We have simulated the return echo of a satellite altimeter from a rough ocean surface using an analytical formula and have studied its sensitivity with respect to various oceanic and altimeter parameters. Our numerical experiment shows that for normally observed significant wave heights (SWH) the effect of off-nadir angle (ONA) up to 0.5° on the leading edge is not severe. Also, small surface roughness skewness seems to have little effect on the overall shape of the echo.

Newton’s iterative scheme has been used to retrieve SWH from the mean return waveform without noise and with additive Gaussian noise typical of Seasat and Geosat altimeters. It has been observed that SWH can be retrieved in the presence of noise with an accuracy of ±0.6 m for ONA less than 0.5°. For higher ONA, accurate retrieval requires the use of precomputed look-up table along with our scheme.

The time series of Indian summer monsoon rainfall for the period 1871–1989 has been analysed using the method of deterministic chaos. It is found that a strange attractor underlies the time series implying the existence of a prediction function. This function has been approximated by a second-degree polynomial, involving the rainfalls of the past seven years and the coefficients have been estimated by least squares fit. The interannual variations of actual and computed rainfalls have been presented for a comparative study.

The variational technique of data assimilation using adjoint equations has been illustrated using a nonlinear oceanographic shallow water model. The technique consists of minimizing a cost function representing the misfit between the model and the data subject to the model equations acting as constraints. The problem has been transformed into an unconstrained one by the use of Lagrange multipliers. Particular emphasis has been laid on finite difference formulation of the algorithm. Several numerical experiments have been conducted using simulated data obtained from a control run of the model. Implications of this technique for assimilating asynoptic satellite altimeter data into ocean models have been discussed.

The aim of this paper is to study the feasibility of deriving vertical wind profiles from current satellite observations. With this aim, we carried out complex empirical orthogonal function (CEOF) analysis of a large number of radiosonde observations of wind profiles over the Indian Ocean during the monsoon months. It has been found that the first two CEOFs explain 67% of the total variance in wind fields. While the first principal component is well correlated with the winds at 850 mb (r = 0:80), the second one is highly correlated with winds at 200 mb (r = 0:89). This analysis formed the basis of a retrieval algorithm which ensures the retrieval of vertical profiles of winds using satellite tracked cloud motion vector winds. Under the assumption that accurate measurements of wind are available at the above mentioned levels, the r.m.s. error of retrieval of each component of wind is estimated to range between 2 ms^-1 and 6 ms^-1 at different levels, which is much less than the natural variance of winds at these levels. For a better visualization of retrieval, we have provided retrieved and true wind profiles side by side for four typical synoptic conditions during the monsoon season.

The nature of the inherent temporal variability of surface winds is analyzed by comparison of winds obtained through different measurement methods. In this work, an auto-correlation analysis of a time series data of surface winds measuredin situ by a deep water buoy in the Indian Ocean has been carried out. Hourly time series data available for 240 hours in the month of May, 1999 were subjected to an auto-correlation analysis. The analysis indicates an exponential fall of the autocorrelation in the first few hours with a decorrelation time scale of about 6 hours. For a meaningful comparison between satellite derived products andin situ data, satellite data acquired at different time intervals should be used with appropriate ‘weights’, rather than treating the data as concurrent in time. This paper presents a scheme for temporal weighting using the auto-correlation analysis. These temporal ‘weights’ can potentially improve the root mean square (rms) deviation between satellite andin situ measurements. A case study using the TRMM Microwave Imager (TMI) and Indian Ocean buoy wind speed data resulted in an improvement of about 10%.

Altimeter data have been assimilated in an ocean general circulation model using the water property conserving scheme. Two runs of the model have been conducted for the year 2004. In one of the runs, altimeter data have been assimilated sequentially, while in another run, assimilation has been suppressed. Assimilation has been restricted to the tropical Indian Ocean. An assessment of the strength of the scheme has been carried out by comparing the sea surface temperature (SST), simulated in the two runs, with in situ derived as well as remotely sensed observations of the same quantity. It has been found that the assimilation exhibits a significant positive impact on the simulation of SST. The subsurface effect of the assimilation could be judged by comparing the model simulated depth of the 20°C isotherm (hereafter referred to as D20), as a proxy of the thermocline depth, with the same quantity estimated from ARGO observations. In this case also, the impact is noteworthy. Effect on the dynamics has been judged by comparison of simulated surface current with observed current at a moored buoy location, and finally the impact on model sea level forecast in a free run after assimilation has been quantified in a representative example.

Wave prediction and hindcast studies are important in ocean engineering, coastal infrastructure development and management. In view of sparse and infrequent in-situ observations, model derived hindcast wave data can be used for the assessment of wave climate in offshore and coastal areas. In the present study, MIKE 21 SW Model has been used to carry out wave hindcast experiments in the Indian Ocean. Model runs have been made for the year 2005 using QuickSCAT scatterometer winds blended with ECMWF model winds. In order to study the impact of southern ocean swells, the model has been run in two different domains, with the southern boundary being shifted far south for the Domain 60S model. The model simulated wave parameters have been validated by comparing with buoy and altimeter data and various statistical yardsticks have been employed to quantify the validation. Possible reason for the poorer performance of the model in the Arabian Sea has also been pointed out.

The OSCAR (ocean surface current analysis real-time),which is a product derived from various satellite observations,has been evaluated in the tropical Indian Ocean (TIO)in two di fferent ways.First,the OSCAR-derived monthly climatology has been compared with available drifter-derived climatology in the TIO.From the comparison of the two climatologies,one can infer that OSCAR product is able to capture the variabilities of the well-known surface current systems in the TIO reasonably well.Fourier analysis of the major current systems,as reproduced by OSCAR,shows that the dominant annual and semiannual periodicities,known to exist in these systems,have been faithfully picked up by OSCAR. Next,the evaluation has been carried out by comparing the OSCAR currents with currents measured by moored buoys.The zonal component of OSCAR-current is in good agreement with corresponding component of buoy-observed current with a correlation exceeding 0.7,while the match between the meridional components is poorer.The locations of the peaks of the mean and eddy kinetic energies are matching in both the climatologies,although the peak in the drifter climatology is stronger than the same in the OSCAR product.Finally,an important feature of Indian Ocean circulation,namely the reverse Wyrtki jet,occurring during anomalous dipole years,has been well-reproduced by OSCAR currents.

The focus of the present study is the assessment of the impact of wind forcing on the spectral wave model MIKE 21 SW in the Indian Ocean region. Three different wind fields, namely the ECMWF analyzed winds, the ECMWF blended winds, and the NCEP blended winds have been used to drive the model. The wave model results have been compared with in-situ observations and satellite altimeter data. This study also evaluated the performance of the wind products during local phenomenon like sea breeze, since it has a significant impact on the wave prediction in the Indian coastal region. Hence we explored the possibility of studying the impact of diurnal variation of winds on coastal waves using different wind fields. An analysis of the model performance has also been made during high wind conditions with the inference that blended winds generate more realistic wave fields in the high wind conditions and are able to produce the growth and decay of waves more realistically.