Solar Irradiance Variability
Claus Fröhlich, PMOD/WRC, Davos Dorf, Switzerland
Introduction
•
•
•
TSI Measurements from space
What about degradation
What corrections are needed
Development of a TSI Composite
•
•
Construction of a composite
Time series and Power Spectrum
Development of a TSI Model
•
•
•
Construction of an empirical model
Comparison of the TSI and model time series
Bi-variate spectral analysis
Variability of Spectral Irradiance
•
VIRGO results for periods shorter than about an year
Conclusions
Acknowledgements: Part of the work presented here has been prepared for several
papers together with Judith Lean. Moreover, this work would not have been possible
without the continuous efforts of the VIRGO team. VIRGO is an experiment on the
cooperative ESA/NASA mission SOHO.
29.08.02 09:35:46
SORCE Meeting, Steamboat Springs, July 17-19, 2002
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TSI Measurements from Space
Total solar irradiance (TSI) monitoring from space with electrically
calibrated radiometers started with the launch of NIMBUS-7 in
November 1978
1.
2.
3.
Several time series exist from
different platforms made by different
radiometers: HF on NIMBUS-7,
ACRIM I on SMM, ERBE on ERBS,
ACRIM II on UARS, VIRGO on
SOHO and ACRIM III on ACRIMSat
This allows the construction of a
composite time series having
improved long-term precision, thus
yielding an unbiased estimate of TSI
and its variability during the last
almost three solar cycles
For the discussion of the reliability of
the composite mainly two issues are
important: the correction for the early
measurements of HF on NIMBUS 7
to account for its degradation and the
tracing of ACRIM II to ACRIM I by
comparison with ERBE and HF over
the gap between them
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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What about Degradation
What can be learned from the VIRGO record?
•
•
Level-1 data
Transfer from ground to space
1.
PMO6V shows ‘normal’
degradation as during earlier
missions (ca. 2 ppm/day)
2.
DIARAD is different and shows
much smaller changes than
before. The DIARAD-R seems
to have more noise
3.
PMO6V show an early
increase which seem to be
typical for these type of
radiometers (as HF and
possibly ACRIM-II)
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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What about Degradation
What can be learned from the VIRGO record:
•
•
Accurate assessment of degradation
Determination of non-exposure dependent changes
1.
Correction of exposure
dependent changes by
comparison with less exposed
radiometer of the same type
2.
Comparison of the two type of
radiometer, PMO6-V and
DIARAD
3.
Relative difference is repeated
for after 1014 days more than 2
years
4.
Conclusion: PMO6V does not
show degradation other than
due to exposure, DIARAD does
(mainly during recovery after
switch-off
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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What Corrections are needed?
Corrections of HF
•
•
Early increase and long-term degradation
Glitches in October 1989 and August 1990
1.
Lee et al., 1995, Chapman et al. 1996 found 2
glitches of 0.36 and 0.37
W/m2
2.
Comparison of HF with
ERBE and a model
shows indeed a sudden
change of HF after a 4day switch-off. It is determined as 0.42 W/m2.
3.
The second glitch (at the
vertical dashed line) is
not confirmed, but a gradual change.
4.
With the glitch correccted
and the trend removed
both the yield a horizontal line with a slope of
-0.001 and -0.031 ppm/d
for HF/ERBE and
HF/model respectively
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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What Corrections are needed?
§ How to refer ACRIM-II to the ACRIM-I scale?
•
•
Comparison with ERBE and HF before and after the gap
Obviously, the result depends on the corrections of HF
1.
As the ration HF/ERBE has already
been corrected the ACRIM-I to
ACRIM-II reference does no longer
really depend on whether one does it
against ERBE or HF
2.
There may be still some other
periods in the HF record which needs
corrections, as e.g. in 1987 as seen
in the ACRIM/HF and HF/ERBE
3.
It is interesting to note that ERBE
shows also some early increase
which seems to be finished by 1989
4.
These comparison show that in
general the long-term behavior
seems to be more robust than the
short-term.
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Construction of the Composite
§ The reference in terms of absolute SI units is ACRIMII, referred to SARR (Crommelynck et al., 1995)
1.
The horizontal lines at zero
indicate the use of the time series
as they are (for VIRGO and
ACRIM-I slightly shifted to match
the record before)
2.
HF seems to have an overall
increase in sensitivity. It is
interesting to note the trend
determined by comparison with
ACRIM-I in 82/82 is the same as
the one determined from the
comparison with ERBE during
89/92 as indicated by the dotted
line
3.
Looking at the ERBE data between
89/92 the issue of bridging the gap
between ACRIM-I and ACRIM-II
may still not be finalized
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Discussion of the composite TSI
Time series
1.
The solar cycle amplitude
amounts to about 0.1%
2.
Cycle 21 is the highest (could be
due to the early HF correction –
may have to be revisited)
3.
Long-term trend as indicated by
the difference between the two
minima 21/22 and 22/23 amounts
to 65.8 ppm, with the latter being
lower. This corresponds to 6.29
ppm/a. This value depends
mainly on the HF correction
which is with 27.6 ppm/a quite
uncertain.
4.
How accurate is this trend? From
comparison with ERBE and
ACRIM-II and III when they are
not part of the composite, a
formal uncertainty about 3 ppm/a
is deduced
5.
The observed trend is with a high
probability (about 2-3σ) not
different from zero.
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Discussion of the composite TSI
§ Power Spectrum
The most interesting features
are:
1.
There is a broad peak around an
11-year period with essentially all
the variance
2.
There is a large dip at about 1450
days (about 4 years). Its origin is
unknown.
3.
There is a broad peak around 1
year, probably due to different
activity levels in the N and S
hemispheres
4.
TSI has only little power at the 27day rotational period. A factor of 2
less than above or below.
5.
The spectrum is flat between about
4 years and 15 days. Below 15
days it decreases with about 1/f3.
6.
The basis for the model used here
comes next. Here we note that
simulates quite well the TSI
spectrum
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Development of an empirical model
How do magnetic fields influence the irradiance?
1.
TSI is only marginally
correlated with global
magnetic fields (absolute and
average)
2.
The effect of magnetic fields
on irradiance is through
changes of the temperature
structure of the solar
atmosphere
3.
These changes can be
monitored by e.g. the MgII
index, the core-to-wing
intensity ratio
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Development of an empirical model
The model is based on sunspot darkening and
brightening by faculae and network
1.
The influence of sunspots on the
irradiance, F 0 , is modeled by the
Photometric Sunspot Index PS
2.
For the facular influence a similar index,
PF can be determined. How-ever, it
depends on the availability of images.
Here we model the influence of faculae
and network PF by the MgII index which
corresponds to the core-to-wing
intensity ratio of the Mg line at 280 nm.
Moreover, we separate PF in a longand short-term part. The former
represents the faculae, the latter the
network
3.
These three components, PS , PFs and
PFl are calibrated by multiple linear
regression against TSI.
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Comparison of TSI with the Model
The Camel/Dromedary
approach
1.
In contrast to sunspots faculae exhibit a
CLV which substantially different from the
photospheric one.
2.
The effect of sunspots peaks at the central
meridian passage where they are darkest.
As faculae and network show limb
brightening they influence the irradiance
(different for luminosity) with two peaks
around the central meridian passage
separated by about 8-10 days
3.
As the irradiance, corrected for sunspots,
F0+PS,, shows a double peak this time
series is convoluted with a double-peak
filter (Camel), whereas PFs with a triangular
one (Dromedary).
4.
The Camel filter is optimized for the
highest correlation between the filtered
⟨F0+PS⟩ and ⟨PFs ⟩, time series.
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Comparison of TSI with the Model
Time Series
1.
The correlation seems to be quite good for the
different periods although the correlation is
calculated with all data.
2.
The model for the maximum of cycle 21 is too
low, and about right for the maxima of 22 and 23.
In general the short-term variation seems to be
underestimated. It is most obvious in cycle 23
with less sunspots. It is interesting to note that
factor for PFs is about 2/3 of the one for PFl.
3.
The correlation with 0.916 tells us that 84% of the
variance is explained
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Comparison of TSI with the Model
Difference between Cycles and Long-term Trends
• The three cycles are quite
different, especially the
ascending part of 22 and 23. For
the latter it could be that a first
maximum was already reached
in late 1998.
• The residual shows a downward trend of 8.8 ppm/a which is
close to the 6.3 ppm/a found
from the difference of TSI at the
two minima 21/22 and 22/23.
29.08.02 09:35:46
SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Comparison of TSI with the model
Bi-variate spectral analysis
•The bi-variate spectral analysis
calculates as a function of
frequency a filter which transforms – in our case – the model
into TSI.
• The association is quantified
by the coherence ρ. 100×ρ2
gives the amount explained in
percent.
• High values with ρ2 >0:94 are
reached at periods around 295,
103, 31 and 24 days and low
ones ρ2 < 0:20 at periods
around 198, 80, 69, 28, 19 and
<8 days.
•The average gain and phase
over the range of periods from
13 to 1200 days amount to 1.02
and -1 deg; respectively which
confirms the regression results.
29.08.02 09:35:46
SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Variability of Spectral Irradiance
SPM VIRGO time series
•For detrending the level-1 SPM,
the combination of the
operational (a) and the backup
(b) cannot be used in the same
way as for the radiometers.
•The back-up (panel b) behave in
an rather unexpected way which
is a combination of the solar and
still not identified instrumental
changes.
•A polynomial fit to the ratio of (a)
to (b) for each channel allows to
construct detrended time series
which allow to study solar
variability up to periods of about
one year.
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Variability of Spectral Irradiance
Multi-variate spectral analysis
1.
The total coherence is quite
high. The share between the
three channels is varying with
frequency
2.
At the rotational frequency the
blue and green are less
contributing than the red. This
is even more pronounced at
the 13-day period
3.
The gain indicates that the
ratio of the three colors to the
total is about 1.8, 2.3 and and
4.1 for red/green/blue
respectively
4.
The results for the phase are
difficult to interpret as they are
quite uncertain.
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SORCE Meeting, Steamboat Springs, July 17-19, 2002
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Conclusions
§
§
§
§
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The solar cycle variation has an amplitude of about 0.1%. The
three cycles as observed are still different – with more
measurements we may eventually understand these differences.
A long-term trend is determined by comparison the two minima
between 21/22 and 22/23 with 6.3 ppm/a. It is, however, mainly
determined by how TSI is determined during the gap between
ACRIM-I and II. The trend is not significantly different from zero
and we are still not able to detect a long-term trend.
86% of the TSI variability can be explained by a 3-component
model (sunspots: PS, MgII index: PFs and PFl). A linear fit to the
residual shows a downward trend of 8.8 ppp/a which is obviously
due to TSI and not the model.
SPM/VIRGO time series provide information about the spectral
redistribution during changes of TSI. These results demonstrate
the importance of continuous time series of spectral irradiance
such as SIM will provide with SORCE
SORCE Meeting, Steamboat Springs, July 17-19, 2002
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