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With the increasing number and intensity of drought events, understanding the ecological drought risk in the Yellow River Basin has become an important prerequisite for ecological protection in the basin. Based on the climate, environment, and human activities in the Yellow River Basin, this study constructed the ecological drought risk evaluation index system and model, revealed the spatial distribution characteristics of risk, and analyzed the dominant factors responsible for ecological drought risk through the bivariate local Moran’s I index and an optimal parameter-based geographic detector (OPGD)-based model. The results show that the high-risk areas of ecological drought are mainly located on the northern Shaanxi Plateau, the central Gansu Plateau, the Ningxia Plain, and the Hetao Plain (except for irrigated areas). From the perspective of land-use types, the ecological drought risk from high to low was wasteland, grassland, woodland, farmland, and town areas. High-risk areas accounted for 20.30% of the total watershed area. Through spatial correlation analysis, it was found that the upper reaches were affected by both surface temperature and precipitation, whereas the Guanzhong Basin and lower reaches were mainly affected by precipitation only. The dominant factors associated with vulnerability and sensitivity were precipitation utilization efficiency and fractional vegetation coverage, respectively. Hazard is the dominant factor leading to regional differences in ecological drought risk, and vulnerability, sensitivity, and exposure can alter the local characteristics of the spatial distribution of ecological drought risk.

This work calculates the current heating and cooling degree days and also examines heating and cooling degree days in relation to three subdivisions of the twenty-first century. On the basis of these data, we were able to calculate the heating and cooling degree months and degree years. After examining both sets of data, we studied the total needs of air conditioning—also referred to in the current paper as climatization needs——for Andalusia as a whole. The results indicate an increase in air conditioning needs, and we also noted that the areas adversely affected by this increase were more numerous than those which benefited, at the end of the century. It should be noted that climate change will also necessitate the gradual replacement of heating with cooling, which will require profound changes in the energy, land planning, and housing policies of the region. The true magnitude of the challenge becomes clear when the climatization degree days are related to the population which they affect; the majority of the population is located in areas where the climatization needs will increase over the course of the century. Undoubtedly, this issue is a major protagonist in the climate change adaptation process in Andalusia.

A simple model for the determination of SO2 emission potential (the permissible emission) in basins is presented. Some Slovenian basins have been chosen to indicate the time increase of SO2 concentrations in the dependence of decay, the emission and relief conditions of basins, and also to indicate the influence of the permissible concentration level on the emission potential.

In order to quantify the impact of the use of different parameterization schemes on regional climate model outputs, hindcast experiments have been completed applying the Regional Climate Model version 4.3 (RegCM4.3) for the Carpathian region and its surroundings at 10-km horizontal resolution with three different cumulus convection schemes. Besides, the sensitivity of outputs for subgrid-scale processes is also studied by activating the subgrid Biosphere-Atmosphere Transfer Scheme (BATS) model within other RegCM experiments. Among the analyzed factors, RegCM is most sensitive to the applied convection scheme. The impact of closure assumption related to the used convective parameterization is secondary, while the use of subgridding has less influence on the outputs. RegCM4.3 results show improved performance over our previous model simulations but still have larger amplitude for annual precipitation cycle than the measurement-based reference data. Our validation results for temperature and precipitation suggest that for the selected region, the overall best performance is achieved when using the mixed Grell-Emanuel scheme together with Fritsch and Chappell closure.

Under the background of global warming, precipitation extremes are the main reasons for the cause of drought-flood disasters at local scales. Regional evaluations on the spatial and temporal variations of precipitation extremes are needed for comprehensively understanding the precipitation-related natural disasters. In this study, ten extreme precipitation indices from 17 meteorological stations in the Hanjiang River Basin, China, were computed and their spatial and temporal variations were analyzed using linear tendency method, based on daily precipitation data for the period of 1960–2015. Results indicated that consecutive dry days, number of heaviest  precipitation days, maximum 1-day precipitation, very wet day precipitation, extremely wet day precipitation, and simple precipitation intensity index exhibited non-significant increasing trends. Consecutive wet days, number of heavy  precipitation days, maximum 5-day precipitation, and total wet day precipitation exhibited non-significant decreasing trends. Using Mann-Kendall test, cumulative anomaly method, and moving t test for cross-validation, an abrupt increase was detected in 1978 for both very wet day precipitation and extremely wet day precipitation and for both these two indices, there were two significant periodic variation cycles, i.e., 1–2 years and 4 years, and in addition, extremely wet day precipitation had a change cycle of 8 years. The cross-wavelet transform method suggested that Pacific Decadal Oscillations and Sea Surface Temperature might be the two driving factors of extreme precipitation variation. The changing trends of precipitation extremes showed regional differences, but the stations with significant trends were not clustered. All the indices were highly correlated with each other, except for the number of consecutive dry days and consecutive wet days. The contribution of extreme precipitation to total precipitation revealed a non-significant increase in the study area. There were negative correlations between most of the indices and elevation with high level of significance. Changes of large-scale atmospheric circulation showed an increasing geopotential height and a weakened summer monsoon and had an impact on the variations of extreme precipitation.

An algorithm for estimating rainfall (based upon scattering of upwelling radiation at 85 GHz) using the Special Sensor Microwave Imager (SSM/I) 85 GHz sensor data has recently been developed at the National Oceanographic and Atmospheric Administration's Office of Research and Applications (NOAA ORA). Spatial and temporal variability in the differences between simple areal-averaged rainfall estimates from a raingage and satellite-derived estimates are examined. These initial comparisons provide insight into the nature of the differences; however, due to substantial amounts of spatial sampling error in the raingage spatial averages, this approach is ineffective at identifying statistically significant differences. Thus, rainfall estimates for this algorithm are examined over the tropical Pacific using a statistical technique, called the “noncontiguous raingage method” (NCR), which minimizes spatial sampling error so that the statistical significance of relationships may be determined. The results indicate that, adjusted with calibration coefficients, the ORA algorithm could produce unbiased estimates of areal rainfall for the tropical Pacific region examined in this study.

When modelling mesoscale effects in the coastal climate we have to account for the significant influence of humidity and for the land-sea contrast which is represented by the roughness lengthz 0 =z 0(x, y) and the heat capacityC 0 =C 0 (x, y). This brings about strong horizontal inhomogenities which affect the meteorological situation significantly. The effects of these inhomogenities on the structure and variation of the boundary layer in the coastal region are studied by use of a three-dimensional numerical model; the formation process of advective fog in connection with different geostrophic winds is also investigated. As main results we present 1) the modifications of wind velocity and wind direction as a function of the roughness distribution and different thermal stratifications and 2) two simulations of advective fog formation assuming different geostrophic wind values in each example.

The urban heat island (UHI) of the city of Bucharest (Romania) is analyzed in terms of its extension, geometry, and magnitude using the surface thermal data provided by the moderate resolution imaging spectroradiometer (MODIS) sensors. An objective method is developed that allows to delineate the UHI. The study focuses on the months of July from the 2000–2006 time interval. The average surface temperatures obtained for each pixel (1 km resolution) were analyzed on cross-profiles that helped us to determine the outline of the UHI. The shifting points identified by the Rodionov test in the temperature series of each profile were considered as possible limits of the UHI. Seemingly, the land cover has a major influence on the extension and the geometry of the Bucharest UHI in July. The magnitude of the heat island was calculated by comparing the average temperature inside its limits and the average temperature of the 5 km (a) and of the 10 km (b) buffers around it. The thermal difference between the UHI and the surrounding area of Bucharest is higher and more variable during the daytime, and is noticeably related to the land cover.