Rainfall retrieval over the ocean with spaceborne W‐band radar

Abstract

[1] A method for retrieving precipitation over the ocean using spaceborne W-band (94 GHz) radar is introduced and applied to the CloudSat Cloud Profiling Radar. The method is most applicable to stratiform-type precipitation. Measurements of radar backscatter from the ocean surface are combined with information about surface wind speed and sea surface temperature to derive the path-integrated attenuation through precipitating cloud systems. The scattering and extinction characteristics of raindrops are modeled using a combination of Mie theory (for raindrops) and the discrete dipole approximation (for ice crystals and melting snow), and a model of the melting layer is implemented to represent the transition between ice and liquid water. Backward Monte Carlo modeling is used to model multiple scattering from precipitating hydrometeors between the radar and ocean surface, which is shown to be significant for precipitation rates exceeding 3-5 mm h À1 , particularly when precipitating ice is present. An uncertainty analysis is presented and the algorithm is applied to near-global CloudSat observations and compared with other near-global precipitation sources. In the tropics, CloudSat tends to underestimate the heaviest precipitation. It is found that in the middle latitudes, however, CloudSat observes precipitation more often and with greater resulting accumulation than other spaceborne sensors.

Improved rain rate and drop size retrievals from airborne Doppler radar

“…At moderate and heavy rain rates we expect R to be close to constant with height unless significant evaporation is evident (Haynes et al, 2009). N w may be expected to be close to values deemed typical by Marshall and Palmer (1948) or Testud et al (2001), i.e.…”

“…Hence we acknowledge that the simultaneous retrieval of cloud and precipitation in warm clouds from 94 GHz radar is a source of uncertainty that warrants further consideration (e.g. Haynes et al, 2009;Hawkness-Smith, 2010;Mace et al, 2016). The retrieved variables ( Fig.11a-e) and forward-modelled radar measurements (Fig.11f-j) are compared at 1 km a.s.l.…”

“…Consequently, operational CloudSat data products currently provide only rain detection over land and not rain rate estimates (e.g. Haynes et al, 2009;. Additional radar measurements that facilitate rain rate estimates over land would offer a significant improvement over existing satellite capabilities.…”

“…The path-integrated attenuation (PIA) can be estimated from the ocean surface backscatter relative to nearby clear-sky profiles (Meneghini et al, 1983) or calculated from sea surface wind speed and temperature (Haynes et al, 2009). Estimates of PIA are used in the rain retrieval algorithms of both TRMM (Iguchi et al, 2000;Meneghini and Liao, 2000) and CloudSat (L'Ecuyer and Haynes et al, 2009; over the ocean; however, the surface backscatter over the land is much more variable and difficult to characterise. Consequently, operational CloudSat data products currently provide only rain detection over land and not rain rate estimates (e.g.…”

“…Even light rain and drizzle make significant contributions to global precipitation at the surface (Haynes et al, 2009;Berg et al, 2010;Behrangi et al, 2012), while the vertical profile of precipitation can be used to estimate the transfer of latent heat (Nelson et al, 2016) and microphysical processes . The intensity and drop size distribution (DSD) of rain are subject to persistent errors in weather and climate models, which frequently produce excess drizzle from shallow maritime clouds (Stephens et al, 2010;Abel and Boutle, 2012).…”