scholarly journals Land-surface modelling in hydrological perspective

2005 ◽  
Vol 2 (6) ◽  
pp. 1815-1848 ◽  
Author(s):  
J. Overgaard ◽  
D. Rosbjerg ◽  
M. B. Butts
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Potential Evapotranspiration ◽  
Distributed Data ◽  
Atmospheric Models ◽  
Dynamic Coupling ◽  
Surface Modelling ◽  
Evaluation Procedures ◽  
Surface Models ◽  
Land Surface Modelling

Abstract. A comprehensive review of energy-based land-surface modelling, as seen from a hydrological perspective, is provided. We choose to focus on energy-based approaches, because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opportunities for evaluation of distributed land-surface models through application of remote sensing are discussed in detail, and the difficulties inherent in various evaluation procedures are presented. Remote sensing is the only source of distributed data at scales that correspond to hydrological modelling scales. Finally, the dynamic coupling of hydrological and atmospheric models is explored, and the future perspectives of such efforts are discussed.

scholarly journals Land-surface modelling in hydrological perspective – a review

2006 ◽  
Vol 3 (2) ◽  
pp. 229-241 ◽  
Author(s):  
J. Overgaard ◽  
D. Rosbjerg ◽  
M. B. Butts
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Potential Evapotranspiration ◽  
Land Surface Models ◽  
Atmospheric Models ◽  
Dynamic Coupling ◽  
Evaluation Procedures ◽  
Surface Models ◽  
Different Types ◽  
Land Surface Modelling

Abstract. The purpose of this paper is to provide a review of the different types of energy-based land-surface models (LSMs) and discuss some of the new possibilities that will arise when energy-based LSMs are combined with distributed hydrological modelling. We choose to focus on energy-based approaches, because in comparison to the traditional potential evapotranspiration models, these approaches allow for a stronger link to remote sensing and atmospheric modelling. New opportunities for evaluation of distributed land-surface models through application of remote sensing are discussed in detail, and the difficulties inherent in various evaluation procedures are presented. Finally, the dynamic coupling of hydrological and atmospheric models is explored, and the perspectives of such efforts are discussed.

scholarly journals FluxnetLSM R package (v1.0): A community tool for processing FLUXNET data for use in land surface modelling

2017 ◽  
Author(s):  
Anna M. Ukkola ◽  
Ned Haughton ◽  
Martin G. De Kauwe ◽  
Gab Abramowitz ◽  
Andy J. Pitman
Keyword(s):  
Land Surface ◽  
R Package ◽  
File Format ◽  
Gap Filling ◽  
Surface Modelling ◽  
Flux Tower ◽  
Surface Models ◽  
Land Surface Modelling ◽  
Scale Surface ◽  
Community Standard

Abstract. Flux towers measure ecosystem-scale surface-atmosphere exchanges of energy, carbon dioxide and water vapour. The network of flux towers now encompasses ~ 900 sites, spread across every continent. Consequently, these data have become an essential benchmarking tool for land surface models (LSMs). However, these data as released are not immediately usable for driving, evaluating and benchmarking LSMs. Flux tower data must first be transformed into a LSM-readable file format, a process which involves changing units, screening missing data and varying degrees of additional gap- filling. All of this often leads to an under-utilisation of these data in model benchmarking. To resolve some of these issues, and to help make flux tower measurements more widely used, we present a reproducible, open-source R package that transforms the latest FLUXNET2015 release into community standard NetCDF files that are directly usable by LSMs.

scholarly journals FluxnetLSM R package (v1.0): a community tool for processing FLUXNET data for use in land surface modelling

2017 ◽  
Vol 10 (9) ◽  
pp. 3379-3390 ◽  
Author(s):  
Anna M. Ukkola ◽  
Ned Haughton ◽  
Martin G. De Kauwe ◽  
Gab Abramowitz ◽  
Andy J. Pitman
Keyword(s):  
Land Surface ◽  
R Package ◽  
File Format ◽  
Gap Filling ◽  
Surface Modelling ◽  
Flux Tower ◽  
Surface Models ◽  
Land Surface Modelling ◽  
Scale Surface ◽  
Community Standard

Abstract. Flux towers measure ecosystem-scale surface–atmosphere exchanges of energy, carbon dioxide and water vapour. The network of flux towers now encompasses ∼ 900 sites, spread across every continent. Consequently, these data have become an essential benchmarking tool for land surface models (LSMs). However, these data as released are not immediately usable for driving, evaluating and benchmarking LSMs. Flux tower data must first be transformed into a LSM-readable file format, a process which involves changing units, screening missing data and varying degrees of additional gap-filling. All of this often leads to an under-utilisation of these data in model benchmarking. To resolve some of these issues, and to help make flux tower measurements more widely used, we present a reproducible, open-source R package that transforms the FLUXNET2015 and La Thuile data releases into community standard NetCDF files that are directly usable by LSMs. We note that these data would also be useful for any other user or community seeking to independently quality control, gap-fill or use the FLUXNET data.

scholarly journals Advances in Land Surface Modelling

2021 ◽  
Author(s):  
Eleanor M. Blyth ◽  
Vivek K. Arora ◽  
Douglas B. Clark ◽  
Simon J. Dadson ◽  
Martin G. De Kauwe ◽  
...  
Keyword(s):  
Land Use ◽  
Water Use ◽  
Land Surface ◽  
Climate Prediction ◽  
Data Availability ◽  
Land Surface Models ◽  
Surface Modelling ◽  
Surface Models ◽  
Weather And Climate ◽  
Land Surface Modelling

AbstractLand surface models have an increasing scope. Initially designed to capture the feedbacks between the land and the atmosphere as part of weather and climate prediction, they are now used as a critical tool in the urgent need to inform policy about land-use and water-use management in a world that is changing physically and economically. This paper outlines the way that models have evolved through this change of purpose and what might the future hold. It highlights the importance of distinguishing between advances in the science within the modelling components, with the advances of how to represent their interaction. This latter aspect of modelling is often overlooked but will increasingly manifest as an issue as the complexity of the system, the time and space scales of the system being modelled increase. These increases are due to technology, data availability and the urgency and range of the problems being studied.

Application of an optimality-based model to operate at half-hourly timestep to implement plant acclimation within a land-surface modelling framework

2021 ◽  
Author(s):  
Giulia Mengoli ◽  
Anna Agustí-Panareda ◽  
Souhail Boussetta ◽  
Sandy P. Harrison ◽  
Carlo Trotta ◽  
...  
Keyword(s):  
Time Scales ◽  
Land Surface ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Extended Model ◽  
Test Model ◽  
Area Index ◽  
Surface Modelling ◽  
Plant Acclimation ◽  
Land Surface Modelling

<p>Vegetation and atmosphere are linked through the perpetual exchange of water, carbon and energy. An accurate representation of the processes involved in these exchanges is crucial in forecasting Earth system states. Although vegetation has become an undisputed key component in land-surface modelling (LSMs), the current generation of models differ in terms of how key processes are formulated. Plant processes react to environmental changes on multiple time scales. Here we differentiate a fast (minutes) and a slower (acclimated – weeks to months) response. Some current LSMs include plant acclimation, even though they require additional parameters to represent this response, but the majority of them represent only the fast response and assume that this also applies at longer time scales. Ignoring acclimation in this way could be the cause of inconsistent future projections. Our proposition is to include plant acclimation in a LSM schema, without having to include new plant-functional-type-dependent parameters. This is possible by using an alternative model development strategy based on eco-evolutionary theory, which explicitly predicts the acclimation of photosynthetic capacities and stomatal behaviour to environmental variations. So far, this theory has been tested only at weekly to monthly timescales. Here we develop and test an approach to apply an existing optimality-based model of gross primary production (GPP), the P model, at the sub-daily timestep necessary for use in an LSM, making an explicit differentiation between the fast and slow responses of photosynthesis and stomatal conductance. We test model performance in reproducing the diurnal cycle of GPP as recorded by flux tower measurements across different biomes, including boreal and tropical forests. The extended model requires only a few meteorological inputs, and a satellite-derived product for leaf area index or green vegetation cover. It is able to manage both timescales of acclimation without PFT-dependent photosynthetic parameters and has shown to operate with very good performance at all sites so far investigated. The model structure avoids the need to store past climate and vegetation states. These findings therefore suggest a simple way to include both instantaneous and acclimated responses within a LSM framework, and to do so in a robust way that does not require the specification of multiple parameters for different plant functional types.</p>

ECLand: an ECMWF land surface modelling platform

2021 ◽  
Author(s):  
Gianpaolo Balsamo ◽  
Souhail Boussetta
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Land Surface Model ◽  
Open Water ◽  
Surface Fluxes ◽  
Surface Model ◽  
New Developments ◽  
Surface Modelling ◽  
Land Surface Modelling ◽  
New Research

<p>The ECMWF operational land surface model, based on the Carbon-Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (CHTESSEL) is the baseline for global weather, climate and environmental applications at ECMWF. In order to expedite its progress and benefit from international collaboration, an ECLand platform has been designed to host advanced and modular schemes. ECLand is paving the way toward a land model that could support a wider range of modelling applications, facilitating global kilometer scales testing as envisaged in the Copernicus and Destination Earth programmes. This presentation introduces the CHTESSEL and its recent new developments that aims at hosting new research applications.</p><p>These new improvements touch upon different components of the model: (i) vegetation, (ii) snow, (iii) soil hydrology, (iv) open water/lakes (v) rivers and (vi) urban areas. The developments are evaluated separately with either offline simulations or coupled experiments, depending on their level of operational readiness, illustrating the benchmarking criteria for assessing process fidelity with regards to land surface fluxes and reservoirs involved in water-energy-carbon exchange, and within the Earth system prediction framework, as foreseen to enter upcoming ECMWF operational cycles.</p><p>Reference: Souhail Boussetta, Gianpaolo Balsamo*, Anna Agustì-Panareda, Gabriele Arduini, Anton Beljaars, Emanuel Dutra, Glenn Carver, Margarita Choulga, Ioan Hadade, Cinzia Mazzetti, Joaquìn Munõz-Sabater, Joe McNorton, Christel Prudhomme, Patricia De Rosnay, Irina Sandu, Nils Wedi, Dai Yamazaki, Ervin Zsoter, 2021: ECLand: an ECMWF land surface modelling platform, MDPI Atmosphere, (in prep).</p>

scholarly journals Evaluating and improving the Community Land Model's sensitivity to land cover

2018 ◽  
Vol 15 (15) ◽  
pp. 4731-4757 ◽  
Author(s):  
Ronny Meier ◽  
Edouard L. Davin ◽  
Quentin Lejeune ◽  
Mathias Hauser ◽  
Yan Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Surface ◽  
Soil Column ◽  
Plant Functional Type ◽  
Model Parameters ◽  
Functional Type ◽  
Land Surface Models ◽  
Surface Models ◽  
Open Land

Abstract. Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remote-sensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate.

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