Abstract
Abstract. The fidelity of the simulated Indian summer monsoon is analysed in the UK Met Office Unified Model Global Ocean Mixed Layer configuration (MetUM-GOML2.0) in terms of its boreal summer mean state and propagation of the boreal summer intraseasonal oscillation (BSISO). The model produces substantial biases in mean June–September precipitation, especially over India, in common with other MetUM configurations. Using a correction technique to constrain the mean seasonal cycle of ocean temperature and salinity, the effects of regional air–sea coupling and atmospheric horizontal resolution are investigated. Introducing coupling in the Indian Ocean degrades the atmospheric basic state compared with prescribing the observed seasonal cycle of sea surface temperature (SST). This degradation of the mean state is attributable to small errors (±0.5 ∘C) in mean SST. Coupling slightly improves some aspects of the simulation of northward BSISO propagation over the Indian Ocean, Bay of Bengal, and India, but degrades others. Increasing resolution from 200 to 90 km grid spacing (approximate value at the Equator) improves the atmospheric mean state, but increasing resolution again to 40 km offers no substantial improvement. The improvement to intraseasonal propagation at finer resolution is similar to that due to coupling.
Highlights
The Indian summer monsoon (ISM) is one of the most significant features of the tropical climate, with boreal summer (June to September; JJAS) rains bringing around 80 % of the annual precipitation over much of India
Over the Bay of Bengal (BoB) there is a significant deficit in the west, but rainfall is close to the Global Precipitation Climatology Project (GPCP) value or even slightly higher in the east
This study has evaluated the simulation of the ISM in Met Office Unified Model (MetUM)-GOML2.0, which uses a mixed layer ocean coupled to the MetUM atmosphere, with atmosphere and ocean at the same resolution
Summary
The Indian summer monsoon (ISM) is one of the most significant features of the tropical climate, with boreal summer (June to September; JJAS) rains bringing around 80 % of the annual precipitation over much of India. The total summer rainfall over the monsoon region is remarkably consistent year to year, with interannual variability (IAV) of only around 10 % of the mean (Turner and Annamalai, 2012), but the most extreme years still have significant impacts on Indian foodgrain production and gross domestic product, especially in years of rainfall deficit (Gadgil and Gadgil, 2006). Further variations include IAV in the onset and withdrawal dates of the monsoon and intraseasonal active-break cycles within a monsoon season. Accurate forecasting of such IAV and intraseasonal variability (ISV) is of crucial socio-economic importance to the region
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