The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission measures the temperature of plants to better understand how much water plants need and how they respond to stress. ECOSTRESS is attached to the International Space Station (ISS) and collects data globally between 52° N and 52° S latitudes. A map of the acquisition coverage can be found on the ECOSTRESS website.

The ECOSTRESS Gridded Downscaled Soil Moisture Instantaneous L3 Global 70 m (ECO_L3G_SM) Version 2 data product provides instantaneous soil moisture (SM) estimates downscaled using linear regression. The linear regression uses up-sampled surface temperature (ST), normalized difference vegetation index (NDVI), and albedo as predictor variables and SM from Goddard Earth Observing System Version 5 (GEOS-5) Forward Processing (FP) as response variables for their relative outputs. Once the regression coefficients have been determined, they are applied to the 70 meter (m) ST, NDVI, and albedo as a first pass, which is then bias corrected using a GEOS-5 FP image. This data product is mosaicked from the L3 tiled SM (ECO_L3T_SM) product, is projected to a globally snapped 0.0006° grid, and has a spatial resolution of 70 m.

The ECO_L3G_SM Version 2 data product contains three layers distributed in an HDF5 file including SM, cloud mask, and water mask.

Known Issues: *Data acquisition gap: ECOSTRESS was launched on June 29, 2018, and moved to autonomous science operations on August 20, 2018, following a successful in-orbit checkout period. On September 29, 2018, ECOSTRESS experienced an anomaly with its primary mass storage unit (MSU). ECOSTRESS has a primary and secondary MSU (A and B). On December 5, 2018, the instrument was switched to the secondary MSU, and science operations resumed. On March 14, 2019, the secondary MSU experienced a similar anomaly, temporarily halting science acquisitions. On May 15, 2019, a new data acquisition approach was implemented, and science acquisitions resumed. To optimize the new acquisition approach, only Thermal Infrared (TIR) bands 2, 4, and 5 are being downloaded. The data products are the same as before, but the bands not downloaded contain fill values (L1 radiance and L2 emissivity). This approach was implemented from May 15, 2019, through April 28, 2023.

*Data acquisition gap: From February 8 to February 16, 2020, an ECOSTRESS instrument issue resulted in a data anomaly that created striping in band 4 (10.5 micron). These data products have been reprocessed and are available for download. No ECOSTRESS data were acquired on February 17, 2020, due to the instrument being in SAFEHOLD. Data acquired following the anomaly have not been affected.

*Data acquisition: ECOSTRESS has now successfully returned to 5-band mode after being in 3-band mode since 2019. This feature was successfully enabled following a Data Processing Unit firmware update (version 4.1) to the payload on April 28, 2023. To better balance contiguous science data scene variables, 3-band collection is currently being interleaved with 5-band acquisitions over the orbital day/night periods.

As part of the BOREAS Follow-on, an extended period of data collection was supported in the NSA because of the continued efforts at the NSA-OBS site. This data set contains near-surface meteorological data collected and averaged over 15 minute intervals from two sites in the NSA, the SRC tower at the Thompson airport (YTH) and a temporary walkup wooden tower at the Old Black Spruce (OBS) tower site.

Contains the data collected in 1995 by the AMS suite A instrument set operated by SRC and provided to BORIS.

The SIFSAP (Single Field-of-View Sounder Atmospheric Products) algorithm provides retrieval for each sounder Field of View (FOV), therefore, it has 3-times higher horizontal spatial resolution and 9-time denser products compared to other current IR sounder products. Since SiFSAP is an FOV-based algorithm, its product variables have an additional dimension which represents the number of FOVs. For CrIS instrument, there are 9 FOVs for each Field of Regard (FOR). The SiFSAP L3 products contain a variety of geophysical parameters retrieved from IR/MW sounder suites measurements, including atmospheric temperature profiles, water vapor, ozone profiles, clouds, and surface properties.

This monthly one half degree latitude by one half degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use). The Level-3 products maximize the yield of each individual variable and level by collecting all cases where the corresponding Level 2 quality control from the top of the atmosphere down to the level where the QC determines that the value is 0 (best) or 1 (good). Below this level, the data is rejected. This gives the greatest possible yield for any given level and variable.

The SIFSAP (Single Field-of-View Sounder Atmospheric Products) algorithm provides retrieval for each sounder Field of View (FOV), therefore, it has 3-times higher horizontal spatial resolution and 9-time denser products compared to other current IR sounder products. Since SiFSAP is an FOV-based algorithm, its product variables have an additional dimension which represents the number of FOVs. For CrIS instrument, there are 9 FOVs for each Field of Regard (FOR). The SiFSAP L3 products contain a variety of geophysical parameters retrieved from IR/MW sounder suites measurements, including atmospheric temperature profiles, water vapor, ozone profiles, clouds, and surface properties.

This daily one half degree latitude by one half degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use). The Level-3 products maximize the yield of each individual variable and level by collecting all cases where the corresponding Level 2 quality control from the top of the atmosphere down to the level where the QC determines that the value is 0 (best) or 1 (good). Below this level, the data is rejected. This gives the greatest possible yield for any given level and variable.

The VIIRS/JPSS1 Thermal Anomalies/Fire 6-Min L2 Swath 750m NRT product, short-name VJ114_NRT is based on the MODIS Fire algorithm. The input to the Active Fires production are Level-1B moderate-resolution reflective band M7, and emissive bands M13 and M15. The fire algorithm first calculates bands M13, M15 brightness temperature (BT) statistics for a group of background pixels adjacent to each potential fire pixel. These statistics are used to set thresholds for several contextual fire detection tests. There is also an absolute fire detection test based on a pre-set M13 BT threshold. If the results of the absolute and relative fire detection tests meet certain criteria, the pixel is labeled as fire. The designation of a pixel as fire from the results of the BT threshold tests may be overridden under sun glint conditions or if too few pixels were used to calculate the background statistics.

The VJ114_NRT product contains several pieces of information for each fire pixel: pixel coordinates, latitude and longitude, pixel M7 reflectance, background M7 reflectance, pixel M13 and M15 BT, background M13 and M15 BT, mean background BT difference, background M13, M15, and BT difference mean absolute deviation, fire radiative power, number of adjacent cloud pixels, number of adjacent water pixels, background window size, number of valid background pixels, detection confidence, land pixel flag, background M7 reflectance, and reflectance mean absolute deviation.

The product provides day and nighttime active fire detection over land and water (from gas flares). The VJ114 product provides fire data continuity with NASA's EOS MODIS 1 km fire product.

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

The VIIRS/NPP Thermal Anomalies/Fire 6-Min L2 Swath 750m NRT product, short-name VNP14_NRT is based on the MODIS Fire algorithm. The input to the Active Fires production are Level-1B moderate-resolution reflective band M7, and emissive bands M13 and M15. The fire algorithm first calculates bands M13, M15 brightness temperature (BT) statistics for a group of background pixels adjacent to each potential fire pixel. These statistics are used to set thresholds for several contextual fire detection tests. There is also an absolute fire detection test based on a pre-set M13 BT threshold. If the results of the absolute and relative fire detection tests meet certain criteria, the pixel is labeled as fire. The designation of a pixel as fire from the results of the BT threshold tests may be overridden under sun glint conditions or if too few pixels were used to calculate the background statistics.

The VNP14_NRT product contains several pieces of information for each fire pixel: pixel coordinates, latitude and longitude, pixel M7 reflectance, background M7 reflectance, pixel M13 and M15 BT, background M13 and M15 BT, mean background BT difference, background M13, M15, and BT difference mean absolute deviation, fire radiative power, number of adjacent cloud pixels, number of adjacent water pixels, background window size, number of valid background pixels, detection confidence, land pixel flag, background M7 reflectance, and reflectance mean absolute deviation.

The product provides day and nighttime active fire detection over land and water (from gas flares). The VNP14 product provides fire data continuity with NASA's EOS MODIS 1 km fire product.

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

The VIIRS/JPSS2 Thermal Anomalies/Fire 6-Min L2 Swath 750m NRT product, short-name VJ214_NRT is based on the MODIS Fire algorithm. The input to the Active Fires production are Level-1B moderate-resolution reflective band M7, and emissive bands M13 and M15. The fire algorithm first calculates bands M13, M15 brightness temperature (BT) statistics for a group of background pixels adjacent to each potential fire pixel. These statistics are used to set thresholds for several contextual fire detection tests. There is also an absolute fire detection test based on a pre-set M13 BT threshold. If the results of the absolute and relative fire detection tests meet certain criteria, the pixel is labeled as fire. The designation of a pixel as fire from the results of the BT threshold tests may be overridden under sun glint conditions or if too few pixels were used to calculate the background statistics.

The VJ214_NRT product contains several pieces of information for each fire pixel: pixel coordinates, latitude and longitude, pixel M7 reflectance, background M7 reflectance, pixel M13 and M15 BT, background M13 and M15 BT, mean background BT difference, background M13, M15, and BT difference mean absolute deviation, fire radiative power, number of adjacent cloud pixels, number of adjacent water pixels, background window size, number of valid background pixels, detection confidence, land pixel flag, background M7 reflectance, and reflectance mean absolute deviation.

The product provides day and nighttime active fire detection over land and water (from gas flares). The VJ214 product provides fire data continuity with NASA's EOS MODIS 1 km fire product.

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

The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder) and AMSU (Advanced Microwave Sounding Unit). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS in combination with the AMSU constitutes an innovative atmospheric sounding group of infrared and microwave sensors. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.

The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.

This monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the comprehensive quality control (QC) methodology. Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables.

WARNING: To users of the derived product “co_mmr_midtrop” (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 48.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply “co_mmr_midtrop” by 28.01/48.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (“mol_lay/co_mol_lay”) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov

Abstract: 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 file format is WMO GRIB-1. The NLDAS-2 monthly climatology data are the monthly data averaged over the thirty years (1980-2009) of the NLDAS-2 monthly data.

A brief description about the NLDAS-2 hourly and monthly VIC LSM data can be found from the GCMD DIFs for GES_DISC_NLDAS_VIC0125_H_V002 and GES_DISC_NLDAS_VIC0125_M_V002.

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 NLDAS-2 VIC monthly climatology data contain forty-three 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.