Short Name:

NCA-LDAS Noah-3.3 Land Surface Model L4 Daily 0.125 x 0.125 degree V001 (NCALDAS_NOAH0125_D) at GES DISC

The National Climate Assessment - Land Data Assimilation System, or NCA-LDAS, is an integrated terrestrial water analysis system created for sustained assessment, analyses, and dissemination of hydrologic indicators in support of the United States NCA activities. The current primary features are high resolution, gridded, daily time series of terrestrial water and energy balance stores, states, and fluxes over the continental U.S., derived from land surface hydrologic modeling with multivariate assimilation of satellite Environmental Data Records (EDRs). The overall goal is to improve scientific understanding, adaptation, and management of hydrologic and related energy resources during a changing climate. The NCA-LDAS data products were simulated for the continental United States for the satellite era from January 1979 to December 2015. The core of NCA-LDAS is the multivariate assimilation of past and current satellite based data records within the Noah Version 3.3 land-surface model (LSM) at 1/8th degree resolution using NASA's Land Information System (LIS; Kumar et al. 2006) software framework during the Earth observing satellite era. The temporal resolution is daily. The file format is NetCDF. NCA-LDAS includes 42 variables including land-surface fluxes (e.g. precipitation, radiation and latent and sensible heat, etc.), stores (e.g. soil moisture and snow), states (e.g., surface temperature), and routing variables (e.g., runoff, streamflow, flooded area, etc.), driven by the atmospheric forcing data from North American Land Data Assimilation System Phase 2 (NLDAS-2; Xia et al., 2012). NCA-LDAS builds upon NLDAS through the addition of multivariate assimilation of earth observations such as soil moisture (Kumar et al, 2014), snow (Liu et al, 2015; Kumar et al, 2015a) and irrigation (Ozdagon et al, 2010; Kumar et al, 2015b). The EDRs that have been assimilated into the NCA-LDAS include soil moisture and snow depth from principally microwave sensors such as SMMR, SSM/I, AMSR-E, ASCAT, AMSR-2 and SMOS, irrigation intensity estimates from MODIS, and snow covered area from multispectral sensors such as AVHRR and MODIS, and the multisensor IMS snow product.

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