Ka-band Altimeter Research Articles

Antarctic ice surface properties inferred from Ka and Ku band altimeter waveforms

Altimetry missions designed for ocean monitoring can also evaluate the Antarctic ice sheet’s mass balance by measuring surface height. However, the returned radar echoes (waveforms) have complex shapes influenced by various snow and ice surface properties at multiple scales. Radar altimeters, operating in different modes and frequencies, interact with these surface properties in diverse ways. In this study, we developed a method to assess Antarctic surface properties using data from SARAL/AltiKa and Sentinel-3A & 3B altimeters for June 2021 and January 2023, respectively. We normalized and averaged the observed waveforms in 5 × 5 km2 grid cells. These were then used to create false-color images, with each grid cell’s average power and time gate represented as different ‘bands’. False-color images were analyzed using Principal Component Analysis (PCA) and ISODATA unsupervised classification to identify regions of Antarctica with similar surface properties. We achieved a percent variance of 73% and 84% for the first three Principal Components (PCs), and 96% and 98% for the first ten PCs with the Sentinel-3 and SARAL/AltiKa datasets, respectively. Finally, we analyzed the Ka and Ku band altimeter waveform shapes for each identified class to better understand snow and ice sensitivity to waveforms.

Improvements in mountain lake monitoring from satellite altimetry over the past 30 years – lessons learned from Tibetan lakes

Satellite altimetry has been widely used for inland water monitoring and modeling in the present decade. In this paper, the availability, data quality, and quantity of a number of spaceborne radar altimetry missions (including Topex/Poseidon (TP), ERS-2, Envisat, Jason-1/−2/−3, CryoSat-2, Saral, and Sentinel-3) are investigated. This is, to the best of our knowledge, the first paper to investigate the influences of onboard trackers, satellite flying directions, and land contamination on Level-1 waveforms and Level-2 measurements over large mountainous lakes. The analyses were conducted over eight Tibetan lakes, which are of varying sizes from ca. 93 to 1046 km2 and are sampled by multiple altimeters.From the results presented in this paper, it is demonstrated that the previous generation of altimeters, such as TP, Jason-1, ERS-2, and Envisat, shows a higher percentage of data unavailability and lower valid observation rates. Investigations of Level-1 waveforms show onboard tracker failing in locking on the lake surface, resulting in data loss or invalid measurements. In addition, the onboard tracking systems are sometimes unstable, resulting in larger along-track standard deviations (SD) (SD > 15 cm). In contrast, the recent generation of altimeters, i.e., Jason-3 and Sentinel-3 with open-loop tracking mode, significantly increases the data availability (> 90% passes and > 60% individual observations) and delivers higher precision measurements (SD around 10 cm). Moreover, the waveform leading edge is very consistent, indicating more stable onboard tracking. Higher quality Jason-3 and Sentinel-3 data allow monitoring of sub- and quasi-monthly lake variations, which are not revealed by e.g., TP and ERS-2 data due to poorer signal-to-noise ratios. Exceptionally, Saral Ka-band altimeter, operated in closed-loop tracking mode, is less affected by flying directions and land contamination (topography and landscapes), delivering high quality measurements (SD around 7 cm for 40 Hz).This study provides a comprehensive comparison of multiple altimeters in monitoring lakes in mountainous areas, and demonstrates the substantial improvements achieved in the past decades. However, care has to be taken when merging data from old generation altimetry missions over mountainous lakes. The lessons learned from these Tibetan lakes can be taken across to other mountain lakes.

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.

Characterizing Rain Cells as Measured by a Ka-Band Nadir Radar Altimeter: First Results and Impact on Future Altimetry Missions

The impact of large atmospheric attenuation events on data quality and availability is a critical aspect for future altimetry missions based on Ka-band altimetry. The SARAL/AltiKa mission and its Ka-band nadir altimeter offer a unique opportunity to assess this impact. Previous publications (Tournadre et al., 2009, 2015) already analyzed the impact of rain on the waveforms at Ka-band and proposed a definition of an elaborate rain flag. This notion tends to give a simpler black and white view of the atmospheric attenuation when the effect on the altimeter measurement is intense. However, in practice, there is a continuum of measurements that may be partially distorted or corrupted by rain events. The present study proposes a wider point of view, directly using the timeseries of the Ka-band altimeter backscattering coefficient for the first time, when previous studies relied on microwave radiometer (MWR) observations or model analyses with coarser resolutions. As guidelines for future Ka-band missions concerning the impact of the atmosphere, the Attenuation CElls Characterization ALgorithm (ACECAL) approach not only provides more representative statistics on rain cells (occurrences, amplitude, size), but also describes the internal structure of the cells. The actual atmospheric attenuation retrieved with ACECAL is about four times larger than the attenuation retrieved from the MWR. At a global scale, 1% of the measurements are affected by an attenuation larger than 23 dB and 10% of the atmospheric attenuation events have a size larger than 40 km. At regional scale, some areas of particular interest for oceanography as Gulf Stream, North Pacific and Brazil currents are more systematically affected compared with global statistics, with atmospheric attenuation up to 8 dB and cell size larger than 25 km when rain occurs. This study also opens some perspectives on the benefits that the community could be drawn from the systematic distribution of the rain cells parameters as secondary products of altimetry missions.

Sea Surface Heights and Marine Gravity Determined from SARAL/AltiKa Ka-band Altimeter Over South China Sea

SARAL/AltiKA (SRL) is the first altimetry satellite with a Ka-band altimeter. To validate the advantages of the Ka-band altimeter over traditional Ku-band altimeters in marine geodetic applications, a comprehensive analysis is carried out over the South China Sea (SCS) (0–30° N, 105–125° E) from three aspects, namely the influence of load on waveforms, the precision of sea surface heights (SSHs), and the precision of altimeter-derived marine gravity field. Coastal waveforms of SRL, Jason-2, and CryoSat-2 are separately compared with corresponding ocean-type waveforms. The radius of coastal influence on SSHs of SRL/exact repeat mission (SRL/ERM) is the smallest, being about 3 km. Crossover discrepancies, global mean sea surface models, and tide gauge data are used to assess the precision of altimetric SSHs. Compared with the SSH precision of Ku-band Jason-2/ERM, the SSH precision of Ka-band SRL/ERM is 4.6% higher over the SCS and 10% higher in offshore areas. Gridded gravity anomalies are derived from measurements of SRL/drifting phase (SRL/DP) and CryoSat-2 through the inverse Vening-Meinesz formula, respectively. According to the assessment by shipborne gravity data and global marine gravity models, the precision of SRL/DP-derived gravity is higher than that of CryoSat-2-derived gravity over the SCS, especially in offshore areas. In some cycles, ground tracks of SRL/ERM have large drifting of more than 10 km from nominal tracks. The results show that the Ka-band altimeter of SRL has better precision in SSHs and marine gravity recovery than the Ku-band altimeter over the SCS, particularly in offshore areas.

Precipitation measurement from SARAL AltiKa and passive microwave radiometer observations

ABSTRACT This study attempts to exploit ‘Satellite with Advanced Research and Global Observation Satellite (Argos) and Ka-band Altimeter (ALtiKa)’ (SARAL/AltiKa) and Passive Microwave Radiometer (PMR) measurements for the retrieval of precipitation and rain rate (R Rain) over the global oceans. The altimetric measurements are affected by the presence of rain and these measurements are thus required to be identified. In this research, the concurrent SARAL and Tropical Rainfall Measuring Mission – Precipitation Radar (TRMM-PR) measurements are used to show the rain sensitivity of some of the altimeter derived parameters and PMR-derived Brightness Temperature. Based on the probability distribution of rain-sensitive parameters, a probabilistic rain identification algorithm is proposed, which is optimized to reduce the false-alarm cases for rain estimation. In the second step, a Genetic Algorithm (GA)-based rain measurement algorithm is developed. The algorithm is applied to a full year (2016) of independent SARAL measurements, compared with collocated Global Precipitation Measurement (GPM) Mission Microwave Imager (GMI) and Special Sensor Microwave Imager Sounder (SSMIS) measurements. Within TRMM latitudinal coverage area (i.e. < ± 40° latitudes), the comparison with GMI and SSMIS shows correlation coefficient (r) of 0.78 and 0.76 and root mean square difference (RMSD) of 0.48 and 0.43 (mm h−1), respectively. The comparison, beyond latitudinal coverage of TRMM-PR (i.e. outside ± 40° latitudes), with GMI and SSMIS, shows r of 0.63 and 0.60 and RMSD of 0.59 and 0.55 (mm h−1), respectively. The algorithm is further applied to measure rain associated with a tropical cyclone. These rain measurements are then compared with near-concurrent rain measurements from SSMIS, and comparison results are presented in the paper.

The use of SARAL/AltiKa altimeter measurements for multi-site hydrodynamic model validation and rating curves estimation: An application to Brahmaputra River

Hydrodynamic (HD) modelling in data sparse region represents a challenge due to poor hydrological and topographic data availability. Recently, remote sensing techniques offer additional data that may help to improve the reliability and accuracy of such analysis. In this study, an attempt has been made to investigate the potential and added value of altimeter measurements for multi-site validation of the HD model and constructed rating curves (RCs) in a sparsely gauged Brahmaputra River, India. The HD model (MIKE 11) was developed for a Brahmaputra River stretch of 135 km, between Tezpur and Guwahati, where 4 ground-tracks of the SARAL/AltiKa (the first Ka band altimeter mission) cross the river. The Nash Sutcliffe efficiency (NSE) between HD model based water level and in-situ water level during calibration (January-October 2013) and validation (January-March 2014) was found to be 0.93 and 0.79 respectively. Calibrated and validated HD model was used to simulate water level and build rating curves at virtual stations. The bias correction (7.2 cm to 9.5 cm) was applied to the altimetry measurements before comparison with the modelled water levels. The root mean square error (RMSE) ranging between 15 cm and 42 cm was observed between the modelled and altimetry-derived water level at all the virtual stations, indicating the potential of satellite altimetry for multi-site validation of the HD model (inline with previous studies) and validation of the constructed RCs. The availability of RCs at virtual stations allows the expansion of the gauging network along the Brahmaputra River, thus enabling the estimation of the discharge at additional locations and the potential evaluation of the contributions of lateral tributaries could be evaluated in future work.

Marine gravity determined from multi-satellite GM/ERM altimeter data over the South China Sea: SCSGA V1.0

High-precision and high-resolution gravity fields can be derived from multi-source satellite altimeter data. A gravity anomaly model around the South China Sea (SCSGA) V1.0 on a 1′ × 1′ grid is established from sea surface heights (SSHs) of several geodetic missions (GMs) and exact repeat missions. Gridded deflections of the vertical are first calculated from SSHs by the least squares collocation (LSC) method and then used to derive gravity anomalies by the inverse Vening Meinesz formula. In gravity derivation processing, we establish an approximate relationship among the precision of altimetric gravity, precision of geoid gradients, and density of geoid gradients (the average number of geoid gradients per 1′ × 1′ region). The weights of geoid gradients from the Ka-band altimeter for the LSC are innovatively determined by an iterative method. Finally, SCSGA V1.0 is assessed by ship-borne gravity anomalies and marine gravity models. The performance of GMs in gravity derivation is evaluated. In general, the altimetric gravity precision in regions with many islands and reefs increases more obviously than those in other regions when the geoid gradient density increases. The standard deviation of SCSGA V1.0 is 2.78 mGal, which is slightly better than those of four recognized global marine gravity models around the SCS. CryoSat-2 is the most important dataset for SCSGA V1.0. Ka-band SARAL/AltiKa plays a major role in gravity derivation, and the contribution of Haiyang-2A is greater than those of other Ku-band satellites, except CryoSat-2. SCSGA V1.0 is concluded to reach an international advanced level for marine gravity from altimeter data around the SCS.

Calibration and Validation of Reprocessed HY-2A Altimeter Wave Height Measurements Using Data from Buoys, Jason-2, Cryosat-2, and SARAL/AltiKa

AbstractThe Haiyang-2A (HY-2A) satellite is China’s first ocean dynamic environment satellite, and the radar altimeter is one of its main payloads. In this study the HY-2A altimeter sensor interim geophysical dataset records (SIGDR) data are reprocessed to obtain better significant wave height (Hs) measurements over a period of more than four years (from 1 October 2011 to 15 March 2016). The reprocessed HY-2A Hs measurements are calibrated and validated using National Data Buoy Center (NDBC) buoys and several operating altimeters: Joint Altimetry Satellite Oceanography Network-2 (Jason-2), CryoSat-2, and Satellite with Argos Data Collection System and Ka-Band Altimeter (SARAL/ALtiKa) The final results of buoys and cross-altimeter comparisons show that the accuracy of the reprocessed HY-2A Hs measurements is significantly improved with respect to the Hs measurements in the operational HY-2A interim geophysical data record (IGDR) publicly distributed by the National Satellite Ocean Application Service (NSOAS), State Oceanic Administration (SOA) of China. Compared with the NDBC Hs measurements, the reprocessed HY-2A Hs measurements show a root-mean-square error (RMSE) of 0.215 m with a positive bias of 0.117 m. After calibrating with the two-branched corrections, the RMSE for the reprocessed HY-2A Hs measurements is reduced to 0.173 m, which is lower than those for the calibrated HY-2A IGDR, Jason-2, Cryosat-2, and SARAL measurements with an RMSE of 0.278, 0.233, 0.239, and 0.184 m, respectively. Long-term validation of the altimeter Hs measurements shows that the reprocessed HY-2A Hs measurements after calibration are stable with respect to the buoys and three other altimeters over the entire period. The reprocessed HY-2A Hs measurements are expected to improve the practical applicability of HY-2A Hs measurements significantly.

Significant wave height assessment using multi mission satellite altimeter over Malaysian seas

Satellite altimeter is one of the useful technique to study the variation of ocean parameters with a good temporal and spatial measurements. In situ measurements such as buoy has own disadvantages in terms of spatial observations. Thus, with the combination of satellite altimeter and buoy can improve the significant wave height measurements for both spatial and temporal over the seas. Generally, the measurement of significant wave height from altimeter using the Ku-band signal, while SARAL is borne with Ka-band altimeter (AltiKa). The aim of this research is to study the reliability of wave height data from the satellite altimeter to support marine renewable energy development. This Significant wave height (Hs) is retrieved from multi mission satellite altimeter by Radar Altimeter Database System (RADS) and evaluated using in-situ measurement over the Malaysian seas (0°N - 14°N and 95°E - 126°E). A validation with selected buoys located at Sabah Sea (5.83 N, 114.39 E) and Sarawak Sea (5.15 N, 111.82 E) is performed by statistical approach and presenting good correlation of 0.92 and 0.18 for RMSE. A climatology assessment is performed by analyzing the condition of significant wave height during monsoons. This paper highlighted, collocation between altimeter and buoy are well-correlated and reliable to use for a marine analysis for renewable energy development.

Ku-/Ka-Band Extrapolation of the Altimeter Cross Section and Assessment With Jason2/AltiKa Data

A simple extrapolation technique is proposed for the intercalibration of the Ku- and Ka-band altimeter data based on a recent analytical scattering model referred to as “GO4.” This method is tested with AltiKa and Jason2-Ku altimeters using one year of reprocessed data with the improved retracking algorithm ICENEW. The variations of the normalized radar cross section with respect to the main oceanic parameters are investigated in the Ku and Ka bands; the latter band is shown to have an increased sensitivity to wind speed, significant wave height as well as sea surface temperature. As a by-product of this analysis, we derive an original expression for the swell impact on the mean square slope, which allows to correct the GO4 model for the contribution of long waves. We show that the Ku/Ka prediction agrees within 0.25 dB with the respective levels of AltiKa and Jason2-Ku cross sections at wind speed larger than 4 m/s.

Retracking of SARAL/AltiKa Radar Altimetry Waveforms for Optimal Gravity Field Recovery

ABSTRACTThe accuracy of the marine gravity field derived from satellite altimetry depends on dense track spacing as well as high range precision. Here, we investigate the range precision that can be achieved using a new shorter wavelength Ka-band altimeter AltiKa aboard the SARAL spacecraft. We agree with a previous study that found that the range precision given in the SARAL/AltiKa Geophysical Data Records is more precise than that of Ku-band altimeter by a factor of two. Moreover, we show that two-pass retracking can further improve the range precision by a factor of 1.7 with respect to the 40 Hz-retracked data (item of range_40 hz) provided in the Geophysical Data Records. The important conclusion is that a dedicated Ka-band altimeter-mapping mission could substantially improve the global accuracy of the marine gravity field with complete coverage and a track spacing of <6 km achievable in ∼1.3 years. This would reveal thousands of uncharted seamounts on the ocean floor as well as important tectonic features such as microplates and abyssal hill fabric.

Monitoring of ocean environmental changes under influence of cyclonic system: Utilization of SARAL and contemporary satellite observations

The landfall of cyclone, Hud-Hud has created a widespread destruction along the coastal regions of northern Andhra Pradesh and southern Odisha, India. The changes have also been observed in the surrounding ocean. Satellite derived ocean geophysical products are used to study the changes. SARAL, the Ka band altimeter on path 438 of 10 October 2014 along with Jason-2 altimeter on path 116 of 12 October 2014 for their along track segments in the Bay of Bengal are studied. SARAL passed a day before its landfall has captured the cyclonic event in its full intensity in their geophysical products. The changes are observed in the Inverted Barometric Pressure Correction (IBPC) by an increase of about a centimeter in coastal waters than those of far off ocean. Increase in surface winds towards the coast from 4.01m/s to 15.52m/s has been observed in the along track data. The significant wave height is also increased from about 1m to 6.43m in the affected area. The contemporary Ku band altimeter, Jason-2 has also shown similar changes in the affected area. Sea Surface Height Anomaly (SSHA) spatial distribution has remained negative along the track under the cyclone foot print. While, Advanced Scatterometer (ASCAT) on 10 October 2014 have shown strong winds (up to 22.7m/s) in the region. This has induced surface mixing and upwelling in the water column leading to cooling of surface waters and enhancement of nutrients in the surface layers. This has lead to higher primary productivity, which is observed in the ocean chlorophyll-a maps. The environmental change in the Bay of Bengal during the cyclonic event has been studied using multiple satellite datasets and drifting buoy observations.

Impact of Assimilating SARAL/AltiKa SWH in SWAN Model During Indian Ocean Tropical Cyclone Phailin

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.

Evaluation of SARAL / AltiKa Measured Significant Wave Height and Wind Speed in the Indian Ocean Region

Significant wave height (SWH) and wind speed (WS) estimated by AltiKa are evaluated using in situ measurements and Jason-2 observations over the Indian Ocean region (30°S – 30°N and 30°E – 120°E). SARAL carried a Ka-band altimeter (AltiKa) along with a dual frequency radiometer onboard. This is the first altimeter operating in such high frequency of 35.75 GHz. Advantage of this high frequency is the narrow foot print of the satellite, which is useful for studies related to coastal regions, with the limitation of high attenuation to rain. From the validation exercise with in situ data for 21 cycles of AltiKa high resolution 40 Hz data, it is observed that the SWH is good while little underestimation of WS is observed. The root mean square error (RMSE) and bias of SWH are 0.21 m, −0.04 m respectively with a scatter index of 0.13; whereas in the case of WS, the RMSE and bias are 1.75 m/s, 0.25 m/s respectively with scatter index of 0.30. Inter-comparison is carried out between AltiKa and Jason-2 at all the cross over points in the Indian Ocean region and the SWH and WS of these two altimeters are in good concurrence with each other with the bias and RMSE of 0.03 m and 0.35 m for SWH and 0.01 m/s and 1.45 m/s for WS. From this study of Ka-band altimeter, it is inferred that the quality of the products is extremely good which is also capable of picking up accurate SWH during extreme events.

Validation of SARAL/AltiKa significant wave height and wind speed observations over the North Indian Ocean

SARAL/AltiKa, a joint Ka-band altimetry mission of the Centre National d’Etudes Spatiales (CNES) and Indian Space Research Organisation (ISRO) was successfully launched on February 25, 2013. The main purpose of this mission is to explore the ocean surface topography. As it is a Ka-band altimeter mission unlike other altimeters which were primarily in Ku-band, it is essential to calibrate and validate AltiKa data products before using the data for oceanographic applications. With this objective, two important geophysical parameters, Significant Wave Height (SWH) and Wind Speed (WS) from SARAL/AltiKa are inter-compared with those from 18 moored buoy stations in the North Indian Ocean (NIO) for a two year period from March 2013 to March 2015. SARAL/AltiKa GDR-T patch-2 version products are collocated with moored buoy observations with a collocation criteria of spatio-temporal window of 50km radius about the buoy location and 30min time for all the altimeter measurements. Following this, linear regression relations are developed and statistical analyses carried out to assess the performance of SARAL/AltiKa. The correlation between SARAL/AltiKa derived SWHs and those from moored buoys is 0.98m with a bias of −0.02m and Root Mean Square Error (RMSE) of 0.15m at 95% confidence level. The WSs derived from SARAL/AltiKa Ka-band correlates reasonably well with buoy observations with a correlation coefficient of 0.91, bias of −0.28m/s and RMSE of 1.13m/s. The inter-comparison results are found to be interesting with a good agreement between SARAL/AltiKa and moored buoys observations of SWH and WS in the NIO where SWHs are less than ∼4m and WS are less than ∼13m/s during the entire analysis period.

Intercomparison of Geophysical Parameters From SARAL/AltiKa and Jason-2 Altimeters

SARAL/AltiKa (AltiKa), a Ka-band altimeter is a joint Indo-French satellite mission launched on 25th February, 2013 by Indian Space Research Organization (ISRO). During the calibration/validation phase of the mission, it is essential to calibrate this altimeter and evaluate its performance for further use by the oceanographers’ community. With this objective, geophysical parameters namely significant wave height (SWH), wind speed (WS), and sea surface height anomaly (SSHA) from Jason-2 are used to assess the performance of AltiKa quantitatively. Additionally, certain supporting direct and indirect measurements from altimeters and radiometers onboard the two missions like normalized backscatter coefficient (Sigma0), brightness temperature ( ${{\rm T}_{\rm B}}$ ), water vapor (WV), and corresponding ionospheric corrections (IC) have also been analyzed. Global analyses show that the various parameters obtained from the two missions are in good agreement with each other even at 95% confidence level. Furthermore, ocean-wise regional analysis reveals that SWH from AltiKa is consistent with those from Jason-2. SSHA from AltiKa and Jason-2 shows a better agreement over the Indian Ocean with correlation coefficient (R) of 0.90 as compared to the Pacific or the Atlantic Oceans. Statistical analyses of other supporting parameters namely ${{\rm T}_{\rm B}}$ and WV from radiometers and IC from global ionosphere maps (GIM) model reveal that values for AltiKa and Jason-2 also compare well with bias [root-mean-square error (RMSE)] of 2.94 K (3.17 K), $\text{0}.\text{65}\;{\text {kg}}/{\text {m}^{2}}$ ( $\text{1}.\text{72}\;{\text {kg}}/{\text {m}^{2}}$ ), and 0.04 m (0.0008 m), respectively. The overall statistics are quite encouraging and envisage the great potential of AltiKa observations for oceanographic applications.

Use of SARAL/AltiKa Observations for Modeling River Flow

In the absence of many gauging stations in the major and mighty river systems, there is a need for satellite-based observations to estimate temporal variations in the river water storage and associated water management. In this study, SARAL/AltiKa application for setting up hydraulic model (HEC-RAS) and river flow simulations over Tapi River India has been discussed. Waveform data of 40 Hz from Ka band altimeter has been used for water levels retrieval in the Tapi river. SARAL/AltiKa retrieved water levels were converted to discharge in the upstream location (track-926) using the rating curve available for the nearby gauging site and using linear spatial interpolation technique. Steady state simulations were done for various flow conditions in the upstream. Validation of river flow model was done in the downstream location (track-367) by comparing simulated and altimeter retrieved water levels (RMSE 0.67 m). Validated model was used to develop rating curve between water levels and simulated discharge for the downstream location which enables to monitor discharge variations from satellite platform in the absence of in situ observations. It has been demonstrated that SARAL/AltiKa data has potential for river flow monitoring and modeling which will feed for flood disaster forecasting, management and planning.

Estimation of Sea Ice Freeboard from SARAL/AltiKa Data

An attempt has been made to derive sea ice freeboard from Ka-band Altimeter (SARAL/AltiKa) over Arctic region for 15 March–15 April 2013 (spring) and 15 September–15 October 2013 (autumn). A waveform template matching technique is employed for classification of leads and floe pixels. The estimated sea ice freeboards were found in close agreement with “Operation IceBridge quick look” freeboards (RMSD = 0.30 m). The differences between the two freeboards were largely due to snow layer over sea ice (R = 0.8). The estimated freeboards were of the order of 0.08–0.15 m during the two seasons.

Detection of Rain/Cloud Pixels by Ka-band AltiKa Altimeter over the Tropical Region: Development of a Rain/Cloud Flag Algorithm and its Validation

A rain/cloud flagging algorithm for the AltiKa waveform is developed. For this purpose, Mean Power Count between 13 and 40 gates and absolute value of off-nadir angle of Altika waveform are utilized against the backdrop of Liquid Water Content (LWC) > 0.25 kg m−2. It is observed that parameter is also affected by strong low-level jet. During the validation phase at near simultaneous time scale with 3B42 rainfall over the Indian Ocean, Probability of Detection (POD) and False Alarm Ratio (FAR) of Flag 1 (for LWC > 0.25 kg m−2) are found to be 0.76 and 0.19, respectively. Similarly POD and FAR of Flag 0 (for LWC ≤ 0.25 kg m−2) are found to be 0.90 and 0.11, respectively. Over the tropics during March 2013 to February 2014, the developed algorithm has detected 6.88% of Flag 1, of which 4.41% are due to rain/cloud, and the remaining 2.48% of flags are primarily due to strong low-level jet. Overall correlation coefficient between occurrence of Flag 1 due to rain/cloud and 3B42 rainfall is found to be 0.76. The developed algorithm is reasonably robust for detecting rain/cloud pixels.