Avian influenza risk mapping in India using machine learning. [PDF]
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Weather-Enhanced Machine Learning for Time-Resolved Risk Stratification of Clinically Managed Hymenoptera-Related Sting Events in an Urban German Region. [PDF]
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Modeling of BOD and COD Concentrations in Aquaculture Sites of the Southeastern Coastal Region of Bangladesh Using Machine Learning. [PDF]
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Rumen DNA virome plasticity and viral metabolic potential are associated with seasonal adaptation in grazing yak and cattle on the Qinghai-Tibet Plateau. [PDF]
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Bridging the weather and climate divide with artificial intelligence. [PDF]
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Season-to-Season Cyclone Frequency Prediction
Monthly Weather Review, 1982Abstract Winter and summer half-year cyclone frequencies for eastern North America and the western North Atlantic were tabulated for 2.5° latitude by 5° longitude grid cells for the years 1885–1980. Correlation matrix eigenvectors were calculated for matrices of both the winter and summer data for a dependent set of years (1885–1959).
Bruce P. Hayden, William Smith
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The seasonal predictability of the wet season over Peninsular Florida
International Journal of Climatology, 2021AbstractIn this study, we examine the seasonal predictability of Peninsular Florida (PF)'s boreal summer season, which is also known as the PF wet season (PFWS) due to the coinciding peak of the robust seasonal cycle of rainfall. The seasonal predictability is examined in the Community Climate System Model, version 4 (CCSM4), which is one of the models
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Supercomputing the Seasonal Weather Prediction
2019Most of the WMO Global Producing Centres for Long-Range Forecasts use ensemble prediction systems together with an ensemble re-forecast dataset, also called hindcast. Both ensembles usually come from integrations of a global coupled atmosphere, ocean, land-surface and sea ice model.
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Seasonal and Decadal Prediction
2011Dynamical seasonal prediction has grown rapidly over the last decade or so. At present, a number of operational centres issue routine seasonal forecasts produced with coupled ocean-atmosphere models. These require real-time knowledge of the state of the global ocean since the potential for climate predictability at seasonal time scales resides mostly ...
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Seasonal predictability of the ensemble seasonal prediction by tier-1 and tier-1.5 models
SPIE Proceedings, 2009By using a hybrid model tier-1 that is coupled in the Indo-Pacific tropical ocean, we perform a set of 10 ensemble runs with different initial condition for two-season period that starts from November 1st and May 1st respectively in 1982 though 2004.
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