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22 results for “Net Ecosystem Exchange”
Isotopic Composition of Net Ecosystem CO2 Exchange at Harvard Forest EMS Tower since 2011
This archive features long-term measurements of the eddy and storage fluxes of 16O12C16O, 16O13C16O, and 18O12C16O at the Harvard Forest EMS flux tower. Provided are the individual isotopologue fluxes, the total CO2 flux, the δ13C and δ18O isofluxes, and various ancillary flux and environmental data. The data are described in Wehr et al (2013), Long-term eddy covariance measurements of the isotopic composition of the ecosystem–atmosphere exchange of CO2 in a temperate forest, Agricultural and Forest Meteorology 181, 69–84. They are also analyzed in Wehr and Saleska (2015), An improved isotopic method for partitioning net ecosystem–atmosphere CO2 exchange, Agricultural and Forest Meteorology 214-215, 515–531, as well as in Wehr et al 2016, Seasonality of Temperate Forest Photosynthesis and Daytime Respiration, Nature (in press). The eddy (iso)fluxes were measured by eddy covariance (EC), with a 30- or 35-minute integration period on a 40- or 45-minute duty cycle (the precise duty cycle was changed during the record to accommodate various synergistic measurement campaigns). The storage fluxes were measured as the increase in storage below 29 m during the EC integration period, based on vertical integrations over 7 air sampling heights on the tower (0.2, 1.0, 7.5, 12.7, 18.1, 24.1, 29.0 m, prior to July 3, 2012), or over 6 air sampling heights on the tower (0.2, 1.0, 7.5, 12.7, 18.1, 29.0 m, after July 3, 2012). Some periods are missing at regular intervals because the system was being used for other measurements, not reported here. Corrected and uncorrected versions of the eddy (iso)fluxes are provided; the corrections account for high-frequency signal attenuation, and were made by comparing w-CO2 and w-T cospectra. The precise method is novel and complex and is described, along with all further details of the measurements, in Wehr et al (2013), Long-term eddy covariance measurements of the isotopic composition of the ecosystem–atmosphere exchange of CO2 in a temperat
Net Ecosystem Exchange, Ecosystem Respiration and meteoclimatic data of Alpine grasslands at Nivolet Plain, Gran Paradiso National Park, Italy 2017-2023
<p>This dataset presents georeferenced measurements collected at the Nivolet Plain in Gran Paradiso National Park (GPNP), western Italian Alps. The dataset includes the Net Ecosystem Exchange (NEE), Ecosystem Respiration (ER) and meteo-climatic variables, i.e. air and soil temperature, air relative humidity, soil volumetric water content, atmospheric pressure and solar irradiance. The measurements were conducted between 2017 and 2023 at five different sites at an elevation of approximately 2550-2750 meters a.s.l.</p> <p>To estimate NEE and ER, we employed the flux chamber method, measuring the temporal variation of carbon dioxide (CO2) concentration inside the chamber over a period of about 90 seconds. We used a customized portable non-steady-state dynamic flux chamber, paired with an InfraRed Gas Analyzer (IRGA) and a portable weather station. Measurements were taken at around 20 points per site during the snow-free season, spanning from June to October.</p> <p>The dataset is provided in a comma-separated text file (.csv) format. Each record corresponds to a single measurement point, with semicolons used as separators. The "NA" notation indicates values that are not available or have been excluded during quality control processes (e.g., due to battery failure). We use point as decimal separator.</p> <p>The sign convention for the fluxes is: a negative value indicates a CO2 flux from the atmosphere to the ecosystem, while a positive value represents a CO2 flux from the soil/ecosystem to the atmosphere. Consequently, ER values are positive, while NEE values can be positive or negative. The units for NEE and ER fluxes are molCO2 m-2 day-1 and μmolCO2 m-2 second-1. The first values in each record of the dataset indicate the observation details (sampling date, site, etc.), followed by the corresponding measured or calculated variables. NEE and ER values were estimated from the slope of the linear regression of CO2 concentration over time (ppm s-1) using a laboratory calibration curve.</p> <p>The calibration curve was created by relating known and pre-set CO2 fluxes (within the range expected in the field) with the corresponding measured slopes. The flux values were then scaled up based on the area of the chamber base (0.036 m2) and adjusted using the ratio of atmospheric pressure and air temperature during the measurement to those recorded during the calibration in the laboratory.</p>
CO2 Net Ecosystem Exchange (NEE) and Ecosystem Respiration (ER) + meteorological parameters in alpine grasslands at Nivolet Plain, Gran Paradiso National Park, 2020 (IGG-CNR-CZO@NIVOLET)
<p>CO2 Net Ecosystem Exchange (NEE) and Ecosystem Respiration (ER) measured at Nivolet Plain, Gran Paradiso National Park, Italy, in a high-altitude Alpine grassland environment (about 2500-2700 m.a.s.l.) using the closed portable flux chamber method during the 2020 vegetative season (July-October), approximately twice a month. NEE is measured with a transparent chamber, while ER with a dark chamber (transparent chamber shaded with a cloth). Data represent the average values and the corresponding standard deviations obtained from five sites at different altitudes and soil substrates. Each average value is obtained as a mean over a set of 20 point-measurements for each site and each sampling date. Flux data are complemented by measurements of soil temperature and soil volumetric water content, air temperature, air RH, and solar radiance.</p> <p>During the measurement, air is pumped from the chamber to an IR gas analyzer (IRGA) and then injected again in the chamber. The CO2 concentration inside the chamber is measured for about 90 seconds and then the rate of concentration change is linearly interpolated (over 60s) to obtain the flux measurements. A detailed description of the sampling method can be found in Magnani et al. (2020).</p> <p>Instrumentation used: accumulation chambers (height: 31.5 cm; area of the base: 363 cm2), LI-COR LI-840 & LI-850 IR spectrophotometers, stainless-steel collars (inserted into the soil to a depth of about 1 cm), portable meteorological stations (pyranometer LSI Lastem DPA053, thermohygrometer LSI Lastem DMA672.1), pt100 soil temperature sensors, SM150T soil moisture sensor.</p>
CO2 Net Ecosystem Exchange (NEE) and Ecosystem Respiration (ER) + meteorological parameters in alpine grasslands at Nivolet Plain, Gran Paradiso National Park, 2021 (IGG-CNR-CZO@NIVOLET)
<p>CO2 Net Ecosystem Exchange (NEE) and Ecosystem Respiration (ER) measured at Nivolet Plain, Gran Paradiso National Park, Italy, in a high-altitude Alpine grassland environment (about 2500-2700 m.a.s.l.) using the closed portable flux chamber method during the 2021 vegetative season (July-October), approximately twice a month. NEE is measured with a transparent chamber, while ER with a dark chamber (transparent chamber shaded with a cloth). Data represent the average values and the corresponding standard deviations obtained from five sites at different altitudes and soil substrates. Each average value is obtained as a mean over a set of 20 point-measurements for each site and each sampling date. Flux data are complemented by measurements of soil temperature and soil volumetric water content, air temperature, air RH, and solar radiance.</p> <p>During the measurement, air is pumped from the chamber to an IR gas analyzer (IRGA) and then injected again in the chamber. The CO2 concentration inside the chamber is measured for about 90 seconds and then the rate of concentration change is linearly interpolated (over 60s) to obtain the flux measurements. A detailed description of the sampling method can be found in Magnani et al. (2020).</p> <p>Instrumentation used: accumulation chambers (height: 31.5 cm; area of the base: 363 cm2), LI-COR LI-840 & LI-850 IR spectrophotometers, stainless-steel collars (inserted into the soil to a depth of about 1 cm), portable meteorological stations (pyranometer LSI Lastem DPA053, thermohygrometer LSI Lastem DMA672.1), pt100 soil temperature sensors, SM150T soil moisture sensor.</p>
Global net ecosystem exchange of CO2 inferred from the OCO-2 XCO2 retrievals (GCAS OCO-2 inversion)
<p>Here is a dataset of global carbon flux estimates over 2015-2019 using the OCO-2 column-averaged dry-air mole fraction (XCO<sub>2</sub>) retrievals (ACOS XCO<sub>2</sub> v10) by the global carbon assimilation system (GCAS v2) (Jiang et al., 2021). </p> <p> </p> <p><strong>Citations:</strong></p> <p>Jiang, F. et al., 2021. Regional CO2 fluxes from 2010 to 2015 inferred from GOSAT XCO2 retrievals using a new version of the Global Carbon Assimilation System. Atmos. Chem. Phys., 21(3): 1963-1985.</p> <p>Jiang, F. et al., 2022. A 10-year global monthly averaged terrestrial net ecosystem exchange dataset inferred from the ACOS GOSAT v9 XCO2 retrievals (GCAS2021), Earth Syst. Sci. Data., 14, 3013–3037.</p> <p>He, W., Jiang, F., Ju, W., et al. Improved constraints on the recent terrestrial carbon sink over China by assimilating OCO-2 XCO<sub>2 </sub>retrievals, JGR-Atmopsheres, 2022, under review.</p> <p><strong>Contacts: </strong></p> <p>Wei He (weihe@nju.edu.cn); Fei Jiang (jiangf@nju.edu.cn)</p> <p>Note: <strong>If you want to use this dataset for your researches, please contact us in advances. </strong>Thank you!</p>
AgriCarbon-EO Winter wheat Net Ecosystem Exchange and Biomass over South-west France at 10 m resolution
<p>Dataset contains the outputs of the AgriCarbon-EO</p> <p>An agronomical modeling tool for the carbon and water flux estimates by Bayesian assimilation of S2 and LandSat8 remote sensing data into the Prosail radiative transfer model and the SAFYE-CO2 crop model.<br> -----------------------<br> -for TILE : T31TCJ <br> -for year: 2017<br> -for Winter wheat crops<br> - at 10 m resolution</p> <p> </p> <p>Maps:<br> -file: "GLA_statmap.tif"<br> Description: A raster with 4 bands containing respectively:<br> *The R2 of the GLAI observed by satellite and simulations from 2016/11/01 until 2017/08/01<br> *The RMSE of the GLAI observed by satellite and simulations from 2016/11/01 until 2017/08/01<br> *The Bias of the GLAI observed by satellite and simulations from 2016/11/01 until 2017/08/01<br> *The number of images that are assimilated into SAFYE-CO2 from 2016/11/01 until 2017/08/01</p> <p>-file: "emerg_wheat_2017.tif"<br> Description: A raster with 2 bands containing respectively:<br> *The mean value of emerg retrieved by the SAFYE-CO2 inversion in days of simulation (the simulation begins the 01/01/2016).<br> *The standard deviation of emerg retrieved by the SAFYE-CO2 inversion.<br> <br> -file: "LUEa_wheat_2017.tif"<br> Description: A raster with 2 bands containing respectively:<br> *The mean value of LUEa retrieved by the SAFYE-CO2 inversion in g/MJ.<br> *The standard deviation of LUEa retrieved by the SAFYE-CO2 inversion in g/MJ.</p> <p>-file: "SENa_wheat_2017.tif"<br> Description: A raster with 2 bands containing respectively:<br> *The mean value of Sena retrieved by the SAFYE-CO2 inversion in °C.<br> *The standard deviation of Sena retrieved by the SAFYE-CO2 inversion in °C.</p> <p>-file: "SENb_wheat_2017.tif"<br> Description: A raster with 2 bands containing respectively:<br> *The mean value of SENb retrieved by the SAFYE-CO2 inversion.<br> *The standard deviation of SENb retrieved by the SAFYE-CO2 inversion.</p> <p>-file: "PRT_La_wheat_2017.tif"<br> Description: A raster with 2 bands containing respectively:<br> *The mean value of DAM retrieved by the SAFYE-CO2 inversion.<br> *The standard deviation of DAM retrieved by the SAFYE-CO2 inversion.</p> <p>-file: "DAM_wheat_2017.tif"<br> Description: A raster with 2 bands containing respectively:<br> *The mean value of DAM retrieved by the SAFYE-CO2 inversion in g/m2.<br> *The standard deviation of DAM retrieved by the SAFYE-CO2 inversion in g/m2.</p> <p>-file: "NEP_wheat_2017.tif"<br> Description: A raster with 2 bands containing respectively:<br> *The mean value of NEP retrieved by the SAFYE-CO2 inversion in g/m2.<br> *The standard deviation of NEP retrieved by the SAFYE-CO2 inversion in g/m2.</p> <p>-file: "NECB_exportG_wheat_2017.tif"<br> Description: A raster with 2 bands containing respectively:<br> *The mean value of NECB retrieved by the SAFYE-CO2 inversion in g/m2 , considering an export scénario with grains export only.<br> *The standard deviation of NECB_exportG retrieved by the SAFYE-CO2 inversion in g/m2.</p> <p>-file: "NECB_exportGLS_wheat_2017.tif"<br> Description: A raster with 2 bands containing respectively:<br> *The mean value of NECB retrieved by the SAFYE-CO2 inversion in g/m2, considering an export scénario with grains, stems and leaves.<br> *The standard deviation of NECB_exportGLS retrieved by the SAFYE-CO2 inversion in g/m2.</p> <p> </p> <p>Shapefiles a GIS: <br> -file: "S2_TILE_T31TCJ.shp"<br> Description: shape file of the contour of the T231 TCJ sentinel2 tile <br> -file: "FR_AUR.shp"<br> Description: shape file of the contour of AURADE experimental field <br> -file: "FR_AUR_TOWER.shp"<br> Description: shape file of the location of the AURADE eddy covariance flux tower<br> -file: "POI_2017.shp"<br> Description: shape file of the location of points of interest that illustrate the ... paper<br> -file: "ESU_DAM.shp"<br> Description: shape file of the contour of the plots where dry biomass samples were taken.<br> -file: "ESU_DAM_points.shp"<br> Description: shape file of the location of the points where dry biomass samples were taken.<br> -file: "mapT31TCJ_spamaps.qgz"<br> QGIS project file for the visualisation of the NEP maps.<br> </p>
Dataset for "Inter-annual variability of summer net ecosystem CO2 exchange in High Arctic tundra" by Braybrook et al.
<p>A dataset with 30 min net ecosystem carbon dioxide exchange measurements (NEE) with and without gap-filling, derived component fluxes, gross primary productivity (GPP) and ecosystem respiration (R<sub>eco</sub>) and ancillary weather variables used to investigate how summer NEE, GPP and R<sub>eco</sub> varied over five years (2008, 2009, 2010, 2012, and 2014) at the Cape Bounty Arctic Watershed Observatory (CBAWO) (74.92˚N, 109.58˚W). The eddy covariance technique was used to measure NEE and a combined light and temperature response model was used to partition NEE into GPP and R<sub>eco</sub>. Further measurement and data processing details are described in the research paper, "Inter-annual variability of summer net ecosystem CO<sub>2</sub> exchange in High Arctic tundra", JGR Biogeosciences, 2021.</p>
Net ecosystem exchange measurements throughout the 2020 growing season across an N fertilization gradient:Nutrient Network. A cross-site investigation of bottom-up control over herbaceous plant community dynamics and ecosystem function.
This experiment is one implementation of a globally distributed experiment, known as the Nutrient Network. At Cedar Creek, as in over 70 other sites in grasslands around the world, the experiment aims to describe impacts of increased nutrients (nitrogen, phosphorus, potassium, sulfur and other metals) and decreased herbivory (removal of mammals by fencing). Two overarching questions are being explored with these manipulations: 1. To what extent are plant production and diversity co-limited by multiple nutrients in herbaceous-dominated communities? 2. Under what conditions do grazers or fertilization control plant biomass, diversity, and composition? By utilizing identical protocols at diverse grassland sites around the world, NutNet aims to uncover both the generalities in ecosystem functioning, and the contingencies or differences which can obscure those common mechanisms. In addition to the standard NutNet protocol, e247 includes an additional low Nitrogen gradient (1 gram Nitrogen per meter squared per year and 5 grams Nitrogen per meter squared per year in addition to the standard 10 grams Nitrogen per meter squared per year).
The role of OCO-3 XCO2 retrievals in estimating global terrestrial net ecosystem exchanges
<p>1.<strong>Exp_OCO3.zip </strong> includes regional posterior carbon fluxes from the assimilation using OCO-3 observations.</p> <p>2.<strong>Exp_OCO2.zip </strong> includes regional posterior carbon fluxes from the assimilation using OCO-2 observations.</p> <p>3.<strong>Exp_OCO3&2.zip </strong> includes regional posterior carbon fluxes from the joint assimilation using OCO-3 and OCO-2 observations together.</p> <p>4.<strong>posterior.fluxes.Exp_OCO3.nc </strong>includes information on the spatial distribution of annual as well as monthly posterior carbon fluxes from the assimilation using OCO-3 observations during August 2019 to December 2022.</p> <p>5.<strong>posterior.fluxes.Exp_OCO2.nc </strong>includes information on the spatial distribution of annual as well as monthly posterior carbon fluxes from the assimilation using OCO-2 observations during August 2019 to December 2022.</p> <p>6.<strong>posterior.fluxes.Exp_OCO3&2.nc </strong>includes information on the spatial distribution of annual as well as monthly posterior carbon fluxes from the joint assimilation using OCO-3 and OCO-2 observations together during August 2019 to December 2022.</p> <p>7.<strong>evaluation_result.txt</strong> includes the results of the evaluation of posterior carbon fluxes using independent CO2 observations from 66 surface flask sites.</p> <p> </p> <p> </p> <p> </p>
Agreement of multiple night- and daytime filtering approaches of eddy covariance-derived net ecosystem CO2 exchange over a mountain forest. Reproducible workflow.
<p>Datasets and python scripts to reproduce results from the publication <em>Agreement of multiple night- and daytime filtering approaches of eddy covariance-derived net ecosystem CO2 exchange over a mountain forest.</em></p> <p>See README.txt for a description of the single files.</p>
Data for "Toward Robust Estimates of Net Ecosystem Exchanges in Mega-Countries using GOSAT and OCO-2 Observations"
<p>This dataset contains carbon fluxes for the 10 largest countries in the world (here EU27 is treated as a country) using GOSAT and OCO-2 observational constraints for 2017-2019.</p>
Daily Net Ecosystem Exchange data for the Rur Catchment Area 2010-2018
<p>Daily raster between 2010 and 2018 of Net Ecosystem Exchange (NEE) for the Rur catchment in western Germany at 250 m spatial resolution as upscaling results for the article <em>Upscaling Net Ecosystem Exchange over Heterogeneous Landscapes with Machine Learning</em> in JGR Biogeosciences.</p> <p>COSMO REA6 data and daily grids of potential evapotranspiration and soil moisture were obtained from the German Weather Service (DWD). ftp://opendata.dwd.de/</p> <p> </p> <p>Bollmeyer, C., Keller, J. D., Ohlwein, C., Wahl, S., Crewell, S., Friederichs, P., et al. (2015). Towards a high-resolution regional re-analysis for the European CORDEX domain. <em>Quarterly Journal of the Royal Meteorological Society, 141</em>, 1–15. <a href="https://doi.org/10.1002/qj.2486">https://doi.org/10.1002/qj.2486</a></p> <p>DWD Climate Data Center (CDC): Daily grids of potential evapotranspiration over grass, version 0.x, 2020.</p> <p>DWD Climate Data Center (CDC): Daily grids of soil moisture under grass and sandy loam, version 0.x,2020.</p>
Data from: Effects of plant functional group loss on soil biota and net ecosystem exchange: a plant removal experiment in the Mongolian grassland
Open the record for dataset details and reuse information.
NACP North American 8-km Net Ecosystem Exchange and Component Fluxes, 2004
This data set provides modeled carbon flux estimates at 8-km spatial resolution over North America for the year 2004 of (1) net ecosystem exchange (NEE) of carbon dioxide (CO2), (2) net ecosystem production (NEP, the balance of net primary production and heterotrophic respiration), (3) stream evasion (CO2 emitted from streams and rivers), (4) emissions from harvested forest and agricultural products, and (5) emissions from biomass burning.Annual estimates, in g C/m2/year, are provided for all five fluxes. Daily estimates, in g C/m2/day, are provided for NEP and stream evasion fluxes. Fluxes for fire emissions, harvest decomposition/respiration, stream evasion, and NEP were derived as described in Section 5.NEE fluxes were estimated using a full bottom-up accounting of NEE produced by integrating emissions from harvested forest and agricultural products, CO2 emitted from streams and rivers, and biomass burning in the CarbonTracker (version 2011_oi) modeling system. NEE estimates were run in the forward mode through the CarbonTracker inversion setup that calculates CO2 uptake and release at the Earth's surface over time. Refer to Turner et al.(2013) for details.There are seven data files in NetCDF (.nc) format with this data set, including: five annual files for fire emissions, harvest decomposition/respiration, stream evasion, NEP, and NEE fluxes; and two daily files for NEP and stream evasion fluxes.
AirMOSS: L4 Modeled Net Ecosystem Exchange (NEE), Continental USA, 2012-2014
This data set provides Level 4 estimates of Net Ecosystem Exchange (NEE) of CO2 across the conterminous USA at a spatial resolution of 50 km. Modeled estimates are provided at hourly and monthly temporal resolutions, from January 2012 through October 2014. The AirMOSS L4 Regional NEE data were produced by the Ecosystem Demography Biosphere Model (ED2) augmented by the AirMOSS-derived L2/3 root zone soil moisture data as an additional input. The AirMOSS soil moisture data were used to estimate the sensitivity of carbon fluxes to soil moisture and to diagnose and improve estimation and prediction of NEE by constraining the model's predictions of soil moisture and its impact on above- and below-ground fluxes.
AirMOSS: L4 Daily Modeled Net Ecosystem Exchange (NEE), AirMOSS sites, 2012-2014
This data set provides Level 4 daily estimates of Net Ecosystem Exchange (NEE) of CO2 at a spatial resolution of 30 arc-seconds (~1 km) for seven of the sites covered by the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) flights, each site spanning ~2500 km2. The daily NEE estimates are generally available from October 2012 through October 2014, although the exact time ranges vary by site. The AirMOSS L4 daily NEE were produced by the Ecosystem Demography Biosphere Model (ED2) augmented by the AirMOSS-derived L2/3 root zone soil moisture data as an additional input. The AirMOSS soil moisture data were used to estimate the sensitivity of carbon fluxes to soil moisture and to diagnose and improve estimation and prediction of NEE by constraining the model's predictions of soil moisture and its impact on above- and below-ground fluxes.
CMS: Modeled Net Ecosystem Exchange at 3-hourly Time Steps, 2004-2010
This data set provides global, gridded, model-derived net ecosystem exchange (NEE) of CO2 flux between the land and atmosphere at 3-hourly time steps over seven years (2004-2010) at three different spatial resolutions: 0.5 x 0.5 degree, 2.0 x 2.5 degrees, and 4.0 x 5.0 degrees (latitude/longitude). The 3-hourly data were derived from monthly NEE outputs of 15 global land surface models and four ensemble products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP).
ABoVE: TVPRM Simulated Net Ecosystem Exchange, Alaskan North Slope, 2008-2017
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).
Carbon Monitoring System Flux from the Net Ecosystem Exchange L4 V1 (CMSFluxNEE) at GES DISC
This dataset provides the Carbon Flux from the Net Ecosystem Exchange.The NASA Carbon Monitoring System (CMS) 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 will use the full range of NASA satellite 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 will maintain a global emphasis while providing finer scale regional information, utilizing space-based and surface-based data and will rapidly initiate generation and distribution of products both for user evaluation and to inform near-term policy development and planning.
CARVE: Net Ecosystem CO2 Exchange and Regional Carbon Budgets for Alaska, 2012-2014
This data set provides estimates of 3-hourly net ecosystem CO2 exchange (NEE) at 0.5-degree resolution over the state of Alaska for 2012-2014. The NEE estimates are the output are from Geostatistical Inverse Modeling of a subset of CARVE aircraft CO2 data, WRF-STILT footprints, and PVPRM-SIF data from flux towers (CRV: located in Fox, AK and BRW: located just outside Barrow, AK). Daily mean NEE is also provided as calculated for all of Alaska and for four sub-regions (0.5-degree resolution) that were defined across Alaska, based on general landcover type: North Slope Tundra, South and West Tundra, Boreal Forests, and Mixed (all other). Also provided are derived annual carbon budgets for (1) all of Alaska with defined contributions from biogenic, fossil fuel, and biomass burning sources and (2) annual biogenic carbon budgets for the four landcover-type regions of Alaska. Provided for completeness are the CARVE aircraft atmospheric measurement data used in estimating NEE.
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