The data set contains the monthly statistics for the SOILM0-100cm variable (0-100 cm top 1 meter soil moisture content) of the North American Land Data Assimilation System Version 2 (NLDAS-2) model. The period of analysis is from 1979-01-02 to 2013-12-31. The statistics for each calendar month are the mean, standard deviation, minimum, maximum, and percentiles in 0.05 interval. The data set also includes a p-value per calendar month of the Kolmogorov-Smirnov (KS) test. The p-value of the KS test shows if the computed empirical cumulative distribution function (CDF) comes from a fitted normal distribution

The goal of NLDAS is to construct quality-controlled, and spatially and temporally consistent, land-surface model (LSM) datasets from the best available observations and model output to support modeling activities. Specifically, this system is intended to reduce the errors in the stores of soil moisture and energy which are often present in numerical weather prediction models, and which degrade the accuracy of forecasts. NLDAS is currently running in near real-time on a 1/8th-degree grid over central North America; retrospective NLDAS datasets and simulations also extend back to January 1979. NLDAS constructs a forcing dataset from gauge-based observed precipitation data (temporally disaggregated using Stage II radar data), bias-correcting shortwave radiation, and surface meteorology reanalyses to drive several different LSMs to produce model outputs of surface fluxes, soil moisture, and snow cover. NLDAS is a collaboration project among several groups: NOAA/NCEP's Environmental Modeling Center (EMC), NASA's Goddard Space Flight Center (GSFC), Princeton University, the University of Washington, the NOAA/NWS Office of Hydrological Development (OHD), and the NOAA/NCEP Climate Prediction Center (CPC). NLDAS is a core project with support from NOAA's Climate Prediction Program for the Americas (CPPA). Data from the project can be accessed from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) as well as from the NCEP/EMC NLDAS website. This service provides access to NASA's North American Land Data Assimilation System (NLDAS) hourly Mosaic land surface model data.

This data set contains thirty-eight fields simulated from the Mosaic land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing and range from Jan 1979 to the present. The temporal resolution is hourly. The file format is netCDF (converted from the GRIB format).Mosaic was developed by Koster and Suarez (1994, 1996) to account for subgrid vegetation variability with a tile approach. Each vegetation tile carries its own energy and water balance and soil moisture and temperature. Each tile has three soil layers, with the first two in the root zone. In NLDAS, Mosaic is configured to support a maximum of 10 tiles per grid cell with a 5% cutoff that ignores vegetation classes covering less than 5% of the cell. Additionally in NLDAS, all tiles of Mosaic in a grid cell have a predominant soil type and three soil layers with fixed thickness values of 10, 30, and 160 cm (hence constant rooting depth of 40 cm and constant total column depth of 200 cm). Details about the NLDAS-2 configuration of the Mosaic LSM can be found in Xia et al. (2012).

The goal of NLDAS is to construct quality-controlled, and spatially and temporally consistent, land-surface model (LSM) datasets from the best available observations and model output to support modeling activities. Specifically, this system is intended to reduce the errors in the stores of soil moisture and energy which are often present in numerical weather prediction models, and which degrade the accuracy of forecasts. NLDAS is currently running in near real-time on a 1/8th-degree grid over central North America; retrospective NLDAS datasets and simulations also extend back to January 1979. NLDAS constructs a forcing dataset from gauge-based observed precipitation data (temporally disaggregated using Stage II radar data), bias-correcting shortwave radiation, and surface meteorology reanalyses to drive several different LSMs to produce model outputs of surface fluxes, soil moisture, and snow cover. NLDAS is a collaboration project among several groups: NOAA/NCEP's Environmental Modeling Center (EMC), NASA's Goddard Space Flight Center (GSFC), Princeton University, the University of Washington, the NOAA/NWS Office of Hydrological Development (OHD), and the NOAA/NCEP Climate Prediction Center (CPC). NLDAS is a core project with support from NOAA's Climate Prediction Program for the Americas (CPPA). Data from the project can be accessed from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) as well as from the NCEP/EMC NLDAS website. This service provides access to NASA's North American Land Data Assimilation System (NLDAS) hourly Mosaic land surface model data.

Smerge-Noah-CCI root zone soil moisture 0-40 cm L4 daily 0.125 x 0.125 degree V2.0 is a multi-decadal root-zone soil moisture product. Smerge is developed by merging the North American Land Data Assimilation System (NLDAS) land surface model output with surface satellite retrievals from the European Space Agency Climate Change Initiative. The data have a 0.125 degree resolution at a daily time-step, covering the entire continental United States and spanning nearly four decades (January 1979 to May 2019).This data product contains root-zone soil moisture of 0 - 40 cm layer, Climate Change Initiative (CCI) derived soil moisture anomalies of 0-40 cm layer, and a soil moisture data estimation flag.This data product is the recommended replacement for the AMSR-E/Aqua root zone soil moisture L3 1 day 25 km x 25 km descending and 2-Layer Palmer Water Balance Model V001 product (LPRM_AMSRE_D_RZSM3), which will be removed from archive on June 27, 2022. Smerge provides a better root zone soil moisture estimation because it has higher data quality and longer temporal coverage.

This data set contains a series of land surface parameters simulated from the VIC land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing and range from Jan 1979 to the present. The temporal resolution is hourly. The file format is WMO GRIB-1. Details about the NLDAS-2 configuration of the VIC LSM can be found in Xia et al. (2012). The version of the VIC model for the NLDAS-2 VIC data available from the NASA GES DISC is VIC-4.0.3; this version of the VIC model is the same as used in Sheffield et al. (2003). The VIC model was developed at the University of Washington and Princeton University as a macroscale, semi-distributed, grid-based, hydrologic model [Liang et al., 1994; Wood et al., 1997]. The full water and energy balance modes of VIC were used for NLDAS-2. VIC uses three soil layers, with thicknesses that vary spatially. The root zone depends on the vegetation type and its root distribution, and can span all three soil layers. The VIC model includes a two-layer energy balance snow model [Cherkauer et al., 2003]. The VIC LSM was forced by the hourly NLDAS-2 forcing "File A" files, and contains forty-three fields. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file (http://disc.sci.gsfc.nasa.gov/hydrology/grib_tabs/gribtab_NLDAS_VIC.002.txt) shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units. For information about the vertical layers of the Soil Moisture Content (PDS 086), Soil Temperature (PDS 085), and Liquid Soil Moisture Content (PDS 151), please see the README Document at ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS2.pdf or the GrADS ctl file at ftp://hydro1.sci.gsfc.nasa.gov/data/gds/NLDAS/NLDAS_VIC0125_H.002.ctl.

Land Data Assimilation System (LDAS) combines multiple sources of observations (such as precipitation gauge data, satellite data, and radar precipitation measurements) to produce estimates of climatological properties at or near the Earth''s surface. This dataset is the primary (default) forcing file (File A) for Phase 2 of the North American …

This data set contains a series of land surface parameters simulated from the Mosaic land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing and range from Jan 1979 to the present. The temporal resolution is hourly. The file format is WMO GRIB-1.

Details about the NLDAS-2 configuration of the Mosaic LSM can be found in Xia et al. (2012).

Mosaic was developed by Koster and Suarez (1994, 1996) to account for subgrid vegetation variability with a tile approach. Each vegetation tile carries its own energy and water balance and soil moisture and temperature. Each tile has three soil layers, with the first two in the root zone. In NLDAS, Mosaic is configured to support a maximum of 10 tiles per grid cell with a 5% cutoff that ignores vegetation classes covering less than 5% of the cell. Additionally in NLDAS, all tiles of Mosaic in a grid cell have a predominant soil type and three soil layers with fixed thickness values of 10, 30, and 160 cm (hence constant rooting depth of 40 cm and constant total column depth of 200 cm).

The Mosaic LSM was forced by the hourly NLDAS-2 forcing "File A" files, and contains thirty-seven fields. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units.

For information about the vertical layers of the Soil Moisture Content (PDS 086) and Soil Temperature (PDS 085), please see the README Document or the GrADS ctl file.

Scientists at NASA Goddard Space Flight Center generate groundwater and soil moisture drought indicators each week. They are based on terrestrial water storage observations derived from GRACE-FO satellite data and integrated with other observations, using a sophisticated numerical model of land surface water and energy processes.This data product is GRACE Data Assimilation for Drought Monitoring (GRACE-DA-DM) Global Version 3.0 from a global GRACE and GRACE-FO data assimilation and drought indicator product generation (Li et al., 2019). It varies from the other GRACE-DA-DM products which are from the U.S. GRACE-based drought indicator product generation (Houborg et al., 2012).The GRACE-DA-DM Global V3.0 is similar to the GRACE-DA-DM U.S. V4.0 product. Both products are based on the Catchment Land Surface Model (CLSM) Fortuna 2.5 version simulation that was created within the Land Information System data assimilation framework (Kumar et al., 2016). GRACE-DA-DM Global V3.0 drought indicator maps are derived from the GLDAS_CLSM025_DA1_D product, at 0.25 degree resolution, forced by ECMWF meteorological data, and assimilated RL06 GRACE and GRACE-FO data from the University of Texas at Austin (Save et al., 2016; Save, 2020). The GRACE-DA-DM U.S. V4.0 is at 0.125 degree, which is based on a model simulation (not published at GES DISC) forced by NLDAS-2 meteorological data and assimilated with RL06 GRACE/GRACE-FO data. More information on GRACE-DA-DM U.S. V4.0 and previous versions of the data can be found in the README.The GRACE-DA-DM Global V3.0 data product contains three drought indicators: Groundwater Percentile, Root Zone Soil Moisture Percentile, and Surface Soil Moisture Percentile. These drought indicators express wet or dry conditions as a percentile, indicating the probability of occurrence within the period of record from 1948 to 2014. The drought indicator data are daily, but available only one day (Monday) per week. The data have a spatial resolution of 0.25 x 0.25 degree with global coverage (60S, 180W, 90N, 180E), and a temporal range from February 2003 to present (with a 3-6 month latency). The data are archived in NetCDF format.The GRACE-DA-DM is an operational project which produces groundwater and soil moisture drought indicators each week. The operational data is available weekly with a 2-9 day latency from the NASA GRACE project home page found under the Documentation tab. The GRACE-DA-DM data distributed here at GESDISC is the final archive version, which is generated after the latest GRACE-FO data are available.

This U.S Geological Survey data release contains soil moisture, actual evapotranspiration, precipitation, and potential evapotranspiration by watershed for the United States from 1980 to 2020. Hourly values from NASA's North American Land Data Assimilation System Phase 2 (NLDAS-2) Noah model were aggregated to daily values and extracted by Geospatial Attributes of Gages for Evaluating Streamflow, version II (GAGES-II) watershed. The daily aggregated values include average soil moisture at four depths, 0 to 10 centimeters (SoilM_0_10cm), 10 to 40 centimeters (SoilM_10_40cm), 40 to 100 centimeters (SoilM_40_100cm), and 100 to 200 centimeters (SoilM_100_200cm); and total actual evapotranspiration (Evap), precipitation (Rainf), and potential evapotranspiration (PotEvap). Each daily value is presented in a table with a row from January 1, 1980 to December 31, 2020. Each column represents a GAGES-II watershed. References: Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow: U.S. Geological Survey dataset, https://doi.org/10.3133/70046617. Xia, Y.L., Mitchell, K., Ek, M., Sheffield, J., Cosgrove, B., Wood, E., Luo, L.F., Alonge, C., Wei, H.L., Meng, J., Livneh, B., Lettenmaier, D., Koren, V., Duan, Q.Y., Mo, K., Fan, Y., and Mocko, D., 2012, Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products: Journal Of Geophysical Research-Atmospheres, v. 117, D03109, https://doi.org/10.1029/2011jd016048. Xia, Y.L., Mitchell, K., Ek, M., Cosgrove, B., Sheffield, J., Luo, L.F., Alonge, C., Wei, H.L., Meng, J., Livneh, B., Duan, Q.Y., and Lohmann, D., 2012, Continental-scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2 (NLDAS-2): 2. Validation of model-simulated streamflow: Journal Of Geophysical Research-Atmospheres, v. 117, D03110, https://doi.org/10.1029/2011jd016051.

The goal of NLDAS is to construct quality-controlled, and spatially and temporally consistent, land-surface model (LSM) datasets from the best available observations and model output to support modeling activities. Specifically, this system is intended to reduce the errors in the stores of soil moisture and energy which are often present in numerical weather prediction models, and which degrade the accuracy of forecasts. NLDAS is currently running in near real-time on a 1/8th-degree grid over central North America; retrospective NLDAS datasets and simulations also extend back to January 1979. NLDAS constructs a forcing dataset from gauge-based observed precipitation data (temporally disaggregated using Stage II radar data), bias-correcting shortwave radiation, and surface meteorology reanalyses to drive several different LSMs to produce model outputs of surface fluxes, soil moisture, and snow cover. NLDAS is a collaboration project among several groups: NOAA/NCEP's Environmental Modeling Center (EMC), NASA's Goddard Space Flight Center (GSFC), Princeton University, the University of Washington, the NOAA/NWS Office of Hydrological Development (OHD), and the NOAA/NCEP Climate Prediction Center (CPC). NLDAS is a core project with support from NOAA's Climate Prediction Program for the Americas (CPPA). Data from the project can be accessed from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) as well as from the NCEP/EMC NLDAS website. This service provides access to NASA's North American Land Data Assimilation System (NLDAS) hourly Mosaic land surface model data.

This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing and range from Jan 1979 to the present. The temporal resolution is monthly. The file format is WMO GRIB-1. The NLDAS-2 monthly Noah model data were generated from the NLDAS-2 hourly Noah model data, as monthly accumulation for rainfall, snowfall, subsurface runoff, surface runoff, total evapotranspiration, snow melt, and monthly averages for other variables. The monthly period of each month is from 00Z at start of the month to 23:59Z at end of the month, with the exception of the very first month in the data set (Jan 1979) which starts at 00Z 02 Jan 1979. Also for the first month (Jan 1979), because the variables listed as instantaneous in the README file do not have valid data exactly on 00Z 02 Jan 1979, and this one hour is not included in the average for this month only.

A brief description about the NLDAS-2 monthly Noah model can be found from the dataset landing page for NLDAS_NOAH0125_H_002 and the NLDAS-2 README document.

Details about the NLDAS-2 configuration of the Noah LSM can be found in Xia et al. (2012).

The NLDAS-2 Noah monthly data contain fifty-two fields. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units.

For information about the vertical layers of the Soil Moisture Content (PDS 086), Soil Temperature (PDS 085), and Liquid Soil Moisture Content (PDS 151) please see the README Document or the GrADS ctl file.

The goal of the North American Land Data Assimilation System (NLDAS) is to construct quality-controlled, and spatially and temporally consistent, land-surface model (LSM) datasets from the best available observations and model output to support modeling activities. Specifically, this system is intended to reduce the errors in the stores of soil moisture and energy which are often present in numerical weather prediction models, and which degrade the accuracy of forecasts. NLDAS is currently running in near real-time on a 1/8th-degree grid over central North America; retrospective NLDAS datasets and simulations also extend back to January 1979. NLDAS constructs a forcing dataset from gauge-based observed precipitation data (temporally disaggregated using Stage II radar data), bias-correcting shortwave radiation, and surface meteorology reanalyses to drive several different LSMs to produce model outputs of surface fluxes, soil moisture, and snow cover. For more information visit: http://ldas.gsfc.nasa.gov/nldas/NLDAS is a collaboration project among several groups: NOAA/NCEP's Environmental Modeling Center (EMC), NASA's Goddard Space Flight Center (GSFC), Princeton University, the University of Washington, the NOAA/NWS Office of Hydrological Development (OHD), and the NOAA/NCEP Climate Prediction Center (CPC). NLDAS is a core project with support from NOAA's Climate Prediction Program for the Americas (CPPA). Data from the project can be accessed from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) as well as from the NCEP/EMC NLDAS website. Data from the project can be accessed from the NASA Goddard Earth Science Data and information Services Center (GES DISC), http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings, as well as from the NCEP/EMC NLDAS.For more information visit http://ldas.gsfc.nasa.gov/nldas/For more information visit http://ldas.gsfc.nasa.gov/nldas/For more information visit http://ldas.gsfc.nasa.gov/nldas/For more information visit http://ldas.gsfc.nasa.gov/nldas/For more information visit http://ldas.gsfc.nasa.gov/nldas/For more information visit http://ldas.gsfc.nasa.gov/nldas/

The goal of NLDAS is to construct quality-controlled, and spatially and temporally consistent, land-surface model (LSM) datasets from the best available observations and model output to support modeling activities. Specifically, this system is intended to reduce the errors in the stores of soil moisture and energy which are often present in numerical weather prediction models, and which degrade the accuracy of forecasts. NLDAS is currently running in near real-time on a 1/8th-degree grid over central North America; retrospective NLDAS datasets and simulations also extend back to January 1979. NLDAS constructs a forcing dataset from gauge-based observed precipitation data (temporally disaggregated using Stage II radar data), bias-correcting shortwave radiation, and surface meteorology reanalyses to drive several different LSMs to produce model outputs of surface fluxes, soil moisture, and snow cover. NLDAS is a collaboration project among several groups: NOAA/NCEP's Environmental Modeling Center (EMC), NASA's Goddard Space Flight Center (GSFC), Princeton University, the University of Washington, the NOAA/NWS Office of Hydrological Development (OHD), and the NOAA/NCEP Climate Prediction Center (CPC). NLDAS is a core project with support from NOAA's Climate Prediction Program for the Americas (CPPA). Data from the project can be accessed from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) as well as from the NCEP/EMC NLDAS website. This service provides access to NASA's North American Land Data Assimilation System (NLDAS) hourly Mosaic land surface model data.

The dataset contains minimum and maximum vapor pressure deficit (VPD) and soil moisture parameters that define the range of suboptimal vegetation function (i.e., between uninhibited photosynthesis and complete shutdown). The ranges were estimated using the Dynamic Canopy Biophysical Properties model (DCBP; Lowman & Barros 2018), which consists of a phenology forecasting model based on the growing season index (GSI), which provides a unitless measure of the potential phenologic state of vegetation based on the concurrent meteorological conditions (Jolly et al. 2005)., The Dynamic Canopy Biophysical Properties model (DCBP) was used to determine the range for suboptimal vegetation function for VPD and soil moisture (Lowman & Barros 2018). This model combines phenologic forecasting with data assimilation to estimate the environmental conditions under which photosynthesis operates. Maximum VPD, VPDmax, and minimum soil moisture, SMmin, denote when plants shut down photosynthetic activity due to water stress in the atmosphere and soil, respectively. The DCBP consists of a phenology forecasting model based on the growing season index (GSI), which provides a unitless measure of the potential phenologic state of vegetation based on the concurrent meteorological conditions (Jolly et al. 2005). In the DCBP, the meteorological conditions that affect plant growth and senescence include minimum daily temperature, daylength, VPD, and soil water potential (Lowman & Barros 2018). The GSI is used to determine a growth vector which takes into account the poten..., The DCBP parameters that determine the thresholds for VPD and soil moisture are stored in netCDF files. Each file is stored as a matrix on the NLDAS CONUS grid at 0.125° spatial resolution and represents the average of 2000 ensemble members. There are four separate files in total:

vpd_max_avg.nc: Maximum VPD threshold vpd_min_avg.nc: Minimum VPD threshold sm_max_avg.nc: Maximum soil moisture threshold sm_min_avg.nc: Minimum soil moisture threshold , # CONUS VPD and soil moisture thresholds for suboptimal vegetation function

https://doi.org/10.5061/dryad.stqjq2c6g

Description of the data and file structure

The DCBP parameters that determine the thresholds for VPD and soil moisture are stored in netCDF files. Each file is stored as a matrix on the NLDAS CONUS grid at 0.125° spatial resolution and represents the average of 2000 ensemble members. There are four separate files in total:

1. vpd_max_avg.nc: Maximum VPD threshold
2. vpd_min_avg.nc: Minimum VPD threshold
3. sm_max_avg.nc: Maximum soil moisture threshold
4. sm_min_avg.nc: Minimum soil moisture threshold

The units for VPD are kPa and the units for soil moisture are m3/m3. Missing data are stored as NaN and occur where pixels are labeled as water in the NLDAS-2 Land/Sea Mask.

Sharing/Access information

Data was derived from the following sources:

• Mitchell, K.E., Lohmann, D., Houser, P.R., Wood, E.F., Schaake, J...

This monthly climatology data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing. The temporal resolution is monthly, ranging from January to December. The NLDAS-2 monthly climatology data are the monthly data averaged over forty years (1981 - 2020). The file format is netCDF. The previous version of this dataset (NLDAS_MC 002) was a 30-year average and was stored in GRIB file format.

A brief description about the NLDAS-2 hourly and monthly Noah LSM data can be found from the dataset landing pages for NLDAS_NOAH0125_H_2.0 and NLDAS_NOAH0125_M_2.0.

Details about the NLDAS-2 configuration of the Noah LSM can be found in Xia et al. (2012).

For more information, please see the README Document.

The National Climate Assessment - Land Data Assimilation System, or NCA-LDAS, is a terrestrial water reanalysis in support of the United States Global Change Research Program's NCA activities. NCA-LDAS features high resolution, gridded, daily time series data products 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 provide the highest quality terrestrial hydrology products that enable improved scientific understanding, adaptation, and management of water and related energy resources during a changing climate.An overview of NCA-LDAS and its capability for developing climate change indicators are provided in Jasinski et al. (2019). Details on the data assimilation used in NCA-LDAS are described in Kumar et al. (2019). Sample mean annual trends are provided in the NCA-LDAS V2.0 README document.This NCA-LDAS version 2.0 data product was simulated for the continental United States for the satellite era from January 1979 to December 2016. 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. NCA-LDAS V001 data will no longer be available and have been superseded by V2.0.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 including SMMR, SSM/I, AMSR-E, ASCAT, AMSR-2, SMOS, and SMAP, irrigation intensity estimates from MODIS, and snow covered area from MODIS and from the multisensor IMS snow product.

This data set contains a series of land surface parameters simulated from the Noah land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing and range from Jan 1979 to the present. The temporal resolution is monthly. The file format is WMO GRIB-1. The NLDAS-2 monthly Noah model data were generated from the NLDAS-2 hourly Noah model data, as monthly accumulation for rainfall, snowfall, subsurface runoff, surface runoff, total evapotranspiration, and snow melt, and monthly average for other variables. Monthly period of each month is from 00Z at start of the month to 23:59Z at end of the month, except the first month (Jan 1979) that starts from 00Z 02 Jan 1979. Also for the first month (Jan 1979), because the variables listed as instantaneous in the README file (http://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS2.pdf) do not have valid data exactly on 00Z 02 Jan 1979, and this one hour is not included in the average for this month only.

Brief description about the NLDAS-2 monthly Noah model can be found from the GCMD DIF for GES_DISC_NLDAS_NOAH0125_H_V002 at http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_NOAH0125_H_V002.

Details about the NLDAS-2 configuration of the Noah LSM can be found in Xia et al. (2012).

The NLDAS-2 Noah monthly data contain fifty-two fields. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file (http://disc.sci.gsfc.nasa.gov/hydrology/grib_tabs/gribtab_NLDAS_NOAH.002.txt) shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units.

For information about the vertical layers of the Soil Moisture Content (PDS 086), Soil Temperature (PDS 085), and Liquid Soil Moisture Content (PDS 151) please see the README Document at ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS2.pdf or the GrADS ctl file at ftp://hydro1.sci.gsfc.nasa.gov/data/gds/NLDAS/NLDAS_NOAH0125_M.002.ctl.

Quality controlled soil depth data have been prepared using the field observation data and the missing data have been estimated with the model prediction using PIHM v2.0 (Soil: CZO soil data, Land Cover: CZO land cover product, Vegetation: PIHMgis, DEM: LIDAR 1m x1m spatial resolution, Bed rock: CZO geology coverage, Precipitation, Temperature, Vapor Pressure, Relative Humidity, Wind Speed and Solar Radiation using NLDAS - 2).

Le système d'assimilation des données terrestres (LDAS, Land Data Assimilation System) combine plusieurs sources d'observations (telles que les données des pluviomètres, les données satellite et les mesures radar des précipitations) pour produire des estimations des propriétés climatologiques à la surface de la Terre ou à proximité. Cet ensemble de données est le fichier de forçage principal (par défaut) (fichier A) pour la phase 2 du North American Land Data Assimilation System (NLDAS-2). Les données sont espacées d'un huitième de degré sur la grille et la résolution temporelle est d'une heure. NLDAS est un projet collaboratif entre plusieurs groupes : le Centre de modélisation environnementale (EMC) de NOAA/NCEP, le Centre de vol spatial Goddard (GSFC) de la NASA, l'université de Princeton, l'université de Washington, l'Office of Hydrological Development (OHD) de NOAA/NWS et le Centre de prévision climatique (CPC) de NOAA/NCEP. NLDAS est un projet essentiel soutenu par le programme de prédiction du climat pour les Amériques (CPPA) de la NOAA. Documentation : Readme Tutoriel Documentation GES DISC Hydrology Documentation sur les tiges de données GES DISC