Please use this identifier to cite or link to this item: http://117.252.14.250:8080/jspui/handle/123456789/4777
Title: 2-The Influence of the Land Surface on Hydrometeorology and Ecology - New Advances from Modelling and Satellite Remote Sensing.
Authors: Hong, Seungbum
Lakshmi, Venkat
Small, Eric E.
Chen, Fei
Keywords: Rainfall
Hydrometeorology
Ecology
High Resolution Land Data Assimilation System (HRLDAS)
Noah Land Surface Model (Noah LSM)
Issue Date: 2009
Publisher: Allied Publishers Pvt. Ltd., New Delhi
Abstract: The importance of land surface processes has long been recognized in hydrometeorology and ecology for they play a key role in climate and weather modeling. However their quantification has been challenging due to the complex nature of the land surface amongst various other reasons. One of the difficult parts in the quantification is the effect of vegetation which are related to land surface processes such soil moisture variation and to atmospheric conditions such as radiation. This study addresses various relational investigations among vegetation properties such as Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Surface Temperature (TSK) and Vegetation Water Content (VegWC) derived from satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) and EOS Advanced Microwave Scanning Radiometer (AMSR-E). The study provides general information about a physiological behavior of vegetation for various environmental conditions. Second, using a coupled mesoscale/land surface model, we examined the effects of vegetation and its relationship with soil moisture on the simulated land-atmospheric interactions through the model sensitivity tests. The Weather Research and Forecasting (VVRF) model was selected for this study and the Noah Land Surface Model (Noah LSM) implemented in the WRF model was used for the model coupled system. This coupled model was tested through two parameterization methods for vegetation fraction using MODIS data and through model initialization of soil moisture from High Resolution Land Data Assimilation System (HRLDAS). Then, this study evaluates the model improvements for each simulation method.
URI: http://117.252.14.250:8080/jspui/handle/123456789/4777
Appears in Collections:Proceedings of the International Conference on Water, Environment, Energy and Society (WEES-2009), 12-16 January 2009 at New Delhi, India, Vol.-1



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.