The effect of interactive ozone chemistry on weak and strong stratospheric polar vortex events

Modeling and observational studies have reported effects of stratospheric ozone extremes on Northern Hemisphere spring climate. Recent work has further suggested that the coupling of ozone chemistry and dynamics amplifies the surface response to midwinter sudden stratospheric warmings (SSWs). Here w...

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Bibliographic Details
Main Authors: Chiodo, Gabriel, Oehrlein, Jessica, Polvani, Lorenzo M.
Format: Dataset
Language:English
Published: Dryad 2020
Subjects:
Online Access:https://dx.doi.org/10.5061/dryad.6q573n5x8
http://datadryad.org/stash/dataset/doi:10.5061/dryad.6q573n5x8
Description
Summary:Modeling and observational studies have reported effects of stratospheric ozone extremes on Northern Hemisphere spring climate. Recent work has further suggested that the coupling of ozone chemistry and dynamics amplifies the surface response to midwinter sudden stratospheric warmings (SSWs). Here we study the importance of interactive ozone chemistry in representing the stratospheric polar vortex and Northern Hemisphere winter surface climate variability. We contrast two simulations from the interactive and specified chemistry (and thus ozone) versions of the Whole Atmosphere Community Climate Model, which is designed to isolate the impact of interactive ozone on polar vortex variability. In particular, we analyze the response with and without interactive chemistry to midwinter SSWs, March SSWs, and strong polar vortex events (SPVs). With interactive chemistry, the stratospheric polar vortex is stronger and more SPVs occur, but we find little effect on the frequency of midwinter SSWs. At the surface, interactive chemistry results in a pattern resembling a more negative North Atlantic Oscillation following midwinter SSWs but with little impact on the surface signatures of late winter SSWs and SPVs. These results suggest that including interactive ozone chemistry is important for representing North Atlantic and European winter climate variability. : This dataset consists of a set of meteorological and chemical fields produced by the CESM-WACCM4 chemistry climate model, which have been used to produce the analysis described in the paper. The data is in NETCDF format and has been post-processed and formatted using the NCO command language (see http://nco.sourceforge.net/ for more details). : Each field is separately saved as NETCDF file, containing a header and metadata (header). Each field is show on geographic coordinates, which can be longitude,latitude (for surface fields, such as surface temperature and sea level pressure), or latitude,pressure level (for zonal mean fields, such as temperature, wind and geopotential height). To open the data, NETCDF libraries should be installed in the user's own operating system. See https://www.unidata.ucar.edu/software/netcdf/ for more information. Each NETCDF file is named using a naming convention which identifies the model used (1), the experiment (2), the time resolution (3), the field name (4), and the time covered. Each file is named as follows: $MODEL.$EXP.$RESOLUTION.$FIELD.$START_YEAR-$END_YEAR.nc $MODEL is waccm4 (the climate model used in this study) $EXP is: chem2000 --> CHEM run with interactive ozone nochem2000 --> NOCHEM run with specified ozone climatology $RESOLUTION is: daily --> meaning that daily values are included in the 'time' dimension. $FIELD is: Z3 --> zonal mean geopotential height (3 dimensions: lat,lev_p,time) T --> zonal mean atmospheric temperature (3 dimensions: lat,lev_p,time) U --> zonal mean zonal wind (3 dimensions: lat,lev_p,time) TOZ** --> total column ozone (1 dimension: time), polar cap average (60-90N) SLP --> sea level pressure (3 dimensions: lon,lat,time) TREFHT --> surface temperature (3 dimensions: lon,lat,time) NAM --> Northern Annular Mode index based on polar cap mean Geopotential (Z3), calculated using the method described in the paper Appendix EHF100 --> Eddy Heat Flux at 100 hPa, polar cap average (60-90N) **NOTE: only available for the CHEM experiment $START_YEAR-$END_YEAR is the time period covered by the simulation, in years. The dimensions in each field are: lon --> longitude lat --> latitude lev (or p_lev) --> pressure level (in hPa units) time --> days since the first year/day of the simulation