Evaluation of satellite-based products for extreme rainfall estimations in the eastern coastal areas of China

Figures & data

Figure 1. (a) Location of the study area, (b) the distributions of rain gauges, and (c) the average monthly rainfall over the eastern coastal areas of China from 2003 to 2015.

Table 1. Results of cross validation.

Interpolation methods	root mean square error (mm/day)	mean absolute error (mm/day)	correlation coefficient
IDW	3.59	1.87	0.81
kriging	4.82	2.23	0.80
co-kriging	4.70	2.65	0.73

Table 2. The basic information on the three satellite-based products.

Products	Spatial resolution	Temporal resolution	Available period	Coverage
3B42V7	0.25°	3-hourly	1998-present	50°N-50°S
CMORPH-RAW	0.25°	3-hourly	2003-present	60°N-60°S
CMORPH-CRT	0.25°	3-hourly	1998-present	60°N-60°S

Table 3. The statistical indicators for evaluating the satellite-based products.

Statistical indicators	Formulas	Perfect value	Unit
Root Mean Square Error (RMSE)	0	mm
Mean Absolute Error (MAE)	0	mm
Relative Bias (RB)	0	%
Correlation Coefficient (CC)	$CC=\frac{{\sum }_{i=1}^n\left(G_i-\bar{G}\right)\left(S_i-\bar{S}\right)}{\sqrt{{\sum }_{i=1}^n{\left(G_i-\bar{G}\right)}^2}\sqrt{{\sum }_{i=1}^n{\left(S_i-\bar{S}\right)}^2}}$	1	NaN

Notes: $n$ represents the number of samples, $G_i$ is gridded gauge rainfall (mm), $S_i$ is satellite-based product rainfall estimates (mm). $\bar{G}$ and $\bar{S}$ are mean values of gridded gauge rainfall and satellite-based product rainfall estimates (mm), respectively. More details are available in Jiang et al. (2018).

Figure 2. The scatter plots of the extreme rainfall amounts of (a) H50p, (b) R95p, (c) R99p from GRD and (1) 3B42V7, (2) CMORPH-RAW, and (3) CMORPH-CRT during the period 2003–2015.

Table 4. The statistical results of satellite-based products for average extreme rainfall.

Indices	Products	RMSE (mm)	MAE (mm)	RB(%)	CC
H50p	3B42V7	15.61	12.41	−4.88	−0.15
	CMORPH-RAW	27.79	25.05	−34.16	−0.44
	CMORPH-CRT	18.67	15.64	−13.62	−0.32
R95p	3B42V7	7.00	5.23	−3.71	0.45
	CMORPH-RAW	14.06	12.32	−31.14	0.43
	CMORPH-CRT	8.39	6.21	−9.92	0.34
R99p	3B42V7	16.62	12.18	−8.14	0.30
	CMORPH-RAW	28.72	23.98	−35.24	0.14
	CMORPH-CRT	19.96	14.93	−15.93	0.16

Figure 3. The spatial distributions of the average extreme rainfall of (a) H50p, (b) R95p, (c) R99p for GRD, 3B42V7, CMORPH-RAW, and CMORPH-CRT during the period 2003–2015.

Figure 4. Two extreme rainfall time series of the Xujiahui station in 2015 and satellite-based product observations. (a) 16–17 June, (b) 27–28 June.

Figure 5. The RB of 3B42V7, CMORPH-RAW, and CMORPH-CRT in different daily rainfall levels.

Figure 6. The overall detection capacity of the three satellite-based products in different daily rainfall thresholds.

Table 5. The parameters used in potential flood simulating model.

Parameters	Data sources	Expressions	Weights	Meanings
C	MOD13A3	See Liu et al. (2013) for details	0.1	The coverage of vegetation
E	MERIT-DEM		0.2	Elevation
SG			0.2	Slope gradient
D	LULC map in 2005	$\mathrm{m}\mathrm{i}\mathrm{n}\left\{\left|x_i-x_j\right|+\left|x_j-y_j\right|\right\}$	0.2	The shortest Euclidean distance between the grid and the water body
R	GRD, satellite-based products	/	0.3	Rainfall information

Notes: $x_i$ ($y_i$) is the longitude (latitude) of central point of grid $i$; $x_i$ ($y_i$) is the longitude (latitude) of point $j$ having the shortest distance to grid $i$ in the water body.

Table 6. Archive of large flood events in the eastern coastal areas of China during 2003–2005.

No.	Latitude	Longitude	Year	Beginning	Ended	Main Cause
(a)	28.83°N	118.40°E	2003	23 June	28 June	Heay rain
(b)	28.42°N	120.83°E	2004	12 August	15 August	Tropical cyclone
(c)	28.12°N	120.86°E	2005	16 July	20 July	Tropical cyclone
(d)	28.58°N	118.55°E	2005	1 September	4 September	Tropical cyclone

Figure 7. The spatial distributions of the flood centroids and potential flood index (PFI) values of GRD, 3B42V7, CMORPH-RAW, and CMORPH-CRT in four flood events. (a) 23–28 June 2003, (b) 12–15 August 2004, (c) 16–20 July 2005, (d) 1–4 September 2005.

Figure 8. The PFI values of GRD, 3B42V7, CMORPH-RAW, and CMORPH-CRT at flood centroids in four flood events. (a) 23–28 June 2003, (b) 12–15 August 2004, (c) 16–20 July 2005, (d) 1–4 September 2005.

Jiang Q, Li WY, Wen JH, Qiu C, Sun WW, Fang QL, Xu M, Tan JG. 2018. Accuracy evaluation of two high-resolution satellite-based rainfall products: TRMM 3B42V7 and CMORPH in Shanghai. Water. 10(1):1–15.

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