@article{890, keywords = {Pharmacology}, author = {Junyi Liang and Gangsheng Wang and Daniel Ricciuto and Lianhong Gu and Paul Hanson and Jeffery Wood and Melanie Mayes}, title = {Evaluating the E3SM land model version 0 (ELMv0) at a temperate forest site using flux and soil water measurements}, abstract = {Abstract. Accurate simulations of soil respiration and carbon dioxide (CO2) fluxes are critical to project global biogeochemical cycles and the magnitude of carbon–climate feedbacks in Earth system models (ESMs). Currently, soil respiration is not represented well in ESMs, and few studies have attempted to address this deficiency. In this study, we evaluated the simulation of soil respiration in the Energy Exascale Earth System Model (E3SM) land model version 0 (ELMv0) using long-term observations from the Missouri Ozark AmeriFlux (MOFLUX) forest site in the central US. Simulations using the default model parameters underestimated soil water potential (SWP) during peak growing seasons and overestimated SWP during non-growing seasons and consequently underestimated annual soil respiration and gross primary production (GPP). A site-specific soil water retention curve greatly improved model simulations of SWP, GPP, and soil respiration. However, the model continued to underestimate the seasonal and interannual variabilities and the impact of the extreme drought in 2012. Potential reasons may include inadequate representations of vegetation mortality, the soil moisture function, and the dynamics of microbial organisms and soil macroinvertebrates. Our results indicate that the simulations of mean annual GPP and soil respiration can be significantly improved by better model representations of the soil water retention curve. }, year = {2019}, booktitle = {Geoscientific Model Development}, journal = {Geoscientific Model Development}, series = {Geoscientific Model Development}, volume = {12}, pages = {1601-1612}, issn = {1991-9603}, doi = {10.5194/gmd-12-1601-2019}, crossref = {}, }