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The Regional and the Seasonal Variability of Extreme Precipitation Trends in Pakistan
미안 사비르 후세인,이승호 한국기상학회 2013 Asia-Pacific Journal of Atmospheric Sciences Vol.49 No.4
The variability of spatial and temporal trends in extreme precipitation indices and the trend directions were studied for the meteorological seasons of 1950 to 2010. A daily precipitation dataset from 15 weather stations in Pakistan was used. Seven indices were chosen: total precipitation from events ≥ 90th, 95th, and 99th percentiles,the number of days with precipitation ≥ 90th, 95th, and 99th percentiles of daily precipitation amounts, and annual dry days. A study investigating temporal changes in the spatial extent of statistically significant extreme precipitation events was performed. Trends were calculated for each of the 30-year moving periods within the 1950-2010 time period using a simple linear regression technique and Kendall’s tau-based slope estimator. A distinct spatial differentiation appeared in the prevailing directional trends between the northern and southwestern parts of the study area. In all seasons, increasing trends in extreme precipitation dominated in northeastern Pakistan,whereas a reducing tendency towards extreme precipitation prevails in the southwestern part of the country.
Station based Profile of Extreme Rainfall Events in the Punjab Province of Pakistan during 1981-2014
Muhammad Nasar u Minallah,알리 시라지,미안 사비르 후세인 건국대학교 기후연구소 2018 기후연구 Vol.13 No.2
The changes in extreme daily rainfall totals in Punjab Province, Pakistan, during the period (1981-2014) are examined in this study. The analysis was focused on the extreme annual and monthly rainfall events, by processing the exceeding of the daily rainfall over various thresholds, which are indicators for the incidence of extreme rainfall events. To analyze the changes in extreme rainfall events and trends of the time series of the annual number of extreme rainfall days (%) the thresholds of 30mm and 50mm has been estimated. Evidence from the twelve stations considered shows that there is an increase in annual number of extreme rainfall days (%) in dataset. These changes of heavy and extreme rainfall events pronounce significant environmental consequences which cause considerable impact on society.