Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin

Shi, Mingjie; Mcdowell, Nate G.; Huang, Huilin; Zahura, Faria; Li, Lingcheng; Forbes, Brieanne; Powers-McCormack, Beck; Chen, Xingyuan

doi:10.15485/2507048

Title: Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin

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Abstract

This data package is associated with the publication “Ecosystem leaf area, gross primary production, and evapotranspiration responses to wildfire in the Columbia River Basin” submitted to Biogeosciences (Shi et al., 2024; doi: 10.22541/au.171053013.30286044/v1). In this research, data products, leaf area index (LAI), gross primary production (GPP), and evapotranspiration (ET), from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to quantify the resistance and resilience of different ecosystem types in the Columbia River Basin (CRB). A machine learning algorithm, random forest (RF), was used to examine the impacts of precipitation, vapor pressure deficit (VPD), and burn severity from Monitoring Trends in Burn Severity (MTBS) on ecosystem resilience. The data package includes the processed MODIS data products, precipitation, VPD, and burn severity in 138 fire regions in CRB and the input files for RF model training. This data package includes six folders. The MODIS products are included in three MODIS_* folders with shell scripts for data clipping and *ncl files for data processing: (1) “/MODIS_LAI_CRB”; (2) “/MODIS_GPP_CRB”; and (3) “/MODIS_ET_CRB”. All the processed data for each fire event are NetCDF formatted. The MTBS burn severity data and the shell and *ncl scripts used for data processing are in the folder named (4)more »« less

Authors:

; Mcdowell, Nate G.;

;

Pacific Northwest National Laboratory (PNNL); Pacific Northwest National Laboratory (PNNL)
Pacific Northwest National Laboratory (PNNL)

Publication Date:: Tue Dec 31 23:00:00 EST 2024

DOE Contract Number:: AC02-05CH11231

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem; River Corridor and Watershed Biogeochemistry SFA

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; Burn severity; CRB; Columbia River Basin; EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WATER VAPOR > WATER VAPOR PROCESSES > EVAPOTRANSPIRATION; ESS-DIVE CSV File Formatting Guidelines Reporting Format; ESS-DIVE File Level Metadata Reporting Format; ESS-DIVE Model Data Archiving Guidelines; ET; Evapotranspiration; GPP; Gross primary production; LAI; LCT; Land Cover Type; Leaf area index; MODIS; MTBS; Moderate Resolution Imaging Spectroradiometer; Monitoring Trends in Burn Severity; Precipitation; Random Forest; Resilience; Resistance; Surface air temperature; VPD; VT; Vegetation Type; Water vapor deficit

OSTI Identifier:: 2507048

DOI:: https://doi.org/10.15485/2507048

Citation Formats


                    Shi, Mingjie, Mcdowell, Nate G., Huang, Huilin, Zahura, Faria, Li, Lingcheng, Forbes, Brieanne, Powers-McCormack, Beck, and Chen, Xingyuan. Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin.  United States: N. p., 2024. 
        Web.  doi:10.15485/2507048.

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                    Shi, Mingjie, Mcdowell, Nate G., Huang, Huilin, Zahura, Faria, Li, Lingcheng, Forbes, Brieanne, Powers-McCormack, Beck, & Chen, Xingyuan. Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin.  United States.  doi:https://doi.org/10.15485/2507048

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                    Shi, Mingjie, Mcdowell, Nate G., Huang, Huilin, Zahura, Faria, Li, Lingcheng, Forbes, Brieanne, Powers-McCormack, Beck, and Chen, Xingyuan. 2024.  
"Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin".  United States.  doi:https://doi.org/10.15485/2507048.  https://www.osti.gov/servlets/purl/2507048. Pub date:Tue Dec 31 23:00:00 EST 2024

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@article{osti_2507048,

  title        = {Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin},

  author       = {Shi, Mingjie and Mcdowell, Nate G. and Huang, Huilin and Zahura, Faria and Li, Lingcheng and Forbes, Brieanne and Powers-McCormack, Beck and Chen, Xingyuan},

  abstractNote = {This data package is associated with the publication “Ecosystem leaf area, gross primary production, and evapotranspiration responses to wildfire in the Columbia River Basin” submitted to Biogeosciences (Shi et al., 2024; doi: 10.22541/au.171053013.30286044/v1). In this research, data products, leaf area index (LAI), gross primary production (GPP), and evapotranspiration (ET), from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to quantify the resistance and resilience of different ecosystem types in the Columbia River Basin (CRB). A machine learning algorithm, random forest (RF), was used to examine the impacts of precipitation, vapor pressure deficit (VPD), and burn severity from Monitoring Trends in Burn Severity (MTBS) on ecosystem resilience. The data package includes the processed MODIS data products, precipitation, VPD, and burn severity in 138 fire regions in CRB and the input files for RF model training. This data package includes six folders. The MODIS products are included in three MODIS_* folders with shell scripts for data clipping and *ncl files for data processing: (1) “/MODIS_LAI_CRB”; (2) “/MODIS_GPP_CRB”; and (3) “/MODIS_ET_CRB”. All the processed data for each fire event are NetCDF formatted. The MTBS burn severity data and the shell and *ncl scripts used for data processing are in the folder named (4) “MTBS_fire”. The ERA meteorological fields and the data processing scritps are in (5) “ERA_Var_CR”. All the scripts for figure development are in the format of *ncl and in the folder (6) “paper_scripts”. See the file ending in “flmd.csv” for a list of all files contained in this data package and descriptions for each. Tabular column headers and units are described in the data dictionary file ending in “dd.csv”.},

  doi          = {10.15485/2507048},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Dec 31 23:00:00 EST 2024},

  month        = {Tue Dec 31 23:00:00 EST 2024}

}

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DOI: https://doi.org/10.15485/2507048

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