It is about climate projections using climate models, and scenarios under East Africa

1. CLIMATE PROJECTIONS UNDER
FUTURE SCENARIOS IN EAST
AFRICAN REGION

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INTRODUCTION
• There are evidences of climate change globally and East African (EA) region in particular
(Houghton et al. 1995 and Li et al. 2019).
• The effects of climate change such as rising temperature and changes in precipitation are
undeniably clear with impacts already affecting ecosystems, biodiversity and people.
• These impacts have the potential to undermine and even, undo progress made in improving the
socio-economic well-being of East Africans.
• The current climate in EA is around 1-1.5˚C warmer than pre-industrial times, and there is high
confidence of further warming in the future (Govt UK, 2022).

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INTRODUCTION
• Future impacts are projected to worsen as the temperature continues to rise
and as precipitation becomes more unpredictable (Shongwe et al., 2011;
Senevirante et al., 2012; Niang et al., 2014; Ongoma et al., 2018; Ayugi
and Tan, 2019; Gebrechorkos et al., 2019).

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INTRODUCTION
• In this work, we used historical and future simulations climate data including
temperature and precipitation from CMIP6 model consist of 20 simulations
to:
 Map climatology for both reference and future scenarios
 Determine the change between reference and future scenarios
• We learnt about future climate at EA region level, as well as how climate might
change in the future.

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METHODOLOGY

6. 1.STUDY AREA
• EA lies in the Equatorial Region, Within 25° E–55°E And -12°
S–23° N (Fig. 1).
• EA:
 Intricate landscape features such as Mt. Kilimanjaro,
Mt. Elgon, Mt. Kenya, Mt. Rwenzori, Lake Victoria, a
large expanse of arid and semi-arid lands (ASALs).
 Highland regions depict fluctuations of temperature
from one region to another and average mean annual
precipitation range between 800 - 1200 mm (Graffiths,
1972; Camberlin, 2018).
Figure 1: East African Region

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2. SOURCE OF DATA
• The surface temperature (tas) and Precipitation (pr) datasets were retrieved from the CMIP6
repository at https://esgf-node.llnl.gov/search/cmip6
• Two types of datasets were used for analyses:
 For temperature and Precipitation, data from 1985-2014 were used as reference; while
data from 2041-2070 were used for projections under SSP1-2.6 and SSP5-8.5

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3. ANALYTICAL METHODS
• The Multi-models Ensembles (MME) is build based on 20 simulations from CMIP6
(Coupled Model Inter-Comparison Project)
• The models at each timescale were first standardized for unit of temperature (from Kelvin
to Celsius)
• The standardized datasets were then re-gridded to a common grid by utilizing the nearest
neighbor interpolation technique
• The Climate Data Operator (CDO) was used in data processing while python packages
(numpy, cartopy, scipy, netCDF4, matplotlib) were used to map the climatology

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3. ANALYTICAL METHODS
 SSP stands for Shared Socioeconomic Pathways, where the SSP 1-2.6 specifically refers to a scenario
where there's strong climate change mitigation while the SSP 5-8.5 represents a business as usual
scenario.

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RESULTS AND DISCUSSION

11. Figure 2: Reference mean temperature climatology (1985-2014) and projections 2041-2070 under scenarios
1. REFERENCE AND PROJECTIONS – TEMPERATURE
(CLIMATOLOGY)
• Under SSP126, the temperature will decrease compared to the BAU scenario in South Sudan,
Somalia, Sudan, Kenya and Eritrea
• Under SSP585 (BAU), the temperature will increase compared to the reference scenario in
South Sudan, Sudan, Kenya and Eritrea
Reference Scenario SSP1-2.6 Scenario SSP5-8.5 Scenario

12. Figure 3: Change between mean temperature climatology (1985-2014) and projections 2041-2070 under scenarios
2. CHANGE - TEMPERATURE
• Both scenarios indicate the positive change (warming) in north-west of East Africa Region
(South Sudan, Uganda, and Sudan), but it appear to be most important under SSP5-8.5
• Both scenarios indicate the negative change (cooling) in Ethiopia, Kenya, and Tanzania, but it
appear to be most important under SSP1-2.6
SSP1-2.6 Scenario SSP5-8 5 Scenario

13. Figure 4: Reference mean precipitation climatology (1985-2014) and projections 2041-2070 under scenarios
3. REFERENCE AND PROJECTIONS – PRECIPITATION
(CLIMATOLOGY)
• The precipitation will increase compared to the reference scenario in Ethiopia, and in
neighboring areas of Lake Victoria for both scenarios (SSP5-8.5, SSP1-2.6)
SSP1-2.6 Scenario SSP1-2.6 Scenario
Reference Scenario

14. Figure 5: Change between mean precipitation climatology (1985-2014) and projections 2041-2070 under scenarios
4. CHANGE - PRECIPITATION
• There is positive change of precipitation in Ethiopia, and in neighboring areas of Lake Victoria
for both scenarios (SSP5-8.5, SSP1-2.6)
SSP1-2.6 Scenario SSP5-8.5 Scenario

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CONCLUSION AND RECOMMENDATIONS
• The results indicated that if no mitigation measures put in place in EA region the temperature and
precipitation will continue to rise in 2041-2070 which will affect the socio-economic of people
• These findings are meaningful to policymakers due to the important projected changes of
temperature and precipitation that can be considered in their planning.
• For climate scientists, comparative studies are needed for further studies by using one RCM
driven by different GCMs and different RCMs driven by different GCMs with diverse SSPs for
constraining uncertainties.

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Thank You Very Much!
Asante Sana!
Merci Beaucoup!
Murakoze Cyane!