The Indian Ocean forecast system

In order to meet the ever growing demand for the prediction of oceanographic parametres in the Indian Ocean for a variety of applications, the Indian National Centre for Ocean Information Services (INCOIS) has recently set-up an operational ocean forecast system, viz. the Indian Ocean Forecast System (INDOFOS). This fully automated system, based on a state-of-the-art ocean general circulation model issues six-hourly forecasts of the sea-surface temperature, surface currents and depths of the mixed layer and the thermocline up to five-days of lead time. A brief account of INDOFOS and a statistical validation of the forecasts of these parametres using in situ and remote sensing data are presented in this article. The accuracy of the sea-surface temperature forecasts by the system is high in the Bay of Bengal and the Arabian Sea, whereas it is moderate in the equatorial Indian Ocean. On the other hand, the accuracy of the depth of the thermocline and the isothermal layers and surface current forecasts are higher near the equatorial region, while it is relatively lower in the Bay of Bengal.

Prediction of the Indian summer monsoon rainfall using a state-of-the-art coupled ocean-atmosphere model

A state-of-the-art model of the coupled ocean-atmosphere system, the climate forecast system (CFS), from the National Centres for Environmental Prediction (NCEP), USA, has been ported onto the PARAM Padma parallel computing system at the Centre for Development of Advanced Computing (CDAC), Bangalore and retrospective predictions for the summer monsoon (June-September) season of 2009 have been generated, using five initial conditions for the atmosphere and one initial condition for the ocean for May 2009. Whereas a large deficit in the Indian summer monsoon rainfall (ISMR; June-September) was experienced over the Indian region (with the all-India rainfall deficit by 22% of the average), the ensemble average prediction was for above-average rainfall during the summer monsoon. The retrospective predictions of ISMR with CFS from NCEP for 1981-2008 have been analysed. The retrospective predictions from NCEP for the summer monsoon of 1994 and that from CDAC for 2009 have been compared with the simulations for each of the seasons with the stand-alone atmospheric component of the model, the global forecast system (GFS), and observations. It has been shown that the simulation with GFS for 2009 showed deficit rainfall as observed. The large error in the prediction for the monsoon of 2009 can be attributed to a positive Indian Ocean Dipole event seen in the prediction from July onwards, which was not present in the observations. This suggests that the error could be reduced with improvement of the ocean model over the equatorial Indian Ocean.

A generalized geo-hazard warning system

An automated geo-hazard warning system is the need of the hour. It is integration of automation in hazard evaluation and warning communication. The primary objective of this paper is to explain a geo-hazard warning system based on Internet-resident concept and available cellular mobile infrastructure that makes use of geo-spatial data. The functionality of the system is modular in architecture having input, understanding, expert, output and warning modules. Thus, the system provides flexibility in integration between different types of hazard evaluation and communication systems leading to a generalized hazard warning system. The developed system has been validated for landslide hazard in Indian conditions. It has been realized through utilization of landslide causative factors, rainfall forecast from NASA's TRMM (Tropical Rainfall Measuring Mission) and knowledge base of landslide hazard intensity map and invokes the warning as warranted. The system evaluated hazard commensurate with expert evaluation within 5-6 % variability, and the warning message permeability has been found to be virtually instantaneous, with a maximum time lag recorded as 50 s, minimum of 10 s. So it could be concluded that a novel and stand-alone system for dynamic hazard warning has been developed and implemented. Such a handy system could be very useful in a densely populated country where people are unaware of the impending hazard.