Book contents
- Frontmatter
- Contents
- Acknowledgement
- OPENING ADDRESS OF THE FIRST GEORGE KOVACS COLLOQUIUM
- HETEROGENEITY AND SCALING LAND-ATMOSPHERIC WATER AND ENERGY FLUXES IN CLIMATE SYSTEMS
- SCALE PROBLEMS IN SURFACE FLUXES
- REMOTE SENSING – INVERSE MODELLING APPROACH TO DETERMINE LARGE SCALE EFFECTIVE SOIL HYDRAULIC PROPERTIES IN SOIL–VEGETATION–ATMOSPHERE SYSTEMS
- THE IMPORTANCE OF LANDSCAPE POSITION IN SCALING SVAT MODELS TO CATCHMENT SCALE HYDROECOLOGICAL PREDICTION
- THE INFLUENCE OF SUBGRID-SCALE SPATIAL VARIABILITY ON PRECIPITATION AND SOIL MOISTURE IN AN ATMOSPHERIC GCM
- MODELLING THE HYDROLOGICAL RESPONSE TO LARGE SCALE LAND USE CHANGE
- AN APPROACH TO REPRESENT MESOSCALE (SUBGRID-SCALE) FLUXES IN GCMs DEMONSTRATED WITH SIMULATIONS OF LOCAL DEFORESTATION IN AMAZONIA
- A HIERARCHICAL APPROACH TO THE CONNECTION OF GLOBAL HYDROLOGICAL AND ATMOSPHERIC MODELS
- STOCHASTIC DOWNSCALING OF GCM-OUTPUT RESULTS USING ATMOSPHERIC CIRCULATION PATTERNS
- DEPENDENCIES OF SPATIAL VARIABILITY IN FLUVIAL ECOSYSTEMS ON THE TEMPORAL HYDROLOGICAL VARIABILITY
- PROBLEMS AND PROGRESS IN MACROSCALE HYDROLOGICAL MODELLING
- PREDICTABILITY OF THE ATMOSPHERE AND CLIMATE: TOWARDS A DYNAMICAL VIEW
- FROM SCALAR CASCADES TO LIE CASCADES: JOINT MULTIFRACTAL ANALYSIS OF RAIN AND CLOUD PROCESSES
- FRACTALS ET MULTIFRACTALS APPLIQUÉS À L'ÉTUDE DE LA VARIABILITÉ TEMPORELLE DES PRÉCIPITATIONS
HETEROGENEITY AND SCALING LAND-ATMOSPHERIC WATER AND ENERGY FLUXES IN CLIMATE SYSTEMS
Published online by Cambridge University Press: 05 November 2011
- Frontmatter
- Contents
- Acknowledgement
- OPENING ADDRESS OF THE FIRST GEORGE KOVACS COLLOQUIUM
- HETEROGENEITY AND SCALING LAND-ATMOSPHERIC WATER AND ENERGY FLUXES IN CLIMATE SYSTEMS
- SCALE PROBLEMS IN SURFACE FLUXES
- REMOTE SENSING – INVERSE MODELLING APPROACH TO DETERMINE LARGE SCALE EFFECTIVE SOIL HYDRAULIC PROPERTIES IN SOIL–VEGETATION–ATMOSPHERE SYSTEMS
- THE IMPORTANCE OF LANDSCAPE POSITION IN SCALING SVAT MODELS TO CATCHMENT SCALE HYDROECOLOGICAL PREDICTION
- THE INFLUENCE OF SUBGRID-SCALE SPATIAL VARIABILITY ON PRECIPITATION AND SOIL MOISTURE IN AN ATMOSPHERIC GCM
- MODELLING THE HYDROLOGICAL RESPONSE TO LARGE SCALE LAND USE CHANGE
- AN APPROACH TO REPRESENT MESOSCALE (SUBGRID-SCALE) FLUXES IN GCMs DEMONSTRATED WITH SIMULATIONS OF LOCAL DEFORESTATION IN AMAZONIA
- A HIERARCHICAL APPROACH TO THE CONNECTION OF GLOBAL HYDROLOGICAL AND ATMOSPHERIC MODELS
- STOCHASTIC DOWNSCALING OF GCM-OUTPUT RESULTS USING ATMOSPHERIC CIRCULATION PATTERNS
- DEPENDENCIES OF SPATIAL VARIABILITY IN FLUVIAL ECOSYSTEMS ON THE TEMPORAL HYDROLOGICAL VARIABILITY
- PROBLEMS AND PROGRESS IN MACROSCALE HYDROLOGICAL MODELLING
- PREDICTABILITY OF THE ATMOSPHERE AND CLIMATE: TOWARDS A DYNAMICAL VIEW
- FROM SCALAR CASCADES TO LIE CASCADES: JOINT MULTIFRACTAL ANALYSIS OF RAIN AND CLOUD PROCESSES
- FRACTALS ET MULTIFRACTALS APPLIQUÉS À L'ÉTUDE DE LA VARIABILITÉ TEMPORELLE DES PRÉCIPITATIONS
Summary
ABSTRACT The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in the land-atmosphere system have become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between micro scale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small-scale heterogeneities and whether ‘effective’ parameters can be used in the macroscale models. To address this question of scaling, three modeling experiments were performed and are reviewed in this paper. The first is concerned with the aggregation of parameters and inputs for a terrestrial water and energy balance model. The second experiment analyzed the scaling behaviour of hydrological responses during rain events and between rain events. The third experiment compared the hydrological responses from distributed models with a lumped model that uses spatially constant inputs and parameters. The results show that the patterns of small scale variations can be represented statistically if the scale is larger than a representative elementary area scale, which appears to be about 2–3 times the correlation length of the process. For natural catchments this appears to be about 1–2 km2. The results concerning distributed versus lumped representations are more complicated. For conditions when the processes are non-linear, lumping results in biases; otherwise a one-dimensional model based on ‘equivalent’ parameters provides quite good results. Further research is needed to understand these conditions fully.
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- Publisher: Cambridge University PressPrint publication year: 1995
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