Inter-calibration of Scatterometers and Radiometers Under Extreme Winds Using NOAA Hurricane Hunter Flight Data

• Main Authors: Rabaneda, Albert S., Portabella, Marcos, Grieco, Giuseppe, Polverari, Federica, Stoffelen, Ad, Sapp, Joe, Jelenak, Zorana, Chang, Paul
• Format: Still Image
• Language: English
• Published: European Space Agency 2022
• Subjects: Pacific; North Atlantic
• Online Access: http://hdl.handle.net/10261/331940

Living Planet Symposium, 23-27 May 2022, Bonn, Germany.-- 12 pages, figures, tables The US National Oceanic and Atmospheric Administration (NOAA) routinely operates “hurricane hunter” flights in the North Atlantic and North-East Pacific. Each flight is equipped with a Stepped Frequency Microwave Radiometer (SFMR) and GPS dropsondes for measuring surface winds, rain rate, sea surface temperature and vertical profiles of wind, pressure and temperature. Data from these in-situ measurements are freely available and are used for a satellite multi-sensor wind data inter-calibration procedure. This study is carried out in the framework of the ESA OCEAN+EXTREMES MAXSS project, and its goal is to obtain a consistent extreme wind data record for scatterometers and radiometers over the period 2010-2020. Over the mentioned period, there is a varying constellation of satellite scatterometers and radiometers. In particular, the following systems have been inter-calibrated: the scatterometers ASCAT-A, ASCAT-B, ASCAT-C, OSCAT (on OceanSat-2), OSCAT-2 (on ScatSat-1), Rapidscat (RSCAT), HY-2A and HY-2B, and the radiometers SMOS, SMAP, Windsat and AMSR-2. Collocated SFMR winds (calibrated with dropsondes) are used as extreme wind reference for inter-calibration purposes. Furthermore, this study also requires the use of to optimize the satellite-SMFR collocations. Storm Best Track (BT) data are used to collocate SFMR wind data in storm-motion centric coordinates with satellite data, and generate a Satellite-SFMR paired database. During the collocation process some thresholds are set, such as maximum time difference (Δt) and spatial difference (Δx) between measurements. After collocation, a comprehensive analysis of the different flags to apply is undertaken. Rigorous flagging can substantially reduce or even remove extreme wind measurements, while permissive flagging can introduce noise and outlier measurements into the filtered dataset. Therefore, the maximum SFMR rain rate threshold, several quality flags from different ...