This data set contains fifty-three 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 hourly. The file format is netCDF (converted from the GRIB format).

The Noah model was developed as the land component of the NOAA NCEP mesoscale Eta model [Betts et al. (1997); Chen et al. (1997); Ek et al. (2003)]. As used in NLDAS-2, recent modifications were made to Noah's cold-season [Livneh et al. (2010)] and warm-season [Wei et al. (2012)] parameterizations. Noah serves as the land component in the evolving Weather Research and Forecasting (WRF) regional atmospheric model, the NOAA NCEP coupled Climate Forecast System (CFS), and the Global Forecast System (GFS). The model simulates the soil freeze-thaw process and its impact on soil heating/cooling and transpiration, following Koren et al. (1999). The model has four soil layers with spatially invariant thicknesses of 10, 30, 60, and 100 cm. The first three layers form the root zone in non-forested regions, with the fourth layer included in forested regions.

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

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.

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 hourly. The file format is WMO GRIB-1.

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

The Noah model was developed as the land component of the NOAA NCEP mesoscale Eta model [Betts et al. (1997); Chen et al. (1997); Ek et al. (2003)]. As used in NLDAS-2, recent modifications were made to Noah's cold-season [Livneh et al. (2010)] and warm-season [Wei et al. (2012)] parameterizations. Noah serves as the land component in the evolving Weather Research and Forecasting (WRF) regional atmospheric model, the NOAA NCEP coupled Climate Forecast System (CFS), and the Global Forecast System (GFS). The model simulates the soil freeze-thaw process and its impact on soil heating/cooling and transpiration, following Koren et al. (1999). The model has four soil layers with spatially invariant thicknesses of 10, 30, 60, and 100 cm. The first three layers form the root zone in non-forested regions, with the fourth layer included in forested regions.

The Noah LSM was forced by the hourly NLDAS-2 forcing "File A" files, and contains fifty-two 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), Soil Temperature (PDS 085), and Liquid Soil Moisture Content (PDS 151), please see the README Document or the GrADS ctl file.

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 monthly. The file format is WMO GRIB-1. The NLDAS-2 monthly Mosaic model data were generated from the NLDAS-2 hourly Mosaic 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.

A brief description about the NLDAS-2 monthly Mosaic model can be found from the GCMD DIF for NLDAS-2 hourly Mosaic data GES_DISC_NLDAS_MOS0125_H_V002.

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

The NLDAS-2 monthly Mosaic model data contain thirty-seven 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) and Soil Temperature (PDS 085), please see the README Document or the GrADS ctl file.

M2TMNXOCN (or tavgM_2d_ocn_Nx) is a time-averaged 2-dimensional monthly mean data collection in Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2). This collection consists of ocean surface diagnostics, such as open water skin temperature (sea surface temperature), open water latent energy flux, open water upward sensible heat flux, and open water net downward longwave ( or shortwave ) flux . The collection also includes variance of certain parameters.

MERRA-2 is the latest version of global atmospheric reanalysis for the satellite era produced by NASA Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-present with the latency of ~3 weeks after the end of a month.

Data Reprocessing: Please check “Records of MERRA-2 Data Reprocessing and Service Changes” linked from the “Documentation” tab on this page. Note that a reprocessed data filename is different from the original file.

MERRA-2 Mailing List: Sign up to receive information on reprocessing of data, changing of tools and services, as well as data announcements from GMAO. Contact the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov) to be added to the list.

Questions: If you have a question, please read "MERRA-2 File Specification Document", “MERRA-2 Data Access – Quick Start Guide”, and FAQs linked from the ”Documentation” tab on this page. If that does not answer your question, you may email the question on data access to the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov), or the question on science to the MERRA-2 science team (merra-questions@lists.nasa.gov).

This monthly climatology 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. The temporal resolution is monthly, ranging from January to December. The NLDAS-2 monthly climatology data are the monthly data averaged over the thirty years (1980 - 2009) of the NLDAS-2 monthly data. The file format is WMO GRIB-1.

A brief description about the NLDAS-2 hourly and monthly Mosaic LSM data can be found from the GCMD DIFs for GES_DISC_NLDAS_MOS0125_H_V002 and GES_DISC_NLDAS_MOS0125_M_V002.

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

The NLDAS-2 Mosaic model monthly climatology data set contains thirty-seven 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.

There are six vertical levels for the Soil Moisture (PDS 086) in the Mosaic GRIB files. For more information, please see the README Document or the GrADS ctl file.

The VIIRS/JPSS2 Active Fires 6-Min L2 Swath 375m NRT with short-name VNP14IMG_NRT is a Near Real Time (NRT) active fire detection data product (Schroeder 2014). The product is built on the EOS/MODIS fire product heritage [Kaufman et al., 1998; Giglio et al., 2003], using a multi-spectral contextual algorithm to identify sub-pixel fire activity and other thermal anomalies in the Level 1 (swath) input data. The algorithm uses all five 375 m VIIRS channels to detect fires and separate land, water, and cloud pixels in the image. Additional 750 m channels complement the available VIIRS multispectral data. Those channels are used as input to the baseline active fire detection product, which provides continuity to the EOS/MODIS 1 km Fire and Thermal Anomalies product.

The VIIRS 375 m fire detection data is a 6-min Level 2 swath product based on the input Science Data Record (SDR) Level 1 swath format. The NRT product is currently available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). The data are formatted as NetCDF4 files.

For more information read VIIRS 375 m Active Fire Algorithm User Guide at https://earthdata.nasa.gov/files/VIIRS_375m_Users_guide_Dec15_v2.pdf

and

Schroeder, W., Oliva, P., Giglio, L., & Csiszar, I. A. (2014). The New VIIRS 375m active fire detection data product: algorithm description and initial assessment. Remote Sensing of Environment, 143, 85-96. doi:10.1016/j.rse.2013.12.008 PDF from UMD

or

visit University of Maryland VIIRS Active Fire Web page at http://viirsfire.geog.umd.edu/

The Western Land Data Assimilation System (WLDAS), developed at Goddard Space Flight Center (GSFC) and funded by the NASA Western Water Applications Office, provides water managers and stakeholders in the western United States with a long-term record of near-surface hydrology for use in drought assessment and water resources planning. WLDAS leverages advanced capabilities in land surface modeling and data assimilation to furnish a system that is customized for stakeholders’ needs in the region. WLDAS uses NASA’s Land Information System (LIS) to configure and drive the Noah Multiparameterization (Noah-MP) Land Surface Model (LSM) version 3.6 to simulate land surface states and fluxes. WLDAS uses meteorological observables from the North American Land Data Assimilation System (NLDAS-2) including precipitation, incoming shortwave and longwave radiation, near surface air temperature, humidity, wind speed, and surface pressure along with parameters such as vegetation class, soil texture, and elevation as inputs to a model that simulates land surface energy and water budget processes. Outputs of the model include soil moisture, snow depth and snow water equivalent, evapotranspiration, soil temperature, as well as derived quantities such as groundwater recharge and anomalies of the state variables.

This dataset holds Level 2 (L2) data for surface emissivity and land surface temperature (LST) collected by the Hyperspectral Thermal Emission Spectrometer (HyTES) instrument. This imagery was acquired as part of the Surface Biology and Geology High-Frequency Time Series (SHIFT) campaign on March 23, 2022. The SHIFT campaign generated precise, high-frequency data on plant communities for nearly 1,656 square kilometers across Santa Barbara County, California, US, and the nearby ocean. HyTES is a compact image spectrometer that acquires data in 256 spectral bands between 7.5 and 12 micrometers; it was deployed on a Twin Otter aircraft. The SHIFT campaign sought to demonstrate the joint use of both VSWIR and thermal infrared (TIR) data. TIR data are used to measure land surface temperature (LST), which informs models of water flux from land surface through processes such as evapotranspiration. LST is sensitive to solar heat gains and local cooling effects due to evaporative cooling. The HyTES instrument measures TIR radiances that can be used to derive LST, emissivity and Level 3 products such as latent heat flux and detection of air pollution sources. The HyTES data are provided in HDF5 format and include 91 flight scenes. In addition, overlay images for emissivity and LST are provided in compressed Keyhole Markup Language (KMZ) along with a quicklook image.

Contains the data collected in 1994 by the AMS suite A instrument set operated by SRC and provided to BORIS.