Climate impact of idealized winter polar mesospheric and stratospheric ozone losses as caused by energetic particle precipitation

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Abstract

<p><strong>Abstract.</strong> Energetic particles enter the polar atmosphere and enhance the production of nitrogen oxides and hydrogen oxides in the winter stratosphere and mesosphere. Both components are powerful ozone destroyers. Recently, it has been inferred from observations that the direct effect of energetic particle precipitation (EPP) causes significant long-term mesospheric ozone variability. Satellites observe a decrease in mesospheric ozone up to 34 % between EPP maximum and EPP minimum. Stratospheric ozone decreases due to the indirect effect of EPP by about 10–15 % observed by satellite instruments. Here, we analyze the climate impact of winter boreal idealized polar mesospheric and polar stratospheric ozone losses as caused by EPP in the coupled Max Planck Institute Earth System Model (MPI-ESM). Using radiative transfer modeling, we find that the radiative forcing of mesospheric ozone loss during polar night is small. Hence, climate effects of mesospheric ozone loss due to energetic particles seem unlikely. Stratospheric ozone loss due to energetic particles warms the winter polar stratosphere and subsequently weakens the polar vortex. However, those changes are small, and few statistically significant changes in surface climate are found.</p>

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An Overview of CMIP5 and the Experiment Design

Karl E. Taylor, Ronald J Stouffer, Gerald Meehl (2012)

The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance our knowledge of climate variability and climate change. Researchers worldwide are analyzing the model output and will produce results likely to underlie the forthcoming Fifth Assessment Report by the Intergovernmental Panel on Climate Change. Unprecedented in scale and attracting interest from all major climate modeling groups, CMIP5 includes “long term” simulations of twentieth-century climate and projections for the twenty-first century and beyond. Conventional atmosphere–ocean global climate models and Earth system models of intermediate complexity are for the first time being joined by more recently developed Earth system models under an experiment design that allows both types of models to be compared to observations on an equal footing. Besides the longterm experiments, CMIP5 calls for an entirely new suite of “near term” simulations focusing on recent decades and the future to year 2035. These “decadal predictions” are initialized based on observations and will be used to explore the predictability of climate and to assess the forecast system's predictive skill. The CMIP5 experiment design also allows for participation of stand-alone atmospheric models and includes a variety of idealized experiments that will improve understanding of the range of model responses found in the more complex and realistic simulations. An exceptionally comprehensive set of model output is being collected and made freely available to researchers through an integrated but distributed data archive. For researchers unfamiliar with climate models, the limitations of the models and experiment design are described.

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Stratospheric harbingers of anomalous weather regimes.

Mark P. Baldwin, Timothy J. Dunkerton (2001)

Observations show that large variations in the strength of the stratospheric circulation, appearing first above approximately 50 kilometers, descend to the lowermost stratosphere and are followed by anomalous tropospheric weather regimes. During the 60 days after the onset of these events, average surface pressure maps resemble closely the Arctic Oscillation pattern. These stratospheric events also precede shifts in the probability distributions of extreme values of the Arctic and North Atlantic Oscillations, the location of storm tracks, and the local likelihood of mid-latitude storms. Our observations suggest that these stratospheric harbingers may be used as a predictor of tropospheric weather regimes.