Description:
This study investigates historical and projected rainfall patterns at Djibouti Airport using observational datasets (CHIRPS, ERA5Land) and climate models, including CanESM2, CanESM5, and regional CORDEX downscaled simulations. The research evaluates model performance through statistical metrics, such as Taylor diagrams and extreme precipitation indices (ETCDDI), and examines projected changes under multiple climate scenarios (RCP4.5, RCP8.5, SSPs). The results provide insights into future rainfall variability, trends in extreme events, and potential drought and wet periods, supporting climate risk assessment and adaptation planning in the Horn of Africa.
Figure 1. Historical CHIRPSv.2 and ERA5Land annual rainfall at Djibouti airport station compared to
corrected rainfall from CanESM2 and RCM (AFR22-CanRCM4, AFR44-SMHI-RCA4,
AFR44-CanRCM4, AFR44-UQAM-CRCM5) over the period 1980-2005 and Taylor Diagram for performance comparison (left panels).The radial
coordinate indicates the variance ratio between the observation and the
satellite data.
Figure 2. Projected rainfall changes relative to the
baseline period 1953–2021 based on CanESM2-CORDEX, the downscaled CanESM2-CMIP5
and CanESM5-CMIP6 using Observation, CHIRPS and ERA5Land datasets. Colored
shaded areas represent the areas of uncertainty (standard deviation) for the
scenarios RCP4.5, RCP.8.5 for CMIP5 and SSP2-RCP4.5and SSP5-RCP8.5 for CMIP6
(right panels). The solid sphere in the boxplot represents the mean, and the
interquartile range spans from Q1 to Q3 within the box square. Horizontal lines
above and below denote the minimum and maximum. Irregular dotted indicate
extreme values (left panels).
Table 1. Overall change
of rainfall for future climate generated using CanESM2, AFR44 and CanESM5 models
in RCP 4.5 and RCP 8.5 scenarios.
Figure 3. Historical and projected
average monthly rainfall at Djibouti airport station (1953-2021) using
statistical downscaling of CanESM2 and CanESM5 and corrected regional model
CORDEX from 2006–2100.
Table 2. Trend of ETCDDI indices for
extreme precipitation (historical (1980-2017) and projected with AFR44.CanRCM4.CHIRPS.RCP45
(2018-2099) at the Djibouti airport station and detection of the stationarity
period with the Pettitt test (Pettitt, 1979) and standard normal homogeneity (SNHT,
Alexandersson 1986).
Figure 4. Projected Interannual
variations (line) and linear trends (dash) in mean annual 3-month RAI at
Djibouti airport station from downscaled CMIP5, CMIP6 and CORDEX based on
observation, CHIRPS and ERA5Land datasets (right panels) and Characteristics of
drought (left panels).
Figure 5. Variation of
ETCDDI indices for projected extreme precipitation (2018-2099) at the Djibouti airport
station with the CanESM2 (CHIRPS.RCP45 and ERA5Land. RCP85), CanESM5 (CHIRPS. RCP45
and ERA5Land. RCP45) and CORDEX (CHIRPS. RCP45 and ERA5Land. RCP45) models.
Figure 5. Projected rainfall changes
relative to the baseline period 1953–2021 based on the downscaled CanESM2-CMIP5
and CanESM5-CMIP6 using Observation, CHIRPS and ERA5Land datasets. Colored
shaded areas represent the areas of uncertainty (standard deviation) for the scenarios
RCP1.9, RCP.2.6 and RCP.7.0 for CMIP5 and SSP1-RCP2.6, SSP3-RCP7.0 and SSP5-RCP8.5
for CMIP6. The solid sphere in the boxplot represents
the mean, and the interquartile range spans from Q1 to Q3 within the box
square. Horizontal lines above and below denote the minimum and maximum.
Irregular dotted indicate extreme values.
Table 3. Evaluation of precipitation projections (very short term) from 2006 to 2021
under the RCP 4.5 scenario simulated at the Djibouti airport station by
Canadian Earth System models derived from CMIP5, CORE-CORDEX and CMIP6.
Table 4. Evaluation of precipitation projections (very short term) from 2006 to 2021
under the RCP 8.5 scenario simulated at the Djibouti airport station by
Canadian Earth System models derived from CMIP5, CORE-CORDEX and CMIP6.
Table 5. Overall change
of average rainfall for future climate generated using CanESM2, AFR44 and
CanESM5 model RCP 4.5 scenarios.
RAINFALL TRESHOLD (Djibouti Case)
·
Q12.5% less than 35.75 mm/annum (Dry
events)
·
Q87.5% more than
291.60/annum (Wet events)
·
Q50% less than 1 mm/month (Dry
events)
·
Q90% more than 32.72 mm/month (Wet
events)
·
Light rainfall (0–0.2(q95) mm/day)
·
Moderate rainfall events (0.2–8(q99) mm/day)
·
Heavy rainfall events (> 8 mm/day).
Abdi-Basid ADAN, 2024
The Abdi-Basid Courses Institute (TABCI)
