Abstract
Error characterization is vital for the advancement of precipitation algorithms, the evaluation of numerical model outputs, and their integration in various hydro-meteorological applications. The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) has been a benchmark for successive Global Precipitation Measurement (GPM) based products. This has given way to the evolution of many multi-satellite precipitation products. This study evaluates the performance of the newly released multi-satellite Multi-Source Weighted-Ensemble Precipitation (MSWEP) product, whose temporal variability was determined based on several data products including TMPA 3B42 RT. The evaluation was conducted over India with respect to the IMD-gauge-based rainfall for pre-monsoon, monsoon, and post monsoon seasons at daily scale for a 35-year (1979–2013) period. The rainfall climatology is examined over India and over four geographical extents within India known to be subject to uniform rainfall. The performance evaluation of rainfall time series was carried out. In addition to this, the performance of the product over different rainfall classes was evaluated along with the contribution of each class to the total rainfall. Further, seasonal evaluation of the MSWEP products was based on the categorical and volumetric indices from the contingency table. Upon evaluation it was observed that the MSWEP products show large errors in detecting the higher quantiles of rainfall (>75th and > 95th quantiles). The MSWEP precipitation product available at a 0.25° × 0.25° spatial resolution and daily temporal resolution matched well with the daily IMD rainfall over India. Overall results suggest that a suitable region and season-dependent bias correction is essential before its integration in hydrological applications. While the MSWEP was observed to perform well for daily rainfall, it suffered from poor detection capabilities for higher quantiles, making it unsuitable for the study of extremes.
Highlights
Precipitation is a crucial variable that drives the atmosphere’s general circulation through latent heat release
To examine the rainfall climatology over India, four different geographical regions are selected based on the uniformity of precipitation over them
It can be observed that while there seems to be a good match during the JJAS season, for the post-monsoon and pre-monsoon seasons, the Multi-Source Weighted-Ensemble Precipitation (MSWEP) tends to overestimate the annual mean rainfall
Summary
Precipitation is a crucial variable that drives the atmosphere’s general circulation through latent heat release. Quantifying its spatiotemporal variability holds paramount importance in fields of hydrology, atmospheric and environmental science, etc. Examining precipitation variability by maintaining a dense network of ground-based rain gauges or Doppler weather radar networks can often be prohibitively costly, especially for developing nations. This gap is duly filled by satellite-based precipitation products made available at a high spatial and temporal resolution. Precipitation estimation from satellites are either based on the indirect relationship of cloud-top temperature by infrared sensors, cloud characteristics of reflectivity by visible sensors, or the sources and sinks of microwave radiations during interaction with atmospheric hydrometeors. While the Climate 2017, 5, 2; doi:10.3390/cli5010002 www.mdpi.com/journal/climate
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
