The Influence of Climate Change and Variability on Spatio-Temporal Rainfall and Temperature Distribution in Zanzibar  

作　　者：Abdalla Hassan Abdalla Kombo Hamad Kai Sara Abdalla Khamis Afredy Lawrence Kondowe Sarah E. Osima Philemon Henry King’uza Asya Omar Hamad Abdalla Hassan Abdalla;Kombo Hamad Kai;Sara Abdalla Khamis;Afredy Lawrence Kondowe;Sarah E. Osima;Philemon Henry King’uza;Asya Omar Hamad(Tanzania Meteorological Authority (TMA), Zanzibar, Tanzania;Faculty of Science, State University of Zanzibar (SUZA), Zanzibar, Tanzania)

机构地区：[1]Tanzania Meteorological Authority (TMA), Zanzibar, Tanzania [2]Faculty of Science, State University of Zanzibar (SUZA), Zanzibar, Tanzania

出　　处：《Atmospheric and Climate Sciences》2023年第2期282-313,共32页大气和气候科学（英文）

摘　　要：Climate change has resulted in serious social-economic ramifications and extremely catastrophic weather events in the world, Tanzania and Zanzibar in particular, with adaptation being the only option to reduce impacts. The study focuses on the influence of climate change and variability on spatio-temporal rainfall and temperature variability and distribution in Zanzibar. The station observation datasets of rainfall, T_max and T_min acquired from Tanzania Meteorological Authority (TMA) and the Coordinated Regional Climate Downscaling Experiment program (CORDEX) projected datasets from the Regional climate model HIRHAM5 under driving model ICHEC-EC-EARH, for the three periods of 1991-2020 used as baseline (HS), 2021-2050 as near future (NF) and 2051-2080 far future (FF), under two representative concentration pathways (RCP) of 4.5 and 8.5, were used. The long-term observed T_max and T_min were used to produce time series for observing the nature and trends, while the observed rainfall data was used for understanding wet and dry periods, trends and slope (at p ≤ 0.05) using the Standardized Precipitation Index (SPI) and the Mann Kendall test (MK). Moreover, the Quantum Geographic Information System (QGIS) under the Inverse Distance Weighting (IDW) interpolation techniques were used for mapping the three decades of 1991-2000 (hereafter D1), 2001-2010 (hereafter D2) and 2011-2020 (hereafter D3) to analyze periodical spatial rainfall distribution in Zanzibar. As for the projected datasets the Climate Data Operator Commands (CDO), python scripts and Grid analysis and Display System (GrADS) soft-wares were used to process and display the results of the projected datasets of rainfall, T_max and T_min for the HS, NF and FF, respectively. The results show that the observed T_max increased by the rates of 0.035℃ yr^-¹ and 0.0169℃ yr^-¹, while the T_min was increased by a rate of 0.064℃ yr<sup>-</sClimate change has resulted in serious social-economic ramifications and extremely catastrophic weather events in the world, Tanzania and Zanzibar in particular, with adaptation being the only option to reduce impacts. The study focuses on the influence of climate change and variability on spatio-temporal rainfall and temperature variability and distribution in Zanzibar. The station observation datasets of rainfall, T_max and T_min acquired from Tanzania Meteorological Authority (TMA) and the Coordinated Regional Climate Downscaling Experiment program (CORDEX) projected datasets from the Regional climate model HIRHAM5 under driving model ICHEC-EC-EARH, for the three periods of 1991-2020 used as baseline (HS), 2021-2050 as near future (NF) and 2051-2080 far future (FF), under two representative concentration pathways (RCP) of 4.5 and 8.5, were used. The long-term observed T_max and T_min were used to produce time series for observing the nature and trends, while the observed rainfall data was used for understanding wet and dry periods, trends and slope (at p ≤ 0.05) using the Standardized Precipitation Index (SPI) and the Mann Kendall test (MK). Moreover, the Quantum Geographic Information System (QGIS) under the Inverse Distance Weighting (IDW) interpolation techniques were used for mapping the three decades of 1991-2000 (hereafter D1), 2001-2010 (hereafter D2) and 2011-2020 (hereafter D3) to analyze periodical spatial rainfall distribution in Zanzibar. As for the projected datasets the Climate Data Operator Commands (CDO), python scripts and Grid analysis and Display System (GrADS) soft-wares were used to process and display the results of the projected datasets of rainfall, T_max and T_min for the HS, NF and FF, respectively. The results show that the observed T_max increased by the rates of 0.035℃ yr^-¹ and 0.0169℃ yr^-¹, while the T_min was increased by a rate of 0.064℃ yr<sup>-</s

关 键 词：Climate Change Climate Variability Spatial and Temporal Distribution Temperature RAINFALL CORDEX 

分 类 号：P46[天文地球—大气科学及气象学]