Publications by authors named "Mark Serreze"

9 Publications

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New climate models reveal faster and larger increases in Arctic precipitation than previously projected.

Nat Commun 2021 Nov 30;12(1):6765. Epub 2021 Nov 30.

College of Engineering, Maths, and Physical Sciences, University of Exeter, Exeter, UK.

As the Arctic continues to warm faster than the rest of the planet, evidence mounts that the region is experiencing unprecedented environmental change. The hydrological cycle is projected to intensify throughout the twenty-first century, with increased evaporation from expanding open water areas and more precipitation. The latest projections from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) point to more rapid Arctic warming and sea-ice loss by the year 2100 than in previous projections, and consequently, larger and faster changes in the hydrological cycle. Arctic precipitation (rainfall) increases more rapidly in CMIP6 than in CMIP5 due to greater global warming and poleward moisture transport, greater Arctic amplification and sea-ice loss and increased sensitivity of precipitation to Arctic warming. The transition from a snow- to rain-dominated Arctic in the summer and autumn is projected to occur decades earlier and at a lower level of global warming, potentially under 1.5 °C, with profound climatic, ecosystem and socio-economic impacts.
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http://dx.doi.org/10.1038/s41467-021-27031-yDOI Listing
November 2021

Shrinking snowpacks, anxious snow lovers Little, Brown, 2021. 320 pp.

Authors:
Mark Serreze

Science 2021 Nov 18;374(6570):944. Epub 2021 Nov 18.

The reviewer is at the National Snow and Ice Data Center (NSIDC), University of Colorado, Boulder, CO 80309, USA, and the author of Brave New Arctic: The Untold Story of the Melting North (Princeton Univ. Press, 2018).

[Figure: see text].
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http://dx.doi.org/10.1126/science.abm3456DOI Listing
November 2021

The Arctic's sea ice cover: trends, variability, predictability, and comparisons to the Antarctic.

Ann N Y Acad Sci 2019 01 28;1436(1):36-53. Epub 2018 May 28.

National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado.

As assessed over the period of satellite observations, October 1978 to present, there are downward linear trends in Arctic sea ice extent for all months, largest at the end of the melt season in September. The ice cover is also thinning. Downward trends in extent and thickness have been accompanied by pronounced interannual and multiyear variability, forced by both the atmosphere and ocean. As the ice thins, its response to atmospheric and oceanic forcing may be changing. In support of a busier Arctic, there is a growing need to predict ice conditions on a variety of time and space scales. A major challenge to providing seasonal scale predictions is the 7-10 days limit of numerical weather prediction. While a seasonally ice-free Arctic Ocean is likely well within this century, there is much uncertainty in the timing. This reflects differences in climate model structure, the unknown evolution of anthropogenic forcing, and natural climate variability. In sharp contrast to the Arctic, Antarctic sea ice extent, while highly variable, has increased slightly over the period of satellite observations. The reasons for this different behavior remain to be resolved, but responses to changing atmospheric circulation patterns appear to play a strong role.
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http://dx.doi.org/10.1111/nyas.13856DOI Listing
January 2019

Arctic sea ice trends, variability and implications for seasonal ice forecasting.

Philos Trans A Math Phys Eng Sci 2015 Jul;373(2045)

National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences, University of Colorado, Campus Box 449, Boulder, CO 80309-0449, USA Centre for Polar Observation and Modelling, Pearson Building, University College London, Gower Street, London WC1E 6BT, UK.

September Arctic sea ice extent over the period of satellite observations has a strong downward trend, accompanied by pronounced interannual variability with a detrended 1 year lag autocorrelation of essentially zero. We argue that through a combination of thinning and associated processes related to a warming climate (a stronger albedo feedback, a longer melt season, the lack of especially cold winters) the downward trend itself is steepening. The lack of autocorrelation manifests both the inherent large variability in summer atmospheric circulation patterns and that oceanic heat loss in winter acts as a negative (stabilizing) feedback, albeit insufficient to counter the steepening trend. These findings have implications for seasonal ice forecasting. In particular, while advances in observing sea ice thickness and assimilating thickness into coupled forecast systems have improved forecast skill, there remains an inherent limit to predictability owing to the largely chaotic nature of atmospheric variability.
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http://dx.doi.org/10.1098/rsta.2014.0159DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4455712PMC
July 2015

Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models.

Glob Chang Biol 2012 Sep 3;18(9):2756-70. Epub 2012 Jul 3.

Biology Department, MS-34, Woods Hole Oceanographic Institution, Woods Hole, MA, 02543, USA; Centre d'Etudes Biologiques de Chizé, Centre National de la Recherche Scientifique, F-79360, Villiers en Bois, France; National Snow and Ice Data Center, Boulder, 80309, CO, USA; Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder, 80309-0449, CO, USA.

Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage-structured, seasonal, nonlinear, two-sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture-mark-recapture analysis, we find that seasonal sea ice concentration anomalies (SICa ) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SICa , because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SICa . We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SICa , which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor penguin. Our analytical approach, in which demographic models are linked to IPCC climate models, is powerful and generally applicable to other species and systems.
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http://dx.doi.org/10.1111/j.1365-2486.2012.02744.xDOI Listing
September 2012

Climate change: Rethinking the sea-ice tipping point.

Authors:
Mark C Serreze

Nature 2011 Mar;471(7336):47-8

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http://dx.doi.org/10.1038/471047aDOI Listing
March 2011

Understanding recent climate change.

Authors:
Mark C Serreze

Conserv Biol 2010 Feb;24(1):10-7

Cooperative Institute for Research in Environmental Sciences, University of Colorado, Colorado Springs, CO 80907, USA.

The Earth's atmosphere has a natural greenhouse effect, without which the global mean surface temperature would be about 33 degrees C lower and life would not be possible. Human activities have increased atmospheric concentrations of carbon dioxide, methane, and other gases in trace amounts. This has enhanced the greenhouse effect, resulting in surface warming. Were it not for the partly offsetting effects of increased aerosol concentrations, the increase in global mean surface temperature over the past 100 years would be larger than observed. Continued surface warming through the 21st century is inevitable and will likely have widespread ecological impacts. The magnitude and rate of warming for the global average will be largely dictated by the strength and direction of climate feedbacks, thermal inertia of the oceans, the rate of greenhouse gas emissions, and aerosol concentrations. Because of regional expressions of climate feedbacks, changes in atmospheric circulation, and a suite of other factors, the magnitude and rate of warming and changes in other key climate elements, such as precipitation, will not be uniform across the planet. For example, due to loss of its floating sea-ice cover, the Arctic will warm the most.
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http://dx.doi.org/10.1111/j.1523-1739.2009.01408.xDOI Listing
February 2010

Perspectives on the Arctic's shrinking sea-ice cover.

Science 2007 Mar;315(5818):1533-6

Cooperative Institute for Research in Environmental Sciences, National Snow and Ice Data Center, Campus Box 449, University of Colorado, Boulder, CO 80309-0449, USA.

Linear trends in arctic sea-ice extent over the period 1979 to 2006 are negative in every month. This ice loss is best viewed as a combination of strong natural variability in the coupled ice-ocean-atmosphere system and a growing radiative forcing associated with rising concentrations of atmospheric greenhouse gases, the latter supported by evidence of qualitative consistency between observed trends and those simulated by climate models over the same period. Although the large scatter between individual model simulations leads to much uncertainty as to when a seasonally ice-free Arctic Ocean might be realized, this transition to a new arctic state may be rapid once the ice thins to a more vulnerable state. Loss of the ice cover is expected to affect the Arctic's freshwater system and surface energy budget and could be manifested in middle latitudes as altered patterns of atmospheric circulation and precipitation.
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http://dx.doi.org/10.1126/science.1139426DOI Listing
March 2007

Meitdown in the North.

Sci Am 2003 Oct;289(4):60-7

U.S. Army Cold Regions Research and Engineering Laboratory-Alaska, USA.

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http://dx.doi.org/10.1038/scientificamerican1003-60DOI Listing
October 2003
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