scholarly journals Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

2013 ◽  
Vol 9 (3) ◽  
pp. 1111-1140 ◽  
Author(s):  
M. Eby ◽  
A. J. Weaver ◽  
K. Alexander ◽  
K. Zickfeld ◽  
A. Abe-Ouchi ◽  
...  

Abstract. Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

2012 ◽  
Vol 8 (4) ◽  
pp. 4121-4181 ◽  
Author(s):  
M. Eby ◽  
A. J. Weaver ◽  
K. Alexander ◽  
K. Zickfeld ◽  
A. Abe-Ouchi ◽  
...  

Abstract. Both historical and idealized climate model experiments are performed with a variety of Earth System Models of Intermediate Complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land-use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes seem to be underestimated. It is possible that recent modelled climate trends or climate-carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2x and 4x CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate-carbon feedbacks. The values from EMICs generally fall within the range given by General Circulation Models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows considerable synergy between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from paleoclimate reconstructions. This in turn could be a result of errors in the reconstructions of volcanic and/or solar radiative forcing used to drive the models or the incomplete representation of certain processes or variability within the models. Given the datasets used in this study, the models calculate significant land-use emissions over the pre-industrial. This implies that land-use emissions might need to be taken into account, when making estimates of climate-carbon feedbacks from paleoclimate reconstructions.


2012 ◽  
Vol 5 (2) ◽  
pp. 917-966 ◽  
Author(s):  
C. Stepanek ◽  
G. Lohmann

Abstract. In this manuscript we describe the experimental procedure employed at the Alfred Wegener Institute in Germany in the preparation of the simulations for the Pliocene Model Intercomparison Project (PlioMIP). We present a description of the utilized community earth system models (COSMOS) and document the procedures which we applied to transfer the Pliocene Research, Interpretation and Synoptic Mapping Project (PRISM) mid-Pliocene reconstruction into model forcing fields. The model setup and spin-up procedure are described for both the paleo and preindustrial (PI) time-slices of PlioMIP experiments 1 and 2, and general results that depict the performance of our model setup for mid-Pliocene conditions are presented. The mid-Pliocene as simulated with our COSMOS-setup and PRISM boundary conditions is both warmer and wetter than the PI. The globally averaged annual mean surface air temperature in the mid-Pliocene standalone atmosphere (fully coupled atmosphere-ocean) simulation is 17.35 °C (17.82 °C), which implies a warming of 2.23 °C (3.40 °C) relative to the respective PI control simulation.


2016 ◽  
Vol 29 (20) ◽  
pp. 7203-7213 ◽  
Author(s):  
Alan J. Hewitt ◽  
Ben B. B. Booth ◽  
Chris D. Jones ◽  
Eddy S. Robertson ◽  
Andy J. Wiltshire ◽  
...  

Abstract The inclusion of carbon cycle processes within CMIP5 Earth system models provides the opportunity to explore the relative importance of differences in scenario and climate model representation to future land and ocean carbon fluxes. A two-way analysis of variance (ANOVA) approach was used to quantify the variability owing to differences between scenarios and between climate models at different lead times. For global ocean carbon fluxes, the variance attributed to differences between representative concentration pathway scenarios exceeds the variance attributed to differences between climate models by around 2025, completely dominating by 2100. This contrasts with global land carbon fluxes, where the variance attributed to differences between climate models continues to dominate beyond 2100. This suggests that modeled processes that determine ocean fluxes are currently better constrained than those of land fluxes; thus, one can be more confident in linking different future socioeconomic pathways to consequences of ocean carbon uptake than for land carbon uptake. The contribution of internal variance is negligible for ocean fluxes and small for land fluxes, indicating that there is little dependence on the initial conditions. The apparent agreement in atmosphere–ocean carbon fluxes, globally, masks strong climate model differences at a regional level. The North Atlantic and Southern Ocean are key regions, where differences in modeled processes represent an important source of variability in projected regional fluxes.


2013 ◽  
Vol 26 (22) ◽  
pp. 8744-8764 ◽  
Author(s):  
Pu Shao ◽  
Xubin Zeng ◽  
Koichi Sakaguchi ◽  
Russell K. Monson ◽  
Xiaodong Zeng

Abstract Eight Earth System Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated, focusing on both the net carbon dioxide flux and its components and their relation with climatic variables (temperature, precipitation, and soil moisture) in the historical (1850–2005) and representative concentration pathway 4.5 (RCP4.5; 2006–2100) simulations. While model results differ, their median globally averaged production and respiration terms from 1976 to 2005 agree reasonably with available observation-based products. Disturbances such as land use change are roughly represented but crucial in determining whether the land is a carbon source or sink over many regions in both simulations. While carbon fluxes vary with latitude and between the two simulations, the ratio of net to gross primary production, representing the ecosystem carbon use efficiency, is less dependent on latitude and does not differ significantly in the historical and RCP4.5 simulations. The linear trend of increased land carbon fluxes (except net ecosystem production) is accelerated in the twenty-first century. The cumulative net ecosystem production by 2100 is positive (i.e., carbon sink) in all models and the tropical and boreal latitudes become major carbon sinks in most models. The temporal correlations between annual-mean carbon cycle and climate variables vary substantially (including the change of sign) among the eight models in both the historical and twenty-first-century simulations. The ranges of correlations of carbon cycle variables with precipitation and soil moisture are also quite different, reflecting the important impact of the model treatment of the hydrological cycle on the carbon cycle.


2011 ◽  
Vol 24 (16) ◽  
pp. 4255-4275 ◽  
Author(s):  
Kirsten Zickfeld ◽  
Michael Eby ◽  
H. Damon Matthews ◽  
Andreas Schmittner ◽  
Andrew J. Weaver

Abstract Coupled climate–carbon models have shown the potential for large feedbacks between climate change, atmospheric CO2 concentrations, and global carbon sinks. Standard metrics of this feedback assume that the response of land and ocean carbon uptake to CO2 (concentration–carbon cycle feedback) and climate change (climate–carbon cycle feedback) combine linearly. This study explores the linearity in the carbon cycle response by analyzing simulations with an earth system model of intermediate complexity [the University of Victoria Earth System Climate Model (UVic ESCM)]. The results indicate that the concentration–carbon and climate–carbon cycle feedbacks do not combine linearly to the overall carbon cycle feedback. In this model, the carbon sinks on land and in the ocean are less efficient when exposed to the combined effect of elevated CO2 and climate change than to the linear combination of the two. The land accounts for about 80% of the nonlinearity, with the ocean accounting for the remaining 20%. On land, this nonlinearity is associated with the different response of vegetation and soil carbon uptake to climate in the presence or absence of the CO2 fertilization effect. In the ocean, the nonlinear response is caused by the interaction of changes in physical properties and anthropogenic CO2. These findings suggest that metrics of carbon cycle feedback that postulate linearity in the system’s response may not be adequate.


2021 ◽  
Author(s):  
Atul Jain ◽  
Xiaoming Xu ◽  
Shijie Shu

<p>The aim of this study is to estimate the net carbon fluxes from agriculture-related land-use and land cover change (LULCC) activities, which are referred to as emissions from the land due to human activities. These include land use (LU, e.g., farmland for food and feed production, including management) and land cover changes (LCC, e.g., deforestation for and reforestation of agricultural land, and conversion of grasslands and pastureland to agriculture land or vice versa). Agriculture land-use practices could be a source of atmospheric CO2. However, the management of agricultural practices may reduce carbon emissions and increase soil carbon sequestration. Simultaneously, land-cover change activities clear existing ecosystems, their biomass and disturb the soil, generating carbon emissions. Previous earth system models usually have a simple or no representation of land agriculture practices, such as planting crops, fertilization, irrigation, harvesting grains for food and livestock-feed, recovering crop residue for feed and other usages, and grazing, livestock-feed, and manure cycle. This study uses a land surface model with spatially heterogeneous representations of such agricultural land use activities, in addition to land cover change, such as the change from forest to agricultural land. Our study shows the net agricultural land area increase of 0.11 million hectares/yr during 2007-2013, including 2.12 million hectares/yr of other land converted to agricultural land and 2.01 million hectares/yr of agricultural land converted to other lands. The results show that global net carbon flux due to agriculture-related LULCC is 2.26 Pg C/yr (net emission), consisting of 38% due to land-use activities and 62% due to land cover change. South America (22%), North America (19%), and South and Southeast Asia (13%) are the top contributing regions for net carbon flux induced by LULCC. South America has contributed the most flux from land cover change (18%), while North America has generated the most carbon flux due to land-use activities (12%) among all macro geopolitical regions.  By quantifying the carbon fluxes induced by different agriculture activities this study provides a complete estimate of the yearly carbon cycle in the agriculture system at the spatial scale, which may improve the representations of agriculture land use activities in Earth System Models.</p>


2016 ◽  
Author(s):  
Dongmin Kim ◽  
Myong-In Lee ◽  
Su-Jong Jeong ◽  
Jungho Im ◽  
Dong Hyun Cha ◽  
...  

Abstract. This study compares historical simulations of the terrestrial carbon cycle produced by 10 Earth System Models (ESMs) that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Using MODIS satellite estimates, this study validates the simulation of gross primary production (GPP), net primary production (NPP), and carbon use efficiency (CUE), which depend on plant function types (PFTs). The models show noticeable deficiencies compared to the MODIS data in the simulation of the spatial patterns of GPP and NPP and large differences among the simulations, although the multi-model ensemble (MME) mean provides a realistic global mean value and spatial distributions. The larger model spreads in GPP and NPP compared to those of surface temperature and precipitation suggest that the differences among simulations in terms of the terrestrial carbon cycle are largely due to uncertainties in the parameterization of terrestrial carbon fluxes by vegetation. The models also exhibit large spatial differences in their simulated CUE values and at locations where the dominant PFT changes, primarily due to differences in the parameterizations. While the MME-simulated CUE values show a strong dependence on surface temperatures, the observed CUE values from MODIS show greater complexity, as well as non-linear sensitivity. This leads to the overall underestimation of CUE using most of the PFTs incorporated into current ESMs. The results of this comparison suggest that more careful and extensive validation is needed to improve the terrestrial carbon cycle in terms of ecosystem-level processes.


2021 ◽  
Author(s):  
Thordis Thorarinsdottir ◽  
Jana Sillmann ◽  
Marion Haugen ◽  
Nadine Gissibl ◽  
Marit Sandstad

<p>Reliable projections of extremes in near-surface air temperature (SAT) by climate models become more and more important as global warming is leading to significant increases in the hottest days and decreases in coldest nights around the world with considerable impacts on various sectors, such as agriculture, health and tourism.</p><p>Climate model evaluation has traditionally been performed by comparing summary statistics that are derived from simulated model output and corresponding observed quantities using, for instance, the root mean squared error (RMSE) or mean bias as also used in the model evaluation chapter of the fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Both RMSE and mean bias compare averages over time and/or space, ignoring the variability, or the uncertainty, in the underlying values. Particularly when interested in the evaluation of climate extremes, climate models should be evaluated by comparing the probability distribution of model output to the corresponding distribution of observed data.</p><p>To address this shortcoming, we use the integrated quadratic distance (IQD) to compare distributions of simulated indices to the corresponding distributions from a data product. The IQD is the proper divergence associated with the proper continuous ranked probability score (CRPS) as it fulfills essential decision-theoretic properties for ranking competing models and testing equality in performance, while also assessing the full distribution.</p><p>The IQD is applied to evaluate CMIP5 and CMIP6 simulations of monthly maximum (TXx) and minimum near-surface air temperature (TNn) over the data-dense regions Europe and North America against both observational and reanalysis datasets. There is not a notable difference between the model generations CMIP5 and CMIP6 when the model simulations are compared against the observational dataset HadEX2. However, the CMIP6 models show a better agreement with the reanalysis ERA5 than CMIP5 models, with a few exceptions. Overall, the climate models show higher skill when compared against ERA5 than when compared against HadEX2. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.</p>


2018 ◽  
Vol 9 (2) ◽  
pp. 507-523 ◽  
Author(s):  
Steven J. Lade ◽  
Jonathan F. Donges ◽  
Ingo Fetzer ◽  
John M. Anderies ◽  
Christian Beer ◽  
...  

Abstract. Changes to climate–carbon cycle feedbacks may significantly affect the Earth system's response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth system models. Here, we construct a stylised global climate–carbon cycle model, test its output against comprehensive Earth system models, and investigate the strengths of its climate–carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon cycle feedbacks and the operation of the carbon cycle. Specific results include that different feedback formalisms measure fundamentally the same climate–carbon cycle processes; temperature dependence of the solubility pump, biological pump, and CO2 solubility all contribute approximately equally to the ocean climate–carbon feedback; and concentration–carbon feedbacks may be more sensitive to future climate change than climate–carbon feedbacks. Simple models such as that developed here also provide workbenches for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the planetary boundaries, that are currently too uncertain to be included in comprehensive Earth system models.


2010 ◽  
Vol 17 (3) ◽  
pp. 269-272 ◽  
Author(s):  
S. Nicolay ◽  
G. Mabille ◽  
X. Fettweis ◽  
M. Erpicum

Abstract. Recently, new cycles, associated with periods of 30 and 43 months, respectively, have been observed by the authors in surface air temperature time series, using a wavelet-based methodology. Although many evidences attest the validity of this method applied to climatic data, no systematic study of its efficiency has been carried out. Here, we estimate confidence levels for this approach and show that the observed cycles are significant. Taking these cycles into consideration should prove helpful in increasing the accuracy of the climate model projections of climate change and weather forecast.


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