U.S. Department of EnergyOffice of Scientific and Technical Information
BSEC VPRM 10m Hourly Biogenic Fluxes in Baltimore (2021)
Abstract
Model outputs from the Vegetation Photosynthesis and Respiration Model (VPRM: version from Horne et al. in prep). Model remote sensing inputs come from Sential 2-derived EVI and LSWI. Model meteorological inputs for two-meter air temperature and shortwave incoming come from the BSEC WRF 2021 Control Run (Foust, W. 2023). Plant functional Types (PFTs) are spatially classified using the Chesapeake Bay Program 2018 land use land cover product. The final biogenic flux (µmol CO2 m^-2 s^-1) outputs of NEE, RESP, and GEE are a weighted average based on the portion of PFTs within the cell. Individual PFT outputs are saved inside PFT directories (e.g., Crops, Grass, etc.) inside the specific month directory. Model outputs are denoted as a negative flux into the land system (i.e., photosynthesis) and a positive flux as a net release into the overlying atmosphere. Respiration (RESP) fluxes are positive and combine heterotrophic (only soil) and autotrophic sources. Gross ecosystem exchange (GEE) is a negative flux driven by only photosynthetic activity from vegetation, and the Net ecosystem exchange (NEE) is the sum of the two (i.e., NEE=RESP+GEE). Data Characteristics Spatial Resolution: 10m Temporal Resolution: Hourly File Format: VPRM__BSEC..tif (Hour is in UTC) For more information on the model results,more »
- Publication Date:
- Research Org.:
- Pacific Northwest National Lab (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Subject:
- BSEC; Baltimore; Baltimore City; Baltimore MD; Climate Change; Ecology; Ecosystems; Land; Urban; VPRM; WRF; baltimore; carbon cycling; carbon dioxide; raster
- OSTI Identifier:
- 2439942
- DOI:
- https://doi.org/10.57931/2439942
Citation Formats
Horne, Jason. BSEC VPRM 10m Hourly Biogenic Fluxes in Baltimore (2021). United States: N. p., 2024.
Web. doi:10.57931/2439942.
Horne, Jason. BSEC VPRM 10m Hourly Biogenic Fluxes in Baltimore (2021). United States. doi:https://doi.org/10.57931/2439942
Horne, Jason. 2024.
"BSEC VPRM 10m Hourly Biogenic Fluxes in Baltimore (2021)". United States. doi:https://doi.org/10.57931/2439942. https://www.osti.gov/servlets/purl/2439942. Pub date:Mon Sep 09 00:00:00 EDT 2024
@article{osti_2439942,
title = {BSEC VPRM 10m Hourly Biogenic Fluxes in Baltimore (2021)},
author = {Horne, Jason},
abstractNote = {Model outputs from the Vegetation Photosynthesis and Respiration Model (VPRM: version from Horne et al. in prep). Model remote sensing inputs come from Sential 2-derived EVI and LSWI. Model meteorological inputs for two-meter air temperature and shortwave incoming come from the BSEC WRF 2021 Control Run (Foust, W. 2023). Plant functional Types (PFTs) are spatially classified using the Chesapeake Bay Program 2018 land use land cover product. The final biogenic flux (µmol CO2 m^-2 s^-1) outputs of NEE, RESP, and GEE are a weighted average based on the portion of PFTs within the cell. Individual PFT outputs are saved inside PFT directories (e.g., Crops, Grass, etc.) inside the specific month directory. Model outputs are denoted as a negative flux into the land system (i.e., photosynthesis) and a positive flux as a net release into the overlying atmosphere. Respiration (RESP) fluxes are positive and combine heterotrophic (only soil) and autotrophic sources. Gross ecosystem exchange (GEE) is a negative flux driven by only photosynthetic activity from vegetation, and the Net ecosystem exchange (NEE) is the sum of the two (i.e., NEE=RESP+GEE). Data Characteristics Spatial Resolution: 10m Temporal Resolution: Hourly File Format: VPRM__BSEC..tif (Hour is in UTC) For more information on the model results, please email Jason Horne (jph6488@psu.edu). References: Foust, W. (2023). BSEC WRF 2021 Control Run Output (v0.1.0) [Data set]. MSD-LIVE Data Repository. https://data.msdlive.org/records/m0e6m-vvq17},
doi = {10.57931/2439942},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2024},
month = {9}
}