Abstract:
AbstractMeasuring precipitation intensity is not straightforward; and over many areas, ground observations are lacking and satellite observations are used to fill this gap. The most common way of retrieving rainfall is by addressing the problem âtopâdownâ by inverting the atmospheric signals reflected or radiated by atmospheric hydrometeors. However, most applications are interested in how much water reaches the ground, a problem that is notoriously difficult to solve from a topâdown perspective. In this study, a novel âbottomâupâ approach is proposed that, by doing âhydrology backward,â uses variations in soil moisture (SM) sensed by microwave satellite sensors to infer preceding rainfall amounts. In other words, the soil is used as a natural rain gauge. Three different satellite SM data sets from the Advanced SCATterometer (ASCAT), the Advanced Microwave Scanning Radiometer (AMSRâE), and the Microwave Imaging Radiometer with Aperture Synthesis are used to obtain three new daily global rainfall products. The âFirst Guess Dailyâ product of the Global Precipitation Climatology Centre (GPCC) is employed as main benchmark in the validation period 2010â2011 for determining the continuous and categorical performance of the SMâderived rainfall products by considering the 5âday accumulated values. The realâtime version of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis product, i.e., the TRMMâ3B42RT, is adopted as a stateâofâtheâart satellite rainfall product. The SMâderived rainfall products show good Pearson correlation values (R) with the GPCC data set, mainly in areas where SM retrievals are found to be accurate. The global median R values (in the latitude band ±50°) are equal to 0.54, 0.28, and 0.31 for ASCATâ, AMSRâEâ, and SMOSâderived products, respectively. For comparison, the median R for the TRMMâ3B42RT product is equal to 0.53. Interestingly, the SMâderived products are found to outperform TRMMâ3B42RT in terms of average global rootâmeanâsquare error statistics and in terms of detection of rainfall events. The regions for which the SMâderived products perform very well are Australia, Spain, South and North Africa, India, China, the Eastern part of South America, and the central part of the United States. The SMâderived products are found to estimate accurately the rainfall accumulated over a 5âday period, an aspect particularly important for their use for hydrological applications, and that address the difficulties of estimating light rainfall from TRMMâ3B42RT.
