Tropospheric Correction Research Articles

Estimating the slip rate on the north Tabriz fault (Iran) from InSAR measurements with tropospheric correction using 3D ray tracing technique

In this paper, interseismic deformation across the north Tabriz fault (NTF) using 17 ASAR/ENVISAT acquisitions on a single track for the period 2003–2010 have been investigated. One of the main limiting factors on the accuracy of interferometric synthetic aperture radar (InSAR) measurements comes from phase propagation delays through the troposphere. In order to retrieve millimeter velocities of interseismic deformations, it is necessary to improve the tropospheric corrections and correct interferograms. For this purpose, the 3D ray tracing technique based on eikonal equations has been used to estimate the tropospheric corrections. The corrected InSAR measurements are used to derive the interseismic displacement velocity field of the study area. The obtained velocity field has enabled us to accurately estimate the slip rate and locking depth for the NTF, using a simple elastic dislocation model. The numerical achievements show a slip rate of 5.6 ± 0.15 mm/yr below a locking depth of 14.5 ± 0.67 km for the NTF. Generally, the results of this paper are confirmed by the previous studies of the NTF parameters and some differences are due to this paper applied method for tropospheric corrections.

Evaluation of Tropospheric & Clock Errors for Precision GPS Positioning & Navigation

Positional inaccuracies in GPS are caused by severalerrors such as Ionospheric, Tropospheric, Satellite Clock, Receiver Clock etc., Instantaneous correction of these error aids in precise navigation. In the present work Original Hopfield model is considered for the tropospheric correction. The instantaneous tropospheric correction results in more precise position using GPS. The decreasing order of components on basis of effect are Ionospheric delay, Tropospheric delay, Clock error, satellite bias error, Receiver error, multipath error, Ephymeris error, random errors etc. It is a time taken process to calculate the individual error separately.so in this paper we only concentrated on simulation and analysis the tropospheric delay, clock error, ephemeris error. We used Modified Hopfield model to analysis Tropospheric delay, receiver instrumental bias for analysis Clock error in between we eliminate Ephymeris error, after obtained results are compared with and without time correction in original Hopfield model.

Tropospheric corrections for InSAR: Statistical assessments and applications to the Central United States and Mexico

The rapid expansion of SAR data availability and advancements in InSAR processing methods has enabled the formation of ground displacement time series for many parts of the world where such research was previously hindered by decorrelation due to sparse temporal sampling and SAR operating frequency. In particular, free and open data access from the European Sentinel-1 constellation and the future NASA-ISRO SAR (NISAR) mission is encouraging the global community to move towards automated, cloud-based processing that can accommodate these rapidly growing data volumes and facilitate the use of a suite of corrections to the data. A key challenge is related to path delays introduced when the radar signal propagates through the troposphere. Tropospheric corrections estimated from empirical, phase-based methods and those using independent data from weather models, GPS, and radiometers have been included in open-source packages such as TRAIN, PyAPS and GACOS. Users within the InSAR community have reported varying degrees of success using these methods in a range of areas around the world. However, the various statistical metrics used to evaluate the reliability of tropospheric corrections are not consistently applied and often depend on the area and the spatial scale over which they are evaluated. Examination of a simple metric such as the overall reduction in phase variability within an interferogram does not allow the user to determine whether the improvement was at large or short length scales. We present a review of existing tropospheric correction methods and statistical performance metrics, providing guidelines for global assessment and verification of the efficacy of tropospheric correction methods. We summarize the assumptions and limitations for each correction method as well as each statistical performance metric. We examine two regions with different atmospheric characteristics - one Sentinel-1 swath covering the central United States and one swath covering south central Mexico, including part of the Pacific coast. As the SAR community moves towards reliance on global and automated InSAR processing platforms that incorporate tropospheric corrections, approaches such as those examined here can aid researchers in their efforts to evaluate such corrections and include their uncertainties in derived products such as surface displacement time series, coseismic offsets, processes that correlate with topography, and signals with smaller magnitude or larger spatial scales such as those associated with small earthquakes, aseismic creep and slow slip events. We found that the GACOS products (leveraging the operational high resolution ECMWF weather model) outperform the other correction methods explored here on average, but this result is highly dependent on location, acquisition time, and data availability. We found spatial structure functions to be most useful for performance assessment because of their ability to convey information about performance at discrete spatial scales.

Exploring GNSS Crowdsourcing Feasibility: Combinations of Measurements for Modeling Smartphone and Higher End GNSS Receiver Performance.

GNSS receiver data crowdsourcing is of interest for multiple applications, e.g., weather monitoring. The bottleneck in this technology is the quality of the GNSS receivers. Therefore, we lay out in an introductory manner the steps to estimate the performance of an arbitrary GNSS receiver via the measurement errors related to its instrumentation. Specifically, we do not need to know the position of the receiver antenna, which allows also for the assessment of smartphone GNSS receivers having integrated antennas. Moreover, the method is independent of atmospheric errors so that no ionospheric or tropospheric correction services provided by base stations are needed. Error models for performance evaluation can be calculated from receiver RINEX (receiver independent exchange format)data using only ephemeris corrections. For the results, we present the quality of different receiver grades through parametrized error models that are likely to be helpful in stochastic modeling, e.g., for Kalman filters, and in assessing GNSS receiver qualities for crowdsourcing applications. Currently, the typical positioning precision for the latest smartphone receivers is around the decimeter level, while for a professional-grade receiver, it is within a few millimeters.

Validation of 7 Years in-Flight HY-2A Calibration Microwave Radiometer Products Using Numerical Weather Model and Radiosondes

Haiyang-2A (HY-2A) has been working in-flight for over seven years, and the accuracy of HY-2A calibration microwave radiometer (CMR) data is extremely important for the wet troposphere delay correction (WTC) in sea surface height (SSH) determination. We present a comprehensive evaluation of the HY-2A CMR observation using the numerical weather model (NWM) for all the data available period from October 2011 to February 2018, including the WTC and the precipitable water vapor (PWV). The ERA(ECMWF Re-Analysis)-Interim products from European Centre for Medium-Range Weather Forecasts (ECMWF) are used for the validation of HY-2A WTC and PWV products. In general, a global agreement of root-mean-square (RMS) of 2.3 cm in WTC and 3.6 mm in PWV are demonstrated between HY-2A observation and ERA-Interim products. Systematic biases are revealed where before 2014 there was a positive WTC/PWV bias and after that, a negative one. Spatially, HY-2A CMR products show a larger bias in polar regions compared with mid-latitude regions and tropical regions and agree better in the Antarctic than in the Arctic with NWM. Moreover, HY-2A CMR products have larger biases in the coastal area, which are all caused by the brightness temperature (TB) contamination from land or sea ice. Temporally, the WTC/PWV biases increase from October 2011 to March 2014 with a systematic bias over 1 cm in WTC and 2 mm in PWV, and the maximum RMS values of 4.62 cm in WTC and 7.61 mm in PWV occur in August 2013, which is because of the unsuitable retrieval coefficients and systematic TB measurements biases from 37 GHz band. After April 2014, the TB bias is corrected, HY-2A CMR products agree very well with NWM from April 2014 to May 2017 with the average RMS of 1.68 cm in WTC and 2.65 mm in PWV. However, since June 2017, TB measurements from the 18.7 GHz band become unstable, which led to the huge differences between HY-2A CMR products and the NWM with an average RMS of 2.62 cm in WTC and 4.33 mm in PWV. HY-2A CMR shows high accuracy when three bands work normally and further calibration for HY-2A CMR is in urgent need. Furtherly, 137 global coastal radiosonde stations were used to validate HY-2A CMR. The validation based on radiosonde data shows the same variation trend in time of HY-2A CMR compared to the results from ECMWF, which verifies the results from ECMWF.

Improved Algorithms for the Measurement of Total Precipitable Water and Cloud Liquid Water from SARAL Microwave Radiometer Observations

SARAL carried onboard a radar altimeter that provides very precise measurements of the sea surface height (SSH). Like other altimetric missions, SARAL carries a passive microwave radiometer (PMR) for wet tropospheric correction to SSH. In the present study, new algorithms are developed for the retrieval of cloud liquid water (CLW) and total precipitable water vapor (TPW) over the global oceans from PMR measurements of the brightness temperatures. A radiative transfer and genetic algorithm based retrieval scheme is proposed for the estimation of CLW and TPW from SARAL PMR. The comparisons of CLW from PMR with independent measurements from GPM-GMI and SSMIS within and outside ±40° latitudes show correlation (R) of 0.86 and 0.83, bias of 0.7 and −3.61 mg/cm2, and root mean square error (RMSE) of 8.42 and 8.07 mg/cm2, respectively. Similarly, TPW from PMR with GPM-GMI and SSMIS show R of 0.99 and 0.98, bias of −0.04 and −0.03 g/cm2 and RMSE of 0.17 and 0.17 g/cm2, respectively. The retrieval accuracy of CLW and TPW from the new algorithms is compared with these parameters provided in the SARAL geophysical data records as finished products, which showed substantial improvement in the quality of the parameters from the new algorithm.

A Spatially Varying Scaling Method for InSAR Tropospheric Corrections Using a High‐Resolution Weather Model

AbstractVariation in tropospheric delay is a major limiting factor on the accuracy of interferometric synthetic aperture radar (InSAR) measurements. This is particularly the case when deformation and topography are correlated. To address limitations of previous InSAR tropospheric correction methods, here we present a new approach that combines the use of both external weather model data and the interferometric phase. We assume that vertical refractivity profiles calculated from a high‐resolution weather model data can generally describe the form of the relationship between tropospheric delay and height but that the magnitude can be incorrect. We estimate a magnitude correction by scaling the original delays to best match the interferometric phase. We validated our new method using simulated data and demonstrate that both coseismic and interseismic signals can be separated from strong tropospheric delays. We also applied our algorithm to the central portion of the Altyn Tagh Fault in northern Tibet, where deformation correlates strongly with topographic relief of 6,000 m, and show that the derived velocity field is more internally consistent and agrees better with independent Global Positioning System measurements.

Estimation of Tropospheric and Ionospheric Delay in DInSAR Calculations: Case Study of Areas Showing (Natural and Induced) Seismic Activity

The article presents a proposal to make simultaneous allowance for both ionospheric and tropospheric corrections in differential synthetic aperture radar interferometry (DInSAR) measurements. Atmospheric delay in the interferometric phase may cause the detection of terrain-surface changes to be impossible or significantly distorted. This fact remains of special importance in the case of surface changes that show limited amplitude and spatial range. Two areas were chosen to verify the validity of the proposed solution. The first area includes terrains affected by underground copper-ore mining activity (Poland), which shows high induced seismic activity. Mining tremors recorded in this area cause the terrain surface to locally subside. The authors analyzed three tremors that were recorded in 2016, 2017, and 2019. Each of the tremors exceeded a magnitude of Mw 4.0. The second area is located in the coastal region of Chile, in the Cardenal Caro province. In this case, the authors focused on a series of three earthquakes recorded on 11 March 2010. The strongest of the earthquakes was of Mw 7.0 magnitude. In the first case, calculations were based on obtained data from the Sentinel 1 satellites, and in the second case from the ALOS-1 satellite. It is demonstrated that simultaneous allowance for both the tropospheric and ionospheric corrections significantly improves the final results. The authors were also able to use the analyzed cases to demonstrate that implementation of the corrections does not have negative influence on the range and magnitude of local ground-surface deformations. At the same time, such implementation minimizes local displacement fluctuations and reduces displacement values in areas affected by deformations. The examples used in the article served to show that tropospheric correction is mainly responsible for global corrections (i.e., within the whole analyzed spatial range), while ionospheric correction reduces local fluctuations.

Robust, Long-term Lake Level Change from Multiple Satellite Altimeters in Tibet: Observing the Rapid Rise of Ngangzi Co over a New Wetland

Satellite altimetry has been successfully applied to monitoring water level variation of global lakes. However, it is still difficult to retrieve accurate and continuous observations for most Tibetan lakes, due to their high altitude and rough terrain. Aiming to generate long-term and accurate lake level time series for the Tibetan lakes using multi-altimeters, we present a robust strategy including atmosphere delay corrections, waveform retracking, outlier removal and inter-satellite bias adjustment. Apparent biases in dry troposphere corrections from different altimeter products are found, and such correctios must be recalculated using the same surface pressure model. A parameter is defined to evaluate the performance of the retracking algorithm. The ICE retracker outperforms the 20% and 50% threshold retrackers in the case of Ngangzi Co, where a new wetland has been established. A two-step algorithm is proposed for outlier removal. Two methods are adopted to estimate inter-satellite bias for different cases of with and without overlap. Finally, a 25-year-long lake level time series of Ngangzi Co are constructed using the TOPEX/Poseidon-family altimeter data from October 1992 to December 2017, resulting in an accuracy of ~17 cm for TOPEX/Poseidon and ~10 cm for Jason-1/2/3. The accuracy of retrieved lake levels is on the order of decimeter. Because of no gauge data available, ICESat and SARAL data with the accuracy better than 7 cm are used for validation. A correlation more than 0.9 can be observed between the mean lake levels from TOPEX/Poseidon-family satellites, ICESat and SARAL. Compared to the previous studies and other available altimeter-derived lake level databases, our result is the most robust and has resulted in the maximum number of continuous samples. The time series indicates that the lake level of Ngangzi Co increased by ~8 m over 1998–2017 and changed with different rates in the past 25 years (-0.39 m/yr in 1992–1997, 1.03 m/yr in 1998–2002 and 0.32 m/yr in 2003–2014). These findings will enhance the understanding of water budget and the effect of climate change.

Independent Assessment of On-Board Microwave Radiometer Measurements in Coastal Zones Using Tropospheric Delays From GNSS

Zenith tropospheric delays (ZTDs) computed at a network of 60 global navigation satellite system (GNSS) stations have been used to assess microwave radiometer (MWR) measurements from eight altimeter missions in coastal zones, where some of these observations become invalid. Results show that ZTDs are determined with an accuracy of a few millimeters; however, jumps are detected in some stations in standard products. The comparison between the MWR-derived wet tropospheric correction (WTC) and the GNSS-derived WTC at the nearby coastal stations illustrates the effect of land contamination in the MWR measurements and yields the distance from coast at which this contamination appears. This distance is different for the analyzed altimetric missions, due to their different footprint sizes and different MWR retrieval algorithms, varying from 10 to 30 km. The root mean square of the differences between GNSS and MWR-derived WTC, at the closest distance at which no land contamination occurs, is in the range of 1.6–1.9 cm for all missions. This coastal assessment also shows the ability of the GNSS-derived path delay plus algorithm to remove this land contamination and to improve the WTC retrieval. Aiming at inspecting the long-term stability of the MWR measurements, the comparisons with GNSS show nonsignificant differences and drifts less than 0.3 mm/year. Therefore, the GNSS-derived WTC is a useful independent source to inspect the land effects on MWR observations and to monitor the stability of these instruments, thus contributing to the retrieval of precise water surface heights from satellite altimetry.

A 1D-Var Approach to Retrieve Clear-Sky Wet Tropospheric Correction from Current and Future Altimetry Missions

AbstractStatistical methods are usually used to provide estimations of the wet tropospheric correction (WTC), necessary to correct altimetry measurements for atmospheric path delays, using brightness temperatures measured at two or three low frequencies from a passive microwave radiometer on board the altimeter mission. Despite their overall accuracy over oceanic surfaces, uncertainties still remain in specific regions of complex atmospheric stratification. Thus, there is still a need to improve the methods currently used by taking into account the frequency-dependent information content of the observations and the atmospheric and surface variations in the surroundings of the observations. In this article we focus on the assimilation of relevant passive microwave observations to retrieve the WTC over ocean using different altimeter mission contexts (current and future, providing brightness temperature measurements at higher frequencies in addition to classical low frequencies). Data assimilation is performed using a one-dimensional variational data assimilation (1D-Var) method. The behavior of the 1D-Var is evaluated by verifying its physical consistency when using pseudo- and real observations. Several observing-system simulation experiments are run and their results are analyzed to evaluate global and regional WTC retrievals. Comparisons of 1D-Var-based TWC retrieval and reference products from classical WTC retrieval algorithms or radio-occultation data are also performed to assess the 1D-Var performances.

WET TROPOSPHERIC CORRECTION’S IMPACT ON SEA LEVEL ANOMALY AROUND THE INDONESIAN SEAS

Global sea level rise in the satellite altimetry era is about 3 mm/yr. The one of main source of uncertainty of global sea level is the wet tropospheric from onboard microwave radiometer which is up to 0.3 mm/yr. The focus of this study is to assess of various wet tropospheric correction impact on sea level anomaly in the Indonesian seas. The result of sea level anomaly linear trend difference between Global Navigation Satellite System and Microwave Radio Meter or ECMWF Re-Analysis Interim is 0.18 mm/yr in agreement with the global wet tropospheric uncertainty.

Analysis of the Effect of Tropospheric Delay on Orthometric Height Determination at High Mountain

The purpose of this study is to precisely determine the orthometric height considering tropospheric delay at the top of the mountain where the height difference with reference ground surface is large. So, GNSS surveying was carried out at Cheonwangbong on Mount Jiri to determine the orthometric height, and GNSS data were processed by both DGNSS and PPP methods to determine ellipsoidal height using Bernese version 5.0 software. In this process, KNGeoid14 Korean geoid model was used and the effects of troposphere delay on the coordinates and orthometric height were analyzed. The study results showed that the tropospheric delay was reduced by 3.04 cm with every 100 m increase of the ellipsoidal height. The orthometric height and RMSE determined by the DGNSS method were found to be 1915.4596 m and 0.0520 m, respectively, and the orthometric height and RMSE determined by the PPP method were found to be 1915.4059 m and 0.0527 m, respectively. So, the difference between the DGNSS method and the PPP method when tropospheric corrections were applied showed a difference of 5.37 cm in orthometric height. And, the results also showed that the difference in whether or not the tropospheric delay model was applied in the calculation of the orthometric height was 1.53 cm in the same DGNSS method.

Fenofibrate and Atorvastatin Have Opposite Effects on the Vascularization and Characteristics of Visceral Adipose Tissue in New Zealand White Rabbits

Unlike previous altimetric missions, the CryoSat-2 altimeter features a novel Synthetic Aperture Radar (SAR) mode that allows higher resolution and more accurate altimeter-derived parameters in the coastal zone, thanks to the reduced along-track footprint. The scope of this study is to quantify regionally the skills of CryoSat-2 SAR altimetry for distances to coast smaller than 10 km, during the mission lifetime and at different time scales. The validated geophysical altimeter parameters are the sea surface height above the ellipsoid, the significant sea wave height and wind speed, all computed at 20 Hz. These have been compared to in situ and regional model data along the coasts of German Bight and West Baltic Sea during a time interval of almost six years, from July 2010 to March 2016, to investigate both instantaneous and seasonal behaviour.From CryoSat-2 FBR (Full Bit Rate) data, a Delay-Doppler processing and waveform retracking tailored specifically to the coastal zone has been carried out, by applying a Hamming window and zero-padding, using an extended vertical swath window in order to mitigate tracker errors. Moreover, a dedicated SAMOSA-based coastal retracker (here referred to as SAMOSA+) has also been implemented.Since one of the highest remaining uncertainties in the altimeter parameters estimated in coastal shallow waters arises from residual errors in the applied range and geophysical corrections, innovative and high resolution solutions for ocean tide model, geoid, mean sea surface and wet tropospheric correction have been selected. As CryoSat-2 SAR and LRM (Low Rate Mode) modes are not collocated in time, in order to quantify the improvement in the coastal zone with respect to pulse-limited altimetry, 20 Hz PLRM (pseudo-LRM) data from CryoSat-2 FBR were built and retracked, adopting the ALES adaptive sub-waveform approach, with a numerical Brown-based retracker, here referred to as TALES.The cross-validation proves the good consistency between PLRM and SAR sea level anomaly in the coastal zone. The regional ocean model (BSH) shows the highest agreement with the SAR sea level anomaly, with a standard deviation of the differences (stdd) of 24 cm, whereas the corresponding value with respect to PLRM is 55 cm. Distance to coast plots show that land contamination begins to affect sea level and wave measurements at 2 km from the coast in SAR and at 3.5 km in PLRM TALES. The analysis of monthly mean time-series shows that SAR Altimetry is able to measure the sea level monthly mean in the coastal zone of the region of interest, during the entire mission, more precisely than PLRM. The cross-validation against in situ data also proves the higher accuracy of SAR SAMOSA+ compared to PLRM TALES in the coastal zone, with average SLA stdd of 4.4 cm and 8.4 cm respectively.

A two-stage tropospheric correction model combining data from GNSS and numerical weather model

We have developed a new concept for providing tropospheric augmentation corrections. The two-stage correction model combines data from a Numerical Weather Model (NWM) and precise ZTDs estimated from Global Navigation Satellite System (GNSS) permanent stations in regional networks. The first-stage correction is generated using the background NWM forecast only. The second-stage correction results from an optimal combination of the background model data and GNSS (near) real-time tropospheric products. The optimum correction is achieved when using NWM for the hydrostatic delay modeling and for vertical scaling, while GNSS products are used for correcting the non-hydrostatic delay. The method is assessed in several variants including study of the combination of NWM and GNSS data, spatial densification of the original NWM grid, and GNSS ZTD densification using tropospheric linear horizontal gradients. The first-stage correction can be characterized by overall accuracy of about 10 mm for ZTD (1-sigma). The second-stage correction supported with GNSS tropospheric products improved the first-stage correction by a factor of 2–4 in terms of the ZTD accuracy and by a factor of 2.5 in terms of its spatio-temporal stability.

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.

An estimation of tropospheric corrections using GPS and synoptic data: Improving Urmia Lake water level time series from Jason-2 and SARAL/AltiKa satellite altimetry

Tropospheric correction is one of the most important corrections in satellite altimetry measurements. Tropospheric wet and dry path delays have strong dependence on temperature, pressure and humidity. Tropospheric layer has particularly high variability over coastal regions due to humidity, wind and temperature gradients. Depending on the extent of water body and wind conditions over an inland water, Wet Tropospheric Correction (WTC) is within the ranges from a few centimeters to tens of centimeters. Therefore, an extra care is needed to estimate tropospheric corrections on the altimetric measurements over inland waters. This study assesses the role of tropospheric correction on the altimetric measurements over the Urmia Lake in Iran. For this purpose, four types of tropospheric corrections have been used: (i) microwave radiometer (MWR) observations, (ii) tropospheric corrections computed from meteorological models, (iii) GPS observations and (iv) synoptic station data. They have been applied to Jason-2 track no. 133 and SARAL/AltiKa track no. 741 and 356 corresponding to 117–153 and the 23–34 cycles, respectively. In addition, the corresponding measurements of PISTACH and PEACHI, include new retracking method and an innovative wet tropospheric correction, have also been used. Our results show that GPS observation leads to the most accurate tropospheric correction. The results obtained from the PISTACH and PEACHI projects confirm those obtained with the standard SGDR, i.e., the role of GPS in improving the tropospheric corrections. It is inferred that the MWR data from Jason-2 mission is appropriate for the tropospheric corrections, however the SARAL/AltiKa one is not proper because Jason-2 possesses an enhanced WTC near the coast. Furthermore, virtual stations are defined for assessment of the results in terms of time series of Water Level Height (WLH). The results show that GPS tropospheric corrections lead to the most accurate WLH estimation for the selected virtual stations, which improves the accuracy of the obtained WLH time series by about 5%.

Evaluation of Coastal Sea Level Offshore Hong Kong from Jason-2 Altimetry

As altimeter satellites approach coastal areas, the number of valid sea surface height measurements decrease dramatically because of land contamination. In recent years, different methodologies have been developed to recover data within 10–20 km from the coast. These include computation of geophysical corrections adapted to the coastal zone and retracking of raw radar echoes. In this paper, we combine for the first time coastal geophysical corrections and retracking along a Jason-2 satellite pass that crosses the coast near the Hong-Kong tide gauge. Six years and a half of data are analyzed, from July 2008 to December 2014 (orbital cycles 1–238). Different retrackers are considered, including the ALES retracker and the different retrackers of the PISTACH products. For each retracker, we evaluate the quality of the recovered sea surface height by comparing with data from the Hong Kong tide gauge (located 10 km away). We analyze the impact of the different geophysical corrections available on the result. We also compute sea surface height bias and noise over both open ocean (>10 km away from coast) and coastal zone (within 10 km or 5 km coast-ward). The study shows that, in the Hong Kong area, after outlier removal, the ALES retracker performs better in the coastal zone than the other retrackers, both in terms of noise level and trend uncertainty. It also shows that the choice of the ocean tide solution has a great impact on the results, while the wet troposphere correction has little influence. By comparing short-term trends computed over the 2008.5–2014 time span, both in the coastal zone and in the open ocean (using the Climate Change Initiative sea level data as a reference), we find that the coastal sea level trend is about twice the one observed further offshore. It suggests that in the Hong Kong region, the short-term sea level trend significantly increases when approaching the coast.

Assessment of radar altimetry correction slopes for marine gravity recovery: A case study of Jason-1 GM data

Marine gravity anomaly derived from satellite altimetry can be computed using either sea surface height or sea surface slope measurements. Here we consider the slope method and evaluate the errors in the slope of the corrections supplied with the Jason-1 geodetic mission data. The slope corrections are divided into three groups based on whether they are small, comparable, or large with respect to the 1 microradian error in the current sea surface slope models. (1) The small and thus negligible corrections include dry tropospheric correction, inverted barometer correction, solid earth tide and geocentric pole tide. (2) The moderately important corrections include wet tropospheric correction, dual-frequency ionospheric correction and sea state bias. The radiometer measurements are more preferred than model values in the geophysical data records for constraining wet tropospheric effect owing to the highly variable water-vapor structure in atmosphere. The items of dual-frequency ionospheric correction and sea state bias should better not be directly added to range observations for obtaining sea surface slopes since their inherent errors may cause abnormal sea surface slopes and along-track smoothing with uniform distribution weight in certain width is an effective strategy for avoiding introducing extra noises. The slopes calculated from radiometer wet tropospheric corrections, and along-track smoothed dual-frequency ionospheric corrections, sea state bias are generally within ±0.5 microradians and no larger than 1 microradians. (3) Ocean tide has the largest influence on obtaining sea surface slopes while most of ocean tide slopes distribute within ±3 microradians. Larger ocean tide slopes mostly occur over marginal and island-surrounding seas, and extra tidal models with better precision or with extending process (e.g. Got-e) are strongly recommended for updating corrections in geophysical data records.

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.