Causes for Intraseasonal Sea Surface Salinity Variability in the Western Tropical Pacific Ocean and Its Seasonality 11 January 2016

Causes for Intraseasonal Sea Surface Salinity Variability in the Western Tropical Pacific Ocean and Its Seasonality

A new CVP-supported paper published in the Journal of Geophysical Research explores variability in ocean salinity and how that variability is connected to air-sea interactions, large-scale ocean circulations, and climate phenomena such as the MJO and ENSO.
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.

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.
Intraseasonal Variability of Upwelling in the Equatorial Eastern Indian Ocean 30 November 2015

Intraseasonal Variability of Upwelling in the Equatorial Eastern Indian Ocean

A new CVP-supported study by Chen et al. titled “Intraseasonal Variability of Upwelling in the Equatorial Eastern Indian Ocean” has been published in the Journal of Geophysical Research: Oceans.

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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