Use of RegCM gridded dataset for thunderstorm favorable conditions analysis over Poland—climatological approach
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- 作者：Ewelina Walawender ; Rafał Kielar ; Zbigniew Ustrnul
- 刊名：Theoretical and Applied Climatology
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：127
- 期：1-2
- 页码：229-240
- 全文大小：4496KB
- 刊物类别：Earth and Environmental Science
- 刊物主题：Atmospheric Sciences; Climatology; Atmospheric Protection/Air Quality Control/Air Pollution; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution;
- 出版者：Springer Vienna
- ISSN：1434-4483
- 卷排序：127
文摘
The paper analyzes equivalent data for a low density meteorological station network (spatially discontinuous data) and poor temporal homogeneity of thunderstorm observational data. Due to that, a Regional Climate Model (RegCM) dataset was tested. The Most Unstable Convective Available Potential Energy index value (MUCAPE) above the 200 J kg−1 threshold was selected as a predictor describing favorable conditions for the occurrence of thunderstorms. The quality of the dataset was examined through a comparison between model results and soundings from several aerological stations in Central Europe. Good, statistically significant (0.05 significance level) results were obtained through correlation analysis; the value of Pearson’s correlation coefficient was above 0.8 in every single case. Then, using methods associated with gridded climatology, data series for 44 weather stations were derived and an analysis of correlation between RegCM modeled data and in situ thunderstorm observations was conducted with coefficients in the range of 0.75–0.90. The possibility of employing the dataset in thunderstorm climatology analysis was checked via a few examples by mapping monthly, seasonal, and annual means. Moreover, long-term variability and trend analysis along with modeled MUCAPE data were tested. As a result, the RegCM modeled MUCAPE gridded dataset was proposed as an easily available, suitable, and valuable predictor for thunderstorm climatology analysis and mapping. Finally, some limitations are discussed and recommendations for further improvements are given.