The M ∼ 8.3–8.4 25 November 1941 was one of the largest submarine strike-slip earthquakes ever recorded in the Northeast (NE) Atlantic basin. This event occurred along the Eurasia–Nubia plate boundary between the Azores and the Strait of Gibraltar. After the earthquake, the tide stations in the NE Atlantic recorded a small tsunami with maximum amplitudes of 40 cm peak to through in the Azores and Madeira islands. In this study, we present a re-evaluation of the earthquake epicentre location using seismological data not included in previous studies. We invert the tsunami travel times to obtain a preliminary tsunami source location using the backward ray tracing (BRT) technique. We invert the tsunami waveforms to infer the initial sea surface displacement using empirical Green's functions, without prior assumptions about the geometry of the source. The results of the BRT simulation locate the tsunami source quite close to the new epicentre. This fact suggests that the co-seismic deformation of the earthquake induced the tsunami. The waveform inversion of tsunami data favours the conclusion that the earthquake ruptured an approximately 160 km segment of the plate boundary, in the eastern section of the Gloria Fault between −20.249 and −18.630° E. The results presented here contribute to the evaluation of tsunami hazard in the Northeast Atlantic basin.

Monitoring lakes in high-latitude areas can provide a better understanding of freshwater systems sensitivity and accrete knowledge on climate change impacts. Phytoplankton are sensitive to various conditions: warmer temperatures, earlier ice-melt and changing nutrient sources. While satellite imagery can monitor phytoplankton biomass using chlorophyll a (Chl) as a proxy over large areas, detection of Chl in small lakes is hindered by the low spatial resolution of conventional ocean color satellites. The short time-series of the newest generation of space-borne sensors (e.g., Sentinel-2) is a bottleneck for assessing long-term trends. Although previous studies have evaluated the use of high-resolution sensors for assessing lakes’ Chl, it is still unclear how the spatial and temporal variability of Chl concentration affect the performance of satellite estimates. We discuss the suitability of Landsat (LT) 30 m resolution imagery to assess lakes’ Chl concentrations under varying trophic conditions, across extensive high-latitude areas in Finland. We use in situ data obtained from field campaigns in 19 lakes and generate remote sensing estimates of Chl, taking advantage of the long-time span of the LT-5 and LT-7 archives, from 1984 to 2017. Our results show that linear models based on LT data can explain approximately 50% of the Chl interannual variability. However, we demonstrate that the accuracy of the estimates is dependent on the lake’s trophic state, with models performing in average twice as better in lakes with higher Chl concentration (>20 µg/L) in comparison with less eutrophic lakes. Finally, we demonstrate that linear models based on LT data can achieve high accuracy (R² = 0.9; p-value < 0.05) in determining lakes’ mean Chl concentration, allowing the mapping of the trophic state of lakes across large regions. Given the long time-series and high spatial resolution, LT-based estimates of Chl provide a tool for assessing the impacts of environmental change.

Monitoring lakes in high-latitude areas can provide a better understanding of freshwater systems sensitivity and accrete knowledge on climate change impacts. Phytoplankton are sensitive to various conditions: warmer temperatures, earlier ice-melt and changing nutrient sources. Satellite imagery can monitor algae biomass over large areas. The detection of chlorophyll a (chl-a) concentrations in small lakes is hindered by the low spatial resolution of conventional ocean colour satellites. The short time-series of the newest generation of space-borne sensors (e.g. Sentinel-2) is a bottleneck for assessing long-term trends. Although previous studies have evaluated the use of high-resolution sensors for assessing lakes' chl-a, it is still unclear how the spatial and temporal variability of chl-a concentration affect the performance of satellite estimates. We discuss the suitability of Landsat (LT) 30-m resolution imagery to assess lakes' chl-a concentrations under varying trophic conditions, across extensive high-latitude areas in Finland. We use in situ data obtained from field campaigns in 19 lakes and generate remote sensing estimates of chl-a, taking advantage of the long-time span of the LT 5 and 7 archives, from 1984 to 2017. Our results show that linear models based on LT data can explain approximately 50 % of the chl-a interannual variability. However, we demonstrate that the accuracy of the estimates is dependent on the lake's trophic state, with models performing in average twice as better in lakes with higher chl-a concentration (> 20 µg/l) in comparison with less eutrophic lakes. Finally, we demonstrate that linear models based on LT data can achieve high accuracy (R2 = 0.9; p-value < 0.05) in determining lakes' annual mean chl-a concentration, allowing the mapping of the trophic state of lakes across large regions. Given the long time-series and high spatial resolution, LT-based estimates of chl-a provide a tool for assessing the impacts of environmental change.

The M~8.3–8.4 25th November 1941 was one of the largest submarine strike-slip earthquakes ever recorded in the North East (NE) Atlantic basin. This event occurred along the Eurasia-Nubia plate boundary between the Azores and the Strait of Gibraltar. After the earthquake, the tide stations in the NE Atlantic recorded a small tsunami with maximum amplitudes of 40 cm peak to throw in Azores and Madeira islands. In this study, we present a re-evaluation of the earthquake epicentre location using seismological data not included in previous studies. We invert the tsunami travel times to obtain a preliminary tsunami source location using a backward ray tracing (BRT) technique. We invert the tsunami waveforms to infer the initial sea surface displacement using Empirical Green Functions without prior assumptions on the geometry of the source. The results of the BRT simulation locate the tsunami source quite close to the new epicentre. This fact suggests that the co-seismic deformation of the earthquake induced the tsunami. The waveform inversion of tsunami data favours the conclusion that the earthquake ruptured approximately 160 km segment of the plate boundary, in the eastern section of the Gloria Fault between −20.249°E and −18.630°E. The results presented here contribute to the evaluation of tsunami hazard in the North East Atlantic basin.