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.

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

This data set provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) particle trajectory data products for particle receptors co-located with atmospheric column observations from the OCO-2 satellite. Meteorological fields from the WRF model are used to drive STILT. STILT applies a Lagrangian particle dispersion model backwards in time from a measurement location (the "receptor" location), to create the adjoint of the transport model in the form of a "footprint" field. The footprint, with units of mixing ratio per surface flux, quantifies the influence of upwind surface fluxes on greenhouse gas concentrations measured at the receptor and is computed by counting the number of particles in a surface-influenced volume and the time spent in that volume. For each column observation location, the receptors are located at 14 discrete vertical levels throughout the atmospheric column. The CMS program is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System uses NASA observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS data products are designed to inform near-term policy development and planning.

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GES_DISC Short Name: CMS_CTL_NA_OCO2_FOOTPRINTS Version ID: 1 Unique ID: C2467863601-GES_DISC

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.

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

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.

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

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.

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