Malawi Dashboard
Overview
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  • Risk Screening Overview
  • Climate Baseline
  • Natural Hazards
  • Climate Future
  • Impacts & Vulnerabilities
  • Adaptation
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Historical Climate Variability and Change
Historical Climate Trends
'cold' days per year 16  
Mean annual rainfall 750-1600 mm  
Mean annual temperature 0.9 °C 1960-2006  
'hot' days per year 30.5  
‘hot’ nights per year 41  
Historical Climate Data
Click on the map to view climate charts for your location of interest.
Key Precipitation Trends
  • The increase in temperature has been most rapid in the rainy summer (December-February) and lowest in the hottest season (September-November).
  • As year-to-year variability in rainfall is very high in Malawi, long-term trends are difficult to identify. In 2006, wet-season (December-February) rainfall over Malawi was markedly low, possibly causing a decreasing trend in December-February rainfall; however, evidence does not reveal consistent decreases.
Key Temperature Trends
  • Mean annual temperature has increased by 0.9°C between 1960 and 2006, an average rate of 0.21°C per decade.
  • The average number of ‘hot’ days per year in Malawi has increased by 30.5 between 1960 and 2003.
  • The average number of ‘hot’ nights per year increased by 41 nights (an additional 11.1% of nights) between 1960 and 2003.
  • The frequency of cold days and nights has decreased significantly since 1960 in all seasons except September-November.

For detailed climate information on available country weather station data, please see the Historical Variability Tool.
Disaster Risk Impacts and Vulnerabilities
Malawi is particularly prone to adverse climate hazards including dry spells, seasonal droughts, intense rainfall, riverine floods and flash floods.
Droughts and floods, the most severe of these hazards, have increased in frequency, intensity and magnitude over the past twenty years.
Floods and droughts are the leading cause of chronic food security, which is endemic in many parts of the country.
Model results estimate that droughts, on average, cause GDP losses of almost 1 percent every year. Economic losses are much higher during extreme droughts.
One study suggests a possibility that rainy seasons will grow shorter, potentially leading to more frequent failures in maize cultivation, which in turn has significant implications for future food security.
Interventions for coping with recurring droughts are likely to be site-specific, depending on terrain, soil type, and methods of water extraction and delivery, among many others. Some of the potential interventions include:
Construction of medium to large-scale dams, and small rainfall harvesting structures, such as water troughs, small dams and infiltration gullies.
Construction of deep wells for the provision of water for domestic purposes, irrigation and animal use.
To cope with recurring floods, potential interventions should focus on the construction of flood protection structures.
Click on the map to view climate charts for your location of interest.
Select a Layer Then Zoom to Explore.
Legend

Layers

cyclones
storm surge
earthquake
earthquake-triggered landslides
precipitation-triggered landslides
droughts
volcanic activity
tsunamis
floods
wildfires
Future Climate Projections
Future Climate Changes
Temperature
Mean annual temperature is projected to increase.
                               by 2060   
                               by 2090

1.1 -3.0°C 1.5-5.0°C
Rainfall
Projections in annual rainfall are inconsistent
Extreme
'Hot' days and nights are projected to increase
Future Trends
  • All projections indicate substantial increases in the frequency of days and nights that are considered ‘hot’ in the current climate. Annually, projections indicate that ‘hot’ days will occur more often.
  • Nights that are considered ‘hot’ for the annual climate of 1970-99 are projected to increase more quickly than hot days. Decreases in the frequency of days and nights that are considered ‘cold’ in current climate are projected, with these events becoming exceedingly rare by the 2090s.
  • Substantial changes in annual rainfall are not projected between June and October and monthly rainfall changes for November through May are inconsistent, with some models projecting increases and others projecting decreases, particularly in the periods from September-May.
  • All models consistently project increases in the proportion of rainfall that falls in heavy events in the annual average of up to 19% by the 2090s.

This chart shows how well the best available climate models capture the seasonal cycle of climate rainfall and/or temperature for the zone selected. The chart presents an envelope analysis of 16 climate model ensembles from the CMIP5 distribution used by the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report. When visualizing the mean climatology the thick line of the historical period represents a proxy measure of actual historical climate that can then be used to compare the historical cycle captured by climate models.

When users select the visualization of ‘Change’ (comparison of future versus historical), the chart depicts the ensemble median (black line), highest 10th percentile, and lowest 90th percentile for the anomalies. The visualization of the ensemble of all models is quite useful for understanding the potential range of climate model outcomes and a simple way to present the idea of climate model uncertainties.

Click on the map to view climate charts for your location of interest.
Choose your variable
Choose your time period
View mean or change
Scenario
Legend
Global Climate Models
bcc_csm1_1 bcc_csm1_1_m ccsm4 cesm1_cam5
csiro_mk3_6_0 fio_esm gfdl_cm3 gfdl_esm2m
giss_e2_h giss_e2_r ipsl_cm5a_mr miroc_esm
miroc_esm_chem miroc5 mri_cgcm3 noresm1_m

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