Suchergebnisse

We examine the weakening of the Atlantic Meridional Overturning Circulation (AMOC) in response to increasing CO2 at different horizontal resolutions in a state-of-the-art climate model and in a small ensemble of models with differing resolutions. There is a strong influence of the ocean mean state on the AMOC weakening: models with a more saline western subpolar gyre have a greater formation of deep water there. This makes the AMOC more susceptible to weakening from an increase in CO2 since weakening ocean heat transports weaken the contrast between ocean and atmospheric temperatures and hence weaken the buoyancy loss. In models with a greater proportion of deep water formation further north (in the Greenland-Iceland-Norwegian basin), deep-water formation can be maintained by shifting further north to where there is a greater ocean-atmosphere temperature contrast. We show that ocean horizontal resolution can have an impact on the mean state, and hence AMOC weakening. In the models examined, those with higher resolutions tend to have a more westerly location of the North Atlantic Current and stronger subpolar gyre. This likely leads to a greater impact of the warm, saline subtropical Atlantic waters on the western subpolar gyre resulting in greater dense water formation there. Although there is some improvement of the higher resolution models over the lower resolution models in terms of the mean state, both still have biases and it is not clear which biases are the most important for influencing the AMOC strength and response to increasing CO2. ; LJ, MR, DI, TK, VM, CR, YR-R were funded by the PRIMAVERA project, funded by the European Union's Horizon 2020 programme under grant agreement 641727. LJ, HH, MR, RW were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra (GA01101). We wish to thank two anonymous reviewers for their comments which improved this manuscript. ; Peer Reviewed ; Postprint (published version)

Global and regional ocean and sea ice reanalysis products (ORAs) are increasingly used in polar research, but their quality remains to be systematically assessed. To address this, the Polar ORA Intercomparison Project (Polar ORA-IP) has been established following on from the ORA-IP project. Several aspects of ten selected ORAs in the Arctic and Antarctic were addressed by concentrating on comparing their mean states in terms of snow, sea ice, ocean transports and hydrography. Most polar diagnostics were carried out for the first time in such an extensive set of ORAs. For the multi-ORA mean state, we found that deviations from observations were typically smaller than individual ORA anomalies, often attributed to offsetting biases of individual ORAs. The ORA ensemble mean therefore appears to be a useful product and while knowing its main deficiencies and recognising its restrictions, it can be used to gain useful information on the physical state of the polar marine environment. ; We acknowledge Dr. Benjamin Rabe and the two anonymous reviewers for their comments that significantly improved the manuscript. EU-COST EOS-1402 Ocean Synthesis action is acknowledged for their support, in particular to assist the organisation of the Polar ORA-IP meetings, both physical and virtual, which were crucial for the study. Work of Uotila was supported by the Finnish Academy (Grants 264358 and 283034) and by the EU MCSA grant 707262-LAWINE. Chevallier, Fučkar, Haines and Massonnet have received funding from the European Union's Horizon 2020 Research and Innovation programme through Grant agreement No. 727862 APPLICATE. Fučkar was a Juan de la Cierva-incorporacion fellow supported by the Spanish government. Goosse is a research director and Massonnet a post-doctoral researcher with the FRS/FNRS, Belgium. The ORA and MMM data used in this study are provided by Hamburg University on the ORA-IP web-site at https ://icdc.cen.uni-hambu rg.de/1/daten /reana lysis -ocean /oraip .html. ; Peer Reviewed ; Postprint (published version)

Global and regional ocean and sea ice reanalysis products (ORAs) are increasingly used in polar research, but their quality remains to be systematically assessed. To address this, the Polar ORA Intercomparison Project (Polar ORA-IP) has been established following on from the ORA-IP project. Several aspects of ten selected ORAs in the Arctic and Antarctic were addressed by concentrating on comparing their mean states in terms of snow, sea ice, ocean transports and hydrography. Most polar diagnostics were carried out for the first time in such an extensive set of ORAs. For the multi-ORA mean state, we found that deviations from observations were typically smaller than individual ORA anomalies, often attributed to offsetting biases of individual ORAs. The ORA ensemble mean therefore appears to be a useful product and while knowing its main deficiencies and recognising its restrictions, it can be used to gain useful information on the physical state of the polar marine environment. ; We acknowledge Dr. Benjamin Rabe and the two anonymous reviewers for their comments that significantly improved the manuscript. EU-COST EOS-1402 Ocean Synthesis action is acknowledged for their support, in particular to assist the organisation of the Polar ORA-IP meetings, both physical and virtual, which were crucial for the study. Work of Uotila was supported by the Finnish Academy (Grants 264358 and 283034) and by the EU MCSA grant 707262-LAWINE. Chevallier, Fučkar, Haines and Massonnet have received funding from the European Union's Horizon 2020 Research and Innovation programme through Grant agreement No. 727862 APPLICATE. Fučkar was a Juan de la Cierva-incorporacion fellow supported by the Spanish government. Goosse is a research director and Massonnet a post-doctoral researcher with the FRS/FNRS, Belgium. The ORA and MMM data used in this study are provided by Hamburg University on the ORA-IP web-site at https ://icdc.cen.uni-hambu rg.de/1/daten /reana lysis -ocean /oraip .html. ; Peer Reviewed ; Postprint (published version)

We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework. ; This research has been supported by the Integrated Research Program for Advancing Climate Models (TOUGOU) of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (grant nos. JPMXD0717935457 and JPMXD0717935561), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (grant no. 274762653), the Helmholtz Climate Initiative REKLIM (Regional Climate Change) and European Union's Horizon 2020 Research & Innovation program (grant nos. 727862 and 800154), the Research Council of Norway (EVA (grant no. 229771) and INES (grant no. 270061)), the US National Science Foundation (NSF) (grant no. 1852977), the National Natural Science Foundation of China (grant nos. 41931183 and 41976026), NOAA's Science Collaboration Program and administered by UCAR's Cooperative Programs for the Advancement of Earth System Science (CPAESS) (grant nos. NA16NWS4620043 and NA18NWS4620043B), and NOAA (grant no. NA18OAR4320123). ; Peer Reviewed ; Postprint (published version)