Predictions at the seasonal to sub-seasonal scale are important for planning and decision-making in a variety of disciplines, and improving understanding and model skill at this timescale is a key research priority. An as yet underexplored approach to sub-seasonal prediction using data science and graph theory methods that are increasingly common to other fields outside of meteorology and climate science shows potential to improve predictions at this challenging timescale.
A new paper in the Journal of Geophysical Research: Oceans explores the ability of 2-dimensional and 3-dimensional storm surge models to simulate current, sediment transport, and the effects of vegetation on storm surge.
If Toto had been a group of climate modelers instead of a band, the song “Africa” might have informed listeners that East Africa has two rainy seasons--long rains from March to May and short rains from October to December.
Research supported by CPO's Climate Variability and Predictability program (CVP) and published in the Journal of Climate tests the wintertime atmospheric response to North Atlantic Ocean circulation variability in CCSM4.
Americans’ health, security and economic wellbeing are tied to climate and weather. Every day, we see communities grappling with environmental challenges due to unusual or extreme events related to climate and weather. In 2011, the United States experienced a record high number (14) of climate- and weather-related disasters where overall costs reached or exceeded $1 billion. Combined, these events claimed 670 lives, caused more than 6,000 injuries, and cost $55 billion in damages. Businesses, policy leaders, resource managers and citizens are increasingly asking for information to help them address such challenges.
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