Retrieving Precipitable Water Vapor From Shipborne Multi‐GNSS Observations

©2019. American Geophysical UnionPrecipitable water vapor (PWV) is an important parameter for climate research and a crucial factor to achieve high accuracy in satellite geodesy and satellite altimetry. Currently Global Navigation Satellite System (GNSS) PWV retrieval using static Precise Point Positioning is limited to ground stations. We demonstrated the PWV retrieval using kinematic Precise Point Positioning method with shipborne GNSS observations during a 20‐day experiment in 2016 in Fram Strait, the region of the Arctic Ocean between Greenland and Svalbard. The shipborne GNSS PWV shows an agreement of ~1.1 mm with numerical weather model data and radiosonde observations, and a root‐mean‐square of ~1.7 mm compared to Satellite with ARgos and ALtiKa PWV. An improvement of 10% is demonstrated with the multi‐GNSS compared to the Global Positioning System solution. The PWV retrieval was conducted under different sea state from calm water up to gale. Such shipborne GNSS PWV has the promising potential to improve numerical weather forecasts and satellite altimetry

Long-term monitoring of landfast sea ice extent and thickness in Kongsfjorden, and related applications (FastIce)

Landfast sea ice covers the inner parts of Kongsfjorden, Svalbard, for a limited time in winter and spring months, being an important feature for the physical and biological fjord systems. Systematic fast-ice monitoring for Kongsfjorden, as a part of a long-term project at the Norwegian Polar Institute (NPI) was started in 2003, with some more sporadic observations from 1997 to 2002. It includes the ice extent mapping and in situ measurements of ice and snow thickness, and freeboard at several sites in the fjord. The permanent presence of NPI personnel in Ny-Ålesund Research Station enables regular in situ fast-ice thickness measurements as long as the fast ice is accessible. Further, daily visits to the observatory on the mountain Zeppelinfjellet close to Ny-Ålesund, allow regular ice extent observations (weather, visibility, and daylight permitting). Data collected within this standardized monitoring programme have contributed to a number of studies. Monitoring of the sea-ice conditions in Kongsfjorden can be used to demonstrate and investigate phenomena related to climate change in the Arctic

On the Response of Polarimetric GNSS-Reflectometry to Sea Surface Roughness

Reflectometry of Global Navigation Satellite Systems (GNSS) signals from the ocean surface has provided a new source of observations to study the ocean-atmosphere interaction. We investigate the sensitivity and performance of GNSS-Reflectometry (GNSS-R) data to retrieve sea surface roughness (SSR) as an indicator of sea state. A data set of one-year observations in 2016 is acquired from a coastal GNSS-R experiment in Onsala, Sweden. The experiment exploits two sea-looking antennas with right- and left-hand circular polarizations (RHCP and LHCP). The interference of the direct and reflected signals captured by the antennas is used by a GNSS-R receiver to generate complex interferometric fringes. We process the interferometric observations to estimate the contributions of direct signals and reflections to the total power. The power estimates are inverted to the SSR using the state-of-the-art model. The roughness measurements from the RHCP and LHCP links are evaluated against match-up wind measurements obtained from the nearest meteorological station. The results report on successful roughness retrieval with overall correlations of 0.76 for both links. However, the roughness effect in LHCP observations is more pronounced. The influence of surrounding complex coastlines and the wind direction dependence are discussed. The analysis reveals that the winds blowing from land have minimal impact on the roughness due to limited fetch. A clear improvement of roughness estimates with an overall correlation of 0.82 is observed for combined polarimetric observations from the RHCP and LHCP links. The combined observations can also improve the sensitivity of GNSS-R measurements to the change of sea state

Characterizing Ionospheric Effects on GNSS Reflectometry at Grazing Angles from Space

Coherent observations in GNSS reflectometry are prominent in regions with smooth reflecting surfaces and at grazing elevation angles. However, within these lower elevation ranges, GNSS signals traverse a more extensive atmospheric path, and increased ionospheric effects (e.g., delay biases) are expected. These biases can be mitigated by employing dual-frequency receivers or models tailored for single-frequency receivers. In preparation for the single-frequency GNSS-R ESA “PRETTY” mission, this study aims to characterize ionospheric effects under variable parameter conditions: elevation angles in the grazing range (5° to 30°), latitude-dependent regions (north, tropic, south) and diurnal changes (day and nighttime). The investigation employs simulations using orbit data from Spire Global Inc.’s Lemur-2 CubeSat constellation at the solar minimum (F10.7 index at 75) in March 2021. Changes towards higher solar activity are accounted for with an additional scenario (F10.7 index at 180) in March 2023. The electron density associated with each reflection event is determined using the Neustrelitz Electron Density Model (NEDM2020) and the NeQuick 2 model. The results from periods of low solar activity reveal fluctuations of up to approximately 300 TECUs in slant total electron content, 19 m in relative ionospheric delay for the GPS L1 frequency, 2 Hz in Doppler shifts, and variations in the peak electron density height ranging from 215 to 330 km. Sea surface height uncertainty associated with ionospheric model-based corrections in group delay altimetric inversion can reach a standard deviation at the meter level

Dielectric sea-ice properties examined by GNSS reflectometry: Findings of the MOSAiC expedition

The dielectric properties of sea ice differ significantly from the open-water surface when we consider the L-band frequency range of GNSS signals. In contrast to water, the signal's penetration into sea ice can reach several decimeters depending on properties like salinity, temperature and thickness. Exploiting these different dielectric properties is a key to use GNSS for sea-ice remote sensing. For this purpose, GNSS reflectometry measurements have been conducted over the Arctic Ocean during the MOSAiC expedition (Multidisciplinary drifting Observatory for the Study of Arctic Climate). A combined receiver setup was used that allows the here described reflectometry study and another study for atmosphere sounding. The setup was mounted, in close cooperation with the Alfred-Wegener-Institute (AWI), on the German research icebreaker Polarstern that drifted during nine months of the expedition with the Arctic sea ice. Here, an initial study is presented that focuses on the expedition's first leg in autumn 2019 when the ship started drifting at about 85°N to 87°N in the Siberian Sector of the Arctic. Profiles of seaice reflectivity are derived with daily resolution considering reflection data recorded at left-handed (LH) and right-handed (RH) circular polarization. Respective model predictions of reflectivity are assuming a sea-ice bulk medium or a sea-ice slab. The later allows to include the effect of signal penetration down to the underlying water. Results of comparison between LH profiles and bulk model confirm the reflectivity contrast (about 10 dB) between sea ice and water. The particularly low level of LH reflectivity in the late observation period (December 2019) indicates the presence of low-saline multiyear (MY) ice. A bias due to snow accumulating on the ice surface may occur. A snow-extended reflection model, driven by additional snow data, can help in future for clarification. Anomalies of observed reflectivity with respect to bulk model predictions are especially obvious at lowest elevation angles. According to the model, the slope of profiles at low elevations is about 1.0 to 1.2 dB/°. The observation shows significantly lower values (< 0.5 dB/°) including negative slopes. A comparison of LH results with the ice slab model provides clarification. The anomalies are induced by signal penetration leading to interference pattern of reflections from the ice's surfaceand bottom. Slope retrievals quantify the anomaly and allow a coarse estimation of the mean seaice temperature (about -10°C in December 2019) based on the slab model predictions. Further investigations are needed to better understand sea-ice reflectivity at RH polarization. RH profiles show a response to sea ice and features at low elevation angles that cannot be explained by current reflection models. As a conclusion, GNSS reflectometry is sensitive to dielectric sea-ice properties. Estimates of ice type/salinity and temperature are reported based on LH observation data. These findings will be exploited to further strengthen the application of GNSS signals for sea-ice remote sensing. Future studies on GNSS observations from ships and satellites are anticipated

Surface reflectivity over Hudson Bay retrieved from TDS-1 mission data

In times of a changing climate and the resulting uncertain consequences for nature and society, a special interest is focused on the large-scale recording of sea ice. Among the existing remote sensing methods, reflected Global Navigation Satellite System (GNSS) signals could play an important role in fulfilling this task. Within this project the sensitivity of GNSS reflection data to sea ice properties is evaluated. Estimates of sea ice reflectivity are derived from the ratio of reflected to direct signal power. It is expected that reflectivity of GNSS signals over smooth sea ice is decreasing with increasing sea ice thickness. The surface's reflectivity depends on the sea ice permittivity, i.e. its dielectric property, its roughness and the signal penetration into the ice body. The signals studied here were recorded in the years 2015 and 2016 by the TechDemoSat-1 (TDS-1) satellite. The TDS-1 payload includes a down-looking left-handed circular polarized antenna with high gain peak to acquire the Earth reflected signal. Another hemispherical up-looking right-handed circular polarized antenna was used to receive direct signal. The data is provided by the manufacturer SSTL and the reflection events were further pre-processed by IEEC to derive georeferenced power values. The project focuses on the signals' link budget to apply necessary corrections. The influence of the attitude uncertainty on gain calculation of the nadir antenna was examined and high nadir angles were filtered. Corrections of antenna gain and Free-Space Path Loss (FSPL) have been applied. The reflectivity was calculated from the corrected power using the data of the upand down-looking links. The differences in FSPL requires a correction of the reflected signal up to +6 dB with respect to the direct signal power level, with the loss increasing in magnitude towards higher incidence angles. The antenna gain correction has to account for the difference between a >13 dB peak value of the high-gain nadir antenna and a 4 dB peak value of the hemispherical zenith antenna. The retrieved reflectivity values are compared to model predictions based on Fresnel coefficients. The relation of reflectivity to sea ice thickness is investigated using a sea ice thickness product of the Soil Moisture and Ocean Salinity (SMOS) satellite of the European Space Agency (ESA). First insights into observations over Hudson Bay indicate that retrieved reflectivity decreases as sea ice increases in thickness. These preliminary results show that the developed approach is promising. Further investigations are needed to account for the dependence on surface roughness. Many studies show the potential of spaceborne GNSS-Reflectometry (GNSS-R) to complement existing remote sensing systems cost-effectively with global coverage

Data Fusion to estimate sea-ice permittivity: a GNSS processor for 1-year MOSAiC data

The retrieval of Earth surface parameter using GNSS reflectometry techniques has become a valuable source for Earth observation. Typical parameters can be found over the open ocean (sea state, oceanwind), over land (soil moisture, inundation areas) or over sea ice (for example its extent andconcentration). The compactness of passive GNSS receiver instrumentation is a crucial advantage forthe versatile application scenarios of GNSS reflectometry techniques. We demonstrate here the estimation sea-ice permittivity based on the fusion GNSS and ancillary data. In the given scenario, GNSS observations were performed on the German research icebreaker Polarstern during its one year drift with the Arctic sea ice as part of the MOSAiC expedition (Multidisciplinary drifting Observatory for the Study of Arctic Climate). A dedicated GORS type (GNSS OccultationReflectometry Scatterometry) receiver was used with three antenna links attached: up-looking master link with right-handed polarization and two side-looking slave links (dual-polarization, leftand right-handed). Coherent samples (in-phase and quadrature) of the respective links are provided by the receiver. The processing steps comprise, at first, the separation of the GNSS multipath signal into direct and reflected contributions using the right- and left-handed slave-link samples. Two steps of data fusion follow, first, combining the separated signal power estimates to obtain reflectivity time series and, second, adding geo-reference to the obtained time series defining specular point and elevation angle. The geo-referencing involves: standard point position data of the GORS receiver and broadcast orbit data of the GNSS satellites (available at the IGS). Additionally, attitude data from the ship's inertial navigation system is used for event masking to assure satellite visibility and account for shadowing of the ship structure. Sea-ice permittivity is finally inverted from the referenced and masked reflectivity time series. For this purpose, the data fusion scheme is extended by ancillary sea ice concentration data acquired on the ship according to the ASSIST protocol (Arctic Ship-based Sea Ice Standardization Tool). The GNSS data processor, presented here, is focused on reflectometry considering the challenges of a ship-based setup (multipath signals and ship's attitude changes). Currently, the processor is enhanced to GNSS remote sensing concept that also monitors ionosphericimpact on the MOSAiC GNSS data record

Monitoring of GNSS Scintillation Indices during the MOSAiC Expedition: Preliminary Results from Eight Months in the Arctic

Polar regions are of particular interest to study the interaction of space weather (solar radiation and particle precipitation) with the Earth’s atmosphere and magnetosphere. We focus here on space-weather induced irregularities of electron density in the upper atmosphere and their impact on radio signals. Such irregularities can disturb radio communication (particularly in air traffic) and radio navigation with GNSS (Global Navigation Satellite Systems) in the polar regions. The global network of GNSS stations to monitor the space weather impact is sparse at high latitudes. The permanent stations, located below 80°N, cannot reach a complete monitoring coverage in the Arctic. The MOSAiC expedition provided an excellent opportunity to collect GNSS data beyond 80°N over a long period of more than 8 months. We focus, here, on a GNSS setup that was installed aboard R/V Polarstern to study the signal’s amplitude and phase scintillation. The respective indices S4 and σφ allow to quantify the impact of space-weather induced irregularities. The MOSAiC record comprises links of three systems: GPS, GLONASS and Galileo. Preliminary GPS results show that anomalies in σφ of about 0.2 rad can be related to particle precipitation. The results indicate that a drifting GNSS setup can contribute to space weather monitoring if the ship's dynamic is carefully taken into account

Sea-ice signatures in coherently reflected GNSS signals: Findings of the MOSAiC expedition

Sea ice is a crucial parameter in the Earth climate system. Its high albedo compared to water influences the oceans' radiation budget. The state of sea ice is highly variable due to seasonal change and global warming. GNSS reflectometry can contribute to global monitoring sea ice. Properties like ice salinity, temperature and thickness affect the signal reflection. The MOSAiC expedition (Multidisciplinary drifting Observatory for the Study of Arctic Climate) gave the opportunity to conduct reflectometry measurements under different sea-ice conditions in the Arctic. A dedicated setup was mounted, in close cooperation with the Alfred-Wegener-Institute (AWI), on the German research icebreaker Polarstern that drifted during nine months with the Arctic sea ice. Here, results from the expedition's first leg in autumn 2019 are presented when the ship started drifting at about 85°N to 87°N in the Siberian Sector of the Arctic. Profiles of sea-ice reflectivity are derived with daily resolution considering reflection data recorded at left-handed (LH) and righthanded (RH) circular polarization. Respective predictions of reflectivity are provided assuming reflection models of bulk sea ice or a sea-ice slab. The later allows to include the effect of signal penetration down to the underlying water. Results of comparison between LH profiles and bulk model confirm that the reflectivity decreases (about 10 dB) when the ship goes into compact sea ice. In the central Arctic period anomaly signatures in observed reflectivity occur. The comparison of signatures and applied models (bulk and slab) indicate the role of coherent signal penetration into the ice. Salinity and temperature of sea ice have influence on these signatures. We conclude that estimation of ice type/salinity and temperature can profit from grazing angle GNSS reflectometry. Future studies will proceed to investigate these signatures in coherent observations

Sea-Ice Permittivity Estimation using GNSS Reflectometry data of the MOSAiC Expedition

Sea ice is a crucial parameter of the Earth climate system. Its high albedo compared to water influences the oceans' radiation budget significantly. The importance of monitoring arises from the high variability of sea-ice state and amount induced by seasonal change and global warming. GNSS reflectometry can contribute to global monitoring of sea ice with high potential to extend the spatio-temporal coverage of today's observation techniques. Properties like ice salinity, temperature and thickness can affect the signal reflection. The MOSAiC expedition (Multidisciplinary drifting Observatory for the Study of Arctic Climate) gave us the opportunity to conduct reflectometry measurements under different sea-ice conditions in the central Arctic. A dedicated setup was mounted, in close cooperation with the Alfred-Wegener-Institute (AWI), on the German research icebreaker Polarstern that drifted for one year with the Arctic sea ice. We present results from data recorded between autumn 2019 and spring 2020. The ship drifted in this period from the Siberian Sector of the Arctic (October 2019), over the central Arctic (November 2019 until May 2020) towards Svalbard (reached in June 2020). Profiles of sea-ice reflectivity over elevation angle (range: 1° to 45°) are derived with daily resolution considering reflection data recorded at left-handed (LH) and right-handed (RH) circular polarization. Respective predictions of reflectivity are based on reflection models of bulk sea ice or a sea-ice slab. The latter allows to include the effect of signal penetration down to the underlying water. Results of comparison between LH profiles and bulk model confirm a reflectivity decreases (about 10 dB) when surrounding open water areas vanish and the ship drifts in compact sea ice. Results from autumn data (until mid-December 2019) have already been published [1,2] and comprise the following. First, estimates of sea-ice permittivity are obtained from mid-elevation range reflectivity (10° to 30°). The median of estimated permittivity 2.4 (period of compact sea ice) lies in the expected range of reported old ice type (mostly second-year ice). Second, anomalies in the low-elevations range of retrieved reflectivity (1° to 10°) give strong indication of signal penetration into the dominating second-year ice with influence of sea ice temperature and thickness. We conclude that sea-ice characterization in future can profit form GNSS reflectometry observations. The on-going study is currently extended to the further evolution of Arctic sea ice during winter and spring period of the MOSAiC expedition. [1] Semmling, A. M., J. Wickert, F. Kreß, M. M. Hoque, D. V. Divine, S. Gerland, and G. Spreen (2021). "Sea-ice permittivity derived from GNSS reflection profiles: Results of the MOSAiC expedition". IEEE Trans. Geosci. Rem. Sens. doi: 10.1109/TGRS.2021.3121993