The lead Principal Investigator (PI) has successfully developed a new analysis framework to diagnose climate feedbacks for global warming studies. The new framework, referred to as the climate feedback response analysis method (CFRAM), differs from existing approaches in that it allows one to determine linearly the partial temperature changes due to external forcing and due to individual feedback processes or agents such as clouds, water vapor, and vertical and horizontal energy transport. These partial temperature changes are addable and their sum gives the total temperature change. The PIs will apply the CFRAM for analyzing and understanding spatial warming patterns of the surface and the atmospheric temperatures in response to anthropogenic greenhouse gases using outputs from an idealized global climate model (GCM) and the fully coupled National Center for Atmospheric Research (NCAR) Community Climate System Model 3 (CCSM3) climate simulations, as well as the existing Intergovernmental Panel on Climate Change (IPCC)-Assessment Report 4 (AR4) GCM climate simulations. The PIs will also compare the new feedback analysis with an existing technique. This will help to shed light on the sources of the large inter-model spread of climate sensitivity derived from IPCC-AR4 climate simulations. Coupled model integrations using CCSM3 with an improved convective parameterization will also be analyzed to explore the dependency of climate feedbacks and sensitivities to model physical parameterizations. The main objectives of the research are:
1) To explore the feasibility of applying the CFRAM to isolating individual contributions to the total temperature change from the external forcing and various physical feedback processes in the context of coupled GCMs with full physical parameterizations.
2) To shed light on the dynamical/thermodynamic origins of the warming pattern asymmetries between (a) surface and atmospheric temperatures, (b) low and high latitudes, and (c) land and ocean.
3) To identify the contributions to the inter-model spread of the global warming and its spatial pattern due to the inter-model spreads of the 3-D structure of the external forcing, water vapor feedback, cloud feedback, surface albedo feedback, and surface turbulent sensible and latent heat flux feedbacks using the outputs from IPCC-AR4 climate simulations.
The research aims to understand fundamental issues in global climate warming due to increases in anthropogenic greenhouse gases and feedback processes in the climate system. Broader impacts of this research include better quantification of the role of each feedback process in climate change and a more quantitative understanding of global warming spatial patterns. Graduate students and postdoctoral researchers will also be educated and trained in climate change science.
Trained two Ph.D students and one M.S. graduate student. Wrote 16 peer-reviewed journal articles List of total publications that have acknowledged this NSF grant (* the publications that are directly related to the core objectives of the proposed study, total of 10 of them) *Lu, J-H, and M. Cai, 2009: Seasonality of Polar Surface Warming Amplification in Climate Simulations. Geophys. Res. Lett., 36, L16704,doi:10.1029/2009GL040133. *Lu, J-H, and M. Cai, 2010: Quantifying Contributions to Polar Warming Amplification in a Coupled General Circulation Model. Clim Dyn. DOI 10.1007/s00382-009-0673-x. *Cai, M., and K-K Tung, 2012: Robustness of Dynamical Feedbacks from Radiative Forcing: 2% Solar versus 2xCO2 Experiments in an Idealized GCM. J. Atmos. Sci., 69, 2256-2271. DOI: 10.1175/JAS-D-11-0117.1. *Park, T-W, Yi Deng, and M. Cai, 2012: Feedback Attribution of the El Niño-Southern Oscillation-related Atmospheric and Surface Temperature Anomalies. J. Geophy. R, 117, D23101, DOI:10.1029/2012JD018468. *Deng, Yi, T-W Park, and M. Cai, 2013: Radiative and Dynamical Forcing of the Surface and Atmospheric Temperature Anomalies Associated with the Northern Annular Mode. J. Climate. DOI: 10.1175/JCLI-D-12-00431.1 Cai, M., and Bohua Huang, 2013: A New Look at the Physics of Rossby Waves: A Mechanical-Coriolis Oscillation. J. Atmos. Sci., DOI:10.1175/JAS-D-12-094.1. Cai, M., and Bohua Huang, 2013: A Dissection of Energetics of the Geostrophic Flow: Reconciliation of Rossby Wave Energy. J. Atmos. Sci., DOI: 10.1175/JAS-D-12-0249.1. Zhang, G., M. Cai, and A. Hu, 2013: Energy Consumption and the Unexplained Winter Warming over Northern Asia and North America. Nature Climate Change. DOI: 10.1038/nclimate1803. *Taylor, P. C., M. Cai, A. Hu, J. Meehl, W. Washington, and G. J. Zhang, 2013: A Decomposition of Feedback Contributions to Polar Warming Amplification. J. Climate. DOI: 10.1175/JCLI-D-12-00696.1. 10. *Song, X., G. J. Zhang, and M. Cai, 2013: Quantifying contributions of climate feedbacks to tropospheric warming in the NCAR CCSM3.0., Clim. Dyn., DOI: 10.1007/s00382-013-1805-x. 11. Zhang, Q., C-S Shin, H. van den Dool, and M. Cai, 2013: CFSv2 Prediction Skill of Stratospheric Anomalies. Clim. Dyn. , DOI:10.1007/s00382-013-1907-5. 12. Cai, M., and C-S Shin, 2014: A Total Flow Perspective of Atmospheric Mass and Angular Momentum Circulations: Boreal Winter Mean State. J. Atmos. Sci., DOI:10.1175/JAS-D-13-0175.1. 13. *Sejas, S., M. Cai, A. Hu, J. Meehl, W. Washington, and P. C. Taylor, 2013: Individual Feedback Contributions to the Seasonality of Surface Warming. J. Climate. DOI:10.1175/JCLI-D-13-00658.1. 14. Cai, M., C. Barton, C-S Shin, and J. M. Chagnon, 2014: The Continuous Mutual Evolution of Equatorial Waves and the Quasi-Biennial Oscillation of Zonal Flow in the Equatorial Stratosphere. J. Atmos. Sci., DOI: 10.1175/JAS-D-14-0032.1. 15. *Song, XL, G. J. Zhang, and M. Cai, 2014: Charactering the climate feedback pattern in the NCAR CCSM3-SOM using hourly data. J. Climate, DOI:10.1175/JCLI-D-13-00567.1. 16. *Sejas, S., O. S. Albert, M. Cai, and Y. Deng, 2014: Feedback Attribution of the Land/Sea Warming Contrast in NCAR CCSM4 Global Warming Simulations. Geophys. Res. Lett. (submitted).
