This paper discusses the upgraded data assimilation (DA) wave forecasting system at the Indian National Centre for Ocean Information Services (INCOIS). Significant wave height (SWH) observations from deep and shallow water buoys in the North Indian Ocean are incorporated into the assimilation system in conjunction with satellite observations from SARAL/AltiKa, Jason-3, Sentinel-3a, and Sentinel-3b. In deep water, satellite DA improved the SWH forecast by 16

Here we discuss various coastal and ocean science applications of the Earth Observation Satellite-04 (EOS04) mission by the Indian Space Research Organisation. Automated oil spill detection using EOS-04, Medium Resolution ScanSAR data is carried out that involves segmenting of dark regions and classification of oil spills from look-alike s using a rank based algorithm. Lagrangian forecasting model is then used to predict the oil spill track. Genetic algorithm is employed to convert backscatter from EOS-04 into Significant Wave Height and wave spectra. The wavelength and propagation direction of ocean internal solitary waves are estimated using EOS-04 data. High resolution data in Fine Resolution Stripmap mode is used to estimate coastal bathymetry based on wave shoaling effect. The unique ability of EOS-04, with a range of spatial resolutions and various modes of operation form an essential ocean observation dataset that enables the scientific community to improve the understanding of complex coastal ocean processes.

In this study, we synergistically used Synthetic Aperture Radar (SAR) and optical observations to characterize the Internal Solitary Waves (ISW) in the Andaman Sea and Arabian Sea region. Total 25 scenes combined from EOS-04, Sentinel-1&2 satellites are considered for the year 2022. Various approaches, including Fast Fourier Transform (FFT), Multiple Image Comparison (MIC), Tidal Time Period (TTP) and Korteweg-de Vries (KdV) equations, were employed to characterize the ISW, and its spatial and seasonal variations are also analysed. The dominant wavelength of ISW over the Andaman Sea in June 2022 is found to be 6500 m travelling towards the Andaman coast. The overall phase speed of ISW in the Andaman Sea lies in the range of 1.87-2.60 ms(-1). It shows a seasonal variation of around 16% between winter and summer months, where a significant variation in the seasonal mixed layer depth was noticed. The phase speed also decreased as the ISW travelled from deep water to shallower regions. In contrast, the dominant wavelength of ISW in the continental shelf region of the west coast of India (near Goa) was much smaller (similar to 400 m) compared to the Andaman Sea. Here, the ISW phase speed estimated using MIC and TTP methods was similar to 0.56 ms(-1) in February 2022. The KdV equation yielded lower estimates of phase speed compared to the other two methods. The use of multiple satellite images and various approaches possess an advantage in comprehending the spatial and temporal variations in the characteristic features of ISW.

SARAL/AltiKa, the first microwave altimeter operating at Ka -band frequency, recently completed nine years of operations in orbit. During these years, it has catered to many applications related to operational oceanography, climate sciences, hydrology and cryosphere. More specifically, in oceanography, SARAL has contributed immensely to operational wave and circulation modelling, eddy detection/tracking, ocean current generation and many more. However, since Feb 2019, SARAL has moved from the drifting phase (DP) to the mispointing phase (MP) due to the malfunctioning of the star sensor of the spacecraft. In this study, we analyse the instrument's performance and its waveforms during its ongoing MP. We find out that during the MP, significant wave height (SWH) measurements are anomalously high between 18 and 24 m, and wind speed measurements are between 16 and 19 m/s. In sea surface height anomaly (SSHA), there is a steady rise in negative values during the MP. In the return waveform, -15% degradation in Brown -type waveforms in the open ocean region is noticed. These changes significantly impact the SARAL applications. Two important applications of wave forecast and eddy detection are discussed here as examples. Following this, we also recommend using provided quality flags so that the data can be further explored for various ocean applications. (c) 2023 COSPAR. Published by Elsevier B.V. All rights reserved.

Probabilistic models for long-term estimations and deep learning models for short-term predictions have been evaluated and analyzed for ocean wave parameters. Estimation of design and operational wave parameters for long-term return periods is essential for various coastal and ocean engineering applications. Three probability distributions, namely generalized extreme value distribution (EV), generalized Pareto distribution (PD), and Weibull distribution (WD), have been considered in this work. The design wave parameter considered is the maximal wave height for a specified return period, and the operational wave parameters are the mean maximal wave height and the highest occurring maximal wave height. For precise location-based estimation, wave heights are considered from a nested wave model, which has been configured to have a 10 km spatial resolution. As per availability, buoy-observed data are utilized for validation purposes at the Agatti, Digha, Gopalpur, and Ratnagiri stations along the Indian coasts. At the stations mentioned above, the long short-term memory (LSTM)-based deep learning model is applied to provide short-term predictions with higher accuracy. The probabilistic approach for long-term estimation and the deep learning model for short-term prediction can be used in combination to forecast wave statistics along the coasts, reducing hazards.

SAtellite-based Marine Process Understanding, Development, Research and Applications (SAMUDRA) for blue economy, a technology development program of the Space Applications Centre, is an umbrella program covering research and applications geared toward physical and biological oceanography making use of current and future satellite observations for developing the nation’s blue economy. The main motivation behind this project was to develop satellite and numerical model-based information and value-added products and to demonstrate the implementation of developed applications for operational requirements. The program also aimed at improving existing methodologies for various applications by utilizing space-based inputs. Several field campaigns with the use of NavIC-enabled instruments and NABHMITRA were conducted for measuring biophysical parameters and validation of developed applications in the coastal regions. One of the key aspects of this project was development of web-based customized tools/dissemination system for providing the information to the end users. Some of the key/notable achievements of SAMUDRA were development of a portal OceanEye (tailor-made web-portal for Shipping Corporation of India), storm-surge/inundation system, oil-spill trajectory modeling, level-next potential fishing zone algorithm and rip current alert system.

A Very Severe Cyclonic Storm ‘Yaas’ developed over the Bay of Bengal (BoB) on 23 May 2021 and crossed over the Odisha coast on 26 May with maximum sustained wind speed of 75 kts. Herein, a pathway has been developed and exemplified for ‘Yaas’ through three-stage cyclone-induced hazard tracking. Days before the cyclone formation, cyclone genesis potential parameter, sea surface temperature (SST) (> 30 °C) and tropical cyclone heat potential (anomaly of 40–80 kJ/cm 2 ) indicated a strong possibility of cyclogenesis in the BoB. A Lagrangian advection model used for its track prediction with 24-h lead-time provided an accuracy of ~ 19 km and ~ 6 h in its landfall location and time. Further, intensity prediction was done using numerical weather prediction model. Geostationary satellites, INSAT-3D/3DR, were used to visualize cyclone structure. Passing of cyclone had its reverbarations in oceans, which are observed in SST drop of ~ 3 °C, salinity and density increase by ~ 1 psu and ~ 2 kg/m 3 , respectively. During the period, 23–26 May 2021, the Ekman suction velocity and chlorophyll concentration were found significantly high at ~ 5 m/day and > 0.5 mg/m 3 , respectively. Forecast of storm surge was found to be between 3.5 and 4 m at coastal locations. Significant wave height was found to be 5.5–9.2 m. The coastal inundation forecast for 24 May 2021 provided its quantitative maximum inland extent. Finally, loss of the crop, fishery and forest areas by strong winds and inundation/ingress of saline water associated with storm surge were examined using SAR and optical data.

A major challenge to the emergence and establishment of new energy technologies such as ocean wave energy is the insufficient or nonexistent database for estimating resource potential. Despite having an extensive coastline, wave energy sources are yet to be developed in India. Hence, the main objective of this study is to identify the potential sites and assess the technical and economic feasibility of harnessing wave energy along the Indian coast. Three hotspots are identified in three coastal regions (east, south and west) based on optimum hotspot index and depth constrain criterion using 19 years of high-resolution wave hindcast. Results indicate that the theoretical potential of location along the west coast (12 kW/m) is highest as compared to a hotspot near the south (8 kW/m) and east coast (6 kW/m). The technical potential and cost of electricity generation at hotspot locations are estimated and compared using four different wave energy converters (WECs): Wavedragon, Pelamis, Oceantec, and Aquabuoy. Oceantec, among all WECs, generates more power (40–57 GWh) and attain a maximum capacity factor (22–31%) as well as the most cost-effective WEC with the lowest Levelized Cost of Energy (LCOE) ranging from 354 to 505 €/MWh at all hotspots. Economic sensitivity analysis reveals that interest rate and operation and maintenance costs are the most and least sensitive parameters, respectively. Outcomes of the present study will contribute to reducing the barriers to the current knowledge of wave energy resources in India.

Y AltiKa, first ever high frequency Ka-band altimeter on board SARAL (Satellite with ARgos and ALtiKa) has gone through different phases of operations, viz. Exact Repeat Mission, (ERM, March 2013 - July 2016), Drifting phase, (DP, July 2016 - January 2018) and then to Mispointing phase, (MP, February 2018 - till date). A detailed assessment of Sea level anomaly (SLA), Significant Wave Height (SWH) and Ocean Surface Wind Speed (WS) has been carried out during these different phases with a focus on the North Indian Ocean. Crossover analysis using the Jason series of satellites available during various phases of SARAL suggest high quality of SARAL/AltiKa data during the ERM and DP with root mean square differences of the order of 0.080 m, 0.25 m and 1 m/s for SLA, SWH and WS respectively. These differences are more during MP, being 0.095 m, 0.45 m and 1.72 m/s for SLA, SWH and WS respectively. Wavenumber Power spectrum computed from the along-track AltiKa SLA reveals that slopes in the mesoscale band (70-250 km) in different phases of operations are not very different. Errors in gridded SARAL/AltiKa SLA with respect to standard AVISO product remains unchanged during DP, but degrade by nearly 9.3% in the MP as compared to ERM. To assess the effect of assimilating along track SWH and SLA from different phases, two set of wave and circulation model simulations, with and without SARAL AltiKa data assimilation, were performed. Assimilation of SWH improved the wave height simulation by similar to 12.8% during the DP and similar to 8% during ERM and MP. As regards to circulation modeling, no significant difference of assimilating SLA from different phases was observed in the mesoscale range. These results indicate the usefulness of SLA from SARAL AltiKa during DP and MP for studying the mesoscale dynamics. (C) 2021 COSPAR. Published by Elsevier B.V. All rights reserved.

The present study analyses the combined offshore wind and wave resource potential along the Indian coast. The state-of-the-art ERA5 reanalysis datasets that provide wind fields at 100 m height have been used for the first time to assess wind resources along the Indian Coast. Further, wave parameters were generated using the WAVEWATCH III (WWIII) model. Long-term spatial air density was considered to find accurate wind power potential. The results reveal that the southern coast of India exhibits higher wind power density and moderate wave energy flux (up to 0.65 kW/m2 and 10 kW/m), respectively. This region has the lowest variability (coefficient of variation <1, skewness <1.5, and kurtosis <4) and less correlation (<0.4). A suitable hotspot is identified based on the collocation feasibility index and depth constraint after excluding conflicted regions. A comprehensive investigation of local wind and wave characteristics was performed at the hotspot. Further, the yearly and monthly cross-correlations between wind and wave at different time lags were analysed. Actual estimation of power generation is carried out with various combinations of wind turbine (SG8.0-167 DD) and wave energy converter (Oceantec). The outcome of the present study will help to initiate the development of joint offshore wind and wave energy farms in India.

In the present work, we have operationally implemented a data assimilation (DA) scheme in the wave forecasting system at the Indian operational agency, Indian National Centre for Ocean Information Services (INCOIS). Significant Wave Height (SWH) measurements from the SARAL/AltiKa, Jason-2 and Jason-3 altimeters were assimilated using the Optimal Interpolation technique. The impact of altimeter DA towards improving the reliability of wave predictions in the Indian Ocean is evaluated by validating the forecasted wave parameters with buoy observations. The assimilation of altimeter data showed considerable improvement in the wave predictions. SWH forecast in the northern Indian Ocean region improved up to similar to 15 % in the first 24 h period. The improvement in forecasted wave parameters were due to the correction in swell forecast, which persists throughout the forecast period. For wind-sea forecast, impact of DA was less visible (similar to 4-6% improvement up to forecast lead time of 24 h), as it is primarily driven by local wind fields. The positive impact of DA on the swell forecast is further established considering a swell surge event, named Kallakkadal.

The present study investigates the feasibility of wave energy exploitation along the Indian coast using 19-year (2000-2018) hindcasted wave data generated by WAVEWATCH-III with a fine spatial resolution (0.1 degrees x 0.1 degrees) and temporal resolution (6 h). The wave model is validated against 12-month measured wave data collected at multiple buoy sites and compared with 19-year ERAS data across the study area. The results show good agreement between model data and the other two datasets. The spatio-temporal variability analysis of wave energy flux reveals that southern coast of India has the mean wave energy flux ranging from 6 to 10 kW/m with a minimum monthly (<2.0), seasonal (<1.0) and annual (<0.2) variability which could be a promising area for future wave energy exploitation. A detailed analysis of wave power resource has been discussed for nine hotspot locations which were selected based on the optimum hotspot index, geographical restrictions on bathymetry and distance to the shore. Further, each hotspot has been analysed through combined scatter and energy diagrams. Finally, electrical power output is estimated at each hotspot using five wave energy converters and observed that the annual energy production at most of the locations is above 800 MWh with more than 70% availability.

Here we provide a brief description of the post-launch data quality evaluation and calibration-validation chain of the SCATSAT-1, the second scatterometers mission of Indian Space Research Organisation. This chain is of absolute importance to monitor the satellite health and its impact on its measurements. It also provides us overview of the suitability of the data for various applications. The results show that the SCATSAT instrument is having nominal behaviour, the measurements are of very high quality and is comparable to the reference mission QuikSCAT. The ocean surface winds derived using SCATSAT-1 are having errors less than 1 m/s and hence it is suitable for all operational meteorological and oceanographic applications.

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.

The current study aims to analyze the wind and wave parameters over Indian Ocean region obtained from first Ka -band altimeter AltiKa onboard SARAL, a collaborative mission of Indian Space Research Organization (ISRO) and Centre National d'Etudes Spatiales (CNES), France. It also demonstrates a real time application of SARAL data by assimilating the wave height in a wave model operational at the Space Applications Centre, ISRO. State-of-the art coastal wave model Simulating Wave Near shore (SWAN) is used for this purpose. The well-tested optimal interpolation technique is adopted for assimilation. Before proceeding to the assimilation per se, SARAL/AltiKa Wind and Significant Wave Height (SWH) have been validated using in- situ observations and WAVEWATCH III model. Apart from assessment of wind and wave data quality, this also served the purpose of providing error covariance to be used in assimilation. Supremacy of the assimilation run over parallel control run without assimilation has been judged by comparing the results with buoy observations at Indian National Centre for Ocean Information System (INCOIS). The statistics of validation of the assimilation run has been found to be extremely encouraging and interesting.

Fine resolution wind data is required in wave models to study the interaction between wind seas generated by coastal winds, and swells. In the present study, a mesoscale model, MM5, which is capable of reproducing fine details of sea breeze characteristics, has been used to simulate winds along the central west coast of India during pre-monsoon season, and these winds are used in the wave model. Our analysis shows that sea breeze induced wind seas are generated roughly around 210km off Goa in the northwest direction, and grow progressively while propagating towards the coast. Relationships between wind speed and wind sea height have been derived, and they fairly explain the generation of wind seas by the sea breeze system. Since, the land breeze is weak and available fetch is very limited, the land breeze has no significant effect on wind sea generation from the northeast direction.

ABSTRACT Shamal events are extra‐tropical weather systems which occur in winter (cold and dry winds) as well as summer (hot and humid winds) with strong northwesterly or northerly winds blowing over the Arabian Peninsula. We have used Weather Research and Forecasting ( WRF ) model to simulate a major winter shamal event (having duration of 3–5 days), which occurred in 2008 and analysed the spatial structure and time evolution of shamal winds over the Arabian Sea ( AS ). The study reveals that horizontally, shamal winds extend upto 14°N and bring out significant changes in the atmospheric temperature—longitudinally from Arabian coast to west coast of India; its vertical extension is upto to approximately 8 km near Oman and approximately 3 km near Ratnagiri coast. Along the Arabian coast a temperature drop of 12 °C is observed and along west coast of India a drop of 5 °C. It gets dissipated when northeast monsoon winds dominate. Its speed reduces from 15 m s −1 (Oman coast) to 9 m s −1 (central AS ) as it propagates into AS . However, it must be noted that the present work is limited to a case study and hence, the southerly extension of the phenomenon and the associated changes in air temperature should not be considered a climatological reference. The shamal events may influence the wind induced circulation, heat flux and stratification in the AS , and these need to be analysed further.