Blending long-term satellite-based precipitation data with gauge observations for drought monitoring: Considering effects of different gauge densities

摘要

Blending satellite-based precipitation estimation (SPE) data and in-situ gauge observation data can generate effective spatially-continuous-precipitation estimates with improved accuracy. This study assessed the improvement of the long-term SPE when blending with in-situ gauge observations for drought monitoring, using a simple but effective blending method named the geographical difference analysis (GDA) method and with the Precipitation Estimation from Remote Sensed Information by using Artificial Neural Networks-Climate Data Records (PERSIANN-CDR) as case study. In-situ precipitation observations from three meteorological station sets with different densities-the sparse (50), medium (200), dense (727) station set-were adopted to evaluate the effect of gauge density on the performance of SPE-gauge data blending. Two widely-used indices-standardized precipitation index (SPI) and self-calibrating Palmer drought severity index (SC_PDSI)-were used as case studies. Except the case of sparse 50-station subset, the SPE-gauge blending shows apparent improvement to the raw PERSIANN-CDR data, for both the accuracy of precipitation input and many aspects of drought monitoring, e.g. reproducing drought magnitude and revealing spatial pattern of drought, in which SC_PDSI shows more significant improvement than SPI. The dense 727-station set shows the largest improvement in the blending data, but the corresponding station-only interpolations also exhibit comparable performance to the blending data, indicating lower utilization value of the SPE data for these cases. Only the blending results of the medium-density 200-station set shows satisfactory drought monitoring performance as well as significant improvements relative to the station-only interpolations. According to the quantitative analyses, the medium density (about 50-75 gauges per 10(6) km(2) in our cases) might be the most economic gauge density for SPE-gauge blending, as it has satisfactory improvement in blending resu