Sea ice loss predicted to slow in the Atlantic, says new CVP-funded research 28 December 2015

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.

Sustainable management and resilience of U.S. fisheries in a changing climate: a collaboration between OAR and NMFS 14 December 2015

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.

Sea level feedback lowers projections of future Antarctic Ice-Sheet mass loss, says CPO-funded research 1 December 2015

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.
XBT Science: assessment of instrumental biases and errors 30 November 2015

XBT Science: assessment of instrumental biases and errors

A new study funded by CPO’s Climate Observation Division was recently published in the Bulletin of the American Meteorological Society. The study by Cheng et al.examines in-depth studies and offers recommendations for correcting biases in expendable bathythermograph (XBT) data.

Novel data science approaches could drive advances in seasonal to sub-seasonal predictions of precipitation 25 November 2015

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.

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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 2017, the United States experienced a record-tying 16 climate- and weather-related disasters where overall costs reached or exceeded $1 billion. Combined, these events claimed 362 lives, and had significant economic effects on the areas impacted, costing more than $306 billion. Businesses, policy leaders, resource managers and citizens are increasingly asking for information to help them address such challenges.

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