Space-borne Synthetic Aperture Radar (SAR) Interferometry (InSAR) is now a key geophysical tool for surface deformation studies. The European Commission’s Sentinel-1 Constellation began acquiring data systematically in late 2014. The data, which are free and open access, have global coverage at moderate resolution with a 6 or 12-day revisit, enabling researchers to investigate large-scale surface deformation systematically through time. However, full exploitation of the potential of Sentinel-1 requires specific processing approaches as well as the efficient use of modern computing and data storage facilities. Here we present Looking Into Continents from Space with Synthetic Aperture Radar (LiCSAR), an operational system built for large-scale interferometric processing of Sentinel-1 data. LiCSAR is designed to automatically produce geocoded wrapped and unwrapped interferograms and coherence estimates, for large regions, at 0.001° resolution (WGS-84 coordinate system). The products are continuously updated at a frequency depending on prioritised regions (monthly, weekly or live update strategy). The products are open and freely accessible and downloadable through an online portal. We describe the algorithms, processing, and storage solutions implemented in LiCSAR, and show several case studies that use LiCSAR products to measure tectonic and volcanic deformation. We aim to accelerate the uptake of InSAR data by researchers as well as non-expert users by mass producing interferograms and derived products.
We investigate crustal deformation due to the extraction of water and steam from a high‐enthalpy geothermal reservoir; a common occurrence, yet not well understood. The cause of this deformation can be a change in pressure or in temperature in the reservoir, both of which can be caused by extraction or injection of geothermal fluids. Our study area, the Hengill mountains in SW Iceland, is an active volcanic center and a plate triple junction that hosts two power plants producing geothermal energy. This combination of natural and anthropogenic processes causes a complex displacement field at the surface. We analyze geodetic data—Global Navigation Satellite System and Interferometric Synthetic Aperture Radar—to obtain the surface velocity field, which we then simulate using an inverse modeling approach. We focus on the deformation around the geothermal power plants but need to model the regional tectonic and volcanic deformation as well, because the signals are overlapping. We find that plate motion and a deep contracting body can explain the broad scale signal in the area. Local deformation near the two power plants, Hellisheidi and Nesjavellir, can be explained by extraction of geothermal fluids. We estimate reservoirs extending from 0.6 to 3.0 km depth at Hellisheidi, and 1.0 to 3.0 km depth at Nesjavellir for observed pressure decrease rates of 0.25 MPa/yr and 0.1 MPa/yr, respectively. We find that the main cause for the subsidence in the geothermal area is the observed pressure drawdown.
Non-eruptive uplift and subsidence episodes remain a challenge for monitoring and hazard assessments in active volcanic systems worldwide. Sources of such deformation may relate to processes such as magma inflow and outflow, motion and phase changes of hydrothermal fluids or magma volatiles, heat transfer from magmatic bodies and heat-mining from geothermal extraction. The Hengill area, in southwest Iceland, hosts two active volcanic systems, Hengill and Hrómundartindur, and two high-temperature geothermal power plants, Hellisheiði and Nesjavellir. Using a combination of geodetic data sets (GNSS and InSAR; Global Navigation Satellite Systems and Interferometry Synthetic Aperture Radar, respectively) and a non-linear inversion scheme to estimate the optimal analytical model parameters, we investigate the ground deformation between 2017–2018. Due to other ongoing deformation processes in the area, such as plate motion, subsidence in the two geothermal production fields, and deep-seated source of contraction since 2006, we estimate 2017–2018 difference velocities by subtracting background deformation, determined from data spanning 2015–2017 (InSAR) or 2009–2017 (GNSS). This method highlights changes in ground deformation observed in 2017–2018 compared to prior years: uplift signal of ∼10 km diameter located in the eastern part of the Hengill area, and geothermal production-related temporal changes in deformation near Húsmúli, in the western part of the Hengill area. We find an inflation source located between the Hengill and Hrómundartindur volcanic complexes, lasting for ∼5 months, with a maximum uplift of ∼12 mm. Our model inversions give a source at depth of ∼6–7 km, located approximately in the same crustal volume as an inferred contracting source in 2006–2017, within the local brittle-ductile transition zone. No significant changes were observed in local seismicity, borehole temperatures and pressures during the uplift episode. These transient inflation and deflation sources are located ∼3 km NW from a source of non-eruptive uplift in the area (1993–1999). We consider possible magmatic and hydrothermal processes as the causes for these inflation-deflation episodes and conclude that further geophysical and geological studies are needed to better understand such episodes.
Abstract. MDAL is the operational Meteosat Second Generation (MSG)-derived daily surface albedo product that has been generated and disseminated in near real time by EUMETSAT Satellite Application Facility for Land Surface Analysis (LSA-SAF) since 2005. We propose and evaluate an update to the MDAL retrieval algorithm which introduces the accounting for aerosol effects as well as other scientific developments: pre-processing recalibration of radiances acquired by the SEVIRI instrument aboard MSG and improved coefficients for atmospheric correction as well as for albedo conversion from narrow- to broadband. We compare the performance of MDAL broadband albedos pre- and post-upgrade with respect to three types of reference data: the EPS Ten-Day Albedo product ETAL is used as the primary reference, while albedo derived from in situ flux measurements acquired by ground stations and MODIS MCD43D albedo data are used to complete the validation. For the comparison to ETAL – conducted over the whole coverage area of SEVIRI – we see a reduction in average white-sky albedo mean bias error (MBE) from −0.02 to negligible levels (<0.001) and a reduction in average mean absolute error (MAE) from 0.034 to 0.026 (−24 %). Improvements can be seen for black-sky albedo as well, albeit less pronounced (14 % reduction in MAE). Further analysis distinguishing individual seasons, regions and land covers show that performance changes have spatial and temporal dependence: for white-sky albedo we see improvements over almost all regions and seasons relative to ETAL, except for Eurasia in winter; resolved by land cover we see a similar effect with improvements for all types for all seasons except winter, where some types exhibit slightly worse results (crop-, grass- and shrublands). For black-sky albedo we similarly see improvements for all seasons when averaged over the full data set, although sub-regions exhibit clear seasonal dependence: the performance of the upgraded MDAL version is generally diminished in local winter but better in local summer. The comparison with in situ observations is less conclusive due to the well-known problem of the spatial representativeness of near-ground observations with respect to satellite pixel footprint sizes. Comparison with MODIS at the same locations shows mixed results in terms of change in performance following the proposed upgrade but proves the good quality of the MDAL products in general. Based on the evidence presented in this study, we consider the updated algorithm version to be able to deliver a valuable improvement of the operational MDAL product. This improvement is two-fold: primarily, there is the refinement of the albedo values themselves; secondarily, the increased alignment with the ETAL product is beneficial for those who wish to exploit synergies between EUMETSAT's geostationary and polar satellites to generate data sets based on the LSA-SAF albedo products from the two different missions.
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