Evaluating the potential of large-scale simulations to predict carbon fluxes of terrestrial ecosystems over a European Eddy Covariance network

Abstract. This paper reports a comparison between large-scale simulations of three different land surface models (LSMs), ORCHIDEE, ISBA-A-gs and CTESSEL, forced with the same meteorological data, and compared with the carbon fluxes measured at 32 eddy covariance (EC) flux tower sites in Europe. The results show that the three simulations have the best performance for forest sites and the poorest performance for cropland and grassland sites. In addition, the three simulations have difficulties capturing the seasonality of Mediterranean and sub-tropical biomes, characterized by dry summers. This reduced simulation performance is also reflected in deficiencies in diagnosed light-use efficiency (LUE) and vapour pressure deficit (VPD) dependencies compared to observations. Shortcomings in the forcing data may also play a role. These results indicate that more research is needed on the LUE and VPD functions for Mediterranean and sub-tropical biomes. Finally, this study highlights the importance of correctly representing phenology (i.e. leaf area evolution) and management (i.e. rotation–irrigation for cropland, and grazing–harvesting for grassland) to simulate the carbon dynamics of European ecosystems and the importance of ecosystem-level observations in model development and validation.

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Evaluating the potential of large scale simulations to predict carbon fluxes of terrestrial ecosystems over a European Eddy Covariance network

Biogeosciences Discussions ◽

10.5194/bgd-10-11857-2013 ◽

2013 ◽

Vol 10 (7) ◽

pp. 11857-11897 ◽

Cited By ~ 2

Author(s):

M. Balzarolo ◽

S. Boussetta ◽

G. Balsamo ◽

A. Beljaars ◽

F. Maignan ◽

...

Keyword(s):

Eddy Covariance ◽

Land Surface ◽

Large Scale ◽

Meteorological Data ◽

Vapour Pressure Deficit ◽

Terrestrial Ecosystems ◽

Carbon Fluxes ◽

Simulation Performance ◽

Research Activities ◽

Forest Sites

Abstract. Understanding and simulating land biosphere processes happening at the interface between plants and atmosphere are important research activities with operational applications for monitoring and predicting seasonal and inter-annual variability of terrestrial carbon fluxes in connection to a changing climate. This paper reports a comparison between three different Land Surface Models (LSMs), ORCHIDEE, ISBA-A-gs and CTESSEL used in the Copernicus-Land project precursor, forced with the same meteorological data, and compared with the carbon fluxes measured at 32 Eddy Covariance (EC) flux tower sites in Europe. The results show that the three models have the best performance for forest sites and the poorest performance for cropland and grassland sites. In addition, the three models have difficulties capturing the seasonality of Mediterranean and Sub-tropical biomes, characterized by dry summers. This reduced simulation performance is also reflected in deficiencies in diagnosed Light Use Efficiency (LUE) and Vapour Pressure Deficit (VPD) dependencies compared to observations. Shortcomings in the forcing data may also play a role. These results indicate that more research is needed on the LUE and VPD functions for Mediterranean and Sub-tropical biomes. Finally, this study highlights the importance well representing phenology (i.e. Leaf Area evolution) and management (i.e. rotation/irrigation for cropland, and grazing/harvesting for grassland) to simulate the carbon dynamics of European ecosystems and the importance of ecosystem level observation in models development and validation.

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A Functional Response Metric for the Temperature Sensitivity of Tropical Ecosystems

Earth Interactions ◽

10.1175/ei-d-17-0017.1 ◽

2018 ◽

Vol 22 (7) ◽

pp. 1-20 ◽

Cited By ~ 3

Author(s):

Gretchen Keppel-Aleks ◽

Samantha J. Basile ◽

Forrest M. Hoffman

Keyword(s):

Growth Rate ◽

Time Scales ◽

Northern Hemisphere ◽

Temperature Sensitivity ◽

Land Surface ◽

Model Development ◽

Terrestrial Ecosystems ◽

Carbon Fluxes ◽

Hemisphere Winter

Abstract Earth system models (ESMs) simulate a large spread in carbon cycle feedbacks to climate change, particularly in their prediction of cumulative changes in terrestrial carbon storage. Evaluating the performance of ESMs against observations and assessing the likelihood of long-term climate predictions are crucial for model development. Here, we assessed the use of atmospheric growth rate variations to evaluate the sensitivity of tropical ecosystem carbon fluxes to interannual temperature variations. We found that the temperature sensitivity of the observed growth rate depended on the time scales over which atmospheric observations were averaged. The temperature sensitivity of the growth rate during Northern Hemisphere winter is most directly related to the tropical carbon flux sensitivity since winter variations in Northern Hemisphere carbon fluxes are relatively small. This metric can be used to test the fidelity of interactions between the physical climate system and terrestrial ecosystems within ESMs, which is especially important since the short-term relationship between ecosystem fluxes and temperature stress may be related to the long-term feedbacks between ecosystems and climate. If the interannual temperature sensitivity is used to constrain long-term temperature responses, the inferred sensitivity may be biased by 20%, unless the seasonality of the relationship between the observed growth rate and tropical fluxes is taken into account. These results suggest that atmospheric data can be used directly to evaluate regional land fluxes from ESMs, but underscore that the interaction between the time scales for land surface processes and those for atmospheric processes must be considered.

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Potential knowledge gain in large-scale simulations of forest carbon fluxes from remotely sensed biomass and height

Forest Ecology and Management ◽

10.1016/j.foreco.2010.11.002 ◽

2011 ◽

Vol 261 (3) ◽

pp. 515-530 ◽

Cited By ~ 10

Author(s):

V. Bellassen ◽

N. Delbart ◽

G. Le Maire ◽

S. Luyssaert ◽

P. Ciais ◽

...

Keyword(s):

Large Scale ◽

Carbon Fluxes ◽

Remotely Sensed ◽

Forest Carbon ◽

Knowledge Gain ◽

Large Scale Simulations

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Phenology-induced energy and carbon fluxes in land surface models

10.5194/egusphere-egu2020-17702 ◽

2020 ◽

Author(s):

Jan De Pue ◽

José Miguel Barrios ◽

Fabienne Maignan ◽

Liyang Liu ◽

Philippe Ciais ◽

...

Keyword(s):

Remote Sensing ◽

Land Surface ◽

Terrestrial Ecosystems ◽

Carbon Fluxes ◽

Land Surface Models ◽

Energy Fluxes ◽

Wide Range ◽

Surface Models ◽

Modelling Strategies ◽

Phenological Cycle

The annual phenological cycle is of key importance for the carbon and energy fluxes in terrestrial ecosystems. Although the processes controlling budburst and leaf senescence are fairly well known, the connection between plant phenology and the carbon fluxes remains a challenging aspect in land surface modelling (LSM). In this study, the modelling strategies of three well stablished LSM are compared. The LSM considered in this study were: ORCHIDEE, ISBA-A-gs and the model driving the LSA-SAF evapotranspiration product (https://landsaf.ipma.pt). The latter model does not simulate the carbon fluxes but focuses on the computation of evapotranspiration and energy fluxes. The phenological cycle is simulated explicitly in the ORCHIDEE model, using empirical relations based on temperature sum, water availability, and other variables. In the ISBA-A-gs model, phenology and LAI development is fully photosynthesis-driven. The phenology in the LSA-SAF model is driven by remote sensing forcing variables, such as LAI observations. Alternatively, the assimilation of remote sensing LAI products is a convenient method to improve the simulated phenological cycle in land surface models. A dedicated module for this operation is available in ISBA-A-gs. Simulations were performed over a wide range of climatological conditions and plant functional types. The results were then validated with in-situ measurements conducted at Fluxnet stations. In addition to the comparison between measured and modelled carbon fluxes, the validation in this study included the intra-annual variation in the simulated phenological cycle.

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Small-scale processes with large-scale impacts: Investigating canopy structure controls on energy fluxes to the forest snowpack

10.5194/egusphere-egu2020-19027 ◽

2020 ◽

Author(s):

Giulia Mazzotti ◽

Richard Essery ◽

Johanna Malle ◽

Clare Webster ◽

Tobias Jonas

Keyword(s):

High Resolution ◽

Land Surface ◽

Large Scale ◽

Meteorological Data ◽

Canopy Structure ◽

Model Performance ◽

Turbulent Fluxes ◽

Temporal Variations ◽

Small Scale ◽

Forest Stands

Forest canopies strongly affect snowpack energetics during wintertime. In discontinuous forest stands, spatio-temporal variations in radiative and turbulent fluxes create complex snow distribution and melt patterns, with further impacts on the hydrological regimes and on the land surface properties of seasonally snow-covered forested environments.As increasingly detailed canopy structure datasets are becoming available, canopy-induced energy exchange processes can be explicitly represented in high-resolution snow models. We applied the modelling framework FSM2 to obtain spatially distributed simulations of the forest snowpack in subalpine and boreal forest stands at high spatial (2m) and temporal (10min) resolution. Modelled sub-canopy radiative and turbulent fluxes were compared to detailed meteorological data of incoming irradiances, air and snow surface temperatures. These were acquired with novel observational systems, including 1) a motorized cable car setup recording spatially and temporally resolved data along a transect and 2) a handheld setup designed to capture temporal snapshots of 2D spatial distributions across forest discontinuities.The combination of high-resolution modelling and multi-dimensional datasets allowed us to assess model performance at the level of individual energy balance components, under various meteorological conditions and across canopy density gradients. We showed which canopy representation strategies within FSM2 best succeeded in reproducing snowpack energy transfer dynamics in discontinuous forests, and derived implications for implementing forest snow processes in coarser-resolution models.

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Water Flux Partitioning for Eddy Covariance Data

10.5194/egusphere-egu2020-18965 ◽

2020 ◽

Author(s):

Jacob Nelson

Keyword(s):

Eddy Covariance ◽

Sap Flow ◽

Meteorological Data ◽

Water Flux ◽

Carbon Fluxes ◽

Seasonal Cycles ◽

Flow Data ◽

The Core ◽

Core Energy ◽

Flux Partitioning

Here we present an overview of methods for partitioning evapotranspiration (ET) from eddy covariance data. We focus on methods that are designed to use the core energy and carbon fluxes, as well as meteorological data, and do not require supplemental measurements or campaigns. A comparison of three such methods for estimating transpiration (T) showed high correlations between them (R2 of &#160;daily T between 0.80 and 0.87) and higher correlations to daily stand T estimates from sap flow data (R2 between 0.58 and 0.66) compared to the tower ET (R2 = 0.49). However, the three methods show significant differences in magnitude, with T/ET values ranging from 45% to 77%. Despite the differences in magnitude, the methods show plausible patterns with respect to LAI, seasonal cycles, WUE, and VPD; moreover, they represent an improvement compared to using ET as a proxy for T even when filtering for days after rain. Finally, we outline practical aspects of applying the methods, such as how to apply the methods and code availability.

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The calibration-free complementary relationship (CR) approach aids large-scale ET estimation

10.5194/egusphere-egu2020-8217 ◽

2020 ◽

Author(s):

Ning Ma ◽

Jozsef Szilagyi ◽

Yinsheng Zhang

Keyword(s):

Remote Sensing ◽

Water Balance ◽

Eddy Covariance ◽

Land Surface ◽

Large Scale ◽

Relative Bias ◽

Dew Point ◽

Surface Model ◽

Complementary Relationship ◽

Calibration Free

Having recognized the limitations in spatial representativeness and/or temporal coverage of (i) current ground evapotranspiration (ETa) observations, and; (ii) land surface model (LSM) and remote sensing (RS) based ETa estimates due to uncertainties in soil and vegetation parameters, a calibration-free nonlinear complementary relationship (CR) model is employed with inputs of air and dew-point temperature, wind speed, and net radiation to estimate monthly ETa over conterminous United States during 1979&#8211;2015. Similar estimates of three land surface models (Noah, VIC, Mosaic), two reanalysis products (NCEP-II, ERA-Interim), two remote-sensing-based (GLEAM, PML) algorithms, and the spatially upscaled eddy-covariance ETa measurements of FLUXNET-MTE plus this new result from CR were validated against water-balance-derived results. We found that the CR outperforms all other methods in the multiyear mean annual HUC2-averaged ETa estimates with RMSE = 51 mm yr&#8722;1, R = 0.98, relative bias of &#8722;1 %, and NSE = 0.94, respectively. Inclusion of the GRACE data into the annual water balances for the considerably shorter 2003&#8211;2015 period does not have much effect on model performance. Besides, the CR outperforms all other models for the linear trends in annual ET rates over the HUC2 basins. Over the significantly smaller HUC6 basins where the water-balance validation is more uncertain, the CR still outperforms all other models except FLUXNET-MTE, which has the advantage of possible local ETa measurements, a benefit that clearly diminishes at the HUC2 scale.&#160;&#160; Because the employed CR method is calibration-free and requires only very few meteorological inputs, yet it yields superior ET performance at the regional scale, we further employed this method to develop a new 34-year (1982-2015) ETa product for China. The new Chinese ETa product was first validated against 13 eddy-covariance measurements in China, producing NSE values in the range of 0.72&#8211;0.95. On the basin scale, the modeled ETa values yielded a relative bias of 6%, and an NSE value of 0.80 in comparison with water-balance-derived evapotranspiration rates across ten major river basins in China, indicating the CR-simulated ETa rates reliable over China. Further evaluations suggest that the CR-based ETa product is more accurate than seven other mainstream ETa products. During last three decades, our new ETa product showed that annual ETa increased significantly over most parts of western and northeastern China, but decreased significantly in many regions of the North China Plain as well as in the eastern and southern coastal regions of China. This new CR-derived ETa product would benefit the community for long-term large-scale hydroclimatological studies.

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Analysis and Reduction of Systematic Errors through a Seamless Approach to Modeling Weather and Climate

Journal of Climate ◽

10.1175/2010jcli3541.1 ◽

2010 ◽

Vol 23 (22) ◽

pp. 5933-5957 ◽

Cited By ~ 123

Author(s):

G. M. Martin ◽

S. F. Milton ◽

C. A. Senior ◽

M. E. Brooks ◽

S. Ineson ◽

...

Keyword(s):

Time Scales ◽

Land Surface ◽

Large Scale ◽

Climate Models ◽

Spatial Scales ◽

Full Range ◽

Model Development ◽

Model Performance ◽

Systematic Errors ◽

Wide Range

Abstract The reduction of systematic errors is a continuing challenge for model development. Feedbacks and compensating errors in climate models often make finding the source of a systematic error difficult. In this paper, it is shown how model development can benefit from the use of the same model across a range of temporal and spatial scales. Two particular systematic errors are examined: tropical circulation and precipitation distribution, and summer land surface temperature and moisture biases over Northern Hemisphere continental regions. Each of these errors affects the model performance on time scales ranging from a few days to several decades. In both cases, the characteristics of the long-time-scale errors are found to develop during the first few days of simulation, before any large-scale feedbacks have taken place. The ability to compare the model diagnostics from the first few days of a forecast, initialized from a realistic atmospheric state, directly with observations has allowed physical deficiencies in the physical parameterizations to be identified that, when corrected, lead to improvements across the full range of time scales. This study highlights the benefits of a seamless prediction system across a wide range of time scales.

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Soil moisture–atmosphere feedback dominates land carbon uptake variability

Nature ◽

10.1038/s41586-021-03325-5 ◽

2021 ◽

Vol 592 (7852) ◽

pp. 65-69

Author(s):

Vincent Humphrey ◽

Alexis Berg ◽

Philippe Ciais ◽

Pierre Gentine ◽

Martin Jung ◽

...

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Climate Models ◽

Climate Model ◽

Dominant Role ◽

Vapour Pressure Deficit ◽

Terrestrial Ecosystems ◽

Surface Model ◽

Carbon Uptake ◽

Model Simulations

AbstractYear-to-year changes in carbon uptake by terrestrial ecosystems have an essential role in determining atmospheric carbon dioxide concentrations1. It remains uncertain to what extent temperature and water availability can explain these variations at the global scale2–5. Here we use factorial climate model simulations6 and show that variability in soil moisture drives 90 per cent of the inter-annual variability in global land carbon uptake, mainly through its impact on photosynthesis. We find that most of this ecosystem response occurs indirectly as soil moisture–atmosphere feedback amplifies temperature and humidity anomalies and enhances the direct effects of soil water stress. The strength of this feedback mechanism explains why coupled climate models indicate that soil moisture has a dominant role4, which is not readily apparent from land surface model simulations and observational analyses2,5. These findings highlight the need to account for feedback between soil and atmospheric dryness when estimating the response of the carbon cycle to climatic change globally5,7, as well as when conducting field-scale investigations of the response of the ecosystem to droughts8,9. Our results show that most of the global variability in modelled land carbon uptake is driven by temperature and vapour pressure deficit effects that are controlled by soil moisture.

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Global evaluation of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 (r5986)

Geoscientific Model Development ◽

10.5194/gmd-14-1987-2021 ◽

2021 ◽

Vol 14 (4) ◽

pp. 1987-2010

Author(s):

Yan Sun ◽

Daniel S. Goll ◽

Jinfeng Chang ◽

Philippe Ciais ◽

Betrand Guenet ◽

...

Keyword(s):

Land Surface ◽

Large Scale ◽

Production Efficiency ◽

Carbon Sink ◽

A Priori ◽

Land Surface Model ◽

Terrestrial Ecosystems ◽

Surface Model ◽

Global Evaluation ◽

Biomass Turnover

Abstract. The availability of phosphorus (P) and nitrogen (N) constrains the ability of ecosystems to use resources such as light, water and carbon. In turn, nutrients impact the distribution of productivity, ecosystem carbon turnovers and their net exchange of CO2 with the atmosphere in response to variation of environmental conditions in both space and time. In this study, we evaluated the performance of the global version of the land surface model ORCHIDEE-CNP (v1.2), which explicitly simulates N and P biogeochemistry in terrestrial ecosystems coupled with carbon, water and energy transfers. We used data from remote sensing, ground-based measurement networks and ecological databases. Components of the N and P cycle at different levels of aggregation (from local to global) are in good agreement with data-driven estimates. When integrated for the period 1850 to 2017 forced with variable climate, rising CO2 and land use change, we show that ORCHIDEE-CNP underestimates the land carbon sink in the Northern Hemisphere (NH) during recent decades despite an a priori realistic gross primary productivity (GPP) response to rising CO2. This result suggests either that processes other than CO2 fertilization, which are omitted in ORCHIDEE-CNP such as changes in biomass turnover, are predominant drivers of the northern land sink and/or that the model parameterizations produce emerging nutrient limitations on biomass growth that are too strict in northern areas. In line with the latter, we identified biases in the simulated large-scale patterns of leaf and soil stoichiometry as well as plant P use efficiency, pointing towards P limitations that are too severe towards the poles. Based on our analysis of ecosystem resource use efficiencies and nutrient cycling, we propose ways to address the model biases by giving priority to better representing processes of soil organic P mineralization and soil inorganic P transformation, followed by refining the biomass production efficiency under increasing atmospheric CO2, phenology dynamics and canopy light absorption.

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