scholarly journals The seasonal cycle of <i>p</i>CO<sub>2</sub> and CO<sub>2</sub> fluxes in the Southern Ocean: diagnosing anomalies in CMIP5 Earth system models

2018 ◽  
Vol 15 (9) ◽  
pp. 2851-2872 ◽  
Author(s):  
N. Precious Mongwe ◽  
Marcello Vichi ◽  
Pedro M. S. Monteiro
Keyword(s):  
Southern Ocean ◽  
Seasonal Cycle ◽  
Dissolved Inorganic Carbon ◽  
Coupled Model ◽  
Dominant Mode ◽  
Cmip5 Models ◽  
Earth System ◽  
System Models ◽  
Rates Of Change ◽  
Earth System Models

Abstract. The Southern Ocean forms an important component of the Earth system as a major sink of CO2 and heat. Recent studies based on the Coupled Model Intercomparison Project version 5 (CMIP5) Earth system models (ESMs) show that CMIP5 models disagree on the phasing of the seasonal cycle of the CO2 flux (FCO2) and compare poorly with available observation products for the Southern Ocean. Because the seasonal cycle is the dominant mode of CO2 variability in the Southern Ocean, its simulation is a rigorous test for models and their long-term projections. Here we examine the competing roles of temperature and dissolved inorganic carbon (DIC) as drivers of the seasonal cycle of pCO2 in the Southern Ocean to explain the mechanistic basis for the seasonal biases in CMIP5 models. We find that despite significant differences in the spatial characteristics of the mean annual fluxes, the intra-model homogeneity in the seasonal cycle of FCO2 is greater than observational products. FCO2 biases in CMIP5 models can be grouped into two main categories, i.e., group-SST and group-DIC. Group-SST models show an exaggeration of the seasonal rates of change of sea surface temperature (SST) in autumn and spring during the cooling and warming peaks. These higher-than-observed rates of change of SST tip the control of the seasonal cycle of pCO2 and FCO2 towards SST and result in a divergence between the observed and modeled seasonal cycles, particularly in the Sub-Antarctic Zone. While almost all analyzed models (9 out of 10) show these SST-driven biases, 3 out of 10 (namely NorESM1-ME, HadGEM-ES and MPI-ESM, collectively the group-DIC models) compensate for the solubility bias because of their overly exaggerated primary production, such that biologically driven DIC changes mainly regulate the seasonal cycle of FCO2.

scholarly journals Context for interpreting equilibrium climate sensitivity and transient climate response from the CMIP6 Earth system models

2020 ◽  
Vol 6 (26) ◽  
pp. eaba1981 ◽  
Author(s):  
Gerald A. Meehl ◽  
Catherine A. Senior ◽  
Veronika Eyring ◽  
Gregory Flato ◽  
Jean-Francois Lamarque ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Climate Response ◽  
Earth System ◽  
Transient Climate Response ◽  
Equilibrium Climate Sensitivity ◽  
System Models ◽  
Intercomparison Project ◽  
Earth System Models

For the current generation of earth system models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6), the range of equilibrium climate sensitivity (ECS, a hypothetical value of global warming at equilibrium for a doubling of CO2) is 1.8°C to 5.6°C, the largest of any generation of models dating to the 1990s. Meanwhile, the range of transient climate response (TCR, the surface temperature warming around the time of CO2 doubling in a 1% per year CO2 increase simulation) for the CMIP6 models of 1.7°C (1.3°C to 3.0°C) is only slightly larger than for the CMIP3 and CMIP5 models. Here we review and synthesize the latest developments in ECS and TCR values in CMIP, compile possible reasons for the current values as supplied by the modeling groups, and highlight future directions. Cloud feedbacks and cloud-aerosol interactions are the most likely contributors to the high values and increased range of ECS in CMIP6.

scholarly journals Inconsistent strategies to spin up models in CMIP5: implications for ocean biogeochemical model performance assessment

2016 ◽  
Vol 9 (5) ◽  
pp. 1827-1851 ◽  
Author(s):  
Roland Séférian ◽  
Marion Gehlen ◽  
Laurent Bopp ◽  
Laure Resplandy ◽  
James C. Orr ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Initial Conditions ◽  
Model Performance ◽  
Cmip5 Models ◽  
Biogeochemical Model ◽  
Earth System ◽  
Model Intercomparison ◽  
System Models ◽  
Marine Biogeochemistry ◽  
Earth System Models

Abstract. During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were made to systematically assess the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. In routine assessments model historical hindcasts were compared with available modern biogeochemical observations. However, these assessments considered neither how close modeled biogeochemical reservoirs were to equilibrium nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESMs) contributes to model-to-model differences in the simulated fields. We take advantage of a 500-year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and holds when confronted with a larger ensemble of CMIP5 models. This shows that drift has implications for performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to-model uncertainty. This requires more attention in future model intercomparison exercises in order to provide quantitatively more correct ESM results on marine biogeochemistry and carbon cycle feedbacks.

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

&lt;p&gt;The Earth&amp;#8217;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.&amp;#160;&lt;/p&gt;&lt;p&gt;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.&lt;br&gt;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.&lt;/p&gt;

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

&lt;p&gt;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&lt;sub&gt;2&lt;/sub&gt; 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.&lt;/p&gt;

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.

How well do the latest Earth System Models capture the behaviour of biogenic secondary organic aerosol in the atmosphere?

2020 ◽  
Author(s):  
Catherine Scott ◽  
Masaru Yoshioka ◽  
Chris Dearden ◽  
Ken Carslaw ◽  
Dominick Spracklen ◽  
...  
Keyword(s):  
Seasonal Cycle ◽  
Particle Number ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Aerosol Size Distribution ◽  
Forest Site ◽  
Earth System ◽  
System Models ◽  
Aerosol Mass ◽  
Earth System Models

&lt;p&gt;Biogenic secondary organic aerosol (SOA) is formed as a result of the atmospheric oxidation of gas-phase biogenic volatile organic compounds (BVOCs). Here, we evaluate the ability of five European Earth System Models (CNRM-ESM2-1, EC-Earth3, IPSL-CM6, NorESM1.2, UKESM1) to capture the amount, and behaviour, of biogenic SOA in the atmosphere.&lt;/p&gt;&lt;p&gt;The ESMs cover a range of complexity in terms of their representation of the sources and processing of biogenic SOA (i.e., from a fixed climatology of SOA amount to an interactive BVOC emission scheme followed by atmospheric processing).&lt;/p&gt;&lt;p&gt;We combine station measurements of BVOC emission and atmospheric BVOC concentrations with remotely sensed isoprene emission estimates to evaluate the models&amp;#8217; representation of the sources of biogenic SOA. We use organic aerosol mass and particle number concentration measurements from a number of forested sites to evaluate the ability of the models to capture the seasonal cycle in the amount of biogenic SOA present, as well as its impact on the aerosol size distribution. Whilst the models appear to capture the seasonal cycle in organic aerosol well for a boreal forest site, the ESMs consistently over-predict the amount of organic aerosol present at a tropical forest location.&amp;#160;&lt;/p&gt;&lt;p&gt;Finally, we explore the ability of these models to capture the observed relationships between organic aerosol mass, or particle number, and temperature. We find that the ESMs equipped with vegetation models that generate BVOC emissions interactively are able to capture well the strength of the observed relationship between temperature and organic aerosol mass. This lends confidence to the ability of these ESMs to accurately represent changes in atmospheric composition driven by climate.&lt;/p&gt;

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

&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;At the heart of this new version is the ESMValCore software package, which provides a configurable framework for finding CMIP files using a &amp;#8220;data reference syntax&amp;#8221;, 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.&lt;/p&gt;&lt;p&gt;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&amp;#8217;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document