Satellite Radar Altimetry Data Research Articles

Contribution of automatically generated radar altimetry water levels from unsupervised classification to study hydrological connectivity within Amazon floodplains

Study regionThe Curuaí floodplain in the low Amazon river in the Pará state of Brazil and Juruá basin, a major Solimões tributary. Study focusCharacterizing the hydrological dynamics of Amazon floodplains is essential to better understand and preserve these environments providing important resources to local populations. Radar altimetry is an effective remote sensing tool for monitoring water levels of continental hydrosystems, including floodplains. An unsupervised classification approach on radar echoes to determine hydrological regimes has recently been tested and showed a strong potential on the Congo River basin. This method is adapted to Envisat and Saral satellite radar altimetry data on two study areas in the Amazon Basin. The aim is to improve inland water detection along altimeter tracks to automatically generate water level time series (WLTS) over rivers, lakes, and poorly monitored floodplains and wetlands. New hydrological insightsResults show a good agreement with land cover maps obtained with optical imagery over selected Amazonian wetlands (70–80% accuracies with Envisat data and 50–60% with Saral data). Automatically generated WLTS are strongly correlated to the manually generated WLTS (R² ≈ 0.9; RMSE < 1 m). Compared to the manual method, the automatic method is faster, more efficient and replicable. Densifying the WL network in the floodplains bring crucial information on the connectivity dynamic between lakes and rivers.

A comparison between Envisat and ICESat sea ice thickness in the Southern Ocean

Abstract. The crucial role that Antarctic sea ice plays in the global climate system is strongly linked to its thickness. While field observations are too sparse in the Southern Ocean to determine long-term trends of the Antarctic sea ice thickness (SIT) on a hemispheric scale, satellite radar altimetry data can be applied with a promising prospect. The European Space Agency's Sea Ice Climate Change Initiative project (ESA SICCI) generates sea ice thickness derived from Envisat, covering the entire Southern Ocean year-round from 2002 to 2012. In this study, the SICCI Envisat Antarctic SIT is first compared with an Ice, Cloud, and land Elevation Satellite (ICESat) SIT product retrieved with a modified ice density algorithm. Both data sets are compared to SIT estimates from upward-looking sonar (ULS) in the Weddell Sea, showing mean differences (MDs) and standard deviations (SDs, in parentheses) of 1.29 (0.65) m for Envisat − ULS (− denotes “minus” and the same below), while we find 1.11 (0.81) m for ICESat − ULS. The inter-comparisons are conducted for all seasons except for winter, based on the ICESat operating periods. According to the results, the differences between Envisat and ICESat SIT reveal significant temporal and spatial variations. More specifically, the smallest seasonal SIT MD (SD) of 0.00 m (0.39 m) for Envisat − ICESat is found in spring (October–November), while a larger MD (SD) of 0.52 (0.68 m) and 0.57 m (0.45 m) exists in summer (February–March) and autumn (May–June). It is also shown that from autumn to spring, mean Envisat SIT decreases while mean ICESat SIT increases. Our findings suggest that both overestimation of Envisat sea ice freeboard potentially caused by radar backscatter originating from inside the snow layer and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E, where EOS stands for Earth Observing System) snow depth biases and sea ice density uncertainties can possibly account for the differences between Envisat and ICESat SIT.

Land Subsidence Estimation With Tide Gauge and Satellite Radar Altimetry Measurements Along the Texas Gulf Coast, USA

A double difference (DD) method was employed to estimate vertical land motion (VLM) at 26 tide gauge (TG) sites with record lengths of at least ten years across the Texas Gulf Coast, USA, between 1993 and 2020. In the method, the first difference was conducted by coupling nearby correlated TG stations to remove sea-level variability for both TG and satellite radar altimetry (SRA) data. Upon completion of the first difference, a second difference was performed by subtracting between TG and SRA data. Results obtained from the DD method were compared against that of: 1) a single difference (SD) method through subtraction between measurements from TG and SRA, and 2) a global navigation satellite system (GNSS) precise point positioning (PPP) method. Results showed that the DD method improved the performance of VLM estimation with an uncertainty below 1.0 mm/yr at most TG stations. Meanwhile, the estimated VLM trends acquired from the DD method correlated better to that of the ground-truth GNSS PPP solutions than the SD method. The DD method possesses great potential to discover VLM knowledge, particularly along coastal regions where other techniques such as GNSS and interferometric synthetic aperture radar (InSAR) are of impaired estimation capability.

Characterizing slope correction methods applied to satellite radar altimetry data: A case study around Dome Argus in East Antarctica

Slope correction is important to improve the accuracy of satellite radar elevation measurements by mitigating the slope-induced error (SE), especially over uneven ground surfaces. Although several slope correction methods have been proposed, guidance in the form of stepwise algorithm on how to implement these methods in processing radar altimetric data at the coding level, and the differences among these methods need to be presented and discussed systematically. In this paper, three existing types of slope correction methods—the direct method (DM), intermediate method (IM), and relocation method (RM, further divided into RM1 and RM2)—are described in detail. In addition, their main differences and features for various scientific applications are analyzed. We conduct a systematic experiment with CryoSat-2 Low Resolution Mode (LRM) data in a physically stable area around Dome Argus in East Antarctica, where in-situ measurements were available for comparison. The slope correction is implemented separately using the three methods, with the latest high-accuracy Reference Elevation Model of Antarctica (REMA) as the a-priori topography model. The bias and precision of the slope-corrected CryoSat-2 data results from the RM2 is −0.18 ± 0.86 m based on the comparison with the field Global Navigation Satellite System (GNSS) data. The results from the RM2 indicate higher precision compared to those from the RM1. According to the correlation analysis of the slope-corrected CryoSat-2 data results (RM1 and RM2), the bias enlarges and the precision becomes worse when the surface slope increases from 0 to 0.85°. After a comprehensively comparative analysis, we find that the results from the RM1 and RM2 are superior in precision (0.93 m and 0.86 m) with respect to the GNSS data. The relatively low precision (1.22 m) from the IM is due to the potential error from the a-priori digital elevation model (DEM). The DM has the lowest precision (2.66 m). Another experiment over rough topography in West Antarctica is carried out for comparison, especially between the RM1 (precision of 15.27 m) and RM2 (precision of 16.25 m). In general, the RM is recommended for the SE elimination among the three methods. Moreover, the RM2 is firstly considered over smooth topography due to the superior performance in bias and precision, while the RM1 is more suggested over the rough topography because of the slightly smaller bias and better precision. The IM relies much on the accuracy of the a-prior DEM and is not usually recommended, because of the strict requirement in the sampling time between the radar altimetry data and the a-priori DEM to avoid any surface change over time.

Altimetry-derived surface water data assimilation over the Nile Basin

Global hydrological models facilitate studying of water resources and their variations over time. The accuracies of these models are enhanced when combined with ever-increasing satellite remotely sensed data. Traditionally, these combinations are done via data assimilation approach, which permits the use of improved hydrological outputs to study regions with limited in-situ measurements such as the Nile Basin. This study aims at using the state-of-art satellite radar altimetry data to enhance a land-based hydrological model for studying water storage changes over the Nile Basin. Altimetry-derived surface water storage, for the first time, is assimilated into the model using the ensemble Kalman filter (EnKF) for the period of 2003 to 2016. Multiple datasets from ground measurements, as well as space observations, are used to evaluate the performance of the assimilated satellite altimetry data. Results indicate that the assimilation successfully improves model outputs, especially the surface water component. The process increases the correlation between surface water storage changes and water level variations from satellite radar altimetry by 0.44 and reduces the surface water discharge root-mean-square errors (RMSE) by approximately 33%.

Characterizing channel-floodplain connectivity using satellite altimetry: Mechanism, hydrogeomorphic control, and sediment budget

In this study, the mechanism of channel-floodplain seasonal connectivity along the Amazon River is analyzed over a full hydrological year through the use of satellite radar altimetry data (Jason-2). This is done via a novel observation-based approach which employs the concurrent measurement of water levels (WLs) over river and floodplain, analyzing seasonal changes in water surface height differences between the two water bodies. Hydrological connectivity thresholds at different stages during the rising phase were identified, and then validated using field data and remote sensing-driven surface suspended sediment maps. Successful decoupling of the two indiscrete flooding processes during the rising phase: channelized and overbank dispersion processes, is one of the major outcomes of this study. Different roles of the connectivity processes on floodplain hydrogeomorphology are highlighted – that channelized flows determine inundation frequency, residence time and development of positive topographic features in the floodplain, while overbank flows contribute a good part of the seasonal water storage and sediment budget in the floodplain, and tends to smooth positive topography built by channelized flows. The zones of overbank flooding, however, are rather localized due to the well-developed natural levee complex and stable channel-dominated floodplain along the river bank. Lastly, the presented approach is straightforward and solely based on publicly available operational data, making it easily adaptable by non-remote sensing experts. Thus, along with the emergence of new radar altimetry platforms, such as ICESat-2 or Jason-3 that could measure WL of smaller lakes, the proposed approach offers the potential to contribute to research on channel-floodplain systems in other rivers at a global scale.

Vertical land motion and relative sea level changes along the coastline of Brest (France) from combined space-borne geodetic methods

In spite of the recent advances and the current perspectives of satellite radar altimetry to reach the coastline and monitor coastal sea level changes, this space-borne technology remains geocentric by essence. In contrast, the quantity that matters for coastal management and society is relative sea level. That is, the sea level relative to the land, as measured by conventional tide gauges. However, two important issues are associated with the use of tide gauges. First, supplemental information is required to separate vertical land motion from ocean climate signals in tide gauge records, and hence to understand the causes of future coastal sea level changes and their relative importance. This can be provided by space-borne geodetic techniques, for instance installing a permanent Global Positioning System (GPS) antenna at the tide gauge. Second, vertical land motion can show local spatial patterns, which limits the spatial validity of the point-wise information at the GPS station. Using Interferometry Synthetic Aperture Radar (InSAR) and high-precision GPS data, the above-mentioned limitations were addressed in the case study of Brest (France). Our findings show that, over the past decades, Brest and its surroundings are overall stable, in agreement with the geological setting, except for the embankment areas of the commercial and military harbours. The GPS-calibrated InSAR results were then further combined with geocentric satellite radar altimetry data to obtain relative sea level trends along the Brest coastline with an unprecedented high-spatial resolution of 200 m. Our approach is applicable beyond the case study of Brest, especially in coastal areas where tide gauge data are not available, provided satellite data are.

Restoring the perennial Great Ruaha River using ecohydrology, engineering and governance methods in Tanzania

The Great Ruaha River (GRR) in Tanzania was perennial before 1993. Its source, the Usangu wetlands, was also perennial. Since then, the GRR has started drying out during the dry season, with a trend towards earlier and longer periods of drying. This drying process degrades the surrounding ecosystems along the entire length of the GRR, including the Ruaha National Park (RNP) and impacts human livelihoods throughout its course; it also impairs the economy of Tanzania through reduced hydropower generation at the Mtera and Kidatu power plants. The Usangu wetlands dried up in 2000, 2002 and 2005 during the dry season and its areal extent has been shrinking. Intensive livestock grazing and both dry and wet season irrigated agriculture in the Usangu wetlands, were the main reasons for this water crisis. In 2006, the Government of Tanzania moved to address the crisis by removing livestock from the Usangu wetlands, attempting to regulate water use in the GRR catchment and expanding the RNP to include the Usangu wetlands.The present study uses satellite radar altimetry data dated 1992 to 2015 for the Usangu wetlands, verified using data from water level loggers, to assess the effects of these hydrological changes. The combined data sets show that the perennial Usangu wetlands have become re-established, though somewhat diminished in size, and that as a result of eutrophication from fertilizers leached from irrigated fields, 95% of their surface is now covered by floating vegetation, resulting in reduced loss of water by evaporation. This reduction has extended the water flow to the GRR by one to two months. These figures highlight the important role played by the wetlands vegetation in controlling the water budget.The hydrological model of the Usangu wetlands was further developed and verified, and then used to justify the construction of a low-level V-notch weir at the outlet of the Usangu wetlands; by slowing down the outflow from the wetlands, this construction would reduce the period of zero flow in the GRR during the dry season by one to two months. Additional ecohydrological solutions based on the improvement of water governance upstream of the Usangu wetlands, such as controlling rice and horticultural irrigation activities along the length of the GRR, should be integrated with this engineering solution; this would meet the hydrological needs of the water users all along the GRR.

Automated Generation of Lakes and Reservoirs Water Elevation Changes From Satellite Radar Altimetry

Limited access to in-situ water level data for lakes and reservoirs have been a major setback for regional and global studies of reservoirs, surface water storage changes, and monitoring the hydrologic cycle. Processing satellite radar altimetry data over inland water bodies on a large scale has been a cumbersome task primarily due to the removal of contaminated measurements as a result of surrounding land. In this study, we proposed a new algorithm to automatically generate time series from raw satellite radar altimetry data without user intervention. With this method, users with a little knowledge on the field can now independently process radar altimetry for diverse applications. The method is based on K-means clustering, interquartile range, and statistical analysis of the dataset for outlier detection. Jason-2 and Envisat radar altimetry data were used to demonstrate the capability of this algorithm. A total of 37 satellite crossings over 30 lakes and reservoirs located in the U.S., Brazil, and Nigeria were used based on the availability of in-situ data. We compared the results against in-situ data and root-mean-square error values ranged from 0.09 to 1.20 m. We also confirmed the potential of this algorithm over rivers and wetlands using the southern Congo River and Everglades wetlands in Florida, respectively. Finally, the different retracking algorithms in Envisat; Ice-1, Ice-2, Ocean, and Sea-Ice were compared using the proposed algorithm. Ice-1 performed best for generating water level time series for in-land water bodies and the result is consistent with previous studies.

CryoSat-2 Altimetry Applications over Rivers and Lakes

Monitoring the variation of rivers and lakes is of great importance. Satellite radar altimetry is a promising technology to do this on a regional to global scale. Satellite radar altimetry data has been used successfully to observe water levels in lakes and (large) rivers, and has also been combined with hydrologic/hydrodynamic models. Except CryoSat-2, all radar altimetry missions have been operated in conventional low resolution mode with a short repeat orbit (35 days or less). CryoSat-2, carrying a Synthetic Aperture Radar (SAR) altimeter, has a 369-day repeat and a drifting ground track pattern and provides new opportunities for hydrologic research. The narrow inter-track distance (7.5 km at the equator) makes it possible to monitor many lakes and rivers and SAR mode provides a finer along-track resolution, higher return power and speckle reduction through multi-looks. However, CryoSat-2 challenges conventional ways of dealing with satellite inland water altimetry data because virtual station time series cannot be directly derived for rivers. We review the CryoSat-2 mission characteristics, data products, and its use and perspectives for inland water applications. We discuss all the important steps in the workflow for hydrologic analysis with CryoSat-2, and conclude with a discussion of promising future research directions.

Mean Sea Surface and ocean circulation in North Atlantic and the Arctic Sea

High resolution Mean Sea Surface (MSS) model and its error estimation over the study region (56°N<ϕ<82°N, 45°W<λ<33°E) have been determined to evaluate Mean Dynamic Topography (MDT) in the Fram Strait and adjacent seas. Multiple high-latitude observing satellite radar altimetry data were used to determine a new MSS model that, hereafter, is called NTNU MSS. Sea Surface Height (SSH) values of the NTNU MSS model vary between 15 to 70 m over the study region, and the internal consistency or the quality estimate for the model ranges from 1 to 5 cm. External comparisons have been performed to validate the NTNU model applying available MSS models such as KMS04, mean and Standard Deviations (SD) of the differences are 1.7 cm and 8.9 cm, respectively. To assess the compatibility of the NTNU MSS model, residual analysis has been carried out relative to geoid and Oceanographic MDT (OMDT) models. Utilizing OCTAS04 geoid and OCCAM MDT models, the SD and mean of the residuals are 13.1 cm and 10.1 cm, respectively. Finally, the surface geostrophic velocities have been computed and compared with the velocities extracted from the OCCAM and KMS04. Differences between the geostrophic velocities derived from the NTNU Synthetic MDT (SMDT) and the OCCAM OMDT are 4.97 and 2.94 cm/s for the mean and SD values.

A new 1 km digital elevation model of the Antarctic derived from combined satellite radar and laser data – Part 1: Data and methods

Abstract. Digital elevation models (DEMs) of the whole of Antarctica have been derived, previously, from satellite radar altimetry (SRA) and limited terrestrial data. Near the ice sheet margins and in other areas of steep relief the SRA data tend to have relatively poor coverage and accuracy. To remedy this and to extend the coverage beyond the latitudinal limit of the SRA missions (81.5° S) we have combined laser altimeter measurements from the Geosciences Laser Altimeter System onboard ICESat with SRA data from the geodetic phase of the ERS-1 satellite mission. The former provide decimetre vertical accuracy but with poor spatial coverage. The latter have excellent spatial coverage but a poorer vertical accuracy. By combining the radar and laser data using an optimal approach we have maximised the vertical accuracy and spatial resolution of the DEM and minimised the number of grid cells with an interpolated elevation estimate. We assessed the optimum resolution for producing a DEM based on a trade-off between resolution and interpolated cells, which was found to be 1 km. This resulted in just under 32% of grid cells having an interpolated value. The accuracy of the final DEM was assessed using a suite of independent airborne altimeter data and used to produce an error map. The RMS error in the new DEM was found to be roughly half that of the best previous 5 km resolution, SRA-derived DEM, with marked improvements in the steeper marginal and mountainous areas and between 81.5 and 86° S. The DEM contains a wealth of information related to ice flow. This is particularly apparent for the two largest ice shelves – the Filchner-Ronne and Ross – where the surface expression of flow of ice streams and outlet glaciers can be traced from the grounding line to the calving front. The surface expression of subglacial lakes and other basal features are also illustrated. We also use the DEM to derive new estimates of balance velocities and ice divide locations.

Circumpolar thinning of Arctic sea ice following the 2007 record ice extent minimum

September 2007 marked a record minimum in sea ice extent. While there have been many studies published recently describing the minimum and its causes, little is known about how the ice thickness has changed in the run up to, and following, the summer of 2007. Using satellite radar altimetry data, covering the Arctic Ocean up to 81.5° North, we show that the average winter sea ice thickness anomaly, after the melt season of 2007, was 0.26 m below the 2002/2003 to 2007/2008 average. More strikingly, the Western Arctic anomaly was 0.49 m below the six‐year mean in the winter of 2007/2008. These results show no evidence of short‐term preconditioning through ice thinning between 2002 and 2007 but show that, after the record minimum ice extent in 2007, the average ice thickness was reduced, particularly in the Western Arctic.

The Gravimetric geoid of Tanzania

In continuation of earlier work on the geoid of Eastern Africa a further study has been undertaken to determine the geoid of Tanzania, bounded by latitude −12° ≤ φ ≤ -1°, longitude 29° ≤ λ ≤ 40°. The geoid was determined at a resolution grid of 5 minutes of arc. The Geodetic Reference System 1980 (GRS80) was used. The data used included the EIGEN-GRACE02S geopotential model to degree and order 120, a recent terrestrial gravity data anomaly set, marine (ship track) gravity and satellite radar altimetry data. A digital terrain model derived from the Shuttle Radar Topography Mission (SRTM) was also used to compute topographical effects. The spherical one-dimensional fast Fourier transform (FFT) method was used to compute the geoid heights residual to the geopotential model. Internal error propagation was used to get a pessimistic accuracy estimate of 30cm, and comparisons are made with heights derived from Transit Doppler observations co-located with trigonometrically determined heights. Gravimetric geoid height differences were compared with corresponding astrogeodetic geoid height differences provided by a 970 km geoidal section.

Mass changes of the Greenland and Antarctic ice sheets and shelves and contributions to sea-level rise: 1992–2002

AbstractChanges in ice mass are estimated from elevation changes derived from 10.5 years (Greenland) and 9 years (Antarctica) of satellite radar altimetry data from the European Remote-sensing Satellites ERS-1 and -2. For the first time, the dH/dt values are adjusted for changes in surface elevation resulting from temperature-driven variations in the rate of firn compaction. The Greenland ice sheet is thinning at the margins (–42 ± 2Gta¯1 below the equilibrium-line altitude (ELA)) and growing inland (+53 ± 2Gta-1 above the ELA) with a small overall mass gain (+11 ± 3Gta–1; –0.03 mma–1 SLE (sea-level equivalent)). The ice sheet in West Antarctica (WA) is losing mass (–47 ± 4Gta–1) and the ice sheet in East Antarctica (EA) shows a small mass gain (+16 ± 11 Gta–1) for a combined net change of –31 ± 12 Gta–1 (+0.08mma–1 SLE). The contribution of the three ice sheets to sea level is +0.05±0.03mma–1. The Antarctic ice shelves show corresponding mass changes of –95 ± 11 Gta–1 in WA and +142 ± 10Gta–1 in EA. Thinning at the margins of the Greenland ice sheet and growth at higher elevations is an expected response to increasing temperatures and precipitation in a warming climate. The marked thinnings in the Pine Island and Thwaites Glacier basins of WA and the Totten Glacier basin in EA are probably ice- dynamic responses to long-term climate change and perhaps past removal of their adjacent ice shelves. The ice growth in the southern Antarctic Peninsula and parts of EA may be due to increasing precipitation during the last century.

Indian Ocean Climate event brings floods to East Africa's lakes and the Sudd Marsh

During an El Niño, the expected rainfall increase over most of the Lake Victoria catchment area is ∼15–25%. However, due to anomalous warming of the western equatorial Indian Ocean during 1997, strong convection developed over parts of the Horn and eastern Africa. This resulted in a much larger 20–160% precipitation excess during the “short rainy” season. Satellite radar altimetry data reveals that not only did Lake Victoria rise by ∼1.7 m, but that the rainfall event similarly affected lakes Tanganyika, Malawi and Turkana. In addition, the seasonal level minima of the Sudd marshes and Lakes T'ana and Nasser continue to increase. Such a rainfall event will have severe, long‐term consequences for the natural surface flows and storages along the White Nile. Based on the hydrological impacts of the historic 1961 East Africa event, we can expect the current high levels of Lake Victoria to be maintained for the remainder of this decade. In addition, we anticipate a major expansion of the permanent swamp regions of the Sudd marshes over the forthcoming seasons. Blue Nile flows, further enhanced by the above‐average 1998 rainfall season, can also be expected to remain high, at least until early 1999.

Weddell Sea tectonics and Gondwana break-up: an introduction

The Weddell Sea, part of the circumpolar Southern Ocean, is probably the most remote, least known and least accessible sea in the world. Difficult ice conditions have limited the acquisition of ship data, although this has been partly offset in recent years by access to satellite radar altimetry data. The Weddell Sea was originally defined by the Admiralty Hydrographic Department in 1932 and redefined by the Antarctic Place Names Committee in 1976 (Hattersley-Smith 1991). It is bounded on the western side by the east coast of the Antarctic Peninsula, on the southern side by the Ronne and Filchner ice fronts, and on the southeastern side by the Dronning Maud Land and Coats Land coasts of East Antarctica (Fig. 1). The South Scotia Ridge separates the Weddell Sea from the Scotia Sea to the north and a line joining Southern Thule in the South Sandwich Islands and Kapp Norvegia in Dronning Maud Land, separates it from the South Atlantic Ocean to the NE. Within this volume, papers relate to the Weddell Sea as defined above, together with part of the adjoining South Atlantic Ocean up to 50°E, and to the geology of the once neighbouring continents of Gondwana. The term Weddell Sea embayment is also used informally throughout this volume to include the embayment area to the south of the Weddell Sea now covered by the Ronne and Filchner ice shelves, including Berkner Island, and the continental shelf north of the Ronne and Filchner ice fronts (Figs 1 & 2).

Variation of Great Lakes water levels derived from Geosat altimetry

A technique for using satellite radar altimetry data to estimate the temporal variation of the water level in moderate to large lakes and enclosed seas is described. Great Lakes data from the first 2 years of the U.S. Navy's Geosat Exact Repeat Mission (November 1986 to November 1988), for which there is an improved orbit, are used to demonstrate the technique. The Geosat results are compared to the lake level data collected by the Great Lakes Section, National Ocean Service, National Oceanic and Atmospheric Administration, and are found to reproduce the temporal variations of the five major lakes with root‐mean‐square error (rms) ranging from 9.4 to 13.8 cm and a combined average of 11.1 cm. Geosat data are also analyzed for Lake St. Clair, representing a moderate‐sized lake, with a resulting rms of 17.0 cm. During this study period, the water level in the Great Lakes varied in a typical annual cycle of about 0.2 m (0.5 m for Lake Ontario) superimposed on a general decline of approximately 0.5 m. The altimeter data reproduced the general decline reasonably well for all the lakes, but the annual cycle was obscured in some lakes due to systematic errors in the altimeter data. Current and future altimetry missions will have markedly improved accuracy which will permit many moderate (25 km diameter) or larger lakes or enclosed seas to be routinely monitored.

Smoothing of Geos 3 satellite radar altimeter data

Filtering of a large portion of Geos 3 satellite radar altimetry data at the Naval Surface Weapons Center has been accomplished by a Wiener smoother. The statistics of the geoid for the Wiener smoother is based on a third‐order Markov process. Because of some limitations the Wiener smoother has been replaced by a Kalman smoother which satisfies more closely the conditions of the altimetry data. The Kalman smoother also uses the same third‐order Markov statistics. A discussion of the smoothers (filter models), results obtained from the models, and a comparison of results with ship survey data are given in this paper.