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.
