3 papers
cs.LG2026
Probabilistic bias adjustment of seasonal forecasts using generative machine learning: A case study of Arctic sea ice predictions
Parsa Gooya, Reinel Sospedra-Alfonso
Seasonal climate predictions support planning and risk management by offering early information of the most likely-to-occur climate conditions in the coming months, and associated…
cs.LG2026
Probabilistic bias adjustment of seasonal predictions of Arctic Sea Ice Concentration
Parsa Gooya, Reinel Sospedra-Alfonso
Seasonal forecast of Arctic sea ice concentration is key to mitigate the negative impact and assess potential opportunities posed by the rapid decline of sea ice coverage. Seasonal…
cs.LG2026
Toward generative machine learning for boosting ensembles of climate simulations
Parsa Gooya, Reinel Sospedra-Alfonso, Johannes Exenberger
Accurately quantifying uncertainty in predictions and projections arising from irreducible internal climate variability is critical for informed decision making. Such uncertainty i…