13
IRUS Total
Downloads

Reliable, robust and realistic: the three R's of next-generation land-surface modelling

File Description SizeFormat 
acp-15-5987-2015 (1).pdfPublished version1.29 MBAdobe PDFView/Open
Title: Reliable, robust and realistic: the three R's of next-generation land-surface modelling
Authors: Prentice, IC
Liang, X
Medlyn, BE
Wang, Y-P
Item Type: Journal Article
Abstract: Land-surface models (LSMs) are increasingly called upon to represent not only the exchanges of energy, water and momentum across the land–atmosphere interface (their original purpose in climate models), but also how ecosystems and water resources respond to climate, atmospheric environment, land-use and land-use change, and how these responses in turn influence land–atmosphere fluxes of carbon dioxide (CO2), trace gases and other species that affect the composition and chemistry of the atmosphere. However, the LSMs embedded in state-of-the-art climate models differ in how they represent fundamental aspects of the hydrological and carbon cycles, resulting in large inter-model differences and sometimes faulty predictions. These “thirdgeneration” LSMs respect the close coupling of the carbon and water cycles through plants, but otherwise tend to be under-constrained, and have not taken full advantage of robust hydrological parameterizations that were independently developed in offline models. Benchmarking, combining multiple sources of atmospheric, biospheric and hydrological data, should be a required component of LSM development, but this field has been relatively poorly supported and intermittently pursued. Moreover, benchmarking alone is not sufficient to ensure that models improve. Increasing complexity may increase realism but decrease reliability and robustness, by increasing the number of poorly known model parameters. In contrast, simplifying the representation of complex processes by stochastic parameterization (the representation of unresolved processes by statistical distributions of values) has been shown to improve model reliability and realism in both atmospheric and land-surface modelling contexts. We provide examples for important processes in hydrology (the generation of runoff and flow routing in heterogeneous catchments) and biology (carbon uptake by speciesdiverse ecosystems). We propose that the way forward for next-generation complex LSMs will include: (a) representations of biological and hydrological processes based on the implementation of multiple internal constraints; (b) systematic application of benchmarking and data assimilation techniques to optimize parameter values and thereby test the structural adequacy of models; and (c) stochastic parameterization of unresolved variability, applied in both the hydrological and the biological domains.
Issue Date: 1-Jun-2015
Date of Acceptance: 13-Apr-2015
URI: http://hdl.handle.net/10044/1/68124
DOI: https://doi.org/10.5194/acp-15-5987-2015
ISSN: 1680-7316
Publisher: Copernicus Publications
Start Page: 5987
End Page: 6005
Journal / Book Title: Atmospheric Chemistry and Physics
Volume: 15
Issue: 10
Copyright Statement: © 2015 Author(s). This work is distributed under the Creative Commons Attribution 3.0 License (https://creativecommons.org/licenses/by/3.0/).
Sponsor/Funder: AXA Research Fund
Funder's Grant Number: AXA Chair Programme in Biosphere and Climate Impacts
Keywords: Science & Technology
Physical Sciences
Meteorology & Atmospheric Sciences
LATITUDE HYDROLOGICAL PROCESSES
TERRESTRIAL CARBON-CYCLE
ENSEMBLE KALMAN FILTER
RIVER-BASIN EXPERIMENT
EARTH SYSTEM MODELS
TORNE-KALIX BASIN
SUBGRID SPATIAL VARIABILITY
SOIL-MOISTURE OBSERVATIONS
ENERGY-BALANCE PROCESSES
GLOBAL VEGETATION MODEL
0401 Atmospheric Sciences
0201 Astronomical And Space Sciences
Publication Status: Published
Online Publication Date: 2015-05-29
Appears in Collections:Department of Life Sciences