Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2017.05.002 |
Comparison of future and base precipitation anomalies by SimCLIM statistical projection through ensemble approach in Pakistan | |
Amin, Asad1; Nasim, Wajid1,2,3; Mubeen, Muhammad1; Kazmi, Dildar Hussain4; Lin, Zhaohui5; Wahid, Abdul6; Sultana, Syeda Refat1; Gibbs, Jim7; Fahad, Shah8 | |
2017-09-15 | |
发表期刊 | ATMOSPHERIC RESEARCH
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ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2017 |
卷号 | 194 |
文章类型 | Article |
语种 | 英语 |
国家 | Pakistan; France; Australia; Peoples R China; New Zealand |
英文摘要 | Unpredictable precipitation trends have largely influenced by climate change which prolonged droughts or floods in South Asia. Statistical analysis of monthly, seasonal, and annual precipitation trend carried out for different temporal (1996-2015 and 2041-2060) and spatial scale (39 meteorological stations) in Pakistan. Statistical downscaling model (SimCLIM) was used for future precipitation projection (2041-2060) and analyzed by statistical approach. Ensemble approach combined with representative concentration pathways (RCPs) at medium level used for future projections. The magnitude and slop of trends were derived by applying Mann-Kendal and Sen's slop statistical approaches. Geo-statistical application used to generate precipitation trend maps. Comparison of base and projected precipitation by statistical analysis represented by maps and graphical visualization which facilitate to detect trends. Results of this study projects that precipitation trend was increasing more than 70% of weather stations for February, March, April, August, and September represented as base years. Precipitation trend was decreased in February to April but increase in July to October in projected years. Highest decreasing trend was reported in January for base years which was also decreased in projected years. Greater variation in precipitation trends for projected and base years was reported in February to April. Variations in projected precipitation trend for Punjab and Baluchistan highly accredited in March and April. Seasonal analysis shows large variation in winter, which shows increasing trend for more than 30% of weather stations and this increased trend approaches 40% for projected precipitation. High risk was reported in base year pre-monsoon season where 90% of weather station shows increasing trend but in projected years this trend decreased up to 33%. Finally, the annual precipitation trend has increased for more than 90% of meteorological stations in base (1996-2015) which has decreased for projected year (2041-2060) up to 76%. These result revealed that overall precipitation trend is decreasing in future year which may prolonged the drought in 14% of weather stations under study. |
英文关键词 | GCM Climate change Mann-Kendall Future projections RCPs Sen' s slop Meteorological stations |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000405043700018 |
WOS关键词 | INDUS RIVER-BASIN ; SEASONAL PRECIPITATION ; SUNFLOWER HYBRIDS ; SUMMER RAINFALL ; TEMPERATURE ; CLIMATE ; TRENDS ; PUNJAB ; MODEL ; SURFACE |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/38065 |
专题 | 地球科学 |
作者单位 | 1.CIIT Ctr Hlth Res, Dept Environm Sci, Vehari 61100, Pakistan; 2.CIHEAM Inst Agron Mediterraneen Montpellier IAMM, 3191 Route Mende, F-34090 Montpellier, France; 3.Natl Agr Res Flagship, CSIRO Sustainable Ecosyst, Toowoomba, Qld 4350, Australia; 4.Pakistan Meteorol Dept, Natl Agromet Ctr, Islamabad, Pakistan; 5.Chinese Acad Sci, Inst Atmospher Phys, Int Ctr Climate & Environm Sci, Beijing, Peoples R China; 6.Bahauddin Zakariya Univ, Dept Environm Sci, Multan, Pakistan; 7.Lincoln Univ, Dept Anim Sci, Livestock Hlth & Prod, Lincoln 7647, Christchurch 85084, New Zealand; 8.Huazhong Agr Univ, Coll Plant Sci & Technol, Wuhan, Hubei, Peoples R China |
推荐引用方式 GB/T 7714 | Amin, Asad,Nasim, Wajid,Mubeen, Muhammad,et al. Comparison of future and base precipitation anomalies by SimCLIM statistical projection through ensemble approach in Pakistan[J]. ATMOSPHERIC RESEARCH,2017,194. |
APA | Amin, Asad.,Nasim, Wajid.,Mubeen, Muhammad.,Kazmi, Dildar Hussain.,Lin, Zhaohui.,...&Fahad, Shah.(2017).Comparison of future and base precipitation anomalies by SimCLIM statistical projection through ensemble approach in Pakistan.ATMOSPHERIC RESEARCH,194. |
MLA | Amin, Asad,et al."Comparison of future and base precipitation anomalies by SimCLIM statistical projection through ensemble approach in Pakistan".ATMOSPHERIC RESEARCH 194(2017). |
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