scholarly journals A flux tower dataset tailored for land model evaluation

2021 ◽  
Author(s):  
Anna M. Ukkola ◽  
Gab Abramowitz ◽  
Martin G. De Kauwe
Keyword(s):  
Data Quality ◽  
Model Evaluation ◽  
Land Surface ◽  
Heat Fluxes ◽  
Surface Model ◽  
Second Phase ◽  
Area Index ◽  
Surface Modelling ◽  
Flux Tower ◽  
Land Surface Modelling

Abstract. Eddy covariance flux towers measure the exchange of water, energy and carbon fluxes between the land and atmosphere. They have become invaluable for theory development and evaluating land models. However, flux tower data as measured (even after site post-processing) are not directly suitable for land surface modelling due to data gaps in model forcing variables, inappropriate gap-filling, formatting and varying data quality. Here we present a quality-control and data-formatting pipeline for tower data from FLUXNET2015, La Thuile and OzFlux syntheses and the resultant 170-site globally distributed flux tower dataset specifically designed for use in land modelling. The dataset underpins the second phase of the PLUMBER land surface model benchmarking evaluation project, an international model intercomparison project encompassing > 20 land surface and biosphere models. The dataset is provided in the Assistance for Land-surface Modelling Activities (ALMA) NetCDF format and is CF-NetCDF compliant. For forcing land surface models, the dataset provides fully gap-filled meteorological data that has had periods of low data quality removed. Additional constraints required for land models, such as reference measurement heights, vegetation types and satellite-based monthly leaf area index estimates, are also included. For model evaluation, the dataset provides estimates of key water, carbon and energy variables, with the latent and sensible heat fluxes additionally corrected for energy balance closure. The dataset provides a total of 1040 site years covering the period 1992–2018, with individual sites spanning from 1 to 21 years. The dataset is available at http://dx.doi.org/10.25914/5fdb0902607e1 (Ukkola et al., 2021).

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 JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator

2014 ◽  
Vol 7 (5) ◽  
pp. 6773-6809
Author(s):  
T. Osborne ◽  
J. Gornall ◽  
J. Hooker ◽  
K. Williams ◽  
A. Wiltshire ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Land Surface Model ◽  
Water Security ◽  
Climate Change Impacts ◽  
Heat Fluxes ◽  
Surface Model ◽  
Yield Model ◽  
Area Index ◽  
The Impact

Abstract. Studies of climate change impacts on the terrestrial biosphere have been completed without recognition of the integrated nature of the biosphere. Improved assessment of the impacts of climate change on food and water security requires the development and use of models not only representing each component but also their interactions. To meet this requirement the Joint UK Land Environment Simulator (JULES) land surface model has been modified to include a generic parametrisation of annual crops. The new model, JULES-crop, is described and evaluation at global and site levels for the four globally important crops; wheat, soy bean, maize and rice is presented. JULES-crop demonstrates skill in simulating the inter-annual variations of yield for maize and soy bean at the global level, and for wheat for major spring wheat producing countries. The impact of the new parametrisation, compared to the standard configuration, on the simulation of surface heat fluxes is largely an alteration of the partitioning between latent and sensible heat fluxes during the later part of the growing season. Further evaluation at the site level shows the model captures the seasonality of leaf area index and canopy height better than in standard JULES. However, this does not lead to an improvement in the simulation of sensible and latent heat fluxes. The performance of JULES-crop from both an earth system and crop yield model perspective is encouraging however, more effort is needed to develop the parameterisation of the model for specific applications. Key future model developments identified include the specification of the yield gap to enable better representation of the spatial variability in yield.

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 Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE

2012 ◽  
Vol 9 (1) ◽  
pp. 439-456 ◽  
Author(s):  
S. Lafont ◽  
Y. Zhao ◽  
J.-C. Calvet ◽  
P. Peylin ◽  
P. Ciais ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Land Surface ◽  
Satellite Remote Sensing ◽  
Carbon Fluxes ◽  
Canopy Conductance ◽  
Area Index ◽  
Surface Modelling ◽  
Land Cover Map ◽  
Land Surface Modelling ◽  
The Impact

Abstract. The Leaf Area Index (LAI) is a measure of the amount of photosynthetic leaves and governs the canopy conductance to water vapor and carbon dioxide. Four different estimates of LAI were compared over France: two LAI products derived from satellite remote sensing, and two LAI simulations derived from land surface modelling. The simulated LAI was produced by the ISBA-A-gs model and by the ORCHIDEE model (developed by CNRM-GAME and by IPSL, respectively), for the 1994–2007 period. The two models were driven by the same atmospheric variables and used the same land cover map (SAFRAN and ECOCLIMAP-II, respectively). The MODIS and CYCLOPES satellite LAI products were used. Both products were available from 2000 to 2007 and this relatively long period allowed to investigate the interannual and the seasonal variability of monthly LAI values. In particular the impact of the 2003 and 2005 droughts were analyzed. The two models presented contrasting results, with a difference of one month between the average leaf onset dates simulated by the two models, and a maximum interannual variability of LAI simulated at springtime by ORCHIDEE and at summertime by ISBA-A-gs. The comparison with the satellite LAI products showed that, in general, the seasonality was better represented by ORCHIDEE, while ISBA-A-gs tended to better represent the interannual variability, especially for grasslands. While the two models presented comparable values of net carbon fluxes, ORCHIDEE simulated much higher photosynthesis rates than ISBA-A-gs (+70%), while providing lower transpiration estimates (−8%).

scholarly journals Modelling LAI, surface water and carbon fluxes at high-resolution over France: comparison of ISBA-A-gs and ORCHIDEE

2011 ◽  
Vol 8 (4) ◽  
pp. 7399-7439 ◽  
Author(s):  
S. Lafont ◽  
Y. Zhao ◽  
J.-C. Calvet ◽  
P. Peylin ◽  
P. Ciais ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Land Surface ◽  
Satellite Remote Sensing ◽  
Carbon Fluxes ◽  
Canopy Conductance ◽  
Area Index ◽  
Surface Modelling ◽  
Land Cover Map ◽  
Land Surface Modelling ◽  
The Impact

Abstract. The Leaf Area Index (LAI) is a measure of the amount of photosynthetic leaves and governs the canopy conductance to water vapor and carbon dioxide. Four different estimates of LAI were compared over France: two LAI products derived from satellite remote sensing, and two LAI simulations derived from land surface modelling. The simulated LAI was produced by the ISBA-A-gs model and by the ORCHIDEE model (developed by CNRM-GAME and by IPSL, respectively), for the 1994–2007 period. The two models were driven by the same atmospheric variables and used the same land cover map (SAFRAN and ECOCLIMAP-II, respectively). The MODIS and CYCLOPES satellite LAI products were used. Both products were available from 2000 to 2007 and this relatively long period allowed to investigate the interannual and the seasonal variability of monthly LAI values. In particular the impact of the 2003 and 2005 droughts were analyzed. The two models presented contrasting results, with a difference of one month between the average leaf onset dates simulated by the two models, and a maximum interannual variability of LAI simulated at springtime by ORCHIDEE and at summertime by ISBA-A-gs. The comparison with the satellite LAI products showed that, in general, the seasonality was better represented by ORCHIDEE, while ISBA-A-gs tended to better represent the interannual variability, especially for grasslands. While the two models presented comparable values of net carbon fluxes, ORCHIDEE simulated much higher photosynthesis rates than ISBA-A-gs (+70 %), while providing lower transpiration estimates (−8 %).

scholarly journals JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator

2015 ◽  
Vol 8 (4) ◽  
pp. 1139-1155 ◽  
Author(s):  
T. Osborne ◽  
J. Gornall ◽  
J. Hooker ◽  
K. Williams ◽  
A. Wiltshire ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Gross Primary Production ◽  
Land Surface Model ◽  
Water Security ◽  
Heat Fluxes ◽  
Surface Model ◽  
Yield Model ◽  
Area Index ◽  
The Impact

Abstract. Studies of climate change impacts on the terrestrial biosphere have been completed without recognition of the integrated nature of the biosphere. Improved assessment of the impacts of climate change on food and water security requires the development and use of models not only representing each component but also their interactions. To meet this requirement the Joint UK Land Environment Simulator (JULES) land surface model has been modified to include a generic parametrisation of annual crops. The new model, JULES-crop, is described and evaluation at global and site levels for the four globally important crops; wheat, soybean, maize and rice. JULES-crop demonstrates skill in simulating the inter-annual variations of yield for maize and soybean at the global and country levels, and for wheat for major spring wheat producing countries. The impact of the new parametrisation, compared to the standard configuration, on the simulation of surface heat fluxes is largely an alteration of the partitioning between latent and sensible heat fluxes during the later part of the growing season. Further evaluation at the site level shows the model captures the seasonality of leaf area index, gross primary production and canopy height better than in the standard JULES. However, this does not lead to an improvement in the simulation of sensible and latent heat fluxes. The performance of JULES-crop from both an Earth system and crop yield model perspective is encouraging. However, more effort is needed to develop the parametrisation of the model for specific applications. Key future model developments identified include the introduction of processes such as irrigation and nitrogen limitation which will enable better representation of the spatial variability in yield.

scholarly journals Influence of Land Cover and Soil Moisture on the Horizontal Distribution of Sensible and Latent Heat Fluxes in Southeast Kansas during IHOP_2002 and CASES-97

2007 ◽  
Vol 8 (1) ◽  
pp. 68-87 ◽  
Author(s):  
Margaret A. LeMone ◽  
Fei Chen ◽  
Joseph G. Alfieri ◽  
Mukul Tewari ◽  
Bart Geerts ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Latent Heat ◽  
Land Surface ◽  
Field Experiments ◽  
Time Of Day ◽  
Horizontal Distribution ◽  
Heat Fluxes ◽  
Surface Model ◽  
Green Vegetation ◽  
The Impact

Abstract Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/ΔxyH for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = Rnet − Gsfc, where Rnet is the net radiation and Gsfc is the flux into the soil; Rnet − Gsfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.

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