Search

An algorithm has been developed to retrieve ocean surface wind speed from Synthetic Aperture Radar (SAR) on-board Radar Imaging Satellite-1 (RISAT-1). The retrieved wind speed is subsequently validated using observations from Advanced Scatterometers (on-board Metop-A, Metop-B) for the period from July 2012 to September 2016. The quality of the retrieved wind speed was assessed using observations from offshore moored buoys in the Bay of Bengal and Arabian Sea. It has been observed that the RISAT-1 derived wind speed, retrieved using three Geophysical Model Functions (GMFs) viz., CMOD5.N, CMOD5 and CMOD_IFR2 are negatively biased relative to ASCAT as well as Buoy. The biases with ASCAT are 0.38 (0.98) ms−1, 0.96 (1.24) ms−1 and 1.31 (1.55) ms−1 respectively for the coastal (offshore) region. The Root Mean Square Difference (RMSD) between RISAT-1 and ASCAT are 1.58 (1.78), 1.8 (1.85) and 1.96 (1.99) in m s−1 respectively for coastal (offshore) waters, which is well within the acceptable limits. Thus it is found that the quality of the wind speed retrieved using CMOD5.N GMF is better than other GMFs. The high resolution wind data available from RISAT-1 SAR opens new pathways for assessing wind energy potential along the Indian coast. [ABSTRACT FROM AUTHOR]

Accurate estimates of sea surface temperature (SST) are crucial for climate studies, numerical weather prediction and air–sea interactions. Following the launch of India’s advanced geostationary satellite – INSAT-3D with two thermal infrared split window channels in 2013, it is now possible to monitor land and ocean surfaces more reliably at higher spatiotemporal scale. In this article, an attempt has been made to develop a more accurate infrared-based cloud-free SST estimates over the tropical Indian Ocean by the synergistic use of geostationary INSAT-3D and polar-orbiting Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) satellite measurements through a successive correction method. This method is applied primarily for the month of May 2015 at coarser spatial resolution and at a daily scale. Results are compared independently with multi-satellite SST estimates and also againstin situobservations such as Argo floats and buoys. The merged SST product shows noticeable improvement over INSAT-3D-based estimates alone. Comparison of the merged SST product with Argo observations shows that the root mean square difference (RMSD) has been improved from 1.23 to 0.79 K, and bias and correlation are also significantly improved. Overall results indicate that the synergistic use of INSAT-3D and MODIS satellite observations has potential for more accurate SST estimation over the tropical Indian Ocean at finer temporal resolution and larger spatial coverage for several near-real time meteorological and oceanographic applications. [ABSTRACT FROM AUTHOR]

The focus of the study is assimilation of significant wave height (SWH) obtained from first Ka-band altimeter AltiKa onboard SARAL, a collaborative mission of the Indian Space Research Organization and Centre National d'Etudes Spatiales, France. The state-of-the art coastal wave model simulating waves near-shore has been used for this purpose. The well-tested optimal interpolation technique is adopted for this assimilation. A distinguishing feature of this study is the test of this assimilation scheme with SARAL/AltiKa data during the occurrence of a recent severe Cyclone Phailin in the Indian Ocean with its associated extreme waves. Before proceeding to assimilation per se, SARAL/AltiKa SWH has been validated using in situ as well as other satellite data. Apart from validation, this intercomparison also served the purpose of providing the needed error covariance to be used in assimilation. The supremacy of an assimilation run over a parallel control run without assimilation has been judged by comparing the results with Indian Ocean buoy observations and also with Jason-2 observations. The statistics of the validation of the assimilation run has been found to be extremely encouraging. [ABSTRACT FROM PUBLISHER]

Five-parameter model (BETA5) has been used to derive significant wave height (SWH) using 20-Hz Jason-2/OSTM Ku band waveforms in the Bay of Bengal basin of the Indian Ocean near the Indian city of Visakhapatnam for the years 2010–2012. Majority of the waveforms are traditional ocean-like waveforms based on Brown model. Nevertheless, quite a few of them have shapes differing significantly from the Brown model. Historically, two standard methods have been used for waveform retracking. One is maximum likelihood estimator (MLE) with 4 parameters, i.e. MLE4 (OCEAN retracker), which uses analytical second-order Brown model and the second one using first-order Brown model is MLE with three parameters, i.e. MLE3. It has been found in the study that standard MLE retrackers are not appropriate for retracking the nontraditional waveforms. Estimated SWHs have been validated against SWH measured by a buoy located in the close proximity of Visakhapatnam. SWH from BETA5 retracker matches buoy-derived SWH quite well except for a positive bias. Also, the bias is less for SWH retrieved using BETA5 than using MLE retrackers. Quantitatively, at a distance of 8 km from the coast correlation coefficient between BETA5 retracked SWH and buoy measured SWH is 0.85 and the unbiased root mean square error (RMSE) of the retracked SWH is 0.26 m. These are better than the corresponding values for MLE3 and OCEAN retrackers. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A diagnostic algorithm for determining the upper layer current in the tropical Indian Ocean (TIO) is presented in this study. The algorithm is based on quasi-linear and steady-state physics. The current in the upper layer consists of three components, namely geostrophic component, wind-driven (Ekman) component and buoyancy component. Each of these components is estimated from different satellite data. The geostrophic component is estimated from merged altimeter product. The Ekman component is estimated from ocean surface winds derived from Oceansat-2 Scatterometer (OSCAT), whereas the buoyancy component is estimated from sea surface temperature (SST) derived from a combination of infrared and microwave radiometers. The product derived for the year 2010 is compared with a similar product, known as Ocean Surface Current Analysis Real-Time (OSCAR), computed by the same algorithm, but with somewhat different data sets. Afterwards, the product is compared with currents measured by several buoys at different locations in the TIO and it is observed that the current variability is better captured by the data generated using the present algorithm. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

The accurate surface wind in the equatorial Indian Ocean is crucial for modeling ocean circulation over this region. In this study, the surface wind analysis generated at the European Center for Medium Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) are compared with NASA QuikSCAT satellite derived Level2B (swath level) and Level3 (gridded) surface winds for the year 2005. It is observed that the ECMWF winds exhibit speed bias of 1.5 m/s with respect to QuikSCAT Level3 in the southern equatorial Indian Ocean. The NCEP winds are found to exhibit speed bias (1.0-1.5 m/s) in the southern equatorial Indian Ocean specifically during January-February 2005. The biases are also observed in the analysis when compared with Level2B product as well; however, it is less in comparison to Level3 products. The amplitude of daily variations of both ECMWF and NCEP wind speed in Bay of Bengal and parts of the Arabian Sea is about 80% of that in QuikSCAT, while in the equatorial Indian Ocean it is about 60% of that of QuikSCAT. [ABSTRACT FROM AUTHOR]

The Sea Surface Temperatures (SST) and currents are simulated over the north Indian Ocean, during the onset phase of southwest monsoon for the three years 1994, 1995, and 1996, using daily Special Sensor Microwave/Imager (SSM/I) winds and National Center for Environmental Prediction (NCEP) heat fluxes as forcings in the 2½ layer thermodynamic numerical ocean model. The results are discussed for the 30-day period from 16 May to 13 June for all the three years, to determine the ocean state during the onset phase of SW monsoon. The maximum variability in the simulated SST is found along the Somali coast, Indian coasts, and equatorial regions. The maximum SST in the North Arabian Sea is found to be greater than 30°C and minimum SST in the west equatorial region is 25°C during the onset phase of all three years. Model SSTs are in agreement with Reynolds SST. SST gradients in the north-south as well as in the east-west directions, west of 80°E are found to change significantly prior to the onset. It can be inferred from the study that the SST gradient of 2.5°C/2000 km is seen due north and due west of the region 2° – 7°S, 60° – 65°E, about 8 to 10 days prior to the arrival of SW monsoon near Kerala coast. Upper and lower layer circulation fields do not show prominent interannual variability. [ABSTRACT FROM AUTHOR]

This article describes the impact of satellite altimeter data on the simulations of sea level variability (SLV) by a nonlinear reduced gravity model of the entire Indian Ocean. The model has been forced by 6-hourly analyzed wind stress data containing SSM/I observations and has been able to produce realistic circulation features. However, SLV values observed by Topex/Poseidon altimeter do not fit these simulations because of imperfect initial data. Hence an attempt has been made to initialize the model using altimeter data. The initialized model-generated SLVvalues have been compared with SLV derived by altimeter for monsoon as well as nonmonsoon months of 1996. Experimental runs have been performed for 10 days, 20 days, and one month. It has been found that the initialized model results on the final day of these experiments are in very good agreement with altimeter data of the same day. It is thus possible, in principle, to hindcast and forecast sea level variations in the time scale of 10 days to one month with the availability of good quality wind data for forcing the model and altimeter observations of sea level for initializing it. [ABSTRACT FROM AUTHOR]

Present study determines sensitivity of different input and dissipation parameterization schemes available in a third-generation wind-wave model, WAVEWATCH III for Indian Ocean (IO), using collocated altimeter and in-situ buoy measurements. For IO, in general, parameterization by Bidlot et al. (2005, referred as BAJ) is found to be the best in simulating SWH, for all the seasons. Albeit NIO is a part of IO, wave climate over this region is different as it exhibits variability in surface wind conditions before, after and during the monsoon phase. Thus, over NIO during pre- and post- monsoon seasons, when the region is dominated by swells propagating from the south, KC (KC denotes Kahma and Calkoen (1992, 1994)) stable parameterization scheme of Tolman and Chalikov (1996) is the better option for input and dissipation source function. During monsoon season, waves over NIO is primarily influenced by strong and persistent southwest monsoonal winds and dominated by young wind seas. BAJ parameterization is suggested as the better option during this phase. To simulate the high waves induced by tropical cyclones, KC stable parameterization of Tolman and Chalikov (1996) is found suitable. [ABSTRACT FROM AUTHOR]