Monsoon Forecasting is a challenging problem over the Indian subcontinent where monsoon constitute a major weather system affecting a large population. Short & medium range and seasonal forecasts are essential for various weather sensitive activities such as farming operations, flood forecasting, water resource management sports, transport etc. Forecasting monsoon weather system and associated rainfall is one of the difficult areas in Numerical Weather Prediction (NWP) due to complex interactions involved. These include impact of topography, treatment of synoptic scale systems, mesoscale convective systems and non-availability of good quality high resolution observations over land and ocean.
IMD has the operational mandate to provide day to day forecasts on short to medium range for various user specific application such as, public weather services, aviation, agriculture, hydrology, disaster management etc. In the past, synoptic methods have been the mainstay of tropical weather forecasting. Of late, NWP methods have acquired greater skills and are playing increasingly important role in the tropical weather prediction, through the progress of dynamical modelling efforts in the tropics has been rather slow as compared to the extra tropics. This is because of some inherent problems associated with the dynamics of the tropical systems. In the extra tropics, the primary energy source for the atmospheric motion is the zonal available potential energy associated with the strong temperature gradients, and there exists a satisfactory dynamical theory of these motions outside the tropics.
In the tropics, on the other hand, the storage of available potential energy is very small due to the very small temperature gradients. Latent heat release in cumulus convection is the primary energy source. Parameterization of cumulus convection in tropical model is therefore very important and is a difficult problem. Added to this, there is the problem of large perennial data gaps in the tropical regions which are largely oceanic. The tropical numerical weather prediction system is required to address these problems adequately. Much progress has been made in recent years in the development of numerical models for low latitudes. The World Weather Watch, now supported by a variety of surface based and spaced based observing platforms has considerably enhanced the observational data base for numerical weather modelling. The availability of faster computers has enabled a large volume of tests on analysis, initialization, sensitivity to physical parameterization and statistical evaluation of NWP, resulting an overall improvement in the skill of tropical dynamical models.
Currently, Forecast Services are based on conventional Synoptic Methods supplemented by use of Numerical Weather Prediction products of different centres. But there is a growing demand to provide quantitative accurate forecasts in short to medium range time scale for parameters such as rainfall, temperature, humidity, wind, cloud etc. To meet this requirement NWP is the only state of the art tool currently available.
In this direction, action was initiated in the Eleventh (XI) - five year plan for a massive up-gradation of weather forecasting capabilities in India under the Modernization Programme of the Government of India, which covers various components such as, atmospheric observation network; strengthening of computing facilities, data integration and product generation and dissemination of information to an optimum level. It aimed for improved forecasting capabilities for high impact weather events like cyclones, severe thunderstorm, heavy rainfall and floods in a significant manner. IMD now has a good network of automatic weather stations, Doppler Weather Radars (DWR), state-of-the-art upper air systems etc. These observations are now being used to run numerical prediction models on High Performance Computing Systems (HPCS).
All current operational Numerical Weather Prediction (NWP) systems/models have limitations in predicting anomalous monsoon features, particularly the extreme events like heavy rainfall. A comparison of skills of global NWP systems of various leading NWP Centres of the world shows that their performance is more or less similar. When it comes to forecast during the monsoon season on short to medium range, no model has been able to predict consistently well the synoptic features beyond 4 to 5 days. No model has skill beyond day 3 in case of even moderate to heavy rainfall.
In general the NWP systems of leading global NWP centres are improving by 1 day of predictive skill per decade. However proportionate improvement in skill has not been noticed over the tropical monsoon region. The major international NWP centres have been able to invest adequate resources, both in terms of computing power and manpower for improving the skill of NWP. The improvements have been generally due to:
√ Improvements in model dynamics and physics
√ Better observations.
√ Careful use of forecast and observations, allowing for their information content and errors - achieved
by variational assimilation e.g., of satellite radiances
√ Four Dimensional Data Assimilation (4D-VAR)
√ Hybrid ensemble DA
A focused effort is required on the national scale for improving the assimilation and forecasting system especially for the monsoon region.