Search

The European CryoSat-2 and Sentinel-3A satellites, soon to be followed by Sentinel-3B, were the first to operate SAR mode altimeters. These missions initiated a new era in satellite altimetry over the oceans, in which a step change in improvement in measurements over the open ocean and coastal zone has been achieved, in terms of accuracy of measurement, the capability to map features that could not previously be resolved, and to provide measurements closer to the coast than ever before. This presentation looks back at a series of three rojects initiated by ESA: SAMOSA, CP4O and SCOOP, reviews the development and assessment of new processing schemes for SAR mode altimeter measurements, plots the performance improvements achieved and then looks ahead to further developments. SAMOSA (SAR Altimetry Mode Studies and Applications) was an ESA-funded project initiated in 2007 to investigate the improvements offered by SAR mode altimetry over ocean, coastal and inland water surfaces, developing practical implementation of new theoretical models for the SAR echo waveform as part of this process. SAMOSA developed physical based models for SAR altimeter ocean waveforms, and applied them to develop re-trackers for SAR mode products, which were further developed and tested on simulated data, airborne data, and then on real satellite data from CryoSat-2. Approaches to reduce SAR mode data to “RDSAR” data were also investigated, to infer the statistical equivalence between SAR mode and the traditional low-resolution altimetry. Subsequent work further developed the “SAMOSA” model, balancing the aim to improve the modelling of the waveform against efficiency of processing to achieve a practical scheme that could be implemented in the Sentinel-3 Ground Segment. CP4O (CryoSat Plus for Oceans) was a project supported under the ESA Programme Element coined “Support to Science Element” (STSE) with the objectives to build a sound scientific basis for new scientific and operational applicat

Sea level is one of the 50 Essential Climate Variables (ECVs) listed by the Global Climate Observing System (GCOS) in climate change monitoring. In the past two decades, sea level has been routinely measured from space using satellite altimetry techniques. In order to address a number of important scientific questions such as "Is sea level rise accelerating?", "Can we close the sea level budget?", "What are the causes of the regional and interannual variability?", "Can we already detect the anthropogenic forcing signature and separate it from the internal/natural climate variability?", and "What are the coastal impacts of sea level rise?", the accuracy of altimetry-based sea level records at global and regional scales needs to be significantly improved. For example, the global mean and regional sea level trend uncertainty should become better than 0.3 and 0.5 mm year−1, respectively (currently 0.6 and 1–2 mm year−1). Similarly, interannual global mean sea level variations (currently uncertain to 2–3 mm) need to be monitored with better accuracy. In this paper, we present various data improvements achieved within the European Space Agency (ESA) Climate Change Initiative (ESA CCI) project on "Sea Level" during its first phase (2010–2013), using multi-mission satellite altimetry data over the 1993–2010 time span. In a first step, using a new processing system with dedicated algorithms and adapted data processing strategies, an improved set of sea level products has been produced. The main improvements include: reduction of orbit errors and wet/dry atmospheric correction errors, reduction of instrumental drifts and bias, intercalibration biases, intercalibration between missions and combination of the different sea level data sets, and an improvement of the reference mean sea surface. We also present preliminary independent validations of the SL_cci products, based on tide gauges comparison and a sea level budget closure approach, as well as comparisons with ocean reana

This study documents a method for increasing the precision of satellite-derived sea level measurements. Results are achieved using an enhanced three-dimensional (3-D) sea state bias (SSB) correction model derived from both Jason-1 altimeter ocean observations (i.e., sea state and wind) and estimates of mean wave period from a numerical ocean wave model, NOAA's WAVEWATCH III. A multiyear evaluation of Jason-1 data indicates sea surface height variance reduction of 1.26 (+/- 0.2) cm(2) in comparison to the commonly applied two-parameter SSB model. The improvement is similar for two separate variance reduction metrics and for separate annual data sets spanning 2002-2004. Spatial evaluation of improvement shows skill increase at all latitudes. Results indicate the new model can reduce the total Jason-1 and Jason-2 altimeter range error budgets by similar to 7.5%. In addition to the 2-D (two-dimensional) and 3-D model differences in correcting the range for wavefield variability, mean model regional differences also occur across the globe and indicate a possible 1-2 cm gradient across ocean basins linked to the zonal variation in wave period (short fetch and period in the west, swells and long period in the east). Overall success of this model provides first evidence that operational wave modeling can support improved ocean altimetry. Future efforts will attempt to work within the limits of wave modeling capabilities to maximize their benefit to Jason-1 and Jason-2 SSB correction methods.