Abstract
<p>Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) showed large uncertainties in simulating atmospheric CO<sub>2</sub> concentrations. We utilize the Earth System Model Evaluation Tool (ESMValTool) to evaluate emission-driven CMIP5 and CMIP6 simulations with satellite data of column-average CO<sub>2</sub> mole fractions (XCO<sub>2</sub>). XCO<sub>2</sub> time series show a large spread among the model ensembles both in CMIP5 and CMIP6. Using the satellite observations as reference, the CMIP6 models have a <span>l</span>ower bias in the the multi-model mean than CMIP5, but the spread remains large. The satellite data are a combined data product covering the period 2003–2014 based on the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)/Envisat (2003–2012) and Thermal And Near infrared Sensor for carbon Observation Fourier transform spectrometer/Greenhouse Gases Observing Satellite (TANSO-FTS/GOSAT) (2009–2014) instruments. While the combined satellite product shows a strong negative trend of decreasing <span>seasonal cycle amplitude (SCA)</span> with increasing XCO<sub>2</sub> in the northern midlatitudes, both CMIP ensembles instead show a non-significant positive trend in the multi-model mean. The negative trend is reproduced by the models when sampling them as the observations, attributing it to sampling characteristics. Applying a mask of the mean data coverage of each satellite to the models, the SCA is higher for the SCIAMACHY/Envisat mask than when using the TANSO-FTS/GOSAT mask. This induces an artificial negative trend when using observational sampling over the full period, as SCIAMACHY/Envisat covers the early period until 2012, with TANSO-FTS/GOSAT measurements starting in 2009. Overall, the CMIP6 ensemble shows better agreement with the satellite data than the CMIP5 ensemble in all considered quantities (mean XCO<sub>2</sub>, growth rate, SCA and trend in SCA). This study shows that the availability of column-integral CO<sub>2</sub> from satellite provides a promising new way to evaluate the performance of Earth system models on a global scale, complementing existing studies that are based on in situ measurements from single ground-based stations.</p>
Highlights
The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) concluded that since 1950 many of the observed changes in the climate system havePublished by Copernicus Publications on behalf of the European Geosciences Union.B
We focus on evaluating the growth rate and the seasonal cycle amplitude of simulated CO2, converted to XCO2, from Coupled Model Intercomparison Project (CMIP) Earth system models (ESMs) which performed emissiondriven simulations with satellite observations in Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6
The MRIESM1 model was the only model in CMIP5 to underestimate XCO2 with respect to the observations, and this was by about 20 ppmv
Summary
The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) concluded that since 1950 many of the observed changes in the climate system haveB. The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) concluded that since 1950 many of the observed changes in the climate system have. Gier et al.: Spatially resolved evaluation of Earth system models been unprecedented in the instrument record, confirming an unequivocal warming of the climate system (IPCC, 2013). Increasing emissions of greenhouse gases (GHGs) are the key drivers of anthropogenic climate change. The most important anthropogenic greenhouse gas is carbon dioxide (CO2), with CO2 emissions contributing more than half of the total global radiative forcing in 2011 relative to 1750 (IPCC, 2013). It is important to monitor the longterm changes in atmospheric CO2 concentrations, to understand the sources and sinks of carbon and to provide reliable projections of future CO2 concentrations under various scenarios
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