气候变化领域集成服务门户(CCPortal): Improving the Snow Volume Scattering Algorithm in a Microwave Forward Model by Using Ground-Based Remote Sensing Snow Observations

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DOI	10.1109/TGRS.2021.3064309
	Improving the Snow Volume Scattering Algorithm in a Microwave Forward Model by Using Ground-Based Remote Sensing Snow Observations
	Dai, L.; Che, T.; Xiao, Lin; Akynbekkyzy, M.; Zhao, K.; Leppanen, L.
通讯作者	Che, T (通讯作者)，Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Peoples R China.
发表日期	2022
ISSN	0196-2892
EISSN	1558-0644
卷号	60
英文摘要	Volume scattering (VS) estimation plays a critical role in microwave emission modeling of the snowpack. However, it is challenging to obtain VS accurately for different frequencies by using the microwave emission model of layered snowpacks (MEMLS), which is one of the representative microwave emission models. This article develops a new VS method to consider frequency and exponential correlation length based on a snowfield campaign from November 2015 to April 2016 in Altay, China. Compared with the commonly used empirical and improved Born approximation (IBA) algorithms, the proposed VS algorithm exhibits better performances at both 18 and 36 GHz with a wide range of snow grain sizes. The bias of brightness temperatures at vertical polarization from the proposed algorithm against the observed brightness temperatures are 1.1 K and x2212;0.4 K at 18 and 36 GHz, respectively; the root mean square errors (RMSEs) are 1.8 K and 2.6 K, respectively. The RMSEs decreased by 16.2 K at 18 GHz and 6.5 K at 36 GHz compared with those from the empirical methods and by 2.1 K and 22.2 K compared with those from the IBA. This work demonstrates that the VS difference between 18 and 36 GHz is larger and the dependence of VS on grain size is weaker than those represented by existing methods.
关键词	RADIATIVE-TRANSFER THEORY QUASI-CRYSTALLINE APPROXIMATION WATER EQUIVALENT EMISSION MODEL RADIOMETER DATA WET SNOW DEPTH BOREAL ASSIMILATION SNOWPACKS
英文关键词	Snow; Microwave theory and techniques; Temperature measurement; Radiometers; Brightness temperature; Biological system modeling; Correlation; Microwave emission model of layered snowpacks (MEMLS); passive microwave (PM); snow cover; volume scattering (VS)
语种	英语
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000730619400011
来源期刊	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/254074
作者单位	[Dai, L.; Akynbekkyzy, M.] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Remote Sensing Gansu Prov, Heihe Remote Sensing Expt Res Stn, Lanzhou 730000, Peoples R China; [Che, T.] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Peoples R China; [Che, T.] Chinese Acad Sci, Ctr Excellence Tibetan Plateau Earth Sci, Beijing 100101, Peoples R China; [Xiao, Lin] Sichuan Agr Univ, Coll Forestry, Natl Forestry & Grassland Adm, Key Lab Forest Resources Conservat & Ecol Safety, Chengdu 611130, Peoples R China; [Zhao, K.] Chinese Acad Sci, Northeast Inst Geog & Agroecol, Changchun 130102, Peoples R China; [Leppanen, L.] Space & Earth Observat Ctr, Finnish Meteorol Inst, Sodankyla 99600, Finland
推荐引用方式 GB/T 7714	Dai, L.,Che, T.,Xiao, Lin,et al. Improving the Snow Volume Scattering Algorithm in a Microwave Forward Model by Using Ground-Based Remote Sensing Snow Observations[J]. 中国科学院西北生态环境资源研究院,2022,60.
APA	Dai, L.,Che, T.,Xiao, Lin,Akynbekkyzy, M.,Zhao, K.,&Leppanen, L..(2022).Improving the Snow Volume Scattering Algorithm in a Microwave Forward Model by Using Ground-Based Remote Sensing Snow Observations.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,60.
MLA	Dai, L.,et al."Improving the Snow Volume Scattering Algorithm in a Microwave Forward Model by Using Ground-Based Remote Sensing Snow Observations".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 60(2022).