Please use this identifier to cite or link to this item: http://117.252.14.250:8080/jspui/handle/123456789/4777
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dc.contributor.authorHong, Seungbum-
dc.contributor.authorLakshmi, Venkat-
dc.contributor.authorSmall, Eric E.-
dc.contributor.authorChen, Fei-
dc.date.accessioned2020-09-10T15:15:33Z-
dc.date.available2020-09-10T15:15:33Z-
dc.date.issued2009-
dc.identifier.urihttp://117.252.14.250:8080/jspui/handle/123456789/4777-
dc.description.abstractThe 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.en_US
dc.language.isoenen_US
dc.publisherAllied Publishers Pvt. Ltd., New Delhien_US
dc.subjectRainfallen_US
dc.subjectHydrometeorologyen_US
dc.subjectEcologyen_US
dc.subjectHigh Resolution Land Data Assimilation System (HRLDAS)en_US
dc.subjectNoah Land Surface Model (Noah LSM)en_US
dc.title2-The Influence of the Land Surface on Hydrometeorology and Ecology - New Advances from Modelling and Satellite Remote Sensing.en_US
dc.typeOtheren_US
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



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