A 1DVAR retrieval applied to GMI: Algorithm description, validation, and sensitivities

Abstract

AbstractA fully physical, 1‐D variational inversion algorithm (1DVAR) has been developed to simultaneously retrieve total precipitable water (TPW), 10 m wind speed, and cloud liquid water path (CLWP) over ocean. Results presented are for the Global Precipitation Measurement Microwave Imager (GMI), but the algorithm is adaptable to any microwave imager. The Colorado State University 1DVAR is novel in that the observation error covariances are not assumed to be zero and empirical orthogonal functions are utilized to retrieve the structure of the water vapor profile, aided by GMI's high‐frequency channels. Validation against radiosonde and ocean buoy observations demonstrates a near zero bias for wind speed and a small positive bias for water vapor, respectively, with RMS errors that rival those of benchmark products. RMS errors against validation are 2.6 mm and 1.2 m/s for TPW and wind speed. No calibration adjustments were made to achieve these results, and no “truth” data were used to train the algorithm. The advantages of this fully physical inversion are its adaptability, transparency, and full description of retrieval errors. Sensitivities of the algorithm are explored in detail.