First spaceborne GNSS-Reflectometry observations of hurricanes from the UK TechDemoSat-1 mission

We present the first examples of GNSS-Reflectometry observations of hurricanes using spaceborne data from the UK TechDemoSat-1 (TDS-1) mission. We confirm that GNSS-R signals can detect ocean condition changes in very high near-surface ocean wind associated with hurricanes. TDS-1 GNSS-R reflections were collocated with IBTrACS hurricane data, MetOp ASCAT A/B scatterometer winds and two re-analysis products. Clear variations of GNSS-R reflected power (σ0) are observed as reflections travel through hurricanes, in some cases up to and through the eye wall. The GNSS-R reflected power is tentatively inverted to estimate wind speed using the TDS-1 baseline wind retrieval algorithm developed for low to moderate winds. Despite this, TDS-1 GNSS-R winds through the hurricanes show closer agreement with IBTrACS estimates than winds provided by scatterometers and reanalyses. GNSS-R wind profiles show realistic spatial patterns and sharp gradients which are consistent with expected structures around the eye of tropical cyclones

EUMETSAT Invitation To Tender 14/209556: JASON-CS SAR Mode Sea State Bias Study. Final report

This document represents the final report of a study funded by EUMETSAT about SAR mode Sea State Bias (SSB) for the Sentinel-6/Jason-CS mission. The study comprises a critical review of SSB estimation methods in conventional (low-resolution mode or LRM) altimetry, theoretical considerations about the effect of swell on SAR altimeter waveforms and empirical investigations with Cryosat-2 SAR mode data to detect swell effects in L1B and Level 2 Sea Surface Height (SSH). The report concludes by summarising the basis for the selection and derivation of the SAR altimeter sea state bias correction algorithm and the methods available to calibrate and validate SAR mode SSB corrections. Theoretical considerations based on simple SAR waveform modelling indicate that multipeaked waveforms could occur in the presence of swell, but that effects become clearly detectable only when swell height exceeds 4 meters, which is relatively rare. In the case of the Cryosat-2 data examined in this study, only 2% of samples satisfied this condition. Experimental investigations of Cryosat-2 SAR mode data in different swell conditions produce no consolidated evidence of swell effects. Although anomalous 20Hz waveforms are occasionally observed, no statistically detectable effect of swell is obtained in the overall results for average L1B waveform shapes and L2 1Hz SSH biases and precisions. However, it is stressed that analyses in this study were limited geographically by the availability of Cryosat-2 SAR mode acquisitions over the ocean that could be collocated with Envisat ASAR swell data. It is strongly advised that analyses should be repeated with a broader geographical scope, including data from the central Pacific and the Southern Ocean where high sea state and swell conditions are more prevalent. It is suggested that this could be achieved using Sentinel-3 SRTM and Sentinel-1 L2 swell products, should such data be available. Empirical SSB estimation methods offer the only viable way forward at present to estimate SAR mode SSB. Parametric, non-parametric and hybrid methods are all relevant, noting that hybrid methods may provide more robust estimates in those high sea state and swell conditions that are less densely populated and where effects will be more significant. The development of SAR mode SSB corrections should include additional dependence on sea state development, which would be consistent with the tendency in LRM towards three-parameters SSB models (e.g. Tran et al., 2010b; Pires et al., 2016). The challenges of calibrating and validating SAR mode SSB corrections are the same - i.e. no better, no worse - than for conventional altimetry. For SAR mode altimetry however, P-LRM offer a unique way of calibrating and validating SAR mode SSB against conventional altimetry by providing coincident range measurements that have been shown to be unbiased against conventional LRM. In the case of Sentinel-6/Jason-CS, interleaved SAR mode will deliver true LRM data that make it possible to tie the Jason-CS SAR mode mission to the long-term altimetric data record without the issues linked to the loss of precision seen for SAR burstmode P-LRM

Sensitivity of GNSS-R spaceborne observations to soil moisture and vegetation

Global navigation satellite systems-reflectometry (GNSS-R) is an emerging remote sensing technique that makes use of navigation signals as signals of opportunity in a multistatic radar configuration, with as many transmitters as navigation satellites are in view. GNSS-R sensitivity to soil moisture has already been proven from ground-based and airborne experiments, but studies using space-borne data are still preliminary due to the limited amount of data, collocation, footprint heterogeneity, etc. This study presents a sensitivity study of TechDemoSat-1 GNSS-R data to soil moisture over different types of surfaces (i.e., vegetation covers) and for a wide range of soil moisture and normalized difference vegetation index (NDVI) values. Despite the scattering in the data, which can be largely attributed to the delay-Doppler maps peak variance, the temporal and spatial (footprint size) collocation mismatch with the SMOS soil moisture, and MODIS NDVI vegetation data, and land use data, experimental results for low NDVI values show a large sensitivity to soil moisture and a relatively good Pearson correlation coefficient. As the vegetation cover increases (NDVI increases) the reflectivity, the sensitivity to soil moisture and the Pearson correlation coefficient decreases, but it is still significant.Postprint (author's final draft

Temporal variability of GNSS-Reflectometry ocean wind speed retrieval performance during the UK TechDemoSat-1 mission

This paper presents the temporal evolution of Global Navigation Satellite System Reflectometry (GNSS-R) ocean wind speed retrieval performance during three years of the UK TechDemoSat-1 (TDS-1) mission. TDS-1 was launched in July 2014 and provides globally distributed spaceborne GNSS-R data over a lifespan of over three years, including several months of 24/7 operations. TDS-1 wind speeds are computed using the NOC Calibrated Bistatic Radar Equation algorithm version 0.5 (C-BRE v0.5), and are evaluated against ERA5 high resolution re-analysis data over the period 2015–2018. Analyses reveal significant temporal variability in TDS-1 monthly wind speed retrieval performance over the three years, with the best performance (~2 m∙s−1) achieved in the early part of the mission (May 2015). The temporal variability of retrieval performance is found to be driven by several non-geophysical factors, including TDS-1 platform attitude uncertainty and spatial/temporal changes in GPS transmit power from certain satellites. Evidence is presented of the impact of the GPS Block IIF Flex mode on retrieved GNSS-R wind speed after January 2017, which results in significantly underestimated ocean winds over a large region covering the North Atlantic, northern Indian Ocean, the Mediterranean, the Black Sea, and the Sea of Okhotsk. These GPS transmit power changes are shown to induce large negative wind speed biases of up to 3 m∙s−1. Analyses are also presented of the sensitivity of TDS-1 wind speed retrieval to platform attitude uncertainty using statistical simulations. It is suggested that a 4° increase in attitude uncertainty can produce up to 1 m∙s−1 increase in RMSE, and that TDS-1 attitude data do not fully reflect actual platform attitude. We conclude that the lack of knowledge about the GNSS-R nadir antenna gain map and TDS-1 platform-attitude limits the ability to determine the achievable wind speed retrieval performance with GNSS-R on TDS-1. The paper provides recommendations that accurate attitude knowledge and a good characterisation of GNSS-R nadir antenna patterns should be prioritised for future GNSS-R missions

Spatial and temporal scales of variability in Tropical Atlantic sea surface salinity from the SMOS and Aquarius satellite missions

Taking advantage of the spatially dense, multi-year time series of global Sea Surface Salinity (SSS) from two concurrent satellite missions, the spatial and temporal decorrelation scales of SSS in the Tropical Atlantic 30°N–30°S are quantified for the first time from SMOS and Aquarius observations. Given the dominance of the seasonal cycle in SSS variability in the region, the length scales are calculated both for the mean and anomaly (i.e. seasonal cycle removed) SSS fields. Different 7–10 days composite SSS products from the two missions are examined to explore the possible effects of varying resolution, bias corrections and averaging characteristics. With the seasonal cycle retained, the SSS field is characterized by strongly anisotropic spatial variability. Homogeneous SSS variations in the Tropics have the longest zonal scales of over ~ 2000 km and long temporal scales of up to ~ 70–80 days, as shown by both SMOS and Aquarius. The longest meridional scales, reaching over ~ 1000 km, are seen in the South Atlantic between ~ 10°–25°S, most discernible in Aquarius data. The longest temporal scales of SSS variability are reported by both satellites to occur in the North-West Atlantic region 15°–30°N, at the Southern end of the Sargasso Sea, with SSS persisting for up to 150–200 days. The removal of the seasonal cycle results in a noticeable decrease in the spatio-temporal decorrelation scales over most of the basin. Overall, with the exception of the differences in the South Atlantic, there is general agreement between the spatial and temporal scales of SSS from the two satellites and different products, despite differences in individual product calibration and resolution characteristics. These new estimates of spatio-temporal decorrelation scales of SSS improve our knowledge of the processes and mechanisms controlling the Tropical Atlantic SSS variability, and provide valuable information for a wide range of oceanographic and modelling applications

Modeling Envisat RA-2 waveforms in the coastal zone: case-study of calm water contamination

Radar altimeters have so far had limited use in the coastal zone, the area with most societal impact. This is due to both lack of, or insufficient accuracy in the necessary corrections, and more complicated altimeter signals. This paper examines waveform data from the Envisat RA-2 as it passes regularly over Pianosa (a 10 km2 island in the NW Mediterranean). Forty-six repeat passes were analysed, with most showing a reduction in signal upon passing over the island, with weak early returns corresponding to the reflections from land. Intriguingly one third of cases showed an anomalously bright hyperbolic feature. This feature may be due to extremely calm waters in the Golfo della Botte (northern side of the island), but the cause of its intermittency is not clear. The modelling of waveforms in such a complex land/sea environment demonstrates the potential for sea surface height retrievals much closer to the coast than is achieved by routine processing. The long-term development of altimetric records in the coastal zone will not only improve the calibration of altimetric data with coastal tide gauges, but also greatly enhance the study of storm surges and other coastal phenomena

An assessment of non-geophysical effects in spaceborne GNSS Reflectometry data from the UK TechDemoSat-1 mission

An assessment of non-geophysical effects in spaceborne global navigation satellite system reflectometry (GNSS-R) data from the UK TechDemoSat-1 (TDS-1) mission is presented. TDS-1 was launched in July 2014 and provides the first new spaceborne GNSS-R data since the pioneering UK-disaster monitoring constellation experiment in 2003. Non-geophysical factors evaluated include ambient L-band noise, instrument operating mode, and platform-related parameters. The findings are particularly relevant to users of uncalibrated GNSS-R signals for the retrieval of geophysical properties of the Earth surface. Substantial attitude adjustments of the TDS-1 platform are occasionally found to occur that introduce large uncertainties in parts of the TDS-1 GNSS-R dataset, particularly for specular points located outside the main beam of the nadir antenna where even small attitude errors can lead to large inaccuracies in the geophysical inversion. Out of eclipse however, attitude adjustments typically remain smaller than 1.5°, with larger deviations of up to 10° affecting less than 5% of the overall sun-lit data. Global maps of L1 ambient noise are presented for both automatic and programmed gain modes of the receiver, revealing persistent L-band noise hotspots along the Equator that can reach up to 2.5 dB, most likely associated with surface reflection of signals from other GNSS transmitters and constellations. Sporadic high-power noise events observed in certain regions point to sources of human origin. Relevant conclusions of this study are that platform attitude knowledge is essential and that radiometric calibration of GNSS-R signals should be used whenever possible. Care should be taken when considering using noise measurements over the equatorial oceans for calibration purposes, as ambient noise and correlated noise in delay–Doppler maps both show more variation than might be expected over these regions

Wind-Wave induced velocity in ATI SAR Ocean Surface Currents: First experimental evidence from an airborne campaign

Conventional and along-track interferometric (ATI) Synthetic Aperture Radar (SAR) sense the motion of the ocean surface by measuring the Doppler shift of reflected signals. Measurements are affected by a Wind-wave induced Artefact Surface Velocity (WASV) which was modelled theoretically in past studies and has been estimated empirically only once before with Envisat ASAR by Mouche et al., (2012). An airborne campaign in the tidally dominated Irish Sea served to evaluate this effect and the current retrieval capabilities of a dual-beam SAR interferometer known as Wavemill. A comprehensive collection of Wavemill airborne data acquired in a star pattern over a well-instrumented validation site made it possible for the first time to estimate the magnitude of the WASV, and its dependence on azimuth and incidence angle from data alone. In light wind (5.5 m/s) and moderate current (0.7 m/s) conditions, the wind-wave induced contribution to the measured ocean surface motion reaches up to 1.6 m/s upwind, with a well-defined 2nd order harmonic dependence on direction to the wind. The magnitude of the WASV is found to be larger at lower incidence angles. The airborne WASV results show excellent consistency with the empirical WASV estimated from Envisat ASAR. These results confirm that SAR and ATI surface velocity estimates are strongly affected by WASV and that the WASV can be well characterized with knowledge of the wind knowledge and of the geometry. These airborne results provide the first independent validation of Mouche et al., 2012, and confirm that the empirical model they propose provides the means to correct airborne and spaceborne SAR and ATI SAR data for WASV to obtain accurate ocean surface current measurements. After removing the WASV, the airborne Wavemill retrieved currents show very good agreement against ADCP measurements with a root mean square error (RMSE) typically around 0.1 m/s in velocity and 10° in direction

Spaceborne GNSS-Reflectometry for ocean winds: First results from the UK TechDemoSat-1 mission

First results are presented for ocean surface wind speed retrieval from reflected GPS signals measured by the Low-Earth-Orbiting UK TechDemoSat-1 satellite (TDS-1). Launched in July 2014, TDS-1 provides the first new spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) data since the pioneering UK-Disaster Monitoring Mission experiment in 2003. Examples of onboard-processed delay Doppler Maps reveal excellent data quality for winds up to 27.9 m/s. Collocated ASCAT scatterometer winds are used to develop and evaluate a wind speed algorithm based on Signal-to-Noise ratio (SNR) and the Bistatic Radar Equation. For SNR greater than 3 dB, wind speed is retrieved without bias and a precision around 2.2 m/s between 3–18 m/s even withoutcalibration. Exploiting lower SNR signals however requires good knowledge of the antenna beam, platform attitude and instrument gain setting. This study demonstrates the capabilities of low-cost, low-mass, low-power GNSS-R receivers ahead of their launch on the NASA CYGNSS constellation in 2016