This study aimed at establishing and quantifying the evolution and socio-economic impacts of extreme rainfall events in October 2019. The study also focused on ascertaining the extent to which the Indian Ocean Dipole ...This study aimed at establishing and quantifying the evolution and socio-economic impacts of extreme rainfall events in October 2019. The study also focused on ascertaining the extent to which the Indian Ocean Dipole (IOD) and the El Ni<span style="white-space:nowrap;">?</span>o Southern Oscillation (ENSO) influenced anomalous rainfall over East Africa (EA) in October 2019. It employed Singular Value Decomposition (SVD) methods to analyze inter-annual variability of EA rainfall and the Sea Surface Temperature Anomalies (SSTA) over the Indian and Pacific Ocean with a focus on October to December 2019 rainfall season. The SVD analysis enabled the exploration of the leading modes from the mean monthly rainfall and SSTs leading to the determination of the likely influence of the IOD and ENSO respectively. The first SVD coupled modes, which dominate the co-variability between the October rainfall over the EA domain, and SSTA over the Indian and Pacific Oceans based on 1981 to 2010 climatology indicate the monopole positive co-variability with rainfall over the entire EA domain. The corresponding spatial pattern for the SSTA over the Indian Ocean (IO) recaptures the positive IOD event while the central equatorial Pacific Ocean (i.e., over Ni<span style="white-space:nowrap;">?</span>o 3.4 region) reveals a monopole positive loading, a typical signal for the warm phase of ENSO. The positive rainfall anomaly over the EA during October is found to be associated with either the IOD event or ENSO condition events independently or in phase. However, the inter-annual variability between October rainfall over EA and ENSO reveals a moderate relationship (r = 0.4212) while a robust association (r = 0.7084) is revealed with IOD. Comparatively, the October 2019 rainfall anomaly peaks the highest in history over the EA and was found to be coupled with highest positive IOD event in record. Unlikely, the 1997 October rainfall (which peaked the second in history), was associated with the co-occurrence of the positive phase of ENSO and 展开更多
This study aimed at assessing the evolution, distribution and the socio-economic impacts of extreme rainfall over East Africa during the March, April and May (MAM) rainfall season focusing on assessing the trends and ...This study aimed at assessing the evolution, distribution and the socio-economic impacts of extreme rainfall over East Africa during the March, April and May (MAM) rainfall season focusing on assessing the trends and contribution of MAM rainfall in mean annual rainfall across the region. It employed Principal Component Analysis (PCA) methods to capture the patterns and variability of MAM rainfall. The PCA results indicated that the first Principal Component (PC) describe 17% of the total variance, while the first six PCs account only 53.5% of the total variance in MAM rainfall, underscoring the complexity of rainfall forcing factors in the region. It has been observed that MAM rainfall accounts about 30% - 60% of the mean annual rainfall in most parts of the region, signifying its importance in agriculture, water, energy and other socio-economic sectors. MAM has been characterized by increasing variability with varying trend patterns across the region. The MAM rainfall trend is not homogeneous across the region;some areas are experiencing a slight decreasing rainfall trend, while other areas are experiencing a slight increasing rainfall trend. The observed trend dynamics is consistent with the global trend patterns in precipitation as depicted in recent Intergovernmental Panel on Climate Change (IPCC) reports. Over the last five years MAM rainfall season have been characterized by record-breaking extremes. On 8th May 2017, Tanga and Mombasa meteorological stations recorded 316 mm and 235.1 mm of rainfall in 24 hours respectively, which are the highest amounts for these respective stations, since their establishment. Record highest 24 hours rainfall amounting to 134.9 mm and 119.4 mm were also observed at Buginyanya and Kawanda meteorological stations in Uganda on 18th March 2018 and 7<sup>th</sup> May 2020. On 6<sup>th</sup> May 2020, Byimana meteorological station in Rwanda, also observed 140.6 mm of rainfall in 24 hours, the highest since its establishment. These extremes have caused multiple losses of life and展开更多
The study aimed at analyzing the trends and variability of temperature extreme</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span st...The study aimed at analyzing the trends and variability of temperature extreme</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">s</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> over </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">the </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">northeastern highlands in Tanzania, specifically over Arusha and Kilimanjaro regions. Quality controlled mean monthly, daily maximum and minimum temperature data for the period 1961 to 2020</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> obtained from Tanzania Meteorological Authority</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> were used in the study. Rclimdex and the National Climate Monitoring Products (NMCP) software</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> developed by the World Meteorological Organization (WMO)</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> were used for computation of the indices at a monthly, season展开更多
Heavy rainfall is one of the primary causes of flood during rainy season in Tanzania leading to severe socio-economic impacts. The study aimed at assessing and characterizing the variability of Heavy Rainfall Events (...Heavy rainfall is one of the primary causes of flood during rainy season in Tanzania leading to severe socio-economic impacts. The study aimed at assessing and characterizing the variability of Heavy Rainfall Events (HREs) using Empirical Orthogonal Function (EOF), Mann-Kendal (MK) trend test, Correlation and Composite analysis methods. Based on the daily-observed precipitation and reanalysis data sets for the October to December (OND) rainfall season of 35 years (1981-2015), the spatial and temporal characteristics of HREs in Tanzania are studied. The relationship between heavy rainfall (HR) and large-scale circulation anomalies including the Indian Ocean dipole (IOD) and El Ni<span style="white-space:nowrap;">?</span>o southern oscillation (ENSO) indices was assessed. The study found that, approximately 590 HREs were concentrated over northern sector and coastal belt of Tanzania. The monthly variability indicates that HREs are more pronounced in December followed by November while October being the least affected. The occurrence of HREs over the Lake Victoria, Kigoma and Tabora is largely attributed to low-level convergence of westerlies and enhanced moisture from Congo basin accompanied by a pronounced rising limb of Indian Walker circulation cell. A time-series analysis of HRE exhibits an inter-annual variation characterized by a slightly increasing trend, though the computed trends were not statistically significant at 95% confidence level. In most part of Tanzania HREs were positively correlated with both ENSO and IOD indices, underscoring the critical role of ENSO and Indian Ocean dynamic in modulating rainfall variability over the region. In general, it has been found that most of the HREs are generally triggered or amplified by large-scale circulation patterns such as ENSO and IOD.展开更多
The current study examines the interannual rainfall variability and its associated atmospheric circulation in Tanzania during October-December (OND) rainfall season based on 1974 to 2010 climatology. The Empirical Ort...The current study examines the interannual rainfall variability and its associated atmospheric circulation in Tanzania during October-December (OND) rainfall season based on 1974 to 2010 climatology. The Empirical Orthogonal Function (EOF), composite and correlation analysis were used in this study. Years with enhanced precipitation are found to be associated with the low level moist and unstable wind from Congo basin which organizes and forms a confluent zone, an inter tropical convergence zone (ITCZ) extending from Congo to northern sector of the country. It however, characterizes low-level westerly moisture flux transport sourced from Congo basin, ascending limb of the local Indian Ocean Walker circulation over East Africa which enhances convection for wetness condition. Wet years are also coupled with the positive Indian Ocean Dipole (IOD) and the warm phase of the El Nino Southern Oscillation (ENSO) condition. On the spatial scale, both the IOD and ENSO indices are well correlated with OND rains over the bimodal areas (Lake Victoria basin, North Eastern Highlands (NEH), and northern coast) with strong correlation being to the NEH. Strong temporal correlation is revealed between the OND rains and IOD (r = 0.6304) compared to ENSO (r = 0.5538) indicating that anomalous warming over the western Indian Ocean has a faster response to OND rains in Tanzania than the remote influence induced by anomalous warming from the central Pacific Ocean. The patterns associated with dry years are found to be linked with the low-level divergence accompanied by convergence in the upper level. This condition enhances continuous descending motion accompanied with suppression in rainfall activities. Dry years are also associated with negative IOD, cold phase of ENSO condition, descending limb of the Walker Circulation and significant reduction in the westerly moisture flux transport sourced from Congo basin towards the western sector and Lake Victoria basin.展开更多
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 desig...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 <span><span><span style="font-family:;" "="">×<span> 250 m resolution;8 days Landsat 7 enhanced thematic mapper (ETM) with resolution of 30 </span>×<span> 30 m composites, and 5 Landsat 8 (LC8) images, to determine the patterns and the variability of the Normalized Difference Vegetation Index (NDVI) and En<span>hanced Vegetation Index (EVI) and TCs impacts on vegetation. Moreover, we</span> <span>used Tropical Rainfall Measuring Mission (TRMM) data and the daily to</span> 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 <span>and April, and minimum (low) values in November. The results for EV</span>I changes based on pre and post storm conditions revealed that most observed stations and most TCs led to significant EVI changes which ranged from </span>-<span>0.05 to 0.19, and </span>-<span>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 Fob<span>ane) </span><span>were associated with positive NDVI changes <i>i.e.</i> (enhancement) of >0.51 </span><span>an</span>d >0.31, and NDVI reduction (<i>i.e.</i> negative changes) of <0.02 and <</span>-<span>0.19 <展开更多
This paper provides <span style="font-family:Verdana;">an </span><span style="font-family:Verdana;">analysis and a description of the best practices and lessons learned in the imp...This paper provides <span style="font-family:Verdana;">an </span><span style="font-family:Verdana;">analysis and a description of the best practices and lessons learned in the implementation of </span><span style="font-family:Verdana;">the </span><span style="font-family:;" "=""><span style="font-family:Verdana;">Global Framework for Climate S</span><span style="font-family:Verdana;">ervices Adaptation Program in Africa (GFCS-APA) focusing on Tanzania </span><span style="font-family:Verdana;">coun</span></span><span style="font-family:Verdana;">try</span><span style="font-family:Verdana;">’s</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> activities. GFCS-APA was the first multi-agency initiative imple</span><span style="font-family:Verdana;">mented </span><span style="font-family:Verdana;">under the Global Framework for Climate Services (GFCS) in two African</span><span style="font-family:Verdana;"> countries, namely Tanzania and Malawi with funding from the Royal</span><span style="font-family:Verdana;"> Govern</span><span style="font-family:Verdana;">ment of Norway. In Tanzania, the programme was implemented in two</span><span style="font-family:Verdana;"> phases from the year 2014 to 2021 in the three pilot districts of Kondoa, Longido and Kiteto located in Dodoma, Arusha and Manyara regions</span></span><span style="font-family:Verdana;">,</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> re</span><span style="font-family:Verdana;">spectively. The overarching goal of the programme was to enable bette</span><span style="font-family:Verdana;">r management of the risks caused by climate variability and change at all levels, from </span><span style="font-family:Verdana;">end-users to policy level, through development and incorporation of</span><span style="font-family:Verdana;"> science</span></span><span style="font-family:Verdana;">-</span><span style="font-family:;" "=""><span style="font-family:Verdana;">based climate in</span><span style="font-family:Ver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 an展开更多
文摘This study aimed at establishing and quantifying the evolution and socio-economic impacts of extreme rainfall events in October 2019. The study also focused on ascertaining the extent to which the Indian Ocean Dipole (IOD) and the El Ni<span style="white-space:nowrap;">?</span>o Southern Oscillation (ENSO) influenced anomalous rainfall over East Africa (EA) in October 2019. It employed Singular Value Decomposition (SVD) methods to analyze inter-annual variability of EA rainfall and the Sea Surface Temperature Anomalies (SSTA) over the Indian and Pacific Ocean with a focus on October to December 2019 rainfall season. The SVD analysis enabled the exploration of the leading modes from the mean monthly rainfall and SSTs leading to the determination of the likely influence of the IOD and ENSO respectively. The first SVD coupled modes, which dominate the co-variability between the October rainfall over the EA domain, and SSTA over the Indian and Pacific Oceans based on 1981 to 2010 climatology indicate the monopole positive co-variability with rainfall over the entire EA domain. The corresponding spatial pattern for the SSTA over the Indian Ocean (IO) recaptures the positive IOD event while the central equatorial Pacific Ocean (i.e., over Ni<span style="white-space:nowrap;">?</span>o 3.4 region) reveals a monopole positive loading, a typical signal for the warm phase of ENSO. The positive rainfall anomaly over the EA during October is found to be associated with either the IOD event or ENSO condition events independently or in phase. However, the inter-annual variability between October rainfall over EA and ENSO reveals a moderate relationship (r = 0.4212) while a robust association (r = 0.7084) is revealed with IOD. Comparatively, the October 2019 rainfall anomaly peaks the highest in history over the EA and was found to be coupled with highest positive IOD event in record. Unlikely, the 1997 October rainfall (which peaked the second in history), was associated with the co-occurrence of the positive phase of ENSO and
文摘This study aimed at assessing the evolution, distribution and the socio-economic impacts of extreme rainfall over East Africa during the March, April and May (MAM) rainfall season focusing on assessing the trends and contribution of MAM rainfall in mean annual rainfall across the region. It employed Principal Component Analysis (PCA) methods to capture the patterns and variability of MAM rainfall. The PCA results indicated that the first Principal Component (PC) describe 17% of the total variance, while the first six PCs account only 53.5% of the total variance in MAM rainfall, underscoring the complexity of rainfall forcing factors in the region. It has been observed that MAM rainfall accounts about 30% - 60% of the mean annual rainfall in most parts of the region, signifying its importance in agriculture, water, energy and other socio-economic sectors. MAM has been characterized by increasing variability with varying trend patterns across the region. The MAM rainfall trend is not homogeneous across the region;some areas are experiencing a slight decreasing rainfall trend, while other areas are experiencing a slight increasing rainfall trend. The observed trend dynamics is consistent with the global trend patterns in precipitation as depicted in recent Intergovernmental Panel on Climate Change (IPCC) reports. Over the last five years MAM rainfall season have been characterized by record-breaking extremes. On 8th May 2017, Tanga and Mombasa meteorological stations recorded 316 mm and 235.1 mm of rainfall in 24 hours respectively, which are the highest amounts for these respective stations, since their establishment. Record highest 24 hours rainfall amounting to 134.9 mm and 119.4 mm were also observed at Buginyanya and Kawanda meteorological stations in Uganda on 18th March 2018 and 7<sup>th</sup> May 2020. On 6<sup>th</sup> May 2020, Byimana meteorological station in Rwanda, also observed 140.6 mm of rainfall in 24 hours, the highest since its establishment. These extremes have caused multiple losses of life and
文摘The study aimed at analyzing the trends and variability of temperature extreme</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">s</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> over </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">the </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">northeastern highlands in Tanzania, specifically over Arusha and Kilimanjaro regions. Quality controlled mean monthly, daily maximum and minimum temperature data for the period 1961 to 2020</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> obtained from Tanzania Meteorological Authority</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> were used in the study. Rclimdex and the National Climate Monitoring Products (NMCP) software</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> developed by the World Meteorological Organization (WMO)</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> were used for computation of the indices at a monthly, season
文摘Heavy rainfall is one of the primary causes of flood during rainy season in Tanzania leading to severe socio-economic impacts. The study aimed at assessing and characterizing the variability of Heavy Rainfall Events (HREs) using Empirical Orthogonal Function (EOF), Mann-Kendal (MK) trend test, Correlation and Composite analysis methods. Based on the daily-observed precipitation and reanalysis data sets for the October to December (OND) rainfall season of 35 years (1981-2015), the spatial and temporal characteristics of HREs in Tanzania are studied. The relationship between heavy rainfall (HR) and large-scale circulation anomalies including the Indian Ocean dipole (IOD) and El Ni<span style="white-space:nowrap;">?</span>o southern oscillation (ENSO) indices was assessed. The study found that, approximately 590 HREs were concentrated over northern sector and coastal belt of Tanzania. The monthly variability indicates that HREs are more pronounced in December followed by November while October being the least affected. The occurrence of HREs over the Lake Victoria, Kigoma and Tabora is largely attributed to low-level convergence of westerlies and enhanced moisture from Congo basin accompanied by a pronounced rising limb of Indian Walker circulation cell. A time-series analysis of HRE exhibits an inter-annual variation characterized by a slightly increasing trend, though the computed trends were not statistically significant at 95% confidence level. In most part of Tanzania HREs were positively correlated with both ENSO and IOD indices, underscoring the critical role of ENSO and Indian Ocean dynamic in modulating rainfall variability over the region. In general, it has been found that most of the HREs are generally triggered or amplified by large-scale circulation patterns such as ENSO and IOD.
文摘The current study examines the interannual rainfall variability and its associated atmospheric circulation in Tanzania during October-December (OND) rainfall season based on 1974 to 2010 climatology. The Empirical Orthogonal Function (EOF), composite and correlation analysis were used in this study. Years with enhanced precipitation are found to be associated with the low level moist and unstable wind from Congo basin which organizes and forms a confluent zone, an inter tropical convergence zone (ITCZ) extending from Congo to northern sector of the country. It however, characterizes low-level westerly moisture flux transport sourced from Congo basin, ascending limb of the local Indian Ocean Walker circulation over East Africa which enhances convection for wetness condition. Wet years are also coupled with the positive Indian Ocean Dipole (IOD) and the warm phase of the El Nino Southern Oscillation (ENSO) condition. On the spatial scale, both the IOD and ENSO indices are well correlated with OND rains over the bimodal areas (Lake Victoria basin, North Eastern Highlands (NEH), and northern coast) with strong correlation being to the NEH. Strong temporal correlation is revealed between the OND rains and IOD (r = 0.6304) compared to ENSO (r = 0.5538) indicating that anomalous warming over the western Indian Ocean has a faster response to OND rains in Tanzania than the remote influence induced by anomalous warming from the central Pacific Ocean. The patterns associated with dry years are found to be linked with the low-level divergence accompanied by convergence in the upper level. This condition enhances continuous descending motion accompanied with suppression in rainfall activities. Dry years are also associated with negative IOD, cold phase of ENSO condition, descending limb of the Walker Circulation and significant reduction in the westerly moisture flux transport sourced from Congo basin towards the western sector and Lake Victoria basin.
文摘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 <span><span><span style="font-family:;" "="">×<span> 250 m resolution;8 days Landsat 7 enhanced thematic mapper (ETM) with resolution of 30 </span>×<span> 30 m composites, and 5 Landsat 8 (LC8) images, to determine the patterns and the variability of the Normalized Difference Vegetation Index (NDVI) and En<span>hanced Vegetation Index (EVI) and TCs impacts on vegetation. Moreover, we</span> <span>used Tropical Rainfall Measuring Mission (TRMM) data and the daily to</span> 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 <span>and April, and minimum (low) values in November. The results for EV</span>I changes based on pre and post storm conditions revealed that most observed stations and most TCs led to significant EVI changes which ranged from </span>-<span>0.05 to 0.19, and </span>-<span>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 Fob<span>ane) </span><span>were associated with positive NDVI changes <i>i.e.</i> (enhancement) of >0.51 </span><span>an</span>d >0.31, and NDVI reduction (<i>i.e.</i> negative changes) of <0.02 and <</span>-<span>0.19 <
文摘This paper provides <span style="font-family:Verdana;">an </span><span style="font-family:Verdana;">analysis and a description of the best practices and lessons learned in the implementation of </span><span style="font-family:Verdana;">the </span><span style="font-family:;" "=""><span style="font-family:Verdana;">Global Framework for Climate S</span><span style="font-family:Verdana;">ervices Adaptation Program in Africa (GFCS-APA) focusing on Tanzania </span><span style="font-family:Verdana;">coun</span></span><span style="font-family:Verdana;">try</span><span style="font-family:Verdana;">’s</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> activities. GFCS-APA was the first multi-agency initiative imple</span><span style="font-family:Verdana;">mented </span><span style="font-family:Verdana;">under the Global Framework for Climate Services (GFCS) in two African</span><span style="font-family:Verdana;"> countries, namely Tanzania and Malawi with funding from the Royal</span><span style="font-family:Verdana;"> Govern</span><span style="font-family:Verdana;">ment of Norway. In Tanzania, the programme was implemented in two</span><span style="font-family:Verdana;"> phases from the year 2014 to 2021 in the three pilot districts of Kondoa, Longido and Kiteto located in Dodoma, Arusha and Manyara regions</span></span><span style="font-family:Verdana;">,</span><span style="font-family:;" "=""><span style="font-family:Verdana;"> re</span><span style="font-family:Verdana;">spectively. The overarching goal of the programme was to enable bette</span><span style="font-family:Verdana;">r management of the risks caused by climate variability and change at all levels, from </span><span style="font-family:Verdana;">end-users to policy level, through development and incorporation of</span><span style="font-family:Verdana;"> science</span></span><span style="font-family:Verdana;">-</span><span style="font-family:;" "=""><span style="font-family:Verdana;">based climate in</span><span style="font-family:Ver
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 an
