Quantitative knowledge of water vapor absorption is crucial for accurate
climate simulations. An open science question in this context concerns the
strength of the water vapor continuum in the near infrared (NIR) at
atmospheric temperatures, which is still to be quantified by measurements.
This issue can be addressed with radiative closure experiments using solar
absorption spectra. However, the spectra used for water vapor continuum
quantification have to be radiometrically calibrated. We present for the
first time a method that yields sufficient calibration accuracy for NIR water
vapor continuum quantification in an atmospheric closure experiment. Our
method combines the Langley method with spectral radiance measurements of a
high-temperature blackbody calibration source (
Solar absorption spectra in the near-infrared (NIR, 4000–14 000 cm
In the far- and mid-infrared spectral range (FIR and MIR), a successful way to quantify the water vapor continuum at atmospheric temperatures
has been demonstrated via so-called radiative closure experiments combining
spectrally resolved atmospheric thermal emission measurements with
coincident measurements of the atmospheric state (e.g., Tobin et al., 1999;
Serio et al., 2008; Delamere et al., 2010). In the NIR, however, closure
studies of this kind have not yet been performed because the atmospheric
thermal emission is too weak in this spectral domain. A potential solution
to this problem in the NIR is the use of solar absorption spectra. We
therefore aim to perform a radiative closure experiment using solar
absorption spectra at the Zugspitze (47.42
In the far- and mid-infrared spectral range, a calibration method for high-resolution spectral radiance measurements based on the observation of two blackbody sources at different temperatures is well established (Revercomb et al., 1988). However, there is currently no standard calibration scheme available for the NIR spectral range. Possible methods include the use of standard lamps (see, e.g., Schmid and Wehrli, 1995). Alternatively, Gardiner et al. (2012) implemented a calibration method based on spectral radiance measurements of a very high-temperature (3000 K) blackbody source. This method is traceable to a primary standard cryogenic radiometer, and a calibration transfer for field measurements was implemented via a portable calibration source (National Physical Laboratory (NPL) Transfer Standard Absolute Radiance Source, TSARS). This transfer of calibration for field measurements is of crucial importance because radiative closure experiments are typically carried out at remote (mountain or polar) observatories because of the low atmospheric humidity required. However, the installation of a very high-temperature calibration source is highly challenging at such sites for several reasons: many remote observatories, including the Zugspitze site, lack sufficient laboratory space with stable ambient conditions (especially temperature) for the installation of a very high-temperature blackbody. Accessibility of the site with heavy instruments may be a further restriction, as is the case for the Zugspitze observatory, where access is only possible by cable car. The calibration method proposed in this study offers an alternative approach to this issue and does not require access to a very high-temperature calibration source.
Furthermore, given the calibration accuracy of 3.3 to 5.9 % attainable
with the approach proposed by Gardiner et al. (2012), significant continuum
absorption could only be measured in a small fraction of the 2500 to
7800 cm
It is therefore the goal of this paper to demonstrate an alternative
calibration scheme which overcomes these shortcomings and meets the
calibration uncertainty of
Instrumental specifications and settings chosen for the solar FTIR spectra acquisition.
Our paper is organized as follows. In Sect. 2, the instrumental setup of the Zugspitze solar FTIR spectrometer, the typical configuration of the spectral radiance measurements for which the calibration is applied, and the blackbody calibration source are presented. Section 3 gives a description of the combined calibration strategy, while the uncertainty associated with the calibration procedure is outlined in Sect. 4. In Sect. 5, the validation of calibration results is discussed. Finally, Sect. 6 provides a summary and conclusions.
The NIR solar absorption spectra to which the calibration is applied are
measured with a solar FTIR spectrometer located at the high-altitude
observatory on the summit of the Zugspitze, Germany (47.42
Spectra are typically measured with a liquid-nitrogen-cooled InSb detector
(1850 to 9600 cm
Blackbody calibration source inside the Zugspitze solar FTIR dome,
additional 90
The calibration procedure makes use of a blackbody calibration source
installed in the Zugspitze solar FTIR dome. The calibration source (MIKRON
M330-EU, Lumasense Technologies) is shown in Fig. 1, while its technical
specifications according to the manufacturer are given in Table 2. Blackbody
spectra are measured with the solar FTIR using the solar tracker optics and
an additional gold-coated 90
Our approach comprises a Langley-type calibration described in Sect. 3.1 and
a blackbody calibration presented in Sect. 3.2. Our new calibration strategy
is a combination of both as explained in Sect. 3.3. The calibration
procedure consists of deducing a calibration curve
The Langley method (e.g., Liou, 2002) has been frequently used for solar-constant determination or calibration of sun photometers. It relies on
repeated measurements of solar irradiance or radiance at a range of solar
zenith angles. According to the Beer–Bouguer–Lambert law, the direct solar
irradiance at a wavenumber
Selection of spectra for the Langley measurements made on 13
December 2013. The Langley plot is based on radiance measurements in the
4300 to 4350 cm
Equation (2) is only fulfilled if atmospheric properties like IWV or aerosol optical thickness do not vary during the measurements. Since IWV varies significantly even on the timescale of a few hours (e.g., Kämpfer et al., 2013; Vogelmann et al., 2015), accurate Langley measurements in spectral regions with significant absorption by water vapor have to be carried out within short time intervals, i.e., at high solar zenith angles. We thereby limited the duration of Langley measurements to 1–2 h, which, based on the results of Vogelmann et al. (2015), leads to an IWV variability of about 1 mm during the measurements. Refraction has a significant influence at high solar zenith angles. In order to include refraction effects, air mass values used in this study were computed by means of ray tracing calculations. More specifically, the ray tracing routine of the PROFFIT software (Hase et al., 2004) was used for air mass calculation. Since atmospheric absorption is dominated by water vapor for most spectral points considered in this study, instead of using the air column, the related water vapor column was utilized as an air mass input to the Langley fits.
Langley calibration coefficients were determined from daily sets of selected
solar FTIR spectra recorded under apparently cloud-free conditions at 0.02 cm
We use a preliminary Langley plot to select the spectra which are least
affected by cloud, IWV variation, and FOV effects:
A spectral interval with little molecular absorption, namely
4300 cm A first estimate of the linear relation avoiding cloud and FOV bias
(continuous black line in Fig. 2) was fitted using the spectra with the
highest mean radiance within each air mass bin (width The maximum deviation from the ideal linear relation not attributable
to FOV influence or IWV temporal variability was calculated. The FOV effect
was estimated as outlined in Sect. 4.1. The IWV influence was estimated
based on the expected variability of about 1mm during the 1–2 h Langley
measurements according to Vogelmann et al. (2015). Spectra consistent with the linear relation determined in (ii) minus the
maximum deviation estimated in (iii) measured at an air mass less than 9.0
were selected for further analysis (dashed line in Fig. 2). An air mass
threshold is required since, at very high solar zenith angles, air mass
calculation becomes increasingly inaccurate, and air mass changes
significantly during the spectral averaging period. The air mass threshold
of 9.0 was chosen because beyond this value, significant deviations from the
linear relation according to Eq. (2) can be observed, which indicate
inaccuracies in the air mass calculation. The selected spectra are shown as
green circles in Fig. 2, while discarded spectra are shown in red.
We further processed Langley data sets with a sufficiently high number of
selected spectra according to the selection criteria presented above
(
Selection of suitable spectral points and averaging for Langley
calibration (measurements from 13 December 2013). Grey: initial Langley fit
results; orange: results not affected by solar lines; purple: results after
applying fit uncertainty threshold; blue: final results after applying
stability threshold; red circles: Langley calibration results averaged over
20 cm
A number of issues have to be considered before generating Langley fits
according to Eq. (2) using the selected spectra. During measurements, the
line of sight of the solar FTIR continuously tracks the position of the
center of the solar disc. Sun tracking inaccuracies influence the Langley
measurements due to the fact that the FOV of the solar FTIR only covers a
fraction of the solar disc (FOV diameter for Langley measurements
0.07
The Langley calibration method requires knowledge of the ESS. In this study,
we use the semiempirical synthetic ESS of Kurucz (2005). This
extra-atmospheric spectrum is widely adopted for atmospheric radiative
transfer calculations due to its high spectral resolution (radiance spectra
are provided with 0.1 cm
The uncertainty of the Langley calibration varies strongly throughout the
spectrum. Therefore, it is necessary to select spectral windows in which
accurate Langley results can be obtained. Figure 3 shows the selection steps
applied to the Langley calibration results Spectral points within solar lines are excluded due to the higher ESS
radiance uncertainty in these regions. More specifically, all points with ESS
radiance more than 1 % below the upper linear envelope using 20 cm All spectral points for which the relative Langley fit uncertainty was
above 0.4 % were discarded (orange points in Fig. 3). Furthermore, regions within solar lines not included in the ESS of
Kurucz (2005) and points with spurious low fit uncertainty due to radiance
measurement noise were excluded. For this purpose, all points for which the
standard deviation of Langley calibration results within a 0.1 cm
Blackbody spectral radiance measurements (see Sect. 3.2) show that the solar
FTIR calibration curve varies only slowly with wavenumber. The filtered
Langley results (blue points in Fig. 3) were therefore averaged
(error-weighted mean using Langley fit uncertainties) over
20 cm
Specifications of the blackbody calibration source.
Spectral radiance measurements of the blackbody calibration source described in Sect. 2.2 are used to determine the shape of the calibration curve in spectral intervals between the points suitable for precise Langley calibration. Contrary to the calibration approach described by Gardiner et al. (2012), using a source with a temperature of 3000 K, a lower cavity temperature of 1973.15 K can be used in the Zugspitze experiment due to the combination with Langley measurements. The settings of the FTIR spectra acquisition were similar to the Langley measurements (see Table 2).
As for the Langley measurements, dry atmospheric conditions imply more
narrow spectral intervals affected by water vapor line absorption and
thereby improve the blackbody calibration accuracy. Therefore, only
measurements with an atmospheric water vapor density
Blackbody radiance spectrum recorded on 24 February 2014 with a cavity temperature of 1923.15 K. Grey: measured spectrum; black: result of spectral line exclusion; red: final spectrum after median filtering.
Only spectral points outside water vapor lines were considered to avoid bias
in the calibration. More specifically, only points less than 10
The combined calibration strategy takes advantage of the low-uncertainty
Langley calibration at suitable spectral points (see Sect. 3.1). In between
the Langley points, the shape of the calibration curve is constrained by the
blackbody measurements (see Sect. 3.2). The combined calibration curve
Several contributions to the calibration uncertainty budget are associated
with the Langley measurements. A first contribution results from the
uncertainty of the Langley fit. This contribution is calculated as an
error-weighted mean over the 2
Combined calibration curve (black line) and selected Langley calibration points (red circles) for the Langley measurements made on 13 December 2013 in combination with blackbody measurements made on 24 February 2014.
Relative 2
Furthermore, the reflectivity of the solar tracker mirrors feature spatial
inhomogeneity due to dirt and aging effects. Due to nonideal alignment of
optical elements of the solar tracker, the area covered by the instrument's
FOV of the tracker mirrors changes over time, i.e., depending on the azimuth
and elevation of the instrument's line of sight. This leads to spurious
radiance variations in the Langley calibration and increases the calibration
uncertainty. To obtain an estimate of this error, the position of the
instrument FOV on the tracker elevation mirror for the azimuth and elevation
values encountered during the Langley calibration has to be measured. This
was achieved using an outgoing laser beam aligned with the instrument's
optical axis, whose position on the tracker mirrors for a given azimuth and
elevation is then monitored. In the spectral regions with least atmospheric
absorption, the diurnal variation of the measured solar radiance is about
5 %. This variation is due to a combination of several contributions: a
first contribution is due to the change in atmospheric optical depth (OD)
with air mass as visible in the Langley plot in Fig. 2. In addition, other
atmospheric effects such as temporally variable clouds contribute to the
observed signal. A final contribution is due to the mirror-related effect
mentioned above. A conservative estimate of the FOV-related error is obtained
assuming that the observed diurnal variation is solely due to mirror
inhomogeneity and that mirror reflectivity drops abruptly by this amount
(5 %) outside the area initially covered by the FOV. Consequently, the
error estimate is obtained by multiplying the 5 % reflectivity change
with the fraction by which the area within the field of view has changed
throughout the time interval over which measurements contributing to the
Langley fit were made. The interval is deduced from the laser measurements.
The resulting Langley calibration uncertainty due to mirror inhomogeneity is
The accuracy of the Langley results is also limited by errors in the air mass values used for the fit. Firstly, this is due to inaccurate solar zenith angle input. A second and by far dominant effect is due to the fact that the relative air mass for absorbing species with different concentration profiles is not equal for a given solar zenith angle. Depending on the spectral region, the dominant contribution to atmospheric OD for most Langley points is either due to water vapor or aerosols. For our analysis, water vapor relative air masses were used. The difference in the calibration results when performing the analysis with relative air columns instead of water vapor columns is up to 0.5 % and was taken as an estimate of the air-mass-related calibration uncertainty (see orange line in Fig. 6).
An additional uncertainty contribution of up to 0.25 % results from the uncertainty of the mispointing correction outlined in Sect. 3.1.3 (purple line in Fig. 6). This contribution includes two effects related to the mispointing uncertainty: the effects of air mass uncertainty in the Langley fit and the uncertainty in the solar limb darkening correction outlined in Sect. 3.1.3.
A further uncertainty contribution is associated with the ESS used in the
Langley calibration. While no uncertainty estimate was provided by the
authors for the spectrum of Kurucz (2005), the 2
However, recent studies on the NIR ESS have yielded results which are partly inconsistent within the respective uncertainties and feature differences of up to 5–10 % (see, e.g., Menang et al., 2013; Bolsée et al., 2014; Thuillier et al., 2014, 2015; Weber et al., 2015). The ongoing discussion about the magnitude of the ESS in the NIR implies that the ESS uncertainty estimates reported by recent studies may underestimate the real uncertainty. Therefore, the absolute radiometric uncertainty of the calibration scheme presented in this study remains tentative and more definite constraints require improved knowledge of the NIR ESS.
However, the ESS uncertainty only has a very minor influence on the main aim of this study, namely the use of calibrated solar FTIR spectra in a closure experiment for quantification of the NIR water vapor continuum. This important feature results from the fact that the same ESS is used for calibration and synthetic spectra calculation in the closure experiment and is demonstrated in the companion paper Part 3. Therefore, in the context of closure experiments, the relevant uncertainty budget does not include the ESS contribution and is shown in Fig. 6.
A further contribution to the calibration uncertainty results from the
blackbody measurements. The blackbody calibration curve uncertainty was
calculated as 2 times the standard deviation of all normalized blackbody
calibration curves recorded under suitably dry atmospheric conditions
(near-surface atmospheric water vapor density
The combined calibration according to Eq. (4) is based on the assumption that
the blackbody calibration curve between suitable Langley points can be
approximately described by multiplying the Langley calibration curve with a
linear function, i.e., that the following relation is fulfilled:
The calibration error induced by omitting the Langley result at each
single Langley spectral point The final shape error estimate is set to 0 at all Langley points
At spectral points between those mentioned in (ii), the estimated error
is calculated by linear interpolation.
The shape error generally increases with increasing Langley point spacing.
By construction, the error estimate resulting from the method given above
corresponds to a mean Langley point spacing 2 times as large as the real
spacing. The error estimate provided above is therefore expected to
overestimate the real errors in most cases. The final shape error estimate
is shown as a green curve in Fig. 6 and is up to 0.5 % throughout the
spectral range considered. This low-uncertainty contribution also shows that
the shape of the calibration curves derived from blackbody and Langley
measurements is in good agreement. However, a comparison of the absolute
calibration relying solely on blackbody measurements with Langley results is
not feasible with the Zugspitze instrumental setup. This is due to the fact
that for blackbody measurements signal losses due to the optics setup bias
the absolute level of the blackbody calibration curve, which, however, does
not influence the accuracy of the calibration with the combined method
presented in this study.
Examination of calibration results.
Thermal emission from instrument parts at room temperature contributes a
fraction of less than 10
A first method to validate the calibration results and the associated error
estimate is to investigate the self-consistency of different calibration
cases, i.e., the reproducibility of the calibration. The self-consistency of
blackbody measurements is presented in Sect. 4.2. This result is then used as
an estimate of the blackbody-related contribution to the total calibration
uncertainty. As outlined in Sect. 4.2, this uncertainty contribution does not
exceed 1.5 % throughout the spectral interval considered for calibration.
The reproducibility of the Langley results is estimated by comparing the
Langley measurements made on 12 December 2013 with the ones made on
13 December 2013. As shown in the Fig. 7a, the calibration curves determined
from those two Langley measurements typically differ by less than 1 %
outside absorption bands. In regions with sparse coverage of Langley points,
i.e., within water vapor absorption bands, differences are typically around
1.5 %. Throughout 91.1 % of the calibration spectral range (2500 to
7800 cm
Note that modifications to the solar FTIR instrument such as realignment of optical elements requires repetition of the calibration procedure and the calibration results are only valid during periods with no significant change of instrument characteristics. Such changes can be detected, e.g., by monitoring the modulation efficiency of the FTIR or the instrumental line shape, which is achieved via routine HCl cell measurements (Hase et al., 2013). During the time interval covered by the measurements included in this study, no significant changes in instrument characteristics were detected.
Apart from modifications to the instrument which were discussed above, the
accuracy of the radiometric calibration can decrease over time due to ice
formation on the liquid nitrogen cooled InSb detector in the case of leaks in
the detector's vacuum enclosure (see Gardiner et al., 2012). As outlined in
the companion paper Part 3, the additional absorption by ice formation is
most pronounced in the 3000 to 3400 cm
A further consistency check of the calibration error estimate provided in
Sect. 4 can be obtained by a closure of calibrated spectra with synthetic
solar absorption spectra obtained by radiative transfer model calculations,
which enables us to detect any large deviations of the real calibration
accuracy from the uncertainty estimate given in Sect. 4. More specifically, a
set of calibrated spectra is compared to synthetic spectra obtained with the
LBLRTM_v12.2 radiative transfer model (Clough et al., 2005). The atmospheric
state used as input to the line-by-line radiative transfer model (LBLRTM)
calculations was determined as outlined in Part 1. In summary, we use water
vapor column data retrieved from the solar FTIR spectra. Water vapor profiles
were set according to four-times-daily National Center for Environmental
Prediction (NCEP) resimulation data, while for temperature profiles we used a
combination of NCEP reanalysis results and a fitted near-surface profile
obtained from FIR thermal emission spectra. CO
For the closure analysis, we used spectra measured under clear-sky conditions
during the December 2013 to February 2014 period, during which no realignment
or other modifications to the spectrometer were performed. All spectra with
an air mass greater than 9.0, i.e., a solar zenith angle greater than
The corresponding synthetic spectra were then computed for all calibrated
spectra in the validation data set. Figure 7b shows the mean measured (black)
and synthetic (red) radiance for this set of spectra. It illustrates the
very good general level of agreement between calibrated and synthetic
spectra. The mean spectral residuals, i.e., the difference between synthetic
and measured radiance is shown in red in Fig. 7c, while the standard
deviation of the residuals is shown in grey. Quantitatively accurate closure
is only possible outside solar lines due to the high ESS uncertainty within the
lines. We therefore exclude these regions from the comparison based on the
selection criterion provided in Sect. 3.1.3. Within atmospheric lines, the
uncertainty of the closure is dominated by atmospheric state and line
parameter uncertainties and therefore does not provide substantial insights
into the calibration accuracy. We therefore discarded these spectral points by
excluding all spectral points below 99 % of the upper envelope to the mean
radiance in 20 cm
The accuracy of the calibration uncertainty provided in Sect. 4 can be assessed by comparing the mean spectral residuals to their estimated uncertainty (blue lines in Fig. 7c). In addition to the calibration uncertainty according to Sect. 4, the residual uncertainty given in Fig. 7 contains several further contributions. These contributions describe the atmospheric-state uncertainty and further contributions related to the solar FTIR spectral radiance measurements. A detailed assessment of this closure uncertainty budget is given in Part 1, Sect. 6. In addition to the contributions listed in Part 1, the uncertainty contribution associated with the water continuum absorption has to be taken into account. Since no uncertainty is provided for the MT_CKD 2.5.2 model (Mlawer et al., 2012) used in the synthetic spectra calculation, the continuum error estimate was set to the difference between the upper and lower end of continuum results provided by recent studies, namely the studies by Ptashnik et al. (2012, 2013) and the MT_CKD 2.5.2 model. A more detailed description of these data sets is given in Part 3.
As visible in Fig. 7c, the mean residuals show very good consistency with the
estimated uncertainty. More specifically, a fraction of 97.7 % of the
residual values lies within the 2
We presented a novel radiometric calibration strategy for high-resolution
solar FTIR spectral radiance measurements in the NIR and MIR which relies on
a combination of the Langley method with radiance measurements of a blackbody
source. While the Langley method yields highly accurate calibration results
at a number of suitable spectral points, the blackbody measurements constrain
the shape of the calibration curve in between these points. The combined
calibration scheme therefore provides a 2
A central advantage of the combined method is that it provides sufficiently accurate calibration for the quantification of the NIR water vapor continuum in an atmospheric radiative closure experiment. Furthermore, the combined calibration scheme can be implemented also at remote sites including the Zugspitze summit observatory and therefore represents a suitable alternative to the method by Gardiner et al. (2012). However, contrary to the method by Gardiner et al. (2012), the combined method presented in this study is not directly traceable to a primary standard and its accuracy for applications beyond closure experiments relies on an accurate knowledge of the ESS, which, as outlined above, is a topic of ongoing research. Therefore, the presented method is currently best suited for the use in closure experiments, while future, more robust constraints on the NIR ESS are expected to provide the foundation for accurate low-uncertainty calibration with the combined method for other applications.
The calibration scheme was implemented in the spectral range of 2500 to
7800 cm
As outlined above, the use of a single blackbody calibration source is
suitable for solar FTIR measurements in the NIR, contrary, e.g., to the
Atmospheric Emitted Radiance Interferometer (AERI) (Knuteson et al., 2004)
that achieves radiometric calibration in the FIR and MIR via the method
proposed by Revercomb et al. (1988) using two blackbody sources at different
cavity temperatures. This is mainly due to the negligible influence of
thermal emission by the instrument on the measured radiance in the NIR (see
Sect. 4.3). A nonlinear detector response represents a further issue that
would require the use of multiple calibration sources. Eventual detector
nonlinearity can be detected in the measured spectra as spurious radiance
exceeding the measurement noise in saturated regions, i.e., within saturated
spectral lines or in spectral regions beyond the detector's measurement
range. However, using this method, no significant nonlinearity was found for
the InSb detector setup used in this study. An extension of the proposed
technique using an additional blackbody source at a different temperature is
therefore useful when applying radiometric calibration to spectra in the
wavenumber range below 2500 cm
The presented scheme therefore fulfills the main goal, i.e., to provide sufficiently accurate radiometric calibration of solar FTIR spectra for the use in radiative closure experiments. Most notably, the calibration scheme thereby enables, for the first time, a quantification of the water vapor continuum in the NIR spectral range under atmospheric conditions, and the corresponding results are presented in the companion publication Part 3.
The underlying data of Fig. 6 are available in the Supplement. Figures 2 to 5 and 7 are illustrations specific to the Zugspitze site. The underlying data can, however, be obtained at any time from the corresponding author on demand.
We are grateful for the constructive and helpful reviews and short comments, which led to significant improvements of this paper. We furthermore thank H. P. Schmid (KIT/IMK-IFU) for his continual interest in this work. Funding by the Bavarian State Ministry of the Environment and Consumer Protection (contracts TLK01U-49581 and VAO-II TP I/01) and Deutsche Bundesstiftung Umwelt is gratefully acknowledged. We thank U. Köhler (Meteorologisches Observatorium Hohenpeißenberg, DWD) for providing ozone column measurements, M. Wiegner (LMU München) for access to sun photometer measurement data, P. Hausmann (KIT/IMK-IFU) for providing IWV retrievals, and F. Hase (KIT/IMK-ASF) for valuable discussions. Additionally, we are grateful for support by the Deutsche Forschungsgemeinschaft and the Open Access Publishing Fund of the Karlsruhe Institute of Technology. The article processing charges for this open-access publication were covered by a Research Centre of the Helmholtz Association. Edited by: H. Maring Reviewed by: three anonymous referees