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Sea ice loss predicted to slow in the Atlantic, says new CVP-funded research

“There is little doubt that we will see a decline in Arctic sea ice cover in this century in response to anthropogenic warming, and yet internal climate variations and other external forcings could generate considerable spread in Arctic sea ice trends on decadal timescales,” begins a newly released article by Yeager et al., in Geophysical Research Letters.

Sea ice loss predicted to slow in the Atlantic, says new CVP-funded research Read More »

Sustainable management and resilience of U.S. fisheries in a changing climate: a collaboration between OAR and NMFS

In partnership with the National Marine Fisheries Service (NMFS) Office of Science and Technology, CPO’s Coastal and Ocean Climate Applications (COCA) program competitively awarded seven grants projects in FY 2015 focused on increasing the understanding of climate-related impacts on fish stocks and fisheries.  The roughly $5 million in grants cover a two- to three-year time period.

Sustainable management and resilience of U.S. fisheries in a changing climate: a collaboration between OAR and NMFS Read More »

Sea level feedback lowers projections of future Antarctic Ice-Sheet mass loss, says CPO-funded research

Research supported by CPO’s MAPP and CVP programs evaluated the influence of the feedback mechanism between sea-level fall and ice sheets on future AIS retreat on centennial and millennial timescales for different emission scenarios, using a coupled ice sheet-sea-level model.

Sea level feedback lowers projections of future Antarctic Ice-Sheet mass loss, says CPO-funded research Read More »

Novel data science approaches could drive advances in seasonal to sub-seasonal predictions of precipitation

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.

Novel data science approaches could drive advances in seasonal to sub-seasonal predictions of precipitation Read More »

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