A Physics-informed Deep Learning Based Clustering to Investigate the Impact of Regional European Radiative Forcing on Arctic Climate and Upper Atmospheric Dynamics. EGU24-16391Copernicus Meetings, 2024. [PUMA: imported topic_earthenvironment]
Arctic climate response to European radiative forcing: a deep learning study on circulation pattern changes. Weather and Climate Dynamics, (5)4:1223-1268, Copernicus Publications, 2024. [PUMA: imported topic_earthenvironment]
ALAS: Active Learning for Autoconversion Rates Prediction from Satellite Data. 3358-3366, PMLR, 2024. [PUMA: imported topic_earthenvironment]
CloudViT: classifying cloud types in global satellite data and in kilometre-resolution simulations using vision transformers. EGUsphere, (2024):1-31, Copernicus Publications, 2024. [PUMA: imported topic_earthenvironment]
Marine cloud base height retrieval from MODIS cloud properties using machine learning. Atmospheric Measurement Techniques, (17)18:5655-5677, Copernicus Publications, 2024. [PUMA: imported topic_earthenvironment]
Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learning. Environmental Data Science, (3):e23, Cambridge University Press, 2024. [PUMA: imported topic_earthenvironment]
Leveraging surface observations and passive satellite retrievals of cloud properties: Applications to cloud type classification and cloud base height retrieval. EGU24-18214Copernicus Meetings, 2024. [PUMA: imported topic_earthenvironment]
Arctic Climate Response to European Radiative Forcing: A Deep Learning Approach. EGUsphere, (2024):1-55, Copernicus Publications, 2024. [PUMA: imported topic_earthenvironment]
From insufficient rainfall to livelihoods: understanding the cascade of drought impacts and policy implications. EGUsphere, (2024):1-20, Copernicus Publications, 2024. [PUMA: imported topic_earthenvironment]
Integrated proactive drought management in hydrosystems and cities: building a nine-step participatory planning methodology. Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, (115)3:2179-2204, Springer & International Society for the Prevention and Mitigation of Natural Hazards, 2023. [PUMA: imported topic_earthenvironment]
Water management assessment with text mining. EGU General Assembly Conference Abstracts, EGU-8349, 2023. [PUMA: imported topic_earthenvironment]
Variational Mode Decomposition Hybridized With Gradient Boost Regression for Seasonal Forecast of Residential Water Demand. Water Resources Management, (35)10:3431-3445, Springer Netherlands, 2021. [PUMA: imported topic_earthenvironment]
Identification of correlation between residential water demand and average income using the pool regression model: Study case in Fortaleza-Brazil. Water Utility Journal, 2020. [PUMA: imported topic_earthenvironment]
Quantifying sensitivity to drought: Study case in São Paulo and Ceará, Brazil. 2019. [PUMA: imported topic_earthenvironment]
A data-driven model to evaluate the medium-term effect of contingent pricing policies on residential water demand. Environmental Challenges, (3):100033, Elsevier, 2021. [PUMA: imported topic_earthenvironment]
A GLM copula approach for multisite annual streamflow generation. Journal of Hydrology, (598):126226, Elsevier, 2021. [PUMA: imported topic_earthenvironment]
Machine Learning for Water Resources Management. 2023. [PUMA: imported topic_earthenvironment]
Performance of rainwater tanks for runoff reduction under climate change scenarios: a case study in Brazil. Urban Water Journal, (17)10:912-922, Taylor & Francis, 2020. [PUMA: imported topic_earthenvironment]
Integrated proactive drought management in hydrosystems and cities: building a nine-step participatory planning methodology. Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, (115)3:2179-2204, Springer, 2023. [PUMA: imported topic_earthenvironment]
Exploring the relationship between climate indices and hydrological time series using a machine learning approach. 2019. [PUMA: imported topic_earthenvironment]