Published in

Chinese Academy of Sciences, Institute of Atmospheric Physics, Atmospheric and Oceanic Science Letters, 5(7), p. 411-416

DOI: 10.1080/16742834.2014.11447199

Links

Tools

Export citation

Search in Google Scholar

The Role of the Aerosol Indirect Effect in the Northern Indian Ocean Warming Simulated by CMIP5 Models

Journal article published in 2014 by Hu Ning, Li Li-Juan ORCID, Li Lijuan, Wang Bin
This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

The northern Indian Ocean (NIO) experienced a decadal-scale persistent warming from 1950 to 2000, which has influenced both regional and global climate. Because the NIO is a region susceptible to aerosols emission changes, and there are still large uncertainties in the representation of the aerosol indirect effect (AIE) in CMIP5(Coupled Model Intercomparison Project Phase 5) models, it is necessary to investigate the role of the AIE in the NIO warming simulated by these models. In this study, the authors select seven CMIP5 models with both the aerosol direct and indirect effects to investigate their performance in simulating the basin-wide decadal-scale NIO warming. The results show that the decreasing trend of the downwelling shortwave flux (FSDS) at the surface has the major damping effect on the SST increasing trend, which counteracts the warming effect of greenhouse gases (GHGs). The FSDS decreasing trend is mostly contributed by the decreasing trend of cloudy-sky surface downwelling shortwave flux (FSDSCL), a metric used to measure the strength of the AIE, and partly by the clear-sky surface downwelling shortwave flux (FSDSC). Models with a relatively weaker AIE can simulate well the SST increasing trend, as compared to observation. In contrast, models with a relatively stronger AIE produce a much smaller magnitude of the increasing trend, indicating that the strength of the AIE in these models may be overestimated in the NIO.