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Article

Challenging a Global Land Surface Model in a Local Socio-Environmental System

1
Department of Geography, Environment, and Spatial Sciences, Michigan State University (MSU), East Lansing, MI 48824, USA
2
National Center for Atmospheric Research, Boulder, CO 80305, USA
3
MSU Center for Global Change and Earth Observation, East Lansing, MI 48824, USA
4
Environmental Science, University of Science and Arts of Oklahoma, Chickasha, OK 73018, USA
*
Author to whom correspondence should be addressed.
Land 2020, 9(10), 398; https://doi.org/10.3390/land9100398
Received: 15 September 2020 / Revised: 12 October 2020 / Accepted: 16 October 2020 / Published: 21 October 2020
(This article belongs to the Section Landscape Ecology)
Land surface models (LSMs) predict how terrestrial fluxes of carbon, water, and energy change with abiotic drivers to inform the other components of Earth system models. Here, we focus on a single human-dominated watershed in southwestern Michigan, USA. We compare multiple processes in a commonly used LSM, the Community Land Model (CLM), to observational data at the single grid cell scale. For model inputs, we show correlations (Pearson’s R) ranging from 0.46 to 0.81 for annual temperature and precipitation, but a substantial mismatch between land cover distributions and their changes over time, with CLM correctly representing total agricultural area, but assuming large areas of natural grasslands where forests grow in reality. For CLM processes (outputs), seasonal changes in leaf area index (LAI; phenology) do not track satellite estimates well, and peak LAI in CLM is nearly double the satellite record (5.1 versus 2.8). Estimates of greenness and productivity, however, are more similar between CLM and observations. Summer soil moisture tracks in timing but not magnitude. Land surface reflectance (albedo) shows significant positive correlations in the winter, but not in the summer. Looking forward, key areas for model improvement include land cover distribution estimates, phenology algorithms, summertime radiative transfer modelling, and plant stress responses. View Full-Text
Keywords: Community Land Model; carbon cycle; landscape ecology; model benchmarking Community Land Model; carbon cycle; landscape ecology; model benchmarking
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MDPI and ACS Style

Dahlin, K.M.; Akanga, D.; Lombardozzi, D.L.; Reed, D.E.; Shirkey, G.; Lei, C.; Abraha, M.; Chen, J. Challenging a Global Land Surface Model in a Local Socio-Environmental System. Land 2020, 9, 398. https://doi.org/10.3390/land9100398

AMA Style

Dahlin KM, Akanga D, Lombardozzi DL, Reed DE, Shirkey G, Lei C, Abraha M, Chen J. Challenging a Global Land Surface Model in a Local Socio-Environmental System. Land. 2020; 9(10):398. https://doi.org/10.3390/land9100398

Chicago/Turabian Style

Dahlin, Kyla M., Donald Akanga, Danica L. Lombardozzi, David E. Reed, Gabriela Shirkey, Cheyenne Lei, Michael Abraha, and Jiquan Chen. 2020. "Challenging a Global Land Surface Model in a Local Socio-Environmental System" Land 9, no. 10: 398. https://doi.org/10.3390/land9100398

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