This study evaluated the performance of the Weather Research and Forecasting (WRF) model with Four-Dimensional Variational (4DVar) data assimilation using the Global Satellite Mapping of Precipitation (GSMaP_NOW). Several verification metrics, including the root mean square error (RMSE), bias Score, equitable threat score (ETS), - fractional bias score (FBS), and fractional skill score (FSS) were employed in the assessment. The results demonstrated that 4DVar improved the accuracy of vertical velocity and specific humidity predictions at mid and upper levels, as well as the enhanced heavy rainfall forecasting. Spatially, 4DVar was able to increase specific humidity and vertical velocity in lowland areas, leading to higher rainfall in those regions. Future studies should investigate the assimilation of additional conventional and satellite observations to further enhance forecast accuracy.
This study investigates the angular distribution of the degree of polarization of diffusely reflected and transmitted natural solar radiation in atmospheric layers subjected to multiple Rayleigh scattering. The analysis employs the Chandrasekhar's S,T-matrix theory and the factorization method. Specific characteristics related to the numerical computation of X and Y functions using the successive approximations method are detailed. The results reveal that when the observation angle equals the illumination angle (& auml; = & auml;4), a notable feature emerges in the angular distribution of the degree of polarization of diffusely transmitted light. At this juncture, a sharp change in the degree of polarization is observed. Additionally, the study examines the dependence of the angular width of this discontinuity on the illumination angle and optical thickness.
The identification, monitoring and prediction of the possible future conditions of drought, a complex disaster, are of significance for decision makers in planning natural-social and human activities and planning, operation, and management of water resources. The present study investigates the meteorological drought experienced by Amasya and Merzifon, located within the transition zone between the Black Sea and continental climates in T & uuml;rkiye. The analysis employs the standardized precipitation index (SPI), the China-Z index (CZI), and the modified China-Z index (MCZI), utilizing annual time scales to assess the precipitation patterns in these regions. The precipitation records obtained from the selected meteorological stations between 1964 and 2023 were analyzed in order to assess the drought and compare the performance of precipitation-based drought indices. The investigation also focused on drought-wet period percentages, the percentages of occurrence of drought classes, and the negative and positive peak index values. According to all three drought indices, significant dry years were identified, including 1964, 1974-1976, 1982, 1984, 1986, 1990, 1999, 2013, 2017, and 2020.The assessment revealed that SPI, CZI, and MCZI performance was similar in identifying drought in transition climate zones. It was also determined that CZI and MCZI are a viable alternative to SPI for drought monitoring.
To better understand the impacts of global and regional climate change, it is essential to conduct investigations at the local level as well, particularly in climatically sensitive areas. The aim of our study is to present the climatic characteristics of the Nagykuns & aacute;g region based on annual data recorded at the Karcag meteorological station (HungaroMet 55405) between 2005 and 2024. Our analysis focuses on the long-term trends of key meteorological variables such as temperature, precipitation, evaporation, sunshine duration, wind speed, and air pressure. For data processing, we used the built-in statistical tools of Microsoft Excel, especially linear regression, moving averages, and trendline fitting. During the examined period, we identified a significant increase in temperature (+0.097 degrees C/year), a slight decrease in precipitation (-9.72 mm/year), and a rise in the number of sunshine hours (+18.95 hours/year). Our results highlight not only the ongoing climatic changes but also the urgent need for regional adaptation measures, particularly in agricultural management and water resource planning. The methodology demonstrates that accessible statistical tools can provide valuable insights to support local climate resilience strategies.
The database of the present examination is the homogenized and interpolated precipitation time series of Hungary, which is diurnal amounts of precipitation for the 1233 grid cells, covering the area of the country for 1971-2022, in the state of the database in 2023. Firstly, the diurnal amount of precipitation over the area of the country, which is the sum of precipitation that falls in each grid cell over the area of the country has been chosen as a variable to be analyzed. Its annual and monthly characteristics have been analyzed for different independent variables. Secondly, spatial characteristics of the diurnal amount of precipitation, that is its distribution among the grid cells have been examined as well. Based on the above time series, nationwide dry, nationwide rainy, and locally rainy/dry days can be distinguished. In this article, we examine the frequency and precipitation yield of both nationwide, and locally rainy days. Precipitation tendency of an area is measured by the frequency of rainy days on the area and their precipitation yield based on the statistics of rainy days per grid. Our basic goal is to explore the temporal and spatial distribution of rainy days nationwide and locally.
This study evaluates the risk of wood decay in cultural heritage sites across the European part of Russia by analyzing climatic influences on timber deterioration. Timber, a critical component of many heritage structures, is particularly vulnerable to fluctuations in air temperature and moisture, which accelerate biological decay processes. Using the Scheffer Climate Index (SCI)-a metric based on average monthly temperature and the number of precipitation days-, the research assesses decay risk over the period 1961-2020 with daily data from the ERA5 reanalysis. The SCI was decomposed into temperature and precipitation components, and trends were quantified using the nonparametric Mann-Kendall test, with analyses performed for both the 1961-1990 and 1991-2020 periods. Results reveal a southwestward increase in SCI values, with the highest risks (SCI > 100) along the Black Sea coast and Caucasus. Notably, northern regions, home to key heritage sites like Kizhi Pogost, exhibited statistically significant upward SCI trends (up to 0.6/year), driven primarily by rising temperatures. Between 1961-1990 and 1991-2020, low-risk areas decreased by 9%, transitioning to moderate risk, while high-risk zones remained stable (similar to 13%). Temperature contributions to SCI increased by 5-20%, whereas precipitation impacts declined, except in northern regions. Sequential analysis highlighted trend onset in the 2000s, particularly in the northwest and Caucasus. These findings underscore a rising climatic threat to wooden architectural heritage and emphasize the need for enhanced conservation strategies to mitigate future decay risks.
This study analyzes trends in three temperature variables (average annual air temperature, maximum air temperature, and minimum air temperature) for 72 time series from 24 meteorological stations in Central Serbia, spanning from 1949 to 2018. Data was sourced from meteorological yearbooks on the website of the Republic Hydrometeorological Institute of Serbia. Three statistical approaches were used: trend equation, trend magnitude, and the non-parametric Mann-Kendall (MK) trend test. GIS was applied to visualize geospatial data distribution. The results indicate a temperature increase in 66 of the 72 time series, with the largest increase of 4.3 degrees C and the smallest of 0.2 degrees C. Temperature decreases were recorded in 6 time series, with the largest decrease of-0.5 degrees C. The MK trend test revealed a statistically significant positive trend in 53 time series. Geospatial analysis showed varying temperatures across the region, with average annual air temperatures ranging from 10.6 degrees C in Dimitrovgrad to 18.1 degrees C in Belgrade. These findings offer insights into climate change in Central Serbia, highlighting areas of temperature increase and decrease, and provide a foundation for future climate research and strategy development.
management of weather conditions plays a critical role in ensuring safe and efficient flight operations in the aviation industry. In this context, the wind factor has a direct impact on aircraft performance and pilot decision-making mechanisms, especially during landing and takeoff processes. Within the scope of the study, 16 years of wind data recorded between 2008 and 2023 at Samsun & Ccedil;ar & uacute;amba, Zonguldak, and Trabzon airports located in the Black Sea Region are analyzed. Innovative Trend Analysis (ITA) and Innovative Polygon Trend Analysis (IPTA) methods are used to analyze the trends of wind direction, speed, and sudden changes. According to the results obtained, the dominant wind direction at Samsun & Ccedil;ar & uacute;amba and Zonguldak airports was determined as east (E), while a dominant wind effect was determined in the south-southwest (SSW) direction at Trabzon Airport. The study reveals the effects of wind factor on flight safety and operational efficiency and provides recommendations for the measures to be taken in the aviation sector and future practices.
This study investigates the influence of the Southern Oscillation and North Sea-Caspian Pattern on maximum rainfall intensities in the Black Sea Region of T & uuml;rkiye. Annual maximum rainfall intensity series from 16 meteorological stations were analyzed, and correlation coefficients were calculated and evaluated at . = 0.01, 0.05, and 0.10 significance levels. Results indicate that the Southern Oscillation predominantly affects short-and medium-duration rainfall in Sinop, whereas the North Sea-Caspian Pattern shows significant correlations with medium-and long-duration rainfall in Bart & Otilde;n, Bayburt, and G & uuml;m & uuml;& uacute;hane. These findings highlight the spatially varying influence of atmospheric oscillations on rainfall extremes in the region.
Drought is a serious environmental issue that negatively impacts water resources, agricultural production, ecosystems, and economic activities as a result of prolonged periods of low precipitation. In particular, the depletion of water resources and difficulties in accessing water pose significant threats to societies. In this context, developing effective forecasting systems in regions at risk of drought is critical for managing water resources more efficiently and taking timely measures. This study examines the potential of integrating various drought indices and machine learning techniques to improve the accuracy of meteorological drought predictions. Using data from 54 meteorological stations in Spain for the 1973-2023 period, drought analyses were conducted based on the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and reconnaissance drought index (RDI). Future drought predictions were made using the Random Forest (RF) algorithm. The RF algorithm successfully analyzed historical climate data to understand the temporal and spatial dynamics of drought occurrences. Additionally, a newly developed drought mapping approach demonstrated that short-term droughts are more prevalent in northern Spain compared to the southern regions. The findings highlight the likelihood of increased drought severity in specific areas and its potential impacts on agricultural production and water management. This study serves as a crucial guide for policymakers aiming to develop drought management strategies and contributes to effective planning to mitigate future drought impacts. Furthermore, the developed software is provided as open source alongside the article.
An exact statistical description of present and future climate requires a database representative in space and time. However, observation records – that is raw climatological time series – are loaded with inhomogeneities due to changes in the location of the weather stations and usage of different instruments and observation protocols. Datasets must be homogenized first, which means that previous measurement data must be adjusted to the present observation protocols, while missing data must be supplemented. The data base of the present examination is the homogenized precipitation time series of Hungary, that is diurnal amounts of precipitation for the 1233 grid cells which cover the area of the country over the period of 1971-2022 in the state of the database in 2023. Firstly, the diurnal amount of precipitation over the area of the country, that is the sum of precipitation what falls in each cell of the grid over the area of the country has been chosen as a variable to be analyzed. Its annual and monthly characteristics have been analyzed for different independent variables. Secondly, spatial characteristics of the diurnal amount of precipitation, that is its distribution among the grid cells have been examined as well. In this article, after summarizing the climatic characteristics and the characteristics for the examined period of the total precipitation in Hungary, we analyze the spatial and temporal statistical properties of the daily dry grids and the dry days per grid. Dry days and grid cells are those when and where the daily precipitation amount is under 0.1 mm.
This study analyzes long-term (1940-2023) monthly temperature trends across the Northern Hemisphere, focusing on tropical, temperate, and polar regions, as well as key mountainous areas such as the Rocky Mountains, the Tibetan Plateau, and the Alps. Results show that polar regions experienced the highest seasonal temperature increase, averaging 0.081 degrees C per season during winter, while tropical regions exhibited the lowest increase, with 0.036 degrees C during winter. In temperate regions, seasonal warming trends ranged from 0.05 degrees C in winter to 0.039 degrees C in summer. Monthly trends revealed that February and March exhibited the highest increases, with rates of 0.0195 degrees C and 0.0194 degrees C, respectively, while August showed the lowest increase at 0.0116 degrees C. Furthermore, trend maps indicate that over 92% of the Northern Hemisphere experienced warming across all months except June and January. These findings provide a comprehensive understanding of regional and seasonal temperature variations in the Northern Hemisphere, emphasizing the importance of localized and temporal analyses for a more nuanced perspective on climate change.
The present study analyzes the long-term (1871-2020) precipitation time series of Mosonmagyar & oacute;v & aacute;r (Hungary) and investigates the precipitation trends affecting winter wheat production. Understanding precipitation trends is important for agriculture due to the increasing frequency and intensity of droughts caused by climate change. In this study, parametric and non-parametric trend tests (linear and Mann-Kendall trend test) were applied, which showed a significant decrease in April and October. A significant downward shift of the mean can be demonstrated in spring by Pettitt's test. This decrease has a negative impact on key growing periods for winter wheat, which poses a serious challenge to conventional wheat production in the region. The research highlights the importance of different agrotechnical solutions to reduce yield losses due to climate change. The results obtained are in line with trends observed in Keszthely (Hungary), which confirms the regional changes. These climatic changes can have a significant impact on the cultivation of our most important domestic food crop, winter wheat, so it is worth preparing for adaptation from this point of view as well.
An exact statistical description of present and future climate requires a database representative in space and time. However, observation records-that is raw climatological time series-are loaded with inhomogeneities due to changes in the location of the weather stations and usage of different instruments and observation protocols. Datasets must be homogenized first, which means that previous measurement data must be adjusted to the present observation protocols, while missing data must be supplemented. The data base of the present examination is the homogenized precipitation time series of Hungary, that is diurnal amounts of precipitation for the 1233 grid cells which cover the area of the country over the period of 1971-2022 in the state of the database in 2023. Firstly, the diurnal amount of precipitation over the area of the country, that is the sum of precipitation what falls in each cell of the grid over the area of the country has been chosen as a variable to be analyzed. Its annual and monthly characteristics have been analyzed for different independent variables. Secondly, spatial characteristics of the diurnal amount of precipitation, that is its distribution among the grid cells have been examined as well. In this article, after summarizing the climatic characteristics and the characteristics for the examined period of the total precipitation in Hungary, we analyze the spatial and temporal statistical properties of the daily dry grids and the dry days per grid. Dry days and grid cells are those when and where the daily precipitation amount is under 0.1 mm.
study investigated the spatial and temporal distribution of aridity indices to determine climatic conditions in regions of southern and eastern Serbia in the period 1961-2022. We used the mean monthly and annual air temperature and precipitation data obtained from nine meteorological stations in the study area. Three indices were used to quantify aridity: the de Martonne aridity index, the Emberger index and the Pinna combinative index. Calculations are carried out on an annual scale for all the indices mentioned. The results show large territorial differences in the de Martonne aridity index, which distinguishes between two climate types on an annual basis. The Emberger index is characterized by humid climate types for all meteorological stations in the area. The Pinna combinative index also indicates humid conditions in the entire area, although the annual values of the index vary considerably. There was no change in the trend of aridity in the study area during the period of investigation. The spatial distribution was determined via the inverse distance weighting interpolated method. The Mann-Kendall test indicated that the aridity trends at all the meteorological stations were not statistically significant.
To better understand outdoor thermal comfort on both seasonal and monthly levels, the current trends and anomalies in the Podrinje-Valjevo Region (PVR) over the past 30 years (1991-2020) and their impact on tourist activities, two bioclimatic indices, the Universal Thermal Climate Index (UTCI) and the Tourism Climatic Index (TCI), were utilized for the temporal assessment of bioclimatic conditions in Loznica and Valjevo. The results show that spring and autumn are the most favorable seasons for outdoor tourism activities, with April, May, September, and October being particularly optimal. According to UTCI, November has also become more bioclimatically favorable due to a rise in average monthly UTCI values. Additionally, UTCI data reveal a notable upward trend in seasonal anomalies, especially during autumn and spring, with average seasonal UTCI values increasing. Although TCI indicates that summer is particularly ideal for tourist outdoor activities and tourists' thermal comfort, UTCI highlights that summer months can cause significant thermal discomfort due to moderate heat stress. The results obtained can serve to more effective tourism planning in the Podrinje-Valjevo Region in Serbia.
To describe and study the climate and its changes more accurately, climate databases are needed that are representative in time and spatial coverage, and that are based on sufficiently long measurement data series. In Hungary, air pressure measurements have a long history, similar to temperature and precipitation, but a homogeneous gridded database of Hungarian air pressure measurements over a century, with a daily resolution covering the whole 20th century, has not yet been produced. Therefore, the main aim of this research was to produce a homogenized gridded daily air pressure database from the beginning of the 20th century, which is currently available from 1961 only. In addition, in the period after 1961, and especially in the last few decades, station data series are used in much greater numbers than before. This will produce a more accurate interpolation, i.e., a more accurate grid point database than at present, which can be updated annually in the future, as for temperature and precipitation. In this paper, we describe the methods used, discuss the station systems used for homogenization and interpolation of air pressure in different time periods, analyze the main verification statistics of the homogenization, and also analyze the results of the interpolation, examine the annual, seasonal, and monthly surface air pressure data series and their extremes, including the daily extremes for the period 1901-2023.
The atmospheric teleconnection presented in our former paper (Babolcsai and Hirsch, 2019) shows a particularly strong regularity between the Euro-Atlantic mean sea level pressure anomaly pattern in September and the pattern three months later, in December, in the current positive AMO (Atlantic Multidecadal Oscillation) phase lasting since 1995. Euro-Atlantic mean sea level pressure anomaly patterns for September were divided into four clusters, whereas cases that could not be classified as any of these, were assigned to a fifth cluster. Based on the clustering, the December macrosynoptic situation in Europe can be predicted in a significant number of cases, and hence the sign of the temperature anomaly in Central Europe. In our paper, these regularities are described, as well as their connection to the polar vortex, which is the main factor in forming the mean sea level anomaly of the winter months of the northern hemisphere. In the last 29 years, clustering based on the mean sea level pressure anomaly for September has been able to divide significantly cold and mild December months even better than the state of the polar vortex in December (sign of the AO index). In addition, a new phenomenon is presented, which might be a sign of climate change and has been interfering in the atmospheric processes since 2019.
It is a well-known phenomenon that sinkholes, compared to their environment, have a relatively colder microclimate, due to the topographic conditions (closed depressions). Its geomorphological characteristics favors the development of cold-air pools and can cause significant temperature anomalies. This process has been documented in several papers before, but the detailed buildup and breakup, and especially the environmental covariates that drive these processes, are not well documented yet. This paper aims to summarize a three months period measurement (spring of 2023) in Northern Hungary, on the karst plateau of the B & uuml;kk Mountains. This plateau is characterized with a complex karst surface development, having interconnected sinkhole systems. The Mohos sinkhole-the largest sinkhole of the area with several contributing smaller sinkholes-was selected for the measurement campaign. A detailed terrain and remotely sensed database were built to characterize the geomorphology and its contribution to the development of the sinkhole's microclimatic system. A sensor system was developed and adopted to the local conditions using 10 directly measured or derived meteorological parameters (air temperature (200 cm, 40 cm), dew point, solar radiation, relative humidity, wind speed, daily evapotranspiration, vapor pressure deficit., and soil temperature), along with two comparison sites from the edge of the sinkhole and from a representative site of the B & uuml;kk Plateau, where no major microclimatic derivation factor was assumed. During this period, the Carpathian Basin was characterized by a significant variability of weather patterns, and was optimal to analyze the behavior of the sinkhole's microclimate system based on the regional weather trends and their atmospheric dynamics. Several temperature inversion events were developed and analyzed to describe the relationships between the cold-air pool development and the external meteorological affects. The events were classified into the commonly accepted categories. The results demonstrated that the time of the lowest recorded temperatures was partly independent from the general temperature regimes. The most important factors are the general geomorphological factors, favorable radiation conditions, and lack of any external physical disturbance. It was also proved that the soil temperature had the largest correlation with the temperature change (r = 0.95), followed by the dew point (r = 0.92), vapor pressure deficit (r = 0.85), wind speed (r = 0.83) and the relative humidity (r =-0.8). That was also documented, that the near-surface dynamics play an important law in the behaviors of the sinkhole microclimate system, thus the buildup and breakup of the cold-air pool.
The issue of drought is treated as an important natural phenomenon that often has a negative impact on both the livelihoods of the population and environmental protection. Many parts of the world have been affected by catastrophic droughts in the past, leading to prolonged periods of famine and disease among local populations. According to the definition provided by the Intergovernmental Panel on Climate Change in 2014 (IPCC), drought can be assessed as a potential hazard and challenge depending on the evaluation of its impact on the population and its economic activities. The aim of this study is to determine drought periods in Bosnia and Herzegovina and to highlight their consequences. For the purpose of analysis, available data on average monthly precipitation from 12 meteorological stations in Bosnia and Herzegovina from 1956 to 2022 were used. The Standardized Precipitation Index (SPI-1 and SPI-3) was used to determine meteorological drought, including its intensity, frequency, and duration. Based on the results obtained, a relatively uniform frequency of drought was observed across the seasons. On the other hand, extreme droughts were most pronounced in winter and spring months. The maximum duration of drought was recorded in Zenica from November 1989 to October 1990.
