IMHE OpenIR  > 山地表生过程与生态调控重点实验室
The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty
Lawrence David M.1; Fisher Rosie A.1; Koven Charles D.2; Oleson Keith W.1; Swenson Sean C.1; Bonan Gordon1; Collier Nathan3; Ghimire Bardan2; van Kampenhout Leo4; Kennedy Daniel5; Kluzek Erik1; Lawrence Peter J.1; Li Fang6; Li Hongyi7; Lombardozzi Danica1; Riley William J.2; Sacks William J.1; Shi Mingjie8,9; Vertenstein Mariana1; Wieder William R.1,18; Xu Chonggang10; Ali Ashehad A.11; Badger Andrew M.1; Bisht Gautam2; van den Broeke Michiel4; Brunke Michael A.13; Burns Sean P.14,35; Buzan Jonathan15; Clark Martyn1; Craig Anthony1; Dahlin Kyla16; Drewniak Beth17; Fisher Joshua B.8,9; Flanner Mark19; Fox Andrew M.20; Gentine Pierre5; Hoffman Forrest3; Keppel-Aleks Gretchen21; Knox Ryan2; Kumar Sanjiv22; Lenaerts Jan23; Leung L. Ruby24; Lipscomb William H.1; Lu Yaqiong25; Pandey Ashutosh22; Pelletier Jon D.26; Perket Justin1,27; Randerson James T.28; Ricciuto Daniel M.29; Sanderson Benjamin M.30; Slater Andrew31; Subin Zachary M.32; Tang Jinyun2; Thomas R. Quinn33; Martin Maria Val34; Zeng Xubin13
Corresponding AuthorLawrence, David M.(dlawren@ucar.edu)
2019
Source PublicationJOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
EISSN1942-2466
Volume11Issue:12Pages:4245-4287
SubtypeArticle
AbstractThe Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.
Keywordglobal land model Earth System Modeling carbon and nitrogen cycling hydrology benchmarking
DOI10.1029/2018MS001583
Indexed BySCI
WOS KeywordWATER-USE EFFICIENCY ; DROUGHT DECIDUOUS PHENOLOGY ; NET PRIMARY PRODUCTIVITY ; CARBON USE EFFICIENCY ; GLOBAL SOIL-MOISTURE ; EARTH SYSTEM MODEL ; ICE-SHEET MODEL ; INTERCOMPARISON PROJECT ; DATA ASSIMILATION ; NITROGEN-CYCLE
Language英语
Quartile2区
Funding ProjectNational Science Foundation (NSF) ; National Center for Atmospheric Research - NSF[1852977] ; RUBISCO Scientific Focus Area (SFA) - Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science ; Columbia University Presidential Fellowship ; U.S. Department of Agriculture NIFA Award[2015-67003-23485] ; NASA Interdisciplinary Science Program Award[NNX17AK19G] ; U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science program[DE-SC0008317] ; U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science program[DESC0016188] ; National Science Foundation[DEB-1153401] ; NASA's CARBON program ; NASA's TE program ; National Aeronautics and Space Administration
TOP
WOS Research AreaMeteorology & Atmospheric Sciences
WOS SubjectMeteorology & Atmospheric Sciences
WOS IDWOS:000502568600001
Funding OrganizationNational Science Foundation (NSF) ; National Center for Atmospheric Research - NSF ; RUBISCO Scientific Focus Area (SFA) - Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science ; Columbia University Presidential Fellowship ; U.S. Department of Agriculture NIFA Award ; NASA Interdisciplinary Science Program Award ; U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science program ; National Science Foundation ; NASA's CARBON program ; NASA's TE program ; National Aeronautics and Space Administration
PublisherAMER GEOPHYSICAL UNION
Citation statistics
Cited Times:57[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/33561
Collection山地表生过程与生态调控重点实验室
Corresponding AuthorLawrence David M.
Affiliation1.Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA;
2.Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA;
3.Computer Science and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA;
4.Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, The Netherlands;
5.Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA;
6.International Center for Climate and Environmental Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China;
7.Department of Civil & Environmental Engineering, University of Houston, Houston, TX, USA;
8.Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA;
9.Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, USA;
10.Los Alamos National Laboratory, Los Alamos, NM, USA;
11.Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA;
12.Cooperative Institute for Research in Environmental Sciences, Boulder, CO, USA;
13.Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA;
14.Department of Geography, University of Colorado Boulder, Boulder, CO, USA;
15.Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA;
16.Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, USA;
17.Environmental Science Division, Argonne National Laboratory, Argonne, IL, USA;
18.Institute of Arctic and Alpine Research, University of Colorado Boulder, Boulder, CO, USA;
19.Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI, USA;
20.School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA;
21.Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, CA, USA;
22.School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL, USA;
23.Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO, USA;
24.Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA;
25.Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China;
26.Department of Geosciences, University of Arizona, Tucson, AZ, USA;
27.NASA Goddard Space Flight Center, Greenbelt, MD, USA;
28.Department of Earth System Science, University of California, Irvine, CA, USA;
29.Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA;
30.CERFACS, Toulouse, France;
31.National Snow and Ice Data Center, Boulder, CO, USA;
32.Energy & Environmental Economics, San Francisco, CA, USA;
33.Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA;
34.Leverhulme Centre for Climate Change Mitigation, Animal and Plant Sciences Department, University of Sheffield, Sheffield, UK;
35.Mesoscale and Microscale Meteorology Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Recommended Citation
GB/T 7714
Lawrence David M.,Fisher Rosie A.,Koven Charles D.,et al. The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty[J]. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS,2019,11(12):4245-4287.
APA Lawrence David M..,Fisher Rosie A..,Koven Charles D..,Oleson Keith W..,Swenson Sean C..,...&Zeng Xubin.(2019).The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty.JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS,11(12),4245-4287.
MLA Lawrence David M.,et al."The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty".JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 11.12(2019):4245-4287.
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