M. Flanner


2019

DOI bib
The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty
David M. Lawrence, Rosie A. Fisher, Charles D. Koven, Keith W. Oleson, Sean Swenson, G. B. Bonan, Nathan Collier, Bardan Ghimire, Leo van Kampenhout, Daniel Kennedy, Erik Kluzek, Fang Li, Hongyi Li, Danica Lombardozzi, William J. Riley, William J. Sacks, Mingjie Shi, Mariana Vertenstein, William R. Wieder, Chonggang Xu, Ashehad A. Ali, Andrew M. Badger, Gautam Bisht, Michiel van den Broeke, Michael A. Brunke, Sean P. Burns, J. R. Buzan, Martyn P. Clark, Anthony P Craig, Kyla M. Dahlin, Beth Drewniak, Joshua B. Fisher, M. Flanner, A. M. Fox, Pierre Gentine, Forrest M. Hoffman, G. Keppel‐Aleks, R. G. Knox, Sanjiv Kumar, Jan T. M. Lenaerts, L. Ruby Leung, William H. Lipscomb, Yaqiong Lü, Ashutosh Pandey, Jon D. Pelletier, J. Perket, James T. Randerson, Daniel M. Ricciuto, Benjamin M. Sanderson, A. G. Slater, Z. M. Subin, Jinyun Tang, R. Quinn Thomas, Maria Val Martin, Xubin Zeng
Journal of Advances in Modeling Earth Systems, Volume 11, Issue 12

The 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.

2018

DOI bib
ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks
Gerhard Krinner, Chris Derksen, Richard Essery, M. Flanner, Stefan Hagemann, Martyn P. Clark, Alex Hall, Helmut Rott, Claire Brutel‐Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad W. Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, F. Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy M. Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, R. M. Law, David M. Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, О. Н. Насонова, Tomoko Nitta, Michio Niwano, John W. Pomeroy, M. S. Raleigh, Gerd Schaedler, В. А. Семенов, Tanya Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, Dan Zhu
Geoscientific Model Development, Volume 11, Issue 12

Abstract. This paper describes ESM-SnowMIP, an international coordinated modelling effort to evaluate current snow schemes, including snow schemes that are included in Earth system models, in a wide variety of settings against local and global observations. The project aims to identify crucial processes and characteristics that need to be improved in snow models in the context of local- and global-scale modelling. A further objective of ESM-SnowMIP is to better quantify snow-related feedbacks in the Earth system. Although it is not part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), ESM-SnowMIP is tightly linked to the CMIP6-endorsed Land Surface, Snow and Soil Moisture Model Intercomparison (LS3MIP).
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