WHU-SGCC: a novel approach for blending daily satellite (CHIRP) and precipitation observations over the Jinsha River basin
Authors: Shen Gaoyun , Chen Nengcheng , Wang Wei , Chen Zeqiang 
Published: November 2019

Abstract. Accurate and consistent satellite-based precipitation estimates
blended with rain gauge data are important for regional precipitation
monitoring and hydrological applications, especially in regions with limited
rain gauges. However, the existing fusion precipitation estimates often have
large uncertainties over mountainous areas with complex topography and
sparse rain gauges, and most of the existing data blending algorithms are
not good at removing the day-by-day errors. Therefore, the development of
effective methods for high-accuracy precipitation estimates over complex
terrain and at a daily scale is of vital importance for mountainous
hydrological applications. This study aims to offer a novel approach for
blending daily precipitation gauge data and the Climate Hazards Group
Infrared Precipitation (CHIRP; daily, 0.05∘) satellite-derived
precipitation developed by UC Santa Barbara over the Jinsha River basin from
1994 to 2014. This method is called the Wuhan University Satellite and Gauge
precipitation Collaborated Correction (WHU-SGCC). The results show that the
WHU-SGCC method is effective for liquid precipitation bias adjustments from
points to surfaces as evaluated by multiple error statistics and from
different perspectives. Compared with CHIRP and CHIRP with station data
(CHIRPS), the precipitation adjusted by the WHU-SGCC method has greater
accuracy, with overall average improvements of the Pearson correlation
coefficient (PCC) by 0.0082–0.2232 and 0.0612–0.3243, respectively, and
decreases in the root mean square error (RMSE) by 0.0922–0.65 and
0.2249–2.9525 mm, respectively. In addition, the Nash–Sutcliffe efficiency
coefficient (NSE) of the WHU-SGCC provides more substantial improvements than
CHIRP and CHIRPS, which reached 0.2836, 0.2944, and 0.1853 in the spring,
autumn, and winter. Daily accuracy evaluations indicate that the WHU-SGCC
method has the best ability to reduce precipitation bias, with average
reductions of 21.68 % and 31.44 % compared to CHIRP and CHIRPS,
respectively. Moreover, the accuracy of the spatial distribution of the
precipitation estimates derived from the WHU-SGCC method is related to the
complexity of the topography. The validation also verifies that the proposed
approach is effective at detecting major precipitation events within the
Jinsha River basin. In spite of the correction, the uncertainties in the
seasonal precipitation forecasts in the summer and winter are still large,
which might be due to the homogenization attenuating the extreme rain event
estimates. However, the WHU-SGCC approach may serve as a promising tool to
monitor daily precipitation over the Jinsha River basin, which contains
complicated mountainous terrain with sparse rain gauge data, based on the
spatial correlation and the historical precipitation characteristics. The
daily precipitation estimations at the 0.05∘ resolution over the
Jinsha River basin during all four seasons from 1990 to 2014, derived from
WHU-SGCC, are available at the PANGAEA Data Publisher for Earth &amp;
Environmental Science portal (https://doi.org/10.1594/PANGAEA.905376, Shen et al., 2019).