Monday, 28 August 2023
Boundary Waters (Hyatt Regency Minneapolis)
Typically, precipitation radar retrieval algorithms assume that the precipitation is uniform throughout the radar resolution volume. For satellite-based radars, the far distance between the radar and the Earth’s surface causes the radar field-of-view (FOV) to have horizontal dimensions ranging from 5 to 10 km in diameter. Since the precipitation is not uniform over these large horizontal scales, the k-Z and R-Z relationships developed for uniform rain will produce underestimated rain rates if sub-FOV precipitation variability is not considered. Thus, satellite rainfall retrieval algorithms parameterize sub-FOV precipitation variability and include adjustments accounting for the variability not resolved in the FOV area-averaged measurements.
This study uses NASA HIWRAP (High-altitude Imaging Wind & Rain Airborne Profiler) radar observations while mounted to the Global Hawk during the NOAA SHOUT (Sensing Hazards with Operational Unmanned Technology) HRR (Hurricane Rapid Response) field campaign to examine spatial precipitation variability over open-ocean conditions. Specifically, the HIWRAP observations are processed to estimate path integrated attenuation (PIA), attenuation corrected reflectivity factor, and rain rate at the native sub-km FOV resolution. These high resolution PIA and reflectivity factor estimates are used to simulate satellite radar observations with FOVs ranging from 1 to 10 km. The simulated area-averaged PIA and reflectivity factors are then used to retrieve area-averaged rain rates, which are compared to the sub-km resolution rain rates accumulated over the same FOV. The analyzes show that the retrieved area-averaged rain rates are less than the reference rain rates with the difference increasing as the FOV precipitation variability increases. The reduction in retrieved rain rate is caused by an over-estimating the PIA, which causes the attenuation-corrected reflectivity factor to be underestimated.
Due to the detailed statistics needed to describe the impact of area-averaging on PIA and reflectivity factor, this presentation is well suited for a poster presentation.
This study uses NASA HIWRAP (High-altitude Imaging Wind & Rain Airborne Profiler) radar observations while mounted to the Global Hawk during the NOAA SHOUT (Sensing Hazards with Operational Unmanned Technology) HRR (Hurricane Rapid Response) field campaign to examine spatial precipitation variability over open-ocean conditions. Specifically, the HIWRAP observations are processed to estimate path integrated attenuation (PIA), attenuation corrected reflectivity factor, and rain rate at the native sub-km FOV resolution. These high resolution PIA and reflectivity factor estimates are used to simulate satellite radar observations with FOVs ranging from 1 to 10 km. The simulated area-averaged PIA and reflectivity factors are then used to retrieve area-averaged rain rates, which are compared to the sub-km resolution rain rates accumulated over the same FOV. The analyzes show that the retrieved area-averaged rain rates are less than the reference rain rates with the difference increasing as the FOV precipitation variability increases. The reduction in retrieved rain rate is caused by an over-estimating the PIA, which causes the attenuation-corrected reflectivity factor to be underestimated.
Due to the detailed statistics needed to describe the impact of area-averaging on PIA and reflectivity factor, this presentation is well suited for a poster presentation.

