Assessment of the Spatio-Temporal Trends of Annual Extreme Temperature Indices over Tanzania during the Period of 1982-2022

Extreme weather and climatic phenomena, such as heatwaves, cold waves, floods and droughts, are expected to become more common and have a significant impact on ecosystems, biodiversity, and society. Devastating disasters are mostly caused by record-breaking extreme events, which are becoming more frequent throughout the world, including Tanzania. A clear global signal of an increase in warm days and nights and a decrease in cold days and nights has been observed. The present study assessed the trends of annual extreme temperature indices during the period of 1982 to 2022 from 29 meteorological stations in which the daily minimum and maximum data were obtained from NASA/POWER. The Mann-Kendall and Sen slope estimator were employed for trend analysis calculation over the study area. The analyzed data have indicated for the most parts, the country has an increase in warm days and nights, extreme warm days and nights and a decrease in cold days and nights, extreme cold days and nights. It has been disclosed that the number of warm nights and days is on the rise, with the number of warm nights trending significantly faster than the number of warm days. The percentile-based extreme temperature indices exhibited more noticeable changes than the absolute extreme temperature indices. Specifically, 66% and 97% of stations demonstrated positive increasing trends in warm days (TX90p) and nights (TN90p), respectively. Conversely, the cold indices demonstrated 41% and 97% negative decreasing trends in TX10p and TN10p, respectively. The results are seemingly consistent with the observed temperature extreme trends in various parts of the world as indicated in IPCC reports.

Analysis of Changes of Extreme Temperature during June to August Season over Tanzania

Natural and human systems are exposed and vulnerable to climate extremes, which contributes to the repercussions of climate variability and the probability of disasters. The impacts of both natural and human-caused climate variability are reflected in the reported changes in climate extremes. Particularly at the local community levels in the majority of the regions, there is currently a dearth of information regarding the distribution, dynamics, and trends of excessive temperatures among the majority of Tanzanians. Over the years 1982-2022, this study examined trends in Tanzania’s extreme temperature over the June to August season. Based on the distinction between absolute and percentile extreme temperatures, a total of eight ETCCDI climate indices were chosen. Mann-Kendall test was used to assess the presence of trends in extreme climatic indices and the Sen’s Slope was applied to compute the extent of the trends in temperature extremes. The study showed that in most regions, there is significant increase of warm days and nights while the significant decrease of cold days and nights was evident to most areas. Moreover, nighttime warming surpasses daytime warming in the study area. The study suggests that anthropogenic influences may contribute to the warming trend observed in extreme daily minimum and maximum temperatures globally, with Tanzania potentially affected, as indicated in the current research. The overall results of this study reflect patterns observed in various regions worldwide, where warm days and nights are on the rise while cold days and nights are diminishing.

Assessment of the Impacts of Tropical Cyclone Fantala to Tanzania Coastal Line: Case Study of Zanzibar

The study investigated the impacts of tropical cyclone (TC) Fantala (11th to 27th 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°C and an SSTs anomaly ranged from 0 to 2.3°C. The vertical wind shear which ridged at Mozambican Channel and over north-eastern Madagascar was high enough (12 - 15 ms-1) 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.

Assessment of the Off-season Rainfall of January to February 2020 and Its Socio Economic Implications in Tanzania: A Case Study of the Northern Coast of Tanzania

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.

Assessing the Impacts of Climate Change and Variability on Maize (Zea mays) Yield over Tanzania

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.

Spatio-Temporal Assessment of the Performance of March to May 2020 Long Rains and Its Socio-Economic Implications in Northern Coast of Tanzania

The spatio-temporal analysis of the performance of the March to May (MAM) 2020 rainfall and its societal implications to Northern Coastal Tanzania (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). Reanalysis 1 datasets of u (zonal) and v (meridional) winds, sea surface temperatures anomalies, relative humidity, amount of precipitable water and ocean net flux were analyzed. Other datasets include the Tanzania Meteorological Authority (TMA) observed rainfall records, maximum and minimum temperatures. Moreover, TMA and Intergovernmental Climate Prediction and Analysis Center (ICPAC). 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-term monthly and MAM percentage changes were calculated. Besides, the correlation between rainfall anomalies with an area-averaged SSTA for defined regions and stations in Zanzibar was 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 ranging 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 SSTA ranged from 0.5°C - 1.5°C and 1.5°C - 2.5°C over Southwestern Indian Ocean (SWIO) and coastal Tanzania and the increased trend of area-averaged SSTA on various SWIO blocks. Besides, 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, a great number of road culverts were washed away, and about 3600 houses were fallen or damaged, leading to a significant number of homeless people. As for NCT, the catastrophes include loss of lives, increased water levels over Lake Victoria leading to flooded islands and re allocation of more than 1000 people. In Kenya, more than 116 people died and 40,000 people were displaced. Conclusively, the study has shown the uniqueness (i.e., strength and societal implications) of MAM 2020 compared to other seasons;hence more studies on understanding the factors affecting extreme rainfall seasons in East Africa are required.

Climatic Indices’ Analysis on Extreme Precipitation for Tanzania Synoptic Stations

Like other countries in East Africa, Tanzania has been affected by extreme precipitation incidences both socially and economically. Determining the trend and variability features of extreme precipitation in the country is crucial. This study used data from 28 meteorological stations for 1981-2020 period to give an annual and seasonal analysis of the patterns of 10 ETCCDI’s extreme precipitation indices over the regions. At annual scale, the results showed that increasing trends had high frequency percentage than the decreasing ones, collecting about 76% in total. The decreasing trend was approximately 24%, and most of the stations with increasing percentage in trend are concentrated in Northern coast, Central, West, North-eastern highlands and Lake Victoria Basin. Most of the stations depicted negative trend are concentrated over Southern region. This highlights that extreme precipitation events have increased over the country for the period 1981-2020. At seasonal scale, during October to December (OND);the patterns of extreme precipitation climatic indices except R99p, showed positive significant increasing trend over Lake Victoria Basin and some Western parts of the country. In general, spatial patterns indicate decrease of precipitation over most parts of the country during OND. The seasonal average time series depicted non-significant positive trend during March to April (MAM) season, except for Consecutive Wet Days (CWD) which showed non-significant decreasing trend. Over the highest mountain in Africa, Kilimanjaro;the study has revealed significant decrease in Annual total-wet Precipitation (PRCPTOT), the number of heavy (very heavy) days of precipitation R10 mm (R20 mm) and Consecutive Wet Days (CWD) during MAM season. While the maximum one-day precipitation amount (RX1 day) was observed to decrease significantly over the Mountain during OND season. The result is very important in risk assessment and preparedness perspective in planning climate change mitigation and adaptations for different sectors like Tourism, Agriculture, Water and Energy.

The Influence of Tropical Cyclones to the Plant Productivity Indices along the Coast of Tanzania

The study investigated the influence of Tropical cyclone (TCs) to the plant productivity indices along the coast of Tanzania using both field observations and change detection methods. These indices are normally designed to maximize the sensitivity of the vegetation characteristics and are very crucial in monitoring droughts intensity, yield and biomass amongst others. The study used three types of satellite imageries including the 16 days Moderate Resolution Imaging Spectroradiometer (MODIS) of 250 × 250 m resolution;8 days Landsat 7 enhanced thematic mapper (ETM) with resolution of 30 × 30 m composites, and 5 Landsat 8 (LC8) images, to determine the patterns and the variability of the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) and TCs impacts on vegetation. Moreover, we used Tropical Rainfall Measuring Mission (TRMM) data and the daily to monthly rainfall data from Tanzanian Meteorological Authority (TMA). The change detection between the pre and post storm (TCs) conditions was used to analyse inter annual variability of EVI over Chwaka, Rufiji and Pugu— Kazimzumbwi. The changes in NDVI and EVI and monthly rainfall at the coastal stations were calculated, plotted and analyzed. The results revealed that, highest EVI values over coastal Tanzania were observed during March and April, and minimum (low) values in November. The results for EVI changes based on pre and post storm conditions revealed that most observed stations and most TCs led to significant EVI changes which ranged from -0.05 to 0.19, and -0.3 to 0.22, for MODIS and L7 ETM data, respectively. As for the spatial changes in NDVI results revealed that, TCs (Besija and Fobane) were associated with positive NDVI changes i.e. (enhancement) of >0.51 and >0.31, and NDVI reduction (i.e. negative changes) of <0.02 and <-0.19 for Chwaka and Rufiji, respectively. Besides the results revealed that, TCs episodes have induced a land cover changes from i.e. water covered areas changed to be vegetation covered especially over the shorelines and inter tidal areas. Indeed, these results were consistent with the analysis of rainfall patterns which indicated that low rainfall occurred in low NDVI areas and vice versa.

Investigating Women’s Realization on Understanding the Impact of Climate Variability in Socioeconomic Performance in Zanzibar, Tanzania: A Case of Jambiani Village

The study employed the triangulation approach to investigate the impact of climate variability on selected socioeconomic indicators, particularly food production, health and education, and how much climate variability and its impact on those indicators was realized and understood among the women living in Jambiani community in Zanzibar. The study used the explanatory, sequential mixed method to collect, datasets related to Jambiani communities (i.e. from the women in Kibigija village), other climate data acquired from Tanzania Meteorological Authority (TMA), Ministries of Agriculture and Health and Southern District in Zanzibar. The results obtained from the analysis of both anecdotal (interview, questionnaire among others) data shows that climate variability was imminent in Jambiani communities between 2010 and 2015 and had a negative impact on food production, health and education. Further results revealed that women working in informal sectors are more vulnerable to climate impacts than women working in formal sectors due to less knowledge and techniques to mitigate/cope with climate variability impacts. Conclusively the study has shown that climate variability affects more women with less awareness of what is happening and how to cope with it, thus the study calls for new research work and increasing the awareness on the impacts of climate on human basic needs.

The Relationship between Extreme Precipitation Events in East Africa during the Short Rainy Season and Indian Ocean Sea Surface Temperature

The East African short rainy season (October-November-December) is one of the major flood seasons in the East African region. The amount of rainfall during the short rainy season is closely related to the lives of the people and the socio-economic development of the area. By using precipitation data and sea surface temperature data, this study reveals the spatial and temporal variation patterns of extreme precipitation during the East African short rainy season. Key findings include significant rainfall variability, with Tanzania experiencing the highest amounts in December due to the southward shift of the Intertropical Convergence Zone (ITCZ), while other regions receive less than 100 mm. Extreme rainfall events (90th percentiles) are evenly distributed, averaging 2 to 10 days annually. Historical data shows maximum seasonal rainfall often peaks at 15 mm, with frequent occurrences of daily rainfall exceeding 10 mm during OND. Additionally, a positive correlation (0.48) between OND precipitation extremes and Indian Ocean Dipole (IOD) anomalies is statistically significant. These findings highlight the climatic variability and potential trends in extreme rainfall events in East Africa, providing valuable insights for regional climate adaptation strategies.

Change in the Number of Tropical Cyclone Landfall and Approach over Mozambique from 1980 to 2020

In this study, the variability of tropical cyclone (TC) landfall and approach over Mozambique as well as the environmental factors influencing were investigated. The frequencies of tropical cyclone landfall and approach as well as environmental factors were compared between the two periods (1980 to 1999 and 2000 to 2020). This study found that, according to International Best Track Archive for Climate Stewardship (IBTrACS) tropical cyclone data, the number of tropical cyclones making landfall over Mozambique increased by about 66% in the second period (2000-2020), compared to 34% in the first period (1980-1999). While the number of tropical cyclone approaches reduced from 59% in the first period to 41% in the second period. An assessment of the environmental conditions showed that warmer sea surface temperature (SST) and low vertical wind shear (VWS) were favorable to more TC genesis and, consequently, an increase in landfalls and a reduction in TC confined to the approach.

An Assessment of the Seasonal Rainfall and Its Societal Implications in Zanzibar Islands during the Season of October to December, 2019

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.

Assessment of the Impacts of Tropical Cyclones Idai to the Western Coastal Area and Hinterlands of the South Western Indian Ocean

Tropical Cyclones (TCs) are among the atmospheric events which may trigger/enhance the occurrence of disasters to the society in most world basins including the Southwestern Indian Ocean (SWIO). This study analyzed the dynamics and the impacts of the Tropical Cyclone (TC) Idai (4th-21st 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), and relative humidity (Rh). The dynamics and movements of Idai were 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-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. The 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°S, with low vertical wind shear over the landfall areas (-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-level vorticity values were also mapped over the landfall areas. More results revealed that countries laying equatorward of 12°S, e.g., 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 a wide spectrum of socio-economic livelihoods including significant loss of lives, injuries, loss of material wealth, infrastructure;indeed, people were forced to leave their houses for quite a longtime;water-borne diseases like malaria, cholera among others were experienced. Furthermore, results and reports revealed that a 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-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. 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 as their coast benefit analysis should be conducted to reduce the societal impacts of these TCs.

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

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, Tmax and Tmin 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 Tmax and Tmin 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, Tmax and Tmin for the HS, NF and FF, respectively. The results show that the observed Tmax increased by the rates of 0.035℃ yr-1 and 0.0169℃ yr-1, while the Tmin was increased by a rate of 0.064℃ yr-1 and 0.104℃ yr-1 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 Tmax 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 Tmin 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.

The Influence of Climate Variability on the Watermelon Production in Zanzibar

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.

The Inter-Annual Variability of Rainfall Onset and Its Implication on Crop Planting in Selected East Africa Countries

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.

Seasonal Prediction of Tropical Cyclones and Storms over the Southwestern Indian Ocean Region Using the Generalized Linear Models

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.

The Influence of Weather and Climate Variability on Groundwater Quality in Zanzibar

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 (Tmax and Tmin), 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, Tmax, and Tmin, 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, Tmax, and Tmin 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.