High resolution rain retrieval from SeaWinds scatterometer data

A wind scatterometer is a radar designed to measure near-surface winds from space. It does this indirectly by measuring the normalized radar backscatter of the ocean's surface from multiple azimuth angles. These high precision backscatter measurements are used to estimate the near-surface vector wind (speed and direction) over the ocean with the aid of a geophysical model function relating the vector wind and the surface backscatter. Rain can adversely affect the accuracy of the scatterometer wind estimates by (1) attenuating the radar signal, (2) perturbing the surface, and (3) adding backscatter from falling drops. The precise effect is dependent on radar frequency, the surface wind and wave conditions and the rain rate, but results in decreased wind measurement accuracy when no compensated for. For example, high rain rates lead to excessive wind speed estimates.

The sensitivity of Ku-band scatterometer backscatter to rain can be exploited to estimate the rain rate by simultaneously retrieving the vector wind (wind speed and direction) and the rain rate using a modified geophysical model function which accounts for both wind and rain. Rain rates derived from the SeaWinds scatterometer have been successfully validated against Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and TRMM microwave imager (TMI) data, as well as Next Generation Weather Radar (NEXRAD). SeaWinds-derived rain rates are unbiased, but exhibit greater variability due to noise than the other sensors. The technique is particularly useful for flagging rain-contaminated wind estimates.

The relatively large (25 km by 35 km) footprint of conventional SeaWinds observations is much larger than typical rain cells and limits the spatial resolution of the SeaWinds rain rate observations. However, the measurement geometry and sampling characteristics of SeaWinds are particularly well-suited for applying reconstruction/resolution enhancement algorithms to generate higher resolution backscatter estimates. These algorithms exploit the oversampling and spatial overlap of SeaWinds measurements to produce backscatter measurements on a 2.5 km resolution grid. Such measurements have been used to retrieve winds at this high spatial resolution. The high resolution wind observations find application in severe weather events and in near-coastal studies.

Here, we consider the use of enhanced resolution SeaWinds scatterometer backscatter observations for high resolution simultaneous wind/rain retrieval. Because of the noise-level of the enhanced resolution backscatter measurements, adjoining observations are combined prior to the application of simultaneous wind/rain retrieval. This degrades the effective resolution, but also reduces the noise in the rain estimates, resulting in a tradeoff between noise level and resolution. Simulation and actual data are used to validate the accuracy of the rain estimates. Although accurate in many conditions, the simultaneous wind/rain retrieval method when used with enhanced resolution SeaWinds backscatter measurements can be ill-conditioned for certain wind directions and measurement geometries, sometimes yielding spurious rain rates in zero rain conditions. This can be a limiting factor in the utility of SeaWinds-derived rain estimates at low rain rates, but does not impact rain rates over 2 mm/hr. It is thus particularly useful in hurricanes. The technique is effective in identifying rain and where conventionally retrieved winds are contaminated by excessive rain.

The high resolution SeaWinds-derived rain fields reveal significant mesoscale features including convective events associated with anonymous winds estimates in conventional wind-only retrieval. SeaWinds-derived high resolution rain rates over hurricanes are compared with TRMM PR and TMI rain observations and with NEXRAD observations. The effective resolution of the SeaWinds-derived rains is lower that TRMM PR, but superior to TRMM TMI. The mean rain rates are similar, though as expected, the SeaWinds-derived rain estimates exhibit greater variability and some wind-dependent biases. We conclude that high resolution SeaWinds-derived rain rates can be a useful tool for monitoring hurricanes and other severe weather events and that the rain rate estimates are useful for rain-flagging conventional SeaWinds-derived wind estimates.