Evaluating the performances of gridded satellite/reanalysis products in representing the rainfall climatology of Ethiopia

Figures & data

Figure 1. The location of Ethiopia from Africa and the meteorological stations used in this study.

Figure 2. The long-term annual average rainfall (1991–2020) values of the observed data, and CHIRPS v2.0 and MSWEP v2.8 estimates over the different AEZs of the country.

Table 1. Descriptions of CHIRPS v2.0 and MSWEP v2.8 rainfall products.

Rainfall products	Coverage	Spatial resolution	Temporal resolution	Owned by	Data available	Input	References
CHIRPS v2.0	50° N-50° S	0.05° (∼5 km)	Daily, pentadal and monthly	California University	1981 to the revision of this paper is performed (i.e. 2023)	TIR-satellite observation, gauge Meteosat TIR imagery	Funk et al. 2015
MSWEP v2.8	Global	0.1° (∼11 km)	3 h, daily and monthly	G-WADI (USA)	1979 to the revision of this paper was undertaken (i.e. 2023)	Satellite-estimates, reanalysis data, gridded gauge	Beck et al. 2019

Figure 3. Schematic diagram showing the methodological flows of this study.

Table 2. The list of the considered performance measure statistics used in this study and its best values.

Statistics and formula	Range	Unit	Best value	References
$\mathrm{POD}=\frac{\mathrm{Hits}}{\mathrm{Hits}+\mathrm{Misses}}$	0 to 1	None	1	Dinku et al. 2018; Fenta et al. 2018
$\mathrm{FAR}=\frac{\text{False\hspace{0.17em}alarms}}{\mathrm{Hits}+\text{False alarms}}$	0 to 1	None	0	Dinku et al. 2018; Fenta et al. 2018
$\mathrm{FBI}=\frac{\mathrm{Hits}+\text{False\hspace{0.17em}alarms}}{\mathrm{Hits}+\mathrm{Misses}}$	0 to ∞	None	1	Fenta et al. 2018
$\mathrm{CSI}=\frac{\mathrm{Hits}}{\mathrm{Hits}+\mathrm{Misses}+\text{False\hspace{0.17em}alarms}}$	0 to 1	None	1	Abebe et al. 2020
$\mathrm{MAE}=\sum \left|(S-G)\right|$	0 to ∞	mm	0	Dinku et al. 2018; Ageet et al. 2022
$\mathrm{RMSE}=\sqrt{\frac{\sum {(G-S)}^2}{N}}$	0 to ∞	mm	0	Ageet et al. 2022
$\mathrm{PBIAS}=\frac{\sum (G-S)}{\sum (G)}\times$100	−∞ to ∞	%	0	Ageet et al. 2022
$r=\frac{{\sum }^{\text{}}\left(G-\overline{G}\right)\left(S-\overline{S}\right)}{\sqrt{{\sum }^{\text{}}{(G-\overline{G})}^2} \sqrt{{\sum }^{\text{}}{(S-\overline{S})}^2}}$	−1 to 1	None	−1 or 1	Dinku et al. 2018; Ageet et al. 2022
$\mathrm{KGE}=1-\sqrt{{\left(r-1\right)}^2+{\left(\beta -1\right)}^2}+{\left(\gamma -1\right)}^2$	−∞ to 1	None	1	Peña‐Guerrero et al. 2022; Gashaw et al. 2023

Where, G is observed rainfall total at a gauge station, $\overline{G}$ is the mean of observed rainfall total at reference gauging station, S is rainfall total for the satellite/reanalysis rainfall product, $\overline{S}$ is the mean rainfall total of the satellite/reanalysis rainfall products, N is the number of data pairs compared, r is Pearson’s correlation coefficient, β is the bias component, $\gamma$ is the variability component.

Table 3. The contingency table presenting the agreement between observed records (Po) and satellite/reanalysis rainfall (Ps) for different rainfall intensity ranges (the threshold is ≥1 mm).

	Po ≥ Threshold	Po ≤ Threshold
Ps ≥ Threshold	Hits	False alarms
Ps ≤ Threshold	Misses	Correct negatives

Table 4. Performances of CHIRPS v2.0 and MSWEP v2.8 annual rainfall estimates at different AEZs of Ethiopia during 1991–2020.

AEZs	Rainfall products		Continuous statistical metrics
			MAE	RMSE	PBIAS (%)	r	KGE
Desert	CHIRPS v2.0	G = 217	53.59	73.73	15.7	0.42	0.27
	MSWEP v2.8	G = 217	72.45	93.54	18	0.19	0.17
Tropical	CHIRPS v2.0	G = 1030.4	55.1	71.89	2.3	0.53	0.63
	MSWEP v2.8	G = 1030.4	118.5	131.15	10.1	0.64	0.62
Sub-tropical	CHIRPS v2.0	G = 1251.1	47.43	69.2	2.9	0.86	0.73
	MSWEP v2.8	G = 1251.1	75.52	102.95	1	0.6	0.6
Temperate	CHIRPS v2.0	G = 1156.7	53.46	69.65	2.9	0.84	0.77
	MSWEP v2.8	G = 1156.7	68.39	83.3	−0.1	0.79	0.72
Alpine	CHIRPS v2.0	955.8	162.99	202.21	−15.1	0.42	0.32
	MSWEP v2.8	955.8	200.15	262.43	−18.8	0.2	−0.02

G is the gauged data’s average annual rainfall, and there are N = 30 data pairs that are compared (mm). Best values are indicated in bold.

Figure 4. The bar graph representation of the observed annual rainfall with MSWEP v2.8 and CHIRPS v2.0 over desert, tropical, sub-tropical, temperate, and alpine AEZs of Ethiopia from 1991 to 2020.

Table 5. Statistical continuous metrics analysis comparing seasonal (Belg and Kiremt) CHIRPS v2.0 and MSWEP v2.8 rainfall estimations with ground gauged data of AEZs in Ethiopia from 1991 and 2020.

	Desert
	Belg (FMAM) (G = 55.9)		Kiremt (JJAS) (G = 138.3)
	CHIRPS v2.0	MSWEP v2.8	CHIRPS v2.0	MSWEP v2.8
MAE	26	33.7	39.77	61.11
RMSE	33.87	45.01	54.03	74.55
PBIAS	3.2	-2.8	18.8	24.6
r	0.56	0.24	0.42	0.17
KGE	0.41	0.2	0.25	0.14
	Tropical
	Belg (FMAM) (G = 324.0)		Kiremt (JJAS) (G = 479.3)
	CHIRPS v2.0	MSWEP v2.8	CHIRPS v2.0	MSWEP v2.8
MAE	24.33	31.9	34.43	70.12
RMSE	30.61	42.97	46.49	80.44
PBIAS	−1.5	0.1	-1.7	13
r	0.83	0.7	0.69	0.63
KGE	0.8	0.69	0.59	0.58
	Sub-tropical
	Belg (FMAM) (G = 333.1)		Kiremt (JJAS) (G = 737.4)
	CHIRPS v2.0	MSWEP v2.8	CHIRPS v2.0	MSWEP v2.8
MAE	21.22	42.48	29.98	46.48
RMSE	28.51	53.47	45.45	53.99
PBIAS	2.9	−3	0.40	1.4
r	0.9	0.7	0.7	0.6
KGE	0.82	0.66	0.7	0.6
	Temperate
	Belg (FMAM) (G = 267.2)		Kiremt (JJAS) G = 771.8)
	CHIRPS v2.0	MSWEP v2.8	CHIRPS v2.0	MSWEP v2.8
MAE	21.07	30.2	43.6	60.65
RMSE	25.17	41.02	58.73	75.89
PBIAS	1.3	−8.1	2.3	2.5
r	0.95	0.88	0.72	0.52
KGE	0.74	0.83	0.68	0.49
	Alpine
	Belg (FMAM) (G = 156.6)		Kiremt (JJAS) G = 755.3)
	CHIRPS v2.0	MSWEP v2.8	CHIRPS v2.0	MSWEP v2.8
MAE	53.96	59.07	111.74	135.74
RMSE	60.92	74.34	144.86	188.39
PBIAS	−31.7	−34.3	−10	−12.8
r	0.73	0.61	0.51	0.27
KGE	0.58	0.35	0.42	0.14

G is the mean seasonal rainfall (mm) measured from 1991 and 2020 in Bega, Belg, and Kiremt, and N = 30 data pairs are compared. Best values are shown in bold.

Figure 6. Line graph of mean monthly observed rainfall with MSWEP v2.8 and CHIRPS v2.0 rainfall over desert, tropical, sub-tropical, temperate, and alpine AEZs of Ethiopia for the time period 1991–2020.

Table 6. Comparing daily rainfall estimates of CHIRPS v2.0 and MSWEP v2.8 with observed rainfall data over the five AEZs of Ethiopia during1991–2020 periods.

AEZs	Rainfall products		Continuous statistical metrics
			MAE	RMSE	PBIAS (%)	r	KGE
Desert	CHIRPS v2.0	G = 0.6	0.85	3.76	15.7	0.26	0.06
	MSWEP v2.8	G = 0.6	0.82	3.76	18	0.28	0.11
Tropical	CHIRPS v2.0	G = 2.8	2	3.01	2.3	0.48	0.48
	MSWEP v2.8	G = 2.8	1.65	2.49	10.1	0.57	0.52
Sub-tropical	CHIRPS v2.0	G = 3.4	1.64	2.52	2.9	0.73	0.7
	MSWEP v2.8	G = 3.4	1.29	2.08	1	0.79	0.79
Temperate	CHIRPS v2.0	G = 3.2	2	3.4	2.9	0.68	0.66
	MSWEP v2.8	G = 3.2	1.54	2.84	−0.1	0.74	0.73
Alpine	CHIRPS v2.0	G = 2.6	3.43	8.29	−15.1	0.38	0.31
	MSWEP v2.8	G = 2.6	2.66	6.47	−18.8	0.49	0.46

N = 10,958 is the data pairs compared, and G represents the observed daily average rainfall (mm). best values are represented in bold.

Table 7. Detection skill scores of daily rainfall (threshold ≥ 1 mm) estimates of CHIRPS v2.0 and MSWEP v2.8 satellite/reanalysis rainfall estimates for Ethiopian AEZs during 1991–2020.

AEZs	Rainfall products	Categorical statistical indices
		POD	FAR	FBI	CSI
Desert	CHIRPS v2.0	0.26	0.54	0.57	0.2
	MSWEP v2.8	0.3	0.49	0.6	0.23
Tropical	CHIRPS v2.0	0.85	0.2	1.07	0.7
	MSWEP v2.8	0.87	0.13	0.98	0.75
Sub-tropical	CHIRPS v2.0	0.95	0.14	1.1	0.82
	MSWEP v2.8	0.94	0.09	1.03	0.86
Temperate	CHIRPS v2.0	0.87	0.21	1.09	0.71
	MSWEP v2.8	0.85	0.09	0.94	0.79
Alpine	CHIRPS v2.0	0.62	0.45	1.14	0.41
	MSWEP v2.8	0.6	0.1	0.67	0.56

N = 10,958 is the number of data pairs compared. Best values are shown in bold.

Figure 7. The PDF daily rainfall events of CHIRPS v2.0 and MSWEP v2.8 products against observed data at different intensity levels over desert, tropical, sub-tropical, temperate, and alpine AEZs of Ethiopia during 1991–2020 periods.

Table 8. Summary of overall performance of CHIRPS v2.0 and MSWEP v2.8 for simulating rainfall from daily to annual temporal scales over the five AEZs of Ethiopia in the majority/entire performance measure statistics.

Temporal scales	Desert		Tropical		Sub-tropical		Temperate		Alpine
	CHIRPS v2.0	MSWEP v2.8	CHIRPS v2.0	MSWEP v2.8	CHIRPS v2.0	MSWEP v2.8	CHIRPS v2.0	MSWEP v2.8	CHIRPS v2.0	MSWEP v2.8
Continuous statistical measures
Daily
Monthly
Belg
Kirmet
Annual
Categorical metrics
PDF

Note: The dark green filled boxes illustrates best performing products in the entire metrics, the light green filled boxes indicates the best performing product in majority performance measures, and the yellow filled boxes represents comparable/equal performance of the two studied rainfall products over the studied five AEZs of the country. Continuous statistical measures include r, MAE, RMSE, PBIAS, and KGE while categorical metrics represents POD, FAR, FBI and CSI, and PDF denotes the eight rainfall intensity classes.

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