TOSCA WG1 Workshop 14-16 May 2012, Berlin
Multi-model intercomparison of the impact of
SORCE measurements in climate models
K. Matthes(1), F. Hansen(1), J.D. Haigh(2), 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;
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
(3)
Outline
• Introduction & Motivation
• Model Descriptions & Experimental Design
• Preliminary results from the multi-model comparison
• Summary
• Outlook
Introduction – 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.“
• „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.“
Motivation – 2 Questions
1. Do the SIM measurements provide real solar
behavior or are they related to instrument
drifts?
1. What are the effects of larger UV variability on
the atmospheric response?
„Top-Down Mechanism“
Gray et al. (2010)
„Top-Down“: Dynamical Interactions
and Transfer to the Troposphere
10-day mean wave-mean flow interactions (Max-Min)
u
EPF
Stratospheric waves
(direct solar effect)
Matthes et al. (2006)
Tropospheric waves
(response to stratospheric changes)
Modeled Signal near Earth Surface
Monthly mean Differences geop. Height (Max-Min) – 1000hPa
ΔT
+
+
-
+
+
+2K
Matthes et al. (2006)
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
Uncertainty in Solar Irradiance Data
Solar Max-Min
NRLSSI vs. SATIRE
Lean et al. (2005)
NRLSSI vs. SIM/SORCE
Krivova et al. (2006)
• larger variation in Krivova data in 200-300 and 300-400nm 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
Model Description &
Experimental Design
Participating Models
SOCOL, T42, L39, 0.01 hPa, nudged QBO, see talk by Eugene Rozanov this afternoon
Caveat: all 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 SC23
„solar max“ 2004
2004:
“solar max”
„solar min“ 2007
(declining phase
of SC23)
2007:
“solar min”
(close to minimum
of SC23)
January Mean Differences
(25N-25S)
Shortwave Heating Rate (K/d)
Temperature (K)
NRL SSI
SORCE
• 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)
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
Definition Ensemble Mean
• Large Multi Model Mean: all 5 models
(FUB-EMAC, GEOS, HadGEM, IC2D, WACCM)
• Small Multi Model Mean: 3 models
(GEOS, HadGEM, WACCM)
Shortwave Heating Rate Differences
January (K/d)
Small multi-model mean
(EMAC-FUB, GEOS, HadGEM, IC2D, WACCM)
(GEOS, HadGEM, WACCM)
SORCE
NRL SSI
Large multi-model mean
• NRL SSI shortwave heating rates: 0.2 K/d
• SORCE shortwave heating rates: 0.9 K/d (4x NRL SSI response)
Temperature Differences
January (K)
Small multi-model mean
(EMAC-FUB, GEOS, HadGEM, IC2D, WACCM)
(GEOS, HadGEM, WACCM)
SORCE
NRL SSI
Large multi-model mean
• NRL SSI temperatures: 0.3 to 0.6 K (stratopause)
• SORCE temperatures: 1.5 to 1.8 K (5x NRL SSI response) colder polar stratosphere
Ozone Differences
January (%)
Large multi-model mean
SORCE
NRL SSI
(GEOS, IC2D, WACCM)
• 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
Zonal Wind Differences
January (m/s)
Small multi-model mean
(EMAC-FUB, GEOS, HadGEM, IC2D, WACCM)
(GEOS, HadGEM, WACCM)
SORCE
NRL SSI
Large multi-model mean
• 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
SORCE Differences
NH Winter – small ensemble mean
Zonal mean zonal wind (m/s)
December
January
February
• downward extension of westerly zonal wind signals to the troposphere
SORCE Geopot. Height Differences
January (gpdm)
10 hPa
100 hPa
NAO/AO positive signal during solar max
500 hPa
Solar Cycle & 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 Cycle & NAO
Solar Max: NAO positive
(high index)
Solar Min: NAO negative
(low index)
Matthes (2011)
Summary
 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
Outlook
• Paper on multi-model comparison to be submitted before 31st July
• coordinated sensitivity experiments within the SPARC-SOLARIS Initiative
for a typical solar max (2002) and solar min (2008) spectrum from the
NRL SSI, SATIRE and the SORCE (and possibly other data or
reconstructions? SCIA, COSI?) data to investigate the atmospheric and
surface climate response between the models in a more consistent way
 SOLARIS/HEPPA workshop 9-12 October 2012 in Boulder
http://www2.acd.ucar.edu/heppasolaris
Thank you very much!
Estes Park/RMNP, 10-15-2011