Geodetic investigation of triggered slip below Fiordland

<p>Secretary Island, at the head of Doubtful Sound in Fiordland, has been seismically active in past 30 years, with earthquakes larger than M w 6.5: the 1989 Doubtful Sound, 1993 Secretary Island, and 2003 Fiordland earthquakes. These events were approximately coincident with the 17° bend in the strike of the young, obliquely-converging, and steeply dipping Puysegur Subduction Zone. This section of the plate interface also has a history of triggered slip: the 1989 earthquake is inferred to have triggered the 1993 earthquake and, further north at George Sound, triggered afterslip was reported following the 2009 Dusky Sound earthquake. We have used L-band (23.6 cm-wavelength) Synthetic Aperture Radar (SAR) data from the ALOS1 and ALOS2 satellites, and C-band (5.5 cm-wavelength) SAR data from Sentinel 1A/B satellites, to test the hypothesis that triggered slip also occurred in the vicinity of Secretary Island following the 2007 George Sound, 2009 Dusky Sound and 2016 Kaikōura earthquakes. SAR images were aligned, interfered, filtered, and unwrapped using GMTSAR processing tools. Long-wavelength ionosphere noise was removed by inverting for the best-fitting linear plane, and we assumed a linear function of height to remove short-wavelength atmospheric noise. Small Baseline Subset (SBAS) timeseries analysis indicated a localised deformation signal centred on Secretary Island following the Dusky Sound earthquake. A re-analysis was undertaken of the co- and post-seismic deformation caused by the Dusky Sound earthquake so that any surface deformation centred on Secretary Island could be isolated. Campaign and continuous Global Positioning System (GPS) data were simultaneously inverted with co- and post-seismic interferograms using a statistical Bayesian modelling approach to determine the optimal Dusky Sound earthquake source parameters. Limitations arising from orbital drift, the frequency of SAR acquisitions and the observation geometry hindered our ability to constrain the timing, magnitude and location of reactivated slip from a source similar to the 2003 Secretary Island earthquake. Our findings indicate that slip was not triggered following either the 2007 George Sound earthquake or 2016 Kaikōura earthquake. However, we cannot rule out triggered slip near Secretary Island following the 2009 Dusky Sound earthquake. Any such slip likely occurred on an area of c. 350 km² (c. 15 km updip of the Secretary Island epicentre) with an average slip of 1–3 m, producing motion away from the satellite of c. 25 mm at Secretary Island.</p>

Geodetic investigation of triggered slip below Fiordland

<p>Secretary Island, at the head of Doubtful Sound in Fiordland, has been seismically active in past 30 years, with earthquakes larger than M w 6.5: the 1989 Doubtful Sound, 1993 Secretary Island, and 2003 Fiordland earthquakes. These events were approximately coincident with the 17° bend in the strike of the young, obliquely-converging, and steeply dipping Puysegur Subduction Zone. This section of the plate interface also has a history of triggered slip: the 1989 earthquake is inferred to have triggered the 1993 earthquake and, further north at George Sound, triggered afterslip was reported following the 2009 Dusky Sound earthquake. We have used L-band (23.6 cm-wavelength) Synthetic Aperture Radar (SAR) data from the ALOS1 and ALOS2 satellites, and C-band (5.5 cm-wavelength) SAR data from Sentinel 1A/B satellites, to test the hypothesis that triggered slip also occurred in the vicinity of Secretary Island following the 2007 George Sound, 2009 Dusky Sound and 2016 Kaikōura earthquakes. SAR images were aligned, interfered, filtered, and unwrapped using GMTSAR processing tools. Long-wavelength ionosphere noise was removed by inverting for the best-fitting linear plane, and we assumed a linear function of height to remove short-wavelength atmospheric noise. Small Baseline Subset (SBAS) timeseries analysis indicated a localised deformation signal centred on Secretary Island following the Dusky Sound earthquake. A re-analysis was undertaken of the co- and post-seismic deformation caused by the Dusky Sound earthquake so that any surface deformation centred on Secretary Island could be isolated. Campaign and continuous Global Positioning System (GPS) data were simultaneously inverted with co- and post-seismic interferograms using a statistical Bayesian modelling approach to determine the optimal Dusky Sound earthquake source parameters. Limitations arising from orbital drift, the frequency of SAR acquisitions and the observation geometry hindered our ability to constrain the timing, magnitude and location of reactivated slip from a source similar to the 2003 Secretary Island earthquake. Our findings indicate that slip was not triggered following either the 2007 George Sound earthquake or 2016 Kaikōura earthquake. However, we cannot rule out triggered slip near Secretary Island following the 2009 Dusky Sound earthquake. Any such slip likely occurred on an area of c. 350 km² (c. 15 km updip of the Secretary Island epicentre) with an average slip of 1–3 m, producing motion away from the satellite of c. 25 mm at Secretary Island.</p>

Design of Orbit Controls for a Multiple CubeSat Mission Using Drift Rate Modulation

For the low-cost improvement of laser communication, which is critical for various applications such as surveillance systems, a study was conducted on relative distance control based on orbital drift rate modulations for multiple CubeSats during formation flying. The VISION mission covered in this paper comprises two CubeSats to demonstrate laser communication technology in space. During the mission, the deputy CubeSat changes the relative distance to execute mission objectives within various scenarios. Impulsive controls decrease, maintain, and increase the relative distance between the CubeSats by changing the orbital drift rates. The simulation results indicated that the desired orbital operation can be conducted within a given ΔV budget. In addition, the errors in the orbit determination, thrust maneuvers, and time synchronization were analyzed to satisfy the mission requirements. The mass-to-area ratio should be matched to adjust the relative distance between satellites with different properties by drift rate modulation. The proposed orbit control method appropriately operated the VISION mission by adjusting the drift rate modulation. The results of this study serve as a basis for the development of complex orbit control simulations and detailed designs that reflect the characteristics of the thrust module and operational aspects.

Retrieval of Daily Mean Top-of-Atmosphere Reflected Solar Flux Using the Advanced Very High Resolution Radiometer (AVHRR) Instruments

The records of the Advanced Very High Resolution Radiometer (AVHRR) instrument observations can resolve the current lack of a long global climate data record of Reflected Solar Flux (RSF), by transforming these measurements into broadband flux at the top-of-atmosphere. This paper presents a methodology for obtaining daily mean RSF (Wm−2) from AVHRR. First, the narrowband reflectances are converted to broadband reflectance using empirical regressions with the Clouds and the Earth’s Radiant Energy System (CERES) observations. Second, the anisotropy is corrected by applying Angular Distribution Models (ADMs), which convert directional reflectance into a hemispherical albedo. Third, the instantaneous albedos are temporally interpolated by a flexible diurnal cycle model, capable of ingesting any number of observations at any time of day, making it suitable for any orbital configuration of NOAA and MetOp satellites. Finally, the twilight conditions prevailing near sunrise and sunset are simulated with an empirical model. The entire day is then integrated into a single daily mean RSF. This paper furthermore demonstrates the methodology by validating a full year (2008) of RSF daily means with the CERES SYN1deg data record, both on daily and subdaily scale. Several configurations are tested, each excluding particular satellites from the constellation in order to mimic orbital changes (e.g., orbital drift), and to assess their relative importance to the daily mean RSF. The best performance is obtained by the combination of at least one mid-morning (NOAA-17 or MetOp-A) and one early afternoon (NOAA-18) orbit. In this case, the RMS difference with CERES is about 7 Wm−2. Removing NOAA-18 degrades the performance to an RMS difference of 12 Wm−2, thereby providing an estimate of the impact of NOAA-19’s orbital drift between 2016 and 2020. Very early or late observations (NOAA-15, NOAA-16) provide little added value, and both mid-morning orbits turn out to be almost interchangeable given their close temporal proximity.

Evaluation of Orbital Drift Effect on Proba-V Surface Reflectances Time Series

Multi-temporal consistency of space-borne observations is an essential requirement for studying inter-annual changes and trends of satellite-derived biophysical products. The Proba-V mission, launched in 2013, was designed to ensure the continuity of the SPOT-VEGETATION long-term data record of global daily observations for land applications. The suitability of Proba-V to provide a temporally consistent data record is, however, potentially jeopardized by the orbital drift effect, which is known to induce spurious trends in time series. The aim of this paper is therefore to evaluate, for the first time, the orbital drift effect on Proba-V surface reflectance time series at 1 km resolution. In order to reliably identify such an effect, a two-fold approach is adopted. A simulation study is first defined to predict the temporal anomalies induced by the drifting illumination conditions. The numerical simulations are used as a benchmark to predict the impact of the drift for a range of sun-viewing angles. Real observations are then analyzed over a large set of land sites, globally spread and spanning a wide range of surface and environmental conditions. The surface anisotropy is characterized using the Ross-Thick Li-Sparse Reciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model. Both the simulation and the analysis of real observations consistently show that the orbital drift induces distinct and opposite trends in the two sides of the sensor across-track swath. Particularly, a positive drift is estimated in backward and a negative one in the forward scattering direction. When observations from all angular conditions are retained, these opposite trends largely compensate, with no remaining statistically significant drifts in time series of surface reflectances or Normalized Difference Vegetation Index (NDVI). As such, the Proba-V archive at 1 km resolution can be reliably used for inter-annual vegetation studies.

NOAA-AVHRR Orbital Drift Correction: Validating Methods Using MSG-SEVIRI Data as a Benchmark Dataset

National Oceanic and Atmospheric Administration–Advanced Very High Resolution Radiometer (NOAA-AVHRR) data provides the possibility to build the longest Land Surface Temperature (LST) dataset to date, starting in 1981 up to the present. However, due to the orbital drift of the NOAA platforms, no LST dataset is available before 2000 and the arrival of newer platforms. Although numerous methods have been developed to correct this orbital drift effect on the LST, a lack of validation has prevented their application. This is the gap we bridge here by using the 15 min temporal resolution of Meteosat Second Generation–Spinning Enhanced Visible and Infra-Red Imager (MSG-SEVIRI) data to simulate drifted and reference LST time series. We then use these time series to validate an orbital drift correction method based on solar zenith angle (SZA) anomalies that we presented in a previous work (C1), as well as two variations of this approach (C0 and C2). Our results show that the C0 method performs better than the two others, although its overall bias absolute value ranges up to 1 K, while standard deviation values remain around 3 K. This is verified for most land covers, for all NOAA platforms, and these statistics remain mostly stable with noise on SZA time series (from 0° to ±10°). With this study, we show that orbital drift correction methods can be thoroughly validated and that such validation should aim toward bias absolute values below 0.1 K and standard deviation values around 1.4 K at coarse spatial resolution. To validate other orbital drift correction approaches, the drifted and reference time series used in this work are freely available for download from the first author’s webpage. This will be the first step toward the building of an orbital-drift-corrected long-term LST dataset.

Dissecting effects of orbital drift of polar-orbiting satellites on accuracy and trends of climate data records of cloud fractional cover

Radiometers such as the AVHRR (Advanced Very High Resolution Radiometer) mounted aboard a series of NOAA and MetOp (Meteorological Operational) polar-orbiting satellites provide 4-decade-long global climate data records (CDRs) of cloud fractional cover. Generation of such long datasets requires combining data from consecutive satellite platforms. A varying number of satellites operating simultaneously in the morning and afternoon orbits, together with satellite orbital drift, cause the uneven sampling of the cloudiness diurnal cycle along a course of a CDR. This in turn leads to significant biases, spurious trends, and inhomogeneities in the data records of climate variables featuring the distinct diurnal cycle (such as clouds). To quantify the uncertainty and magnitude of spurious trends in the AVHRR-based cloudiness CDRs, we sampled the 30 min reference CM SAF (European Organisation for the Exploitation of Meteorological Satellites – EUMETSAT – Satellite Application Facility on Climate Monitoring) Cloud Fractional Cover dataset derived from Meteosat First and Second Generation (COMET) at times of the NOAA and MetOp satellite overpasses. The sampled cloud fractional cover (CFC) time series were aggregated to monthly means and compared with the reference COMET dataset covering the Meteosat disc (up to 60∘ N, S, W, and E). For individual NOAA and MetOp satellites the errors in mean monthly CFC reach ±10 % (bias) and ±7 % per decade (spurious trends). For the combined data record consisting of several NOAA and MetOp satellites, the CFC bias is 3 %, and the spurious trends are 1 % per decade. This study proves that before 2002 the AVHRR-derived CFC CDRs do not comply with the GCOS (Global Climate Observing System) temporal stability requirement of 1 % CFC per decade just due to the satellite orbital-drift effect. After this date the requirement is fulfilled due to the numerous NOAA and MetOp satellites operating simultaneously. Yet, the time series starting in 2003 is shorter than 30 years, which makes it difficult to draw reliable conclusions about long-term changes in CFC. We expect that the error estimates provided in this study will allow for a correct interpretation of the AVHRR-based CFC CDRs and ultimately will contribute to the development of a novel satellite orbital-drift correction methodology widely accepted by the AVHRR-based CDR providers.

A global long-term (1981–2000) land surface temperature product for NOAA AVHRR

Land surface temperature (LST) plays an important role in the research of climate change and various land surface processes. Before 2000, global LST products with relatively high temporal and spatial resolutions are scarce, despite a variety of operational satellite LST products. In this study, a global 0.05∘×0.05∘ historical LST product is generated from NOAA advanced very-high-resolution radiometer (AVHRR) data (1981–2000), which includes three data layers: (1) instantaneous LST, a product generated by integrating several split-window algorithms with a random forest (RF-SWA); (2) orbital-drift-corrected (ODC) LST, a drift-corrected version of RF-SWA LST; and (3) monthly averages of ODC LST. For an assumed maximum uncertainty in emissivity and column water vapor content of 0.04 and 1.0 g cm−2, respectively, evaluated against the simulation dataset, the RF-SWA method has a mean bias error (MBE) of less than 0.10 K and a standard deviation (SD) of 1.10 K. To compensate for the influence of orbital drift on LST, the retrieved RF-SWA LST was normalized with an improved ODC method. The RF-SWA LST were validated with in situ LST from Surface Radiation Budget (SURFRAD) sites and water temperatures obtained from the National Data Buoy Center (NDBC). Against the in situ LST, the RF-SWA LST has a MBE of 0.03 K with a range of −1.59–2.71 K, and SD is 1.18 K with a range of 0.84–2.76 K. Since water temperature only changes slowly, the validation of ODC LST was limited to SURFRAD sites, for which the MBE is 0.54 K with a range of −1.05 to 3.01 K and SD is 3.57 K with a range of 2.34 to 3.69 K, indicating good product accuracy. As global historical datasets, the new AVHRR LST products are useful for filling the gaps in long-term LST data. Furthermore, the new LST products can be used as input to related land surface models and environmental applications. Furthermore, in support of the scientific research community, the datasets are freely available at https://doi.org/10.5281/zenodo.3934354 for RF-SWA LST (Ma et al., 2020a), https://doi.org/10.5281/zenodo.3936627 for ODC LST (Ma et al., 2020c), and https://doi.org/10.5281/zenodo.3936641 for monthly averaged LST (Ma et al., 2020b).

A global long-term (1981–2000) land surface temperature product for NOAA AVHRR

Land Surface Temperature (LST) plays an important role in the research of climate change and various land surface processes. Before 2000, global LST products with relatively high temporal and spatial resolutions are scarce, despite of a variety of operational satellite LST products. In this study, a global 0.05° × 0.05° historical LST product is generated from NOAA AVHRR data (1981–2000), which includes three data layers: (1) instantaneous LST, a product generated by integrating several Split-Window Algorithms with a Random Forest (RF-SWA); (2) orbital drift corrected (ODC) LST, a drift corrected version of RF-SWA LST; (3) monthly averages of ODC LST. For an assumed maximum uncertainty in emissivity and column water vapour content of 0.04 and 1.0 g/cm2, respectively and evaluated against the simulation data set, the RF-SWA method has a Mean Bias Error (MBE) of less than 0.10 K and a Standard Deviation (STD) of 1.10 K. To compensate the influence of orbital drift on LST, the retrieved RF-SWA LST was normalized with an improved ODC method. The RF-SWA LST were validated with in-situ LST from Surface Radiation Budget (SURFRAD) sites and water temperatures obtained from the National Data Buoy Center (NDBC). Against the in-situ LST, the RF-SWA LST has a MBE 0.03 K with a range of −1.59 K–2.71 K and STD is 1.18 K with a range of 0.84 K–2.76 K. Since water temperature only changes slowly, the validation of ODC LST was limited to SURFRAD sites, for which the MBE is 0.54 K with a range of −1.05 K to 3.01 K and STD is 3.57 K with a range of 2.34 K to 3.69 K, indicating a good product accuracy. As global historical datasets, the new AVHRR LST products are useful for filling the gaps in long-term LST data. Furthermore, the new LST products can be used as input to related land surface models and environmental applications. Furthermore, in support of the scientific research community, the datasets are freely available at https://doi.org/10.5281/zenodo.3934354 for RF-SWA LST (Ma et al., 2020a); https://doi.org/10.5281/zenodo.3936627 for ODC LST (Ma et al., 2020c); https://doi.org/10.5281/zenodo.3936641 for monthly averaged LST (Ma et al., 2020b).