The Science

The land surface is a crucial part of the Earth system, and land surface models (LSMs) are key to some of the most important problems facing society today.  But large uncertainty in LSM predictions, and a poor ability to attribute the sources of that uncertainty, mean that new strategies are needed.  Researchers at Lawrence Berkley National Laboratory identify three “grand challenges” facing LSM developers and propose strategies to help overcome these problems.

The Impact

This article, part of an invited collection of Grand Challenges papers published in AGU journals, seeks to focus LSM developers on the largest problems facing land surface science. Highlighting key barriers in LSM science, this article seeks to galvanize the community to focus on problems related to process complexity, the many dimensions of sub-gridscale heterogeneity, and the representation of coupled physical-ecological dynamics.

Summary

LSMs are critical pieces of Earth system models, needed for projection of the extent of global change as well as impacts on critical terrestrial systems such as agriculture, freshwater resources, ecosystems, and built infrastructure. However, LSM predictions show a stubborn uncertainty that has been difficult to attribute to specific process representations and parameter values.  At the same time, the scope of LSMs has grown complex—for valid reasons—because of the many interacting processes that make up terrestrial systems. The researchers argue that, as a first “Grand Challenge”, the LSM community must focus more clearly on the process complexity of LSMs, in order to better allow scaling from simplified models to highly interacting representation of a full LSM.  A second “Grand Challenge” relates to the differing views of heterogeneity in LSMs, which focus on various subsets and combinations of, e.g., disturbance, hillslopes, microclimate, vegetation communities, recent weather, snow depth, land management, and others.  But a general approach to identifying what are the dominant dimensions of heterogeneity at a given location, and how to most efficiently resolve that heterogeneity has not yet emerged.  A third “Grand Challenge” is on how to understand the dynamics of model parameters that are governed by complex interactions between physical and ecological dynamics; in particular the article reviews three leading approaches (empirical, optimality-based, and competition-resolving) and identifies questions about when to use each of these, how different aspects may and may not be combined, and what the implications are for each of these.

Principal Investigator

Charlie Koven
Lawrence Berkeley National Laboratory
cdkoven@lbl.gov

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
daniel.stover@science.doe.gov

Funding

DOE Early Career Research Program, Rubisco SFA, NGEE-Tropics

References