RESUMO
Spaceborne radars offer a unique three-dimensional view of the atmospheric components of the Earth's hydrological cycle. Existing and planned spaceborne radar missions provide cloud and precipitation information over the oceans and land difficult to access in remote areas. A careful look into their measurement capabilities indicates considerable gaps that hinder our ability to detect and probe key cloud and precipitation processes. The international community is currently debating how the next generation of spaceborne radars shall enhance current capabilities and address remaining gaps. Part of the discussion is focused on how to best take advantage of recent advancements in radar and space platform technologies while addressing outstanding limitations. First, the observing capabilities and measurement highlights of existing and planned spaceborne radar missions including TRMM, CloudSat, GPM, RainCube, and EarthCARE are reviewed. Then, the limitations of current spaceborne observing systems, with respect to observations of low-level clouds, midlatitude and high-latitude precipitation, and convective motions, are thoroughly analyzed. Finally, the review proposes potential solutions and future research avenues to be explored. Promising paths forward include collecting observations across a gamut of frequency bands tailored to specific scientific objectives, collecting observations using mixtures of pulse lengths to overcome trade-offs in sensitivity and resolution, and flying constellations of miniaturized radars to capture rapidly evolving weather phenomena. This work aims to increase the awareness about existing limitations and gaps in spaceborne radar measurements and to increase the level of engagement of the international community in the discussions for the next generation of spaceborne radar systems.
RESUMO
The Global Precipitation Measurement satellite's Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR) are designed to provide the most accurate instantaneous precipitation estimates currently available from space. The GPM Combined Algorithm (CORRA) plays a key role in this process by retrieving precipitation profiles that are consistent with GMI and DPR measurements; therefore it is desirable that the forward models in CORRA use the same geophysical input parameters. This study explores the feasibility of using internally consistent emissivity and surface backscatter cross section (σ 0) models for water surfaces in CORRA. An empirical model for DPR Ku and Ka σ 0 as a function of 10m wind speed and incidence angle is derived from GMI-only wind retrievals under clear conditions. This allows for the σ 0 measurements, which are also influenced by path-integrated attenuation (PIA) from precipitation, to be used as input to CORRA and for wind speed to be retrieved as output. Comparisons to buoy data give a wind rmse of 3.7 m/s for Ku+GMI and 3.2 m/s for Ku+Ka+GMI retrievals under precipitation (compared to 1.3 m/s for clear-sky GMI-only), and there is a reduction in bias from the GANAL background data (-10%) to the Ku+GMI (-3%) and Ku+Ka+GMI (-5%) retrievals. Ku+GMI retrievals of precipitation increase slightly in light (< 1 mm/hr) and decrease in moderate to heavy precipitation (> 1mm/hr). The Ku+Ka+GMI retrievals, being additionally constrained by the Ka reflectivity, increase only slightly in moderate and heavy precipitation at low wind speeds (< 5 m/s) relative to retrievals using the surface reference estimate of PIA as input.