Intraseasonal SST-precipitation relationship and its spatial variability over the tropical summer monsoon region

Abstract

International audienceThe SST-precipitation relationship in the intraseasonal variability (ISV) over the Asian monsoon region is examined using recent high quality satellite data and simulations from a state of the art coupled model, the climate forecast system version 2 (CFSv2). CFSv2 demonstrates high skill in reproducing the spatial distribution of the observed climatological mean summer monsoon precipitation along with its interannual variability, a task which has been a conundrum for many recent climate coupled models. The model also exhibits reasonable skill in simulating coherent northward propagating monsoon intraseasonal anomalies including SST and precipitation, which are generally consistent with observed ISV characteristics. Results from the observations and the model establish the existence of spatial variability in the atmospheric convective response to SST anomalies, over the Asian monsoon domain on intraseasonal timescales. The response is fast over the Arabian Sea, where precipitation lags SST by ~5 days; whereas it is slow over the Bay of Bengal and South China Sea, with a lag of ~12 days. The intraseasonal SST anomalies result in a similar atmospheric response across the basins, which consists of a destabilization of the bottom of the atmospheric column, as observed from the equivalent potential temperature anomalies near the surface. However, the presence of a relatively strong surface convergence over the Arabian Sea, due to the presence of a strong zonal gradient in SST, which accelerates the upward motion of the moist air, results in a relatively faster response in terms of the local precipitation anomalies over the Arabian Sea than over the Bay of Bengal and South China Sea. With respect to the observations, the ocean-atmosphere coupling is well simulated in the model, though with an overestimation of the intraseasonal SST anomalies, leading to an exaggerated SST-precipitation relationship. A detailed examination points to a systematic bias in the thickness of the mixed layer of the ocean model, which needs to be rectified. A too shallow (deep) mixed layer enhances (suppress) the amplitude of the intraseasonal SST anomalies, thereby amplifying (lessening) the ISV and the active-break phases of the monsoon in the model

Drying of Indian subcontinent by rapid Indian Ocean warming and a weakening land-sea thermal gradient

“…The Indian Ocean and monsoon exhibit a coupled relationship 32,42,43 , and it is also possible that a feedback from a weak monsoon accelerates the warming in the Indian Ocean 22 . Some studies have suggested a role for anthropogenic aerosols in weakening the monsoon circulation during the recent decades 40,[44][45][46][47][48] .…”

“…For the numerical model experiments, we use the standard configuration of a global coupled ocean-atmosphere model, the Climate Forecast System version 2 (CFSv2). The CFSv2 model simulates the mean monsoon and its interannual variability reasonably well, and hence used in this study 42 . The oceanic component has a 0.25-0.5°horizontal resolution, 40 vertical levels and includes an ice model.…”

Intraseasonal Variability in Coupled GCMs: The Roles of Ocean Feedbacks and Model Physics

“…For example, several studies (e.g., Fu et al 2003;Roxy and Tanimoto 2007;Roxy et al 2013) attribute the increased low-level convergence to increased shallow convection, which results from enhanced SST-induced convective instability. Some studies suggest a windevaporation feedback (e.g., Marshall et al 2008) whereby increased shortwave fluxes lead to enhanced surface evaporation and low-level convergence, while others (Hsu and Li 2012) suggest that intraseasonal SST gradients themselves can induce modest low-level convergence anomalies according to the ideas of Lindzen and Nigam (1987) and Back and Bretherton (2009).…”

“…Among the improvements cited were stronger ISO variability in AGCMs with a weak or nonexistent MJO, reduced ISO variability in AGCMs with excessive variability, more realistic phase speed (either faster or slower than in the AGCM) and wavenumber-frequency spectra, more realistic horizontal and vertical structure of the MJO, better eastward propagation (not always accompanied by better northward propagation during boreal summer), and better northward propagation during boreal summer season (not always accompanied by better eastward propagation). Clearly, there are nuanced modelto-model differences in the nature of improvement due to coupling, and a few studies suggest either that the coupling strength is too strong in some models (Wu et al 2008;Bollasina and Nigam 2009) or that the coupled SST variability can be too high (Roxy et al 2013).…”

“…These experiments provide insights into the role of air-sea coupling on tropical intraseasonal variability (ISV), although each study has its limitations. In particular, studies that compare coupled GCM (CGCM) simulations to either observations or AMIP simulations with the same AGCM (e.g., Kemball-Cook et al 2002;Fu et al 2002;Sperber et al 2005;Zhang et al 2006;Wu et al 2008;Bollasina and Nigam 2009;Wang and Seo 2009;Roxy et al 2013;DeMott et al 2011) are complicated by differences in the basic state climate associated with coupled model SST biases.…”