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These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-3 Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project.

This is the fine resolution version of the previously released GSSTFYC.2c.

This is the Yearly Climatology product; data are projected to equidistant Grid that covers the globe at 0.25x00.25 degree cell size, resulting in data arrays of 1440x720 size.

Starting from previous Version 2c, these data have only one set of Combined data, "Set1". The Yearly Climatology HDF-EOS5 file also contains one extra grid of NCEP Climatology, "NCEP".

These data are part of the Goddard Satellite-based Surface Turbulent Fluxes Version 3 (GSSTF3) Dataset recently produced through a MEaSURES funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project.

These data are the Goddard Satellite-based Surface Turbulent Fluxes Version-3 (GSSTF3) Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project.

This suite of GSSTF version 3 products is the 0.25x0.25 deg resolution version of the GSSTF 2c collections. It does not contain, however, the "WB" variable - 'lowest 500-m precipitable water' (g/cm**2).

This is the Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 0.25 degree cell size, resulting in data arrays of 1440x720 size.

The total annual freezing and thawing indices are defined as the
cumulative number of degree-days when air temperatures are below and
above zero degrees Celsius. The total annual freezing index has been
widely used to predict permafrost distribution; estimate the
maximum thickness of sea, lake, and river ice, and the maximum depth of
ground-frost penetration; and classify snow types. The annual total
thawing index has been used to predict permafrost distribution and to
estimate the maximum depth of thaw in frozen ground. Both total
freezing and thawing indices are important parameters for engineering
design in cold regions.

Data coverage is global. The data set contains the total annual freezing and thawing indices with a spatial resolution of 0.5 degrees
latitude by 0.5 degrees longitude. Two data files are available, for
the freeze and thaw indices respectively, in flat binary format. Each
file is approximately 1 MB in size. The total annual freezing and
thawing indexes were calculated based upon the monthly mean air
temperature by Legates and Willmott (1990).

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 monthly, was reprocessed and replaced its previous data product on November 19, 2019. The data product was generated through temporal averaging of the reprocessed 3-hourly data, 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.

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 0.25 degree monthly, was reprocessed and replaced its previous data product on November 19, 2019. The data product was generated through temporal averaging of the reprocessed 3-hourly data, 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.

The GEOS-5 FP-IT Assimilation Geo-colocated to OMI/Aura UV-2 1-Orbit L2 Support Swath 13x24km (OMUFPITMET) provides selected parameters from GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath.

The fields in this product include surface pressure, vertical temperature profiles, surface and vertical wind profiles, tropopause pressure, boundary layer top pressure, and surface geopotenial. The OMI team also provides a corresponding product for the OMI VIS swath, OMVFPITMET. The product has been generated for convenient use by the OMI/Aura team in their L2 algorithms, and for research where those L2 products are used. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir. To reduce the size of each orbital file, FP-IT data fields with a vertical dimension of 72 layers have been reduced to 47 layers in OMUFPITMET by combining layers above the troposphere.

The OMUFPITMET files are in netCDF4 format which is compatible with most HDF5 readers and tools. Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official.

The monthly climatology dataset contains a series of land surface parameters simulated from the Noah 3.6.1 model in the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). The dataset comprises of 12 monthly files, each representing the monthly data averaged over 35 years from 1982 to 2016, based on the FLDAS Noah Land Surface Model L4 Global Monthly 0.1 x 0.1 degree (MERRA-2 and CHIRPS) V001 (FLDAS_NOAH01_C_GL_M_001) monthly data. The data are in 0.10 degree resolution and the spatial coverage is global (60S, 180W, 90N, 180E). The FLDAS regional monthly climatology datasets will no longer be available and have been superseded by the global monthly climatology dataset.

More information about the monthly FLDAS can be found from the dataset landing page for FLDAS_NOAH01_C_GL_M_001 and the FLDAS README document.

In November 2020, all FLDAS data werepost-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 affectthe meteorological forcing variables. More information on this can be found in the FLDAS README document, and the MOD44W MODIS land mask is available on the FLDAS Project site. If you had downloaded any FLDAS data prior to November 2020, please download the data again to receive the post-processed data.

The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to seek the basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between ISCCP data, GCM parameterizations, and higher space and time resolution cloud data. To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.A subset of the ISCCP Stage DX Cloud Product (Revised Algorithm) are included for the FIRE Marine Stratocumulus region.

The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to seek the basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between ISCCP data, GCM parameterizations, and higher space and time resolution cloud data. To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.Data were collected from the NCAR Electra aircraft during the FIRE Marine Stratocumulus experiment in July 1987. The data were produced by the NCAR Research Aviation Facility (RAF) Data Management Group, with the GENPRO-II data processing software. The format of these data include a header file and a data file which corresponds to all or part of a particular aircraft flight.