Raindrop Signature from Microwave Radiometer Over Deserts. Issue 16 (10th August 2020)

• Record Type: Journal Article
• Authors: You, Yalei; Joseph Munchak, S.; Ferraro, Ralph; Mohr, Karen; Peters‐Lidard, Christa; Prigent, Catherine; Ringerud, Sarah; Rudlosky, Scott; Wang, Heshun; Norouzi, Hamidreza; Prakash, Satya
• Is Part Of: Geophysical research letters. Volume 47:Issue 16(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-08-10
• Subjects: Rainfall -- desert -- raindrop emission; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2020GL088656
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Rainfall estimates from spaceborne microwave radiometers form the foundation of global precipitation data sets. Since the beginning of the satellite microwave rainfall estimation era in the 1980s, the primary signature leveraged over land for these estimates has been the brightness temperature (TB) depression due to ice particle scattering. Contrary to this practice, time series analyses based on observations from two spaceborne radars and two spaceborne radiometers reveal a TB increase at H19 due to raindrop emission as the primary cloud particle signature over desert terrain. Low surface emissivity supports the use of liquid raindrop emission as the primary signature over desert surfaces. In these regions, the surface rain rate better correlates with the liquid raindrop emission signal than with the scattering induced by ice further aloft, suggesting a new potential for improving rainfall estimation over deserts by exploiting the liquid raindrop emission signature. Plain Language Summary: Global rainfall mapping is a very challenging task since ground‐based observations from radars or rain‐gauges are limited or unavailable over many regions (e.g., desert). Satellite observations provide the unique opportunity to map the rainfall over these regions. Deserts cover about one third of the Earth's land surface, while the current satellite rainfall estimate techniques over deserts relate the ice particles aloft with surface rain rates, leading to large estimation uncertainties. This study for the first time reports the liquid raindrop signature over deserts from the satellite observations, which could represent a fundamental algorithm change over deserts when estimating rainfall from space. Key Points: Time series analyses reveal a TB increase at H19 due to raindrop emission as the primary cloud signature over deserts Low surface emissivity supports the use of raindrop emission as the primary signature over deserts Surface rain rate better correlates with the raindrop emission signal than with the scattering induced by ice further aloft