The assessment of the performance of the October to December (OND), 2019 rainfall season in Zanzibar (Unguja and Pemba) with reference to local downscaled Tanzania Meteorological Authority (TMA) forecast, and regional...The assessment of the performance of the October to December (OND), 2019 rainfall season in Zanzibar (Unguja and Pemba) with reference to local downscaled Tanzania Meteorological Authority (TMA) forecast, and regional (Intergovernmental Authority on Development Climate Prediction and Application Center (IGAD-ICPAC) weather forecasts were assessed by comparing the long term average of OND rainfall data and previous OND rainfall seasons of 2016, 2017 and 2018 as well as extreme positive Indian Ocean Dipole (IOD) during OND seasons of 1961, 1994, 1997, 2006 and 2019 for Zanzibar. The study assessed zonal (u) and meridional (v) winds at 850 and 200 mb, monthly and dekadal sea surface temperature (SST);the Madden Julien Oscillations (MJO) forecast reports and the ocean heat content data. Both gridded and observed datasets were processed into dekadal, monthly and seasonal averages and then analysed. The results revealed that, based on the observations, above normal rainfall of 936 and 908 mm were reported at stations of Kisauni (Unguja) and Karume airport (Pemba) during 2019 OND season. This amount was the first and second ever recorded for the extreme positive IOD during OND seasons of 1961, 1994, 1997, 2006 and 2019, and also the first for the previous higher OND rainfall seasons of 2016, 2017 and 2018 which was highly variable. Moreover, these values were second ever-recorded highest OND rainfall since 1916 to 2019 where the first one was observed in 1961. Furthermore, the results revealed that 2019 OND seasonal rainfall had the highest amount of contribution based on historical climatology. For instance, the 2019 OND rainfall for Kisauni, Pemba airport and Matangatuani contributed to 198%, 303% and 231% of the long term (1987-2016) mean OND rainfall in Zanzibar. Indeed, the results show that the presence of the MJO during OND and the enhanced positive IOD was among the causes for the observed wetness of the 2019 OND in Zanzibar and most parts of the country. Moreover, the dominant easterly, southeasterly and northwesterly onshore winds during 2019 OND also contributed to heavy rainfall. The monthly rainfall variability among stations had the highest amount of rainfall which ranges from 400 to 500 mm which was observed during October in Kisauni and Karume airport, while the lowest amount ranging from 150 to 180 mm was observed during November in Matangatuani and the surrounding stations. Based on the comparison of the forecasted reports issued by ICPAC and TMA, the results revealed that irrespective of not considering the likelihood of occurrence of MJO and strong positive IOD both forecasts has performed well with that of ICPAC being leading. Conclusively, since the 2019 OND season has been uniquely characterized by the presence of MJO and IOD polarities it would be worthful to consider the two as input parameters during the OND rainfall forecast over the region.展开更多
The study investigated the impacts of tropical cyclone (TC) Fantala (11<sup>th</sup> to 27<sup>th</sup> April, 2016) to the coastal areas of Tanzania, Zanzibar in particular. Daily reanalysis d...The study investigated the impacts of tropical cyclone (TC) Fantala (11<sup>th</sup> to 27<sup>th</sup> April, 2016) to the coastal areas of Tanzania, Zanzibar in particular. Daily reanalysis data consisting of wind speed, sea level pressure (SLP), sea surface temperatures (SSTs) anomaly, and relative humidity from the National Centres for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) were used to analyze the variation in strength of Fantala as it was approaching the Tanzania coastal line. In addition observed rainfall from Tanzania Meteorological Authority (TMA) at Zanzibar office, Global Forecasting System (GFS) rainfall estimates and satellite images were used to visualize the impacts of tropical cyclone Fantala to Zanzibar. The results revealed that, TC Fantala was associated with deepening/decreasing in SLP (from 1012 - 1010 mb) around the north-western Madagascar and coastal Tanzania, whereas the mean SSTs was greater than 28<span style="white-space:nowrap;">°</span>C and an SSTs anomaly ranged from 0 to 2.3<span style="white-space:nowrap;">°</span>C. The vertical wind shear which ridged at Mozambican Channel and over north-eastern Madagascar was high enough (12 - 15 ms<sup>-1</sup>) to support the intensifying of Fantala. The thermodynamic and dynamic conditions of Fantala influenced heavy rainfall of greater than 170 mm over most stations in Zanzibar. Moreover, Fantala disrupted the temporal variability of 2016 March to May (MAM) seasonal rainfall. Besides, more than 420 people were homeless, at least 3330 houses were destroyed, and about 2 people died. As for mainland Tanzania Fantala resulted in a death of 12 people in Kilimanjaro and Arusha, more than 315 houses were washed away by flooding leading to 13,933 people being homeless. Conclusively the study calls for an extensive research work based on examining and forecasting the TCs rainfall impacts and their contribution during the two rainfall seasons of OND and MAM in Tanzania.展开更多
This article examines the off season rainfall in northern coast Tanzania(NCT)including Zanzibar which occurred in January and February 2020(JF).Like the JF rainfalls of 2001,2004,2010,2016 and 2018,the JF(2020)rainfal...This article examines the off season rainfall in northern coast Tanzania(NCT)including Zanzibar which occurred in January and February 2020(JF).Like the JF rainfalls of 2001,2004,2010,2016 and 2018,the JF(2020)rainfall was more unique in damages including loss of lives,properties and infrastructures.The study used the NCEP/NCAR reanalysis data to examine the cause of uniqueness of JF rainfall in 2001,2004,2010,2016,2018 and 2020 over NCT and Zanzibar.These datasets include monthly mean u,v wind at 850,700,500,and 200 mb;SSTs,mean sea level pressure(MSLP)anomalies,Dipole Mode Index(DMI),and monthly rainfall from NCT and Zanzibar stations.Datasets were processed and calculated into long term,seasonal,and monthly averages,indeed,Precipitation Index(PI)was calculated.Correlation analysis between the rainfall(December to January),SST,DMI and 850 mb wind vectors;and long-term percentage contribution of investigated parameters was calculated.Results revealed significant positive and negative correlations between JF rainfall,SSTs and DMI.Moreover,JFs of 2004 and 2016 had higher rainfalls of 443 mm with percentage contribution of up to 406%,while January and February,2020 had the highest of 269.1 and 101.1mm in Zanzibar and 295 and 146.1 mm over and NCT areas,with highest January long-term rainfall contribution of 356%in Zanzibar and 526%over NCT.The DJF(2019/20)had the highest rainfall record of 649.5 mm in Zanzibar contributing up to 286%,while JF 2000 rainfall had a good spatial and temporal distribution over most NCT areas.JF,2020 rainfall had impacts of more than 20 people died in Lindi and several infrastructures including Kiyegeya Bridge in Morogoro were damaged.Conclusively,more research works on understanding the dynamics of wet and dry JF seasons should be conducted.展开更多
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
Surface ozone is among the greenhouse gases which form a blanket that causes the heat trapping effect and warms the atmosphere with related consequences such as atmospheric temperature rise. The aim of this study is t...Surface ozone is among the greenhouse gases which form a blanket that causes the heat trapping effect and warms the atmosphere with related consequences such as atmospheric temperature rise. The aim of this study is to investigate the temporal relationship between the meteorological conditions and the surface ozone concentrations.In this study surface ozone and meteorological measurements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
Climate change and variability, has embarked societies in Zanzibar to rely on horticulture (i.e. watermelon production) as an adaptive measure due to an unpromising situation of commonly used agricultural yields. Curr...Climate change and variability, has embarked societies in Zanzibar to rely on horticulture (i.e. watermelon production) as an adaptive measure due to an unpromising situation of commonly used agricultural yields. Currently, there is either no or scant information that describes the influence of climate changes and variability to watermelon production in Zanzibar. Thus, this study aimed to determine the influence of climate variability on the quantity of watermelon production in Zanzibar. The study used both primary and secondary datasets, which include the anecdotal information collected from interviewers’ responses from four districts of Unguja and Pemba, and climate parameters (rainfall, maximum and minimum temperature (Tmax and Tmin) acquired from Tanzania Meteorological Authority (TMA) at Zanzibar offices. Pearson correlation was used for analyzing the association between watermelon production and climate parameters, while paired t-test was applied to show the significance of the mean differences of watermelon and climate parameters for two periods of 2014-2017 and 2018-2021, respectively. Percentage changes were used to feature the extent to which the two investigated parameters affect each other. The anecdotal responses were sorted, calculated in monthly and seasonal averages, plotted and then analyzed. Results have shown a strong correlation (r = 0.8 at p ≤ 0.02, and r = 0.7) between watermelon production, Tmax and rainfall during OND, especially in Unguja, as well as Tmin during JJA (i.e. r = - 0.8 at p ≤ 0.02) in Pemba. Besides, results have shown the existence of significant differences between the means of watermelon production and climate parameter for the two stated periods, indicating that the climate parameters highly affects the watermelon production by either enhancing or declining the yields by 69% - 162% and 17% - 77%, respectively. Moreover, results have shown that respondents were aware that excess temperature intensity during dry periods can lead to high production costs due number of soil and other environmental factors. Besides the results have shown that OND seasonal rainfall and MAM Tmax had good association with watermelon production in Unguja while JJA Tmin declined the production in Pemba. Thus, the study concludes that seasonal variability of climate parameter has a significant influence on the watermelon production. The study calls for more studies on factors affecting watermelon production (e.g. soil characteristics, pest sides and manure), and recommends for climate based decision making on rain fed agricultural yields and routine monitoring of weather information.展开更多
Tropical cyclones (TCs) and storms (TSs) are among the devastating events in the world and southwestern Indian Ocean (SWIO) in particular. The seasonal forecasting TCs and TSs for December to March (DJFM) and November...Tropical cyclones (TCs) and storms (TSs) are among the devastating events in the world and southwestern Indian Ocean (SWIO) in particular. The seasonal forecasting TCs and TSs for December to March (DJFM) and November to May (NM) over SWIO were conducted. Dynamic parameters including vertical wind shear, mean zonal steering wind and vorticity at 850 mb were derived from NOAA (NCEP-NCAR) reanalysis 1 wind fields. Thermodynamic parameters including monthly and daily mean Sea Surface Temperature (SST), Outgoing Longwave Radiation (OLR) and equatorial Standard Oscillation Index (SOI) were used. Three types of Poison regression models (i.e. dynamic, thermodynamic and combined models) were developed and validated using the Leave One Out Cross Validation (LOOCV). Moreover, 2 × 2 square matrix contingency tables for model verification were used. The results revealed that, the observed and cross validated DJFM and NM TCs and TSs strongly correlated with each other (p ≤ 0.02) for all model types, with correlations (r) ranging from 0.62 - 0.86 for TCs and 0.52 - 0.87 for TSs, indicating great association between these variables. Assessment of the model skill for all model types of DJFM and NM TCs and TSs frequency revealed high skill scores ranging from 38% - 70% for TCs and 26% - 72% for TSs frequency, respectively. Moreover, results indicated that the dynamic and combined models had higher skill scores than the thermodynamic models. The DJFM and NM selected predictors explained the TCs and TSs variability by the range of 0.45 - 0.65 and 0.37 - 0.66, respectively. However, verification analysis revealed that all models were adequate for predicting the seasonal TCs and TSs, with high bias values ranging from 0.85 - 0.94. Conclusively, the study calls for more studies in TCs and TSs frequency and strengths for enhancing the performance of the March to May (MAM) and December to October (OND) seasonal rainfalls in the East African (EA) and Tanzania in particular.展开更多
The marine accidents are among the main components of the Zanzibar Disaster Management Policy (2011) and the Zanzibar Blue Economy Policy (2020). These policies aimed to institute legal frame works and procedures for ...The marine accidents are among the main components of the Zanzibar Disaster Management Policy (2011) and the Zanzibar Blue Economy Policy (2020). These policies aimed to institute legal frame works and procedures for reducing both the frequency of marine accidents and their associated fatalities. These fatalities include deaths, permanent disabilities and loss of properties which may result into increased poverty levels as per the sustainable development goal one (SDG1) which stipulates on ending the poverty in all its forms everywhere. Thus, in the way to support these Government efforts, the influence of climate and weather on marine accidents along Zanzibar and Pemba Channels was investigated. The study used the 10 years (2013-2022) records of daily rainfall and hourly wind speed acquired from Tanzania Meteorological Authority (TMA) (for the observation stations of Zanzibar, Pemba, Dares Salaam and Tanga), and the significant wave heights data, which was freely downloaded from Globally Forecasting System (GFS-World model of 13 km resolution). The marine accident records were collected from TASAC and Zanzibar Maritime Authority (ZMA), and the anecdotal information was collected from heads of quay and boat captains in different areas of Zanzibar. The Mann Kendal test, was used to determine the slopes and trends direction of used weather parameters, while the Pearson correlations analysis and t-tests were used to understand the significance of the underlying relationship between the weather and marine accidents. The paired t-test was used to evaluate the extent to which weather parameters affect the marine accidents. Results revealed that the variability of extreme weather events (rainfall, ocean waves and wind speed) was seen to be among the key factors for most of the recorded marine accidents. For instance, in Pemba high rainfall showed an increasing trend of extreme rainfall events, while Zanzibar has shown a decreasing trend of these events. As for extreme wind events, results show that Dar es Salaam and Tanga had an increasing trend, while Zanzibar and Pemba had shown a decreasing trend. As for the monthly variability of frequencies of extreme rainfall events, March to May (MAM) season was shown to have the highest frequencies over all stations with the peaks at Zanzibar and Pemba. On the other hand, high frequency of extreme wind speed was observed from May to September with peaks in June to July, and the highest strength was observed during 09:00 to 15:00 GMT. Moreover, results revealed an increasing trend of marine accidents caused by bad weather except during November. Also, results showed that bad weather conditions contributed to 48 (32%) of all 150 recorded accidents. Further results revealed significant correlation between the extreme wind and marine accidents, with the highest strong correlation of r = 0.71 (at p ≤ 0.007) and r = 0.75 (at p ≤ 0.009) at Tanga and Pemba, indicating the occurrence of more marine accidents at the Pemba channel. Indeed, strong correlation of r = 0.6 between extreme rainfall events and marine accidents was shown in Pemba, while the correlations between extremely significant wave heights and marine accidents were r = 0.41 (at p ≤ 0.006) and r = 0.34 (p ≤ 0.0006) for Pemba and Zanzibar Channel, respectively. In conclusion, the study has shown high influence between marine accidents and bad weather events with more impacts in Pemba and Zanzibar. Thus, the study calls for more work to be undertaken to raise the awareness on marine accidents as a way to alleviate the poverty and enhance the sustainable blue economy.展开更多
Climate change and variability have been inducing a broad spectrum of impacts on the environment and natural resources including groundwater resources. The study aimed at assessing the influence of weather, climate va...Climate change and variability have been inducing a broad spectrum of impacts on the environment and natural resources including groundwater resources. The study aimed at assessing the influence of weather, climate variability, and changes on the quality of groundwater resources in Zanzibar. The study used the climate datasets including rainfall (RF), Maximum and Minimum Temperature (T<sub>max</sub> and T<sub>min</sub>), the records acquired from Tanzania Meteorological Authority (TMA) Zanzibar office for 30 (1989-2019) and 10 (2010-2019) years periods. Also, the Zanzibar Water Authority (ZAWA) monthly records of Total Dissolved Solids (TDS), Electrical Conductivity (EC), and Ground Water Temperature (GWT) were used. Interpolation techniques were used for controlling outliers and missing datasets. Indeed, correlation, trend, and time series analyses were used to show the relationship between climate and water quality parameters. However, simple statistical analyses including mean, percentage changes, and contributions to the annual and seasonal mean were calculated. Moreover, t and paired t-tests were used to show the significant changes in the mean of the variables for two defined periods of 2011-2015 and 2016-2020 at p ≤ 0.05. Results revealed that seasonal variability of groundwater quality from March to May (MAM) has shown a significant change in trends ranging from 0.1 to 2.8 mm/L/yr, 0.1 to 2.8 μS/cm/yr, and 0.1 to 2.0℃/yr for TDS, EC, and GWT, respectively. The changes in climate parameters were 0.1 to 2.4 mm/yr, 0.2 to 1.3℃/yr and 0.1 to 2.5℃/yr in RF, T<sub>max</sub>, and T<sub>min</sub>, respectively. From October to December (OND) changes in groundwater parameters ranged from 0.2 to 2.5 mm/L/yr 0.1 to 2.9 μS/cm/yr, and 0.1 to 2.1℃/yr for TDS, EC, and GWT, whereas RF, T<sub>max</sub>, and T<sub>min</sub> changed from 0.3 to 1.8 mm/yr, 0.2 to 1.9℃/yr and 0.2 to 2.0℃/yr, respectively. Moreover, the study has shown strong correlations between climate and water quality parameters in MAM and OND. Besides, the paired correlation has shown significant changes in all parameters except the rainfall. Conclusively, the study has shown a strong influence of climate variability on the quality of groundwater in Zanzibar, and calls for more studies to extrapolate these results throughout Tanzania.展开更多
The inter-annual variability of rainfall onset and crop replanting in East Africa (EA) was assessed using daily estimated rainfall data from climate hazard group infrared precipitation (CHIRPS Ver2.0) and monthly Sea ...The inter-annual variability of rainfall onset and crop replanting in East Africa (EA) was assessed using daily estimated rainfall data from climate hazard group infrared precipitation (CHIRPS Ver2.0) and monthly Sea Surface Temperature (SST) indices [Indian Ocean Dipole (IOD) and El-Ni?o Southern Oscillation (ENSO) at NINO3.4 region] from the National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). The data covered a period of 40 years from1981 to 2020. The methods of cumulative of daily mean rainfall, percentage of onset date departure (PODD), Mann-Kendall (MK) trend test, student t-test, and correlation were applied in the analysis. The results showed that early onset with dry spell (WDS) consideration frequently occurs in Uganda between the first and second dekads of September, while late rainfall onset WDS occurs in the first and second dekads of December over central and Northern Kenya as well as in the Northeastern highlands, parts of the northern coast and unimodal regions in Tanzania. Rainfall onset with no dry spell (WnDS) portrayed an average of 10 days before the occurrence of true onset WDS, with maximum onset departure days (ODD) above 30 days across the Rift Valley area in Kenya and the Northeastern highlands in Tanzania. The high chance of minimum ODD is seen over entire Uganda and the area around Lake Victoria. However, few regions, such as Nakuru (Kenya) Gulu and Kibale (Uganda), and Gitega (Burundi), revealed a slight positive linear trend while others showed negative trend. Significant positive patterns for correlation between onset WDS and SST indices (IOD and NINO 3.4) were discovered in Northern and Northeastern Kenya, as well as areas along the Indian Ocean (over Tanzania’s Northern Coast). Inter-annual relationship between onset dates WDS and IOD (NINO3.4) indices exhibits a high correlation coefficient r = 0.23 (r = 0.48) in Uganda and r = 0.44 (r = 0.36) in Kenya. On the other hand, a negative correlation was revealed over Burundi and Tanzania (over a unimodal region). A high percentage of PODD was observed, ranging from 40% to 70% over the Rift Valley in Kenya and at the Northeastern highlands in Tanzania. However, a strong PODD above 70% was observed over Tanga and the Northern Pwani Region in Tanzania. These findings will help farmers to understand the appropriate time for crop planting, as well as help other socio-economic activities that strongly depend on rainfall.展开更多
文摘The assessment of the performance of the October to December (OND), 2019 rainfall season in Zanzibar (Unguja and Pemba) with reference to local downscaled Tanzania Meteorological Authority (TMA) forecast, and regional (Intergovernmental Authority on Development Climate Prediction and Application Center (IGAD-ICPAC) weather forecasts were assessed by comparing the long term average of OND rainfall data and previous OND rainfall seasons of 2016, 2017 and 2018 as well as extreme positive Indian Ocean Dipole (IOD) during OND seasons of 1961, 1994, 1997, 2006 and 2019 for Zanzibar. The study assessed zonal (u) and meridional (v) winds at 850 and 200 mb, monthly and dekadal sea surface temperature (SST);the Madden Julien Oscillations (MJO) forecast reports and the ocean heat content data. Both gridded and observed datasets were processed into dekadal, monthly and seasonal averages and then analysed. The results revealed that, based on the observations, above normal rainfall of 936 and 908 mm were reported at stations of Kisauni (Unguja) and Karume airport (Pemba) during 2019 OND season. This amount was the first and second ever recorded for the extreme positive IOD during OND seasons of 1961, 1994, 1997, 2006 and 2019, and also the first for the previous higher OND rainfall seasons of 2016, 2017 and 2018 which was highly variable. Moreover, these values were second ever-recorded highest OND rainfall since 1916 to 2019 where the first one was observed in 1961. Furthermore, the results revealed that 2019 OND seasonal rainfall had the highest amount of contribution based on historical climatology. For instance, the 2019 OND rainfall for Kisauni, Pemba airport and Matangatuani contributed to 198%, 303% and 231% of the long term (1987-2016) mean OND rainfall in Zanzibar. Indeed, the results show that the presence of the MJO during OND and the enhanced positive IOD was among the causes for the observed wetness of the 2019 OND in Zanzibar and most parts of the country. Moreover, the dominant easterly, southeasterly and northwesterly onshore winds during 2019 OND also contributed to heavy rainfall. The monthly rainfall variability among stations had the highest amount of rainfall which ranges from 400 to 500 mm which was observed during October in Kisauni and Karume airport, while the lowest amount ranging from 150 to 180 mm was observed during November in Matangatuani and the surrounding stations. Based on the comparison of the forecasted reports issued by ICPAC and TMA, the results revealed that irrespective of not considering the likelihood of occurrence of MJO and strong positive IOD both forecasts has performed well with that of ICPAC being leading. Conclusively, since the 2019 OND season has been uniquely characterized by the presence of MJO and IOD polarities it would be worthful to consider the two as input parameters during the OND rainfall forecast over the region.
文摘The study investigated the impacts of tropical cyclone (TC) Fantala (11<sup>th</sup> to 27<sup>th</sup> April, 2016) to the coastal areas of Tanzania, Zanzibar in particular. Daily reanalysis data consisting of wind speed, sea level pressure (SLP), sea surface temperatures (SSTs) anomaly, and relative humidity from the National Centres for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) were used to analyze the variation in strength of Fantala as it was approaching the Tanzania coastal line. In addition observed rainfall from Tanzania Meteorological Authority (TMA) at Zanzibar office, Global Forecasting System (GFS) rainfall estimates and satellite images were used to visualize the impacts of tropical cyclone Fantala to Zanzibar. The results revealed that, TC Fantala was associated with deepening/decreasing in SLP (from 1012 - 1010 mb) around the north-western Madagascar and coastal Tanzania, whereas the mean SSTs was greater than 28<span style="white-space:nowrap;">°</span>C and an SSTs anomaly ranged from 0 to 2.3<span style="white-space:nowrap;">°</span>C. The vertical wind shear which ridged at Mozambican Channel and over north-eastern Madagascar was high enough (12 - 15 ms<sup>-1</sup>) to support the intensifying of Fantala. The thermodynamic and dynamic conditions of Fantala influenced heavy rainfall of greater than 170 mm over most stations in Zanzibar. Moreover, Fantala disrupted the temporal variability of 2016 March to May (MAM) seasonal rainfall. Besides, more than 420 people were homeless, at least 3330 houses were destroyed, and about 2 people died. As for mainland Tanzania Fantala resulted in a death of 12 people in Kilimanjaro and Arusha, more than 315 houses were washed away by flooding leading to 13,933 people being homeless. Conclusively the study calls for an extensive research work based on examining and forecasting the TCs rainfall impacts and their contribution during the two rainfall seasons of OND and MAM in Tanzania.
文摘This article examines the off season rainfall in northern coast Tanzania(NCT)including Zanzibar which occurred in January and February 2020(JF).Like the JF rainfalls of 2001,2004,2010,2016 and 2018,the JF(2020)rainfall was more unique in damages including loss of lives,properties and infrastructures.The study used the NCEP/NCAR reanalysis data to examine the cause of uniqueness of JF rainfall in 2001,2004,2010,2016,2018 and 2020 over NCT and Zanzibar.These datasets include monthly mean u,v wind at 850,700,500,and 200 mb;SSTs,mean sea level pressure(MSLP)anomalies,Dipole Mode Index(DMI),and monthly rainfall from NCT and Zanzibar stations.Datasets were processed and calculated into long term,seasonal,and monthly averages,indeed,Precipitation Index(PI)was calculated.Correlation analysis between the rainfall(December to January),SST,DMI and 850 mb wind vectors;and long-term percentage contribution of investigated parameters was calculated.Results revealed significant positive and negative correlations between JF rainfall,SSTs and DMI.Moreover,JFs of 2004 and 2016 had higher rainfalls of 443 mm with percentage contribution of up to 406%,while January and February,2020 had the highest of 269.1 and 101.1mm in Zanzibar and 295 and 146.1 mm over and NCT areas,with highest January long-term rainfall contribution of 356%in Zanzibar and 526%over NCT.The DJF(2019/20)had the highest rainfall record of 649.5 mm in Zanzibar contributing up to 286%,while JF 2000 rainfall had a good spatial and temporal distribution over most NCT areas.JF,2020 rainfall had impacts of more than 20 people died in Lindi and several infrastructures including Kiyegeya Bridge in Morogoro were damaged.Conclusively,more research works on understanding the dynamics of wet and dry JF seasons should be conducted.
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Surface ozone is among the greenhouse gases which form a blanket that causes the heat trapping effect and warms the atmosphere with related consequences such as atmospheric temperature rise. The aim of this study is to investigate the temporal relationship between the meteorological conditions and the surface ozone concentrations.In this study surface ozone and meteorological measurements
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.
文摘Climate change and variability, has embarked societies in Zanzibar to rely on horticulture (i.e. watermelon production) as an adaptive measure due to an unpromising situation of commonly used agricultural yields. Currently, there is either no or scant information that describes the influence of climate changes and variability to watermelon production in Zanzibar. Thus, this study aimed to determine the influence of climate variability on the quantity of watermelon production in Zanzibar. The study used both primary and secondary datasets, which include the anecdotal information collected from interviewers’ responses from four districts of Unguja and Pemba, and climate parameters (rainfall, maximum and minimum temperature (Tmax and Tmin) acquired from Tanzania Meteorological Authority (TMA) at Zanzibar offices. Pearson correlation was used for analyzing the association between watermelon production and climate parameters, while paired t-test was applied to show the significance of the mean differences of watermelon and climate parameters for two periods of 2014-2017 and 2018-2021, respectively. Percentage changes were used to feature the extent to which the two investigated parameters affect each other. The anecdotal responses were sorted, calculated in monthly and seasonal averages, plotted and then analyzed. Results have shown a strong correlation (r = 0.8 at p ≤ 0.02, and r = 0.7) between watermelon production, Tmax and rainfall during OND, especially in Unguja, as well as Tmin during JJA (i.e. r = - 0.8 at p ≤ 0.02) in Pemba. Besides, results have shown the existence of significant differences between the means of watermelon production and climate parameter for the two stated periods, indicating that the climate parameters highly affects the watermelon production by either enhancing or declining the yields by 69% - 162% and 17% - 77%, respectively. Moreover, results have shown that respondents were aware that excess temperature intensity during dry periods can lead to high production costs due number of soil and other environmental factors. Besides the results have shown that OND seasonal rainfall and MAM Tmax had good association with watermelon production in Unguja while JJA Tmin declined the production in Pemba. Thus, the study concludes that seasonal variability of climate parameter has a significant influence on the watermelon production. The study calls for more studies on factors affecting watermelon production (e.g. soil characteristics, pest sides and manure), and recommends for climate based decision making on rain fed agricultural yields and routine monitoring of weather information.
文摘Tropical cyclones (TCs) and storms (TSs) are among the devastating events in the world and southwestern Indian Ocean (SWIO) in particular. The seasonal forecasting TCs and TSs for December to March (DJFM) and November to May (NM) over SWIO were conducted. Dynamic parameters including vertical wind shear, mean zonal steering wind and vorticity at 850 mb were derived from NOAA (NCEP-NCAR) reanalysis 1 wind fields. Thermodynamic parameters including monthly and daily mean Sea Surface Temperature (SST), Outgoing Longwave Radiation (OLR) and equatorial Standard Oscillation Index (SOI) were used. Three types of Poison regression models (i.e. dynamic, thermodynamic and combined models) were developed and validated using the Leave One Out Cross Validation (LOOCV). Moreover, 2 × 2 square matrix contingency tables for model verification were used. The results revealed that, the observed and cross validated DJFM and NM TCs and TSs strongly correlated with each other (p ≤ 0.02) for all model types, with correlations (r) ranging from 0.62 - 0.86 for TCs and 0.52 - 0.87 for TSs, indicating great association between these variables. Assessment of the model skill for all model types of DJFM and NM TCs and TSs frequency revealed high skill scores ranging from 38% - 70% for TCs and 26% - 72% for TSs frequency, respectively. Moreover, results indicated that the dynamic and combined models had higher skill scores than the thermodynamic models. The DJFM and NM selected predictors explained the TCs and TSs variability by the range of 0.45 - 0.65 and 0.37 - 0.66, respectively. However, verification analysis revealed that all models were adequate for predicting the seasonal TCs and TSs, with high bias values ranging from 0.85 - 0.94. Conclusively, the study calls for more studies in TCs and TSs frequency and strengths for enhancing the performance of the March to May (MAM) and December to October (OND) seasonal rainfalls in the East African (EA) and Tanzania in particular.
文摘The marine accidents are among the main components of the Zanzibar Disaster Management Policy (2011) and the Zanzibar Blue Economy Policy (2020). These policies aimed to institute legal frame works and procedures for reducing both the frequency of marine accidents and their associated fatalities. These fatalities include deaths, permanent disabilities and loss of properties which may result into increased poverty levels as per the sustainable development goal one (SDG1) which stipulates on ending the poverty in all its forms everywhere. Thus, in the way to support these Government efforts, the influence of climate and weather on marine accidents along Zanzibar and Pemba Channels was investigated. The study used the 10 years (2013-2022) records of daily rainfall and hourly wind speed acquired from Tanzania Meteorological Authority (TMA) (for the observation stations of Zanzibar, Pemba, Dares Salaam and Tanga), and the significant wave heights data, which was freely downloaded from Globally Forecasting System (GFS-World model of 13 km resolution). The marine accident records were collected from TASAC and Zanzibar Maritime Authority (ZMA), and the anecdotal information was collected from heads of quay and boat captains in different areas of Zanzibar. The Mann Kendal test, was used to determine the slopes and trends direction of used weather parameters, while the Pearson correlations analysis and t-tests were used to understand the significance of the underlying relationship between the weather and marine accidents. The paired t-test was used to evaluate the extent to which weather parameters affect the marine accidents. Results revealed that the variability of extreme weather events (rainfall, ocean waves and wind speed) was seen to be among the key factors for most of the recorded marine accidents. For instance, in Pemba high rainfall showed an increasing trend of extreme rainfall events, while Zanzibar has shown a decreasing trend of these events. As for extreme wind events, results show that Dar es Salaam and Tanga had an increasing trend, while Zanzibar and Pemba had shown a decreasing trend. As for the monthly variability of frequencies of extreme rainfall events, March to May (MAM) season was shown to have the highest frequencies over all stations with the peaks at Zanzibar and Pemba. On the other hand, high frequency of extreme wind speed was observed from May to September with peaks in June to July, and the highest strength was observed during 09:00 to 15:00 GMT. Moreover, results revealed an increasing trend of marine accidents caused by bad weather except during November. Also, results showed that bad weather conditions contributed to 48 (32%) of all 150 recorded accidents. Further results revealed significant correlation between the extreme wind and marine accidents, with the highest strong correlation of r = 0.71 (at p ≤ 0.007) and r = 0.75 (at p ≤ 0.009) at Tanga and Pemba, indicating the occurrence of more marine accidents at the Pemba channel. Indeed, strong correlation of r = 0.6 between extreme rainfall events and marine accidents was shown in Pemba, while the correlations between extremely significant wave heights and marine accidents were r = 0.41 (at p ≤ 0.006) and r = 0.34 (p ≤ 0.0006) for Pemba and Zanzibar Channel, respectively. In conclusion, the study has shown high influence between marine accidents and bad weather events with more impacts in Pemba and Zanzibar. Thus, the study calls for more work to be undertaken to raise the awareness on marine accidents as a way to alleviate the poverty and enhance the sustainable blue economy.
文摘Climate change and variability have been inducing a broad spectrum of impacts on the environment and natural resources including groundwater resources. The study aimed at assessing the influence of weather, climate variability, and changes on the quality of groundwater resources in Zanzibar. The study used the climate datasets including rainfall (RF), Maximum and Minimum Temperature (T<sub>max</sub> and T<sub>min</sub>), the records acquired from Tanzania Meteorological Authority (TMA) Zanzibar office for 30 (1989-2019) and 10 (2010-2019) years periods. Also, the Zanzibar Water Authority (ZAWA) monthly records of Total Dissolved Solids (TDS), Electrical Conductivity (EC), and Ground Water Temperature (GWT) were used. Interpolation techniques were used for controlling outliers and missing datasets. Indeed, correlation, trend, and time series analyses were used to show the relationship between climate and water quality parameters. However, simple statistical analyses including mean, percentage changes, and contributions to the annual and seasonal mean were calculated. Moreover, t and paired t-tests were used to show the significant changes in the mean of the variables for two defined periods of 2011-2015 and 2016-2020 at p ≤ 0.05. Results revealed that seasonal variability of groundwater quality from March to May (MAM) has shown a significant change in trends ranging from 0.1 to 2.8 mm/L/yr, 0.1 to 2.8 μS/cm/yr, and 0.1 to 2.0℃/yr for TDS, EC, and GWT, respectively. The changes in climate parameters were 0.1 to 2.4 mm/yr, 0.2 to 1.3℃/yr and 0.1 to 2.5℃/yr in RF, T<sub>max</sub>, and T<sub>min</sub>, respectively. From October to December (OND) changes in groundwater parameters ranged from 0.2 to 2.5 mm/L/yr 0.1 to 2.9 μS/cm/yr, and 0.1 to 2.1℃/yr for TDS, EC, and GWT, whereas RF, T<sub>max</sub>, and T<sub>min</sub> changed from 0.3 to 1.8 mm/yr, 0.2 to 1.9℃/yr and 0.2 to 2.0℃/yr, respectively. Moreover, the study has shown strong correlations between climate and water quality parameters in MAM and OND. Besides, the paired correlation has shown significant changes in all parameters except the rainfall. Conclusively, the study has shown a strong influence of climate variability on the quality of groundwater in Zanzibar, and calls for more studies to extrapolate these results throughout Tanzania.
文摘The inter-annual variability of rainfall onset and crop replanting in East Africa (EA) was assessed using daily estimated rainfall data from climate hazard group infrared precipitation (CHIRPS Ver2.0) and monthly Sea Surface Temperature (SST) indices [Indian Ocean Dipole (IOD) and El-Ni?o Southern Oscillation (ENSO) at NINO3.4 region] from the National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). The data covered a period of 40 years from1981 to 2020. The methods of cumulative of daily mean rainfall, percentage of onset date departure (PODD), Mann-Kendall (MK) trend test, student t-test, and correlation were applied in the analysis. The results showed that early onset with dry spell (WDS) consideration frequently occurs in Uganda between the first and second dekads of September, while late rainfall onset WDS occurs in the first and second dekads of December over central and Northern Kenya as well as in the Northeastern highlands, parts of the northern coast and unimodal regions in Tanzania. Rainfall onset with no dry spell (WnDS) portrayed an average of 10 days before the occurrence of true onset WDS, with maximum onset departure days (ODD) above 30 days across the Rift Valley area in Kenya and the Northeastern highlands in Tanzania. The high chance of minimum ODD is seen over entire Uganda and the area around Lake Victoria. However, few regions, such as Nakuru (Kenya) Gulu and Kibale (Uganda), and Gitega (Burundi), revealed a slight positive linear trend while others showed negative trend. Significant positive patterns for correlation between onset WDS and SST indices (IOD and NINO 3.4) were discovered in Northern and Northeastern Kenya, as well as areas along the Indian Ocean (over Tanzania’s Northern Coast). Inter-annual relationship between onset dates WDS and IOD (NINO3.4) indices exhibits a high correlation coefficient r = 0.23 (r = 0.48) in Uganda and r = 0.44 (r = 0.36) in Kenya. On the other hand, a negative correlation was revealed over Burundi and Tanzania (over a unimodal region). A high percentage of PODD was observed, ranging from 40% to 70% over the Rift Valley in Kenya and at the Northeastern highlands in Tanzania. However, a strong PODD above 70% was observed over Tanga and the Northern Pwani Region in Tanzania. These findings will help farmers to understand the appropriate time for crop planting, as well as help other socio-economic activities that strongly depend on rainfall.
