Abstract This work investigated the annual variations in dry snow (DSRZ) and wet snow radar zones (WSRZ) in the north of the Antarctic Peninsula between 2015-2023. A specific code for snow zone detection on Sentinel-1 images was created on Google Earth Engine by combining the CryoSat-2 digital elevation model and air temperature data from ERA5. Regions with backscatter coefficients (σ⁰) values exceeding -6.5 dB were considered the extent of surface melt occurrence, and the dry snow line was considered to coincide with the -11 °C isotherm of the average annual air temperature. The annual variation in WSRZ exhibited moderate correlations with annual average air temperature, total precipitation, and the sum of annual degree-days. However, statistical tests indicated low determination coefficients and no significant trend values in DSRZ behavior with atmospheric variables. The results of reducing DSRZ area for 2019/2020 and 2020/2021 compared to 2018/2018 indicated the upward in dry zone line in this AP region. The methodology demonstrated its efficacy for both quantitative and qualitative analyses of data obtained in digital processing environments, allowing for the large-scale spatial and temporal variations monitoring and for the understanding changes in glacier mass loss. (DSRZ (WSRZ 20152023. 20152023 2015 2023. 2023 2015-2023 Sentinel1 Sentinel 1 Sentinel- CryoSat2 CryoSat 2 CryoSat- ERA5 ERA σ⁰ σ (σ⁰ 6.5 65 6 5 -6. occurrence 11 -1 C precipitation degreedays. degreedays degree days. days degree-days However variables 20192020 2019 2020 2019/202 20202021 2021 2020/202 20182018 2018 2018/201 region environments largescale large scale loss 2015202 201 202 2015-202 (σ 6. -6 - 2019202 2019/20 2020202 2020/20 2018201 2018/20 201520 20 2015-20 201920 2019/2 202020 2020/2 201820 2018/2 20152 2015-2 20192 2019/ 20202 2020/ 20182 2018/ 2015-

ABSTRACT Knowledge of coastal hydrodynamics is essential for understanding the processes of transport of dissolved or particulate material since in these areas there are large ports and the vessel traffic with a greater possibility of accidents. Studies related to currents are of fundamental importance to support decision-making to mitigate environmental impacts. The present work aims to test the technique of measuring currents through drones, as it has the advantage of a quick response in obtaining and analyzing data. For this study, a field survey was carried out in the region of the mouth of Lagoa dos Patos, RS, Brazil. The method's validation was done through the use of a colored tracer in which it was used to measure the surface current velocities simultaneously with the vectors generated by the drone. The results obtained a percentage difference between the methods of 10%, both for speed and for current direction, showing to be very promising for the use of drones to obtain surface current fields. In this way, it opens a new perspective in carrying out field experiments, so new experiments will be carried out to verify the feasibility of using this technique in different conditions, such as in the surf zone and areas with the presence of density fronts. accidents decisionmaking decision making impacts data study Patos RS Brazil method s drone 10 10% direction fields way conditions fronts 1

Abstract This study evaluated feasibility statistically and analyzed, during the freezing period, the relationship between brightness temperature (Tb) data of the 37V polarisation and the GR3719 (Gradient Ratio 37V and 19V) obtained by Special Sensor Microwave/Imager from F11 and F13 satellites with sea ice thickness (SIT) data obtained in the Weddell Sea through Antarctic Sea Ice Processes and Climate program. The multiple linear regression (MLR) was applied at 1,520 points, with 70% of these points being randomly separated to generate the MLR and 30% to carry out the validation. To perform the temporal mapping, the MLR was applied only to pixels with sea ice concentration (SIC) ≥ 90%, obtained through the fraction image calculated from the spectral linear mixing model (SLMM) using the Tb in the channels and polarizations 19H, 19V and 37V. The results of the SLMM validation process for estimating the SIC were σ = 10.5%, RMSE = 11.0%, and bias = -2.8%, and the SIT based on the MLR, the results were R² = 0.57, RMSE = 0.268 m, and bias = 0.103 m. In the SIT mapping, we highlight the trend of thickness reduction on the east coast of the Antarctic Peninsula during the period 1992–2009. analyzed (Tb V GR GR371 Gradient MicrowaveImager Microwave Imager F F1 (SIT program (MLR 1520 1 520 1,52 70 30 mapping (SIC 90 90% (SLMM 19H H 105 10 5 10.5% 110 11 0 11.0% 2.8%, 28 2 8 -2.8% R 057 57 0.57 0268 268 0.26 m 0103 103 0.10 19922009 1992 2009 1992–2009 GR37 152 52 1,5 7 3 9 10.5 11.0 2.8% -2.8 05 0.5 026 26 0.2 010 0.1 1992200 199 200 1992–200 GR3 15 1, 10. 11. 2.8 -2. 0. 02 01 199220 19 20 1992–20 2. -2 19922 1992–2 - 1992–

Abstract Several studies have utilized passive microwave imagery for monitoring snowmelt in Antarctica. However, due to the low spatial resolution of these images (25 km), the quantification of snowmelt is not precise. To enhance the accuracy of these estimations, this study proposed a subpixel analysis approach based on a Spectral Linear Mixing Model. This approach was applied to images obtained from channels 18/19 GHz and 37 GHz, both horizontally and vertically polarized, acquired from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), and Special Sensor Microwave Imager/Sounder (SSM/IS) instruments, spanning the period 1978-2018. The spatiotemporal analysis of the estimated snowmelt fraction images indicated that the most persistent and intensive melt was observed on the Antarctic Peninsula, particularly on the Larsen, Wilkins, George VI, and Wordie ice shelves. The melting period in the Antarctic Peninsula began in late October, with a peak in early January, and ended in late March. Other regions with persistent and intensive snowmelt were Mary Bird Land and Wilkes Land, followed by Dronning Maud Land, Amery Ice Shelf, Filchner-Ronne Ice Shelf, and Ross Ice Shelf. These snowmelt data are valuable for modeling the impacts of snowmelt on glacial systems, local coastal environments, and sea-level rise. Antarctica However 25 (2 km, km , km) precise estimations Model 1819 18 19 18/1 3 polarized SMMR, SMMR (SMMR) SSM/I, SSMI SSM/I SSM I (SSM/I) ImagerSounder Sounder SSM/IS SSMIS IS (SSM/IS instruments 19782018. 19782018 1978 2018. 2018 1978-2018 Larsen Wilkins VI shelves October January March Shelf FilchnerRonne Filchner Ronne systems environments sealevel sea level rise 2 ( 181 1 18/ (SMMR (SSM/I 1978201 197 201 1978-201 197820 20 1978-20 19782 1978-2 1978-

Abstract Using data from SCAR observations, ERA5 reanalysis, and regional climate model simulations (RACMO), we examined the influence of large- and regional-scale climate forcing on temperature and precipitation variations in the South Shetland Islands (SSI). Specifically, we focused on understanding how regional climate indices influence the temporal variability of temperature and precipitation on the SSI. Our findings indicate that both large- and regional-scale climate indices significantly impact the interannual and seasonal temperature variability in the SSI. For instance, the Amundsen Sea Low, characterised by low-pressure systems over the Amundsen Sea, and sea ice extent in the northwestern part of the Weddell Sea, exert a strong influence on temperature variability (r from -0.64 to -0.87; p < 0.05). In contrast, precipitation variability in this region is primarily controlled by regional climatic indices. Particularly, anomalies in atmospheric and surface pressure over the Drake Passage region strongly regulate the interannual variability of precipitation in the SSI (r from -0.46 to -0.70; p < 0.05). Large-scale climatic indices demonstrate low but statistically significant correlations, including the Southern Annular Mode and deep convection in the central tropical Pacific. Given the importance of temperature and precipitation in the glacier changes, we recommend assessing the impact of the Drake region on SSI glaciers. observations ERA reanalysis RACMO, RACMO , (RACMO) large regionalscale scale . (SSI) Specifically instance Low lowpressure r 0.64 064 0 64 -0.6 0.87 087 87 -0.87 0.05. 005 0.05 05 0.05) contrast Particularly 0.46 046 46 -0.4 0.70 070 70 -0.70 Largescale Large correlations Pacific changes glaciers (RACMO (SSI 0.6 06 6 -0. 0.8 08 8 -0.8 00 0.0 0.4 04 4 0.7 07 7 -0.7 0. -0 -

Abstract The classification of Synthetic Aperture Radar (SAR) images by knowledge-based algorithms with elevation and backscatter thresholds were used in several studies to detect the Wet Snow Radar Zone (WSZ) in the Antarctic Peninsula. To identify it more accurately based on its seasonal variations, this study proposed the additional use of a threshold in synthetic images, created by rationing summer and winter sigma linear images. In our algorithm we used the following thresholds to detect the WSZ in Envisat ASAR imageries, using the Radarsat Antarctic Map Digital Elevation Model as ancillary data: i) -25 dB < s0 < -14 dB; ii) slinear summer / slinear winter < 0.4; iii) elevation H < 1,200 m for northern tip and H < 800 m for southern tip of the Antarctic Peninsula. The classified images were post-processed by a focal majority 5 x 5 filter and superimposed by an image of rock outcrops derived from the Antarctic Digital Database. The ratio image threshold allowed discriminating the WSZ from the Dry Snow Radar Zone and radar shadows, as well as transitional areas between this glacier zone and the Frozen Percolation Radar Zone, which would be classified incorrectly if we used only elevation and backscatter thresholds.

Abstract This paper describes wave prediction results for Patos Lagoon's northern sector through numerical modeling using Delft3D software. ERA-Interim satellite reanalysis data of wind intensity and direction were used as inputs to force the hydrodynamic model. For SWAN calibration and validation in the study region, wave parameters were used. These parameters were acquired in situ by a directional waverider buoy. Statistical data showed the good performance of the model, albeit with a tendency to overestimate significant wave height and underestimate peak period and propagation direction. Once validated, wave parameters for five points at different depths were obtained during the four seasons of the year between 2017 and 2018. In general, it was observed that the largest ripples come from the S and SSW directions and occurred during spring at the deepest point under wind conditions exceeding 10 m s-1. Ripples up to 0.30 m account for 77.9 % at the shallowest point and 65.7 % at the deepest point. Thus, the study area was classified as low energy and characterized by small, high-frequency, short-period ripples strongly influenced and determined by the local depth because larger ripples are always observed in the deepest locations, giving the lagoon a characteristic of depth-limited ripples. The results obtained here have the potential to contribute to territorial management of the region, with emphasis on the Integral Protection Conservation Unit located in the study area (Itapuã State Park) and on the development and safety of the important, heavily used navigation route that connects Rio Grande Port to the state capital, Porto Alegre.