Country

Tanzania, United Republic of

Explore historical and projected climate data, climate data by sector, impacts, key vulnerabilities and what adaptation measures are being taken. Explore the overview for a general context of how climate change is affecting Tanzania, United Republic of.

Climate ProjectionsMean Projections

This page presents Tanzania, United Republic of’s projected climate. Information is shown by climatologies, as either projected mean or anomaly (change). We offer a range of variables at both national and sub-national aggregations. Data is presented spatially, as a seasonal cycle, time series, or heatplot, which shows seasonal change over long-term time horizons. Data can be analyzed as both annual and seasonal; monthly data is available in the Data Download page. You can further tailor your analysis by selecting different projected climatologies and emission scenarios, or Representative Concentration Pathways (RCPs). Projection data on this page is presented as multi-model ensembles, which represent the range and distribution of the most plausible projected outcomes of change in the climate system. It is important to note that RCPs are “what if scenarios” and provide insight into future climates based on defined emissions and mitigation efforts. Data for specific coordinates can be downloaded in the Data Download page.  

Climate projection data is modeled data from the global climate model compilations of the Coupled Model Inter-comparison Projects (CMIPs), overseen by the World Climate Research Program. The data currently presented is derived from the fifth phase of the CMIPs, CMIP5. The CMIPs form the data foundation of the IPCC Assessment Reports. CMIP5 is used for the IPCC's Fifth Assessment Report and CMIP6 will be used for the IPCC's Sixth Assessment Report. Projection data is presented at a 1.0º x 1.0º (100km x 100km) resolution.

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Use the menu above to visualize different climate projection layers and chart data. Click on the map to get location specific data.


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Climate Data Projections

The climate science community sources a suite of global climate models to help decision makers understand the projections of future climate change and related impacts, among the most widely used are the Coupled Model Intercomparison Project, Phase 5 (CMIP5) models included in the IPCC's Fifth Assessment Report (AR5). Key projected climate trends summarized from the country's Second National Communication (2014) includes:

Temperature

  • More warming is projected over the Western side of the country, whereby a warming of up to 3.4ºC is projected by 2100.
  • A warming of less than 1.76ºC for 2050 and 3.28ºC for 2100 is projected over parts of the northern coast regions and north-eastern highlands.
  • A warming in excess of 1.77ºC for 2050 and 3.3ºC for 2100 is projected over the Lake Victoria zone.
  • A warming in excess of 1.39ºC for 2050 is projected in central Tanzania zone. 
  • And a warming of 3.18ºC for 2100 is projected for the southern coast including Mtwara and Lindi regions.

Precipitation

  • Rainfall projections indicate that some parts of the country may experience an increase in mean annual rainfall of up to 18-28% by 2100, particularly over the Lake Victoria Basin and North-Eastern Highland.
  • The South Western Highlands and Western Zones of the country are projected to experience an increase in annual rainfall by up to 9.9% in 2050 and by up to 17.7% in 2100.
  • The North Coast Zone is projected to have an 66 increase of about 1.8% in 2050 and 5.8% in 2100 while the Central Zone is projected to have an increase of up to 9.9% in 2050 and up to 18.4% in 2100.
  • The Southern Coast Zone is projected to have a decrease of up to 7% in 2050 and an increase of annual rainfall of about 9.5% in 2100.

This section allows the visualization of  climate variables and indices derived from scientifically vetted CMIP5 projections for different timeframes, statistics, emission scenarios, and climate models. 

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Use the menu above to visualize different climate projection layers and chart data. Click on the map to get location specific data.


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