A gas chromatograph for quantification of peroxycarboxylic nitric anhydrides calibrated by thermal dissociation cavity ring-down spectroscopyAtmospheric Measurement Techniques, 7, 3263-3283, 2014Author(s): T. W. Tokarek, J. A. Huo, C. A. Odame-Ankrah, D. Hammoud, Y. M. Taha, and H. D. OsthoffThe peroxycarboxylic nitric anhydrides (PANs, molecular formula:
RC(O)O2NO2) can readily be observed by gas chromatography (PAN-GC)
coupled to electron capture detection. Calibration of a PAN-GC remains a
challenge, because the response factors differ for each of the PANs, and because their
synthesis in sufficiently high purity is non-trivial, in particular for PANs
containing unsaturated side chains. In this manuscript, a PAN-GC and its
calibration using diffusion standards, whose output was quantified by blue
diode laser thermal dissociation cavity ring-down spectroscopy (TD-CRDS), are
described. The PAN-GC peak areas correlated linearly with total peroxy
nitrate (ΣPN) mixing ratios measured by TD-CRDS
(r > 0.96). Accurate determination of response factors
required the concentrations of PAN impurities in the synthetic standards to
be subtracted from ΣPN. The PAN-GC and its TD-CRDS calibration method
were deployed during ambient air measurement campaigns in Abbotsford, BC,
from 20 July to 5 August 2012, and during the Fort McMurray Oil Sands
Strategic Investigation of Local Sources (FOSSILS) campaign at the AMS13
ground site in Fort McKay, AB, from 10 August to 5 September 2013. The PAN-GC
limits of detection for PAN, PPN, and MPAN during FOSSILS were 1, 2, and
3 pptv, respectively. For the Abbotsford data set, the PAN-GC mixing ratios
were compared, and agreed with those determined in parallel by thermal
dissociation chemical ionization mass spectrometry (TD-CIMS). Advantages and
disadvantages of the PAN measurement techniques used in this work and the
utility of TD-CRDS as a PAN-GC calibration method are discussed.

Retrieval of cirrus cloud optical thickness and top altitude from geostationary remote sensingAtmospheric Measurement Techniques, 7, 3233-3246, 2014Author(s): S. Kox, L. Bugliaro, and A. OstlerA novel approach for the detection of cirrus clouds and the retrieval of
optical thickness and top altitude based on the measurements of the Spinning
Enhanced Visible and Infrared Imager (SEVIRI) aboard the geostationary
Meteosat Second Generation (MSG) satellite is presented. Trained with 8 000 000 co-incident measurements of the Cloud-Aerosol Lidar with Orthogonal
Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder
Satellite Observations (CALIPSO) mission the new "cirrus optical properties
derived from CALIOP and SEVIRI algorithm during day and night" (COCS)
algorithm utilizes a backpropagation neural network to provide accurate
measurements of cirrus optical depth τ at λ = 532 nm and top
altitude z every 15 min covering almost one-third of the Earth's atmosphere.
The retrieved values are validated with independent measurements of CALIOP
and the optical thickness derived by an airborne high spectral resolution
lidar.

The AquaVIT-1 intercomparison of atmospheric water vapor measurement techniquesAtmospheric Measurement Techniques, 7, 3177-3213, 2014Author(s): D. W. Fahey, R.-S. Gao, O. Möhler, H. Saathoff, C. Schiller, V. Ebert, M. Krämer, T. Peter, N. Amarouche, L. M. Avallone, R. Bauer, Z. Bozóki, L. E. Christensen, S. M. Davis, G. Durry, C. Dyroff, R. L. Herman, S. Hunsmann, S. M. Khaykin, P. Mackrodt, J. Meyer, J. B. Smith, N. Spelten, R. F. Troy, H. Vömel, S. Wagner, and F. G. WienholdThe AquaVIT-1 intercomparison of atmospheric water vapor measurement
techniques was conducted at the aerosol and cloud simulation chamber AIDA
(Aerosol Interaction and Dynamics in the Atmosphere) at
the Karlsruhe Institute of Technology, Germany, in October 2007. The overall
objective was to intercompare state-of-the-art and prototype atmospheric
hygrometers with each other and with independent humidity standards under
controlled conditions. This activity was conducted as a blind
intercomparison with coordination by selected referees. The effort was
motivated by persistent discrepancies found in atmospheric measurements
involving multiple instruments operating on research aircraft and balloon
platforms, particularly in the upper troposphere and lower stratosphere,
where water vapor reaches its lowest atmospheric values (less than 10 ppm).
With the AIDA chamber volume of 84 m3, multiple instruments analyzed
air with a common water vapor mixing ratio, by extracting air into
instrument flow systems, by locating instruments inside the chamber, or
by sampling the chamber volume optically. The intercomparison was successfully
conducted over 10 days during which pressure, temperature, and mixing ratio
were systematically varied (50 to 500 hPa, 185 to 243 K, and 0.3 to 152 ppm).
In the absence of an accepted reference instrument, the absolute accuracy of
the instruments was not established. To evaluate the intercomparison, the
reference value was taken to be the ensemble mean of a core subset of the
measurements. For these core instruments, the agreement between 10 and
150 ppm of water vapor is considered good with variation about the reference
value of about ±10% (±1σ). In the region of most
interest between 1 and 10 ppm, the core subset agreement is fair with
variation about the reference value of ±20% (±1σ).
The upper limit of precision was also derived for each instrument from the
reported data. The implication for atmospheric measurements is that the
substantially larger differences observed during in-flight intercomparisons
stem from other factors associated with the moving platforms or the
non-laboratory environment. The success of AquaVIT-1 provides a template for
future intercomparison efforts with water vapor or other species that are
focused on improving the analytical quality of atmospheric measurements on
moving platforms.

Reconstruction of global solar radiation time series from 1933 to 2013 at the Izaña Atmospheric ObservatoryAtmospheric Measurement Techniques, 7, 3139-3150, 2014Author(s): R. D. García, E. Cuevas, O. E. García, V. E. Cachorro, P. Pallé, J. J. Bustos, P. M. Romero-Campos, and A. M. de FrutosThis paper presents the reconstruction of the 80-year time series of daily
global solar radiation (GSR) at the subtropical high-mountain
Izaña Atmospheric Observatory (IZO) located in Tenerife (The Canary
Islands, Spain). For this purpose, we combine GSR estimates from sunshine
duration (SD) data using the Ångström–Prescott method over the
1933/1991 period, and GSR observations directly performed by pyranometers
between 1992 and 2013. Since GSR measurements have been used as a reference,
a strict quality control has been applied based on principles of physical
limits and comparison with LibRadtran model. By comparing with high quality
GSR measurements, the precision and consistency over time of GSR estimations
from SD data have been successfully documented. We obtain an overall root
mean square error (RMSE) of 9.2% and an agreement between the variances
of GSR estimations and GSR measurements within 92%. Nonetheless, this
agreement significantly increases when the GSR estimation is done considering
different daily fractions of clear sky (FCS). In that case, RMSE is reduced
by half, to about 4.5%, when considering percentages of
FCS > 40% (~ 90% of days in the testing period).
Furthermore, we prove that the GSR estimations can monitor the GSR anomalies
in consistency with GSR measurements and, then, can be suitable for
reconstructing solar radiation time series. The reconstructed IZO GSR time
series between 1933 and 2013 confirms change points and periods of
increases/decreases of solar radiation at Earth's surface observed at
a global scale, such as the early brightening, dimming and brightening. This
fact supports the consistency of the IZO GSR time series presented in this
work, which may be a reference for solar radiation studies in the subtropical
North Atlantic region.

Evaluation of wind profiles from the NERC MST radar, Aberystwyth, UKAtmospheric Measurement Techniques, 7, 3113-3126, 2014Author(s): C. F. Lee, G. Vaughan, and D. A. HooperThis study quantifies the uncertainties in winds measured by the Aberystwyth
Mesosphere–Stratosphere–Troposphere (MST) radar (52.4° N,
4.0° W), before and after its renovation in March 2011. A total of 127
radiosondes provide an independent measure of winds. Differences between
radiosonde and radar-measured horizontal winds are correlated with long-term
averages of vertical velocities, suggesting an influence from local mountain
waves. These local influences are an important consideration when using radar
winds as a measure of regional conditions, particularly for numerical weather
prediction. For those applications, local effects represent a source of
sampling error additional to the inherent uncertainties in the measurements
themselves. The radar renovation improved the signal-to-noise ratio (SNR) of measurements, with a
corresponding improvement in altitude coverage. It also corrected an
underestimate of horizontal wind speeds attributed to beam formation
problems, due to pre-renovation component failure. The root mean square error (RMSE) in
radar-measured horizontal wind components, averaged over half an hour,
increases with wind speed and altitude, and is 0.8–2.5 m s−1
(6–12% of wind speed) for post-renovation winds. Pre-renovation values
are typically 0.1 m s−1 larger. The RMSE in radial velocities is
<0.04 m s−1. Eight weeks of special radar operation are used to
investigate the effects of echo power aspect sensitivity. Corrections for
echo power aspect sensitivity remove an underestimate of horizontal wind
speeds; however aspect sensitivity is azimuthally anisotropic at the scale of
routine observations (≈1 h). This anisotropy introduces random
error into wind profiles. For winds averaged over half an hour, the RMSE
is around 3.5% above 8 km, but as large as 4.5% in the
mid-troposphere.

Aircraft testing of the new Blunt-body Aerosol Sampler (BASE)Atmospheric Measurement Techniques, 7, 3085-3093, 2014Author(s): A. Moharreri, L. Craig, P. Dubey, D. C. Rogers, and S. DhaniyalaThere is limited understanding of the role of aerosols in the formation and
modification of clouds, partly due to inadequate data on such systems.
Aircraft-based aerosol measurements in the presence of cloud particles have
proven to be challenging because of the problem of cloud droplet/ice particle
shatter and the generation of secondary artifact particles that contaminate
aerosol samples. Recently, the design of a new aircraft inlet, called the
Blunt-body Aerosol Sampler (BASE), which enables sampling of interstitial
aerosol particles, was introduced. Numerical modeling results and laboratory
test data suggested that the BASE inlet should sample interstitial particles
with minimal shatter particle contamination. Here, the sampling performance
of the inlet is established from aircraft-based measurements. Initial
aircraft test results obtained during the PLOWS (Profiling of Winter Storms)
campaign indicated two problems with the original BASE design: separated
flows around the BASE at high altitudes and a significant shatter problem
when sampling in drizzle. The test data were used to improve the accuracy of
flow and particle trajectory modeling around the inlet, and the results from
the improved flow model were used to guide design modifications of the BASE to
overcome the problems identified in its initial deployment. The performance
of the modified BASE was tested during the ICE–T (Ice in Clouds Experiment –
Tropics) campaign, and the inlet was seen to provide near shatter-free
measurements in a wide range of cloud conditions. The initial aircraft test
results, design modifications, and the performance characteristics of the BASE
relative to another interstitial inlet, the submicron aerosol inlet (SMAI),
are presented.

An inverse-modelling approach for frequency response correction of capacitive humidity sensors in ABL research with small remotely piloted aircraft (RPA)Atmospheric Measurement Techniques, 7, 3059-3069, 2014Author(s): N. Wildmann, F. Kaufmann, and J. BangeThe measurement of water vapour concentration in the atmosphere is an ongoing
challenge in environmental research. Satisfactory solutions exist for
ground-based meteorological stations and measurements of mean values.
However, carrying out advanced research of thermodynamic processes aloft as well, above the
surface layer and especially in the atmospheric boundary layer (ABL),
requires the resolution of small-scale turbulence. Sophisticated optical
instruments are used in airborne meteorology with manned aircraft to achieve
the necessary fast-response measurements of the order of 10 Hz (e.g. LiCor
7500). Since these instruments are too large and heavy for the application on
small remotely piloted aircraft (RPA), a method is presented in this study that enhances small capacitive humidity sensors to be able to resolve
turbulent eddies of the order of 10 m. The sensor examined here is a
polymer-based sensor of the type P14-Rapid, by the Swiss company Innovative
Sensor Technologies (IST) AG, with a surface area of less than 10 mm2 and
a negligible weight. A physical and dynamical model of this sensor is
described and then inverted in order to restore original water vapour
fluctuations from sensor measurements. Examples of flight measurements show
how the method can be used to correct vertical profiles and resolve
turbulence spectra up to about 3 Hz. At an airspeed of 25 m s−1 this
corresponds to a spatial resolution of less than 10 m.

Smoothing error pitfallsAtmospheric Measurement Techniques, 7, 3023-3034, 2014Author(s): T. von ClarmannThe difference due to the content of a priori information between a
constrained retrieval and the true atmospheric state is usually represented
by a diagnostic quantity called smoothing error. In this paper it is shown
that, regardless of the usefulness of the smoothing error as a diagnostic
tool in its own right, the concept of the smoothing error as a component of
the retrieval error budget is questionable because it is not compliant with
Gaussian error propagation. The reason for this is that the smoothing error
does not represent the expected deviation of the retrieval from the true
state but the expected deviation of the retrieval from the atmospheric state
sampled on an arbitrary grid, which is itself a smoothed representation of
the true state; in other words, to characterize the full loss of information
with respect to the true atmosphere, the effect of the representation of
the atmospheric state on a finite grid also needs to be considered. The idea of a
sufficiently fine sampling of this reference atmospheric state is problematic
because atmospheric variability occurs on all scales, implying that there is
no limit beyond which the sampling is fine enough. Even the idealization of
infinitesimally fine sampling of the reference state does not help, because
the smoothing error is applied to quantities which are only defined in a
statistical sense, which implies that a finite volume of sufficient spatial
extent is needed to meaningfully discuss temperature or concentration.
Smoothing differences, however, which play a role when measurements are
compared, are still a useful quantity if the covariance matrix involved has
been evaluated on the comparison grid rather than resulting from
interpolation and if the averaging kernel matrices have been evaluated on a
grid fine enough to capture all atmospheric variations that the instruments are
sensitive to. This is, under the assumptions stated, because the undefined
component of the smoothing error, which is the effect of smoothing implied by
the finite grid on which the measurements are compared, cancels out when the
difference is calculated. If the effect of a retrieval constraint is to be
diagnosed on a grid finer than the native grid of the retrieval by means of
the smoothing error, the latter must be evaluated directly on the fine grid,
using an ensemble covariance matrix which includes all variability on the
fine grid. Ideally, the averaging kernels needed should be calculated
directly on the finer grid, but if the grid of the original averaging kernels
allows for representation of all the structures the instrument is sensitive to, then their
interpolation can be an adequate approximation.

Validation of XCH4 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement dataAtmospheric Measurement Techniques, 7, 2987-3005, 2014Author(s): M. Inoue, I. Morino, O. Uchino, Y. Miyamoto, T. Saeki, Y. Yoshida, T. Yokota, C. Sweeney, P. P. Tans, S. C. Biraud, T. Machida, J. V. Pittman, E. A. Kort, T. Tanaka, S. Kawakami, Y. Sawa, K. Tsuboi, and H. MatsuedaColumn-averaged dry-air mole fractions of methane (XCH4), retrieved
from Greenhouse gases Observing SATellite (GOSAT) short-wavelength infrared
(SWIR) spectra, were validated by using aircraft measurement data from the
National Oceanic and Atmospheric Administration (NOAA), the US Department
of Energy (DOE), the National Institute for Environmental Studies (NIES),
the HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT
validation aircraft observation campaign over Japan. In the calculation of
XCH4 from aircraft measurements (aircraft-based XCH4), other
satellite data were used for the CH4 profiles above the tropopause. We
proposed a data-screening scheme for aircraft-based XCH4 for reliable
validation of GOSAT XCH4. Further, we examined the impact of GOSAT SWIR
column averaging kernels (CAK) on the aircraft-based XCH4 calculation
and found that the difference between aircraft-based XCH4 with and
without the application of the GOSAT CAK was less than ±9 ppb at
maximum, with an average difference of −0.5 ppb.

We compared GOSAT XCH4 Ver. 02.00 data retrieved within ±2° or ±5° latitude–longitude boxes centered at
each aircraft measurement site with aircraft-based XCH4 measured on a
GOSAT overpass day. In general, GOSAT XCH4 was in good agreement with
aircraft-based XCH4. However, over land, the GOSAT data showed a
positive bias of 1.5 ppb (2.0 ppb) with a standard deviation of 14.9 ppb
(16.0 ppb) within the ±2° (±5°) boxes,
and over ocean, the average bias was 4.1 ppb (6.5 ppb) with a standard
deviation of 9.4 ppb (8.8 ppb) within the ±2° (±5°) boxes. In addition, we obtained similar results when we used
an aircraft-based XCH4 time series obtained by curve fitting with
temporal interpolation for comparison with GOSAT data.

A horizontal mobile measuring system for atmospheric quantitiesAtmospheric Measurement Techniques, 7, 2967-2980, 2014Author(s): J. Hübner, J. Olesch, H. Falke, F. X. Meixner, and T. FokenA fully automatic horizontal mobile measuring system (HMMS) for atmospheric
quantities has been developed. The HMMS is based on the drive mechanism of
a garden railway system and can be installed at any location and along any
measuring track. In addition to meteorological quantities (temperature,
humidity and short-/long-wave down/upwelling radiation), HMMS also measures
trace gas concentrations (carbon dioxide and ozone). While sufficient spatial
resolution is a problem even for measurements on distributed towers, this
could be easily achieved with the HMMS, which has been specifically developed
to obtain higher information density about horizontal gradients in
a heterogeneous forest ecosystem. There, horizontal gradients of
meteorological quantities and trace gases could be immense, particularly at
the transition from a dense forest to an open clearing, with large impact on
meteorological parameters and exchange processes. Consequently, HMMS was
firstly applied during the EGER IOP3 project (ExchanGE processes in mountainous
Regions – Intense Observation Period 3) in the Fichtelgebirge
Mountains (SE Germany) during summer 2011. At a constant 1 m above
ground, the measuring track of the HMMS consisted of a straight line
perpendicular to the forest edge, starting in the dense spruce forest and
leading 75 m into an open clearing. Tags with bar codes, mounted every
metre on the wooden substructure, allowed (a) keeping the speed of the HMMS
constant (approx. 0.5 m s−1) and (b) operation of the HMMS in
a continuous back and forth running mode. During EGER IOP3, HMMS was
operational for almost 250 h. Results show that – due to considerably
long response times (between 4 and 20 s) of commercial
temperature, humidity and the radiation sensors – true spatial variations of
the meteorological quantities could not be adequately captured (mainly at the
forest edge). Corresponding dynamical (spatial) errors of the measurement
values were corrected on the basis of well-defined individual response times
of the sensors and application of a linear correction algorithm. Due to the
very short response times (≤ 1 s) of the applied commercial
CO2 and O3 analysers, dynamical errors for the trace gas data
were negligible and no corrections were done.

GOME-2 total ozone columns from MetOp-A/MetOp-B and assimilation in the MACC systemAtmospheric Measurement Techniques, 7, 2937-2951, 2014Author(s): N. Hao, M. E. Koukouli, A. Inness, P. Valks, D. G. Loyola, W. Zimmer, D. S. Balis, I. Zyrichidou, M. Van Roozendael, C. Lerot, and R. J. D. SpurrThe two Global Ozone Monitoring Instrument (GOME-2) sensors operated in
tandem are flying onboard EUMETSAT's (European Organisation for the Exploitation of Meteorological Satellites) MetOp-A and MetOp-B satellites,
launched in October 2006 and September 2012 respectively. This paper
presents the operational GOME-2/MetOp-A (GOME-2A) and
GOME-2/MetOp-B (GOME-2B)
total ozone products provided by the EUMETSAT Satellite
Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF).
These products are generated using the latest version of the GOME
Data Processor (GDP version 4.7). The enhancements in GDP 4.7, including the
application of Brion–Daumont–Malicet ozone absorption cross sections, are
presented here. On a global scale, GOME-2B has the same high accuracy as the
corresponding GOME-2A products. There is an excellent agreement between the
ozone total columns from the two sensors, with GOME-2B values slightly lower
with a mean difference of only 0.55±0.29%. First global validation
results for 6 months of GOME-2B total ozone using ground-based measurements
show that on average the GOME-2B total ozone data obtained with GDP 4.7 are
slightly higher than, both, Dobson observations by about 2.0±1.0% and
Brewer observations by about 1.0±0.8%. It is concluded that the
total ozone columns (TOCs) provided by GOME-2A and GOME-2B are consistent
and may be used simultaneously without introducing systematic effects, which
has been illustrated for the Antarctic ozone hole on 18 October 2013.
GOME-2A total ozone data have been used operationally in the Copernicus
atmospheric service project MACC-II (Monitoring Atmospheric Composition and
Climate – Interim Implementation) near-real-time (NRT) system since October 2013.
The magnitude of the bias correction needed for assimilating GOME-2A
ozone is reduced (to about −6 DU in the global mean) when the GOME-2 ozone
retrieval algorithm changed to GDP 4.7.

Derivation of tropospheric methane from TCCON CH4 and HF total column observationsAtmospheric Measurement Techniques, 7, 2907-2918, 2014Author(s): K. M. Saad, D. Wunch, G. C. Toon, P. Bernath, C. Boone, B. Connor, N. M. Deutscher, D. W. T. Griffith, R. Kivi, J. Notholt, C. Roehl, M. Schneider, V. Sherlock, and P. O. WennbergThe Total Carbon Column Observing Network (TCCON) is a global
ground-based network of Fourier transform spectrometers that produce
precise measurements of column-averaged dry-air mole fractions of
atmospheric methane (CH4). Temporal variability in the total
column of CH4 due to stratospheric dynamics obscures
fluctuations and trends driven by tropospheric transport and local surface fluxes
that are critical for understanding CH4 sources and sinks.
We reduce the contribution of stratospheric variability from the total
column average by subtracting an estimate
of the stratospheric CH4 derived from simultaneous
measurements of hydrogen fluoride (HF). HF provides a proxy for
stratospheric CH4 because it is strongly correlated to CH4 in the
stratosphere, has an accurately known tropospheric abundance (of zero), and
is measured at most TCCON stations. The stratospheric partial column of CH4 is
calculated as a function of the zonal and annual trends in the
relationship between CH4 and HF in the stratosphere, which
we determine from ACE-FTS satellite data. We also explicitly take
into account the CH4 column averaging kernel to estimate the
contribution of stratospheric CH4 to the total column. The
resulting tropospheric CH4 columns are consistent with in
situ aircraft measurements and augment existing observations in the
troposphere.

Influence of changes in humidity on dry temperature in GPS RO climatologiesAtmospheric Measurement Techniques, 7, 2883-2896, 2014Author(s): J. Danzer, U. Foelsche, B. Scherllin-Pirscher, and M. SchwärzRadio occultation (RO) data are increasingly used in climate
research. Accurate phase (change) measurements of Global Positioning
System (GPS) signals are the basis for the retrieval of near-vertical profiles of bending angle, microwave refractivity, density,
pressure, and temperature. If temperature is calculated from
observed refractivity with the assumption that water vapor is zero,
the product is called "dry temperature", which is commonly used to
study earth's atmosphere, e.g., when analyzing temperature
trends due to global warming. Dry temperature is a useful quantity,
since it does not need additional background information in its
retrieval. However, it can only be safely used as proxy for physical
temperature, where moisture is negligible. The altitude region above
which water vapor does not play a dominant role anymore, depends
primarily on latitude and season.

In this study we first investigated the influence of water vapor on
dry temperature RO profiles. Hence, we analyzed the maximum altitude
down to which monthly mean dry temperature profiles can be regarded
as being equivalent to physical temperature. This was done by
examining dry temperature to physical temperature differences of
monthly mean analysis fields from the European Centre for
Medium-Range Weather Forecasts (ECMWF), studied from 2006 until
2010. We introduced cutoff criteria, where maximum temperature
differences of −0.1, −0.05, and
−0.02 K were allowed (dry temperature is always lower than
physical temperature), and computed the corresponding altitudes. As
an example, a temperature difference of −0.05 K in the
tropics was found at an altitude of about 14 km, while at
higher northern latitudes in winter it was found at an altitude of
about 9–10 km, in summer at about
11 km.

Furthermore, regarding climate change, we expect an increase of
absolute humidity in the atmosphere. This possible trend in water
vapor could yield a wrongly interpreted dry temperature trend. As
a consequence, we performed a model study, investigating the
increase in height of the transition region between moist and dry
air. We used data from the fifth phase of the Coupled Model
Intercomparison Project (CMIP5), analyzing again monthly mean dry
temperature to physical temperature differences, now from the years
2006 to 2050. We used the highest emission scenario RCP8.5
(representative concentration pathway), studying all available
models of the CMIP5 project, analyzing one internal run per model,
with the goal to identify the altitude region where trends in dry
temperature can be safely regarded as reflecting trends in physical
temperature. From all models we therefore choose a selection of
models ("max 8" CMIP5 models), which showed the largest trend
differences. As a result, our trend study suggests that the lower
boundary of the region where dry temperature is essentially equal to
physical temperature rises about 150 m decade−1.

Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithmsAtmospheric Measurement Techniques, 7, 2839-2867, 2014Author(s): U. Hamann, A. Walther, B. Baum, R. Bennartz, L. Bugliaro, M. Derrien, P. N. Francis, A. Heidinger, S. Joro, A. Kniffka, H. Le Gléau, M. Lockhoff, H.-J. Lutz, J. F. Meirink, P. Minnis, R. Palikonda, R. Roebeling, A. Thoss, S. Platnick, P. Watts, and G. WindThe role of clouds remains the largest uncertainty in climate
projections. They influence solar and thermal radiative transfer and
the earth's water cycle. Therefore, there is an urgent need for
accurate cloud observations to validate climate models and to
monitor climate change. Passive satellite imagers measuring
radiation at visible to thermal infrared (IR) wavelengths provide
a wealth of information on cloud properties. Among others, the cloud
top height (CTH) – a crucial parameter to estimate the thermal cloud
radiative forcing – can be retrieved. In this paper we investigate
the skill of ten current retrieval algorithms to estimate the CTH
using observations from the Spinning Enhanced Visible and InfraRed
Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the
first part we compare ten SEVIRI cloud top pressure (CTP)
data sets with each other. The SEVIRI algorithms catch the
latitudinal variation of the CTP in a similar way. The agreement is
better in the extratropics than in the tropics. In the tropics
multi-layer clouds and thin cirrus layers complicate the CTP
retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus,
marine stratocumulus and the optically thick cores of the deep
convective system.

In the second part of the paper the SEVIRI retrievals are compared
to CTH observations from the Cloud–Aerosol LIdar with Orthogonal
Polarization (CALIOP) and Cloud Profiling Radar (CPR)
instruments. It is important to note that the different measurement
techniques cause differences in the retrieved CTH data. SEVIRI
measures a radiatively effective CTH, while the CTH of the active
instruments is derived from the return time of the emitted radar or lidar
signal. Therefore, some systematic differences are expected. On
average the CTHs detected by the SEVIRI algorithms are 1.0 to
2.5 km lower than CALIOP observations, and the correlation
coefficients between the SEVIRI and the CALIOP data sets range
between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer
to the CPR measurements than to CALIOP measurements. The biases between SEVIRI and
CPR retrievals range from −0.8 km to 0.6 km.
The correlation coefficients of CPR and
SEVIRI observations vary between 0.82 and 0.89. To discuss the
origin of the CTH deviation, we investigate three
cloud categories: optically thin and thick single layer as well as
multi-layer clouds. For optically thick clouds the correlation
coefficients between the SEVIRI and the reference data sets are
usually above 0.95. For optically thin single layer clouds the
correlation coefficients are still above 0.92. For this cloud
category the SEVIRI algorithms yield CTHs that are lower than CALIOP
and similar to CPR observations. Most challenging are the
multi-layer clouds, where the correlation coefficients are for most
algorithms between 0.6 and 0.8. Finally, we evaluate the
performance of the SEVIRI retrievals for boundary layer clouds.
While the CTH retrieval for this cloud type is relatively accurate,
there are still considerable differences between the
algorithms. These are related to the uncertainties and limited
vertical resolution of the assumed temperature profiles in
combination with the presence of temperature inversions, which lead
to ambiguities in the CTH retrieval. Alternative approaches for the
CTH retrieval of low clouds are discussed.

Retrieval of sulfur dioxide from a ground-based thermal infrared imaging cameraAtmospheric Measurement Techniques, 7, 2807-2828, 2014Author(s): A. J. Prata and C. BernardoRecent advances in uncooled detector technology now offer the possibility of
using relatively inexpensive thermal (7 to 14 μm) imaging devices
as tools for studying and quantifying the behaviour of hazardous gases and
particulates in atmospheric plumes. An experimental fast-sampling (60 Hz)
ground-based uncooled thermal imager (Cyclops), operating with four spectral
channels at central wavelengths of 8.6, 10, 11 and 12 μm and one
broadband channel (7–14 μm) has been tested at several volcanoes
and at an industrial site, where SO2 was a major constituent of the
plumes. This paper presents new algorithms, which include atmospheric
corrections to the data and better calibrations to show that SO2 slant
column density can be reliably detected and quantified. Our results indicate
that it is relatively easy to identify and discriminate SO2 in
plumes, but more challenging to quantify the column densities. A full
description of the retrieval algorithms, illustrative results and a detailed
error analysis are provided. The noise-equivalent temperature difference
(NEΔT) of the spectral channels, a fundamental measure of the quality
of the measurements, lies between 0.4 and 0.8 K, resulting in slant column
density errors of 20%. Frame averaging and improved NEΔT's can
reduce this error to less than 10%, making a stand-off, day or night
operation of an instrument of this type very practical for both monitoring
industrial SO2 emissions and for SO2 column densities and emission
measurements at active volcanoes. The imaging camera system may also be used
to study thermal radiation from meteorological clouds and the
atmosphere.

Validation of the Aura High Resolution Dynamics Limb Sounder geopotential heightsAtmospheric Measurement Techniques, 7, 2775-2785, 2014Author(s): L. L. Smith and J. C. GilleThe geopotential height (GPH) product created from global observations by
the High Resolution Dynamics Limb Sounder (HIRDLS) instrument on NASA's
Earth Observing System (EOS) Aura spacecraft is discussed. The accuracy,
resolution and precision of the HIRDLS version 7 algorithms are assessed and
data screening recommendations are made. Comparisons with GPH from
observations, reanalyses and models including European Centre for
Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), and
National Centers for Environmental Prediction/National Center for
Atmospheric Research (NCEP/NCAR) Reanalysis illustrate the HIRDLS GPHs have a
precision ranging from 2 to 30 m and an accuracy of ±100 m up to 1 hPa.
Comparisons indicate HIRDLS GPH may have a slight low bias in the tropics
and a slight high bias at high latitudes. Geostrophic winds computed with
HIRDLS GPH qualitatively agree with winds from other data sources including
ERA-Interim.

Potential of airborne lidar measurements for cirrus cloud studiesAtmospheric Measurement Techniques, 7, 2745-2755, 2014Author(s): S. Groß, M. Wirth, A. Schäfler, A. Fix, S. Kaufmann, and C. VoigtAerosol and water vapour measurements were performed with the lidar system
WALES of Deutsches Zentrum für Luft- und Raumfahrt (DLR) in October and
November 2010 during the first mission with the new German research aircraft
G55-HALO. Curtains composed of lidar profiles beneath the aircraft show the
vertical and horizontal distribution and variability of water vapour mixing
ratio and backscatter ratio above Germany. Two missions on 3 and
4 November 2010 were selected to derive the water vapour mixing ratio inside
cirrus clouds from the lidar instrument. A good agreement was found with
in situ observations performed on a second research aircraft flying below
HALO. ECMWF analysis temperature data are used to derive relative humidity
fields with respect to ice (RHi) inside and outside of cirrus clouds from the lidar water vapour
observations. The RHi variability is dominated by small-scale fluctuations in
the water vapour fields while the temperature variation has a minor impact.
The most frequent in-cloud RHi value from lidar observations is 98%. The
RHi variance is smaller inside the cirrus than outside of the cloud.
2-D histograms of relative humidity and backscatter ratio show
significant differences for in-cloud and out-of-cloud situations for two
different cirrus cloud regimes. Combined with accurate temperature
measurements, the lidar observations have a great potential for detailed
statistical cirrus cloud and related humidity studies.

The MUSICA MetOp/IASI H2O and δD products: characterisation and long-term comparison to NDACC/FTIR dataAtmospheric Measurement Techniques, 7, 2719-2732, 2014Author(s): A. Wiegele, M. Schneider, F. Hase, S. Barthlott, O. E. García, E. Sepúlveda, Y. González, T. Blumenstock, U. Raffalski, M. Gisi, and R. KohlheppWithin the project MUSICA (MUlti-platform remote Sensing of Isotopologues for
investigating the Cycle of Atmospheric water) ground- and space-based remote
sensing as well as in situ data sets of tropospheric water vapour
isotopologues are provided. The space-based remote-sensing data set is
produced from spectra measured by the IASI (Infrared Atmospheric Sounding
Interferometer) sensor and is potentially available on a global scale.

Here, we present the MUSICA IASI data for three different geophysical
locations (subtropics, midlatitudes, and Arctic), and we provide a
comprehensive characterisation of the complex nature of such space-based
isotopologue remote-sensing products. The quality assessment study is
complemented by a comparison to MUSICA's ground-based FTIR (Fourier Transform
InfraRed) remote-sensing data retrieved from the spectra recorded at three
different locations within the framework of NDACC (Network for the Detection
of Atmospheric Composition Change).

We confirm that IASI is able to measure tropospheric H2O profiles with a
vertical resolution of about 4 km and a random error of about 10%. In
addition IASI can observe middle tropospheric δD that adds
complementary value to IASI's middle tropospheric H2O observations. Our
study presents theoretical and empirical proof that IASI has the capability
for a global observation of middle tropospheric water vapour isotopologues on
a daily timescale and at a quality that is sufficiently high for water cycle
research purposes.

The Sofia University Atmospheric Data Archive (SUADA)Atmospheric Measurement Techniques, 7, 2683-2694, 2014Author(s): G. Guerova, T. Simeonov, and N. YordanovaAtmospheric sounding using the Global Navigation Satellite Systems (GNSS) is
a well-established research field in Europe. At present, GNSS data from 1800
stations are available for model validation and assimilation in
state-of-the-art models used for operational numerical weather prediction
centres in Europe. Advances in GNSS data processing make it possible also to
use the GNSS data for climatic trend analysis, an emerging new application.
In Bulgaria and southeastern Europe, the use of GNSS for atmospheric sounding
is currently under development.

As a first step, the Sofia University Atmospheric Data Archive (SUADA) is
developed. SUADA is a user-friendly database, and includes GNSS tropospheric
products like zenith total delay (ZTD) and derivatives like vertically
integrated water vapour (IWV), as well as observations from radiosonde (RS)
and surface atmospheric data. Archived in SUADA are (1) GNSS tropospheric
products (over 12 000 000 individual observations) and derivatives (over
55 000) from five GNSS processing strategies and 37 stations for the period
1997–2013, with temporal resolutions from 5 min to 6 h, and (2) radiosonde
IWV data (over 6000 observations) for station Sofia (1999–2012).

Presented are two applications of the SUADA data for the study of long- and
short-term variations of IWV over Bulgaria during the 2007 heatwave and
intense precipitation events in 2012.