Articles | Volume 22, issue 6
https://doi.org/10.5194/hess-22-3311-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-3311-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jun 2018
Research article |
| 14 Jun 2018
| 14 Jun 2018
Harnessing big data to rethink land heterogeneity in Earth system models
Nathaniel W. Chaney
CORRESPONDING AUTHOR
Program in Atmospheric and Oceanic Sciences, Princeton University,
Princeton, New Jersey, USA
Marjolein H. J. Van Huijgevoort
Program in Atmospheric and Oceanic Sciences, Princeton University,
Princeton, New Jersey, USA
Elena Shevliakova
NOAA/Geophysical Fluid Dynamics
Laboratory, Princeton, New Jersey, USA
Sergey Malyshev
NOAA/Geophysical Fluid Dynamics
Laboratory, Princeton, New Jersey, USA
Paul C. D. Milly
US Geological Survey, Princeton, New Jersey, USA
Paul P. G. Gauthier
Department of Geosciences, Princeton University, Princeton, New
Jersey, USA
Benjamin N. Sulman
Sierra Nevada Research Institute, University of
California, Merced, California, USA
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Cited
35 citations as recorded by crossref.
- REPRESENT HILL-VALLEY MOISTURE CONTRAST BY LAND SURFACE MODEL WITH LATERAL SUBSURFACE FLOW K. ADACHI et al. 10.2208/jscejhe.77.2_I_223
- Retrieving Heterogeneous Surface Soil Moisture at 100 m Across the Globe via Fusion of Remote Sensing and Land Surface Parameters J. Huang et al. 10.3389/frwa.2020.578367
- The Persistent Challenge of Surface Heterogeneity in Boundary-Layer Meteorology: A Review E. Bou-Zeid et al. 10.1007/s10546-020-00551-8
- Validation of the Community Land Model Version 5 Over the Contiguous United States (CONUS) Using In Situ and Remote Sensing Data Sets Y. Cheng et al. 10.1029/2020JD033539
- Hydrologic connectivity drives extremes and high variability in vegetation productivity across Australian arid and semi-arid ecosystems A. Norton et al. 10.1016/j.rse.2022.112937
- HydroBlocks v0.2: enabling a field-scale two-way coupling between the land surface and river networks in Earth system models N. Chaney et al. 10.5194/gmd-14-6813-2021
- Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions H. Wainwright et al. 10.5194/hess-26-429-2022
- Impact of Updating Vegetation Information on Land Surface Model Performance M. Ruiz‐Vásquez et al. 10.1029/2023JD039076
- Representing Intercell Lateral Groundwater Flow and Aquifer Pumping in the Community Land Model F. Felfelani et al. 10.1029/2020WR027531
- Spatial heterogeneity effects on land surface modeling of water and energy partitioning L. Li et al. 10.5194/gmd-15-5489-2022
- Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime M. Huang et al. 10.5194/gmd-15-6371-2022
- Combining hyper-resolution land surface modeling with SMAP brightness temperatures to obtain 30-m soil moisture estimates N. Vergopolan et al. 10.1016/j.rse.2020.111740
- A multi-factor integrated method of calculation unit delineation for hydrological modeling in large mountainous basins B. Li et al. 10.1016/j.jhydrol.2021.126180
- Ying Fan and groundwater’s global impact A. Potkay et al. 10.1016/j.jhydrol.2022.128923
- Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses X. Zhang et al. 10.1029/2023WR035572
- Flexible vector-based spatial configurations in land models S. Gharari et al. 10.5194/hess-24-5953-2020
- Investigating the response of land–atmosphere interactions and feedbacks to spatial representation of irrigation in a coupled modeling framework P. Lawston-Parker et al. 10.5194/hess-27-2787-2023
- On the similarity of hillslope hydrologic function: a clustering approach based on groundwater changes F. Maina et al. 10.5194/hess-26-3805-2022
- Coupling machine learning and physical modelling for predicting runoff at catchment scale S. Zubelzu et al. 10.1016/j.jenvman.2024.120404
- Towards a multiscale crop modelling framework for climate change adaptation assessment B. Peng et al. 10.1038/s41477-020-0625-3
- Effects of complex terrain on the shortwave radiative balance: a sub-grid-scale parameterization for the GFDL Earth System Model version 4.1 E. Zorzetto et al. 10.5194/gmd-16-1937-2023
- Hillslope Hydrology in Global Change Research and Earth System Modeling Y. Fan et al. 10.1029/2018WR023903
- Modelling of the shallow water table at high spatial resolution using random forests J. Koch et al. 10.5194/hess-23-4603-2019
- Representing Intrahillslope Lateral Subsurface Flow in the Community Land Model S. Swenson et al. 10.1029/2019MS001833
- Snow disappearance timing associated with elevation and vegetation type determines heterogeneity in spring onset in interior Alaska S. Kawashima et al. 10.1016/j.polar.2022.100918
- Towards an Optimal Representation of Sub‐Grid Heterogeneity in Land Surface Models L. Torres‐Rojas et al. 10.1029/2022WR032233
- The Tyranny of Small Scales—On Representing Soil Processes in Global Land Surface Models D. Or 10.1029/2019WR024846
- Semi‐Coupling of a Field‐Scale Resolving Land‐Surface Model and WRF‐LES to Investigate the Influence of Land‐Surface Heterogeneity on Cloud Development J. Simon et al. 10.1029/2021MS002602
- Impacts of Sub‐Grid Topographic Representations on Surface Energy Balance and Boundary Conditions in the E3SM Land Model: A Case Study in Sierra Nevada D. Hao et al. 10.1029/2021MS002862
- Field-scale soil moisture bridges the spatial-scale gap between drought monitoring and agricultural yields N. Vergopolan et al. 10.5194/hess-25-1827-2021
- Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS T. Kim et al. 10.1016/j.jhydrol.2021.126423
- SMAP-HydroBlocks, a 30-m satellite-based soil moisture dataset for the conterminous US N. Vergopolan et al. 10.1038/s41597-021-01050-2
- Towards quick parameter estimation of hydrological models with large number of computational units V. Vema & K. Sudheer 10.1016/j.jhydrol.2020.124983
- Moisture Fluctuations Modulate Abiotic and Biotic Limitations of H2 Soil Uptake M. Bertagni et al. 10.1029/2021GB006987
- A Catchment‐Based Hierarchical Spatial Tessellation Approach to a Better Representation of Land Heterogeneity for Hyper‐Resolution Land Surface Modeling L. Huang et al. 10.1029/2021WR031589
35 citations as recorded by crossref.
- REPRESENT HILL-VALLEY MOISTURE CONTRAST BY LAND SURFACE MODEL WITH LATERAL SUBSURFACE FLOW K. ADACHI et al. 10.2208/jscejhe.77.2_I_223
- Retrieving Heterogeneous Surface Soil Moisture at 100 m Across the Globe via Fusion of Remote Sensing and Land Surface Parameters J. Huang et al. 10.3389/frwa.2020.578367
- The Persistent Challenge of Surface Heterogeneity in Boundary-Layer Meteorology: A Review E. Bou-Zeid et al. 10.1007/s10546-020-00551-8
- Validation of the Community Land Model Version 5 Over the Contiguous United States (CONUS) Using In Situ and Remote Sensing Data Sets Y. Cheng et al. 10.1029/2020JD033539
- Hydrologic connectivity drives extremes and high variability in vegetation productivity across Australian arid and semi-arid ecosystems A. Norton et al. 10.1016/j.rse.2022.112937
- HydroBlocks v0.2: enabling a field-scale two-way coupling between the land surface and river networks in Earth system models N. Chaney et al. 10.5194/gmd-14-6813-2021
- Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions H. Wainwright et al. 10.5194/hess-26-429-2022
- Impact of Updating Vegetation Information on Land Surface Model Performance M. Ruiz‐Vásquez et al. 10.1029/2023JD039076
- Representing Intercell Lateral Groundwater Flow and Aquifer Pumping in the Community Land Model F. Felfelani et al. 10.1029/2020WR027531
- Spatial heterogeneity effects on land surface modeling of water and energy partitioning L. Li et al. 10.5194/gmd-15-5489-2022
- Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime M. Huang et al. 10.5194/gmd-15-6371-2022
- Combining hyper-resolution land surface modeling with SMAP brightness temperatures to obtain 30-m soil moisture estimates N. Vergopolan et al. 10.1016/j.rse.2020.111740
- A multi-factor integrated method of calculation unit delineation for hydrological modeling in large mountainous basins B. Li et al. 10.1016/j.jhydrol.2021.126180
- Ying Fan and groundwater’s global impact A. Potkay et al. 10.1016/j.jhydrol.2022.128923
- Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses X. Zhang et al. 10.1029/2023WR035572
- Flexible vector-based spatial configurations in land models S. Gharari et al. 10.5194/hess-24-5953-2020
- Investigating the response of land–atmosphere interactions and feedbacks to spatial representation of irrigation in a coupled modeling framework P. Lawston-Parker et al. 10.5194/hess-27-2787-2023
- On the similarity of hillslope hydrologic function: a clustering approach based on groundwater changes F. Maina et al. 10.5194/hess-26-3805-2022
- Coupling machine learning and physical modelling for predicting runoff at catchment scale S. Zubelzu et al. 10.1016/j.jenvman.2024.120404
- Towards a multiscale crop modelling framework for climate change adaptation assessment B. Peng et al. 10.1038/s41477-020-0625-3
- Effects of complex terrain on the shortwave radiative balance: a sub-grid-scale parameterization for the GFDL Earth System Model version 4.1 E. Zorzetto et al. 10.5194/gmd-16-1937-2023
- Hillslope Hydrology in Global Change Research and Earth System Modeling Y. Fan et al. 10.1029/2018WR023903
- Modelling of the shallow water table at high spatial resolution using random forests J. Koch et al. 10.5194/hess-23-4603-2019
- Representing Intrahillslope Lateral Subsurface Flow in the Community Land Model S. Swenson et al. 10.1029/2019MS001833
- Snow disappearance timing associated with elevation and vegetation type determines heterogeneity in spring onset in interior Alaska S. Kawashima et al. 10.1016/j.polar.2022.100918
- Towards an Optimal Representation of Sub‐Grid Heterogeneity in Land Surface Models L. Torres‐Rojas et al. 10.1029/2022WR032233
- The Tyranny of Small Scales—On Representing Soil Processes in Global Land Surface Models D. Or 10.1029/2019WR024846
- Semi‐Coupling of a Field‐Scale Resolving Land‐Surface Model and WRF‐LES to Investigate the Influence of Land‐Surface Heterogeneity on Cloud Development J. Simon et al. 10.1029/2021MS002602
- Impacts of Sub‐Grid Topographic Representations on Surface Energy Balance and Boundary Conditions in the E3SM Land Model: A Case Study in Sierra Nevada D. Hao et al. 10.1029/2021MS002862
- Field-scale soil moisture bridges the spatial-scale gap between drought monitoring and agricultural yields N. Vergopolan et al. 10.5194/hess-25-1827-2021
- Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS T. Kim et al. 10.1016/j.jhydrol.2021.126423
- SMAP-HydroBlocks, a 30-m satellite-based soil moisture dataset for the conterminous US N. Vergopolan et al. 10.1038/s41597-021-01050-2
- Towards quick parameter estimation of hydrological models with large number of computational units V. Vema & K. Sudheer 10.1016/j.jhydrol.2020.124983
- Moisture Fluctuations Modulate Abiotic and Biotic Limitations of H2 Soil Uptake M. Bertagni et al. 10.1029/2021GB006987
- A Catchment‐Based Hierarchical Spatial Tessellation Approach to a Better Representation of Land Heterogeneity for Hyper‐Resolution Land Surface Modeling L. Huang et al. 10.1029/2021WR031589
Discussed (preprint)
Latest update: 22 Apr 2024
Short summary
The petabytes of existing global environmental data provide an invaluable asset to improve the characterization of land heterogeneity in Earth system models. This study introduces a clustering algorithm that summarizes a domain's heterogeneity through spatially interconnected clusters. A series of land model simulations in central California using this approach illustrate the critical role that multi-scale heterogeneity can have on the macroscale water, energy, and carbon cycles.
The petabytes of existing global environmental data provide an invaluable asset to improve the...
