An OSSE evaluation of the GNSS-R altimetry data for the GEROS-ISS mission as a complement to the existing observational networks
Introduction
Satellite radar altimeter data are a unique global and near-real time observation of Sea Level Anomalies (SLA) providing locations, amplitudes, and trajectories of mesoscale eddies. This altimetry data is essential for operational oceanography in its ability to constrain ocean models by data assimilation and to serve coastal applications (Counillon and Bertino, 2009; Oke et al., 2008; Le Traon et al., 2015).
The South China Sea (SCS) is the widest marginal sea in the western Pacific and has a deep semi-enclosed basin. The Luzon Strait is its only deep connection to the Pacific Ocean, which allows the intrusion of saline water into the SCS (Metzger and Hurlburt, 1996; Qu et al., 2009; Xue et al., 2004). 20 years of altimeter data have stimulated studies of the mesoscale eddy activity in the SCS (Roemmich et al., 2001; Shaw et al., 1999; Wunsch, 1999). Using these data in the period of 1992–2009, Chen et al. (2011) showed that the eddies propagate mainly southwestward along the continental slope in the northern SCS. By carrying heat and salt, mesoscale eddies play an important role for the SCS circulations and for the distribution of heat in the western boundary current (Wang et al., 2006; Wang et al., 2008).
The assimilation of SLA data from altimeters can significantly improve the representation of mesoscale eddy activities in the SCS (Wu et al., 1999; Xie et al., 2011; Xu et al., 2012) and have therefore a high value for operational ocean forecast. In order to constrain well the mesoscale circulations, at least three or four altimeters are required (Le Traon et al., 2015). However, the spacing between two adjacent SLA tracks can exceed 100 km. Together with the long repeat cycle of polar orbit satellite (~10 days), they set a limit for the use of altimetry on scales smaller than 100 km (Dibarboure et al., 2014). A further complication is that extreme weather events (typhoons in the case of the Pacific Ocean) can degrade altimeter retrievals, which is unfortunate at times when extra high precision would be necessary to avoid human and material losses.
A different observation system has been proposed to resolve small eddies, based on the Global Navigation Satellite Systems (GNSS) that are widely used for global positioning and navigation. The GNSS systems currently in activity are the United States' Global Positioning System (GPS), the Russian Federation's Global Orbiting Navigation Satellite System (GLONASS), the European Galileo, the BEIDOU (also known as COMPASS) being developed by P. R. China and the Indian Regional Navigation Satellite System (IRNSS). The GNSS satellites are far more numerous than satellite altimeters. Martín-Neira (1993) proposed to track the reflected GNSS signals off the ocean surface and to correlate them to the ones received directly to diagnose sea surface heights. This observation approach was named GNSS Reflectometry (GNSS-R). In theory, it is a bistatic radar altimeter where the transmitters are GNSS satellites. Initial spaceborne results from the UK-Disaster Monitoring Constellation (UK-DMC) indicated the GNSS-R potentiality to detect wave motion and wind speed (Clarizia et al., 2009; Gleason et al., 2005), which motivated this innovative approach to be applied to ocean remote sensing.
The radio signals from the GNSS satellites are constantly broadcast to the Earth. The delayed signals reflected off the rough ocean surface, together with information on the receiver's antenna position and the propagation medium, can be used to determine the ocean surface height. Ruffini et al. (2004) analyzed the reflected signals from two synchronous GPS receivers on an aircraft at 1 km altitude, and retrieved a mesoscale altimetry signal as provided by monostatic radar altimeters such as Jason-1. Using the derivative of the delay waveforms of the reflected GPS signals, Rius et al. (2010) developed and implemented a method to produce altimetry observations in one flight experiment in the North Sea, off the coast of Norway. Cardellach et al. (2014) retrieved 2 cm/km topographic slopes along the Baltic Sea using GNSS-R measurements from a 3 km altitude flight. Using the data from the GPS receiver on board the TechdemoSAT-1 (TDS-1) satellite at 635 km orbit altitude, Clarizia et al. (2016) estimated the first spaceborne observation of sea surface height during a 6-month period using the publicly available GPS code of coarser delay resolution. Li et al. (2016) considered the GPS and GLONASS constellation and use the concerned GNSS-R altimetry to improve the map of mesoscale SSH in the North Pacific. However, in the previous studies the possible improvements induced by GNSS-R are usually investigated individually, in isolation from the existing ocean observation networks.
A scientific experiment, titled “GNSS REflectometry, Radio Occultation and Scatterometry aboard the International Space Station” (GEROS-ISS hereafter), has been proposed to ESA (Wickert et al., 2011; Wickert et al., 2016). The main objective is to measure SSH using GNSS-R. Studies were performed in this context to mature the delay waveform method, based on the cross-correlation of the direct and reflected signals; in order to acquire the full transmitted bandwidth (higher delay resolution), also called interferometric technique. Note that the interferometric technique has much better altimetric accuracy than the conventional GNSS-R technique implemented in TechDemoSat-1 and CYGNSS missions, which uses only a tenth of the GNSS transmitted signal bandwidth. In addition, the dedicated correction schemes are planned for the GEROS-ISS mission, which are simply not available for the ad-hoc analysis in Clarizia et al. (2016). It includes very essential schemes like precise orbit determination, ionospheric and tropospheric correction. They examine the use of carrier phase residuals (Semmling et al., 2016) to further extend the incidence range of altimetry observations. A general advantage relative to conventional altimetry lies in the high spatial coverage achieved by the large range of GNSS-R incidence angles. Saynisch et al. (2015) illustrates the Agulhas current system improved by assimilating the GNSS-R altimetry data only. GEROS-ISS has a low orbit altitude ~400 km and incidence angles within two windows of 18–45° and 60–85°.
The present study includes a mature budget of systematic errors for spaceborne interferometric GNSS-R, and attempts to evaluate quantitatively the impact of this new kind of altimetry data under more realistic conditions, assuming the GNSS-R operates at its target performance. In this study, the data assimilation system is set up in a HYCOM model of the South China Sea (SCS) using the Ensemble Optimal Interpolation (EnOI). The additional SSH observations from GEROS-ISS are assimilated into and compared to another data assimilation run only using traditional altimetry data. The data assimilation system used for this study is described in Section 2. Section 3 describes the SSH estimation in the Observation System Simulation Experiment (OSSE) from June to July 2014 in the SCS. Section 4 compares the two data assimilation runs with and without the SSH observations from GEROS-ISS, and evaluates quantitatively the impacts. Finally, the conclusions and discussions of future possible steps are given in Section 5.
Section snippets
The nested high resolution model in the SCS
The model uses the version 2.2 of the Hybrid Coordinate Ocean Model (HYCOM) in which vertical layers can change smoothly from isopycnal in stratified open ocean to z-coordinates in surface mixed waters. HYCOM is applied widely from deep oceans to shelf seas (Chassignet et al., 2003; Winther and Evensen, 2006). A nested HYCOM model system is used (as shown in Fig. 1), in the intention to resolve the Kuroshio intrusions through the Luzon Strait. The inner model has a homogeneous horizontal
Synthetic SSH measurements by GNSS-R
The GNSS-R altimetry solution is extracted from the bi-static range or delay measurement which can be divided into eight different components: geometric delays due to the relative position of the transmitter, ocean surface and the receiver, clock errors, tropospheric and ionospheric delays induced by the atmosphere, multipath caused by the receiving antenna surroundings, delays inside of the concerned instruments, sea state and electromagnetic bias (Ghavidel and Camps, 2016), and noise (Rius et
Design and evaluation of the OSSE runs
In the experimental period from 18th June to 31st July 2014, the “true” SSH has been fed to the synthetic simulator of GNSS-R (Section 3). Based on the four GNSS constellations of GPS, GLONASS, GALILEO and BEIDOU under the target parameters designed in GEROS-ISS, the simulated measurements of SSH are fed back into the SCS assimilative system. To evaluate quantitatively the impacts of the GNSS-R altimetry data with respect to the present observation network, two assimilation runs are performed:
Conclusions
The altimetry data from GNSS-R has drawn some attention in the recent years (Li et al., 2014; Semmling et al., 2016; Wickert et al., 2016), even though the expected uncertainties of the signal are higher than from traditional radar altimeters. The GNSS-R uncertainty is mainly driven by the noise term (linked to the transmitted signal structure), with systematic errors mostly induced by the troposphere and the ionosphere. Those are considered in this study to generate synthetic SLA measurements
Acknowledgment
This study was supported by ESA contract 4000111952/14/NL/MV (Project GARCA) and an allocation of CPU time from the Norwegian Supercomputing Project (NOTUR II grant numbers: nn2993k, nn9481k and NS2993K).
References (68)
- et al.
The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system
Remote Sens. Environ.
(2012) - et al.
The Bluelink ocean data assimilation system (BODAS)
Ocean Model
(2008) - et al.
An introduction to the South China Sea throughflow: its dynamics, variability, and implication for climate
Dyn. Atmos. Oceans
(2009) - et al.
Sea surface height variations in the South China Sea from satellite altimetry
Oceanol. Acta
(1999) - et al.
A comparison of sequential assimilation schemes for ocean prediction with the HYbrid Coordinate Ocean Model (HYCOM): Twin Experiments with static forecast error covariances
Ocean Model.
(2011) - et al.
Estimation of extreme wind speed in SCS and NWP by a non-stationary model
Theor. Appl. Mech. Lett.
(2016) - et al.
A hybrid coordinate ocean model for shelf sea simulation
Ocean Model.
(2006) - et al.
Assessment and inter-comparison of five high-resolution sea surface temperature products in the shelf and coastal seas around China
Cont. Shelf Res.
(2008) - et al.
Coordinate transformation on a sphere using conformal mapping
Mon. Weather Rev.
(1999) - et al.
GPS meteorology: remote sensing of atmospheric water vapor using the global positioning system
J. Geophys. Res.
(1992)