Multi-model intercomparison of the impact of SORCE measurements in climate models TOSCA WG1 Workshop May 2012, Berlin K. Matthes (1), J.D. Haigh (2), F. Hansen (1), J.W. Harder (3), S. Ineson (4), K. Kodera (5,6), U. Langematz (7), D.R. Marsh (8), A.W. Merkel (3), P.A. Newman (9), S. Oberländer (7), A.A. Scaife (4), R.S. Stolarski (9,10), W.H. Swartz (11) (1) Helmholtz-Zentrum für Ozeanforschung Kiel (GEOMAR), Kiel, Germany; (2) Imperial College, London, UK; (3) LASP, CU, Boulder, USA; (4) Met Office Hadley Centre, Exeter, UK; (5) Meteorological Research Institute, Tsukuba, Japan; (6) STEL University of Nagoya, Nagoya, Japan; (7) Freie Universität Berlin, Institute für Meteorologie, Berlin, Germany; (8) NCAR, Boulder USA; (9) NASA GSFC, Greenbelt, USA; (10) John Hopkins University, Baltimore, USA; (11) JHU Applied Physics Laboratory, Laurel, USA

Outline Motivation Model Descriptions and Experimental Design Preliminary results from the multi-model comparison Summary Outlook

SORCE/SIM measurements from 2004 to 2007: increased solar spectral irradiance at UV and IR wavelengths even as solar and TSI decreased => SIM spectral data into climate models => „the effects of solar variability on temperature throughout the atmosphere may be contrary to current expectations“ (Haigh et al., 2010) => higher solar activity cools Earth But: SIM trends relative to TSI and solar activity during solar min => unlikely to be solar in origin „It is doubtful that simulations of climate and atmospheric change using SIM measurements are indicative of real behavior in the Earth‘s climate and atmosphere.“ (Lean and DeLand, 2012) „SIM‘s solar spectral irradiance measurements from April 2004 to December 2008 and inferences of their climatic implications are incompatible with the historical solar UV irradiance database […] but are consistent with known effects of instrument sensitivity drifts.“ (Lean and DeLand, 2012) „To prevent future research following a path of unrealistic solar-terrestrial behavior, the SORCE SIM observations should be used with extreme caution in studies of climate and atmospheric change until additional validation and uncertainty estimates are available.“(Lean and DeLand, 2012) Motivation

2 questions: 1.Do the SIM measurements provide true solar behavior or are these related to instrument drifts? 2.What is the effect of larger UV variability on the Earth‘s atmosphere? (focus of this study) Motivation

„Top-down mechanism“

„Top-down“: Dynamical Interactions and Transfer to the Troposphere 10-day mean wave-mean flow interactions (Max-Min) u Stratospheric waves (direct solar effect) Tropospheric waves (response to stratospheric changes) EPF Matthes et al. (2006)

Modeled Signal near Earth Surface Monthly mean Differences geop. Height (Max-Min) – 1000hPa Significant tropospheric effects (AO-like pattern) result from changes in wave forcing in the stratosphere and troposphere which changes the meridional circulation and surface pressure Matthes et al. (2006) +2K ΔT

Uncertainty in Solar Irradiance Data Solar Max-Min Lean vs. Krivova Lean et al. (2005)Krivova et al. (2006) larger variation in Krivova data in and nm range SORCE measurements from 2004 through 2007 show very different spectral distribution (in-phase with solar cycle in UV, out-of-phase in VIS and NIR) => Implications for solar heating and ozone chemistry

Participating Models 1. Compare Existing Model Runs Caveat: all the models used a slightly different experimental setup, so it won’t be possible to do an exact comparison

Differences in Experimental Setup

Experimental Design Time series of F10.7cm solar flux „solar max“ 2004 „solar min“ : “solar max” (declining phase of SC23) 2007: “solar min” (close to minimum of SC23)

January Mean Differences (25N-25S) NRL SSI SORCE Shortwave Heating Rate (K/d)Temperature (K) larger shortwave heating rate and temperature differences for SORCE than NRL SSI data FUB-EMAC and HadGEM only include radiation, not ozone effects

January Mean Differences (25N-25S) Ozone (%)Temperature (K) larger ozone variations below 10hPa and smaller variations above for SORCE than NRL SSI data height for negative ozone signal in upper strat. differs between models

Shortwave Heating Rate Differences January (K/d) EMAC-FUBGEOS IC2DHadGEMWACCM NRL SSI SORCE NRL SSI shortwave heating rates: 0.2 to 0.3 K/d SORCE shortwave heating rates: 0.7 to >1.0 K/d (3x NRL SSI response)

Shortwave Heating Rate Differences January (K/d) Large multi-model mean (EMAC-FUB, GEOS, HadGEM, IC2D, WACCM) Small multi-model mean (GEOS, HadGEM, WACCM) NRL SSI SORCE

Temperature Differences January (K) EMAC-FUBGEOS IC2DHadGEMWACCM NRL SSI SORCE NRL SSI temperatures: 0.5 to 1.0 K (stratopause) SORCE temperatures: 2.5 to 4.0 K (4-5x NRL SSI response) colder polar stratosphere

Temperature Differences January (K) Large multi-model mean (EMAC-FUB, GEOS, HadGEM, IC2D, WACCM) Small multi-model mean (GEOS, HadGEM, WACCM) SORCE NRL SSI

Ozone Differences January (%) EMAC-FUBGEOS IC2DHadGEMWACCM NRL SSI SORCE larger ozone variations below 10hPa and smaller variations above for SORCE than NRL SSI data height for negative ozone signal in upper strat. differs between models

Ozone Differences January (%) Large multi-model mean (EMAC-FUB, GEOS, HadGEM, IC2D, WACCM) Small multi-model mean (GEOS, HadGEM, WACCM) SORCE NRL SSI

Zonal Wind Differences January (m/s) EMAC-FUBGEOS IC2DHadGEMWACCM NRL SSI SORCE consistently stronger zonal wind signals for SORCE than NRL SSI data wind signal in SORCE data characterized by strong westerly winds at polar latitudes, and significant and similar signals in NH troposphere

Zonal Wind Differences January (m/s) Large multi-model mean (EMAC-FUB, GEOS, HadGEM, IC2D, WACCM) Small multi-model mean (GEOS, HadGEM, WACCM) SORCE NRL SSI

SORCE Wind Differences NH Winter EMAC-FUBGEOS IC2DHadGEMWACCM Dec Jan Feb

SORCE Wind Differences NH Winter Large multi-model mean (EMAC-FUB, GEOS, HadGEM, IC2D, WACCM) Small multi-model mean (GEOS, HadGEM, WACCM) Dec Jan Feb

SORCE Geopot. Height Differences January (gpdm) EMAC-FUBGEOS HadGEMWACCM 500 hPa 100 hPa 10 hPa NAO/AO positive signal during solar max strongest for HadGEM and WACCM

SORCE Geopot. Height Differences January (gpdm) Large multi-model mean (EMAC-FUB, GEOS, HadGEM, WACCM) Small multi-model mean (GEOS, HadGEM, WACCM) 500 hPa 100 hPa 10 hPa

Solar Cycle and the NAO Solar Max: NAO positive (high index) Colder stratosphere => stronger NAO, i.e. stronger Iceland low, higher pressure over Azores  amplified storm track  mild conditions over northern Europe and eastern US => dry conditions in the mediterranean

Solar Min Surface Pressure Signal Ineson et al. (2011) Model (HadGEM) Observations (Reanalyses) 90 (95%) significances 25 (50%) of interannual standard deviation

Solar Cycle and the NAO Solar Max: NAO positive (high index) Solar Min: NAO negative (low index) Matthes (2011)

 Consistently larger amplitudes in 2004 to 2007 in solar signals for SORCE than for NRL SSI data in temperature, ozone, shortwave heating rates, zonal winds and geopotential heights  Larger ozone variations below 10hPa and smaller variations above for SORCE than NRL SSI data; height for negative ozone signal in upper stratosphere differs between models  Solar cycle effect on AO/NAO contributes to substantial fraction of typical year-to-year variations and therefore is a potentially useful source of improved decadal climate predictability (Ineson et al. (2011))  Results for the SORCE spectral irradiance data are provisional because of the need for continued degradation correction validation and because of the short length of the SORCE time series which does not cover a full solar cycle Summary

Next step: coordinated sensitivity experiments for a typical solar max (2002) and solar min (2008) spectrum from the NRL SSI and the SORCE data to investigate the atmospheric and surface climate response between the models in a more consistent way => White paper until early December, experiments to be started early 2012 in order to be ready for the SOLARIS/HEPPA workshop 8-12 October 2012 here in Boulder! Outlook

Thank you very much! Estes Park/RMNP,