Historical global Earth System Model simulations with E3SM's dynamic root module Article Swipe
Max Berkelhammer
,
Beth Drewniak
,
Miquel A. Gonzàlez‐Meler
,
Benjamin Ahlswede
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.15485/1814209
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.15485/1814209
This data package contains global-scale Earth System Model simulations run with DOE's E3SM Model. The package includes one set of simulations run in the default configuration and a second set of simulations run with the dynamic root module enabled. These two datasets can be used to assess the impact that dynamic roots have on Land Surface fluxes such as carbon and water. The outputs are provided here on a 0.5 x 0.5 global grid at monthly resolution. The simulations were run with atmospheric forcing from the Global Soil Wetness Project. We provide specifically here Gross Primary Production, Transpiration, relative root fraction per soil layer as well as Air Temperature, Precipitation and all the parameterizations used for the simulations. Our purpose for generating and analyzing these simulations was to assess the role that root dynamics and foraging for water has in the recovery timescale of ecosystems following climate perturbation. All data provided are in the "netcdf" format using standard CF-1 (Climate and Forecast) Convention. The data are broken up into 20 year chunks to facilitate easier read-in. The data are all machine readable using various software platforms including Matlab, NCO, Panoply and GrADS.
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https://doi.org/10.15485/1814209Digital Object Identifier
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Historical global Earth System Model simulations with E3SM's dynamic root moduleWork title
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datasetOpenAlex work type
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enPrimary language
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2021Year of publication
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2021-01-01Full publication date if available
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Max Berkelhammer, Beth Drewniak, Miquel A. Gonzàlez‐Meler, Benjamin AhlswedeList of authors in order
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https://www.osti.gov/biblio/1814209Publisher landing page
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| abstract_inverted_index.software | 184 |
| abstract_inverted_index.standard | 157 |
| abstract_inverted_index.Forecast) | 161 |
| abstract_inverted_index.analyzing | 123 |
| abstract_inverted_index.following | 145 |
| abstract_inverted_index.including | 186 |
| abstract_inverted_index.platforms | 185 |
| abstract_inverted_index.timescale | 142 |
| abstract_inverted_index.ecosystems | 144 |
| abstract_inverted_index.facilitate | 173 |
| abstract_inverted_index.generating | 121 |
| abstract_inverted_index.Convention. | 162 |
| abstract_inverted_index.Production, | 96 |
| abstract_inverted_index.atmospheric | 82 |
| abstract_inverted_index.resolution. | 76 |
| abstract_inverted_index.simulations | 8, 20, 31, 78, 125 |
| abstract_inverted_index.Temperature, | 108 |
| abstract_inverted_index.global-scale | 4 |
| abstract_inverted_index.simulations. | 117 |
| abstract_inverted_index.specifically | 92 |
| abstract_inverted_index.Precipitation | 109 |
| abstract_inverted_index.configuration | 25 |
| abstract_inverted_index.perturbation. | 147 |
| abstract_inverted_index.Transpiration, | 97 |
| abstract_inverted_index.parameterizations | 113 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile |