About Us
The Earth behaves as a single interlinked and self regulating system. Its subsystems, viz. atmosphere, hydrosphere, cryosphere, geosphere and biosphere function together and their interactions are significant and complex. The energy and material transport within and across subsystems occur from local to global scale in varying space and time. Improved and reliable forecast of weather and climate requires integration of observations using very high resolution dynamical models with realistic representation of all physical processes and their complex non linear interactions. Since weather is an initial value problem, accuracy of the initial condition is as important as the accuracy of the model. Thus, data assimilation is a crucial component of weather predictions. As conventional data coverage is spatially and temporally limited, satellite data provides much better coverage in both space and time. About 90% of the data that goes into the assimilation of any analysis-forecast system comprise of data from satellite and rest from in situ platforms. In addition, it is important that adequate computing facility is available for carrying out various numerical experiments pertaining to various programs of the Ministry. This involves augmenting the computational power for the training school where hand on training are to be conducted with high resolution state of the art weather and climate numerical models , conducting research and development work for improving forecasts in the short, medium and long range scales for monsoon mission programs that involve sensitivity experiments for various physical processes. , the impact studies of different physical parameterization schemes etc. , data impact studies, ensemble prediction models with more members, climate change scenario generation for hundreds of years etc. In addition, it is essential to carry out studies related to observation simulation experiments (OSE), observation system simulation experiments (OSSE) and targeted observation experiments that can guide the planners on the location and type of observations that are crucial for the numerical models. Accordingly observation network can be better formulated. This is highly compute intensive job. Large number of numerical experiments shall have to be carried out to identify these crucial locations where observation network need to be strengthened. Hence, it is seen that the entire range of research work involves simulation runs of multiple versions of the same high resolution analysis forecast model which means the utilization of HPC time as well as storage also becomes manifold (directly depending on the total number of experiments undertaken by each student). In order to study the effect/impact on a large temporal scale (from monthly to decadal to 100s of years), these runs are to be undertaken accordingly. In addition, for understanding the micro scale process studies one has to go for extremely high resolution models that can resolve scales of the cloud and related processes. Thus these entire range of studies require not only high level of computer storage but also high computational power.