Are Earth system models able to reproduce the soil heterotrophic respiration fluxes?

2021 ◽  
Author(s):  
Bertrand Guenet ◽  
Jérémie Orliac ◽  
Lauric Cécillon ◽  
Olivier Torres ◽  
Laurent Bopp
Keyword(s):  
Soil Respiration ◽  
Coupled Model ◽  
Global Scale ◽  
Heterotrophic Respiration ◽  
Earth System ◽  
Mixed Effect ◽  
Microbial Decomposition ◽  
System Models ◽  
Earth System Models ◽  
Climate Dynamic

<p>Earth system models (ESMs) are numerical representations of the Earth system aiming at representing the climate dynamic including feedbacks between climate and carbon cycle. CO<sub>2</sub> flux due to soil respiration including heterotrophic respiration coming from the soil organic matter (SOM) microbial decomposition and autotrophic respiration coming from the roots respiration is one of the most important flux between the surface and the atmosphere. Thus, even small changes in this flux may impact drastically the climate dynamic. It is therefore essential that ESMs reliably reproduce soil respiration. Until recently, such an evaluation at global scale of the ESMs was not straightforward because of the absence of observation-derived product to evaluate heterotrophic respiration fluxes from ESMs at global scale. Recently, several gridded products were published opening a new research avenue on climate-carbon feedbacks. In this study, we used simulations from 13 ESMs performed within the sixth coupled model intercomparison project (CMIP6) and we evaluate their capacities to reproduce the heterotrophic respiration flux using three gridded observation-based products. We first evaluate the total heterotrophic respiration flux for each model as well as the spatial patterns. We observed that most of the models are able to reproduce the total heterotrophic respiration flux but the spatial analysis underlined that this was partially due to some bias compensation between regions overestimating the flux and regions underestimating the flux. To better identify the causes of the identified bias in predicting the total heterotrophic respiration flux, we analysed the residues of ESMs using linear mixed effect models and we observed that lithology and climate were the most important drivers of the ESMs residues. Our results suggest that the response of SOM microbial decomposition to soil moisture and temperature must be improved in the next ESMs generation and that the effect of lithology should be better taken into account.</p>

scholarly journals Causes of uncertainty in observed and projected heterotrophic respiration from Earth System Models

2017 ◽  
Author(s):  
Cary Lynch ◽  
Corinne Hartin ◽  
Min Chen ◽  
Ben Bond-Lamberty
Keyword(s):  
Model Development ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Heterotrophic Respiration ◽  
Climate Variables ◽  
Earth System ◽  
System Models ◽  
Scenario Evaluation ◽  
Statistical Relationships ◽  
Earth System Models

Abstract. Heterotrophic respiration (RH) is a large component of the terrestrial carbon cycle, but one poorly simulated by Earth system models (ESMs), which diverge significantly in their historical and future RH projections. There is little understanding, however, of the causes of this variability and its consequences for future model development and scenario evaluation, and examining the relationships between RH and key climate variables may help to understand where and why models are divergent. We quantified the statistical relationships between RH and other terrestrial/climate variables across a suite of 25 ESMs from the Coupled Model Intercomparison Project phase 5 (CMIP5) for the 20th and 21st centuries, comparing the models both to each other and to an observation-driven global RH dataset. Compared to observations, ESMs consistency overestimate both the magnitude and climate sensitivity of global RH. The relationship between RH and surface air temperature (TAS) is strong, especially at high latitudes, and largely consistent across models. The observed RH and precipitation (PR) relationship is strong and positive (r ≥ 0.5, P 

scholarly journals Examining soil carbon uncertainty in a global model: response of microbial decomposition to temperature, moisture and nutrient limitation

2013 ◽  
Vol 10 (6) ◽  
pp. 10229-10269
Author(s):  
J.-F. Exbrayat ◽  
A. J. Pitman ◽  
Q. Zhang ◽  
G. Abramowitz ◽  
Y.-P. Wang
Keyword(s):  
Soil Carbon ◽  
Nutrient Limitation ◽  
Historical Change ◽  
Cmip5 Models ◽  
Earth System ◽  
Microbial Decomposition ◽  
Soil C ◽  
System Models ◽  
C And N ◽  
Earth System Models

Abstract. Reliable projections of future climate require land–atmosphere carbon (C) fluxes to be represented realistically in Earth System Models. There are several sources of uncertainty in how carbon is parameterized in these models. First, while interactions between the C, nitrogen (N) and phosphorus (P) cycles have been implemented in some models, these lead to diverse changes in land–atmosphere fluxes. Second, while the parameterization of soil organic matter decomposition is similar between models, formulations of the control of the soil physical state on microbial activity vary widely. We address these sources uncertainty by implementing three soil moisture (SMRF) and three soil temperature (STRF) respiration functions in an Earth System Model that can be run with three degrees of biogeochemical nutrient limitation (C-only, C and N, and C and N and P). All 27 possible combinations of a SMRF with a STRF and a biogeochemical mode are equilibrated before transient historical (1850–2005) simulations are performed. As expected, implementing N and P limitation reduces the land carbon sink, transforming some regions from net sinks to net sources over the historical period (1850–2005). Differences in the soil C balance implied by the various SMRFs and STRFs also change the sign of some regional sinks. Further, although the absolute uncertainty in global carbon uptake is reduced, the uncertainty due to the SMRFs and STRFs grows relative to the inter-annual variability in net uptake when N and P limitations are added. We also demonstrate that the equilibrated soil C also depend on the shape of the SMRF and STRF. Equilibration using different STRFs and SMRFs and nutrient limitation generates a six-fold range of global soil C that largely mirrors the range in available (17) CMIP5 models. Simulating the historical change in soil carbon therefore critically depends on the choice of STRF, SMRF and nutrient limitation, as it controls the equilibrated state to which transient conditions are applied. This direct effect of the representation of microbial decomposition in Earth System Models adds to recent concerns on the adequacy of these simple representations of very complex soil carbon processes.

Disentangeling the shortwave surface energy balance in earth system models

2021 ◽  
Author(s):  
Kine Onsum Moseid
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Atmospheric Aerosols ◽  
Surface Energy Balance ◽  
Coupled Model ◽  
Shortwave Radiation ◽  
Earth System ◽  
System Models ◽  
Aerosol Forcing ◽  
Earth System Models

<p>The Earth’s surface energy balance is heavily affected by incoming solar radiation and how it propagates through our atmosphere. How the sunlight propagates towards the surface depends on the atmospheric presence of aerosols, gases, and clouds. </p><p>Surface temperature evolution according to earth system models (ESMs) in the historical experiment from the coupled model intercomparison project phase 6 (CMIP6) suggests that models may be overly sensitive to aerosol forcing. Other studies have found that ESMs do not recreate observed decadal patterns in surface shortwave radiation - suggesting the models inaccurately underestimate the shortwave impact of atmospheric aerosols. These contradictory results act as a basis for our study.<br>Our study decomposes what determines both all sky and clear sky downwelling shortwave radiation at the surface in ESMs, using different experiments of CMIP6. We try to determine the respective role of aerosols, clouds and gases in the shortwave energy balance at the surface, and assess the effect of seasonality and regional differences.</p>

scholarly journals Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6

2020 ◽  
Author(s):  
Roland Séférian ◽  
Sarah Berthet ◽  
Andrew Yool ◽  
Julien Palmiéri ◽  
Laurent Bopp ◽  
...  
Keyword(s):  
Coupled Model ◽  
Climate Feedback ◽  
Full Potential ◽  
Earth System ◽  
Current Generation ◽  
System Models ◽  
Biogeochemical Models ◽  
Marine Biogeochemistry ◽  
Intercomparison Project ◽  
Earth System Models

Abstract Purpose of Review The changes or updates in ocean biogeochemistry component have been mapped between CMIP5 and CMIP6 model versions, and an assessment made of how far these have led to improvements in the simulated mean state of marine biogeochemical models within the current generation of Earth system models (ESMs). Recent Findings The representation of marine biogeochemistry has progressed within the current generation of Earth system models. However, it remains difficult to identify which model updates are responsible for a given improvement. In addition, the full potential of marine biogeochemistry in terms of Earth system interactions and climate feedback remains poorly examined in the current generation of Earth system models. Summary Increasing availability of ocean biogeochemical data, as well as an improved understanding of the underlying processes, allows advances in the marine biogeochemical components of the current generation of ESMs. The present study scrutinizes the extent to which marine biogeochemistry components of ESMs have progressed between the 5th and the 6th phases of the Coupled Model Intercomparison Project (CMIP).

scholarly journals Plant Physiology Increases the Magnitude and Spread of the Transient Climate Response to CO2 in CMIP6 Earth System Models

2020 ◽  
Vol 33 (19) ◽  
pp. 8561-8578
Author(s):  
Claire M. Zarakas ◽  
Abigail L. S. Swann ◽  
Marysa M. Laguë ◽  
Kyle C. Armour ◽  
James T. Randerson
Keyword(s):  
Plant Physiology ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Physiological Effect ◽  
Climate Response ◽  
Earth System ◽  
Transient Climate Response ◽  
Near Surface ◽  
System Models ◽  
Earth System Models

AbstractIncreasing concentrations of CO2 in the atmosphere influence climate both through CO2’s role as a greenhouse gas and through its impact on plants. Plants respond to atmospheric CO2 concentrations in several ways that can alter surface energy and water fluxes and thus surface climate, including changes in stomatal conductance, water use, and canopy leaf area. These plant physiological responses are already embedded in most Earth system models, and a robust literature demonstrates that they can affect global-scale temperature. However, the physiological contribution to transient warming has yet to be assessed systematically in Earth system models. Here this gap is addressed using carbon cycle simulations from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP) to isolate the radiative and physiological contributions to the transient climate response (TCR), which is defined as the change in globally averaged near-surface air temperature during the 20-yr window centered on the time of CO2 doubling relative to preindustrial CO2 concentrations. In CMIP6 models, the physiological effect contributes 0.12°C (σ: 0.09°C; range: 0.02°–0.29°C) of warming to the TCR, corresponding to 6.1% of the full TCR (σ: 3.8%; range: 1.4%–13.9%). Moreover, variation in the physiological contribution to the TCR across models contributes disproportionately more to the intermodel spread of TCR estimates than it does to the mean. The largest contribution of plant physiology to CO2-forced warming—and the intermodel spread in warming—occurs over land, especially in forested regions.

Compatible Fossil Fuel CO2 emissions in the CMIP6 Earth System Models’ Historical and Shared Socioeconomic Pathway experiments of the 21st Century

2020 ◽  
pp. 1-72
Author(s):  
Spencer K. Liddicoat ◽  
Andy J. Wiltshire ◽  
Chris D. Jones ◽  
Vivek K. Arora ◽  
Victor Brovkin ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Fossil Fuel ◽  
Coupled Model ◽  
Historical Record ◽  
Emission Rates ◽  
Earth System ◽  
Uncertainty Range ◽  
System Models ◽  
Earth System Models ◽  
Fossil Fuel Emissions

AbstractWe present the compatible CO2 emissions from fossil fuel burning and industry, calculated from the historical and Shared Socioeconomic Pathway (SSP) experiments of nine Earth System Models (ESMs) participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The multi-model mean FF emissions match the historical record well and are close to the data-based estimate of cumulative emissions (392±63 GtC vs 400±20 GtC respectively). Only two models fall inside the observed uncertainty range; while two exceed the upper bound, five fall slightly below the lower bound, due primarily to the plateau in CO2 concentration in the 1940s. The ESMs’ diagnosed FF emission rates are consistent with those generated by the Integrated Assessment Models (IAMs) from which the SSPs’ CO2 concentration pathways were constructed; the simpler IAMs’ emissions lie within the ESMs’ spread for seven of the eight SSP experiments, the other being only marginally lower, providing confidence in the relationship between the IAMs’ FF emission rates and concentration pathways. The ESMs require fossil fuel emissions to reduce to zero and subsequently become negative in SSP1-1.9, SSP1-2.6, SSP4-3.4 and SSP5-3.4over. We also present the ocean and land carbon cycle responses of the ESMs in the historical and SSP scenarios. The models’ ocean carbon cycle responses are in close agreement, but there is considerable spread in their land carbon cycle responses. Land use and land cover change emissions have a strong influence over the magnitude of diagnosed fossil fuel emissions, with the suggestion of an inverse relationship between the two.

ESMValCore: analyzing CMIP data made easy

2020 ◽  
Author(s):  
Bouwe Andela ◽  
Lisa Bock ◽  
Björn Brötz ◽  
Faruk Diblen ◽  
Laura Dreyer ◽  
...  
Keyword(s):  
Open Source ◽  
Performance Metrics ◽  
Modular Design ◽  
Coupled Model ◽  
Application Programming Interface ◽  
Earth System ◽  
Evaluation Tool ◽  
System Models ◽  
Scientific Analysis ◽  
Earth System Models

<p>The Earth System Model Evaluation Tool (ESMValTool) is a free and open-source community diagnostic and performance metrics tool for the evaluation of Earth system models participating in the Coupled Model Intercomparison Project (CMIP). Version 2 of the tool (Righi et al. 2019, www.esmvaltool.org) features a brand new design, consisting of ESMValCore (https://github.com/esmvalgroup/esmvalcore), a package for working with CMIP data and ESMValTool (https://github.com/esmvalgroup/esmvaltool), a package containing the scientific analysis scripts. This new version has been specifically developed to handle the increased data volume of CMIP Phase 6 (CMIP6) and the related challenges posed by the analysis and the evaluation of output from multiple high-resolution or complex Earth system models. The tool also supports CMIP5 and CMIP3 datasets, as well as a large number of re-analysis and observational datasets that can be formatted according to the same standards (CMOR) on-the-fly or through scripts currently included in the ESMValTool package.</p><p>At the heart of this new version is the ESMValCore software package, which provides a configurable framework for finding CMIP files using a “data reference syntax”, applying commonly used pre-processing functions to them, running analysis scripts, and recording provenance. Numerous pre-processing functions, e.g. for data selection, regridding, and statistics are readily available and the modular design makes it easy to add more. The ESMValCore package is easy to install with relatively few dependencies, written in Python 3, based on state-of-the-art open-source libraries such as Iris and Dask, and widely used standards such as YAML, NetCDF, CF-Conventions, and W3C PROV. An extensive set of automated tests and code quality checks ensure the reliability of the package. Documentation is available at https://esmvaltool.readthedocs.io.</p><p>The ESMValCore package uses human-readable recipes to define which variables and datasets to use, how to pre-process that data, and what scientific analysis scripts to run. The package provides convenient interfaces, based on the YAML and NetCDF/CF-convention file formats, for running diagnostic scripts written in any programming language. Because the ESMValCore framework takes care of running the workflow defined in the recipe in parallel, most analyses run much faster, with no additional programming effort required from the authors of the analysis scripts. For example, benchmarks show a factor of 30 speedup with respect to version 1 of the tool for a representative recipe on a 24 core machine. A large collection of standard recipes and associated analysis scripts is available in the ESMValTool package for reproducing selected peer-reviewed analyses. The ESMValCore package can also be used with any other script that implements it’s easy to use interface. All pre-processing functions of the ESMValCore can also be used directly from any Python program. These features allow for use by a wide community of scientific users and developers with different levels of programming skills and experience.</p><p>Future plans involve extending the public Python API (application programming interface) from just preprocessor functions to include all functionality, including finding the data and running diagnostic scripts. This would make ESMValCore suitable for interactive data exploration from a Jupyter Notebook.</p>

Future fires in the Coupled Model Intercomparison Project (CMIP) phase 6

2020 ◽  
Author(s):  
Gitta Lasslop ◽  
Stijn Hantson ◽  
Victor Brovkin ◽  
Fang Li ◽  
David Lawrence ◽  
...  
Keyword(s):  
Land Use ◽  
Fire Regime ◽  
Coupled Model ◽  
Fire Regimes ◽  
Atmospheric Composition ◽  
Cloud Formation ◽  
Burned Area ◽  
Earth System ◽  
System Models ◽  
Earth System Models

<p>Fires are an important component in Earth system models (ESMs), they impact vegetation carbon storage, vegetation distribution, atmospheric composition and cloud formation. The representation of fires in ESMs contributing to CMIP phase 5 was still very simplified. Several Earth system models updated their representation of fires in the meantime. Using the latest simulations of CMIP6 we investigate how fire regimes change in the future for different scenarios and how land use, climate and atmospheric CO<sub>2</sub> concentration contribute to the fire regimes changes. We quantify changes in fire danger, burned area and carbon emissions on an annual and seasonal basis. Factorial model simulations allow to quantify the influence of land use, climate and atmospheric CO<sub>2</sub> on fire regimes.</p><p>We complement the information on fire regime change supplied by ESMs that include a fire module with a statistical modelling approach for burned area. This will use information from simulated changes in climate, vegetation and socioeconomic changes (population density and land use) provided for a set of different future scenarios. This allows the integration of information provided by global satellite products on burned area with the process-based simulations of climate and vegetation changes and information from socioeconomic scenarios.</p><p> </p>

scholarly journals An interactive ocean surface albedo scheme (OSAv1.0): formulation and evaluation in ARPEGE-Climat (V6.1) and LMDZ (V5A)

2018 ◽  
Vol 11 (1) ◽  
pp. 321-338 ◽  
Author(s):  
Roland Séférian ◽  
Sunghye Baek ◽  
Olivier Boucher ◽  
Jean-Louis Dufresne ◽  
Bertrand Decharme ◽  
...  
Keyword(s):  
Surface Albedo ◽  
Diffuse Radiation ◽  
Ocean Surface ◽  
Ocean Waves ◽  
Global Scale ◽  
Shortwave Radiation ◽  
Earth System ◽  
Diffuse Solar Radiation ◽  
System Models ◽  
Earth System Models

Abstract. Ocean surface represents roughly 70 % of the Earth's surface, playing a large role in the partitioning of the energy flow within the climate system. The ocean surface albedo (OSA) is an important parameter in this partitioning because it governs the amount of energy penetrating into the ocean or reflected towards space. The old OSA schemes in the ARPEGE-Climat and LMDZ models only resolve the latitudinal dependence in an ad hoc way without an accurate representation of the solar zenith angle dependence. Here, we propose a new interactive OSA scheme suited for Earth system models, which enables coupling between Earth system model components like surface ocean waves and marine biogeochemistry. This scheme resolves spectrally the various contributions of the surface for direct and diffuse solar radiation. The implementation of this scheme in two Earth system models leads to substantial improvements in simulated OSA. At the local scale, models using the interactive OSA scheme better replicate the day-to-day distribution of OSA derived from ground-based observations in contrast to old schemes. At global scale, the improved representation of OSA for diffuse radiation reduces model biases by up to 80 % over the tropical oceans, reducing annual-mean model–data error in surface upwelling shortwave radiation by up to 7 W m−2 over this domain. The spatial correlation coefficient between modeled and observed OSA at monthly resolution has been increased from 0.1 to 0.8. Despite its complexity, this interactive OSA scheme is computationally efficient for enabling precise OSA calculation without penalizing the elapsed model time.

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