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  • ABoVE: Level-4 WRF-STILT Footprint Files for Circumpolar Receptors, 2016-2019

    https://cmr.earthdata.nasa.gov/search/concepts/C2181255288-ORNL_CLOUD.xml
    Description:

    This dataset provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) Footprint data products for receptors (observations) located at positions along flight paths and at various fixed observing sites at circumpolar locations at northern latitudes during 2016-2019. Each aircraft and station position is treated as an independent receptor in the WRF-STILT model in order to simulate the land surface influence on observed atmospheric constituents. The footprints are independent of chemical species and can be applied to different flux models and incorporated into formal inversion frameworks. The particle trajectories that determine the footprint field are constrained only by the outer edges of the WRF modeling domain. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by the thawing of Arctic permafrost.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 30 -180 90 180

    ORNL_CLOUD Short Name: ABoVE_Footprints_WRF_AK_NWCa_1896 Version ID: 1 Unique ID: C2181255288-ORNL_CLOUD

  • ABoVE: Level-4 WRF-STILT Particle Trajectories for Circumpolar Receptors, 2016-2019

    https://cmr.earthdata.nasa.gov/search/concepts/C2180373101-ORNL_CLOUD.xml
    Description:

    This dataset provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) particle trajectory files for receptors located at positions along flight paths and at various fixed observing sites at circumpolar locations above 45 degrees North during 2016-2019. The particle files describe the motion of particles released backward in time over a 10-day period. The particle files are separated into archives by platform type (some platforms are combined) and can be characterized as either low resolution or high resolution depending on whether the subsequent footprint fields were generated on a circumpolar 0.5-degree grid (low-resolution) or both 0.5-degree and 0.1-degree grids (high-resolution). The platforms include flux towers at fixed sites, laboratory measurements of whole air samples collected by Programmable Flask Packages (PFP) onboard aircraft, and observations by NASA's Orbiting Carbon Observatory-2 satellite. These particle files were thinned to retain particle location information only when the particles have non-zero contributions to the corresponding footprint field. These particle files are used to compute the footprint fields available in a companion dataset. The particle trajectories that determine the footprint field are constrained only by the outer edges of the WRF modeling domain. Likewise, the companion footprint files are provided on a regular latitude-longitude grid. This dataset extends previous research on the atmospheric transport of land-surface emissions of greenhouse gases by the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) project. In particular, the content of the low-resolution particle files is similar to those for the CARVE dataset.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 10 -180 90 180

    ORNL_CLOUD Short Name: ABoVE_Particles_WRF_AK_NWCa_1895 Version ID: 1 Unique ID: C2180373101-ORNL_CLOUD

  • ABoVE: TVPRM Simulated Net Ecosystem Exchange, Alaskan North Slope, 2008-2017

    https://cmr.earthdata.nasa.gov/search/concepts/C2240727916-ORNL_CLOUD.xml
    Description:

    This dataset includes hourly net ecosystem exchange (NEE) simulated by the Tundra Vegetation Photosynthesis and Respiration Model (TVPRM) at 30 km horizontal resolution for the Alaskan North Slope for 2008-2017. TVPRM calculates tundra NEE from air temperature, soil temperature, photosynthetically active radiation (PAR), and solar-induced chlorophyll fluorescence (SIF) using functional relationships derived from eddy covariance tower measurements. These relationships were then scaled over the region using gridded meteorology and a vegetation map. The site-level CO2 fluxes fell into two distinct ecosystem groups: inland tundra (ICS, ICT, ICH, IVO) and coastal tundra (ATQ, BES, BEO, CMDL). The expanded modeling framework allowed for the easy substitution of ecological behaviors and environmental drivers, including the choice of representative inland tundra site, coastal tundra site, vegetation map (CAVM, RasterCAVM, or ABoVE-LC), meteorological reanalysis product (NARR or ERA5), and SIF product (GOME2, GOSIF, or CSIF). Using all of these variations generated an ensemble of 288 different TVPRM simulations of regional CO2 flux and one additional simulation option with added aquatic and zero curtain fluxes (AqZC).

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 56.09 -177.47 77.26 -128.59

    ORNL_CLOUD Short Name: NorthSlope_NEE_TVPRM_1920 Version ID: 1 Unique ID: C2240727916-ORNL_CLOUD

  • CARVE Modeled Gross Ecosystem CO2 Exchange and Respiration, Alaska, 2012-2014

    https://cmr.earthdata.nasa.gov/search/concepts/C2236236883-ORNL_CLOUD.xml
    Description:

    This data set provides 3-hourly estimates of gross ecosystem CO2 exchange (GEE) and respiration (autotrophic and heterotrophic) for the state of Alaska from 2012 to 2014. The data were generated using the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM) and are provided at ~ 1 km2 [1/4-degree (longitude) by 1/6-degree (latitude)] pixel resolution. The PolarVPRM produces high-frequency estimates of GEE of CO2 for North American biomes from remotely-sensed data sets. For Alaska, the model used meteorological inputs from the North American regional re-analysis (NARR) and inputs of fractional snow cover and land surface water index (LSWI) from the Moderate Resolution Imaging Spectroradiometer (MODIS). Land surface greenness was factored into the model from three sources: 1) Enhanced Vegetation Index (EVI) from MODIS; 2) Solar Induced Florescence (SIF) from the Orbiting Carbon Observatory 2 (OCO-2); and 3) SIF from the Global Ozone Monitoring Experiment 2 (GOME-2). Three independent estimates of GEE are included in the data set, one for each source of greenness observations.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 55 -179 73 -134

    ORNL_CLOUD Short Name: Polar-VPRM_Alaskan-NEE_1314 Version ID: 1 Unique ID: C2236236883-ORNL_CLOUD

  • CMS: CO2 Signals Estimated for Fossil Fuel Emissions and Biosphere Flux, California

    https://cmr.earthdata.nasa.gov/search/concepts/C1377051683-ORNL_DAAC.xml
    Description:

    This data set provides estimated CO2 emission signals for 16 regions (air quality basins) in California, USA, during the individual months of November 2010 and May 2011. The CO2 signals were predicted from simulated atmospheric CO2 observations and modeled fossil fuel emissions and biosphere CO2 fluxes. Data is also provided for the land surface in the larger modeling domain outside California. CO2 signals refer to the local enhancement or depletion in atmospheric CO2 concentration caused by fossil fuel emissions or biospheric exchange occurring within the region.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 32.2 -124.51 42.82 -115.96

    ORNL_DAAC Short Name: CMS_WRF_Footprints_CO2_Signals_1381 Version ID: 1 Unique ID: C1377051683-ORNL_DAAC

  • High Resolution Global Contiguous SIF Estimates from OCO-2 SIF and MODIS, Version 2

    https://cmr.earthdata.nasa.gov/search/concepts/C2207986708-ORNL_CLOUD.xml
    Description:

    This dataset provides spatially-contiguous global mean daily solar-induced chlorophyll fluorescence (SIF) estimates at 0.05 degree (approximately 5 km at the equator) spatial and 16-day temporal resolution from September 2014 through July 2020. This product was derived from Orbiting Carbon Observatory-2 (OCO-2) SIF observations and produced by training an artificial neural network (ANN) on the native OCO-2 SIF observations and MODIS BRDF-corrected seven-band surface reflectance along OCO-2's orbits. The trained ANN model was then applied to predict mean daily SIF (mW/m2/nm/sr) in OCO-2's gap regions based on MODIS reflectance and landcover. This framework was stratified by biomes and 16-day time steps. This dataset's high resolution and global contiguous coverage will greatly enhance the synergy between satellite SIF and photosynthesis measured on the ground at consistent spatial scales. Potential applications of this dataset include advancing dynamic drought monitoring and mitigation, informing agricultural planning and yield estimation, and providing a benchmark for upcoming satellite missions with SIF capabilities at higher spatial resolutions.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    ORNL_CLOUD Short Name: Global_SIF_OCO2_MODIS_1863 Version ID: 2 Unique ID: C2207986708-ORNL_CLOUD

  • Multi-Instrument Fused bias-corrected XCO2 and other select fields aggregated as Level 4 daily files V3 (MultiInstrumentFusedXCO2)

    https://cmr.earthdata.nasa.gov/search/concepts/C2219373930-GES_DISC.xml
    Description:

    Gridded carbon dioxide mole fraction (XCO2) and other select variables created by applying local kriging (also known as optimal interpolation) to daily aggregates of Orbiting Carbon Observatory (OCO-2) and Greenhouse Gases Observing Satellite (GOSAT) bias corrected data. This is the latest version of this collection. The DOIs assigned to previous versions, which are no longer available, now direct to this page.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    GES_DISC Short Name: MultiInstrumentFusedXCO2 Version ID: 3 Unique ID: C2219373930-GES_DISC

  • OCO-2 GEOS Level 3 daily, 0.5x0.625 assimilated CO2 V10r (OCO2_GEOS_L3CO2_DAY) at GES DISC

    https://cmr.earthdata.nasa.gov/search/concepts/C2240248762-GES_DISC.xml
    Description:

    This is the Gridded Daily OCO-2 Carbon Dioxide assimilated dataset. The OCO-2 mission provides the highest quality space-based XCO2 retrievals to date. However, the instrument data are characterized by large gaps in coverage due to OCO-2’s narrow 10-km ground track and an inability to see through clouds and thick aerosols. This global gridded dataset is produced using a data assimilation technique commonly referred to as state estimation within the geophysical literature. Data assimilation synthesizes simulations and observations, adjusting the state of atmospheric constituents like CO2 to reflect observed values, thus gap-filling observations when and where they are unavailable based on previous observations and short transport simulations by GEOS. Compared to other methods, data assimilation has the advantage that it makes estimates based on our collective scientific understanding, notably of the Earth’s carbon cycle and atmospheric transport. OCO-2 GEOS (Goddard Earth Observing System) Level 3 data are produced by ingesting OCO-2 L2 retrievals every 6 hours with GEOS CoDAS, a modeling and data assimilation system maintained by NASA’s Global Modeling and Assimilation Office (GMAO). GEOS CoDAS uses a high-performance computing implementation of the Gridpoint Statistical Interpolation approach for solving the state estimation problem. GSI finds the analyzed state that minimizes the three-dimensional variational (3D-Var) cost function formulation of the state estimation problem.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    GES_DISC Short Name: OCO2_GEOS_L3CO2_DAY Version ID: 10r Unique ID: C2240248762-GES_DISC

  • OCO-2 GEOS Level 3 monthly, 0.5x0.625 assimilated CO2 V10r (OCO2_GEOS_L3CO2_MONTH) at GES DISC

    https://cmr.earthdata.nasa.gov/search/concepts/C2240248790-GES_DISC.xml
    Description:

    This is the Gridded Monthly OCO-2 Carbon Dioxide assimilated dataset. The OCO-2 mission provides the highest quality space-based XCO2 retrievals to date. However, the instrument data are characterized by large gaps in coverage due to OCO-2’s narrow 10-km ground track and an inability to see through clouds and thick aerosols. This global gridded dataset is produced using a data assimilation technique commonly referred to as state estimation within the geophysical literature. Data assimilation synthesizes simulations and observations, adjusting the state of atmospheric constituents like CO2 to reflect observed values, thus gap-filling observations when and where they are unavailable based on previous observations and short transport simulations by GEOS. Compared to other methods, data assimilation has the advantage that it makes estimates based on our collective scientific understanding, notably of the Earth’s carbon cycle and atmospheric transport. OCO-2 GEOS (Goddard Earth Observing System) Level 3 data are produced by ingesting OCO-2 L2 retrievals every 6 hours with GEOS CoDAS, a modeling and data assimilation system maintained by NASA’s Global Modeling and Assimilation Office (GMAO). GEOS CoDAS uses a high-performance computing implementation of the Gridpoint Statistical Interpolation approach for solving the state estimation problem. GSI finds the analyzed state that minimizes the three-dimensional variational (3D-Var) cost function formulation of the state estimation problem.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    GES_DISC Short Name: OCO2_GEOS_L3CO2_MONTH Version ID: 10r Unique ID: C2240248790-GES_DISC

  • OCO-2 Gridded bias-corrected XCO2 and other select fields aggregated as Level 4 daily files V3 (OCO2GriddedXCO2)

    https://cmr.earthdata.nasa.gov/search/concepts/C2219374142-GES_DISC.xml
    Description:

    Gridded carbon dioxide mole fraction (XCO2) and other select variables created by applying local kriging (also known as optimal interpolation) to daily aggregates of Orbiting Carbon Observatory (OCO-2) bias corrected data. This is the latest version of this collection. The DOIs assigned to previous versions, which are no longer available, now direct to this page.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    GES_DISC Short Name: OCO2GriddedXCO2 Version ID: 3 Unique ID: C2219374142-GES_DISC