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101 results for “Land Surface Model”
Improved cross-scale snow cover simulations by developing a scale-aware parameterization in the Noah-MP land surface model
<p>Noah-MP data used to support the analyses conducted by Abolafia-Rosenzweig et al.: <strong>Improved </strong><strong>cross-scale </strong><strong>snow cover simulations by developing a scale-aware parameterization in the Noah-MP land surface model</strong></p>
Land surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation and land cover parameters
<p>The datasets archived here include simulation results shown in the paper, “Land surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation and land cover parameters”, published in Hydrology and Earth System Sciences (Maertens et al., 2021). The simulations were conducted over the South-American Dry Chaco and output on the different water budget components was produced with three land surface models (CLM2.0, CLSM-F2.5, and Noah3.6) embedded in the NASA Land Information System (LIS). The default LIS parameters were revised with (i) improved soil parameters, (ii) satellite-based interannually varying vegetation indices (leaf area index and green vegetation fraction), and (iii) yearly land cover information. For each experiment described in the manuscript, we provide daily netcdf files (0.125° resolution, period Jan 1992 – Dec 2015). The conducted experiments are simulations with (i) default LIS parameters (BL), (ii) updated soil parameters (REV<sub>s</sub>) and (iii) interannualy varying vegetation and land cover parameters (REV<sub>SV</sub>).<br> For details, please refer to</p> <p>Maertens, M., De Lannoy, G. J. M., Apers, S., Kumar, S. V., and Mahanama, S. P. P.: Land Surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation and land cover parameters, Hydrology and Earth System Sciences.</p> <p>Please contact Michiel Maertens (michiel.maertens@kuleuven.be) or Gabriëlle De Lannoy (gabrielle.delannoy@kuleuven.be) for any questions.</p>
Code and Data: WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America
<p>Data and code used to obtain results published in Garcia-Garcia et al 2021: WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America. Submited to<em> Geosci. Model Dev</em>.</p>
Impact of updating vegetation information on land surface model performance
<p>ECLand model outputs generated and analyzed during the study "<span>Impact of updating vegetation information on land surface model performance</span>"</p>
Validation of a new global irrigation scheme in the ORCHIDEE land surface model - Dataset
<p>Datasets used in the paper 'Validation of a new global irrigation scheme in the ORCHIDEE land surface model', submitted to GMD</p>
Net Primary Production (NPP) estimates from 4 Land Surface Modelling (LSM) in Fennoscandia 1997-2013
<p>The file "Dec1997_Dec2013_4LSM_subCLINF_npp_.RData" contains NPP (Net Primary Production) estimates from 4 Land Surface Modelling (LSM): JULES, ORCHIDEE-MICT, ORCHIDEE-HLveg and CLM5 over the nordic area encompassing Norway, Sweden, Finland and western Russia (58.25-71.25 North and 4.75-34.75 East).</p> <p>The data is used in the paper: <a href="https://www.biogeosciences-discuss.net/bg-2019-252/">Leibovici DG</a>, Quegan S, Comyn-Platt E, Hayman G, Val Martin M, Guimberteau M, Druel A, Zhu D, and Ciais P (2020) Spatio-Temporal Variations and Uncertainty in Land Surface Modelling for High Latitudes: Univariate Response Analysis.<strong> Biogeosciences (accepted 5Feb2020) </strong></p>
Correlation Analysis and Simulation Modeling of Land use Land Cover change and its Link with Land surface temperature
<p>The uploaded data is related to LULC modeling. Data consist of driving variables and correlation analysis between LST and NDVI in different LULC classes.</p>
Merged HLS2 (L30), ERA5-Land inputs and sample predictions of land surface temperature for the IBM granite-geospatial-land-surface-temperature model
<p>This dataset contains merged Harmonized Landsat-Sentinel 2 (HLS2) (L30 only) and ERA5-Land data following the UTM CRS:WGS84. It has been assembled for predicting land surface temperature with a fine-tuned granite geospatial foundation model developed by IBM Research. In addition, we include sample predictions of land surface temperature derived from this model. Please see https://huggingface.co/ibm-granite/granite-geospatial-land-surface-temperature for more information on data preparation and model use.</p> <p><strong>HLS:</strong></p> <p>Masek, J., J. Ju, J. Roger, S. Skakun, E. Vermote, M. Claverie, J. Dungan, Z. Yin, B. Freitag, C. Justice. HLS Sentinel-2 MSI Surface Reflectance Daily Global 30m v2.0. 2021, distributed by NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/HLS/HLSS30.002 </p> <h4><strong>ERA5-Land:<br></strong></h4> <p>Copernicus Climate Change Service, Climate Data Store, (2024): ERA5-land post-processed daily-statistics from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: <a href="https://doi.org/10.24381/cds.e9c9c792">10.24381/cds.e9c9c792</a> (Accessed on 05-11-2024)</p> <h4><strong>LST-predictions:</strong></h4> <p>These predictions of land surface temperature are derived from the IBM granite-geospatial-land-surface-temperature model and have been made available for Abidjan, Côte d’Ivoire and Johannesburg, South Africa for the period 2013-2023. </p> <h4>Attribution</h4> <p>Copernicus programme:</p> <p>Contains modified Copernicus Climate Change Service information [2024]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.</p> <p><strong>Data</strong></p> <p>Muñoz Sabater, J., Comyn-Platt, E., Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N., Cagnazo, C., Cucchi, M. (2024): ERA5-land post-processed daily-statistics from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: <a href="https://doi.org/10.24381/cds.e9c9c792">10.24381/cds.e9c9c792</a> (Accessed on 05-11-2024)</p>
Novel representation of leaf phenology improves simulation of Amazonian evergreen forest photosynthesis in a land surface model
<p>This dataset contains the LAI, Litterfall and GPP etc. of the four Amazon FLUX sites (BR-Sa1, BR-Sa3, BR-Ma2 and GF-Guy) simulated using the improved ORCHIDEE model and the corresponding FLUXNET eddy-covariance or ground-measured data. The more detial please the ReadMe.pdf in the zip.</p> <p>Data is organized with netCDF4(.nc).</p> <p><br> If you want to know more detail please contact: chenxzh73@mail.sysu.edu.cn</p>
GLDAS CLM Land Surface Model L4 3 hourly 1.0 x 1.0 degree Subsetted V001 (GLDAS_CLM10SUBP_3H) at GES DISC
With the upgraded Land Surface Models (LSMs) and updated forcing data sets, the GLDAS version 2.1 (GLDAS-2.1) production stream serves as a replacement for GLDAS-001. The entire GLDAS-001 collection from January 1979 through March 2020 was decommissioned on June 30, 2020 and removed from the GES DISC system. For more information, please see the IMPORTANT NOTICE document.This data set contains a series of land surface parameters simulated from the Common Land Model (CLM) V2.0 model in the Global Land Data Assimilation System (GLDAS). The data are in 1.0 degree resolution and range from January 1979 to present. The temporal resolution is 3-hourly. This simulation was forced by a combination of NOAA/GDAS atmospheric analysis fields, spatially and temporally disaggregated NOAA Climate Prediction Center Merged Analysis of Precipitation (CMAP) fields, and observation based downward shortwave and longwave radiation fields derived using the method of the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET). The simulation was initialized on 1 January 1979 using soil moisture and other state fields from a GLDAS/CLM model climatology for that day of the year. WGRIB or another GRIB reader is required to read the files. 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.
GLDAS Noah Land Surface Model L4 3 hourly 0.25 x 0.25 degree V2.1 (GLDAS_NOAH025_3H) at GES DISC
NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present. GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.GLDAS-2.1 data products are now available in two production streams: one stream is forced with combined forcing data including GPCP version 1.3 (the main production stream), and the other stream is processed without this forcing data (the early production stream). Since the GPCP Version 1.3 data have a 3-4 month latency, the GLDAS-2.1 data products are first created without it, and are designated as Early Products (EPs), with about 1.5 month latency. Once the GPCP Version 1.3 data become available, the GLDAS-2.1 data products are processed in the main production stream and are removed from the Early Products archive.This data product, reprocessed in January 2020, is for GLDAS-2.1 Noah 3-hourly 0.25 degree data from the main production stream and it is a replacement to its previous version.The 3-hourly data product was simulated with the Noah Model 3.6 in Land Information System (LIS) Version 7. The data product contains 36 land surface fields from January 2000 to present. The GLDAS-2.1 data are archived and distributed in NetCDF format. The GLDAS-2.1 products supersede their corresponding GLDAS-1 products.The GLDAS-2.1 simulation started on January 1, 2000 using the conditions from the GLDAS-2.0 simulation. This simulation was forced with National Oceanic and Atmospheric Administration (NOAA)/Global Data Assimilation System (GDAS) atmospheric analysis fields (Derber et al., 1991), the disaggregated Global Precipitation Climatology Project (GPCP) V1.3 Daily Analysis precipitation fields (Adler et al., 2003; Huffman et al., 2001), and the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET) radiation fields. The simulation used with GDAS and GPCP only from 2000 to February 2001, followed by addition of AGRMET for March 1, 2001 onwards.In October 2020, all 3-hourly and monthly GLDAS-2 data were post-processed with the MOD44W MODIS land mask. Previously, some grid boxes over inland water were considered as over land and, thus, had non-missing values. The post-processing corrected this issue and masked out all model output data over inland water; the post-processing did not affect the meteorological forcing variables. More information can be found in the GLDAS-2 README. The MOD44W MODIS land mask is available on the GLDAS Project site.If you had downloaded the GLDAS data prior to November 2020, please download the data again to receive the post-processed data.
GLDAS Noah Land Surface Model L4 monthly 1.0 x 1.0 degree Early Product V2.1 (GLDAS_NOAH10_M_EP) at GES DISC
NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present. GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.GLDAS-2.1 data products are now available in two production streams: one stream is forced with combined forcing data including GPCP version 1.3 (the main production stream), and the other stream is processed without this forcing data (the early production stream). Since the GPCP Version 1.3 data have a 3-4 month latency, the GLDAS-2.1 data products are first created without it, and are designated as Early Products (EPs), with about 1.5 month latency. Once the GPCP Version 1.3 data become available, the GLDAS-2.1 data products are processed in the main production stream and are removed from the Early Products archive. This data product is an Early Product for GLDAS-2.1 Noah 1.0 degree monthly dataset. The monthly data product was generated through temporal averaging of GLDAS-2.1 Noah 3-hourly data simulated with the Noah Model 3.6 in Land Information System (LIS) Version 7. The data product contains 36 land surface fields from January 2000 to present.The GLDAS-2.1 simulation started on January 1, 2000 using the conditions from the GLDAS-2.0 simulation. This simulation was forced with National Oceanic and Atmospheric Administration (NOAA)/Global Data Assimilation System (GDAS) atmospheric analysis fields (Derber et al., 1991), the disaggregated Global Precipitation Climatology Project (GPCP) V1.3 Daily Analysis precipitation fields (Adler et al., 2003; Huffman et al., 2001), and the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET) radiation fields. The simulation used with GDAS and GPCP only from 2000 to February 2001, followed by addition of AGRMET for March 1, 2001 onwards.The GLDAS-2.1 products supersede their corresponding GLDAS-1 products.The GLDAS-2.1 data are archived and distributed in NetCDF format.
GLDAS Catchment Land Surface Model L4 3 hourly 1.0 x 1.0 degree Early Product V2.1 (GLDAS_CLSM10_3H_EP) at GES DISC
NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present. GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.GLDAS-2.1 data products are now available in two production streams: one stream is forced with combined forcing data including GPCP version 1.3 (the main production stream), and the other stream is processed without this forcing data (the early production stream). Since the GPCP Version 1.3 data have a 3-4 month latency, the GLDAS-2.1 data products are first created without it, and are designated as Early Products (EPs), with about 1.5 month latency. Once the GPCP Version 1.3 data become available, the GLDAS-2.1 data products are processed in the main production stream and are removed from the Early Products archive. This data product is an Early Product for GLDAS-2.1 Catchment 1.0 degree 3-hourly dataset. The GLDAS-2.1 3 hourly 1.0 degree product was simulated with the Catchment-F2.5 Land Surface Model in Land Information System (LIS) Version 7. The data product contains 34 land surface fields from January 2000 to present. The GLDAS-2.1 simulation started on January 1, 2000 using the conditions from the GLDAS-2.0 simulation. This simulation was forced with National Oceanic and Atmospheric Administration (NOAA)/Global Data Assimilation System (GDAS) atmospheric analysis fields (Derber et al., 1991), the disaggregated Global Precipitation Climatology Project (GPCP) V1.3 Daily Analysis precipitation fields (Adler et al., 2003; Huffman et al., 2001), and the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET) radiation fields. The simulation used with GDAS and GPCP only from 2000 to February 2001, followed by addition of AGRMET for March 1, 2001 onwards.The GLDAS-2.1 products supersede their corresponding GLDAS-1 products.The GLDAS-2.1 data are archived and distributed in NetCDF format.
GLDAS VIC Land Surface Model L4 3 hourly 1.0 x 1.0 degree Early Product V2.1 (GLDAS_VIC10_3H_EP) at GES DISC
NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present. GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.GLDAS-2.1 data products are now available in two production streams: one stream is forced with combined forcing data including GPCP version 1.3 (the main production stream), and the other stream is processed without this forcing data (the early production stream). Since the GPCP Version 1.3 data have a 3-4 month latency, the GLDAS-2.1 data products are first created without it, and are designated as Early Products (EPs), with about 1.5 month latency. Once the GPCP Version 1.3 data become available, the GLDAS-2.1 data products are processed in the main production stream and are removed from the Early Products archive. This data product is an Early Product for GLDAS-2.1 VIC 1.0 degree 3-hourly dataset. The GLDAS-2.1 VIC 1.0 degree 3-hourly data product was simulated with the VIC Land Surface Model 4.1.2 in Land Information System (LIS) Version 7. The data product contains 34 land surface fields from January 2000 to present.The GLDAS-2.1 simulation started on January 1, 2000 using the conditions from the GLDAS-2.0 simulation. This simulation was forced with National Oceanic and Atmospheric Administration (NOAA)/Global Data Assimilation System (GDAS) atmospheric analysis fields (Derber et al., 1991), the disaggregated Global Precipitation Climatology Project (GPCP) V1.3 Daily Analysis precipitation fields (Adler et al., 2003; Huffman et al., 2001), and the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET) radiation fields. The simulation used with GDAS and GPCP only from 2000 to February 2001, followed by addition of AGRMET for March 1, 2001 onwards.The GLDAS-2.1 products supersede their corresponding GLDAS-1 products.The GLDAS-2.1 data are archived and distributed in NetCDF format.
NLDAS Noah Land Surface Model L4 Monthly 0.125 x 0.125 degree V2.0 (NLDAS_NOAH0125_M) at GES DISC
This data set contains fifty-two fields 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 netCDF (converted from the GRIB format). The NLDAS-2 monthly Noah model data, containing fifty-two fields, 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. Details about the NLDAS-2 configuration of the Noah LSM can be found in Xia et al. (2012).
NLDAS Noah Land Surface Model L4 Monthly Climatology 0.125 x 0.125 degree V2.0 (NLDAS_NOAH0125_MC) at GES DISC
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.
NLDAS VIC Land Surface Model L4 Monthly Climatology 0.125 x 0.125 degree V2.0 (NLDAS_VIC0125_MC) at GES DISC
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. The temporal resolution is monthly, ranging from January to December. The NLDAS-2 monthly climatology data are the NLDAS-2 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 VIC LSM data can be found from the NLDAS_VIC0125_H_2.0 and NLDAS_VIC0125_M_2.0 landing pages.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).For more information, please see the README Document.
GLDAS Noah Land Surface Model L4 3 hourly 1.0 x 1.0 degree V2.0 (GLDAS_NOAH10_3H) at GES DISC
NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present. GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.This data product, GLDAS-2.0 1.0 degree 3-hourly, was reprocessed and replaced its previous data product on November 22, 2019. The data product contains a series of land surface parameters simulated from the Noah Model 3.6, and currently covers from January 1948 to December 2014, but will be extended as the data becomes available. The GLDAS-2.0 data are archived and distributed in netCDF format.The GLDAS-2.0 model simulations were initialized on simulation date January 1, 1948, using soil moisture and other state fields from the LSM climatology for that day of the year. The simulations were forced by the global meteorological forcing data set from Princeton University (Sheffield et al., 2006). Each simulation uses the common GLDAS data sets for land water mask (MOD44W: Carroll et al., 2009) and elevation (GTOPO30) along with the model default land cover and soils datasets. Noah model uses the Modified IGBP MODIS 20-category vegetation classification and the soil texture based on the Hybrid STATSGO/FAO) datasets. The MODIS based land surface parameters are used in the current GLDAS-2.0 and GLDAS-2.1 products while the AVHRR base parameters were used in GLDAS-1 and previous GLDAS-2 products (prior to October 2012). The land mask was modified to accommodate the river routing scheme included in the simulations in the fall 2019 update. In October 2020, all 3-hourly and monthly GLDAS-2 data were post-processed with the MOD44W MODIS land mask. Previously, some grid boxes over inland water were considered as over land and, thus, had non-missing values. The post-processing corrected this issue and masked out all model output data over inland water; the post-processing did not affect the meteorological forcing variables. More information can be found in the GLDAS-2 README. The MOD44W MODIS land mask is available on the GLDAS Project site.If you had downloaded the GLDAS data prior to November 2020, please download the data again to receive the post-processed data.
GLDAS Catchment Land Surface Model L4 monthly 1.0 x 1.0 degree V2.1 (GLDAS_CLSM10_M) at GES DISC
NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present. GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.GLDAS-2.1 data products are now available in two production streams: one stream is forced with combined forcing data including GPCP version 1.3 (the main production stream), and the other stream is processed without this forcing data (the early production stream). Since the GPCP Version 1.3 data have a 3-4 month latency, the GLDAS-2.1 data products are first created without it, and are designated as Early Products (EPs), with about 1.5 month latency. Once the GPCP Version 1.3 data become available, the GLDAS-2.1 data products are processed in the main production stream and are removed from the Early Products archive. This data product is for GLDAS-2.1 Catchment monthly 1.0 degree data from the main production stream. It was generated through temporal averaging of GLDAS-2.1 3-hourly data simulated with the Catchment-F2.5 Land Surface Model in Land Information System (LIS) Version 7. The data product contains 34 land surface fields from January 2000 to present. The GLDAS-2.1 data are archived and distributed in NetCDF format. The GLDAS-2.1 simulation started on January 1, 2000 using the conditions from the GLDAS-2.0 simulation. This simulation was forced with National Oceanic and Atmospheric Administration (NOAA)/Global Data Assimilation System (GDAS) atmospheric analysis fields (Derber et al., 1991), the disaggregated Global Precipitation Climatology Project (GPCP) V1.3 Daily Analysis precipitation fields (Adler et al., 2003; Huffman et al., 2001), and the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET) radiation fields. The simulation used with GDAS and GPCP only from 2000 to February 2001, followed by addition of AGRMET for March 1, 2001 onwards.In October 2020, all 3-hourly and monthly GLDAS-2 data were post-processed with the MOD44W MODIS land mask. Previously, some grid boxes over inland water were considered as over land and, thus, had non-missing values. The post-processing corrected this issue and masked out all model output data over inland water; the post-processing did not affect the meteorological forcing variables. More information can be found in the GLDAS-2 README. The MOD44W MODIS land mask is available on the GLDAS Project site.If you had downloaded the GLDAS data prior to November 2020, please download the data again to receive the post-processed data.
FLDAS2 Noah-MP GDAS Land Surface Model L4 Central Asia Daily 0.01 degree x 0.01 degree V001 (FLDAS_NOAHMP001_G_CA_D)
This dataset contains land surface parameters simulated by the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System version 2 (FLDAS2) Central Asia model. The FLDAS2 Central Asia model is a custom instance of the NASA Land Information System that has been adapted to work with domains, data streams, and monitoring and forecast requirements associated with food security assessment in data-sparse, developing country settings. The data are produced using the Noah Multi-Parameterization (Noah-MP) version 4.0.1 Land Surface Model (LSM) forced by Global Data Assimilation System (GDAS) meteorological data.The FLDAS2 Central Asia dataset is produced daily with a one-day latency. Data are available from October 1, 2000 to present. The dataset contains 27 parameters at a 0.01 degree spatial resolution over the Central Asia region (30-100°E, 21-56°N).
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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