B019-0010
Have Land Surface and Carbon Cycle Processes in Earth System Models Improved Over Time?

Tuesday, 8 December 2020
Poster
Forrest M. Hoffman1,2, Nathan Collier3, Mingquan Mu4, Cheng-En Yang2, Charles Koven5, David M Lawrence6, Gretchen Keppel-Aleks7, Min Xu8, Qing Zhu5, Weiwei Fu4, Jiafu Mao9, Hyungjun Kim10, Jefferson Keith Moore11, William J Riley5 and James Tremper Randerson12, (1)Oak Ridge National Laboratory, Computational Sciences & Engineering Division and Climate Change Science Institute, Oak Ridge, TN, United States, (2)University of Tennessee, Civil and Environmental Engineering, Knoxville, TN, United States, (3)Oak Ridge National Laboratory, Computational Earth Sciences, Oak Ridge, TN, United States, (4)University of California Irvine, Irvine, CA, United States, (5)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (6)National Center for Atmospheric Research, Boulder, CO, United States, (7)University of Michigan Ann Arbor, Climate and Space Sciences and Engineering, Ann Arbor, MI, United States, (8)Oak Ridge National Laboratory, Computational Sciences and Engineering Division and Climate Change Science Institute, Oak Ridge, TN, United States, (9)Oak Ridge National Laboratory, Environmental Sciences Division and Climate Change Science Institute, Oak Ridge, TN, United States, (10)The University of Tokyo, Institute of Industrial Science, Tokyo, Japan, (11)University of California Irvine, Earth System Science, Irvine, CA, United States, (12)University of California Irvine, Department of Earth System Science, Irvine, CA, United States
Abstract:
Better representation of biogeochemistry–climate feedbacks and ecosystem processes in Earth system models (ESMs) is essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century and beyond. Model–data comparison and integration activities are required to inform improvement of land carbon cycle models and the design of new measurement campaigns aimed at reducing uncertainties associated with key land surface processes. The International Land Model Benchmarking (ILAMB) Package was designed to facilitate systematic and comprehensive model–data comparison and improve understanding of factors influencing model fidelity. We used ILAMB to benchmark and intercompare terrestrial carbon cycle models coupled within ESMs used to conduct historical simulations for the Fifth and Sixth Phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). Results indicate that the suite of CMIP6 land models exhibits better performance than the suite of CMIP5 land models in comparison with observations for a variety of biogeochemical, hydrological, and energy-related variables. These improvements are partially attributed to reductions of biases in temperature, precipitation, and incoming radiation, suggesting that free-running atmosphere models in these ESMs also improved; however, biases in some regions increased. An analysis of forcing variables, prognostic land variables, and relationships from variable-to-variable comparisons indicate an overall improvement in most CMIP6 models, with relationships for some models exhibiting the greatest improvement in ILAMB scores, suggesting that improved model process representation in some models, and likely increased model complexity, contributed to improved model performance. We further analyze the degree to which the range of model uncertainties may have been reduced for CMIP6 land models as compared with CMIP5 land models.