Impacts Analysis of Typical Spectral Absorption Models on Geostationary Millimeter Wave Atmospheric Radiation Simulation
CHEN Hao1,2, WANG Hao3*, HAN Wei3, GU Song-yan4, ZHANG Peng4, KANG Zhi-ming1
1. Jiangsu Meteorological Observatory, Nanjing 210008, China
2. Key Laboratory of Transportation Meteorology, China Meteorological Administration, Nanjing 210008, China
3. Numerical Weather Prediction Center of China Meteorological Administration, Beijing 100081, China
4. National Satellite Meteorological Center, Beijing 100081, China
Abstract：To analyze atmospheric radiation characteristics of geostationary millimeter wave remote sensing, three different typical spectral absorption line database based line-by-line millimeter wave atmospheric absorption models, Millimeter-wave Propagation Model(MPM), ROSenkranz Model (ROS), High-resolution TRAN smission molecular absorption Model(HITRAN), were applied. Under different atmospheric temperature, pressure and water vapor conditions, the differences between the three models were analyzed on 424 GHz, which are planned to add to a geostationary satellite. A multi-layer millimeter wave radiative transfer model was presented. By utilizing intensively observing radiosonde data of Shanghai, simulated millimeter wave radiations of Fengyun 3B(FY3B) microwave humidity sounder (MWHS) were calculated under the three atmospheric absorption models. The simulations were compared with the real observations of FY3B MWHS, with temporal-spatial matching. The accuracy of the three models was analyzed. Simulations show that, for 424 GHz channels, the trends of the three models’ results are the same over atmospheric temperature, pressure and water vapor. The values of MPM and ROS are much closer to each other than HITRAN. The performance of MPM is better than ROS and HITRAN. Simulation errors in channel 5 are less than channel 3 and 4 of FY3B/MWHS.
Key words：Multi-layer millimeter wave radiative transfer model; Microwave and millimeter-wave spectral absorption line database; Line-by-line absorption model; Geostationary millimeter wave remote sensing; Resonant and non-resonant absorption
[1] Ogut M, Bosch-Lluis X, Reising S C. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(8): 5344.
[2] Zou C Z, Goldberg M D, Hao X. Science Advances, 2018, 4: eaau0049.
[3] Hou X, Han Y, Hu X, et al. Journal of Meteorological Research, 2019, 33(4): 695.
[4] LU Nai-meng, DING Lei, ZHENG Xiao-bing, et al（卢乃锰，丁 雷，郑小兵, 等）. Journal of Remote Sensing（遥感学报）, 2020, 24(6): 672.
[5] LU Nai-meng, GU Song-yan（卢乃锰, 谷松岩）. Advances in Meteorological Science and Technology（气象科技进展）, 2016, 6(1): 120.
[6] Saunders R, Hocking J, Turner E, et al. Geoscientific Model Development, 2018, 11: 2717.
[7] Moradi I, Goldberg M, Brath M, et al. Journal of Geophysical Research: Atmospheres, 2020, 125(6), e2019JD031831.
[8] Golovachev Y, Etinger A, Pinhasi G A, et al. Journal of Applied Physics, 2019, 125(15): 151612.
[9] Makarov D S, Vilkov I N, Koshelev M A, et al. Radiophysics and Quantum Electronics, 2018, 60(10): 808.
[10] Hill C, Gordon I E, Kochanov R V, et al. Journal of Quantitative Spectroscopy and Radiative Transfer, 2016, 177: 4.
