Oscar Alves

TL;DR: In this article, the authors assessed the performance of multilevel ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980-2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC).

TL;DR: In this article, a multi-reanalysis ensemble is used to estimate the signal-to-noise ratio (SNR) of the ocean state and to estimate uncertainty levels.

TL;DR: In this article, a 10-member ensemble of hindcasts from POAMA, the Australian Bureau of Meteorology coupled ocean-atmosphere seasonal prediction system, is assessed using a 10.5-day forecast, with a bivariate correlation exceeding 0.5 and the bivariate RMSE remaining below 1.4.

TL;DR: In this article, a 1-month lead retrospective analysis of 13 state-of-the-art coupled climate models and their multi-model ensemble (MME) is presented.

TL;DR: In this paper, the authors explored the ability to predict the differences in pattern of anomalous ocean temperatures for two prominent types of El Nino, traditional cold tongue events that have maximum surface warming in the eastern Pacific, and warm pool events that had maximum surface heating in the central Pacific.