Ashrit R.,Institutional Area II |
Sharma K.,Institutional Area II |
Dube A.,Institutional Area II |
Iyengar G.,Institutional Area II |
And 2 more authors.
Mausam | Year: 2015
The daily rainfall over India during the monsoon season (June-September) is governed by the interplay of the large-scale, synoptic and mesoscale disturbances, many of which are sporadic rainfall spells and extremely intense. These spells often bring extreme amounts of rain over only a few days, which can have sizable impacts on the estimated seasonal mean rainfall. The record rainfall of over 100 cm/day in Mumbai on 26th July, 2005 is an outlier/extreme at over 20 standard deviations for activity of typical June-September average rainfall of 18 mm/day with daily standard deviation of 28 mm/day. While such outliers are not uncommon in India during the monsoon season, they pose serious challenge to even the high resolution forecast models. The statistics of these outlier events are examined both for observed and model-forecast daily rainfall for recent seven monsoon seasons (2007-2013). Some of the extreme one day rainfall events (over the plains of eastern India) contribute up to 30% of the seasonal total rain. This study presents rainfall verification over India using traditional verification scores such as Probability of Detection (POD), Equitable Threat Score (ETH), Critical Success Index (CSI) etc. for various categories. Further, the statistical challenges associated with the verification of the extreme events are discussed. A brief review of the new methods suggested in literature for verification of the extreme events, such as Odds Ratio (OR), Extreme Dependency Score (EDS), Symmetric Extreme Dependency Score (SEDS), Extremal Dependence Index (EDI) and Symmetric EDI (SEDI) is provided with example application to Indian context. © 2015, India Meteorological Department. All rights reserved.
Ashrit R.,Institutional Area II |
Mohandas S.,Institutional Area II
Journal of Earth System Science | Year: 2010
There have been very few mesoscale modelling studies of the Indian monsoon, with focus on the verification and intercomparison of the operational real time forecasts. With the exception of Das et al (2008), most of the studies in the literature are either the case studies of tropical cyclones and thunderstorms or the sensitivity studies involving physical parameterization or climate simulation studies. Almost all the studies are based on either National Center for Environmental Prediction (NCEP), USA, final analysis fields (NCEP FNL) or the reanalysis data used as initial and lateral boundary conditions for driving the mesoscale model. Here we present a mesoscale model forecast verification and intercomparison study over India involving three mesoscale models: (i) the Weather Research and Forecast (WRF) model developed at the National Center for Atmospheric Research (NCAR), USA, (ii) the MM5 model developed by NCAR, and (iii) the Eta model of the NCEP, USA. The analysis is carried out for the monsoon season, June to September 2008. This study is unique since it is based entirely on the real time global model forecasts of the National Centre for Medium Range Weather Forecasting (NCMRWF) T254 global analysis and forecast system. Based on the evaluation and intercomparison of the mesoscale model forecasts, we recommend the best model for operational real-time forecasts over the Indian region. Although the forecast mean 850 hPa circulation shows realistic monsoon flow and the monsoon trough, the systematic errors over the Arabian Sea indicate an easterly bias to the north (of mean flow) and westerly bias to the south (of mean flow). This suggests that the forecasts feature a southward shift in the monsoon current. The systematic error in the 850 hPa temperature indicates that largely the WRF model forecasts feature warm bias and the MM5 model forecasts feature cold bias. Features common to all the three models include warm bias over northwest India and cold bias over southeast peninsula. The 850 hPa specific humidity forecast errors clearly show that the Eta model features dry bias mostly over the sea, while MM5 features moist bias over large part of domain. The RMSE computed at different levels clearly establish that WRF model forecasts feature least errors in the predicted free atmospheric fields. Detailed rainfall forecast verification further establishes that the WRF model forecast rainfall skill remains more or less same in day-2 and day-3 as in day-1, while the forecast skill in the MM5 and Eta models, deteriorates in day-2 and day-3 forecasts. © Indian Academy of Sciences.