On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results
<p>Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evaluation of models' ability to do this...
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Copernicus Publications
2024-12-01
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| Series: | Biogeosciences |
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| author | G. Abramowitz G. Abramowitz A. Ukkola A. Ukkola S. Hobeichi S. Hobeichi J. Cranko Page J. Cranko Page M. Lipson M. G. De Kauwe S. Green S. Green C. Brenner C. Brenner J. Frame G. Nearing M. Clark M. Best P. Anthoni G. Arduini S. Boussetta S. Caldararu S. Caldararu K. Cho M. Cuntz D. Fairbairn C. R. Ferguson H. Kim Y. Kim J. Knauer J. Knauer D. Lawrence X. Luo S. Malyshev T. Nitta J. Ogee K. Oleson C. Ottlé P. Peylin P. de Rosnay H. Rumbold B. Su N. Vuichard A. P. Walker X. Wang-Faivre Y. Wang Y. Zeng |
| author_facet | G. Abramowitz G. Abramowitz A. Ukkola A. Ukkola S. Hobeichi S. Hobeichi J. Cranko Page J. Cranko Page M. Lipson M. G. De Kauwe S. Green S. Green C. Brenner C. Brenner J. Frame G. Nearing M. Clark M. Best P. Anthoni G. Arduini S. Boussetta S. Caldararu S. Caldararu K. Cho M. Cuntz D. Fairbairn C. R. Ferguson H. Kim Y. Kim J. Knauer J. Knauer D. Lawrence X. Luo S. Malyshev T. Nitta J. Ogee K. Oleson C. Ottlé P. Peylin P. de Rosnay H. Rumbold B. Su N. Vuichard A. P. Walker X. Wang-Faivre Y. Wang Y. Zeng |
| author_sort | G. Abramowitz |
| collection | DOAJ |
| description | <p>Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evaluation of models' ability to do this is performed in a wide range of simulation environments, often without explicit consideration of the degree of observational constraint or uncertainty and typically without quantification of benchmark performance expectations. We describe a Model Intercomparison Project (MIP) that attempts to resolve these shortcomings, comparing the surface turbulent heat flux predictions of around 20 different land models provided with in situ meteorological forcing evaluated with measured surface fluxes using quality-controlled data from 170 eddy-covariance-based flux tower sites.</p>
<p>Predictions from seven out-of-sample empirical models are used to quantify the information available to land models in their forcing data and so the potential for land model performance improvement. Sites with unusual behaviour, complicated processes, poor data quality, or uncommon flux magnitude are more difficult to predict for both mechanistic and empirical models, providing a means of fairer assessment of land model performance. When examining observational uncertainty, model performance does not appear to improve in low-turbulence periods or with energy-balance-corrected flux tower data, and indeed some results raise questions about whether the energy balance correction process itself is appropriate. In all cases the results are broadly consistent, with simple out-of-sample empirical models, including linear regression, comfortably outperforming mechanistic land models.</p>
<p>In all but two cases, latent heat flux and net ecosystem exchange of CO<span class="inline-formula"><sub>2</sub></span> are better predicted by land models than sensible heat flux, despite it seeming to have fewer physical controlling processes. Land models that are implemented in Earth system models also appear to perform notably better than stand-alone ecosystem (including demographic) models, at least in terms of the fluxes examined here. The approach we outline enables isolation of the locations and conditions under which model developers can <i>know</i> that a land model can improve, allowing information pathways and discrete parameterisations in models to be identified and targeted for future model development.</p> |
| format | Article |
| id | doaj-art-0e1f69fbe78f48a0a8a5c2dcdd806470 |
| institution | DOAJ |
| issn | 1726-4170 1726-4189 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Biogeosciences |
| spelling | doaj-art-0e1f69fbe78f48a0a8a5c2dcdd8064702025-08-20T02:50:20ZengCopernicus PublicationsBiogeosciences1726-41701726-41892024-12-01215517553810.5194/bg-21-5517-2024On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary resultsG. Abramowitz0G. Abramowitz1A. Ukkola2A. Ukkola3S. Hobeichi4S. Hobeichi5J. Cranko Page6J. Cranko Page7M. Lipson8M. G. De Kauwe9S. Green10S. Green11C. Brenner12C. Brenner13J. Frame14G. Nearing15M. Clark16M. Best17P. Anthoni18G. Arduini19S. Boussetta20S. Caldararu21S. Caldararu22K. Cho23M. Cuntz24D. Fairbairn25C. R. Ferguson26H. Kim27Y. Kim28J. Knauer29J. Knauer30D. Lawrence31X. Luo32S. Malyshev33T. Nitta34J. Ogee35K. Oleson36C. Ottlé37P. Peylin38P. de Rosnay39H. Rumbold40B. Su41N. Vuichard42A. P. Walker43X. Wang-Faivre44Y. Wang45Y. Zeng46CLEX, UNSW Sydney, Sydney, AustraliaCCRC, UNSW Sydney, Sydney, AustraliaCLEX, UNSW Sydney, Sydney, AustraliaCCRC, UNSW Sydney, Sydney, AustraliaCLEX, UNSW Sydney, Sydney, AustraliaCCRC, UNSW Sydney, Sydney, AustraliaCLEX, UNSW Sydney, Sydney, AustraliaCCRC, UNSW Sydney, Sydney, AustraliaBureau of Meteorology, Melbourne, AustraliaSchool of Biological Sciences, University of Bristol, Bristol, BS8 1TQ, UKCLEX, UNSW Sydney, Sydney, AustraliaCCRC, UNSW Sydney, Sydney, AustraliaInstitute for Hydrology and Water Management, University of Natural Resources and Life Sciences, Vienna, AustriaDepartment of Geological Sciences, University of Alabama, Tuscaloosa, AL, USADepartment of Geological Sciences, University of Alabama, Tuscaloosa, AL, USAGoogle Research, Mountain View, CA, USADepartment of Civil Engineering, University of Calgary, Calgary, CanadaUKMO, Exeter, UKKarlsruhe Institute of Technology, Institute of Meteorology and Climate Research/Atmospheric Environmental Research, 82467 Garmisch-Partenkirchen, GermanyEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKMax Planck Institute for Biogeochemistry, Jena, GermanyDiscipline of Botany, School of Natural Sciences, trinity College Dublin, Dublin, IrelandDepartment of Civil and Environmental Engineering, Yonsei University, Seoul, South KoreaINRAE, Nancy, FranceEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKAtmospheric Sciences Research Center, University at Albany, State University of New York, Albany, NY, USAHydroKlima Lab, KAIST, Daejeon, South KoreaDepartment of Civil and Environmental Engineering, Yonsei University, Seoul, South KoreaCSIRO Environment, Canberra, AustraliaHawkesbury Institute for the Environment, Western Sydney University, Sydney, AustraliaNCAR, Boulder, CO, USADepartment of Geography, National University of Singapore, SingaporeNOAA GFDL, Princeton, NJ, USAInstitute of Industrial Science, The University of Tokyo, Tokyo, JapanINRAE, Nancy, FranceNCAR, Boulder, CO, USALSCE, Paris, FranceLSCE, Paris, FranceEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKUKMO, Exeter, UKFaculty of Geo-Information Science and Earth Observation, University of Twente, the NetherlandsLSCE, Paris, FranceEnvironmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USALSCE, Paris, FranceFaculty of Geo-Information Science and Earth Observation, University of Twente, the NetherlandsFaculty of Geo-Information Science and Earth Observation, University of Twente, the Netherlands<p>Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evaluation of models' ability to do this is performed in a wide range of simulation environments, often without explicit consideration of the degree of observational constraint or uncertainty and typically without quantification of benchmark performance expectations. We describe a Model Intercomparison Project (MIP) that attempts to resolve these shortcomings, comparing the surface turbulent heat flux predictions of around 20 different land models provided with in situ meteorological forcing evaluated with measured surface fluxes using quality-controlled data from 170 eddy-covariance-based flux tower sites.</p> <p>Predictions from seven out-of-sample empirical models are used to quantify the information available to land models in their forcing data and so the potential for land model performance improvement. Sites with unusual behaviour, complicated processes, poor data quality, or uncommon flux magnitude are more difficult to predict for both mechanistic and empirical models, providing a means of fairer assessment of land model performance. When examining observational uncertainty, model performance does not appear to improve in low-turbulence periods or with energy-balance-corrected flux tower data, and indeed some results raise questions about whether the energy balance correction process itself is appropriate. In all cases the results are broadly consistent, with simple out-of-sample empirical models, including linear regression, comfortably outperforming mechanistic land models.</p> <p>In all but two cases, latent heat flux and net ecosystem exchange of CO<span class="inline-formula"><sub>2</sub></span> are better predicted by land models than sensible heat flux, despite it seeming to have fewer physical controlling processes. Land models that are implemented in Earth system models also appear to perform notably better than stand-alone ecosystem (including demographic) models, at least in terms of the fluxes examined here. The approach we outline enables isolation of the locations and conditions under which model developers can <i>know</i> that a land model can improve, allowing information pathways and discrete parameterisations in models to be identified and targeted for future model development.</p>https://bg.copernicus.org/articles/21/5517/2024/bg-21-5517-2024.pdf |
| spellingShingle | G. Abramowitz G. Abramowitz A. Ukkola A. Ukkola S. Hobeichi S. Hobeichi J. Cranko Page J. Cranko Page M. Lipson M. G. De Kauwe S. Green S. Green C. Brenner C. Brenner J. Frame G. Nearing M. Clark M. Best P. Anthoni G. Arduini S. Boussetta S. Caldararu S. Caldararu K. Cho M. Cuntz D. Fairbairn C. R. Ferguson H. Kim Y. Kim J. Knauer J. Knauer D. Lawrence X. Luo S. Malyshev T. Nitta J. Ogee K. Oleson C. Ottlé P. Peylin P. de Rosnay H. Rumbold B. Su N. Vuichard A. P. Walker X. Wang-Faivre Y. Wang Y. Zeng On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results Biogeosciences |
| title | On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results |
| title_full | On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results |
| title_fullStr | On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results |
| title_full_unstemmed | On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results |
| title_short | On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results |
| title_sort | on the predictability of turbulent fluxes from land plumber2 mip experimental description and preliminary results |
| url | https://bg.copernicus.org/articles/21/5517/2024/bg-21-5517-2024.pdf |
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