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An Enhanced Model of Land Water and Energy for Global Hydrologic and Earth-System Studies
Abstract
LM3 is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and to extend the scope of the predecessor Land Dynamics (LaD) and LM3V models by better quantifying the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multilayer representations of temperature, liquid water content, and ice content of both snowpack and macroporous soil–bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and provides qualitatively (though not always quantitatively) reasonable estimates, from a global perspective, of observed spatial and/or temporal variations of vegetation density, albedo, streamflow, water-table depth, permafrost, and lake levels. Amplitude and phase of annual cycle of total water storage are simulated well. Realism of modeled lake levels varies widely. The water table tends to be consistently too shallow in humid regions. Biophysical properties have an artificial stepwise spatial structure, and equilibrium vegetation is sensitive to initial conditions. Explicit resolution of thick (>100 m) unsaturated zones and permafrost is possible, but only at the cost of long (≫300 yr) model spinup times.
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Cites
A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species
Farquhar, G. D., von Caemmerer, S., & Berry, J. A. (1980) · Planta · doi:10.1007/bf00386231 · Cited by 8,796
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Large influence of soil moisture on long-term terrestrial carbon uptake
Green, J. K., Seneviratne, S. I., Berg, A. M., Findell, K. L., Hagemann, S., Lawrence, D. M., & Gentine, P. (2019) · Nature · doi:10.1038/s41586-018-0848-x · Cited by 773
Self-citationStructure and Performance of GFDL's CM4.0 Climate Model
Held, I. M., Guo, H., Adcroft, A., Dunne, J. P., Horowitz, L. W., Krasting, J., Shevliakova, E., Winton, M., Zhao, M., Bushuk, M., et al. (2019) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2019ms001829 · Cited by 594
Self-citationGlobal patterns and dynamics of climate–groundwater interactions
Cuthbert, M. O., Gleeson, T., Moosdorf, N., Befus, K. M., Schneider, A., Hartmann, J., & Lehner, B. (2019) · Nature Climate Change · doi:10.1038/s41558-018-0386-4 · Cited by 538
Self-citationGlobal hydrology 2015: State, trends, and directions
Bierkens, M. F. P. (2015) · Water Resources Research · doi:10.1002/2015wr017173 · Cited by 493
Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2
Sulman, B. N., Phillips, R. P., Oishi, A. C., Shevliakova, E., & Pacala, S. W. (2014) · Nature Climate Change · doi:10.1038/nclimate2436 · Cited by 454
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Metadata
- Authors
- Milly, P. C. D., Malyshev, S. L., Shevliakova, E., Dunne, K. A., Findell, K. L., Gleeson, T., Liang, Z., Phillipps, P., Stouffer, R. J., & Swenson, S.
- Venue
- Journal of Hydrometeorology
- Publisher
- American Meteorological Society
- Published
- 2014-10
- Volume
- 15
- Issue
- 5
- Pages
- 1739-1761
- ISSN
- 1525-7541 (ISSN-L)
- 1525-755X
- OpenAlex
- W1975106412
- Cited by
- 218
- References
- 1
- FWCI
- 9.42
- Type
- journal article
- Language
- en
- Open access
- closed
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- Milly, P. C. D., Malyshev, S. L., Shevliakova, E., Dunne, K. A., Findell, K. L., Gleeson, T., Liang, Z., Phillipps, P., Stouffer, R. J., & Swenson, S. (2014). An Enhanced Model of Land Water and Energy for Global Hydrologic and Earth-System Studies. Journal of Hydrometeorology. https://doi.org/10.1175/jhm-d-13-0162.1
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.