[대기] 기상기후세미나 (김동혁 박사, 서울대학교)
일시 : 2026-10-08(목) 14:30 ~ 15:30
연사 : 김동혁 박사
소속 : Institute of Natural Sciences, Yonsei University
문의 : 강준호(leonardo47@snu.ac.kr )
장소 : 501동 1층 목암홀
Title: Representing cloud hydrometeors for passive microwave radiative transfer simulations
[Abstract]
Spaceborne microwave sensors can detect the radiative signatures of hydrometeors. Particularly, the brightness temperatures (TBs) measured by microwave radiometers reflect the combined signatures of absorption, emission, and scattering by hydrometeors. These signatures are governed by the microphysical properties of hydrometeors, including number, size, density, and shape. To utilize the microphysical information contained in satellite microwave TB observations, cloud-precipitation estimation algorithms and all-sky data assimilation frameworks require high-quality, physically reliable radiative transfer simulations. To achieve this, two major issues should be considered: (1) maintaining microphysical consistency in the simulation framework and (2) improving scattering calculations for nonspherical ice particles. This presentation reviews methods of cloud hydrometeor representation, from conventional approaches to recently proposed methods that address these two issues. In particular, two state-of-the-art methods developed to satisfy these considerations for improved radiative transfer simulations are presented. Both methods implement the self-similar Rayleigh-Gans approximation (SSRGA) to improve scattering calculations for nonspherical ice particles. The first method, SSRGA-OPT, combines SSRGA with the optimal habit selection method, which identifies the optimal predefined particle habit according to riming conditions. The second method, SSRGA-PARA, employs the riming-dependent SSRGA formulations to represent nonspherical ice particles as synthetic habit mixtures. Both methods effectively leverage the diverse SSRGA particle habits to represent varying microphysical properties of nonspherical ice particles, enhancing microphysical consistency in the radiative transfer simulation framework. The simulation performance of the proposed methods was evaluated against the Global Precipitation Measurement Mission Microwave Imager (GMI) observations for 15 typhoon cases. The methods reduced the simulation biases and uncertainties arising from the conventional spherical assumption and one-shape-fits-all approach. Furthermore, the methods exhibited strong simulation performance, yielding good histogram agreement between the GMI TB simulations and observations.
[Abstract]
Spaceborne microwave sensors can detect the radiative signatures of hydrometeors. Particularly, the brightness temperatures (TBs) measured by microwave radiometers reflect the combined signatures of absorption, emission, and scattering by hydrometeors. These signatures are governed by the microphysical properties of hydrometeors, including number, size, density, and shape. To utilize the microphysical information contained in satellite microwave TB observations, cloud-precipitation estimation algorithms and all-sky data assimilation frameworks require high-quality, physically reliable radiative transfer simulations. To achieve this, two major issues should be considered: (1) maintaining microphysical consistency in the simulation framework and (2) improving scattering calculations for nonspherical ice particles. This presentation reviews methods of cloud hydrometeor representation, from conventional approaches to recently proposed methods that address these two issues. In particular, two state-of-the-art methods developed to satisfy these considerations for improved radiative transfer simulations are presented. Both methods implement the self-similar Rayleigh-Gans approximation (SSRGA) to improve scattering calculations for nonspherical ice particles. The first method, SSRGA-OPT, combines SSRGA with the optimal habit selection method, which identifies the optimal predefined particle habit according to riming conditions. The second method, SSRGA-PARA, employs the riming-dependent SSRGA formulations to represent nonspherical ice particles as synthetic habit mixtures. Both methods effectively leverage the diverse SSRGA particle habits to represent varying microphysical properties of nonspherical ice particles, enhancing microphysical consistency in the radiative transfer simulation framework. The simulation performance of the proposed methods was evaluated against the Global Precipitation Measurement Mission Microwave Imager (GMI) observations for 15 typhoon cases. The methods reduced the simulation biases and uncertainties arising from the conventional spherical assumption and one-shape-fits-all approach. Furthermore, the methods exhibited strong simulation performance, yielding good histogram agreement between the GMI TB simulations and observations.
첨부파일 (1개)
- Abstract(10.08).pdf (45 KB, download:4)
