Jason-2 Altimeter Research Articles

The effects of non-local observations on the adjoint estimation of local model parameters: An example of Manning’s n coefficient in a tidal model over the Bohai, Yellow, and East China Seas

Accurate parameter estimation is a key issue for enhancing the performance of hydrological models. With the rapid development of satellite technology, integrating satellite data and numerical modelling for parameter estimation has gained more prominence. The limited spatial coverage of altimeters necessitates areas without direct local observations to rely only on information from nearby non-local observations. However, the relation is far from clear between non-local observations and the estimation of local model parameters. In this study, a two-dimensional adjoint tidal model over the Bohai, Yellow, and East China Seas (BYECS) is developed, assimilating observations from TOPEX/Poseidon, Jason-1, and Jason-2 altimeters in conjunction with tide-gauge stations. In twin experiments, the feasibility and reliability of utilizing non-local observations are emphasized by varying synthetic observations. The experiments also reveal how the number and distance of non-local observations affect the ill-posedness of local parameter estimation. The estimation errors can be reduced by increasing observations within a ‘critical distance’, beyond which the accuracy does not improve further. Subsequently, the robustness of ‘critical distance’ is discussed under different prescribed parameter distributions, sizes of predefined optimized area, and random observational errors, indicating that the ‘critical distance’ is approximately 1.0°-2.0°. These results provide a positive reference for practical experiment. In BYECS, the order of Manning’s n coefficient ranges from 10-4 to 10-1, with an average value of 0.0246 in shallow waters. The spatial distribution reveals 9 high-value areas, primarily modulated by a concurrence of sandy sediment and weak tidal currents. This study offers valuable insights into refining the adjoint model for physical parameter estimation, particularly in anticipation of the expanded spatial coverage of SWOT. Compared to only assimilating T/P series altimeters, incorporating SWOT reduces discrepancies by over 38%. Additionally, the spatial Manning’s n coefficient provides guidance for enhancing tidal simulation in other models.

Analysis of wave breaking on synthetic aperture radar at C-band during tropical cyclones

ABSTRACT The purpose of our work is to analyze the effect of wave breaking on dual-polarized (vertical-vertical (VV) and vertical-horizontal (VH)) synthetic aperture radar (SAR) image in the C-band during tropical cyclones (TCs) based on the machine learning method. In this study, more than 1300 Sentinel-1 (S-1) interferometric-wide (IW) and extra wide (EW) mode SAR images are collocated with wave simulations from the WAVEWATCH-III (WW3) model during 400 TCs. The validation of the significant wave height (SWH) simulated using the WW3 model against Jason-2 altimeter data. The winds for S-1 SAR images are reconstructed using wind retrievals in VV and VH polarization. The non-polarized (NP) contribution σ wb caused by wave breaking is assumed to be the result of the SAR-measured normalized radar cross-section (NRCS) σ 0 minus the Bragg resonant roughness σ br without the distortion of rain cells during TCs. The σ br is simulated by imputing wave spectra from the WW3 model into the theoretical backscattering model. It is found that the ratio (σ wb /σ 0) in VV polarization is related to the wind speed, the wind direction relative with the flight orientation, and radar incidence angle. Following this rationale, the Adaptive Boosting (AdaBoost) model was used for the estimation of NP contribution σ wb during TCs and are implemented for more than 300 dual-polarized S-1 images to validate the model. It is found that for the comparison between the sum of simulation NRCS and SAR observations, the root mean squared error (RMSE) is 1.95 dB and the coefficient (COR) is 0.86, which is better than a 2.83 dB RMSE and a 0.67 COR by empirical model. It is concluded that the AdaBoost model has a good performance on NP component simulation during TCs.

The Influence of Typhoon-Induced Wave on the Mesoscale Eddy

The strong wind-induced current and sea level have influences on the wave distribution in a tropical cyclone (TC). In particular, the wave–current interaction is significant in the period in which the TC passed the mesoscale eddy. In this study, the wave fields of Typhoon Chan-hom (2015) are hindcastly simulated using a coupled oceanic model that utilizes a nested triangle grid, i.e., the finite-volume community ocean model-simulating waves nearshore (FVCOM-SWAVE) model. The forcing wind field is composited from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data and the simulation using a parametric Holland model, denoted as H-E. The open boundary fields include tide data from TPOX.5 and the hybrid coordinate ocean model (HYCOM) global datasets, including sea surface temperature (SST), sea surface salinity, sea surface current, and sea level data. The simulated oceanic parameters (e.g., the significant wave height, SWH) are validated against the measurements from the Jason-2 altimeter, yielding a root mean square error (RMSE) of 0.58 m for the SWH, a correlation (COR) coefficient of 0.94, and a scatter index (SI) of 0.23. Similarly, the simulated SSTs are compared with the remote sensing products of the remote sensing system (REMSS) and the measurements from Argos, yielding an RMSE of <0.8 °C, a COR of >0.95, and an SI of <0.04. The significant zonal asymmetry of the wave distribution along the typhoon track is observed. The Stokes drift is calculated from the FVCOM-SWAVE simulation results, and then the contribution of the Stokes transport is estimated using the Ekman–Stokes numbers. It is found that the ratio of the Stokes transport to the total net transport can reach >80% near the typhoon center, and the ratio is reduced to approximately <20% away from the typhoon center, indicating that Stokes transport is an essential aspect in the water mixing during a TC. The mesoscale eddies are detected by the sea level anomalies (SLA) fusion data from AVISO. It is found that the significant wave heights, Stokes drift, and Stokes transport inside the eddy area were higher than those outside the eddy area. These parameters inside the cold mesoscale eddies were higher than t inside the warm mesoscale eddies. Otherwise, the SST mainly increased within the cold mesoscale eddies area, while decreased within the warm mesoscale eddies area. The influence of mesoscale eddies on the SST was in proportion to the eddy radius and eddy EKE.

Wave and Meso-Scale Eddy Climate in the Arctic Ocean

Under global climate change, the characteristics of oceanic dynamics are gradually beginning to change due to melting sea ice. This study focused on inter-annual variation in waves and mesoscale eddies (radius > 40 km) in the Arctic Ocean from 1993 to 2021. The waves were simulated by a numerical wave model, WAVEWATCH-III (WW3), which included a parameterization of ice–wave interaction. The long-term wind data were from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-5), and current and sea level data from the HYbrid Coordinate Ocean Model (HYCOM)were used as the forcing fields. The simulated significant wave heights (SWHs) were validated against the 2012 measurements from the Jason-2 altimeter, yielding a 0.55 m root mean square error (RMSE) with a 0.95 correlation (COR). The seasonal variation in WW3-simulated SWH from 2021 to 2022 showed that the SWH was the lowest in summer (July and August 2021) and highest in winter (November 2021 to April 2022). This result indicates that parts of the Arctic could become navigable in summer. The mesoscale eddies were identified using a daily-averaged sea level anomalies (SLA) product with a spatial resolution of a 0.25° grid for 1993−2021. We found that the activity intensity (EKE) and radius of mesoscale eddies in the spatial distribution behaved in opposing ways. The analysis of seasonal variation showed that the increase in eddy activity could lead to wave growth. The amplitude of SWH peaks was reduced when the Arctic Oscillation Index (AOI) was <−1.0 and increased when the AOI was >0.5, especially in the case of swells. The amplitude of SWH oscillation was low, and the EKE and radius of eddies were relatively small. Although the radius and EKE of eddies were almost similar to the AOI, the waves also influenced the eddies.

On Modelling Sea State Bias of Jason-2 Altimeter Data Based on Significant Wave Heights and Wind Speeds

Altimeter data processing is very important to improve the quality of sea surface height (SSH) measurements. Sea state bias (SSB) correction is a relatively uncertain error correction due to the lack of a clear theoretical model. At present, the commonly used methods for SSB correction are polynomial models (parametric models) and non-parametric models. The non-parametric model usually was constructed by collinear data. However, the amount of collinear data was enormous, and it contained redundant information. In this study, the non-parametric regression estimation model was optimized by using the parameter replacement method of ascending and descending tracks based on the crossover data. In this method, significant wave heights from the Jason-2 altimeter data during cycles 200–301 and wind speed from the ERA5 reanalysis data were used. The non-parametric regression estimation model of Jason-2 was constructed by combining it with local linear regression, Epanechnikov kernel function and local window width. At the same time, based on the significant wave height and wind speed at the crossover points, the SSB polynomial model containing six parameters was constructed by using the Taylor series expansion, and the model was optimized. By comparing polynomial model construction with different parameters, the optimized model was obtained. The SSH of the crossover points and the tide gauge records were used to validate these results derived from two models and GDR. Compared with the crossover discrepancies of SSH corrected by the polynomial model, the RMS of the crossover discrepancies of SSH corrected by the non-parametric regression estimation model was reduced by 7.9%. Compared with the crossover discrepancies of SSH corrected by the conventional non-parametric model from GDR, the RMS of the crossover discrepancies of SSH corrected by the non-parametric regression estimation model was reduced by 4.1%. This shows that the precision of the SSHs derived by after the SSB correction, as calculated by the non-parametric regression estimation model, was better than that of the polynomial model and the SSB correction from GDR. Using the Jason-2 altimeter data, the along-track geoid gradient and the sea level change rate of the global ocean were determined by using two models to correct the SSB. By comparing the results of the two models, the accuracy of the geoid gradient along the orbit that was obtained by the non-parametric regression estimation model was better than that of the polynomial model and GDR. The global average sea level change rate after the non-parametric regression estimation model correction was 3.47 ± 0.09 mm/y, which was the closest to the average sea level change rate that has been published in the international literature within this field.

Local Tide and Geoid Corrections Significantly Improve Coastal Retracked Jason Sea Surface Heights in the Philippines

Retracking algorithms increase the accuracy of coastal sea surface height (SSH) measurements. However, it is still important to validate these retracking estimates with tide gauge (SSHtg) observations. We downloaded the freely available Jason altimeter SSH processed using the XTRACK-ALES algorithm, then detided the SSH using different tide models. The first model is the default tidal correction based on Finite Element Solution 2014 (SSHfes), and the second model is the T_Tide harmonic analysis of the nearest tide gauge (SSHaltimeter). SSHfes showed a very poor correlation (< 0.31) and very high root mean square error (RMSE, > 29 cm). In contrast, SSHaltimeter generally showed a very high correlation (> 0.91) and low RMSE (< 17.4 cm). A further quality check based on the average and standard deviation of the difference between the SSH readings (SSHfes – SSHtg and SSHaltimeter – SSHtg) also showed the superior performance of SSHaltimeter, which scored < 9.3 and < 16.5 cm, respectively; compared to SSHfes, which scored < 9.3 cm and > 27 cm for the same parameters. The poor performance from the SSHfes likely comes from the complex bathymetry and coastal geomorphology of the country, which is not accounted for in the FES. The Philippines generally has a narrow shelf, and the FES tide corrections may be related to deep-water tides rather than the shallow-water tides observed from tide gauges. Despite the high correlation and agreement between the SSHaltimeter and SSHtg, the rate of sea level rise from the SSHaltimeter in some sites is more than twice the rate from SSHtg, which indicates the possible influence of the vertical land movement.

A combined denoising method of empirical mode decomposition and singular spectrum analysis applied to Jason altimeter waveforms: A case of the Caspian Sea

During the satellite pulse propagation and reception, the altimeter waveform is inevitably affected by noise. To reduce the noise level in Jason altimeter waveforms, we used singular spectrum analysis (SSA), empirical mode decomposition (EMD), and the combination of SSA and EMD to obtain the denoised waveforms. The advantages of the combined method were verified and the accuracy of the mean sea surface height (MSSH) model was improved. Comparing the denoising effect of the three methods, the results show that the signal-to-noise ratio (SNR), correlation coefficient and root-mean-square error are effectively improved by the combination of SSA and EMD. The sea surface heights (SSHs) were remeasured with a 50% threshold retracker of denoised waveforms, and the MSSH model of the Caspian Sea with a grid of 1′×1′ was established from the retracked SSHs of Jason-1/2/3. Taking the mean value of the four models as a control, it is found that the model calculated by the combined denoising method has the highest accuracy. This indicates that using the combined denoising method to reduce the noise level is beneficial to improve the accuracy of the MSSH model.

Australian Coastal Sea Level Trends Over 16 yr of Reprocessed Jason Altimeter 20‐Hz Data Sets

AbstractThis article analyzes the variation of sea level trends along the Australian coast zone (0–100 km) using 16 yr (2002–2018) of tide gauge records, reprocessed Jason data and European Space Agency (ESA) Climate Change Initiative (CCI) sea level product. The reprocessed Jason data are first compared with tide gauge and 3‐yr Sentinel‐3A data. Then the empirical orthogonal function analysis demonstrates that local sea levels are not only significantly affected by the El Niño Southern Oscillation‐related signals, but also moderately correlated with the Indian Ocean Dipole. A multivariate linear regression model with optimized noise model is thus built to reduce the impact of natural variability on the trend estimation. The results show that the geographical pattern of sea level rise from reprocessed Jason data and ESA CCI sea level product are highly consistent, with the rates decreasing from the northeast coast (6–8 mm yr−1) anticlockwise to the southeast coast (2–4 mm yr−1). The sea level trends from reprocessed Jason data are in good agreement with those from tide gauge records, though they are ∼1.5 mm yr−1 higher than those from the ESA CCI data product. The discrepancy between two altimeter datasets is acceptable considering the trend uncertainty (i.e., one standard deviation) from 20‐Hz along‐track points is at the level of 1–2 mm yr−1. It is also found that sea level trends decrease significantly from 5.8 ± 1.5 mm yr−1 offshore to 3.4 ± 1.2 mm yr−1 toward the southeast coasts. This may be because the continental slope precludes the propagation of sea levels from the East Australian Current dominated oceans to the coast.

Short-Term Variations in Water Temperature of the Antarctic Surface Layer

Against the background of global climate change, the warming water temperature of Antarctic surface water (<500 m) is worthy of study. Therefore, the purpose of this study was to investigate short-term variations in the water temperature of Antarctic surface water from January 2000 to December 2016, using offline coupled ocean models, i.e., the WAVEWATCH-III (WW3) model and the Stony Brook Parallel Ocean Model (sbPOM). The validation of the WW3-simulated significant wave height (SWH) against the measurements from the Jason-2 altimeter produced a root mean square error (RMSE) of 0.39 m with a 0.30-m bias. Moreover, the sbPOM-simulated water temperatures were compared with the collocated measurements from Argo buoys, yielding, and RMSE for water temperatures of less than 1.0 °C and a correlation coefficient (COR) of 0.92. The annual variation in the sbPOM-simulated water temperatures of the Antarctic surface water layer showed that the sea surface temperatures (SSTs) of the Pacific Ocean and Atlantic Ocean were greater than the SST of the Indian Ocean. Moreover, the SST rapidly increased to 2 °C in the Pacific Ocean in specific years due to El Nino and La Nina events. The vertical profile of the water temperature showed that the depth of the cool water in the Indian Ocean has decreased to 100 m since 2008, while the depth in the Pacific Ocean and Atlantic Ocean is about 200 m. It was also found that the seasonal variations in the water temperature at depths of 0 m, 50 m, and 100 m in the Pacific Ocean were more sensitive to El Nino events between January and June. However, it was revealed in this work that the increasing intensity of El Nino and La Nina events could reduce water warming in the Pacific Ocean.

Waveform Decontamination for Improving Satellite Radar Altimeter Data Over Nearshore Area: Upgraded Algorithm and Validation

One of the thorniest problems in altimetry community is retrieving accurate coastal sea surface height, especially in the last several kilometers offshore. It is confirmed in previous studies that decontaminating waveforms is beneficial to improve the quality of coastal SSHs. In this article, we proposed an upgraded strategy for waveform decontamination, including a novel realignment algorithm and gate-wise outlier detector. We validated the new strategy in four test regions using Jason-2 altimeter data. In the validation process, we compared retracked SSHs by 16 retrackers, which include retrackers provided in SGDR (Sensor Geophysical Data Record), ALES (Adaptive Leading Edge Subwaveform), and PISTACH (Prototype Innovant de Système de Traitement pour les Applications Côtières et l’Hydrologie) products. Comparison results verified that retracking the waveforms decontaminated using our new method can greatly improve the SSHs in the coastal region. The 20% threshold retracker (DW-TR20) and the ICE1 retracker (DW-ICE1) based on the decontaminated waveforms outperform other retrackers, especially in 0–4 km zone offshore. DW-TR20 and DW-ICE1 can provide robust SSHs with a consistent accuracy in 0–20 km coastal band and a high correlation (>0.9) with nearby gauge data. To conclude, the upgraded waveform decontamination strategy provides a promising solution for coastal altimetry, which makes it possible to extend reliable observations to the last several kilometers offshore.

Analysis of Wave-Induced Stokes Transport Effects on Sea Surface Temperature Simulations in the Western Pacific Ocean

This study investigated the performance of two ocean wave models, that is, Simulation Wave Nearshore (SWAN) and WAVEWATCH-III (WW3), and the interannual and seasonal variability of transport induced by Stokes drift during the period from 1989 to 2019. Three types of sea surface wind products were used for wave simulation: the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim, the Cross Calibrated Multi-Platform Version 2.0 (CCMP V2.0) from Remote Sensing Systems (RSS), and the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS). The modeling was validated against wave measurements from the Jason-2 altimeter in 2015. The analysis found that the root mean square error (RMSE) of significant wave height (SWH) from the WW3 model using CCMP wind data was 0.17 m, which is less than the ~0.6-m RMSE of SWH from the SWAN model using the other types of wind data. The simulations from the WW3 model using CCMP wind data indicated that the Stokes transport is up to 2 m2/s higher in the South China Sea and Japan Sea than that at other ocean regions in January. The interannual variation showed that the Stokes transport generally increased from 0.25 m2/s in 1989 to 0.35 m2/s in 2018. We also found that the accuracy of the sea surface temperature (SST) simulation using the Stony Brook Parallel Ocean Model (sbPOM) is improved by as much as 0.5 °C when Stokes transport is considered to validate the sbPOM-simulated SST against the measurements from Argo in 2012–2015. In particular, the Stokes transport has a negative effect on Summer (March to June) and has a positive effect in Autumn (July to September), which is probably caused by the tropical cyclones.

A Study of Wave-Induced Effects on Sea Surface Temperature Simulations during Typhoon Events

In this work, we investigate sea surface temperature (SST) cooling under binary typhoon conditions. We particularly focus on parallel- and cross-type typhoon paths during four typhoon events: Tembin and Bolaven in 2012, and Typhoon Chan-hom and Linfa in 2015. Wave-induced effects were simulated using a third-generation numeric model, WAVEWATCH III (WW3), and were subsequently included in SST simulations using the Stony Brook Parallel Ocean Model (sbPOM). Four wave-induced effects were analyzed: breaking waves, nonbreaking waves, radiation stress, and Stokes drift. Comparison of WW3-simulated significant wave height (SWH) data with measurements from the Jason-2 altimeter showed that the root mean square error (RMSE) was less than 0.6 m with a correlation (COR) of 0.9. When the four typhoon-wave-induced effects were included in sbPOM simulations, the simulated SSTs had an RMSE of 1 °C with a COR of 0.99 as compared to the Argos data. This was better than the RMSE and COR recovered between the measured and simulated SSTs, which were 1.4 °C and 0.96, respectively, when the four terms were not included. In particular, our results show that the effects of Stokes drift, as well as of nonbreaking waves, were an important factor in SST reduction during binary typhoons. The horizontal profile of the sbPOM-simulated SST for parallel-type typhoon paths (Typhoons Tembin and Bolaven) suggested that the observed finger pattern of SST cooling (up to 2 °C) was probably caused by drag from typhoon Tembin. SST was reduced by up to 4 °C for cross-type typhoon paths (Typhoons Chan-hom and Linfa). In general, mixing significantly increased when the four wave-induced effects were included. The vertical profile of SST indicated that disturbance depth increased (up to 100 m) for cross-type typhoon paths because the mixing intensity was greater for cross-type typhoons than for parallel-type typhoons.

Quantifying the precision of retracked Jason-2 sea level data in the 0–5 km Australian coastal zone

This paper aims to quantify the precision of retracked Jason-2 altimeter sea level data (2008–2016) in the 0–5 km Australian coastal zone. A new retracking strategy has been developed to achieve the highest possible precision of coastal sea-level data. Coastal waveforms were classified into four groups according to the adaptability of dedicated coastal retrackers, from which each group was reprocessed using an optimal retracker. A modified Brown model was introduced to reprocess the quasi-specular waveforms over calm waters. A seamless transition of sea surface heights from different retrackers was achieved by estimating and removing the significant wave height dependent height differences. In order to generate the 20-Hz sea level anomaly (SLA) and total water level envelope (TWLE) at the coast, the regional along-track mean sea surface (MSS) with a high spatial resolution (~300 m) was estimated. Compared to the global MSS model, the use of the along-track MSS has dramatically reduced the SLA variance by 140 cm2 in the 0–15 km coastal strip.The results from the evaluation of data precision for Jason-2 ground tracks and the validation against tide gauges show that this new retracking strategy can retrieve more reliable sea level data nearshore. The precision of 20-Hz sea level data in the 0–5 km Australian coastal strip ranges typically from 5 cm to 6 cm in most coastal areas, which is only ~1 cm lower than that beyond 5 km off the coastline. However, in Northwest Australian and some coastal regions, the data precision drops to ≥7 cm due partly to the specific coastal sea states and topography. In addition, it is found that the altimeter and tide gauge TWLE time series have a high correlation (>0.8) in the 0–5 km distance band, indicating that coastal sea-level data are useful for applications such as estimation of river plumes, long-term variation of water level in lakes and rivers, and the analysis of storm surges.

WAVEFORM CLASSIFICATION AND RETRACKING OF JASON-2 AND JASON-3 IN HALMAHERA SEA

The accuracy of sea surface heights (SSHs) estimation from satellite altimeters is strongly influenced by the microwave reflected signals (or waveforms). Waveforms in open oceans generally have ideal shapes following the Brown (1977) model. However, in coastal and shallow waters, the signals are disturbed by lands, thus resulting in complicated waveforms (non-Brown). Non-Brown waveforms produce inaccurate SSH estimations; therefore, specialized protocols such as waveform classification and retracking are crucial when attempting to produce accurate estimations. In this study, waveforms of Jason-2 and Jason-3 satellite altimeters in the Halmahera were classified and retracked using several algorithms, such as Offset Centre of Gravity (OCOG), Ice, Threshold, and Improved Threshold. The results showed that waveforms in the Halmahera Sea had ten generic classes with dominant class of the Browns. The validation results showed that all retrackers (except OCOG) had the value of correlations exceeding 0.75, and Root Mean Square Error (RMSE) smaller than 25 cm at a distance of 5-20 km from the land. The Threshold 10% was the most common retracker that appeared with the highest improvement percentage (IMP), meanwhile the Ice retracker consistently produced the best correlation (0.86) and the lowest RMSE (16cm). The retracking results showed that waveform retracking generally can improve SSH estimation accuracy from ocean (standard) retracker.

Revisit of a Case Study of Spilled Oil Slicks Caused by the Sanchi Accident (2018) in the East China Sea

Marine oil spills occur suddenly and pose a serious threat to ecosystems in coastal waters. Oil spills continuously affect the ocean environment for years. In this study, the oil spill caused by the accident of the Sanchi ship (2018) in the East China Sea was hindcast simulated using the oil particle-tracing method. Sea-surface winds from the European Centre for Medium-Range Weather Forecasts (ECMWF), currents simulated from the Finite-Volume Community Ocean Model (FVCOM), and waves simulated from the Simulating WAves Nearshore (SWAN) were employed as background marine dynamics fields. In particular, the oil spill simulation was compared with the detection from Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) images. The validation of the SWAN-simulated significant wave height (SWH) against measurements from the Jason-2 altimeter showed a 0.58 m root mean square error (RMSE) with a 0.93 correlation (COR). Further, the sea-surface current was compared with that from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2), yielding a 0.08 m/s RMSE and a 0.71 COR. Under these circumstances, we think the model-simulated sea-surface currents and waves are reliable for this work. A hindcast simulation of the tracks of oil slicks spilled from the Sanchi shipwreck was conducted during the period of 14–17 January 2018. It was found that the general track of the simulated oil slicks was consistent with the observations from the collected GF-3 SAR images. However, the details from the GF-3 SAR images were more obvious. The spatial coverage of oil slicks between the SAR-detected and simulated results was about 1 km2. In summary, we conclude that combining numerical simulation and SAR remote sensing is a promising technique for real-time oil spill monitoring and the prediction of oil spreading.

Influence of temporal resolution on the performance of global ionospheric maps

Global ionosphere maps (GIM) computed from dual-frequency GNSS measurements have been widely used for monitoring ionosphere as well as providing ionospheric corrections in Space Geodesy since 1998. This work focuses on a comprehensive study of the influence of time resolution on GIM performance. One and a half solar cycle of the IGS GIM with higher time resolution and accuracy (the UPC-IonSAT Quarter-of-an-hour time resolution Rapid GIM, AKA uqrg) has been taken as baseline to downsample them to all possible sub-daily temporal resolutions. The performance of the resulting GIMs has been assessed by directly comparing with external vertical total electron content (VTEC) measurements from Jason altimeters over oceanic regions. In order to perform a complete assessment and analysis of involved GIMs, the influence of geographical position and solar and geomagnetic activities was also taken into account during more than one solar cycle. In addition, to have a clear view at the smaller time resolutions, a more accurate assessment, the dSTEC test based on external GNSS measurements not used in the GIM generation was also done during two solstice and two equinox days in 2015 over continental regions. The assessment shows that discrepancy among GIMs with different time resolutions becomes more apparent at low latitudes and also at high solar-geomagnetic activity. The results also suggest that the accuracy for GIMs with time resolution smaller or equal to 60 min is consistent during the period from 2002 to 2019 and is more accurate than other GIMs with lower temporal resolution. Accordingly, high time resolution (including 15, 30, 45 and 60 min) is recommended for the application of GIMs with the highest accuracy.

Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.

Daily harmonics of ionospheric total electron content from satellite altimetry

Daily harmonics of the ionosphere’s total electron content (TEC) can be mapped using Global Navigation Satellite Systems (GNSS), as recently accomplished by Lean and colleagues. Here those harmonics are determined (over oceans only) by tidal analysis of ionospheric path delay from dual-frequency radar altimetry. Data from TOPEX, Jason-1, and Jason-2 altimeters are used, with focus on periods of medium to high solar activity. Diurnal-band signals are aliased by the altimeter sampling, but TOPEX-Jason orbits were designed to achieve acceptable tidal aliasing. Altimeter maps reveal where corresponding GNSS-based maps are in error, generally near the geomagnetic equator where high-wavenumber features are overly smoothed. When ocean tides are deduced from single-frequency altimetry, a task that relies on accurate GNSS-based ionospheric path corrections, any TEC errors leak directly into the tide solutions. TEC errors near and west of the Weddell Sea are likely problematic for the CryoSat-2 mission.

Denoising Effect of Jason-1 Altimeter Waveforms with Singular Spectrum Analysis: A Case Study of Modelling Mean Sea Surface Height over South China Sea

Altimeter waveforms are usually contaminated due to nonmarine surfaces or inhomogeneous sea state conditions. The present work aimed to present how the singular spectrum analysis (SSA) can be used to reduce the noise level in Jason-1 altimeter waveforms to obtain SSA-denoised waveforms, improving the accuracy of a mean sea surface height (MSSH) model. Comparing the retracked sea surface heights (SSHs) by a 50% threshold retracker for the SSA-denoised waveforms with those for the raw waveforms, the results indicated that SSA allowed a noise reduction on Jason-1 waveforms, improving the accuracy of retracked SSHs. The MSSH model (called Model 1) over the South China Sea with a grid of 2′ × 2′ was established from the retracked SSHs of Jason-1 by the 50% threshold retracker for the SSA-denoised waveforms. Comparing Model 1 and Model 2 (established from the retracked SSHs by the 50% threshold retracker for the raw waveforms) with the CLS15 and DTU18 models in the South China Sea, it was found that the accuracy of Model 1 was higher than that of Model 2, which indicates that using SSA to reduce noise level in Jason-1 waveforms can effectively improve the accuracy of the MSSH model.

Indian Ocean wave forecasting system for wind waves: development and its validation

ABSTRACT Present study aims at the development of the Indian Ocean wave forecasting system for wind waves using WAVEWATCH-III wave model and a detailed validation of the same to ensure the model reliability for operational use. WAVEWATCH-III model has a multi-grid approach with resolution varying from 100 km (global grid) to 4 km (coastal grid), and is driven by the 10 m wind, produced by the ECMWF meteorological model. Two different observation data sets, provided by a network of buoys and Jason-2 altimeter, have been used for the evaluationof the model skill. The reliability of the wave model is tested separately for deep and for coastal waters, and reliable (correlation > 0.8 and Scatter Index < 30%) performance is found for both areas for the year 2016. A spatial validation using the satellite data also supported the reliability of the forecast in the IO. Verification during the extreme conditions also showed an accurate performance of the model in predicting the wave heights with correlation >0.9 and Scatter Index < 20%. The overall analysis endorses the model reliability over the IO, making this model very suitable, and hence it could be used for the operational forecasting purpose and other maritime services.