Francis and Gadgil1 have made many interesting correlations of meteorological variables and events, and have proposed

that unfavourable SST (sea surface temperature)gradient between the Bay of Bengal and EEIO (eastern equatorial

Indian ocean) led to the large deficit of monsoon rainfall in 2009. In their own words, ‘. . . a drought was not expected from the predictions generated by the leading centres in the world using complex models of the coupled ocean–atmosphere system. Models had generally predicted above average rainfall for June–July–August (JJA) over most of the Indian region, which is almost the opposite to what was observed’

Sinha, UN

English

Francis and Gadgil1 have made many interesting correlations of meteorological variables and events, and have proposed\ud
that unfavourable SST (sea surface temperature)gradient between the Bay of Bengal and EEIO (eastern equatorial\ud
Indian ocean) led to the large deficit of monsoon rainfall in 2009. In their own words, ‘. . . a drought was not expected from the predictions generated by the leading centres in the world using complex models of the coupled ocean–atmosphere system. Models had generally predicted above average rainfall for June–July–August (JJA) over most of the Indian region, which is almost the opposite to what was observed’

NAL-IR

CORRESPONDENCE  CURRENT SCIENCE, VOL. 98, NO. 2, 25 JANUARY 2010 134 On the predictive behaviour of the Indian monsoon in June 2009  Francis and Gadgil1 have made many in-teresting correlations of meteorological variables and events, and have proposed that unfavourable SST (sea surface tem-perature) gradient between the Bay of Bengal and EEIO (eastern equatorial  Indian ocean) led to the large deficit of monsoon rainfall in 2009. In their own words, ‘. . . a drought was not expected from the predictions generated by the leading centres in the world using com-plex models of the coupled ocean–atmosphere system. Models had gener-ally predicted above average rainfall for June–July–August (JJA) over most of the Indian region, which is almost the oppo-site to what was observed’.  The Flosolver Laboratory at National Aerospace Laboratories (NAL) has over the years developed various versions of the software called ‘Varsha’ for forecast-ing weather over the globe. The code has a special boundary layer parameteriza-tion scheme for the tropics and a refined scheme for handling the moist adiabat. During the monsoon season, a rainfall forecast for each month has been made in the first week of the month since 2006. Since 2007, these forecasts have been routinely sent to the Director General of Meteorology (DGM) of the India Mete-orological Department (IMD).  For June 2009, a preliminary Varsha forecast of all-India rainfall was sent to DGM on 29 May 2009 and an updated forecast (promised in this letter of 29 May) was sent on 8 June 2009. The fig-ures sent are reproduced here, as Figures 1 and 2 respectively. There can be no doubt that the Varsha clearly forecast a substantial rainfall deficit. Figure 3 com-pares IMD-reported rainfall2 for June 2009 with the five-day moving average of the Varsha forecast. The preliminary forecast clearly indicates a June rainfall well below the long-term mean. The up-dated forecast for the same month shows a 51% deficiency, and this prediction was clearly stated and highlighted in the correspondence with DGM of IMD. It is seen that the trend of observed rainfall is     Figure 1. Preliminary Varsha prediction for June 2009.     Figure 2. Updated Varsha prediction for June 2009.   Figure 3. Comparison of Varsha rainfall forecast and IMD  Observation, June 2009.    Figure 4. Comparison of Varsha forecast and IMD observation for June 1992. CORRESPONDENCE  CURRENT SCIENCE, VOL. 98, NO. 2, 25 JANUARY 2010 135  Figure 5. Comparison of Varsha forecast and IMD observation for June 1995.    Figure 6. Comparison of Varsha forecast and IMD observation for June 2005.   reasonably well captured by Varsha; in particular there is no prediction of above-average rainfall.  Given the limitations of available data, various modelling constraints and long-standing scientific questions about pre-dictability on longer time scales, we put on record that no claims are made for the spatial and temporal accuracy in the all India precipitation forecasts. But, given the long term of one month and the spa-tial extent of the Indian region, the ob-served trend is well captured not only for June 2009 but also for July–September 2009. Indeed, we find that in the last 20 years for which model forecasts have been made (and whose results have been presented in various fora sponsored by MoES), in all four cases where the  deficit in June rainfall exceeded 20% the trends forecast by Varsha have beenqualitatively correct, as shown in Figures 4–6. For example, in all these cases the relatively low rainfall in the first half of the month, followed by higher rainfall in the second half is well depicted in the forecast.  Although NAL may not be a ‘leading centre of meteorological forecasting’ in the world, it so happens that its Varsha code picked up the deficit rainfall 3–4 weeks in advance and captured its sever-ity three weeks in advance this June. Therefore, it would not be correct to conclude that atmospheric models in general do not have the skill of picking up the severe deficit of rainfall such as what was experienced in June 2009.   1. Francis, P. A. and Gadgil, S., Curr. Sci., 2009, 97, 1291–1295. 2. India Meteorological Department, http:// www.imd.gov.in  ACKNOWLEDGEMENTS. The work car-ried out at NAL on Varsha development and associated Flosolver hardware has been spon-sored under the NMITLI programme of CSIR since 2001, and also by the MoES since 2007. We are grateful for the support, and for the advice we have received from the Monitoring Committee of the NMITLI project (currently consisting of Dr T. S. Prahlad, Prof. V. S. Ramamurthy, Dr M. Rajeevan and Prof.  R. Narasimha (Chairman)).   U. N. SINHA  #2, ‘MAA’, 6th Cross, Bagalagunte, Nagasandra Post, Bangalore 560 073, India e-mail: sinhaun47@gmail.com        

On the predictive behaviour of the Indian monsoon in June 2009

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