Abstract
AbstractThis study analyzes the prediction of Indian monsoon low pressure systems (LPSs) on an extended time scale of 15 days by models of the Subseasonal-to-Seasonal (S2S) prediction project. Using a feature-tracking algorithm, LPSs are identified in 11 S2S models during a common reforecast period of June–September 1999–2010, and then compared with 290 and 281 LPSs tracked in ERA-Interim and MERRA-2 reanalysis datasets. The results show that all S2S models underestimate the frequency of LPSs. They are able to represent transits, genesis, and lysis of LPSs; however, large biases are observed in the Australian Bureau of Meteorology, China Meteorological Administration (CMA), and Hydrometeorological Centre of Russia (HMCR) models. The CMA model exhibits large LPS track position error and the intensity of LPSs is overestimated (underestimated) by most models when verified against ERA-Interim (MERRA-2). The European Centre for Medium-Range Weather Forecasts and Met Office models have the best ensemble spread–error relationship for the track position and intensity, whereas the HMCR model has the worst. Most S2S models are underdispersive—more so for the intensity than the position. We find the influence of errors in the LPS simulation on the pattern of total precipitation biases in all S2S models. In most models, precipitation biases increase with forecast lead time over most of the monsoon core zone. These results demonstrate the potential for S2S models at simulating LPSs, thereby giving the possibility of improved disaster preparedness and water resources planning.
Highlights
Monsoon low pressure systems (LPSs) are important synopticscale cyclonic disturbances that are embedded in the South Asian monsoon circulation
The multimodel mean of Coupled Model Intercomparison Project-5 (CMIP5) and CMIP3 models exhibit wet biases over eastern parts of the Arabian Sea during the summer season (Sperber et al 2013); similar wet biases are found in the Japan Meteorological Agency (JMA), Environment and Climate Change Canada (ECCC), and China Meteorological Administration (CMA) (ISAC-CNR and Korea Meteorological Administration (KMA)) models in this study
We have analyzed the prediction of Indian monsoon low pressure systems (LPSs) by 11 models of the Subseasonal-to-Seasonal (S2S) prediction project (Vitart et al 2017)
Summary
Monsoon low pressure systems (LPSs) are important synopticscale cyclonic disturbances that are embedded in the South Asian monsoon circulation These systems, which have a life-span of 3–5 days, most frequently form over the head of the Bay of Bengal and adjoining land area, from where they propagate in a west-northwest direction toward India (Daggupaty and Sikka 1977; Godbole 1977; Boos et al 2015; Hunt and Parker 2016). Hodges and Emerton (2015) investigated the prediction of TCs in the Northern Hemisphere in the ECMWF ensemble and deterministic prediction systems during May–October 2008–12 They inferred that initial periods during forecasts had smaller error growth, and the location of TCs was more predictable than the intensity. D How statistically reliable are S2S models at predicting LPSs? d How do forecast lead time and the presence of LPSs influence the pattern of precipitation errors in S2S models?
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