scholarly journals Sensitivity and predictive uncertainty of the ACASA model at a spruce forest site

2010 ◽  
Vol 7 (11) ◽  
pp. 3685-3705 ◽  
Author(s):  
K. Staudt ◽  
E. Falge ◽  
R. D. Pyles ◽  
K. T. Paw U ◽  
T. Foken
Keyword(s):  
Latent Heat ◽  
Goodness Of Fit ◽  
Net Ecosystem Exchange ◽  
Heat Fluxes ◽  
Transfer Model ◽  
Forest Site ◽  
Area Index ◽  
Predictive Uncertainty ◽  
Mountainous Regions ◽  
Generalized Likelihood Uncertainty Estimation

Abstract. The sensitivity and predictive uncertainty of the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) was assessed by employing the Generalized Likelihood Uncertainty Estimation (GLUE) method. ACASA is a stand-scale, multi-layer soil-vegetation-atmosphere transfer model that incorporates a third order closure method to simulate the turbulent exchange of energy and matter within and above the canopy. Fluxes simulated by the model were compared to sensible and latent heat fluxes as well as the net ecosystem exchange measured by an eddy-covariance system above the spruce canopy at the FLUXNET-station Waldstein-Weidenbrunnen in the Fichtelgebirge Mountains in Germany. From each of the intensive observation periods carried out within the EGER project (ExchanGE processes in mountainous Regions) in autumn 2007 and summer 2008, five days of flux measurements were selected. A large number (20000) of model runs using randomly generated parameter sets were performed and goodness of fit measures for all fluxes for each of these runs were calculated. The 10% best model runs for each flux were used for further investigation of the sensitivity of the fluxes to parameter values and to calculate uncertainty bounds. A strong sensitivity of the individual fluxes to a few parameters was observed, such as the leaf area index. However, the sensitivity analysis also revealed the equifinality of many parameters in the ACASA model for the investigated periods. The analysis of two time periods, each representing different meteorological conditions, provided an insight into the seasonal variation of parameter sensitivity. The calculated uncertainty bounds demonstrated that all fluxes were well reproduced by the ACASA model. In general, uncertainty bounds encompass measured values better when these are conditioned on the respective individual flux only and not on all three fluxes concurrently. Structural weaknesses of the ACASA model concerning the soil respiration calculations and the simulation of the latent heat flux during dry conditions were detected, with improvements suggested for each.

scholarly journals Sensitivity and predictive uncertainty of the ACASA model at a spruce forest site

2010 ◽  
Vol 7 (3) ◽  
pp. 4223-4271 ◽  
Author(s):  
K. Staudt ◽  
E. Falge ◽  
R. D. Pyles ◽  
K. T. Paw U ◽  
T. Foken
Keyword(s):  
Goodness Of Fit ◽  
Net Ecosystem Exchange ◽  
Heat Fluxes ◽  
Transfer Model ◽  
Forest Site ◽  
Area Index ◽  
Predictive Uncertainty ◽  
Mountainous Regions ◽  
The Individual ◽  
Generalized Likelihood Uncertainty Estimation

Abstract. The sensitivity and predictive uncertainty of the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) was assessed by employing the Generalized Likelihood Uncertainty Estimation (GLUE) method. ACASA is a stand-scale, multi-layer soil-vegetation-atmosphere transfer model that incorporates a third order closure method to simulate the turbulent exchange of energy and matter within and above the canopy. Fluxes simulated by the model were compared to sensible and latent heat fluxes as well as the net ecosystem exchange measured by an eddy-covariance system above the spruce canopy at the FLUXNET-station Waldstein-Weidenbrunnen in the Fichtelgebirge Mountains in Germany. From each of the intensive observation periods carried out within the EGER project (ExchanGE processes in mountainous Regions) in autumn 2007 and summer 2008, five days of flux measurements were selected. A large number (20 000) of model runs using randomly generated parameter sets were performed and goodness of fit measures for all fluxes for each of these runs calculated. The 10% best model runs for each flux were used for further investigation of the sensitivity of the fluxes to parameter values and to calculate uncertainty bounds. A strong sensitivity of the individual fluxes to a few parameters was observed, such as the leaf area index. However, the sensitivity analysis also revealed the equifinality of many parameters in the ACASA model for the investigated periods. The analysis of two time periods, each representing different meteorological conditions, provided an insight into the seasonal variation of parameter sensitivity. The calculated uncertainty bounds demonstrated that all fluxes were well reproduced by the ACASA model. In general, uncertainty bounds encompass measured values better when these are conditioned on the respective individual flux only and not on all three fluxes concurrently. Structural weaknesses of the ACASA model concerning the soil respiration calculations were detected and improvements suggested.

scholarly journals How representative are FLUXNET measurements of surface fluxes during temperature extremes?

2018 ◽  
Author(s):  
Sophie V. J. van der Horst ◽  
Andrew J. Pitman ◽  
Martin G. De Kauwe ◽  
Anna Ukkola ◽  
Gab Abramowitz ◽  
...  
Keyword(s):  
Temperature Distribution ◽  
Latent Heat ◽  
Net Ecosystem Exchange ◽  
The United States ◽  
Fair Use ◽  
Heat Fluxes ◽  
Temperature Extremes ◽  
Measured Temperature ◽  
Sensible Heat ◽  
Lower Tail

Abstract. In response to a warming climate, temperature extremes are changing in many regions of the world. Therefore, understanding how the fluxes of sensible heat, latent heat and net ecosystem exchange respond and contribute to these changes is important. We examined 216 sites from the open access Tier 1 FLUXNET2015 and Free-Fair-Use La Thuile datasets, focussing only on observed (non-gap filled) data periods. We examined the availability of sensible heat, latent heat and net ecosystem exchange observations coincident in time with measured temperature for all temperatures, and separately for the upper and lower tail of the temperature distribution and expressed this availability as a measurement ratio. We showed that the measurement ratios for both sensible and latent heat fluxes are generally lower (0.79 and 0.73 respectively) than for temperature, and the measurement ratio of net ecosystem exchange measurements are appreciably lower (0.42). However, sites do exist with a high proportion of measured sensible and latent heat fluxes, mostly over the United States, Europe and Australia. Few sites have a high proportion of measured fluxes at the lower tail of the temperature distribution over very cold regions (e.g. Alaska, Russia) and at the upper tail in many warm regions (e.g. Central America and the majority of the Mediterranean region), and many of the world’s coldest and hottest regions are not represented in the freely available FLUXNET data at all (e.g. India, the Gulf States, Greenland and Antarctica). However, some sites do provide measured fluxes at extreme temperatures suggesting an opportunity for the FLUXNET community to share strategies to increase measurement availability at the tails of the temperature distribution. We also highlight a wide discrepancy between the measurement ratios across FLUXNET sites that is not related to the actual temperature or rainfall regimes at the site, which we cannot explain. Our analysis provides guidance to help select eddy covariance sites for researchers interested in exploring responses to temperature extremes.

scholarly journals Ability of a soil–vegetation–atmosphere transfer model and a two-source energy balance model to predict evapotranspiration for several crops and climate conditions

2019 ◽  
Vol 23 (12) ◽  
pp. 5033-5058
Author(s):  
Guillaume Bigeard ◽  
Benoit Coudert ◽  
Jonas Chirouze ◽  
Salah Er-Raki ◽  
Gilles Boulet ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Latent Heat ◽  
Sensible Heat Flux ◽  
Heat Fluxes ◽  
Balance Model ◽  
Transfer Model ◽  
Climate Conditions ◽  
Crop Types ◽  
Svat Model

Abstract. The heterogeneity of Agroecosystems, in terms of hydric conditions, crop types and states, and meteorological forcing, is difficult to characterize precisely at the field scale over an agricultural landscape. This study aims to perform a sensitivity study with respect to the uncertain model inputs of two classical approaches used to map the evapotranspiration of agroecosystems: (1) a surface energy balance (SEB) model, the Two-Source Energy Balance (TSEB) model, forced with thermal infrared (TIR) data as a proxy for the crop hydric conditions, and (2) a soil–vegetation–atmosphere transfer (SVAT) model, the SEtHyS model, where hydric conditions are computed from a soil water budget. To this end, the models' skill was compared using a large and unique in situ database covering different crops and climate conditions, which was acquired over three experimental sites in southern France and Morocco. On average, the models provide 30 min estimations of latent heat flux (LE) with a RMSE of around 55 W m−2 for TSEB and 47 W m−2 for SEtHyS, and estimations of sensible heat flux (H) with a RMSE of around 29 W m−2 for TSEB and 38 W m−2 for SEtHyS. A sensitivity analysis based on realistic errors aimed to estimate the potential decrease in performance induced by the spatialization process. For the SVAT model, the multi-objective calibration iterative procedure (MCIP) is used to determine and test different sets of parameters. TSEB is run with only one set of parameters and provides acceptable performance for all crop stages apart from the early growing season (LAI < 0.2 m2 m−2) and when hydric stress occurs. An in-depth study on the Priestley–Taylor key parameter highlights its marked diurnal cycle and the need to adjust its value to improve flux partitioning between the sensible and latent heat fluxes (1.5 and 1.25 for France and Morocco, respectively). Optimal values of 1.8–2 were highlighted under cloudy conditions, which is of particular interest due to the emergence of low-altitude drone acquisition. Under developed vegetation (LAI > 0.8 m2 m−2) and unstressed conditions, using sets of parameters that only differentiate crop types is a valuable trade-off for SEtHyS. This study provides some scientific elements regarding the joint use of both approaches and TIR imagery, via the development of new data assimilation and calibration strategies.

scholarly journals Ecosystem model optimization using in situ flux observations: benefit of Monte Carlo versus variational schemes and analyses of the year-to-year model performances

2014 ◽  
Vol 11 (24) ◽  
pp. 7137-7158 ◽  
Author(s):  
D. Santaren ◽  
P. Peylin ◽  
C. Bacour ◽  
P. Ciais ◽  
B. Longdoz
Keyword(s):  
Monte Carlo ◽  
Eddy Covariance ◽  
Latent Heat ◽  
Environmental Changes ◽  
Beech Forest ◽  
Heat Fluxes ◽  
Surface Model ◽  
Forest Site ◽  
Weather Regimes ◽  
Variational Scheme

Abstract. Terrestrial ecosystem models can provide major insights into the responses of Earth's ecosystems to environmental changes and rising levels of atmospheric CO2. To achieve this goal, biosphere models need mechanistic formulations of the processes that drive the ecosystem functioning from diurnal to decadal timescales. However, the subsequent complexity of model equations is associated with unknown or poorly calibrated parameters that limit the accuracy of long-term simulations of carbon or water fluxes and their interannual variations. In this study, we develop a data assimilation framework to constrain the parameters of a mechanistic land surface model (ORCHIDEE) with eddy-covariance observations of CO2 and latent heat fluxes made during the years 2001–2004 at the temperate beech forest site of Hesse, in eastern France. As a first technical issue, we show that for a complex process-based model such as ORCHIDEE with many (28) parameters to be retrieved, a Monte Carlo approach (genetic algorithm, GA) provides more reliable optimal parameter values than a gradient-based minimization algorithm (variational scheme). The GA allows the global minimum to be found more efficiently, whilst the variational scheme often provides values relative to local minima. The ORCHIDEE model is then optimized for each year, and for the whole 2001–2004 period. We first find that a reduced (<10) set of parameters can be tightly constrained by the eddy-covariance observations, with a typical error reduction of 90%. We then show that including contrasted weather regimes (dry in 2003 and wet in 2002) is necessary to optimize a few specific parameters (like the temperature dependence of the photosynthetic activity). Furthermore, we find that parameters inverted from 4 years of flux measurements are successful at enhancing the model fit to the data on several timescales (from monthly to interannual), resulting in a typical modeling efficiency of 92% over the 2001–2004 period (Nash–Sutcliffe coefficient). This suggests that ORCHIDEE is able robustly to predict, after optimization, the fluxes of CO2 and the latent heat of a specific temperate beech forest (Hesse site). Finally, it is shown that using only 1 year of data does not produce robust enough optimized parameter sets in order to simulate properly the year-to-year flux variability. This emphasizes the need to assimilate data over several years, including contrasted weather regimes, to improve the simulated flux interannual variability.

scholarly journals How representative are FLUXNET measurements of surface fluxes during temperature extremes?

2019 ◽  
Vol 16 (8) ◽  
pp. 1829-1844 ◽  
Author(s):  
Sophie V. J. van der Horst ◽  
Andrew J. Pitman ◽  
Martin G. De Kauwe ◽  
Anna Ukkola ◽  
Gab Abramowitz ◽  
...  
Keyword(s):  
Temperature Distribution ◽  
Latent Heat ◽  
Net Ecosystem Exchange ◽  
The United States ◽  
Fair Use ◽  
Heat Fluxes ◽  
Temperature Extremes ◽  
Measured Temperature ◽  
Sensible Heat ◽  
Lower Tail

Abstract. In response to a warming climate, temperature extremes are changing in many regions of the world. Therefore, understanding how the fluxes of sensible heat, latent heat and net ecosystem exchange respond and contribute to these changes is important. We examined 216 sites from the open access Tier 1 FLUXNET2015 and free fair-use La Thuile data sets, focussing only on observed (non-gap-filled) data periods. We examined the availability of sensible heat, latent heat and net ecosystem exchange observations coincident in time with measured temperature for all temperatures, and separately for the upper and lower tail of the temperature distribution, and expressed this availability as a measurement ratio. We showed that the measurement ratios for both sensible and latent heat fluxes are generally lower (0.79 and 0.73 respectively) than for temperature measurements, and the measurement ratio of net ecosystem exchange measurements are appreciably lower (0.42). However, sites do exist with a high proportion of measured sensible and latent heat fluxes, mostly over the United States, Europe and Australia. Few sites have a high proportion of measured fluxes at the lower tail of the temperature distribution over very cold regions (e.g. Alaska, Russia) or at the upper tail in many warm regions (e.g. Central America and the majority of the Mediterranean region), and many of the world's coldest and hottest regions are not represented in the freely available FLUXNET data at all (e.g. India, the Gulf States, Greenland and Antarctica). However, some sites do provide measured fluxes at extreme temperatures, suggesting an opportunity for the FLUXNET community to share strategies to increase measurement availability at the tails of the temperature distribution. We also highlight a wide discrepancy between the measurement ratios across FLUXNET sites that is not related to the actual temperature or rainfall regimes at the site, which we cannot explain. Our analysis provides guidance to help select eddy covariance sites for researchers interested in understanding and/or modelling responses to temperature extremes.

scholarly journals Roles of spatially varying vegetation on surface fluxes within a small mountainous catchment

2010 ◽  
Vol 7 (1) ◽  
pp. 593-619
Author(s):  
G. N. Flerchinger ◽  
D. Marks ◽  
M. L. Reba ◽  
Q. Yu ◽  
M. S. Seyfried
Keyword(s):  
Water Balance ◽  
Latent Heat ◽  
Populus Tremuloides ◽  
Sensible Heat Flux ◽  
Growing Season ◽  
Carbon Fluxes ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Sensible Heat ◽  
Area Index

Abstract. Understanding the role of ecosystems in modulating energy, water and carbon fluxes is critical to quantifying the variability in energy, carbon, and water balances across landscapes. This study compares and contrasts the seasonal surface fluxes of sensible heat, latent heat and carbon fluxes measured over different vegetation in a rangeland mountainous environment within the Reynolds Creek Experimental Watershed. Eddy covariance systems were used to measure surface fluxes over low sagebrush (Artemesia arbuscula), aspen (Populus tremuloides) and the understory of grasses and forbs beneath the aspen canopy. Peak leaf area index of the sagebrush, aspen, and aspen understory was 0.77, 1.35, and 1.20, respectively. The sagebrush and aspen canopies were subject to similar meteorological forces, while the understory of the aspen was sheltered from the wind. Estimated cumulative evapotranspiratation from the sagebrush, aspen understory, and aspen trees were 399 mm, 205 mm and 318 mm. A simple water balance of the catchment indicated that of the 700 mm of areal average precipitation, 442 mm was lost to evapotranspiration, and 254 mm of streamflow was measured from the catchment; water balance closure for the catchment was within 7 mm. Fluxes of latent heat and carbon for all sites were minimal through the winter. Growing season fluxes of latent heat and carbon were consistently higher above the aspen canopy than from the other sites. While growing season carbon fluxes were very similar for the sagebrush and aspen understory, latent heat fluxes for the sagebrush were consistently higher. Higher evapotranspiration from the sagebrush was likely because it is more exposed to the wind. Sensible heat flux from the aspen tended to be slightly less than the sagebrush site during the growing season when the leaves were actively transpiring, but exceeded that from the sagebrush in May, September and October when the net radiation was offset by evaporative cooling. Results from this study illustrate the influence of vegetation on the spatial variability of surface fluxes across mountainous rangeland landscapes.

scholarly journals Parameter interactions and sensitivity analysis for modelling carbon heat and water fluxes in a natural peatland, using CoupModel v5

2016 ◽  
Vol 9 (12) ◽  
pp. 4313-4338 ◽  
Author(s):  
Christine Metzger ◽  
Mats B. Nilsson ◽  
Matthias Peichl ◽  
Per-Erik Jansson
Keyword(s):  
Aerodynamic Resistance ◽  
Net Ecosystem Exchange ◽  
Heat Fluxes ◽  
Sensitivity Analyses ◽  
Area Index ◽  
Soil Temperatures ◽  
Parameter Interactions ◽  
And Performance ◽  
Carbon Dioxide Co2 ◽  
Parameter Ranges

Abstract. In contrast to previous peatland carbon dioxide (CO2) model sensitivity analyses, which usually focussed on only one or a few processes, this study investigates interactions between various biotic and abiotic processes and their parameters by comparing CoupModel v5 results with multiple observation variables. Many interactions were found not only within but also between various process categories simulating plant growth, decomposition, radiation interception, soil temperature, aerodynamic resistance, transpiration, soil hydrology and snow. Each measurement variable was sensitive to up to 10 (out of 54) parameters, from up to 7 different process categories. The constrained parameter ranges varied, depending on the variable and performance index chosen as criteria, and on other calibrated parameters (equifinalities). Therefore, transferring parameter ranges between models needs to be done with caution, especially if such ranges were achieved by only considering a few processes. The identified interactions and constrained parameters will be of great interest to use for comparisons with model results and data from similar ecosystems. All of the available measurement variables (net ecosystem exchange, leaf area index, sensible and latent heat fluxes, net radiation, soil temperatures, water table depth and snow depth) improved the model constraint. If hydraulic properties or water content were measured, further parameters could be constrained, resolving several equifinalities and reducing model uncertainty. The presented results highlight the importance of considering biotic and abiotic processes together and can help modellers and experimentalists to design and calibrate models as well as to direct experimental set-ups in peatland ecosystems towards modelling needs.

scholarly journals Leaf Area Index Specification for Use in Mesoscale Weather Prediction Systems

2009 ◽  
Vol 137 (10) ◽  
pp. 3535-3550 ◽  
Author(s):  
Christoph Knote ◽  
Giovanni Bonafe ◽  
Francesca Di Giuseppe
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Latent Heat ◽  
Positive Impact ◽  
Weather Prediction ◽  
Heat Fluxes ◽  
Mediterranean Ecosystem ◽  
Small Scale ◽  
Limited Area ◽  
Area Index

Abstract The energy budget at the surface is strongly influenced by the presence of vegetation, which alters the partitioning of thermal energy between sensible and latent heat fluxes. Despite its relevance, numerical weather prediction (NWP) systems often use only two parameters to describe the vegetation cover: the fractional area of vegetation occupying a given pixel and the leaf area index (LAI). In this study, the Consortium for Small-Scale Modelling (COSMO) limited-area forecast model is used to investigate the sensitivity of regional predictions to LAI assumptions over the Italian peninsula. Three different approaches are compared: a space- and time-invariant LAI dataset, a LAI specification based on Coordination of Information on the Environment (CORINE) land classes, and a Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-retrieved dataset. The three approaches resolve increasingly higher moments both in time and space of LAI probability density functions. Forecast scores employing the three datasets can therefore be used to assess the required degree of accuracy needed for this parameter. The MODIS dataset is the only one able to capture the expected vegetative cycle that is typical of the Mediterranean ecosystem and noticeably improves the 850-hPa temperature and humidity forecast scores up to +72 h forecast time. This suggests that accounting for LAI temporal and spatial variability could potentially improve the prevision of lower-level variables. Nevertheless, model biases of 2-m screen temperatures are not substantially reduced by the more detailed LAI specification when comparisons to synoptic observing stations are performed. Using long-term measurements collected by the CarboEurope project, a detailed verification of sensible and latent heat flux predictions is also presented. It shows that the desirable positive impact arising from a better LAI specification is nullified by the large uncertainties in the initialization of the soil moisture, which remains a crucial parameter for the reduction of screen-level biases.

scholarly journals The importance of process interactions and parameter sensitivity for modelling the carbon dynamics in a natural peatland

2016 ◽  
Author(s):  
Christine Metzger ◽  
Mats B. Nilsson ◽  
Matthias Peichl ◽  
Per-Erik Jansson
Keyword(s):  
Net Ecosystem Exchange ◽  
Heat Fluxes ◽  
Sensitivity Analyses ◽  
Area Index ◽  
Soil Temperatures ◽  
Model Constraint ◽  
And Performance ◽  
Carbon Dioxide Co2 ◽  
Improved Model ◽  
Parameter Ranges

Abstract. In contrast to previous peatland carbon dioxide (CO2) model sensitivity analyses, usually focusing on only one or few modules, this study investigates interactions between various biotic and abiotic processes and their parameters by comparing CoupModel results with multiple observation variables. Many interactions were found not only within, but also between the various model modules. Each measurement variable was sensitive to up to ten (out of 54) parameters, from up to seven different processes. The constrained parameter ranges varied, depending on the variable and performance index chosen as criteria, and on other calibrated parameters (equifinalities). Therefore, transferring parameter ranges between models needs to be done with caution, especially if such ranges were achieved by considering only few processes. The identified interactions and constrained parameters will be of high interest to use for comparisons with model results and data from similar ecosystems. All of the available measurement variables (net ecosystem exchange, leaf area index, sensible and latent heat fluxes, net radiation, soil temperatures, water table depth and snow depth) improved model constraint. Additional measurements of soil hydraulic properties or water content would reduce equifinalities and constrain additional parameters that showed high range of uncertainty. The presented results can help modellers and experimentalists to design model calibrations and experimental setups on peatlands.

Sign in / Sign up

Export Citation Format

Share Document