ISSI team workshop, Bern, January, 2015 Eugene Rozanov PMOD/WRC, Davos and IAC ETH, Zurich, Switzerland Simulation of the NO y production by auroral electrons and solar protons and their effects on ozone with the CCM SOCOL v3.0

ISSI team workshop, Bern, January, 2015 New SPARC Chemistry- Climate Models inter comparison project (CCMI) started more than a year ago;

ISSI team workshop, Bern, January, 2015 First time ever EP are included in the forcing set of CCMI

ISSI team workshop, Bern, January, 2015 Solar variability. The solar radiative forcing data are provided at gfz- potsdam.de/input_data. php. Daily, spectrally-resolved solar irradiance data from the NRLSSI model (Lean et al., 2005), which have been used in previous CCMVal and CMIP5 experiments, are recommended. In addition, the inclusion of atmospheric ionization by solar protons (and related HOx and NOx production) are strongly encouraged by using the GOES-based ionization rate data set and a methodology to derive HOx and NOx production rates from Jackman et al.(2009). Models capable of considering indirect particle effects by the inclusion of an Ap-parameterized auroral source or upper boundary condition are encouraged to do so.

ISSI team workshop, Bern, January, 2015 AO CCM SOCOL/MPI-OM

ISSI team workshop, Bern, January, 2015 Recommended Ap index for CCMI runs REF–C1,C2 REF–C2ST

ISSI team workshop, Bern, January, 2015 Applied SPE IR (annual mean: 50 km, polar cap)

ISSI team workshop, Bern, January, 2015 Ion and neutral chemsitry: Treatment in the models Below 90 km: Complete ion chemsitry (50+ species) - SOCOL i Computationally expensive Parameterizations of NO x and HO x production Porter et al., 1976; Solomon et al., N *, 0.55 N( 4 S) and 2 HO x per ion pair; widely applied below 90 km (WACCM, HAMMONIA, EMAC, SOCOL...)

ISSI team workshop, Bern, January, 2015

NO x and HO x production Widely used parameterization (0.7 N * N( 4 S) + up to 2 HOx per Ion Pair) against complete ion chemistry CCM SOCOL (Egorova et al., 2011)

ISSI team workshop, Bern, January, 2015 Ion and neutral chemsitry: Treatment in the models Below 90 km: Verronen and Lehman, 2013 LUT, includes HNO 3 production Nieder et al., 2014 (LUT) LUT

ISSI team workshop, Bern, January, 2015 Applied annual mean Ap index

ISSI team workshop, Bern, January, 2015 Ion and neutral chemsitry: Treatment in the models Above 90 km: 5-ion scheme – WACCM, HAMMONIA NO x (ppbv) from MIPAS. HEPPA-2, Courtesy of B. Funke

ISSI team workshop, Bern, January, 2015 Baumgartner et al, 2009 Treatment of the auroral electrons in SOCOL

ISSI team workshop, Bern, January, 2015 Time evolution of VMR CO 70 o S-90 o S Simulated CO (ppbv) MIPAS CO (ppmv), Funke et al., 2014a

ISSI team workshop, Bern, January, 2015 Time evolution of VMR CH 4 70 o S-90 o S Simulated CH 4 (ppbv) MIPAS CH 4 (ppmv), Funke et al., 2014a

ISSI team workshop, Bern, January, 2015 Time evolution of VMR NO y 70 o S-90 o S Simulated NO y (ppbv) MIPAS NO y (ppmv), Funke et al., 2014a

ISSI team workshop, Bern, January, 2015 Time evolution of VMR NO y 70 o S-90 o S Simulated NO y (ppbv) MIPAS NO y (ppmv), Funke et al., 2014a

ISSI team workshop, Bern, January, 2015 Time evolution of VMR NO y 70 o N-90 o N Simulated NO y (ppbv) MIPAS NO y (ppmv), Funke et al., 2014a

ISSI team workshop, Bern, January, 2015 Time evolution of VMR NO y 70 o N-90 o N Simulated NO y (ppbv) MIPAS NO y (ppmv), Funke et al., 2014a

ISSI team workshop, Bern, January, 2015 How to extract EPP-NOy 1.By comparison with the reference model runs Pro: clear approach. Contra: not compatible with observations. 2. Using correlations with other tracer (e.g., CH 4, CO) Pro: comparable to observation. Contra: Not always clear what we are getting. 3. Multiple linear regression analysis Pro: potentially comparable to observation. Contra: Not so easy to introduce time lag.

ISSI team workshop, Bern, January, 2015 Time evolution of VMR NO y 70 o S-90 o S Simulated NO y (ppbv) w/o EPP Simulated NO y (ppbv) with EPP

ISSI team workshop, Bern, January, 2015 NO y (ppbv) produced by EPP (70 o S-90 o S, mean)

ISSI team workshop, Bern, January, 2015 NO y produced by EPP relative to background (70 o S-90 o S, mean)

ISSI team workshop, Bern, January, 2015 NO y produced by EPP relative to background (70 o S-90 o S, mean) EPP contribution to NO y column km (Funke et al., 2014a)

ISSI team workshop, Bern, January, 2015 How to extract EPP-NOy 1.By comparison with the reference model runs Pro: clear approach. Contra: not compatible with observations. 2. Using correlations with other tracer (e.g., CH 4, CO) Pro: comparable to observation. Contra: Not always clear what we are getting. 3. Multiple linear regression analysis Pro: potentially comparable to observation. Contra: Not so easy to introduce time lag.

ISSI team workshop, Bern, January, 2015 EPP-NOx from NOx-CH 4 correlations From Randall et al., 2007)

ISSI team workshop, Bern, January, 2015 EPP-NOx from NOx-CH 4 correlations From Randall et al., 2007)

ISSI team workshop, Bern, January, 2015 Conclusions SPE and auroral electrons influence on the atmosphere were simulated with CCM SOCOL in the framework of CCMI project using SPR induced ionization and parameterized NO x influx; The influence of EPP on NO y is visible in the model output The response of NO y is in qualitative agreement with satellite data The influence of both SPE and auroral electrons is visible The work on the evaluation of quantitative agreement between model and satellite data is in progress