担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：npj Climate and Atmospheric Science  

Radiative forcing is an essential metric for accurate climate prediction. Clouds are a well-known source of uncertainty, but the radiative effects of precipitation (REP) are poorly understood and excluded from most general circulation models (GCMs). This is because conventional GCMs treat precipitation diagnostically, and thus, are transparent to shortwave and longwave radiation. In this study, we investigated the REP at global and regional scales by employing three sub-models incorporating (1) diagnostic precipitation, (2) prognostic precipitation without REP, and (3) prognostic precipitation with REP. We found that REP alters not only the local thermodynamic profile but also the remote precipitation rate and distribution through changes in atmospheric circulation. The polar surface temperature increases by more than 1 K in the winter when considering REP. The 34 CMIP6 models show systematic differences in Arctic amplification depending on REP, emphasising that GCMs should include REP to improve confidence in simulating atmosphere-ocean-cryosphere interactions.

DOI： 10.1038/s41612-024-00684-4

Scopus

その他リンク： https://www.nature.com/articles/s41612-024-00684-4

担当区分：最終著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Atmospheric Chemistry and Physics  

Process-oriented observational constraints for the anthropogenic effective radiative forcing due to aerosol-cloud interactions (ERFaci) are highly desirable because the uncertainty associated with ERFaci poses a significant challenge to climate prediction. The contoured frequency by optical depth diagram (CFODD) analysis supports the evaluation of model representation of cloud liquid-to-rain conversion processes because the slope of a CFODD, generated from joint MODerate Resolution Imaging Spectroradiometer (MODIS)-CloudSat cloud retrievals, provides an estimate of cloud droplet collection efficiency in single-layer warm liquid clouds. Here, we present an updated CFODD analysis as an observational constraint on the ERFaci due to warm rain processes and apply it to the U.S. Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2). A series of sensitivity experiments shows that E3SMv2 droplet collection efficiencies and ERFaci are highly sensitive to autoconversion, i.e., the rate of mass transfer from cloud liquid to rain, yielding a strong correlation between the CFODD slope and the shortwave component of ERFaci (ERFaciSW; Pearson's RCombining double low line-0.91). E3SMv2's CFODD slope (0.20g±g0.04) is in agreement with observations (0.20g±g0.03). The strong sensitivity of ERFaciSW to the CFODD slope provides a useful constraint on highly uncertain warm rain processes, whereby ERFaciSW, constrained by MODIS-CloudSat, is estimated by calculating the intercept of the linear association between the ERFaciSW and the CFODD slopes, using the MODIS-CloudSat CFODD slope as a reference.

DOI： 10.5194/acp-24-5287-2024

Scopus

担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Scientific Reports  

There is little consensus among global climate models (CGMs) regarding the response of lightning flash rates to past and future climate change, largely due to graupel not being included in models. Here a two-moment prognostic graupel scheme was incorporated into the MIROC6 GCM and applied in three experiments involving pre-industrial aerosol, present-day, and future warming simulations. The new microphysics scheme performed well in reproducing global distributions of graupel, convective available potential energy, and lightning flash rate against satellite retrievals and reanalysis datasets. The global mean lightning rate increased by 7.1% from the pre-industrial period to the present day, which was attributed to increased graupel occurrence. The impact of future warming on lightning activity was more evident, with the rate increasing by 18.4%K-1 through synergistic contributions of destabilization and increased graupel. In the Arctic, the lightning rate depends strongly on the seasonality of graupel, emphasizing the need to incorporate graupel into GCMs for more accurate climate prediction.

DOI： 10.1038/s41598-024-54544-5

Scopus

PubMed

担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：論文集(書籍)内論文  

DOI： 10.1007/978-981-15-2527-8_35-3

DOI： 10.1007/978-981-15-2760-9_35

掲載種別：研究論文（学術雑誌）   出版者・発行元：Frontiers in Climate  

The Clouds and the Earth's Radiant Energy System (CERES) project has now produced over two decades of observed data on the Earth's Energy Imbalance (EEI) and has revealed substantive trends in both the reflected shortwave and outgoing longwave top-of-atmosphere radiation components. Available climate model simulations suggest that these trends are incompatible with purely internal variability, but that the full magnitude and breakdown of the trends are outside of the model ranges. Unfortunately, the Coupled Model Intercomparison Project (Phase 6) (CMIP6) protocol only uses observed forcings to 2014 (and Shared Socioeconomic Pathways (SSP) projections thereafter), and furthermore, many of the ‘observed' drivers have been updated substantially since the CMIP6 inputs were defined. Most notably, the sea surface temperature (SST) estimates have been revised and now show up to 50% greater trends since 1979, particularly in the southern hemisphere. Additionally, estimates of short-lived aerosol and gas-phase emissions have been substantially updated. These revisions will likely have material impacts on the model-simulated EEI. We therefore propose a new, relatively low-cost, model intercomparison, CERESMIP, that would target the CERES period (2000-present), with updated forcings to at least the end of 2021. The focus will be on atmosphere-only simulations, using updated SST, forcings and emissions from 1990 to 2021. The key metrics of interest will be the EEI and atmospheric feedbacks, and so the analysis will benefit from output from satellite cloud observation simulators. The Tier 1 request would consist only of an ensemble of AMIP-style simulations, while the Tier 2 request would encompass uncertainties in the applied forcing, atmospheric composition, single and all-but-one forcing responses. We present some preliminary results and invite participation from a wide group of models.

DOI： 10.3389/fclim.2023.1202161

Scopus

開催年月日： 2020年7月

記述言語：英語   会議種別：口頭発表（一般）  

開催地：Online (Zoom)   国名：日本国  

開催年月日： 2020年1月

記述言語：英語   会議種別：口頭発表（一般）  

開催地：Boston   国名：アメリカ合衆国  

開催年月日： 2016年10月

記述言語：日本語   会議種別：口頭発表（一般）  

開催地：名古屋大学   国名：日本国  

開催年月日： 2019年12月

記述言語：英語   会議種別：口頭発表（一般）  

国名：アメリカ合衆国  

開催年月日： 2019年11月

記述言語：英語   会議種別：口頭発表（一般）  

国名：日本国  

出版者・発行元：Frontiers in Climate  

In the published article, there was an error in affiliation 17. Instead of “Commenwealth Scientific and Industrial Research Organisation (CSIRO), Environment, Aspendale, VIC, Australia”, it should be “Commonwealth Scientific and Industrial Research Organisation (CSIRO), Environment, Aspendale, VIC, Australia”. Additionally, author David Paynter had the incorrect affiliation specified, rather than 4 “NASA Langley Research Center”, it is 5 “NOAA Geophysical Fluid Dynamics Laboratory”. In the published article, there was an error in the Funding statement. The support of the U.S. Department of Energy, Office of Science was omitted and a part of the funding statement was incorrectly included in the Acknowledgments. The correct Funding and Acknowledgments statements appear below. Climate modeling at GISS was supported by the NASA Modeling, Analysis and Prediction program and simulations are made possible by the NASA Center for Climate Simulation (NCCS). We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinates and promotes CMIP activities. TA was supported by both the Met Office Hadley Centre Climate Programme funded by BEIS, and the European Union's Horizon 2020 research and innovation programme under grant agreement 820829. The work of PD was performed under the auspices of the U.S. Department of Energy, Office of Science, Earth, and Environmental Systems Sciences Division, Regional and Global Model Analysis Program by Lawrence Livermore National Laboratory (LLNL) under Contract DE-AC52-07NA27344. LLNL Release Number: LLNL-JRNL-849403. BM acknowledges support by the U.S. Department of Energy under Award Number DE-SC0022070 and National Science Foundation (NSF) IA 1947282; the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under Cooperative Agreement No. 1852977; and the National Oceanic and Atmospheric Administration under award NA20OAR4310392. TM was supported by the Japan Society for the Promotion of Science KAKENHI (Grant JP19H05669), the Advanced Studies of Climate Change Projection (SENTAN) of the Ministry of Education, Culture, Sports, Science, and Technology (Grant JPMXD0722680395), the Environment Research and Technology Development Fund (Grant JPMEERF21S12004) of the Environmental Restoration and Conservation Agency Provided by the Ministry of Environment of Japan, and the JST FOREST Program (Grant JPMJFR206Y). We thank Leo Donner, Vaishali Naik, Fabien Paulot, and two reviewers for comments on the draft paper. The authors apologize for these errors and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

DOI： 10.3389/fclim.2023.1298599

Scopus

その他リンク： http://doi.org/10.5281/zenodo.1442468

その他リンク： http://doi.org/10.5281/zenodo.3370823

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