Impacts of Indian Ocean SST biases on the Indian Monsoon: as simulated in a global coupled model

2013 ◽  
Vol 42 (1-2) ◽  
pp. 271-290 ◽  
Author(s):  
Chloé Prodhomme ◽  
Pascal Terray ◽  
Sébastien Masson ◽  
Takeshi Izumo ◽  
Tomoki Tozuka ◽  
...  
2004 ◽  
Vol 24 (2-3) ◽  
pp. 145-168 ◽  
Author(s):  
P. Terray ◽  
E. Guilyardi ◽  
A. S. Fischer ◽  
P. Delecluse

2007 ◽  
Vol 20 (10) ◽  
pp. 2147-2164 ◽  
Author(s):  
Renguang Wu ◽  
Ben P. Kirtman

Abstract The biennial variability is a large component of year-to-year variations in the Indian summer monsoon (ISM). Previous studies have shown that El Niño–Southern Oscillation (ENSO) plays an important role in the biennial variability of the ISM. The present study investigates the role of the Indian Ocean in the biennial transition of the ISM when the Pacific ENSO is absent. The influence of the Indian and Pacific Oceans on the biennial transition between the ISM and the Australian summer monsoon (ASM) is also examined. Controlled numerical experiments with a coupled general circulation model (CGCM) are used to address the above two issues. The CGCM captures the in-phase ISM to ASM transition (i.e., a wet ISM followed by a wet ASM or a dry ISM followed by a dry ASM) and the out-of-phase ASM to ISM transition (i.e., a wet ASM followed by a dry ISM or a dry ASM followed by a wet ISM). These transitions are more frequent than the out-of-phase ISM to ASM transition and the in-phase ASM to ISM transition in the coupled model, consistent with observations. The results of controlled coupled model experiments indicate that both the Indian and Pacific Ocean air–sea coupling are important for properly simulating the biennial transition between the ISM and ASM in the CGCM. The biennial transition of the ISM can occur through local air–sea interactions in the north Indian Ocean when the Pacific ENSO is suppressed. The local sea surface temperature (SST) anomalies induce the Indian monsoon transition through low-level moisture convergence. Surface evaporation anomalies, which are largely controlled by surface wind speed changes, play an important role for SST changes. Different from local air–sea interaction mechanisms proposed in previous studies, the atmospheric feedback is not strong enough to reverse the SST anomalies immediately at the end of the monsoon season. Instead, the reversal of the SST anomalies is accomplished in the spring of the following year, which in turn leads to the Indian monsoon transition.


2011 ◽  
Vol 39 (3-4) ◽  
pp. 729-754 ◽  
Author(s):  
Pascal Terray ◽  
Kakitha Kamala ◽  
Sébastien Masson ◽  
Gurvan Madec ◽  
A. K. Sahai ◽  
...  

2017 ◽  
Vol 30 (20) ◽  
pp. 8159-8178 ◽  
Author(s):  
H. Annamalai ◽  
Bunmei Taguchi ◽  
Julian P. McCreary ◽  
Motoki Nagura ◽  
Toru Miyama

Abstract Forecasting monsoon rainfall using dynamical climate models has met with little success, partly due to models’ inability to represent the monsoon climatological state accurately. In this article the nature and dynamical causes of their biases are investigated. The approach is to analyze errors in multimodel-mean climatological fields determined from CMIP5, and to carry out sensitivity experiments using a coupled model [the Coupled Model for the Earth Simulator (CFES)] that does represent the monsoon realistically. Precipitation errors in the CMIP5 models persist throughout the annual cycle, with positive (negative) errors occurring over the near-equatorial western Indian Ocean (South Asia). Model errors indicate that an easterly wind stress bias Δτ along the equator begins during April–May and peaks during November; the severity of the Δτ is that the Wyrtki jets, eastward-flowing equatorial currents during the intermonsoon seasons (April–May and October–November), are almost eliminated. An erroneous east–west SST gradient (warm west and cold east) develops in June. The structure of the model errors indicates that they arise from Bjerknes feedback in the equatorial Indian Ocean (EIO). Vertically integrated moisture and moist static energy budgets confirm that warm SST bias in the western EIO anchors moist processes that cause the positive precipitation bias there. In CFES sensitivity experiments in which Δτ or warm SST bias over the western EIO is artificially introduced, errors in the EIO are similar to those in the CMIP5 models; moreover, precipitation over South Asia is reduced. An overall implication of these results is that South Asian rainfall errors in CMIP5 models are linked to errors of coupled processes in the western EIO, and in coupled models correct representation of EIO coupled processes (Bjerknes feedback) is a necessary condition for realistic monsoon simulation.


2015 ◽  
Vol 65 (7) ◽  
pp. 1037-1046 ◽  
Author(s):  
Wei Liu ◽  
Jian Lu ◽  
Shang-Ping Xie

Sign in / Sign up

Export Citation Format

Share Document