ORCID Profile
0000-0001-6500-2101
Current Organisation
University of Tokyo
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Publisher: American Meteorological Society
Date: 05-2016
Publisher: American Meteorological Society
Date: 09-2013
Publisher: American Meteorological Society
Date: 08-05-2013
DOI: 10.1175/JCLI-D-12-00429.1
Abstract: The Transpose-Atmospheric Model Intercomparison Project (AMIP) is an international model intercomparison project in which climate models are run in “weather forecast mode.” The Transpose-AMIP II experiment is run alongside phase 5 of the Coupled Model Intercomparison Project (CMIP5) and allows processes operating in climate models to be evaluated, and the origin of climatological biases to be explored, by examining the evolution of the model from a state in which the large-scale dynamics, temperature, and humidity structures are constrained through use of common analyses. The Transpose-AMIP II experimental design is presented. The project requests participants to submit a comprehensive set of diagnostics to enable detailed investigation of the models to be performed. An ex le of the type of analysis that may be undertaken using these diagnostics is illustrated through a study of the development of cloud biases over the Southern Ocean, a region that is problematic for many models. Several models share a climatological bias for too little reflected shortwave radiation from cloud across the region. This is found to mainly occur behind cold fronts and/or on the leading side of transient ridges and to be associated with more stable lower-tropospheric profiles. Investigation of a case study that is typical of the bias and associated meteorological conditions reveals the models to typically simulate cloud that is too optically and physically thin with an inversion that is too low. The evolution of the models within the first few hours suggests that these conditions are particularly sensitive and a positive feedback can develop between the thinning of the cloud layer and boundary layer structure.
Publisher: American Geophysical Union (AGU)
Date: 25-09-2020
DOI: 10.1029/2019RG000678
Abstract: We assess evidence relevant to Earth's equilibrium climate sensitivity per doubling of atmospheric CO 2 , characterized by an effective sensitivity S . This evidence includes feedback process understanding, the historical climate record, and the paleoclimate record. An S value lower than 2 K is difficult to reconcile with any of the three lines of evidence. The amount of cooling during the Last Glacial Maximum provides strong evidence against values of S greater than 4.5 K. Other lines of evidence in combination also show that this is relatively unlikely. We use a Bayesian approach to produce a probability density function (PDF) for S given all the evidence, including tests of robustness to difficult‐to‐quantify uncertainties and different priors. The 66% range is 2.6–3.9 K for our Baseline calculation and remains within 2.3–4.5 K under the robustness tests corresponding 5–95% ranges are 2.3–4.7 K, bounded by 2.0–5.7 K (although such high‐confidence ranges should be regarded more cautiously). This indicates a stronger constraint on S than reported in past assessments, by lifting the low end of the range. This narrowing occurs because the three lines of evidence agree and are judged to be largely independent and because of greater confidence in understanding feedback processes and in combining evidence. We identify promising avenues for further narrowing the range in S , in particular using comprehensive models and process understanding to address limitations in the traditional forcing‐feedback paradigm for interpreting past changes.
Publisher: IOP Publishing
Date: 08-2014
Publisher: Springer Science and Business Media LLC
Date: 17-08-2015
DOI: 10.1038/NCLIMATE2743
Publisher: The Royal Society
Date: 13-11-2015
Abstract: We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the in idual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed.
Publisher: Springer Science and Business Media LLC
Date: 31-03-2015
DOI: 10.1038/NGEO2398
Publisher: Meteorological Society of Japan
Date: 2013
Publisher: Meteorological Society of Japan
Date: 2013
No related grants have been discovered for Masahiro Watanabe.