This dataset contains Level-3 Dynamic OPERA Surface Water Extent from Sentinal-1 (DSWx-S1) product version 1. DSWx-S1 provides near-global geographical mapping of surface water extent over land at a spatial resolution of 30 meters over the Military Grid reference System (MGRS) grid system, with a temporal revisit frequency between 6-12 days. Using Sentinel-1 radar observations, DSWx-S1 maps open inland water bodies greater than 3 hectares and 200 meters in width, irrespective of cloud conditions and daylight illumination that often pose challenges to optical sensors. Forward production of the DSWx-S1 data record began in Sept 2024. Each product is distributed as a set of 3 GeoTIFF (Geographic Tagged Image File Format) files including water classification and associated confidence layers.

To access the calibration/validation database for OPERA Dynamic Surface Water Extent Products, please contact podaac@podaac.jpl.nasa.gov

In this project, we leverage the near-monthly, 5-day long expeditions to oligotrophic waters approximately 100 km from Oahu, Hawaii, conducted by the Hawaii Ocean Time-series (HOT) program. We will participate in ~30 HOT cruises across all seasons over a 3-year period, amounting to ~ 150 days of high-quality collection of a suite of essential parameters for PACE Mission validation.

This data set is produced by the Jet Propulsion Laboratory (JPL) as part of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the ocean bottom pressure (OBP) anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents sea floor pressure changes due to the integral effect of ocean and atmosphere processes, including global mean ocean bottom pressure changes (mean ocean mass and mean atmosphere mass over the global oceans). A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats.

GRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 – 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the ocean bottom pressure data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this RL06.3 is an updated release of the previous RL06.1. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data.

This dataset contains gridded monthly global water storage/height anomalies relative to a time-mean, derived from GRACE and GRACE-FO and processed at JPL using the Mascon approach (RL06.3Mv04). A Coastal Resolution Improvement (CRI) filter has been applied to this data set to reduce signal leakage errors across coastlines. For most land hydrology, oceanographic as well as land-ice applications this is the recommend data set for the analysis of surface mass changes. The data are provided in a single data file in netCDF format, with water storage/height anomalies in equivalent water thickness units (cm). The data are derived from solving for monthly gravity field variations on geolocated spherical cap mass concentration functions, rather than global spherical harmonic coefficients. Additionally, realistic geophysical information is introduced during the computation to intrinsically remove correlated errors. Thus, these Mascon grids do not need to be de-correlated or smoothed, like traditional spherical harmonic gravity solutions.



The complete Mascon solution consists of 4,551 independent estimates of surface mass change that have been derived using an equal-area 3-degree grid of individual mascons. A subset of these individual mascons span coastlines, and contain mixed land and ocean mass change signals. In a post-processing step, the CRI filter is applied to those mixed land/ocean Mascons to separate land and ocean mass. The land mask used to perform this separation is provided in the same directory as this dataset, as are uncertainty values, and the gridded mascon-ID number to enable further analysis. Since the individual mascons act as an inherent smoother on the gravity field, a set of optional gain factors (for continental hydrology applications) that can be applied to the solution to study mass change signals at sub-mascon resolution is also provided within the same data directory as the Mascon data. For use-case examples and further background on the gain factors, please see Wiese, Landerer & Watkins, 2016, https://doi.org/10.1002/2016WR019344.



This RL06.3Mv04 is an updated version of the previous Tellus JPL Mascon RL06.1Mv03 (DOI, 10.5067/TEMSC-3JC63). For a detailed description on the Mascon solution, including the mathematical derivation, implementation of geophysical constraints, and solution validation, please see Watkins et al., 2015, doi: 10.1002/2014JB011547. For a detailed description of the CRI filter implementation, please see Wiese et al., 2016, doi:10.1002/2016WR019344.

This data set is produced by the Jet Propulsion Laboratory (JPL) as part of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the terrestrial water storage anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents the total terrestrial water storage anomalies from soil moisture, snow, surface water (incl. rivers, lakes, reservoirs etc.), as well as groundwater and aquifers. A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats.

GRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 – 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the terrestrial water storage data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this RL06.3 is an updated release of the previous RL06.1. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data.

This dataset contains gridded monthly global water storage/height anomalies relative to a time-mean, derived from GRACE and GRACE-FO and processed at JPL using the Mascon approach (RL06.3Mv04). These data are provided in a single data file in netCDF format, and can be used for analysis for ocean, ice, and hydrology phenomena. The data are provided in a single data file in netCDF format, with water storage/height anomalies in equivalent water thickness units (cm). The data are derived from solving for monthly gravity field variations on geolocated spherical cap mass concentration functions, rather than global spherical harmonic coefficients. Additionally, realistic geophysical information is introduced during the computation to intrinsically remove correlated errors. Thus, these Mascon grids do not need to be de-correlated or smoothed, like traditional spherical harmonic gravity solutions.



The complete Mascon solution consists of 4,551 independent estimates of surface mass change that have been derived using an equal-area 3-degree grid of individual mascons. Please note that this dataset does not correct for leakage errors across coastlines; it is therefore recommended only for users who want to apply their own algorithm to separate between land and ocean mass very near coastlines.



This RL06.3Mv04 is an updated version of the previous Tellus JPL Mascon RL06.1Mv03. For more information, please visit https://grace.jpl.nasa.gov/data/get-data/jpl_global_mascons/. For a detailed description on the Mascon processing, including the mathematical derivation, implementation of geophysical constraints, and validation, please see Watkins et al., 2015, doi: 10.1002/2014JB011547. This product is intended for expert use only; other users are encouraged to use the CRI-filtered Mascon dataset, which is available here: https://podaac.jpl.nasa.gov/dataset/TELLUS_GRAC-GRFO_MASCON_GRID_RL06.3_V4.

This dataset contains simulations of net primary production (NPP), heterotrophic respiration (RH), net ecosystem production (NEP), and soil temperature data in North American boreal forests for the period 1986-2020. Data sources included historical fire sources and Landsat data. The delta Normalized Burn Ratio (dNBR), which can be used to represent burn severity for a fire, was calculated for each individual fire over the time period. The interactions between canopy, fire and soil thermal dynamics were modelled using a soil surface energy balance model incorporated into a previous Terrestrial Ecosystem Model (TEM). Using the revised TEM, two regional simulations were conducted with and without fire disturbance. Fire polygons were dissected into each unit with unique fire history and then intersected with each grid cell to measure fire impacts. The output values for each grid cell are the area-weighted mean of each fire polygon and unburned area within the cell. Two extra simulations without a canopy energy balance scheme were also conducted to quantify the impact of the canopy. Soil temperature was simulated with and without the canopy energy balance scheme in the model in addition to considering fire impacts.

This dataset contains water surface elevations at selected point locations generated from the AirSWOT data collected during the Spring and Fall 2021 Delta-X deployments over the Atchafalaya and Terrebonne basins in Louisiana, USA. AirSWOT uses near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and produce continuous gridded elevation data. The Level 3 (L3) data were created by masking land areas out of the AirSWOT Level 2 products, then filtering and averaging to the AirSWOT heights to produce water surface elevations at selected points throughout the scene. The AirSWOT elevation data are useful for calibrating elevation and slopes along the main channels, as well as tying observations to open ocean tidal conditions. AirSWOT performance in the floodplain was limited by the presence of vegetation and the very small slope characteristic of two dimensional floodplain discharge. Therefore, the bulk of the AirSWOT data collections were targeted at the larger channels, since the channel discharge provides the necessary boundary conditions for potential overflow to islands and floodplains. The data are provided in comma-separated values (CSV) format.

This dataset provides input data and model code to run the Marsh Accretion Rates (NUMAR) process model used to predict soil accretion rates and chemical properties for marsh sites in the Mississippi River Delta. NUMAR is a modification of the NUMAN model by Chen and Twilley (1999) that was developed for mangrove environments. This dataset provides Python code, input data in comma separated values (CSV) format, and documentation for installing and running the model in Portable Document Format (PDF).

FOR EXPERT USE ONLY. This dataset contains estimates of the total month-by-month geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission measurements, produced by the NASA Jet Propulsion Laboratory (JPL). The data are provided as spherical harmonic coefficients, averaged over approximately a month, and available from 2018 onward. These coefficients are derived from the Microwave Instrument (MWI) measured intersatellite range changes between the twin spacecraft of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) mission. The GRACE-FO mission, a joint partnership between NASA and the German Research Centre for Geosciences (GFZ), launched on 22 May 2018. It uses twin satellites to accurately map variations in the Earth's gravity field and surface mass distribution. It is designed as a successor to the Gravity Recovery and Climate Experiment (GRACE) mission.



This GRACE-FO RL06.3 data is an updated version of the GRACE-FO RL06.1 Level-2 data products. RL06.3 differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 satellite: Level-2 RL06.3 uses ACH1B RL04 that is contained within the ACX2 Level-1 bundle, which replaces ACH1B RL04 contained within the ACX Level-1 bundle that was used for Level-2 RL06.1 (note: ACX2-L1B is only applicable for 01/2023 onwards in wide-pointing operational mode; from 6/2018 through 12/2022, RL06.1 and RL06.3 GRACE-FO data are identical and based on ACX; ACX2 is not available for 03/2023-06/2023 as the satellites were not in wide-pointing mode during that period). All GRACE-FO RL06.3 Level-2 products are fully compatible with the GRACE RL06 level-2 fields. Refer to the mission page for more information.