气候变化领域集成服务门户(CCPortal): Auto-calibration system developed to assimilate AMSR-E data into a land surface model for estimating soil moisture and the surface energy budget

CCPortal

DOI	10.2151/jmsj.85A.229
	Auto-calibration system developed to assimilate AMSR-E data into a land surface model for estimating soil moisture and the surface energy budget
	Yang, Kun; Watanabe, Takahiro; Koike, Toshio; Li, Xin; Fuji, Hideyuki; Tamagawa, Katsunori; Ma, Yaoming; Ishikawa, Hirohiko
发表日期	2007
ISSN	0026-1165
EISSN	2186-9057
起始页码	229
结束页码	242
卷号	85A
英文摘要	Low-frequency microwave brightness temperature is strongly affected by near-surface soil moisture; therefore, it can be assimilated into a land surface model to improve modeling of soil moisture and the surface energy budget. This study presents a new variational land system used to assimilate AMSR-E brightness temperature of vertical polarization of 6.9 GHz and 18.7 GHz. The system consists of a land surface model (LSM) used to calculate surface fluxes and soil moisture, a radiative transfer model (RTM) to estimate the microwave brightness temperature, and an optimization scheme to search for optimal values of soil moisture by minimizing the difference between modeled and observed brightness temperature. The LSM is an improved simple biosphere model for sparse vegetation modeling and the RTM is a Q-h model that can account for the effects of surface roughness and vegetation. Several parameters in the LSM and RTM can significantly affect the outputs of the land data assimilation system but their values are either highly variable or unavailable. To solve this problem, we developed a dual-pass assimilation technique. Pass 1 inversely estimates the optimal values of the model parameters with long-term (similar to months) forcing data and brightness temperature data, while Pass 2 estimates the near-surface soil moisture in a daily assimilation cycle. This system is driven by well-established reanalysis data and global data sets of leaf area index, precipitation, and surface radiation, and was tested at a CEOP (Coordinate Enhanced Observing Period) reference site on the Tibetan Plateau. The system not only detected the effect of precipitation events that were missing in the forcing data, but also led to a significant improvement in modeling of the surface energy budget.
关键词	SOUTHERN GREAT-PLAINS REMOTE-SENSING DATA HETEROGENEOUS LANDSCAPE PARAMETERIZATION SIB2 ATMOSPHERIC GCMS SATELLITE DATA MICROWAVE DATA VEGETATION ALGORITHM SCALE
语种	英语
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:000246144200012
来源期刊	JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/257503
推荐引用方式 GB/T 7714	Yang, Kun,Watanabe, Takahiro,Koike, Toshio,et al. Auto-calibration system developed to assimilate AMSR-E data into a land surface model for estimating soil moisture and the surface energy budget[J]. 中国科学院青藏高原研究所,2007,85A.
APA	Yang, Kun.,Watanabe, Takahiro.,Koike, Toshio.,Li, Xin.,Fuji, Hideyuki.,...&Ishikawa, Hirohiko.(2007).Auto-calibration system developed to assimilate AMSR-E data into a land surface model for estimating soil moisture and the surface energy budget.JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN,85A.
MLA	Yang, Kun,et al."Auto-calibration system developed to assimilate AMSR-E data into a land surface model for estimating soil moisture and the surface energy budget".JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN 85A(2007).