A&A 419, 345-356 (2004)
M. Kretzschmar 1, - J. Lilensten 1 - J. Aboudarham 2
1 - Laboratoire de Planétologie de Grenoble, Bât. D de Physique, BP 53, 38041 Saint-Martin-d'Hères Cedex, France
2 - LESIA, Observatoire de Paris, 92190 Meudon, France
Received 28 April 2003 / Accepted 27 January 2004
This paper aims to build a quiet Sun EUV reference spectrum from the SOHO - SUMER database. We make use of 750 quiet Sun spectra spread over a large range of solar activity. They are carefully calibrated both in terms of frequency and intensity. The data do not show any noticeable variations versus the solar activity. This allows us to build a quiet Sun reference spectrum from data scattered over any solar activity level. We consider separately the continuum, the thick-line spectra, and the thin-line spectra. The former is computed from an average of the H Lyman and C I continua. The thick lines are directly assembled from the SUMER files. To retrieve a broad set of thin lines, we use the SUMER measurements to compute a mean Differential Emission Measure, which is then inverted. This results in a reference spectrum for the Quiet Sun, which is compared to previous studies.
Key words: Sun: UV radiation
Because the solar EUV flux is absorbed by the upper terrestrial atmosphere, it can only be observed from space. This reinforces the need for models. Most of the current models rely on a few experiments taken onboard the Atmosphere Explorer (AE) missions (i.e. Hinteregger et al. 1981). A first reference flux SC#21REF was assembled from measurements performed in July 1976 ( f10.7 = 70) (Hinteregger 1976). An extrapolation model - SERF1 (Hinteregger 1981) - allows estimation of the flux during other periods of solar activity. Torr et al. (1979) and Torr & Torr (1985) proposed two EUV reference fluxes for aeronomy called F79050N ( f10.7 = 243) and SC#REFW ( f10.7= 68). The EUV spectrum was split in 37 bins including wavelength intervals as well as spectral lines. The authors suggested deducing fluxes at other activity levels with an exponential interpolation between the two reference fluxes. This work showed itself to be extremely useful. One of its qualities was that the authors proposed the corresponding absorption and ionization cross sections for the major thermospheric species. Tobiska (1991) and Tobiska & Eparvier (1998) developed a model called EUV97, which takes data from other sources into account: SME, OSO; AEROS; rockets and ground-based facilities. This model takes into account the solar emission zone (i.e. chromosphere, transition region or corona) of numerous lines. It proposes a formula to retrieve the solar flux given the decimetric index and its average. A new version, SOLAR2000, has recently been developed. It uses a new input parameter named E10.7, computed from a previous version of the code (Tobiska et al. 2000). The second improved model is EUVAC (Richards et al. 1994). Its main difference from previous models is the reference flux chosen, and the interpolation formula. The coronal flux is also constrained to be at most 80% of the total.
Finally, Warren et al. (1996) have proposed a different approach to model the solar EUV flux by combining a spectral emission line database, solar emission-measure distributions, and estimates from ground-based solar images of the fraction of the Sun covered by the various types of activity to synthesize the irradiance. The goal was to determine a way to estimate the irradiance from EUV line emission formed in the upper chromosphere and lower transition region from the Ca II K-line through the model. It requires building spectra for typical solar areas, such as quiet area, coronal hole, and active region. Based on this approach, the emission measure was derived from the spectrum of a portion of the quiet solar disk measured with the Harvard instrument onboard Skylab, and compilations of atomic data (Warren et al. 1998a,b). Hereafter we refer to this work as the NRLEUV quiet Sun spectrum.
This last method looks to be very promising. It raises new questions, among which is the representativeness of the spectra for the different solar areas. The present work contributes to the effort for improving the modelling of the solar EUV flux. More specifically, it aims at defining a quiet Sun EUV reference spectrum, in the context of the solar EUV flux modelling using the differential emission measure (DEM) method for the thin lines. For this purpose, we use the recent solar data from the well calibrated spectrometer SUMER onboard SOHO. Section 2 presents the instrument and the reduction procedure. In Sect. 3, we discuss the results of this reduction procedure and the variability of the observed spectral line intensities. In Sect. 4, we use these intensities to compute a synthetic spectrum through the determination of a differential emission measure. Optically thick lines and continuum are taken into account to derive the reference spectrum. Section 5 compares our results with previous work and discusses the implications for the modelling of the solar EUV flux.
For our purpose, the use of the SUMER instrument has various advantages: (i) the calibration has been checked several times through the observation of well-known stable stars, computation of line intensity ratios, and comparison with the SOLSTICE instrument (Wilhelm et al. 1999). This led to an uncertainty of 15% and 33% for detector A before and after SOHO recovery respectively, and 20% and 36% for detector B (Wilhelm et al. 2000); (ii) SUMER data are available during the whole ascending phase of Solar cycle 23; (iii) all the SUMER data used are in the public domain and were retrieved from the MEDOC SOHO database (http://www.medoc-ias.u-psud.fr).
For the present study, we selected about 750 SUMER files from 1996 to
ranging from 750 to 1100 Å. Figure 1 shows their spectral
coverage versus time. The
choice of the upper wavelength
motivated by ionospheric study requirements. The lower limit
to the compromise between the lower wavelength for first order
observations with SUMER (660 Å with detector B)
and limitations due to the amount and availability of data.
We selected uniformly spread data over time in order to get an
homogeneous set of observations during the selected period. Since
SUMER reduced its observations on the solar disk with the increasing
solar activity and lifetime of the mission, we have taken a smaller
number of observation files during the first year of the SOHO
mission, with regard to what was available. This provides an
equilibrium between the amount of observations at different times of
the solar cycle. Their variability and therefore the variability of
what is called the quiet Sun area (sometimes also shortened to "quiet Sun'') is discussed in Sect. 3 and the
standard deviations are shown in Tables 1
|Figure 1: Spectral coverage versus date of quiet Sun observation contained in the selected files.|
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Finally, we used EIT images (Delaboudinière et al. 1995) to identify the emission region of each file. SOHO/EIT works at 4 wavelengths (Fe IX-X at 171 Å, Fe XII at 195 Å, Fe XV at 284 Å and He II at 304 Å) corresponding to various temperatures (respectively K, K, K and K). Thus the whole-Sun images from EIT provide the context of the observations. We classified the emission region of each SUMER spectrum into four areas: quiet Sun area, coronal hole, active region, and other. This last area contains emission regions which where identified as a mix of two or more of the three previous areas, as well as emission regions containing particular features (i.e. filament, or case where a part of the SUMER slit was above the limb). All 4 types of emission region were identified by looking directly at the nearest EIT images (see Fig. 4 for an example); with the possibility to classify a region in the "other'' category when the identification is unsure, this method is suitable to distinguish between the 3 traditional categories of emission region. Since the SUMER spectrometer has very sensitive detectors, only a few observations of active regions are available. Moreover, there are very few hot coronal lines in the spectral range used; these lines are very useful to characterize coronal holes, since their intensities are lower in coronal holes than in quiet areas. For these reasons, we only deal here with quiet Sun observations, which leaves us with about 400 SUMER files.
Table 1: The first two columns are explicit. The third column shows the number of SUMER data files used to compute the average intensity. The fourth column shows (in percent) the statistical standard deviation of the averaged intensity, while the fifth column shows the averaged intensity. The sixth column shows intensity values from NRLEUV. The seventh column gives, when available, values from: 1 Wilhelm et al. (1998), observed near disk center. 2 Wilhelm et al. (1998), mean intensity deduced from full Sun observation. All intensities are in mW m-2 sr-1.
Once these corrections has been applied, we used the RADIOMETRY.PRO routine (with keyword "epoch 9'' in most cases, see Wilhelm et al. 2000) with appropriate keywords, to convert count rates into physical units. We then have at our disposal the correct intensity for detector images contained in the files.
We end up with a very large amount of data. It is therefore necessary to develop an automatic reduction procedure.
Table 2: Calculated and observed mean intensities for optically thin lines used in the DEM computation. The first three columns are explicit. The fourth column shows the number of SUMER data files used to compute the mean intensity. The fifth column shows (in percent) the statistical standard deviation of the mean intensity. The sixth and seventh columns show the mean (or "observed'') and calculated intensity. The eighth column shows their ratio.
The SUMER data contained in each file is a 3-dimensional array representing spectral and spatial (along the North-South slit) dimensions, and successive exposures. First, we average each image of the SUMER detector in time and space according to the following procedure: for each file, we add the different exposures of the detector and divide the result by the number of exposures. When the solar emission is recorded from the same zone of the Sun during the entire file, this method is equivalent to averaging the data in time. When the pointing of the SUMER instrument changes between each image (When SUMER is in RASTER mode, the east-west pointing changes by a few arcseconds between each exposure), this averages the data both in time and space. Finally, we also average the intensity spectra over the whole observed zone, either 120 or depending on the slit used by SUMER for the observation. We are then left with one unidimensional array of spectral intensity. In this way, we trade in space and time resolution for noise reduction and homogenization; this is not restrictive since we are mainly interrested in building an averaged quiet Sun intensity and studying its variation over different solar activities (i.e. over a time scale of the order of the solar cycle). However, the relevance of this averaging process and the representativeness of the averaged intensities will be discussed in Sect. 3, by looking at the intensity distribution.
To identify and fit the spectral lines, we first developed the following procedure to achieve the wavelength calibration of each file:
The next step was to retrieve the line intensities. This was done with an automatic fitting procedure for the optically thin lines, as described below:
Direct integration is performed for optically thick lines. This case is discussed further in Sect. 3.2.
|Figure 2: Intensity histogram for ( top) N IV line at 765 Å and ( bottom) H I line at 918 Å. The total number indicates the number of intensities in the bands. The full line indicates the best fit with a lognormal distribution.|
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For some lines, the number of SUMER data files is not big enough to recognize the usual intensity distribution. However, we have kept these lines when they were useful for the DEM computation - see Sect. 4.3 and Table 2 - or when we found no published value - see Table 1 and file numbers less than about 8 files. In the following, we work with the intensities averaged over the total observed zone in each SUMER file (also referred to one observation), either 120 or depending on the slit used by SUMER for the observations. This allows us to study the variability of the quiet sun intensity versus the ascending phase of the solar cycle. Note that averaging these intensities is equivalent to averaging all the intensities computed in the bins.
|Figure 3: Quiet area intensities for N IV (765.15 Å). Squares: quiet solar activity ( ). Triangles: medium activity ( ). Crosses: high activity ( f10.7 > 150). The line shows the theoretical center-to-limb variation, while small symbols show the intensities transposed to the center of the solar disk.|
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This figure shows two important features: firstly, the data do not make it possible to distinguish between intensity variations due to center to limb variation and quiet Sun intensity variations due to solar activity. Next, the data show a non-negligible variation for intensities emitted in a quiet area, even at similar solar conditions and for the area close to the disk center. This variation, which can be large, is due both to intrinsic variations in and between quiet regions and to differences in the observation properties; for example, two spectra recorded from a short exposure in a small area may have very different amplitudes depending on the proportion of enhanced network present in the region or on the existence of a short-time explosive event such as blinkers; on the other hand, a spectrum recorded with a long exposure in a big solar area should be an average of all the components of the quiet Sun. The intrinsic temporal variability of the EUV quiet Sun emission has been notably studied by Brkovic et al. (2002) from SUMER and CDS measurements. They found a relative intensity variation of the order of 20% for several chromospheric lines. The brightness change remains the same for time scales less and longer than 5 min. For lines emitted in the transition region, the relative variation of the intensity is of the order of 40%, with a greater brightness change for time scales longer than 5 min and less than 80 min. They also noted that the SUMER data have a larger variation than those from CDS. This could be explained by their different spatial resolutions.
These 3 parameters (intrinsic variation between quiet areas, center to limb variation, and variation of quiet area emission with solar activity) are very important for the reconstruction of the whole Sun emission from measurements made in small portions of the solar disk.
|Figure 4: Slit position for the SUMER observations on 1997 January 23, using an EIT image at 171 Å (north is up). No significant changes of the appearance of the solar disk appearance were observed for the different files at this date. Note that the south edge of the Sun is at the bottom of the figure. The dark areas correspond to coronal holes.|
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To study the variability of the quiet Sun intensity vs. solar activity, we split the data into 3 classes, depending on the global solar activity. We chose to use the f10.7 index as the indicator of this activity because we aim to investigate the variation of the intensities emitted by quiet area of the Sun versus the solar cycle; the underlying question is "Do the quiet Sun areas take part in the increase of the solar flux with the solar cycle?". As classically made in many aeronomical studies, we have chosen 3 activity classes: quiet ( f10.7 < 100), mean ( ), active ( ). The results are shown in Fig. 3. For example, the data obtained for a heliocentric angle of about at low activity came from measurements made on January 23, 1997, between 19h41m11s and 23h31m11s. For the six squares, the pointing was the same; the slit position on the solar disk is shown in Fig. 4, and the emitting region is clearly a "quiet" region. Looking at several EIT images covering the whole observation time of the 6 files, we could not see any significant changes in this region. The measured intensity for the N IV 765.15 Å line increases from 60.1 mW m-2 sr-1 at 19h41 to 108.1 at 22h14 and then decreases to 79.3 at 23h31. We carefully investigated these measurements for errors occurring in the calculation of the intensity (data corrections, error during the identification or the fitting procedure) or in the identification of the emitting region. Looking at the variation of the emission along the slit, it appears that the strong intensity for the data taken at 22h14 comes from a strong emission enhancement of a small zone of about . An explosive event, or more generally the "quiet Sun activity'', could be responsible for this strong increase.
The standard deviation for the intensities shown in Fig. 3 (not corrected from the center-to-limb variation) is 28%, while the mean relative deviation is about 20%. These variations confirm the importance of averaging intensities to retrieve typical values. Moreover, the small explosive events surrounded by a large quiet area, such as the one discussed above, could not be detected as an "active region component'' from ground-based solar measurements to determine the area proportion of the solar disk occupied by the different activity features (i.e. quiet Sun, active region, and coronal hole). Therefore, we include them in our set of "quiet Sun'' intensities.
As noted above, intensity variations due to center-to-limb effect and solar cycle can be difficult to distinguish in our dataset, since unfortunately most of our measurements of quiet area intensities at high solar activity are far from the disk center (i.e. ).
It remains unclear whether quiet areas of the solar disk are involved in the whole Sun EUV intensity increase during a solar cycle. Because there was no continuous EUV measurement during the ascending phase of the solar cycle until SOHO, we may refer to studies of the chromospheric network variability. White & Livingston (1981) have studied Ca II H and K profiles from minimum to maximum of solar cycle 21 and did not observe any change in a quiet region at disk center, suggesting no long term variation for the quiet network. This result was confirmed by Labonte & Howard (1982) using full-disk Mount Wilson daily magnetograms. On the other hand, Kariyappa & Sivaraman (1994) found that the network area was anti-correlated with the solar cycle, from Ca II spectroheliograms covering the period 1957-1983. Finally, Pauluhn & Solanki (2002) have studied quiet Sun EUV intensity changes from 1996 to 2000 with SUMER and CDS data. They found a possible increase of quiet Sun He I 584 Å intensity with the solar cycle, but this result is subject to a large measurement uncertainty. The amount of the increase is estimated to be with CDS and with the SUMER measurements. Note that when we apply a center to limb correction to intensity values, it appears in most cases that high intensities recorded at high activity have similar values as intensities measured near the disk center. This case is illustrated by the two measurements in Fig. 3 at . However, since it is unclear if we must keep high intensities recorded at large to compute significant averaged quiet Sun intensities, we only keep those at ; this limits the theoretical variation due to the center to limb effect to about . Since this is of the same order as the dispersion of intensities (Fig. 3), we do not apply the correction.
We may now look at the intensities recorded at low and high solar activity, at similar . The example given in Fig. 3 is characteristic of other lines, and it was not possible to detect any increase of the quiet Sun intensity with solar activity. If this increase is present, as suggested by Pauluhn & Solanki (2002), it is hidden by the uncertainty and the dispersion of the data.
Intensities averaged over the whole data set are shown in Table 2 with their standard deviations, for all optically thin lines. One may check that the case of the N IV 765.15 Å line is typical.
In Fig. 5, all the intensity values for the H I 918.13 Å line are plotted versus the heliocentric angle at the center of their emission zone. As in Fig. 3, we cannot see any tendency of the quiet Sun intensity to vary as a function of solar activity or heliocentric angle. This is representative of the other optically thick lines in our data set.
As in the case of the optically thin lines, we must take into account the center to limb variation to compute the average intensity. Wilhelm et al. (1998) found little or no limb brightening for lines emitted by Si I, He I, and H I ions, compared to the case of optically thin lines. Warren et al. (1998c) found a brightening of approximately 20% near the limb for the H Lyman lines; this increase is of the order of the intensity variation on the solar disc. No brightening was found by Warren et al. for the C II 1036 Å line and the Lyman continuum. SUMER data used in our study are consistent with these results (as shown in Fig. 5 in the case of H I 918 Å). Therefore, we assume that there is no significant center to limb
variation for optically thick lines and continua (including the C I continuum), and we
the mean intensity from all the
|Figure 5: Quiet area intensities for H I (918.13 Å). Squares: quiet solar activity ( ). Triangles: medium activity ( ). Crosses: high activity ( f10.7 > 150).|
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|Figure 6: Fit of the continuum background. The full line is the mean SUMER spectrum at 1 Å resolution. The dotted line represents the fitted continuum. In the region between 793 and 892 Å, there is a lack of data corresponding to our selection criteria.|
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The fitted continua are slightly different from those obtained in the NRLEUV case from SKYLAB data. Both our peak and slope of the hydrogen Lyman continuum are lower. The values of the peak of the C I continuum are similar both in the NRLEUV spectrum and in this work, while we find a lower slope.
The intensities of each optically thin line may be deduced from a
small number of
line measurements through the computation of a Differential Emission
Measure (DEM). This
well-known process has been described in detail by various authors
(see for example
Pottasch 1963; Landi & Landini 1997; Warren
et al. 1998a). Typically, the intensity
of an optically thin line may be written as
Table 3: Numerical values for the quiet sun DEM. DEM is in cm-5 K-1.
There is a close agreement with the NRLEUV DEM, although they are computed from different data sets. The data used in the NRLEUV case consist of an averaged composite spectrum assembled from measurements made near solar minimum (between May 1974 and January 1975), while the intensities used in this work were averaged from a very large range of solar activity. The similarity of the results indicates that the DEMs and inferred thin lines are representative of an averaged quiet area on the solar disk. The computed intensities are shown in Table 2. There is a general good agreement between computed and observed intensities; but there are discrepancies for some lines. The discrepancies in the C II and S III lines may be explained by the possibility that these lines are not effectively thin, since they are formed at a low temperature. Disagreements for the line of the O VI ion were already noted (Judge et al. 1995). Note that the presence of these lines in the computation of the DEM does not change the shape of the DEM. Generally, the agreement is within the range found in previous studies by various authors.
|Figure 7: Mean quiet Sun differential emission measure from SUMER.|
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|Figure 8: Comparison of the synthetic reference spectrum with the SUMER data. Left panels show the spectrum in three different wavelength ranges; right panels show the ratio of the synthetic spectrum (labeled "this work'') to the composite SUMER spectrum.|
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Table 4: Intensity (in mW m-2 sr-1) for strong optically thin lines.
|Figure 9: Comparison of NRLEUV reference spectrum with this work. Left and right panels are defined as in Fig. 8.|
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|Figure 10: Comparison of NRLEUV reference spectrum with the composite SUMER spectrum. Left and right panels are defined as in Fig. 8.|
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We thank P. Lantos (LESIA) for his active and strong support, and W. Kofman (LPG) for helpful discussions. We thank the MEDOC staff and the CHIANTI researchers for their help, and the staff of SUMER and EIT for providing access to their data. This work has been supported by the PNST-CNRS research program and LESIA at Paris Observatory. The computations have been performed at the Service de Calcul Intensif of the Grenoble Observatory.