Investigation of the Robust El Nino-like Tropical Pacific Sea Surface Temperature Response to Global Warming in CMIP5 Models

碩士 === 國立臺灣大學 === 大氣科學研究所 === 104 === Sea surface temperature anomaly (SSTA) in tropical Pacific region has been suggested to account for some significant climate changes, for instance, the weakening of Walker circulation, the expansion of the Hadley cell edges and subtropical deserts, and the shif...

Full description

Bibliographic Details
Main Authors: Hung-Yi Tseng, 曾弘毅
Other Authors: 黃彥婷
Format: Others
Language:en_US
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/24009581248000894162
Description
Summary:碩士 === 國立臺灣大學 === 大氣科學研究所 === 104 === Sea surface temperature anomaly (SSTA) in tropical Pacific region has been suggested to account for some significant climate changes, for instance, the weakening of Walker circulation, the expansion of the Hadley cell edges and subtropical deserts, and the shift of tropical rainband. Under global warming, most global climate models (GCMs) project an El Nino-like SST warming pattern, with enhanced warming in equatorial region, and a reduced zonal SST gradient along the equator. However, some previous studies have questioned the reliability of these robust responses across GCMs, since most GCMs experience difficulties simulating the observed climatology and ENSO variability in the tropical Pacific. The goal of this thesis is to evaluate the confidence of such El Nino-like SSTA pattern in tropical Pacific region among most GCMs through understanding its formation mechanisms. We demonstrate that the reduced evaporative damping related with the structure of climatological evaporation and the enhanced greenhouse effect related with increasing water vapor over the equatorial central Pacific, are the two major contributors to the SSTA pattern. Furthermore, it is suggested that (1) the biases of present day climatology in GCM simulations may lead to an error of future SST projection, and (2) the global warming scenario and El Nino events share some common atmospheric climate feedbacks, despite the distinct triggering mechanisms. The results set the foundations to evaluate our confidence of the projected SSTA in each GCM by performing a process-based comparison with the observational and reanalysis data.