Tropical Cyclones (TCs) are among the atmospheric events which may trigger/enhance the occurrence of disasters to the society in most world basins including <span style="font-family:Verdana;">the </...Tropical Cyclones (TCs) are among the atmospheric events which may trigger/enhance the occurrence of disasters to the society in most world basins including <span style="font-family:Verdana;">the </span><span style="font-family:;" "=""><span style="font-family:Verdana;">Southwestern Indian Ocean (SWIO). This study analyzed the dynamics and the impacts of the Tropical Cyclone (TC) Idai (4</span><sup><span style="font-family:Verdana;">th</span></sup><span style="font-family:Verdana;">-21</span><sup><span style="font-family:Verdana;">st</span></sup><span style="font-family:Verdana;"> March, 2019) which devastated most of the SWIO countries. The study used the Reanalysis 1 products of daily zonal (u) and meridional (v) winds, Sea Surface Temperatures (SSTs), amount of Precipitable Water (PRW), </span></span><span style="font-family:Verdana;">and relative humidity</span><span style="font-family:Verdana;"> (Rh). The dynamics and movements of Idai w</span><span style="font-family:Verdana;">ere</span><span style="font-family:Verdana;"> analyzed using the wind circulation at 850, 700, 500 and 200 mb, where the TC dynamic variables like vertical wind shear, vorticity, and the mean zonal wind were calculated using u and v components. Using the open Grid Analysis and Display System (GrADS) software the data was processed into three</span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">time epochs of pre, during and post;and then analyzed to feature the state of the atmosphere before (pre), during and post TC Idai using all datasets. </span><span style="font-family:Verdana;">The </span><span style="font-family:;" "=""><span style="font-family:Verdana;">amount of precipitable water was used to map the rainfall on pre, during, and post Idai as well as during its landfall. The results revealed that dynamics of TC Idai was intensifying the weather (over Mozambique) and clearing the weather equatorward or southward of 12<span style="white-space:nowrap;">°</span>S, with low vertical wind shear over the landfall areas (</span><span style="white-space:nowrap;font-family:Verdana;">-</span><span style="font-family:Verdana;"></span><span style="font-family:Verdana;">3 to 3 m/s) and higher shear values (10 - 40 m/s) northward and southward of the Mozambican channel. Higher moisture content (80 - 90%) and higher PRW (40 - 60 mm/day) mapped during Idai over the lowland areas of Mozambique propagating westward. Higher low</span></span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">level vorticity values were also mapped over the landfall areas. More results revealed that countries laying equatorward of 12<span style="white-space:nowrap;">°</span>S</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> e.g.</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> the northern coastal areas of Kenya (Turkana and Baringo) and Tanzania, Idai disrupted the 2019 March to May (MAM) seasonal rainfall by inducing long dry spell which accelerated the famine over the northeastern Kenya (Turkana). Moreover, results revealed that the land falling of Idai triggered intensive flooding which affected </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">wide spectrum of socio</span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">economic livelihoods including significant loss of lives, injuries, loss of material wealth, infrastructure;indeed, people were forced to le</span><span style="font-family:Verdana;">ave</span><span style="font-family:Verdana;"> their houses for quite </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">longtime;water</span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">born</span><span style="font-family:Verdana;">e</span><span style="font-family:Verdana;"> diseases like malaria, cholera among others were experienced. Furthermore, results and reports revealed that </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">large amount of funds were raised to combat the impacts of Idai. For instance, USAID/OFDA used about $14,146,651 for human aid and treatment of flood</span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">prone diseases like Cholera in Mozambique ($13,296,651), Zimbabwe ($100,000), and Malawi ($280,000), respectively. Also a death toll of about 602 in Mozambique and 344 in Zimbabwe, and more than 2500 cases of injured people were reported</span><span style="font-family:Verdana;">.</span><span style="font-family:Verdana;"> Conclusively the study has shown that TCs including Idai and other are among the deadliest natural phenomenon which great affects the human and his environments, thus extensive studies on TCs frequency, strength, tracks as well </span><span style="font-family:Verdana;">as </span><span style="font-family:Verdana;">their coast benefit analysis should be conducted to reduce the societal impacts of these TCs.</span>展开更多
This study aimed at understanding the impacts of the seasonal hydroclimatic variables on maize yield and developing of statistical crop model for future maize yield prediction over Tanzania. The food security of the c...This study aimed at understanding the impacts of the seasonal hydroclimatic variables on maize yield and developing of statistical crop model for future maize yield prediction over Tanzania. The food security of the country is basically determined by availability of maize. Unfortunately, agriculture over the country is mainly rain fed hence highly endangered by the detrimental consequences of climate change and variability. Observed climate data was acquired from Tanzania Meteorological Authority (TMA) and Maize yield data from Food and Agriculture Organization (FAO). The study used the Mann-Kendall test and Sen’s slope for trend and magnitude detection in minimum, maximum temperature and rainfall at the 95% confidence level. The results have shown that rainfall is decreasing over the country and especially during the growing season but increasing during short rains season. Characteristics of seasonal climatic variables, cycle during growing period were linked to maize yield, and high (low) yield was reported during anomalous wet (dry) growing seasons. This portrays seasonal dependence of maize production. Statistical crop model was built by aggregating spatial regions that have statistically significant relation with maize yield. Results show that, 58.8% of yield variance is linked to seasonal hydroclimate variability. Rainfall emerged as the dominant predictor variable for maize yield since it accounts for 44.1% of yield variance. The modeled and observed yields exhibit statistically substantial relationship (r = 0.78) hence depicting high credence of the built statistical crop model. Also, the results revealed a decreasing trend in Maize yield with further Lessing trend is projected to proceed in the future. This calls for adaptation and implementation of appropriate regional measures to raise maize production in order to feed the burgeoning human population amidst climate change.展开更多
The spatio-temporal analysis of the performance of the March to May</span><span style="font-family:""> (MAM) <span>2020 rainfall and its societal implications to Northern Coastal Tanza...The spatio-temporal analysis of the performance of the March to May</span><span style="font-family:""> (MAM) <span>2020 rainfall and its societal implications to Northern Coastal Tanzania</span> (NCT) including Zanzibar was investigated. The uniqueness of the October to December, 2019 (OND) rainfall and the extension of the January to February, 2020 rainfall in Zanzibar which coincided with MAM 2020 rainfall was among the issues which prolonged MAM 2020 rainfall in NCT and Zanzibar. The National Center for Environmental Prediction (NCEP) in collaboration with National Center for Atmospheric Research (NCAR)</span><span style="font-family:"">.</span><span style="font-family:""> Reanalysis 1 datasets of <i>u</i> (zonal)</span><span style="font-family:""> </span><span style="font-family:"">and <i>v</i> (meridional)</span><span style="font-family:""> </span><span style="font-family:"">winds</span><span style="font-family:"">,</span><span style="font-family:""> sea surface temperatures anomalies, relative humidity, amount of precipitable water and ocean net flux were</span><span style="font-family:""><span style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-attachment:initial;background-origin:initial;background-clip:initial;"> </span></span><span style="background-color:;"></span><span style="font-family:""><span style="background:yellow;"></span><span>analyzed. Other datasets include the Tanzania Meteorological Authority (TMA) observed rainfall</span> records</span><span style="font-family:"">,</span><span style="font-family:""> maximum and minimum temperature</span><span style="font-family:"">s</span><span style="font-family:"">. Moreover, <span>TMA and Intergovernmental Climate Prediction and Analysis Cente</span>r (ICPAC)</span><span style="font-family:"">.</span><span style="font-family:""> MAM 2020 rainfall and temperature forecast reports were interpreted. Gridded and observed datasets were calculated into monthly and seasonal averages. As for observed data, long</span><span style="font-family:"">-</span><span style="font-family:"">term monthly and MAM percentage changes were calculated. Besides, </span><span style="font-family:"">the </span><span style="font-family:"">correlation between rainfall anomalies with an area</span><span style="font-family:"">-</span><span style="font-family:"">averaged SST<sub>A</sub> for defined regions and stations in Zanzibar w</span><span style="font-family:"">as</span><span style="font-family:""> performed. Lastly, the calculated monthly and seasonal rainfall was compared to MAM periods of 2016, 2017, 2018 and 2019. Results revealed that consecutive five MAM seasonal rainfall was among the highest ones in records with that of 2020 being exceptional. These MAM seasons had percentage contribution ranged from 68% - 212%, 150% - 304%, 22% - 163% and 57% - 170% for stations in Zanzibar and 130% - 230%, 57% - 168% and 230% - 706% for NCT station, respectively. Compared to previous MAM seasons of 2016-2019, MAM 2020 rainfall season was spatially well distributed in our study area with rainfall rang</span><span style="font-family:"">ing</span><span style="font-family:""> from 1200 to 2100 mm and up to 900 in most Zanzibar and NCT stations. Indeed, the study revealed that the observed highest rainfall and flooding was enhanced by wet seasons of MAM 2019, OND 2019 and DFJ (2019-2020). Other dynamics which accelerated MAM 2020 rainfall were the higher SST<sub>A</sub> ranged f<span>rom 0.5<span style="white-space:nowrap;">°</span>C - 1.5<span style="white-space:nowrap;">°</span>C and 1.5<span style="white-space:nowrap;">°</span>C - 2.5<span style="white-space:nowrap;">°</span>C over Southwestern Indian Ocean </span>(SWIO) and coastal Tanzania</span><span style="font-family:""> and</span><span style="font-family:""> the increased trend of area</span><span style="font-family:"">-</span><span style="font-family:"">averaged SST<sub>A</sub> on various SWIO blocks. </span><span style="font-family:"">Besides,</span><span style="font-family:""> parameters including Rhum, PWR and wind regimes were supporting the MAM 2020 rainfall. The socio-economic implications of these rains were strong and spatially well distributed in Zanzibar. For instance, a death toll of about 10 people, </span><span style="font-family:"">a </span><span style="font-family:"">great number of road culverts were washed away, </span><span style="font-family:"">and </span><span style="font-family:"">about 3600 houses </span><span style="font-family:"">were </span><span style="font-family:"">fallen or damaged, leading to </span><span style="font-family:"">a </span><span style="font-family:"">significant number of homeless people. As for NCT</span><span style="font-family:"">,</span><span style="font-family:""> the catastrophes include loss of lives</span><span style="font-family:"">,</span><span style="font-family:""> increased water levels over Lake <span>Victoria leading to flooded islands and re</span></span><span style="font-family:""> </span><span style="font-family:"">allocation of more than 1000 </span><span style="font-family:"">people. In Kenya</span><span style="font-family:"">,</span><span style="font-family:""> more than 116 people died and 40,000 people were displaced. Conclusively</span><span style="font-family:"">,</span><span style="font-family:""> the study has shown the unique<span>ness (<i>i</i>.<i>e</i>.</span></span><span style="font-family:"">,</span><span style="font-family:""> strength and societal implications) of MAM 2020 compared to </span><span style="font-family:"">other seasons;hence more studies on understanding the factors affecting extreme rainfall seasons in East Africa are required</span><span style="font-family:"">.展开更多
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...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<sub>max</sub> and T<sub>min</sub> 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<sub>max</sub> and T<sub>min</sub> 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<sub>max</sub> and T<sub>min</sub> for the HS, NF and FF, respectively. The results show that the observed T<sub>max</sub> increased by the rates of 0.035℃ yr<sup>-</sup><sup>1</sup> and 0.0169℃ yr<sup>-</sup><sup>1</sup>, while the T<sub>min</sub> was increased by a rate of 0.064℃ yr<sup>-</sup><sup>1</sup> and 0.104℃ yr<sup>-</sup><sup>1</sup> for Unguja and Pemba, respectively. The temporal distribution of wetness and dryness indices showed a climate shift from near normal to moderate wet during 2005 at Zanzibar Airport, while normal to moderately dry conditions, were observed in Pemba at Matangatuani. The decadal rainfall variability and distributions revealed higher rainfall intensity with an increasing trend and good spatial distribution in D3 from March to May (MAM) and October to December (OND). The projected results for T<sub>max</sub> during MAM and OND depicted higher values ranging from 1.7℃ - 1.8℃ to 1.9℃ - 2.0℃ and 1.5℃ to 2.0℃ in FF compared to NF under both RCPs. Also, higher T<sub>min</sub> values of 1.12℃ - 1.16℃ was projected in FF for MAM and OND under both RCPs. Besides, the rainfall projection generally revealed increased rainfall intensity in the range of 0 - 25 mm for Pemba and declined rainfall in the range of 25 - 50 mm in Unguja under both RCPs in perspectives of both NF and FF. Conclusively the study has shown that the undergoing climate change has posed a significant impact on both rainfall and temperature spatial and temporal distributions in Zanzibar (Unguja and Pemba), with Unguja being projected to have higher rainfall deficits while increasing rainfall strengths in Pemba. Thus, the study calls for more studies and formulation of effective adaptation, strategies and resilience mechanisms to combat the projected climate change impacts especially in the agricultural sector, water and food security.展开更多
文摘Tropical Cyclones (TCs) are among the atmospheric events which may trigger/enhance the occurrence of disasters to the society in most world basins including <span style="font-family:Verdana;">the </span><span style="font-family:;" "=""><span style="font-family:Verdana;">Southwestern Indian Ocean (SWIO). This study analyzed the dynamics and the impacts of the Tropical Cyclone (TC) Idai (4</span><sup><span style="font-family:Verdana;">th</span></sup><span style="font-family:Verdana;">-21</span><sup><span style="font-family:Verdana;">st</span></sup><span style="font-family:Verdana;"> March, 2019) which devastated most of the SWIO countries. The study used the Reanalysis 1 products of daily zonal (u) and meridional (v) winds, Sea Surface Temperatures (SSTs), amount of Precipitable Water (PRW), </span></span><span style="font-family:Verdana;">and relative humidity</span><span style="font-family:Verdana;"> (Rh). The dynamics and movements of Idai w</span><span style="font-family:Verdana;">ere</span><span style="font-family:Verdana;"> analyzed using the wind circulation at 850, 700, 500 and 200 mb, where the TC dynamic variables like vertical wind shear, vorticity, and the mean zonal wind were calculated using u and v components. Using the open Grid Analysis and Display System (GrADS) software the data was processed into three</span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">time epochs of pre, during and post;and then analyzed to feature the state of the atmosphere before (pre), during and post TC Idai using all datasets. </span><span style="font-family:Verdana;">The </span><span style="font-family:;" "=""><span style="font-family:Verdana;">amount of precipitable water was used to map the rainfall on pre, during, and post Idai as well as during its landfall. The results revealed that dynamics of TC Idai was intensifying the weather (over Mozambique) and clearing the weather equatorward or southward of 12<span style="white-space:nowrap;">°</span>S, with low vertical wind shear over the landfall areas (</span><span style="white-space:nowrap;font-family:Verdana;">-</span><span style="font-family:Verdana;"></span><span style="font-family:Verdana;">3 to 3 m/s) and higher shear values (10 - 40 m/s) northward and southward of the Mozambican channel. Higher moisture content (80 - 90%) and higher PRW (40 - 60 mm/day) mapped during Idai over the lowland areas of Mozambique propagating westward. Higher low</span></span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">level vorticity values were also mapped over the landfall areas. More results revealed that countries laying equatorward of 12<span style="white-space:nowrap;">°</span>S</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> e.g.</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> the northern coastal areas of Kenya (Turkana and Baringo) and Tanzania, Idai disrupted the 2019 March to May (MAM) seasonal rainfall by inducing long dry spell which accelerated the famine over the northeastern Kenya (Turkana). Moreover, results revealed that the land falling of Idai triggered intensive flooding which affected </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">wide spectrum of socio</span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">economic livelihoods including significant loss of lives, injuries, loss of material wealth, infrastructure;indeed, people were forced to le</span><span style="font-family:Verdana;">ave</span><span style="font-family:Verdana;"> their houses for quite </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">longtime;water</span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">born</span><span style="font-family:Verdana;">e</span><span style="font-family:Verdana;"> diseases like malaria, cholera among others were experienced. Furthermore, results and reports revealed that </span><span style="font-family:Verdana;">a </span><span style="font-family:Verdana;">large amount of funds were raised to combat the impacts of Idai. For instance, USAID/OFDA used about $14,146,651 for human aid and treatment of flood</span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;">prone diseases like Cholera in Mozambique ($13,296,651), Zimbabwe ($100,000), and Malawi ($280,000), respectively. Also a death toll of about 602 in Mozambique and 344 in Zimbabwe, and more than 2500 cases of injured people were reported</span><span style="font-family:Verdana;">.</span><span style="font-family:Verdana;"> Conclusively the study has shown that TCs including Idai and other are among the deadliest natural phenomenon which great affects the human and his environments, thus extensive studies on TCs frequency, strength, tracks as well </span><span style="font-family:Verdana;">as </span><span style="font-family:Verdana;">their coast benefit analysis should be conducted to reduce the societal impacts of these TCs.</span>
文摘This study aimed at understanding the impacts of the seasonal hydroclimatic variables on maize yield and developing of statistical crop model for future maize yield prediction over Tanzania. The food security of the country is basically determined by availability of maize. Unfortunately, agriculture over the country is mainly rain fed hence highly endangered by the detrimental consequences of climate change and variability. Observed climate data was acquired from Tanzania Meteorological Authority (TMA) and Maize yield data from Food and Agriculture Organization (FAO). The study used the Mann-Kendall test and Sen’s slope for trend and magnitude detection in minimum, maximum temperature and rainfall at the 95% confidence level. The results have shown that rainfall is decreasing over the country and especially during the growing season but increasing during short rains season. Characteristics of seasonal climatic variables, cycle during growing period were linked to maize yield, and high (low) yield was reported during anomalous wet (dry) growing seasons. This portrays seasonal dependence of maize production. Statistical crop model was built by aggregating spatial regions that have statistically significant relation with maize yield. Results show that, 58.8% of yield variance is linked to seasonal hydroclimate variability. Rainfall emerged as the dominant predictor variable for maize yield since it accounts for 44.1% of yield variance. The modeled and observed yields exhibit statistically substantial relationship (r = 0.78) hence depicting high credence of the built statistical crop model. Also, the results revealed a decreasing trend in Maize yield with further Lessing trend is projected to proceed in the future. This calls for adaptation and implementation of appropriate regional measures to raise maize production in order to feed the burgeoning human population amidst climate change.
文摘The spatio-temporal analysis of the performance of the March to May</span><span style="font-family:""> (MAM) <span>2020 rainfall and its societal implications to Northern Coastal Tanzania</span> (NCT) including Zanzibar was investigated. The uniqueness of the October to December, 2019 (OND) rainfall and the extension of the January to February, 2020 rainfall in Zanzibar which coincided with MAM 2020 rainfall was among the issues which prolonged MAM 2020 rainfall in NCT and Zanzibar. The National Center for Environmental Prediction (NCEP) in collaboration with National Center for Atmospheric Research (NCAR)</span><span style="font-family:"">.</span><span style="font-family:""> Reanalysis 1 datasets of <i>u</i> (zonal)</span><span style="font-family:""> </span><span style="font-family:"">and <i>v</i> (meridional)</span><span style="font-family:""> </span><span style="font-family:"">winds</span><span style="font-family:"">,</span><span style="font-family:""> sea surface temperatures anomalies, relative humidity, amount of precipitable water and ocean net flux were</span><span style="font-family:""><span style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-attachment:initial;background-origin:initial;background-clip:initial;"> </span></span><span style="background-color:;"></span><span style="font-family:""><span style="background:yellow;"></span><span>analyzed. Other datasets include the Tanzania Meteorological Authority (TMA) observed rainfall</span> records</span><span style="font-family:"">,</span><span style="font-family:""> maximum and minimum temperature</span><span style="font-family:"">s</span><span style="font-family:"">. Moreover, <span>TMA and Intergovernmental Climate Prediction and Analysis Cente</span>r (ICPAC)</span><span style="font-family:"">.</span><span style="font-family:""> MAM 2020 rainfall and temperature forecast reports were interpreted. Gridded and observed datasets were calculated into monthly and seasonal averages. As for observed data, long</span><span style="font-family:"">-</span><span style="font-family:"">term monthly and MAM percentage changes were calculated. Besides, </span><span style="font-family:"">the </span><span style="font-family:"">correlation between rainfall anomalies with an area</span><span style="font-family:"">-</span><span style="font-family:"">averaged SST<sub>A</sub> for defined regions and stations in Zanzibar w</span><span style="font-family:"">as</span><span style="font-family:""> performed. Lastly, the calculated monthly and seasonal rainfall was compared to MAM periods of 2016, 2017, 2018 and 2019. Results revealed that consecutive five MAM seasonal rainfall was among the highest ones in records with that of 2020 being exceptional. These MAM seasons had percentage contribution ranged from 68% - 212%, 150% - 304%, 22% - 163% and 57% - 170% for stations in Zanzibar and 130% - 230%, 57% - 168% and 230% - 706% for NCT station, respectively. Compared to previous MAM seasons of 2016-2019, MAM 2020 rainfall season was spatially well distributed in our study area with rainfall rang</span><span style="font-family:"">ing</span><span style="font-family:""> from 1200 to 2100 mm and up to 900 in most Zanzibar and NCT stations. Indeed, the study revealed that the observed highest rainfall and flooding was enhanced by wet seasons of MAM 2019, OND 2019 and DFJ (2019-2020). Other dynamics which accelerated MAM 2020 rainfall were the higher SST<sub>A</sub> ranged f<span>rom 0.5<span style="white-space:nowrap;">°</span>C - 1.5<span style="white-space:nowrap;">°</span>C and 1.5<span style="white-space:nowrap;">°</span>C - 2.5<span style="white-space:nowrap;">°</span>C over Southwestern Indian Ocean </span>(SWIO) and coastal Tanzania</span><span style="font-family:""> and</span><span style="font-family:""> the increased trend of area</span><span style="font-family:"">-</span><span style="font-family:"">averaged SST<sub>A</sub> on various SWIO blocks. </span><span style="font-family:"">Besides,</span><span style="font-family:""> parameters including Rhum, PWR and wind regimes were supporting the MAM 2020 rainfall. The socio-economic implications of these rains were strong and spatially well distributed in Zanzibar. For instance, a death toll of about 10 people, </span><span style="font-family:"">a </span><span style="font-family:"">great number of road culverts were washed away, </span><span style="font-family:"">and </span><span style="font-family:"">about 3600 houses </span><span style="font-family:"">were </span><span style="font-family:"">fallen or damaged, leading to </span><span style="font-family:"">a </span><span style="font-family:"">significant number of homeless people. As for NCT</span><span style="font-family:"">,</span><span style="font-family:""> the catastrophes include loss of lives</span><span style="font-family:"">,</span><span style="font-family:""> increased water levels over Lake <span>Victoria leading to flooded islands and re</span></span><span style="font-family:""> </span><span style="font-family:"">allocation of more than 1000 </span><span style="font-family:"">people. In Kenya</span><span style="font-family:"">,</span><span style="font-family:""> more than 116 people died and 40,000 people were displaced. Conclusively</span><span style="font-family:"">,</span><span style="font-family:""> the study has shown the unique<span>ness (<i>i</i>.<i>e</i>.</span></span><span style="font-family:"">,</span><span style="font-family:""> strength and societal implications) of MAM 2020 compared to </span><span style="font-family:"">other seasons;hence more studies on understanding the factors affecting extreme rainfall seasons in East Africa are required</span><span style="font-family:"">.
文摘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<sub>max</sub> and T<sub>min</sub> 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<sub>max</sub> and T<sub>min</sub> 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<sub>max</sub> and T<sub>min</sub> for the HS, NF and FF, respectively. The results show that the observed T<sub>max</sub> increased by the rates of 0.035℃ yr<sup>-</sup><sup>1</sup> and 0.0169℃ yr<sup>-</sup><sup>1</sup>, while the T<sub>min</sub> was increased by a rate of 0.064℃ yr<sup>-</sup><sup>1</sup> and 0.104℃ yr<sup>-</sup><sup>1</sup> for Unguja and Pemba, respectively. The temporal distribution of wetness and dryness indices showed a climate shift from near normal to moderate wet during 2005 at Zanzibar Airport, while normal to moderately dry conditions, were observed in Pemba at Matangatuani. The decadal rainfall variability and distributions revealed higher rainfall intensity with an increasing trend and good spatial distribution in D3 from March to May (MAM) and October to December (OND). The projected results for T<sub>max</sub> during MAM and OND depicted higher values ranging from 1.7℃ - 1.8℃ to 1.9℃ - 2.0℃ and 1.5℃ to 2.0℃ in FF compared to NF under both RCPs. Also, higher T<sub>min</sub> values of 1.12℃ - 1.16℃ was projected in FF for MAM and OND under both RCPs. Besides, the rainfall projection generally revealed increased rainfall intensity in the range of 0 - 25 mm for Pemba and declined rainfall in the range of 25 - 50 mm in Unguja under both RCPs in perspectives of both NF and FF. Conclusively the study has shown that the undergoing climate change has posed a significant impact on both rainfall and temperature spatial and temporal distributions in Zanzibar (Unguja and Pemba), with Unguja being projected to have higher rainfall deficits while increasing rainfall strengths in Pemba. Thus, the study calls for more studies and formulation of effective adaptation, strategies and resilience mechanisms to combat the projected climate change impacts especially in the agricultural sector, water and food security.