Generic Mapping Tools (GMT) is an open‐source software package for the analysis and display of geoscience data, helping scientists to analyze, interpolate, filter, manipulate, project, and plot time series and gridded data sets. The GMT toolbox includes about 80 core and 40 supplemental program modules sharing a common set of command options, file structures, and documentation. Its power to process data and produce publication‐quality graphic presentations has made it vital to a large scientific community that now includes more than 25,000 individual users. GMT's website (http://gmt.soest.hawaii.edu/) exceeds 20,000 visits per month, and server logs show roughly 2000 monthly downloads.

The Generic Mapping Tools (GMT) software is ubiquitous in the Earth and ocean sciences. As a cross‐platform tool producing high‐quality maps and figures, it is used by tens of thousands of scientists around the world. The basic syntax of GMT scripts has evolved very slowly since the 1990s, despite the fact that GMT is generally perceived to have a steep learning curve with many pitfalls for beginners and experienced users alike. Reducing these pitfalls means changing the interface, which would break compatibility with thousands of existing scripts. With the latest GMT version 6, we solve this conundrum by introducing a new “modern mode” to complement the interface used in previous versions, which GMT 6 now calls “classic mode.” GMT 6 defaults to classic mode and thus is a recommended upgrade for all GMT 5 users. Nonetheless, new users should take advantage of modern mode to make shorter scripts, quickly access commonly used global data sets, and take full advantage of the new tools to draw subplots, place insets, and create animations.

Satellite radar altimeter measurements show that the average elevation of the Antarctic Ice Sheet interior fell by 0.9 +/- 0.5 centimeters per year from 1992 to 1996. If the variability of snowfall observed in Antarctic ice cores is allowed for, the mass imbalance of the interior this century is only -0.06 +/- 0.08 of the mean mass accumulation rate.

Abstract. The radial orbit error has long been the major error source in ERS-1 altimetry, crippled by having only satellite laser ranging for precise tracking and relying on insufficiently accurate general-purpose gravity field models. Altimeter crossovers are used very effectively as additional tracking data to laser ranging. The ERS Tandem Mission even provides the unique possibility to simultaneously determine orbits of two similar satellites flying the same orbit.Altimeter crossovers between the two satellites then link the two orbits into a common reference frame. Tailoring of the Joint Gravity Model 3 (JGM 3) is another step to reduce orbit errors. This technique is aimed at the reduction of the geographically anticorrelated orbit error (observed in the crossover height differences) through the adjustment of selected gravity field parameters. The resulting Delft Gravity Model (DGM)-E04 has reduced this part of the orbit error by a factor of 2, performs even better with respect to the ESA-provided orbits, and also outperforms the recent Earth Geopotential Model EGM96 in this respect. ERS-1 and ERS-2 orbits for the entire Tandem Mission are computed and studied in detail, and orbit errors due to the gravity field and nonconservative forces are identified. Analyses systematically show that the orbits computed with JGM 3 have a radial root-mean-square orbit accuracy of 7 cm, with DGM-E04 5 cm. IntroductionThe Tandem The bulky satellites ERS-1 and ERS-2 were never designed for high-accuracy orbit determination, and the loss of the Precise Range and Range-Rate Equipment (PRARE) tracking system left ERS-1 even more poorly equipped for orbit determination. Yet, subdecimetric orbit accuracy is not of academic interest only. The ERS altimetric system has performed well above expectations and is unique because of its multidisciplinary character, sampling not only ocean but also land and ice surfaces, in combination with the suite of instruments on board, providing, e.g., simultaneous measurements of wet tropospheric content and surface temperature. Undoubtedly, ERS will always lag behind on the 2-cm root-meansquare orbit accuracy of the TOPEX/POSEIDON altimeter mission [Marshall et al., 1995], so only when the precise orbit determination is stretched to its very limits, ERS altimetry will be regarded a reliable source of information. Only then will ERS be able to demonstrate its additive value in ocean research and its unique capabilities in, e.g., monitoring of the ice sheet mass balance.In section 2 we will discuss the numerous advances made in ERS operational and precise orbit determination over the years up to the current state-of-the-art modeling. An important step in this is the development of the ERS-tailored Delft Gravity Model (DGM)-E04 (section 3). In section 4, DGM-E04 demonstrates that it constitutes a remarkable improvement on the ERS orbits but also has a more general applicability. Section 5 examines the effect of nonconservative forces acting on the satellite. Section 6 combines all results and attem...

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Coastal zones are highly dynamical systems affected by a variety of natural and anthropogenic forcing factors that include sea level rise, extreme events, local oceanic and atmospheric processes, ground subsidence, etc. However, so far, they remain poorly monitored on a global scale. To better understand changes affecting world coastal zones and to provide crucial information to decision-makers involved in adaptation to and mitigation of environmental risks, coastal observations of various types need to be collected and analyzed. In this white paper, we first discuss the main forcing agents acting on coastal regions (e.g., sea level, winds, waves and currents, river runoff, sediment supply and transport, vertical land motions, land use) and the induced coastal response (e.g., shoreline position, estuaries morphology, land topography at Frontiers in Marine Science | www.frontiersin.org 1 July 2019 | Volume 6 | Article 348Benveniste et al.Requirements for a Coastal Zone Observing System the land-sea interface and coastal bathymetry). We identify a number of space-based observational needs that have to be addressed in the near future to understand coastal zone evolution. Among these, improved monitoring of coastal sea level by satellite altimetry techniques is recognized as high priority. Classical altimeter data in the coastal zone are adversely affected by land contamination with degraded range and geophysical corrections. However, recent progress in coastal altimetry data processing and multisensor data synergy, offers new perspective to measure sea level change very close to the coast. This issue is discussed in much detail in this paper, including the development of a global coastal sea-level and sea state climate record with mission consistent coastal processing and products dedicated to coastal regimes. Finally, we present a new promising technology based on the use of Signals of Opportunity (SoOp), i.e., communication satellite transmissions that are reutilized as illumination sources in a bistatic radar configuration, for measuring coastal sea level. Since SoOp technology requires only receiver technology to be placed in orbit, small satellite platforms could be used, enabling a constellation to achieve high spatio-temporal resolutions of sea level in coastal zones.

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Remotely sensed infrared images of Hurricane Katrina taken on 26, 27, and 28 August 2005 (Figure 1, left panels) show the aerial extent of the cloud cover and the central “eye” increasing as the storm that swamped areas of the U.S. Gulf Coast intensified. Computer animations of such image sequences show forecasters the tracks of storms and are a familiar staple of weather news. Less well known is the role that satellite altimetry plays both in forecasting conditions that can intensify a tropical storm and in observing the storm conditions at the sea surface. Satellite altimeter data indicate that Katrina intensified over areas of anomalously high dynamic topography rather than areas of unusually warm surface waters. Altimeter data from Katrina also for the first time observed the building of a storm surge.