气候变化领域集成服务门户(CCPortal): The influence of assimilating leaf area index in a land surface model on global water fluxes and storages

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DOI	10.5194/hess-24-3775-2020
	The influence of assimilating leaf area index in a land surface model on global water fluxes and storages
	Zhang X.; Maggioni V.; Rahman A.; Houser P.; Xue Y.; Sauer T.; Kumar S.; Mocko D.
发表日期	2020
ISSN	1027-5606
起始页码	3775
结束页码	3788
卷号	24 期号:7
英文摘要	Vegetation plays a fundamental role not only in the energy and carbon cycles but also in the global water balance by controlling surface evapotranspiration (ET). Thus, accurately estimating vegetation-related variables has the potential to improve our understanding and estimation of the dynamic interactions between the water, energy, and carbon cycles. This study aims to assess the extent to which a land surface model (LSM) can be optimized through the assimilation of leaf area index (LAI) observations at the global scale. Two observing system simulation experiments (OSSEs) are performed to evaluate the efficiency of assimilating LAI into an LSM through an ensemble Kalman filter (EnKF) to estimate LAI, ET, canopy-interception evaporation (CIE), canopy water storage (CWS), surface soil moisture (SSM), and terrestrial water storage (TWS). Results show that the LAI data assimilation framework not only effectively reduces errors in LAI model simulations but also improves all the modeled water flux and storage variables considered in this study (ET, CIE, CWS, SSM, and TWS), even when the forcing precipitation is strongly positively biased (extremely wet conditions). However, it tends to worsen some of the modeled water-related variables (SSM and TWS) when the forcing precipitation is affected by a dry bias. This is attributed to the fact that the amount of water in the LSM is conservative, and the LAI assimilation introduces more vegetation, which requires more water than what is available within the soil. © 2020 Author(s).
语种	英语
scopus关键词	Carbon; Evapotranspiration; Soil moisture; Surface measurement; Vegetation; Water supply; Canopy interception; Ensemble Kalman Filter; Land surface modeling; Land surface models; Observing system simulation experiments; Surface evapotranspiration; Surface soil moisture; Terrestrial water storage; Digital storage; evaporation; evapotranspiration; leaf area index; precipitation (climatology); soil moisture; soil-vegetation interaction; water flux; water storage
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159341
作者单位	Zhang, X., Department of Civil Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, United States; Maggioni, V., Department of Civil Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, United States; Rahman, A., Department of Civil Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, United States; Houser, P., Department of Civil Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, United States; Xue, Y., Department of Civil Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, United States; Sauer, T., Department of Civil Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 20771, United States; Kumar, S., Hydrological Sciences Laboratory, Nasa Goddard Space Flight Center, Greenbelt, MD 20771, United States; Mocko, D., Hydrological Sciences Laboratory, Nasa Goddard Space Flight Center, ...
推荐引用方式 GB/T 7714	Zhang X.,Maggioni V.,Rahman A.,et al. The influence of assimilating leaf area index in a land surface model on global water fluxes and storages[J],2020,24(7).
APA	Zhang X..,Maggioni V..,Rahman A..,Houser P..,Xue Y..,...&Mocko D..(2020).The influence of assimilating leaf area index in a land surface model on global water fluxes and storages.Hydrology and Earth System Sciences,24(7).
MLA	Zhang X.,et al."The influence of assimilating leaf area index in a land surface model on global water fluxes and storages".Hydrology and Earth System Sciences 24.7(2020).