Satellite With ARgos And ALtiKa Research Articles

A machine‐learning and data assimilation forecasting framework for surface waves

In this article, we combine deep symbolic regression (DSR) and ensemble optimal interpolation‐based data assimilation (DA) methods to correct the error in forecasts from the numerical model WaveWatch III. In our experiments, DA and DSR training is performed on hindcasts and then the model is integrated forward in time using both the numerical model and the symbolic expressions generated from the DSR procedure to generate the forecasts. The DSR method is utilized in this article to generate the symbolic equations that correct the model error in the WaveWatch III/ DA system. The proposed algorithm takes the zonal () and meridional () wind components from Global Forecast System (GFS) forecasts, wave heights from WaveWatch III, and geographical coordinates (latitude and longitude) to model physical relationships not included in the original numerical model. The DA is performed using Jason‐2 and Satellite with ARgos and ALtiKa (SARAL) altimeter measurements, and the independent testing uses in situ buoys. The root‐mean‐squared deviation (RMSD) of the proposed method is better than that of the numerical model with/without DA for up to 42 hr with only 12 days of assimilation spin‐up cycle. The symbolic equation generated from the proposed framework can be used to correct the predictions from WaveWatch III for weather prediction.

SARAL/AltiKa data analysis for oceanographic research: Impact of drifting and post star sensor anomaly phases

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 ∼ 12.8% during the DP and ∼ 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.

Numerical Analysis of the Effect of Binary Typhoons on Ocean Surface Waves in Waters Surrounding Taiwan

The ocean surface waves during Super Typhoons Maria (2018), Lekima (2019), and Meranti (2016) were reproduced using hybrid typhoon winds and a fully coupled wave-tide-circulation modeling system (SCHISM-WWM-III). The hindcasted significant wave heights are in good agreement with the along-track significant wave heights measured by the altimeters aboard the SARAL (Satellite with ARgos and ALtiKa) and Jason-2 satellites. Two numerical experiments pairing Super Typhoons Maria (2018) and Meranti (2016) and Super Typhoons Lekima (2019) and Meranti (2016) were conducted to analyze the storm wave characteristics of binary and individual typhoons. Four points located near the tracks of the three super typhoons were selected to elucidate the effects of binary typhoons on ocean surface waves. The comparisons indicate that binary typhoons not only cause an increase in the significant wave height simulations at four selected pints but also result in increases in the one-dimensional wave energy and two-dimensional directional wave spectra. Our results also reveal that the effects of binary typhoons on ocean surface waves are more significant at the periphery of the typhoon than near the center of the typhoon. The interactions between waves generated by Super Typhoons Maria (2018) and Meranti (2016) or Super Typhoons Lekima (2019) and Meranti (2016) might be diminished by Taiwan Island even if the separation distance between two typhoons is <700 km.

A combined passive–active microwave retrieval of ocean surface wind speed from SARAL-AltiKa microwave radar altimeter and radiometer

SARAL (Satellite with Argos and AltiKa) is the first satellite radar altimetry mission to fly a Ka-band instrument (AltiKa), which has completed 5 years in orbit on 25th February 2018. Ka-band SARAL-AltiKa suffers larger signal attenuation due to atmospheric water content and also exhibits a different relationship with wind speed than at Ku and C band. Here an augmentation of our earlier geophysical model function (GMF) that was developed based on first principles for wind speed retrieval from SARAL-AltiKa is proposed. This GMF is further augmented here, taking advantage of the co-aligned passive microwave radiometer making measurements of brightness temperature (BT) along with the primary active radar AltiKa measurements of radar backscatter (RB) and significant wave height (SWH) in conjunction with a large matched database of wind speed from Jason-2, respectively. The retrieved wind speed from currently modified algorithm provides an accuracy of 1.34 ms−1 in root mean square deviation with global buoys. Finally, the new algorithm has been used successfully in demonstrating its applicability in capturing regional to global wind field features and compared with other independent satellite measurements like OceanSat scatterometer, Jason-2 altimeter and DMSP-SSM/I radiometer.

The Drifting Phase of SARAL: Securing Stable Ocean Mesoscale Sampling with an Unmaintained Decaying Altitude

The French/Indian altimeter project Satellite with ARGOS and AltiKa (SARAL) completed its nominal 3-year mission on the historical European Remote-sensing Satellite (ERS) orbit in Spring 2016. In order to extend the lifetime of the satellite as much as possible, the agencies in charge of SARAL decided to initiate a so-called drifting phase where the satellite altitude is no longer maintained. In this paper we describe how the ocean mesoscale sampling capability of SARAL has been preserved during the drifting phase by initiating it at a specific altitude: the optimal starting point was approximately 1 km above the historical ERS/ENVIronment SATellite (ENVISAT) orbit. This strategy secured the ocean mesoscale sampling capability of SARAL drifting phase (DP) for 6 years or more. We also generalize these findings: any altimeter could follow SARAL’s drifting phase strategy if their maneuvering capability is limited. Lastly, we explain how an altimetry mission or an entire altimeter constellation could be operated without any form of altitude control: some specific altitude bands (e.g., near 1230 km) guarantee a high-quality mesoscale sampling for years or decades even if the altitude is not maintained.

Estimation of Water Level Changes of Large-Scale Amazon Wetlands Using ALOS2 ScanSAR Differential Interferometry

Differential synthetic aperture radar (SAR) interferometry (DInSAR) has been successfully used to estimate water level changes (∂h/∂t) over wetlands and floodplains. Specifically, amongst ALOS PALSAR datasets, the fine-beam stripmap mode has been mostly implemented to estimate ∂h/∂t due to its availability of multitemporal images. However, the fine-beam observation mode provides limited swath coverage to study large floodplains and wetlands, such as the Amazon floodplains. Therefore, for the first time, this paper demonstrates that ALOS2 ScanSAR data can be used to estimate the large-scale ∂h/∂t in Amazon floodplains. The basic procedures and challenges of DInSAR processing with ALOS2 ScanSAR data are addressed and final ∂h/∂t maps are generated based on the Satellite with ARgos and ALtiKa (SARAL) altimetry’s reference data. This study reveals that the local ∂h/∂t patterns of Amazon floodplains are spatially complex with highly interconnected floodplain channels, but the large-scale (with 350 km swath) ∂h/∂t patterns are simply characterized by river water flow directions.

Evolution of the Performances of Radar Altimetry Missions from ERS-2 to Sentinel-3A over the Inner Niger Delta

Radar altimetry provides unique information on water stages of inland hydro-systems. In this study, the performance of seven altimetry missions, among the most commonly used in land hydrology (i.e., European Remote-Sensing Satellite-2 (ERS-2), ENVIronment SATellite (ENVISAT), Satellite with Argos and ALtika (SARAL), Jason-1, Jason-2, Jason-3 and Sentinel-3A), are assessed using records from a dense in situ network composed of 19 gauge stations in the Inner Niger Delta (IND) from 1995 to 2017. Results show an overall very good agreement between altimetry-based and in situ water levels with correlation coefficient (R) greater than 0.8 in 80% of the cases and Root Mean Square Error (RMSE) lower than 0.4 m in 48% of cases. Better agreement is found for the recently launched missions such as SARAL, Jason-3 and Sentinel-3A than for former missions, indicating the advance of the use of the Ka-band for SARAL and of the Synthetic-aperture Radar (SAR) mode for Sentinel-3A. Cross-correlation analysis performed between water levels from the same altimetry mission leads to time-lags between the upstream and the downstream part of the Inner Niger Delta of around two months that can be related to the time residence of water in the drainage area.

A global high-resolution ocean wave model improved by assimilating the satellite altimeter significant wave height

This study examines the effects of data assimilation using Significant Wave Height (SWH) from three satellite altimeters, notably the Jason-2, Jason-3 and SAtellite with ARgos and ALtiKa (SARAL), orbiting in space and incorporating the data into a global high-resolution ocean wave model. The third-generation wave model, WAVEWATCH III (WW3), was adopted for numerical simulation and its spatial resolution was refined to 0.2°. Data assimilation is carried out using the Optimal Interpolation (OI) scheme to demonstrate the feasibility and the benefits of simultaneously assimilating the along-track SWH data from multi-satellite altimeters into a global ocean wave model. Higher resolution global ocean wave models can advantageously account for the swell propagation from deep ocean waters without open boundary conditions, as well as simulate smaller scale wind waves from the coastal zones conveniently, effectively and in tandem. The Root Mean Square (RMS) of non-assimilation experiment is 0.54 m, which is smaller than the previous coarse resolution global wave modelling. Minor improvement is found when only one 10-min frequency, SWH data from the Jason-2 altimeter was assimilated into the global ocean wave model. However, the RMS against buoy observations is highly reduced (i.e. approximately 0.42 m) when the SWH data from three satellite altimeters (i.e. Jason-2, Jason-3 and SARAL) are simultaneously assimilated into the global high-resolution ocean wave model and in return, led to significant model improvement. This study can also provide some implications for wave predictions in global oceans.

Elevation Change Derived from SARAL/ALtiKa Altimetric Mission: Quality Assessment and Performance of the Ka-Band

The waveform retracking algorithm is a key factor that affects the accuracy of elevation change from satellite altimetry over an ice sheet. The elevation change results from four waveform retracker algorithms (ICE1/ICE2/Sea Ice/OCEAN) provided by the Satellite with ARgos and ALtiKa (SARAL/ALtiKa) data were compared using repeated SARAL data between March 2013 and April 2016 to determine the optimal retracker in the crossovers of descending and ascending orbits over a Greenland ice sheet (GrIS). The ICE1 provided slightly better results than the three other algorithms with the lowest standard deviation (SD) of 0.30 m year−1. Further comparison was also conducted between the Satellite with ARgos and ALtiKa (SARAL) and Operation ICEBridge laser data, thereby indicating that ICE1 was the best retracker with an Root Mean Square Error (RMSE) of 0.43 m year−1. The distribution of elevation change rate and uncertainties over Greenland from SARAL were presented using the selected ICE1 retracker with a volume loss of 40 ± 12 km3 year−1. This volume loss did not include the fast-changing coastal areas of the GrIS. A large thinning was observed in Jakobshavn Isbræ, and a trend that extended far inland was also found from 2013–2016. Furthermore, a melting ice sheet was observed in the large areas northwest over the GrIS.

Independent Assessment of Sentinel-3A Wet Tropospheric Correction over the Open and Coastal Ocean

Launched on 16 February 2016, Sentinel-3A (S3A) carries a two-band microwave radiometer (MWR) similar to that of Envisat, and is aimed at the precise retrieval of the wet tropospheric correction (WTC) through collocated measurements using the Synthetic Aperture Radar Altimeter (SRAL) instrument. This study aims at presenting an independent assessment of the WTC derived from the S3A MWR over the open and coastal ocean. Comparisons with other four MWRs show Root Mean Square (RMS) differences (cm) of S3A with respect to these sensors of 1.0 (Global Precipitation Measurement (GPM) Microwave Imager, GMI), 1.2 (Jason-2), 1.3 (Jason-3), and 1.5 (Satellite with ARgos and ALtika (SARAL)). The linear fit with respect to these MWR shows scale factors close to 1 and small offsets, indicating a good agreement between all these sensors. In spite of the short analysis period of 10 months, a stable temporal evolution of the S3A WTC has been observed. In line with the similar two-band instruments aboard previous European Space Agency (ESA) altimetric missions, strong ice and land contamination can be observed, the latter mainly found up to 20–25 km from the coast. Comparisons with the European Centre for Medium-Range Weather Forecasts (ECMWF) and an independent WTC derived only from third party data are also shown, indicating good overall performance. However, improvements in both the retrieval algorithm and screening of invalid MWR observations are desirable to achieve the quality of the equivalent WTC from Jason-3. The outcome of this study is a deeper knowledge of the measurement capabilities and limitations of the type of MWR aboard S3A and of the present WTC retrieval algorithms.

Multi-Satellite Altimeter Validation along the French Atlantic Coast in the Southern Bay of Biscay from ERS-2 to SARAL

Monitoring changes in coastal sea levels is necessary given the impacts of climate change. Information on the sea level and its changes are important parameters in connection to climate change processes. In this study, radar altimetry data from successive satellite missions, European Remote Sensing-2 (ERS-2), Jason-1, Envisat, Jason-2, and Satellite with ARgos and ALtiKa (SARAL), were used to measure sea surface heights (SSH). Altimetry-derived SSH was validated for the southern Bay of Biscay, using records from seven tide gauges located along the French Atlantic coast. More detailed comparisons were performed at La Rochelle, as this was the only tide gauge whose records covered the entire observation period for the different radar altimetry missions. The results of the comparison between the altimetry-based and in-situ SSH, recorded from zero to five kilometers away from the coast, had root mean square errors (RMSE) ranging from 0.08 m to 0.21 m, 0.17 m to 0.34 m, 0.1 m to 0.29 m, 0.18 m to 0.9 m, and 0.22 m to 0.89 m for SARAL, Jason-2, Jason-1, ENVISAT, and ERS-2, respectively. Comparing the missions on the same orbit, ENVISAT had better results than ERS-2, which can be accounted for by the improvements in the sensor mode of operation, whereas the better results obtained using SARAL are related to the first-time use of the Ka-band for an altimetry sensor. For Jason-1 and Jason-2, improvements were found in the ocean retracking algorithm (MLE-4 against MLE-3), and also in the bi-frequency ionosphere and radiometer wet troposphere corrections. Close to the shore, the use of model-based ionosphere (GIM) and wet troposphere (ECMWF) corrections, as applied to land surfaces, reduced the error on the SSH estimates.

CryoSat-2 Full Bit Rate Level 1A processing and validation for inland water applications

This study uniquely processes Cryosat-2 Full Bit Rate (FBR) SAR Level 1A data to recover inland water heights. The processing methodology involves an azimuthal Fast Fourier Transform (FFT) for the burst echo data followed by beam formation directed towards equi-angular ground points, stacking, slant range correction, multi-looking and finally retracking. It is seen that speckle in the burst echo data affects the recovered heights with precise heights recovered only through stacking and forming multi-look waveforms. Also investigated is the effect of different numbers of multi-looks in the stack to form the final waveform for retracking. A number of empirical retrackers are utilized over inland waters and compared against the oceanic SAMOSA2 and the OCOG/Threshold retrackers. Use of the SAMOSA2 retracker is shown to be inappropriate for inland waters. The use of 81 multi-looks from the stack centred on the nadir direction is shown to be preferred across Tonlé Sap with the RMS of height residuals in the range 4–6 cm. External validation across Tonlé Sap using gauge data shows that CryoSat-2 heights (RMS 42.1 cm) are comparable to OSTM (RMS 42.6 cm) despite the CryoSat-2 non-repeating orbit which precludes the use of a mean profile. Validation against gauge data at Kratie on the Mekong gives an RMS of 59.9 cm for Cryosat-2 against an RMS of 35.5 cm and 52.2 cm derived from Envisat. The CryoSat-2 results utilize an approximate correction for river slope as the river crossings span 5 km upstream to 80 km downstream of the gauge while the repeat pass crossings of Envisat are at 7 km and 43 km from the gauge. Validation of Amazon altimetric Surface Water Elevation (SWE) showed RMS agreement of 27.3 cm with Obidos gauge data and 56.3 cm at Manacapuru 650 km upstream of Obidos. Overall validations showed that CryoSat-2 altimetric river heights are more accurate than those from TOPEX/Poseidon, OSTM and Envisat for relatively large water bodies but less accurate than the Ka band SARAL (Satellite with ARgos and ALtiKa).

SARAL/AltiKa Mission: Applications Using Ka-band Altimetry

Observations from AltiKa (nadir altimeter in Ka-band) on board the Satellite with ARGOS and AltiKa (SARAL) mission have been used for exploring new, unique and challenging areas. These application areas are coastal altimetry, inland hydrology and cryosphere (continental and sea ice). High rate (40-Hz) data from AltiKa has been exploited for retrieving very useful oceanic parameters (sea surface height anomaly, significant wave height and ocean surface wind) in the coastal waters (up to ~ 3 km off coast) of Indian landmass region. Validation carried out using buoys and tide gauge suggest exceedingly high correlation (~ 0.7–0.9) in the region of 3–10 km from the coast for each of these parameters. AltiKa is able to provide reasonably good quality ocean parameters much nearer to the coast (up to 3–10 km) as compared to Jason-2 (up to 8–10 km). Under the land hydrology, some of the extreme events such as flood wave (Brahmaputra river) and hydrological drought (Ukai reservoir) over India have been captured extremely well by AltiKa data. Brahmaputra river flood plain experiences flood waves almost every year. Flood wave of Brahmaputra river was captured using the AltiKa data on 9th June 2015. Two important aspects of cryospheric applications of AltiKa data has revealed interesting findings. During 2013–2015, East Antarctica is gaining ice with maximum change of 0.6 m in many regions. While in the west near Thwaites glacier and Pine Island glacier, more than 2 m reduction in the elevation has been observed. Winter sea ice freeboard thickness values were found to be higher than those estimated during summer period in both Arctic and Antarctic regions.

Calibration and Validation of HY-2 Altimeter Wave Height

AbstractHai Yang-2 (HY-2) satellite altimeter measurements of significant wave height () are analyzed over the period from 1 October 2011 to 6 December 2014. They are calibrated and validated against in situ buoys and other concurrently operating altimeters: Jason-2, CryoSat-2, and Satellite with Argos and ALtiKa (SARAL). In general, the HY-2 altimeter measurements agree well with buoy measurements, with a bias of −0.22 m and a root-mean-square error (RMSE) of 0.30 m. When the reduced major axis (RMA) regression procedure was applied to the entire period, the RMSE was reduced by 33% to 0.2 m. A further comparison with other satellite altimeters, however, revealed two additional features of HY-2 estimates over this period. First, a noticeable mismatch is present between HY-2 and the other satellite altimeters for high seas ( > 6 m). Second, a jump increase in HY-2 values was detected starting in April 2013, which was associated with the switch to backup status of the HY-2 sensors and the subsequent update of its data processing software. Although reported by previous studies, these two deficiencies had not been accounted for in calibrations. Therefore, the HY-2 wave height records are now subdivided into two phases (time periods pre- and post-April 2013) and a two-branched calibration is proposed for each phase. These revised calibrations, validated throughout the range of significant wave heights of 1–9 m, are expected to improve the practical applicability of HY-2 measurements significantly.

Estimating discharge from the Godavari River using ENVISAT, Jason-2, and SARAL/AltiKa radar altimeters

ABSTRACTThe present work discusses the application of radar altimeters on-board Environmental Satellite (ENVISAT), Jason-2, and Satellite with Argos and AltiKa (SARAL) missions to estimate the Godavari River discharge draining into the Bay of Bengal for the period 2002–2014. Ranges retrieved from the ICE-1 and ICE-3 retracker algorithms were used to estimate the river heights, followed by important range corrections. In situ radar gauge data at Yanam station and river discharge data from Dowlaiswaram dam were used to construct rating curves. This technique was applied to the ENVISAT (2002–2010), SARAL (2013–2014) derived river heights at Yanam and ENVISAT (2002–2010), SARAL (2013–2014), Jason-2 (2008–2014) derived river heights at Bhadrachalam. A hydrodynamic model was used to validate the ENVISAT and SARAL derived heights at Yanam; found that the modelled data are highly correlated with correlation coefficient r = 0.9. We estimate the standard errors of river height for all three altimeters. The values range from 0.15 to 0.40 m, quite within the acceptable accuracy of altimetry for hydrology/river applications. The root mean square error (RMSE) between ENVISAT and in situ discharge is 366 and 253 m3 s−1 at Yanam and Bhadrachalam, respectively. With Jason-2, it is around 620 m3 s−1 at Bhadrachalam. The residual error in individual altimetry data estimates is of the order ±15–25% of the in situ river discharge. The standard errors from ENVISAT at Yanam (Bhadrachalam) for the years 2007, 2008, 2009, and 2010 are 0.10% (14.70%), 10.30% (2.80%), 8.20% (26.50%), and 25.30% (10.20%), respectively; which are within the range of acceptable errors for discharge measurements (10–25%).

Comparison of SARAL and Jason-1/2 altimetry-derived geoids for geophysical exploration over the Indian offshore

Satellite with ARgos and ALtika (SARAL) altimeter includes the ALTIKA payload, a 35.75 GHz Ka band radar altimeter. High pulse repetition frequency of SARAL (4 KHz) satellite provides better along-track information. Jason-1/2 data have been extensively utilized as a follow-up of TOPEX/Poseidon altimeter data for its accurate measurements of the sea surface heights, particularly for geodetic mission of Jason-1. In this study, we have compared SARAL and Jason-1/2 altimetry-derived classical and residual geoids over the Indian offshore using Rapp’s, EGM96 and EGM08 gravity model coefficients, which are of interest for better understanding of geological and structural evolution/interpretation. SARAL and Jason-1/2 data have also been used over the two prominent geological features over the Indian offshore, namely the Bombay High in the western offshore and the 85°E Ridge in the Bay of Bengal. The SARAL altimetry-derived geoids could delineate these major geological/structural features with distinct residual geoidal lows.

Ice sheet survey over Antarctica using satellite altimetry: ERS-2, Envisat, SARAL/AltiKa, the key importance of continuous observations along the same repeat orbit

From September 2002 to October 2010, the Envisat radar altimeter surveyed Greenland and Antarctica ice sheets on a 35 day repeat orbit, providing a unique data set for ice sheet mass balance studies. Up to 85 repeat cycles are available and the whole Envisat data set may be along-track processed in order to provide height variability and trend with a good spatial resolution for the objectives of ice sheet survey.Soon, a joint Centre National d’Etudes Spatiales/Indian Space Research Organisation mission, SARAL (Satellite with Argos and AltiKa), with the AltiKa payload on board, will be launched on exactly the same orbit (less than 1 km of the nomimal orbit in the across-track direction). This will allow an extension of previous European Remote Sensing (ERS) satellite, ERS-1 and ERS-2, and Envisat missions of the European Space Agency (ESA), in particular from the point of view of ice altimetry. However, AltiKa operates in the Ka band (36.8 GHz), a higher frequency than the classical Ku band (13.6 GHz), leading to important modifications and potential improvements in the interactions between radar wave and snow-pack.In this paper, a synthesis is presented of all available information relevant to ice altimetry scientific purposes as derived from the Envisat mission: mean and temporal derivatives of the height − but also of the backscatter and of the two waveform parameters − snow-pack change corrections, across-track surface slope at 1 km scale, etc. The spatial and temporal variability of ice sheet surface elevation is investigated with the help of the high-resolution Envisat along-track observations. We show that at least 50 repeat cycles are needed to reach the required accuracy for the elevation trend. It is thus advocated as potentially highly beneficial for SARAL/AltiKa as a follow-on mission. Moreover, the novel characteristics of SARAL/AltiKa are promising in improving our understanding of snow penetration impact.

Model Function for Wind Speed Retrieval from SARAL-AltiKa Radar Altimeter Backscatter: Case Studies with TOPEX and JASON Data

In this article, a forward model is developed for estimation of the microwave nadir-viewing radar backscatter of a sea surface at C-, Ku- and Ka-bands during clear sky conditions. The forward simulations are carried out based on electromagnetic field theory of stratified media under various conditions like, sea surface temperature, salinity and wind. This theoretical basis is tested as a model function for retrieval of oceanic wind speed from the radar backscatter measurements from earlier or existing altimeters such as TOPEX/Poseidon and Jason-2 during non-raining conditions. Results show that the present model provides a better agreement with real altimeter data for wind speed retrieval at Ku-band. Moreover, a multiple regression approach is utilized to find the underlying relationship between radar backscatter and wind speed at Ka-band that could be possibly utilized for the retrieval of oceanic wind speed from the AltiKa radar measurements onboard the recently launched Satellite with Argos and AltiKa (SARAL).

Calibration of SARAL/AltiKa Wind Speed

Satellite with ARgos and ALtiKa (SARAL)/AltiKa is the first oceanographic radar altimeter that operates in Ka-band which is very sensitive to the atmospheric factors like liquid water and water vapor. An empirical recipe is proposed to partially compensate for this impact for the purpose of ocean surface wind speed (SWS) evaluation. The results compare well with numerical prediction model fields and in situ measurements. SARAL SWS computed using the proposed recipe shows very low bias (below 0.4 m/s). The random error at a scale of 75 km is estimated at about 1.0 m/s, which is very close to that of the Ku-band altimeters.

Simulation of SARAL (Satellite with ARgos and ALtika) resolution gravity over the western Indian offshore for geological/structural interpretation

SARAL (Satellite with ARgos and ALtika) is expected to be launched in early 2011 by ISRO which includes the ALTIKA payload, a 35.75 GHz Ka band radar altimeter. The present investigation compares a simulated SARAL altimetric gravity field with various existing satellite altimetric gravity and ship-borne gravity over the western Indian offshore which is of interest for better understanding of geological evolution and oil prospecting. These comparisons show the superiority of high-resolution satellite gravity and simulated SARAL-resolution gravity over previous, lower resolution ERS-1 altimetric gravity. The SARAL simulated gravity also shows a high correlation with respect to available ship-borne gravity data as evident from power spectral density analyses. Thus, it is found to be quite useful for geological/structural interpretation and exploration in the Indian offshore.