harnessing big data to rethink land heterogeneity in earth system models

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ID: 248102
2018
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Abstract
The continual growth in the availability, detail, and wealth of environmental data provides an invaluable asset to improve the characterization of land heterogeneity in Earth system models – a persistent challenge in macroscale models. However, due to the nature of these data (volume and complexity) and computational constraints, these data are underused for global applications. As a proof of concept, this study explores how to effectively and efficiently harness these data in Earth system models over a 1/4° ( ∼  25 km) grid cell in the western foothills of the Sierra Nevada in central California. First, a novel hierarchical multivariate clustering approach (HMC) is introduced that summarizes the high-dimensional environmental data space into hydrologically interconnected representative clusters (i.e., tiles). These tiles and their associated properties are then used to parameterize the sub-grid heterogeneity of the Geophysical Fluid Dynamics Laboratory (GFDL) LM4-HB land model. To assess how this clustering approach impacts the simulated water, energy, and carbon cycles, model experiments are run using a series of different tile configurations assembled using HMC. The results over the test domain show that (1) the observed similarity over the landscape makes it possible to converge on the macroscale response of the fully distributed model with around 300 sub-grid land model tiles; (2) assembling the sub-grid tile configuration from available environmental data can have a large impact on the macroscale states and fluxes of the water, energy, and carbon cycles; for example, the defined subsurface connections between the tiles lead to a dampening of macroscale extremes; (3) connecting the fine-scale grid to the model tiles via HMC enables circumvention of the classic scale discrepancies between the macroscale and field-scale estimates; this has potentially significant implications for the evaluation and application of Earth system models.
Reference Key
chaney2018hydrologyharnessing Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;N. W. Chaney;M. H. J. Van Huijgevoort;E. Shevliakova;S. Malyshev;P. C. D. Milly;P. P. G. Gauthier;B. N. Sulman
Journal materials research bulletin
Year 2018
DOI
10.5194/hess-22-3311-2018
URL
https://www.hydrol-earth-syst-sci.net/22/3311/2018/hess-22-3311-2018.pdf
Keywords
anthropology recreationenvironmental sciences sanitary engineeringgeography technologyenvironmental technology

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