous organic matter that supports ecosystem respiration and carbon mineralization in excess of rates of primary production. However, lake metabolic patterns vary according to regional climatic characteristics, hydrological connectivity, organic matter sources and intrinsic lake properties, and the metabolism of most Arctic lakes is unknown. We sampled 35 waterbodies along a connectivity gradient from headwater to downstream lakes, on southern Victoria Island, Nunavut, in an area characterized by low precipitation, organic-poor soils, and high evaporation rates. We evaluated whether lakes were net autotrophic or heterotrophic during the open water period using an oxygen isotopic mass balance approach. Most of the waterbodies were autotrophic and sites of net organic matter production or close to metabolic equilibrium. Autotrophy was associated with higher benthic primary production, as compared to its pelagic counterpart, due to the high irradiance reaching the bottom and efficient internal carbon and nutrient cycling. Highly connected midstream and downstream lakes showed efficient organic matter cycling, as evidenced by the strong coupling between gross primary production (GPP) and ecosystem respiration, while decoupling was observed in some headwater lakes with significantly higher GPP. The shallow nature of lakes in the flat, arid region of southern Victoria Island supports net autotrophy in most lakes during the open water season. Ongoing climate changes that lengthen the ice-free irradiance period and increase rates of nutrient evapoconcentration may further promote net autotrophy, with uncertain long-term effects for lake functioning.

Evaluation of ERA5 and MERRA-2 Reanalysis Datasets over the Aegean Region, Türkiye

Reanalysis products are among the most-used datasets in the atmospheric sciences since they comprehensively describe the observed climate at sub-daily intervals in a region. Two reanalysis datasets, namely, the fifth generation of European Centre for Medium-range Weather Forecast (ECMWF) atmospheric reanalysis of global climate (ERA5) and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2), were evaluated for the representation of air temperature at 2 m, mean sea level pressure and wind speed over the Aegean Region of Türkiye during the period 1963–2020. Hourly reanalysis data were compared with observations in 19 meteorological stations in the region. Several statistical parameters, such as root mean square error (RMSE), correlation coefficient (R), and mean bias error (MBE), were used to evaluate the performances of the datasets. The results indicated that air temperature and mean sea level pressure are generally better represented by the MERRA-2 reanalysis in the region, whereas the ERA5 reanalysis dataset better represents wind speed. MERRA-2 had lower RMSE and slightly better performance at 11 stations with high R (&amp;gt;0.98) for mean sea level pressure. The MERRA-2 reanalysis dataset had a high overall R (&amp;gt;0.94) for air temperature and performed better at 12 stations. The overall regional R-value for the ERA5 wind speed dataset was 0.58, and ERA5 showed better performance at 13 individual stations for wind speed. Our results guide which reanalysis dataset better represents the regional climate characteristics for selected parameters.

Changes in regional climatic characteristics in the Non-Chernozem zone of the Russian Federation and their impact on soybean yields

The work analyzes agroclimatic resources in the Non- Chernozem zone of Russia for the period from 1981 to 2023. As a result of studying the data array, it was established that the values of the sum of active temperatures in the agroclimatic subzones of the Non-Black Earth Region increased by 200-250°C, the amount of precipitation falling during the growing season decreased by 20-40 mm, the hydrothermal humidification coefficient (HTC) of Selyaninov decreased by 0.1- 0.3 p. The changes led to a shift of the isotherm of the sum of active temperatures by 150-200 km towards high latitudes. A grouping of years of research was carried out according to the hydrothermal coefficient, the yield and growing season of soybean variety Georgia were determined. As a result of the research, it was revealed that the highest average seed yield for the group of years (moistening conditions) was obtained in the year with sufficient moisture and amounted to 2.47 t/ha, and the lowest - 1.18 t/ha per year with insufficient moisture. A significant relationship has been established between seed yield, the weight of 1000 seeds and the HTC of the growing season: the variation in soybean yield during the years of research is 63% associated with the influence of factors: the weight of 1000 seeds and the HTC of May-August (R2 = 0.63). Thus, the recorded upward trend in the sum of active temperatures in the region for the crop is positive and contributes to the expansion of soybean crops in the Non- Chernozem zone of the Russian Federation.

Разработка критериев оценки пригодности лесных участков для создания лесных плантаций в ДФО

The long-term experience of studying the problem of developing criteria for assessing the suitability of forest plots for the creation of forest plantations is summarized, which was the purpose of the research. The objects of research include forest plots for the creation of forest plantations located in the forest areas of the Far Eastern Federal District (FEFD); soils, snow cover, light regime, temperature, water bodies within the borders of the subjects of the Far Eastern Federal District of the Russian Federation; reclaimed areas; seedlings and cuttings of larch, etc. coniferous and deciduous species; natural and climatic factors. The research methods used are the matapparat, geoinformation systems and remote sensing of the Earth. The application of the research method for obtaining information about an object or phenomenon without direct physical contact with it made it possible to identify disturbed lands using multispectral combined images and calculate the NDVI image index. A low NDVI index was found in the studied area (from 0.034 to 0.063), indicating weak reforestation. Based on these limiting factors, taking into account the regional natural and climatic characteristics of the Far Eastern Federal District, a detailed differentiation of criteria for assessing the suitability of forest plots from a minimum (1) to a maximum (5) value is proposed by summing up their estimated indicator. Based on the analysis of the obtained results, the possibility of successful cultivation of plantation forests with the use of biostimulants has been proved.

Реконструкция благоустройства и озеленения жилой застройки 70-80 гг. на юго-востоке города Караганды

The article discusses the issues of reconstruction of green spaces and improvement of typical courtyard spaces that do not meet the modern needs of residents and the qualities of a modern living environment. The main problems of the study are the spontaneity of parking, the impersonality of the territory, and the lack of differentiation of the yard into zones for diverse social activities. Without clear functional zoning of a residential yard, the potential of empty spaces is devalued, which leads to a deterioration in the environmental and aesthetic qualities of residential areas, desolation and the “dying away” of green recreation areas. The comfort and safety of the microclimate of residential areas are the basis for the formation of a harmonious environment in multi-storey residential buildings. During the study, a questionnaires and surveys of neighborhood residents were conducted, as well as a functional analysis of existing residential areas. Based on aforementioned information and analogues of landscaping and improvement of residential courtyards in South Korea, conclusions are drawn regarding the similarities and differences in approaches, and a conceptual proposal is formed. The concept for the reconstruction of a residential courtyard is a unified system of principles for humanizing the city’s residential environment with minimal means of improvement, using “reserve territories” and regional natural and climatic features.

Research on the Current Situation of Thermal Environment in Guanzhong Farmhouses and Strategies for Improving Human Settlement Environment

Energy is one of the most important factors that constrain global economic development, and it is the fundamental guarantee for national economic development and the circular development of various industrial links. Building energy conservation is the key to achieving energy conservation and emission reduction. The Guanzhong region is a typical cold winter and hot summer area, and in the development process, Guanzhong residential buildings have also formed a set of construction strategies suitable for the regional climate characteristics. Combining local unique construction techniques and materials, the building exhibits significant local characteristics. This study analyzed the climate characteristics and passive technologies in the Guanzhong region, and constructed a 3D model of typical rural houses. Based on field research, a green development strategy was proposed by comparing and analyzing the differences between actual monitoring of ventilation and lighting and mathematical simulation. This study contributes to promoting the improvement of regional living environment and sustainable development.

Estimation of the Optimal Storage Capacity of Rainwater Harvesting System Considering Regional Climate Characteristics

Due to the influence of climate change, the frequency and intensity of droughts in the Korean Peninsula regions are increasing. Moreover, regional rainfall deviations are increasing, increasing the severity of localized droughts. Accordingly, it is necessary to enhance water resource utilization through recycling and establishing a robust safety net for water supply. This necessitates the implementation of rainwater harvesting systems to augment water reuse capabilities. When planning the storage capacity of a rainwater harvesting system, it is important to calculate the appropriate capacity. Therefore, we created an Excel tool for water balance analysis in this study. It incorporates diverse rainwater uses, their respective usage conditions, and daily usage quantities. A water balance analysis was performed, applying the climate characteristics of different regions. A cost-benefit analysis was applied to the economic feasibility analysis, and a B/C regression curve by region and catchment area was derived based on the results of the water balance analysis. The tool is believed to be an effective support measurement to help decision-makers to calculate the appropriate storage capacity of rainwater harvesting systems in the relevant regions.

Analyzing uncertainty in probable maximum precipitation estimation with large ensemble climate simulation data

AbstractThis study aimed to evaluate probable maximum precipitation (PMP) estimated using surface dew points (SDP) or actual precipitable water obtained from upper‐air data (UAD) in the moisture‐maximization method with the help of sufficient extreme precipitation events using large‐scale climate ensemble simulation data (d4PDF). The deviations between the PMP variables estimated by the SDP and UAD approaches were analyzed for southern and northern areas of Japan to consider the regional characteristics of the deviations. We found that the deviations were high in northern areas where the SDPs are relatively low during precipitation events. The PMPs estimated using each approach were also compared to the extreme‐scale reference precipitation proposed in this study. The SDP approach overestimated the PMPs by over 20% compared to the reference precipitation in the northern region. However, the UAD approach showed very low average errors in all southern and northern areas. This tendency of the SDP approach was significantly related to the regional climatic characteristics of the SDP, which indicated that the SDP approach may estimate an uncertain PMP value depending on each regional climatic characteristic compared to the UAD approach. Regional climatic characteristics should be considered when using the SDP approach to estimate the PMP.

Analysis of the Composite Risk Grade for Multi Extreme Climate Events in China in Recent 60 Years

Much attention has been given to the change rule of a single extreme event, and there are few reports on comprehensive characteristics of multiple extreme events in a certain region. Based on the analyzes of annual frequency of extreme high temperature, extreme low temperature, extreme drought, extreme precipitation, and extreme typhoon events in China from 1961 to 2020, a multi extreme events composite risk grade index (MXCI) was constructed and applied to the comprehensive characteristics analyzes of multiple extreme events in China. The results show that the high value areas of MXCI were mainly located in southeast China and southwest China. Over the past 60 years, the MXCI has shown a decreasing trend in western China and most of southeastern China, and an increasing trend in the middle zone from southwest China to northeast China. Through comparative analysis, MXCI can objectively reflect the comprehensive characteristics of multiple extreme climate events in a region, which is helpful to understand regional extreme climate characteristics and effectively cope with extreme climate risks.

Drought characteristics in Mediterranean under future climate change

The present work aims to address the physical properties of different drought types under near-future climates in the Mediterranean. To do so, we use a multi-model mean of the bias-adjusted and downscaled product of five Earth System Models participating in the Coupled Model Intercomparison Project—phase6 (CMIP6), provided by Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), under four shared socioeconomic pathways (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5) for the period 2021–2060, to estimate the Standardized Precipitation Evapotranspiration Index (SPEI) at 1-, 6-, and 12-month time scales, and address the meteorological, agricultural, and hydrological drought, respectively. Additionally, SPEI is calculated from the bias-adjusted CMIP6 historical simulations and the reanalysis ‘WFDE5’ for 1980–2014 as a historical and reference period. The comparison of the CMIP6 with WFDE5 reveals a consistently increasing tendency for drought occurrences in the Mediterranean, particularly for agricultural and hydrological drought time scales. Nonetheless, an overestimation in historical trend magnitude is shown by the CMIP6 with respect to WFDE5. The projection results depict drought frequencies ranging between 12 and 25% of the studied period 2021–2060, varying with regions and climate scenarios. The tendency to increase the drought frequency is more pronounced in the southern than northern Mediterranean countries. Drought severity is remarkable in the aggregated time scales; consequently, more pressure is foreseen in the food and water sectors. Drought seasonality reveals a higher tendency for drought occurrences in summer (autumn) months for the meteorological (agricultural) droughts. The driving factor(s) for drought occurrence strongly depends on regional climate characteristics.

Diurnal cycle of precipitation and its possible causes: A case study in Shandong Province, China

AbstractAccurate information on diurnal precipitation variations is essential for understanding the mechanism of precipitation formation, assessing the regional climate characteristics, and improving the simulation performance of climate models. Taking Shandong Province, East China, as a case study, 123 stations with hourly observational precipitation data were divided into three categories by the harmonic analysis on diurnal variation of precipitation, and the diurnal variations in precipitation amount, frequency and intensity were further analysed to derive the precipitation partition. The results showed that: (1) the peak precipitation frequency at different types of stations occurred steadily around 0400–0600 LST, whereas the peak precipitation intensity existed at different moments such as 0200 and 1700, and precipitation amount mostly showed a double‐peak pattern in the early morning (0400–0600 LST) and late afternoon (1600–1800 LST); (2) early morning precipitation was mainly driven by persistent precipitation, which contributed between 65.2% and 84.3%, while precipitation peaks in the late afternoon with a significant increase in the contribution of short duration precipitation; and (3) the influence of mountain–plain circulation and the increasing effect of topographic uplift on precipitation may be the main reasons for the formation of early morning precipitation peaks. The strength of sea–land winds and local convection was also key factors affecting the diurnal variation of precipitation.

The impact of climate change on cognitive performance of children in English school stock: A simulation study

Children in England spend around 30% of their time in schools to gain knowledge and skills. Climate change could impact schools' thermal environments and children's learning performance by impairing their cognitive ability. This study presents an evaluation approach to investigating and quantifying climate change's impact on the cognitive performance of children across English school stocks. The study also evaluates the potential of possible strategies for mitigating the impacts of climate change. The results show that future climates are projected to increase cognitive performance loss of children in school archetypes representative of school stocks, with variations based on regional climate characteristics. Increasing ventilation rates proves to be an effective means of reducing cognitive performance loss, while its effectiveness diminishes as outdoor temperatures rise in the future. Thus, the introduction of air conditioning becomes a potentially more beneficial strategy, despite the associated increase in cooling energy demand. Moreover, higher ventilation rates in air-conditioned classrooms can further improve children's cognitive performance. The use of cognitive performance loss as a Key Performance Indicator (KPI) allows for better communication and understanding of climate change risks faced by schools among building and non-building experts. The proposed evaluation approach remains adjustable and can be continuously updated and enhanced as new insights from psychological research emerge.

Thunderstorm and hailstorm environments in Mexico

AbstractThunderstorm and hailstorm environments from 1981 to 2018 are analysed using the proximity soundings approach based on the European Centre for Medium‐Range Weather Forecasts Reanalysis v5 (ERA5) reanalysis dataset. Given the nature of the severe weather dataset, four proximity soundings 0000, 0600, 1200, and 1800 local time were retrieved per day with hail activity or thunderstorms. After quality control, a total of 30,760 vertical profiles were used and grouped seasonally and spatially to consider the local variation of the convective environments. Diverse instability, kinematic, and composite parameters were calculated to characterize the environments for these two convective hazards. The results indicate differences mainly modulated by orographic features, continentality, regional climate, and general synoptic characteristics. Higher instability environments of thunderstorms and hailstorms are observed in the subregions near moisture sources such as oceans, principally during summer and autumn when tropical activity occurs. High wind shear environments are concentrated during winter and spring, mainly in central and northern regions of the country, associated with the passage of frontal systems. The covariates are reasonably accurate at predicting severe weather, but their prediction skill decreases during the warm season when severe weather is more common in Mexico. Increased knowledge of severe weather and associated convective hazards will improve weather forecasting and may be helpful in disaster risk reduction due to meteorological hazards in Mexico.