Data Assimilation Experiments Using An Indian Ocean General Circulation Model

Abstract

Today, ocean modeling is fast developing as a versatile tool for the study of earth’s climate, local marine ecosystems and coastal engineering applications. Though the field of ocean modeling began in the early 1950s along with the development of climate models and primitive computers, even today, the state-of-the-art ocean models have their own limitations. Many issues still remain such as the uncertainity in the parameterisation of essential processes that occur on spatial and temporal scales smaller than that can be resolved in model calculations, atmospheric forcing of the ocean and the boundary and initial conditions.

The advent of data assimilation into ocean modeling has heralded a new era in the field of ocean modeling and oceanic sciences. “Data assimilation” is a methodology in which observations are used to improve the forecasting skill of operational meteorological models.

The study in the present thesis mainly focuses on obtaining a four dimensional realization (the spatial description coupled with the time evolution) of the oceanic flow that is simultaneously consistent with the observational evidence and with the dynamical equations of motion and to provide initial conditions for predictions of oceanic circulation and tracer distribution.

A good implementation of data assimilation can be achieved with the availability of large number of good quality observations of the oceanic fields as both synoptic and in-situ data. With the technology in satellite oceanography and insitu measurements advancing by leaps over the past two decades, good synoptic and insitu observations of oceanic fields have been achieved. The current and expected explosion in remotely sensed and insitu measured oceanographic data is ushering a new age of ocean modeling and data assimilation. The thesis presents results of analysis of the impact of data assimilation in an ocean general circulation model of the North Indian Ocean.

In this thesis we have studied the impact of assimilation of temperature and salinity profiles from Argo floats and Sea Surface height anomalies from satellite altimeters in a Sigma-coordinate Indian Ocean model. An ocean data assimilation system based on the Regional Ocean Modeling System (ROMS) for the Indian Ocean is used. This model is implemented, validated and applied in a climatological simulation experiment to study the circulation in the Indian Ocean. The validated model is then used for the implementation of the data assimilation system for the Indian Ocean region. This dissertation presents the qualitative and quantitative comparisons of the model simulations with and without subsurface temperature and salinity profiles and sea surface height anamoly data assimilation for the Indian Ocean region. This is the first ever reported data assimilation studies of the Argo subsurface temperature and salinity profile data with ROMS in the Indian Ocean region.