A new algorithm for classification of sea ice types on Sentinel-1 Synthetic Aperture Radar (SAR) data using a convolutional neural network (CNN) is presented. The CNN is trained on reference ice charts produced by human experts and compared with an existing machine learning algorithm based on texture features and random forest classifier. The CNN is trained on two datasets in 2018 and 2020 for retrieval of four classes: ice free, young ice, first-year ice and old ice. The accuracy of our classification is 90.5% for the 2018-dataset and 91.6% for the 2020-dataset. The uncertainty is a bit higher for young ice (85%/76% accuracy in 2018/2020) and first-year ice (86%/84% accuracy in 2018/2020). Our algorithm outperforms the existing random forest product for each ice type. It has also proved to be more efficient in computing time and less sensitive to the noise in SAR data. The code is publicly available.

Over the last 3 decades, GPS measurements have been instrumental in quantifying tectonic plates current motion and deformation. Complex patterns of deformation along the plate boundaries revealed heterogeneous coupling on the plates interface and imaged seismic segments at different stages of their seismic cycle. Along the South-American trench in Chile, where large earthquakes occur frequently, continuous GPS observations (cGPS) captured both the long-term plate motion and the transient deformations associated to the seismic cycle. Over the years, a network of hundreds of cGPS stations has been deployed all across the South-American continent by many different institutions for \m{many ?}all sorts of purposes ranging from geographic reference to Tsunami early warning. We report here on the processing of 20 years (2000-2020) worth of data over a selection of cGPS stations, devoted to the quantification and analysis of the deformation along the Chilean subduction zone between 18°S and 40°S. We use all available data near the trench in Chile and a less dense network inside the continent where the gradient of deformation is lesser. Our database, named SOAM_GNSS_solENS, provides time series of precise daily station position, obtained from double difference (DD) processing and expressed in the International Terrestrial Reference Frame 2014 (ITRF14). These time series allow to quantify, with \m{sub-?}sub-millimetric precision, any kind of ongoing deformation process, either from tectonic origin such as interseismic deformation, co- and post-seismic displacements associated with earthquakes, transient deformation associated to seismic swarms and/or a-seismic slow-slip events, or of other origin such as hydrological loading (for ex, the Amazonian basin load) or any other type of loading affecting the surface of the earth (tides, atmosphere, etc...). We also provide a database of coseismic displacements associated with close to 60 earthquakes of Mw larger than 6.5 that occurred over the last 20 years within the observation area. All time series are directly accessible through a deposit and we also plan make them available through a web interface that will allow any user to perform elementary operations like estimating offsets, detecting outliers, detrending, filtering and stacking. That database will evolve with time, aggregating more data. In the future, we also plan to complement that database with a rapid solution in quasi real time processed in Precise Point Positioning (PPP), and with hourly atmospheric delays associated to water vapor contains of the lower layer of the atmosphere.

Over the last decade, three major subduction earthquakes, Maule Mw 8.8 (2010), Illapel Mw 8.3 (2015) and Iquique Mw 8.1 (2014), occurred in Chile and generated significant post-seismic deformations. These large scale and long lasting deformations can be quantified with modern GNSS precise positioning and highlight visco-elastic processes in the asthenosphere. Here, we calculate the ratios of cumulative post-seismic displacements after 5 years over the co-seismic offsets. We find that at any distance from the trench, ratios are similar for the three earthquakes despite their different magnitudes which imply induced stresses that are more than one order of magnitude apart. This observation suggests that the post-seismic deformation is related to the same effective viscosity for the three earthquakes, indicating Newtonian rheology, rather than power-law rheology in the asthenosphere.

<p>Ever since the Maule earthquake (Mw8.8, 2010), a quick vertical uplift is measured thanks to GNSS in the Andes, facing the rupture zone (~250 km to the trench). Models built for the Maule earthquake [Klein et al. 2016] have highlighted that a low-viscosity channel is required to explain the post-seismic uplift. This channel is located along the slab between 50 km and 130 km depth and has a viscosity of a few 10<sup>17</sup> Pa.s - lower than in the asthenosphere, 10<sup>18</sup> Pa.s. </p> <p>After the Illapel earthquake (Mw8.3, 2015), simple observations on GNSS time-series show that no uplift occurred in the Andes at an equivalent distance to the trench than in the case of the Maule earthquake. The subduction in the Illapel region is characterized by a flat-slab (called the Pampean flat-slab) in contrast with the normal-dipping subduction in the region of Maule.</p> <p>Here, we investigate what is the impact of the Pampean flat-slab on the post-seismic deformations of the Illapel earthquake. In particular, we try to understand  whether the presence of the flat-slab inhibits the effect of the low-viscosity channel. For that purpose we compare GNSS vertical displacements with predictions in both regions of Maule and Illapel from a 3D spherical finite-element model that accounts for the slab geometry of the Chilean subduction zone.</p>

<p>Thanks to space geodesy we know with a millimetric precision how the lithosphere deforms at each stage of the seismic cycle. In particular, during the post-seismic phase, it can deform over thousands of kilometers and for decades. These deformations are partly due to viscoelastic relaxation of the asthenosphere.</p> <p>In a previous work, we have shown that at the temporal and spatial scale of the seismic cycle, the viscoelastic relaxation can be modeled by a linear creep law [Boulze et al. 2022]. Therefore, because of the linearity of the creep law, the superposition principle applies and the present day deformation is simply the sum of the post-seismic deformations induced by past earthquakes. Based on this result, the objective of our work is to determine what slip history is needed on the Chilean subduction interface to reproduce the current deformation of South America, which is well measured by GNSS.</p> <p>To investigate this challenging problem, we first develop a 3D spherical finite-element model of the Chilean subduction zone. This model covers the entire South American continent and incorporates a slab with a geometry described by Slab2.0 model [Hayes et al. 2018]. Then, we compare different ways to model the seismic cycle using the backslip theory [Savage 1983]. Finally, by comparing GPS time-series with our seismic cycle model prediction, we discuss many ingredients of the model: e.g. the viscosity of the asthenosphere (Maxwell, Burgers), the impact of a flat slab and low viscosity zones, the magnitude and extent of historical earthquakes.</p>