Tauktae, a category-4 pre-monsoon tropical cyclone, originated over the Arabian Sea (AS), and made landfall in Gujarat, India on 17 May 2021, causing the loss of livelihoods, property and the economy in the region. In this study, the in-situ buoy and satellite observations are explored to analyse the conducive ocean condition before the formation of the cyclone primarily from the air–sea interaction perspective. Impacts of the storm during and after the passage of the cyclone are also observed using satellite measurements and numerical models. The warming observed in AS prior to the event is due to the substantial freshening of around 1PSU with respect to previous years causing stratification, near the coasts of Kerala and Karnataka. Buoy observations at AD10 during the formation and intensification of Cyclone Tauktae revealed surface cooling of approximately 1 °C and an increase in surface salinity by 0.5–1 PSU associated with the cyclone’s passage. The predicted storm surge height is estimated to be 2–4 m during the landfall of Tauktae cyclone, which is in good agreement with the India Meteorological Department report. Similarly, model predicted significant wave height closely matches with the in-situ buoy observations.

The integration of Ocean Colour Monitor (OCM-3) and scatterometer (SCAT-3) payloads onboard EOS-06 offers a powerful approach for advancing both meteorological and oceanographic applications. This study comprehensively overviews key applications that harness the synergy between simultaneous OCM-3 and scatterometer observations. These applications span operational and scientific domains, showcasing the versatility and value of combined satellite datasets. In the operational context, a multi-satellite parameter approach is employed to identify Potential Fishing Zones (PFZ). This methodology leverages chlorophyll gradients derived from OCM-3 data, coupled with scatterometer-derived wind propagation, to enhance PFZ predictions. From a scientific perspective, the study delves into several critical oceanographic processes. The role of Ekman transport, derived from satellite winds, is investigated to elucidate its influence on chlorophyll distribution patterns. Additionally, finite-size Lyapunov exponents (FSLEs) are computed from ocean current data, revealing co-variability with large chlorophyll eddies in the Arabian Sea. The dynamics of sediment plumes in the Krishna-Godavari basin are presented in the study based on the EOS-06 data. The paper also showcases the influence of high winds during cyclones on biological productivity using EOS-06 data.

EOS-06 Scatterometer is a continuity mission of SCATSAT-1 and carries a Ku-band Scatterometer with a scanning pencil beam configuration. It deploys two beams, a vertically polarized outer beam and a horizontally polarized inner beam, to cover a swath of 1800 km. The mission mainly caters to ocean wind measurements for oceanographic applications and weather forecasting, with the data being extensively used for cyclogenesis predictions across the globe, specifically, the tropical regions. In order to ensure data quality and suitability for operational applications, the data products need to be extensively calibrated and validated. This paper discusses the generation, calibration, validation and retrieval aspects of EOS-06 Scatterometer data products carried out in the Indian Space Research Organization (ISRO).

SARAL/AltiKa, the world’s first Ka-band altimeter, marks a significant technological advancement through the collaboration of the Indian Space Research Organization (ISRO) and the Centre National d’Etudes Spatiales (CNES). Launched on February 25, 2013, SARAL/AltiKa has made pivotal contributions to climate research and ocean monitoring, despite facing operational challenges such as orbit shifts in 2016 and the onset of the mispointing phase (MP) in 2019. This review highlights the broad spectrum of applications enabled by SARAL/AltiKa, particularly in India, from geodetic studies and coastal current analysis to oil spill tracking and wave model assimilation. An analysis of data from the MP phase (cycles 160–180) confirms the satellite’s continued ability to provide reliable geophysical measurements, further validated against merged altimeter products. SARAL/AltiKa’s significant contributions to operational oceanography and weather forecasting in India underscore its enduring scientific and practical impact.

This study demonstrates an effective approach to assimilate satellite observations of chlorophyll into coupled physical–biogeochemical model using a non-linear technique to improve model simulations of chlorophyll. For this purpose, ensemble-based particle filter technique, a non-linear technique, is developed to assimilate satellite observations of chlorophyll into the model for the year 2019 for the Bay of Bengal. Non-linear assimilation schemes pose a stringent computational limitation while employing in to a state-of-the-art coupled model. A unique approach is adopted in the study which is the use of the boot strap technique with particle filter to generate particles representing the probability density function of model chlorophyll. This approach has substantially reduced the computational time required for the generation of particles, which otherwise needs a distinct model run for each particle generation in the conventional particle filter technique. Higher weightage is assigned to the particles closer to observations and these strong particles are used to initialize the model for the next time step, while the weaker particles get discarded. Comparison with satellite data shows the efficacy of the data assimilation in correcting model bias significantly. The findings from the study indicate the influence of underlying physical processes and seasons dominating in the region on the efficacy of assimilation to improve on model simulations. Comparison with Bio-Argo floats highlights the significant improvement observed in model surface and sub-surface chlorophyll in both RMSE and bias correction. An 18

Wave hindcasting is pivotal for offshore operations and still poses challenges to modelers. Enhancing the accuracy of wave prediction involves either leveraging wind inputs from atmospheric models or assimilating wave observations. The present study uses an ensemble-based wave data assimilation method to refine wave parameter predictions. Focusing on the Bay of Bengal in the Indian Ocean. The wind-wave model, SWAN has been set up with forcing from six-hourly ECMWF ERA5 wind datasets with a resolution of 0.25°x0.25°. To generate an ensemble of wave fields, the wind vector has been perturbed from its initial states. Subsequently, the ensemble-based data assimilation scheme was developed to enhance the accuracy of significant wave height and mean wave period derived from the wind-wave model. The proposed scheme strategically distributes the errors across the model domain through a gain matrix. The study further highlights gain contours at various observation locations to illustrate the efficacy of the assimilation process. Based on the results, significant improvements in wave height prediction with the assimilation scheme demonstrate an effectiveness of 30

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.

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.

We combined observations of ocean surface winds from Indian SCATterometer SATellite-1 (SCATSAT-1) with a background wind field from a numerical weather prediction (NWP) model available at National Centre for Medium-Range Weather Forecast (NCMRWF) to generate a 6-hourly gridded hybrid wind product. A distinctive feature of the study is to produce a global gridded wind field from SCATSAT-1 scatterometer passes with spatio-temporal data gaps at regular synoptic hours relevant for forcing models and other NWP studies. We are following the concept from the modern particle filter technique, which does not represent the model probability density function (PDF) as Gaussian. We generated the 6-hourly hybrid winds for 2018 and validated them using the wind speed from daily gridded level-4 SCATSAT-1 winds (L4AW), Cross Calibrated Multi-Platform (CCMP) dataset and global buoy data from National Data Buoy Centre (NDBC). The results suggest the potential of the technique to produce scatterometer winds at the desired temporal frequency with significantly less noise and bias along the swath. The study shows that the generated hybrid winds are of prime quality compared with the already existing daily products available from Indian Space Research Organization (ISRO).

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.

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 CNES/ISRO altimetric satellite SARAL/AltiKa was launched in February 2013 and since then has provided useful data for various scientific and operational applications in oceanography, hydrology, cryospheric sciences and geodesy. However, a Reaction Wheel problem forced relaxation of the repeatability constraint on the satellite's orbit, which has been drifting slowly since July 2016. Beyond the expected contributions of this mission and its very good integration into the objectives of the constellation of altimetric satellites, it has become more and more apparent that specific contributions and innovations related to the main specification of SARAL/AltiKa, that is to say the use of the Ka-band, have clearly emerged. The advantages of the Ka-band are in short the reduction of ionosphere effects, the smaller footprint, the better horizontal resolution and the higher vertical resolution. A drawback of the Ka-band is the attenuation due to water/water vapor in case of rain and the resulting loss of data. The main objective of this paper is to highlight the specific advances of the Ka-band in different scientific and technical fields and to show why they are promising for the future and open the way to several missions or mission projects. Although unplanned initially, the fine coverage of the Drifting Phase brings some interesting openings especially for geodesy and hydrology applications.

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.

Arabian Sea (AS), the western sector of North Indian Ocean (NIO) produce smaller number of tropical cyclones as compared to Bay of Bengal. Though limited in numbers, the cyclones over Arabian sea are catastrophic by character. This make west coast of Indian subcontinent vulnerable to these hazards. The post-monsoon cyclogenesis over this region is known to be modulated by both monsoon rainfall and the El-Niño accompanied with positive Indian Ocean Dipole events. No single phenomena, however, can fully explain the variability observed in AS region. In this study, it is observed that apart from several known atmospheric forcings, inter-annual variability of ocean heat content (OHC) influence the post-monsoon AS cyclogenesis. The OHC of this region is partially modulated by the changes in salinity. Heat exchanges between the South West Indian Ocean (SWIO) and AS also modulates the OHC over AS. This remote influence is facilitated largely by the variability in the equatorial currents. Further it is seen that the recent trend of increased OHC post-2011 matches with the enhanced sea surface carbon over AS.

Indian Space Research Organization (ISRO) has started contributing towards international tandem space-borne scatterometer missions by successfully launching a Ku-band pencil-beam scatterometer onboard Oceansat-2 in September 2009. The Oceansat-2 scatterometer (OSCAT) continued to provide good quality observations of ocean surface vector winds till February 2014, when a major power failure ceased the mission. In September 2016, ISRO launched another Ku-band scatterometer as a sole payload onboard Scatsat-1. The Scatsat-1 followed the design heritage of OSCAT with some improved configuration. After the initial CAL/VAL phase, the Scatsat-1was to found to provide excellent quality of wind products. The present status of Scatsat-1 is operational. The operational data products from Scatsat-1 as well as archived products from OSCAT are available from both National Remote Sensing Centre (NRSC, www.nrsc.gov.in) and Meteorological and Oceanographic Satellite Data Archival Centre (MOSDAC, www.mosdac.gov.in). Apart from the operational products from these scatterometers, there are several other value added products are routinely generated and disseminated from MOSDAC. Table-1 shows the brief descriptions of the operational and value added products available from Scatsat-1.

In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology.Thepaperstarts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the ‘‘Green ” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion. (cid:1) 2021 COSPAR. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/).

Satellite observations over the Arabian Sea (AS) have revealed a strong signature of air–sea interaction during the Indian Ocean monsoon. In this study, satellite observations of ocean surface winds from the SCATSAT scatterometer are used to study the monsoonal variability in wind and SST (WS) coupling over the AS at the oceanic mesoscale for the period 2017 to 2019. The study investigates the role of critical parameters including SST gradient, wind speed steadiness and wind directional steadiness with respect to coupling during the winter and summer monsoons. Mesoscale WS coupling is stronger in the summer monsoon. A seasonally varying threshold of SST gradient required for the generation of WS coupling is clearly visible. This threshold is higher during the summer monsoon (0.8 °C/100 km) than during the winter monsoon (0.4 °C/100 km). Results reveal the need for a strong background wind field along with SST gradient for the generation of strong WS coupling. While a strong SST gradient (> 0.8 °C/100 km) is sufficient to overcome the adverse influence of background wind conditions, strong support from the stable background wind fields is necessary in the regions with a relatively weak SST gradient (> 0.4 °C/100 km) for the generation of coupling. The observed coupling between the SST and wind is quantified using a coupling coefficient. The coupling between wind stress divergence and downwind SST gradient is more prominent. It is observed that large warming of seawater (SST anomaly > 1 °C) suppressed the positive linear coupling between anomalies of wind speed and SST in the western AS during the summer monsoon.

Amphan, a category-5 tropical cyclone, originated over Bay of Bengal (BoB) and had a landfall in West Bengal, India on 20 May, causing havoc in the region. In this study, in-situ buoy and various satellite measurements are used to analyse the ocean condition before and after the storm, primarily from the air-sea interaction perspective. Widespread anomalous warming was observed in BoB before the event, due to high net surface insolation received by the ocean. The warm SST anomalies in the central BoB were coincident with anti-cyclonic warm core eddies, implying availability of higher oceanic heat content. Observations from BD13 buoy, close to the cyclone track showed heating of the overlying atmosphere due to this ocean warming. Strong surface cooling was observed after passage of the cyclone due to wind induced upper-ocean mixing that is stimulated by low stratification in BoB.