Hidden Tropical Pacific Sea Surface Temperature States Reveal Global Predictability for Monthly Precipitation for Sub‐Season to Annual Scales

نویسندگان

چکیده

We present the first global precipitation predictability estimates corresponding to recently discovered flavors of El Niño Southern Oscillation (ENSO) that are encoded in hidden states Tropical Pacific sea surface temperatures identified using a non-homogeneous Markov model. For each calendar month and for state, we assess future through conditional standardized anomaly average standard deviation monthly precipitation, at 1, 3, 6, 9, 12 months lead times. find statistically significant potential predictive skill key regions state month, even 12-months future. apply algorithm sequentially over period record identify can be consistently predicted different times months. The cross-validated correlation is demonstrably superior regression with an ENSO index used same way.

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ژورنال

عنوان ژورنال: Geophysical Research Letters

سال: 2022

ISSN: ['1944-8007', '0094-8276']

DOI: https://doi.org/10.1029/2022gl099572