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Miguel Mendes Lima
Miguel Mendes Lima
Instituto Dom Luiz, Faculdade de Ciências da Universidade de Lisboa
Verified email at fc.ul.pt
Title
Cited by
Cited by
Year
The compound event that triggered the destructive fires of October 2017 in Portugal
AM Ramos, A Russo, CC DaCamara, S Nunes, P Sousa, PMM Soares, ...
IScience 26 (3), 2023
192023
The increasing frequency of tropical cyclones in the Northeastern Atlantic sector
MM Lima, A Hurduc, AM Ramos, RM Trigo
Frontiers in Earth Science 9, 745115, 2021
142021
Upper-ocean response to the passage of tropical cyclones in the Azores region
MM Lima, CM Gouveia, RM Trigo
Ocean Science 18 (5), 1419-1430, 2022
102022
The future of extreme meteorological fire danger under climate change scenarios for Iberia
VA Bento, DCA Lima, LC Santos, MM Lima, A Russo, SA Nunes, ...
Weather and Climate Extremes 42, 100623, 2023
62023
An evaluation of the atmospheric instability effect on wildfire danger using ERA5 over the Iberian Peninsula
LC Santos, MM Lima, VA Bento, SA Nunes, CC DaCamara, A Russo, ...
Fire 6 (3), 120, 2023
52023
Updating the assessment of climate change impact on temperature at decadal scale and consolidating with CMIP6 future projections
MO Molina, PMM Soares, MM Lima, TH Gaspar, DCA Lima, AM Ramos, ...
2024
Updating the assessment of climate change at decadal scale and consolidating with CMIP6 future projections
O Molina, PMM Soares, MM Lima, DCA Lima, T Gaspar, R Trigo
EGU General Assembly Conference Abstracts, 435, 2024
2024
High-Resolution Simulation of the Extreme Fire Event in Central Portugal, Pedrogão Grande (2017)
L Santos, MM Lima, PMM Soares, RM Trigo, RM Cardoso
EGU24, 2024
2024
Langragian analysis of the extreme-windstorm dynamics associated to post-tropical cyclone Leslie landfall in Portugal
M Lima, LC Santos, RM Cardoso, PMM Soares, RM Trigo
EGU24, 2024
2024
Inferring significant wave height from seismic data: A comparison between methods.
F Bolrão, M Lima, S Sheriffdeen, D Rodrigues, G Silveira, T Bui-Thanh, ...
EGU General Assembly Conference Abstracts, EGU21-14837, 2021
2021
Predicting ocean activity from seismic data using machine learning techniques
S Custódio, F Bolrão, T Bui, C Hadziioannou, M Lima, D Rodrigues, ...
EGU General Assembly Conference Abstracts, 22619, 2020
2020
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