Precipitation retrieval by the L1‐norm regularization: Typhoon Hagibis case

Abstract

AbstractThis study examines precipitation retrieval by the L1‐norm regularization using the infrared brightness temperatures from the Himawari‐8/Advanced Himawari Imager (AHI) of the typhoon Hagibis and analyses the advantages of high temporal resolution data. The AHI data covering the entire life cycle of typhoon Hagibis are implemented and we label “precipitation” and “non‐precipitation” fields‐of‐view (FOVs) based on the variation of brightness temperature gradient in AHI channels 8–16. In the precipitation FOVs, we implement the L1‐norm regularization where contribution rate of the “input variable” in the objective functional is obtained by approximating the degree of freedom for signal. The proposed approach is an effective method to obtain sparse solutions, which can express most or all atomic information by a small amount of atomic information. Several experiments reveal that the retrieved precipitation of typhoon Hagibis exhibits good structural similarity in consistency with the global precipitation measurement (GPM) precipitation values. In particular, the proposed approach provides better structural similarity (SSIM) and peak signal‐to‐noise ratio (PSNR) value compared with the random forest method, which is beneficial in extreme precipitation.