Clouds have an important role in Earth's radiative budget. Since the late 1970s, considerable instrumental developments have been made in order to quantify cloud microphysical and optical properties, for both airborne and ground-based applications. Intercomparison studies have been carried out in the past to assess the reliability of cloud microphysical properties inferred from various measurement techniques. However, observational uncertainties still exist, especially for droplet size distribution measurements and need to be reduced.
In this work, we discuss results from an intercomparison campaign, performed at the Puy de Dôme in May 2013. During this campaign, a unique set of cloud instruments was operating simultaneously in ambient air conditions and in a wind tunnel. A Particle Volume Monitor (PVM-100), a Forward Scattering Spectrometer Probe (FSSP), a Fog Monitor (FM-100), and a Present Weather Detector (PWD) were sampling on the roof of the station. Within a wind tunnel located underneath the roof, two Cloud Droplet Probes (CDPs) and a modified FSSP (SPP-100) were operating. The main objectives of this paper are (1) to study the effects of wind direction and speed on ground-based cloud observations, (2) to quantify the cloud parameters discrepancies observed by the different instruments, and (3) to develop methods to improve the quantification of the measurements.
The results revealed that all instruments showed a good agreement in their
sizing abilities, both in terms of amplitude and variability. However, some
of them, especially the FM-100, the FSSP and the SPP, displayed large
discrepancies in their capability to assess the magnitude of the total
number concentration of the cloud droplets. As a result, the total liquid
water content can differ by up to a factor of 5 between the probes. The use
of a standardization procedure, based on data of integrating probes (PVM-100
or visibilimeter) and extinction coefficient comparison substantially
enhanced the instrumental agreement. During this experiment, the total
concentration agreed in variations with the visibilimeter, except for the
FSSP, so a corrective factor can be applied and it ranges from 0.44 to 2.2.
This intercomparison study highlights the necessity to have an instrument
which provides a bulk measurement of cloud microphysical or optical
properties during cloud ground-based campaigns. Moreover, the FM and FSSP
orientation was modified with an angle ranging from 30 to
90
The cloud droplet size distribution is one of the key parameters for a quantitative microphysical description of clouds (Pruppacher and Klett, 1997). It plays an important role in the radiative characteristics of clouds and, for example, is needed to assess the anthropogenic influence on the size and number concentration of cloud droplets (Twomey, 1974, 1977) and on the cloud lifetime (Albrecht, 1989). Moreover, the knowledge of droplet size distribution is crucial for a better understanding of the onset of precipitation (Kenneth and Ochs, 1993) and the aerosol–cloud interaction (McFarquhar et al., 2011). According to Brenguier et al. (2003), aerosol–cloud interaction studies need accurate assessment of the cloud microphysical properties such as liquid water content (LWC), concentration and effective diameter. The representation of liquid stratiform clouds in current climate models is relatively poor, leading to large uncertainties in climate predictions (Randall et al., 2007). Radiative, dynamic and feedback processes involved in liquid clouds still need to be studied (e.g., Petters et al., 2012; Bennartz et al., 2013; Boucher et al., 2013) and thus require accurate measurement instrumentation. In-situ measurements may be directly used for model validations, or to improve and validate remote sensing, radar and lidar retrieval algorithms.
A large number of instruments have been developed since the late 1970s to attempt to obtain precise information on cloud microphysical and optical properties. Two strategies are mainly used to measure in situ properties of clouds. The first one consists of mounting instruments under the wings of an aircraft that flies within the cloud (Gayet et al., 2009; Baumgardner et al., 2011; Brenguier et al., 2013), and the second one consists of instruments operated on a ground-based platform, generally on a mountain site, whose the altitude allows sampling natural clouds (Kamphus et al. 2010; Hoyle et al., 2015).
Generally speaking, cloud in situ probes fall into two categories: single particle counters (SPCs) and ensemble-of-particles probes (EPP). The later ones measure laser light scattered by an ensemble of droplets passing through the sample volume of the probe (see e.g, Gerber, 1984, 1991; Wendisch et al., 2002). The main measurement principle for the size detection used in most of these devices is based on a conversion of the forward scattering of light into a size bin using the Lorentz–Mie theory (Mie, 1908). However, despite significant technical progress, previous intercomparison studies showed that in situ measurements of cloud particles are still subject to a wide range of biases, uncertainties and limitations (see for instance, Baumgardner, 1983; Gerber et al., 1999; Burnet and Brenguier, 1999, 2002; Lance et al., 2010; Spiegel et al., 2012). The main problems are the assessment of the sampling volume and the impact of the wind speed and direction on ground-based measurements.
Lance et al. (2010) used glass beads to study the calibration accuracy of
the Cloud Droplet Probe (CDP). They found that the calibration was
consistent with the theoretical instrument response provided by the
manufacturer. On the other hand, laboratory experiments with water droplets
originated from a piezo-electric drop generator showed a 2
Therefore, although studies comparing cloud properties derived from different methods or instrumentations exist, there is still a need for detailed comparison studies under variable sampling conditions, in order to derive robust standardization and potential corrections of the measurements. Moreover, as Brenguier et al. (2013) concluded, it is still of crucial importance to perform liquid water–cloud instrumental comparison with ground-based experiments.
The research station located on the Puy de Dôme, in central France, is
an ideal place for intercomparison studies of cloud microphysical
measurements. The station is in clouds approximately 50 % of the time on
average (annual mean). The station consists of a platform on the roof, where
ground-based instrumentation can be installed, and a wind tunnel facing the
dominant western winds used to sample air masses at air speeds up to 55 m s
Section 2 of this paper presents the measurement site and the instrumentation used during the campaign. Section 3 addresses the comparison of the data recorded with the ground-based and the wind tunnel instruments. A proposed method to correct and standardize these measurements is outlined. Main causes of potential biases and effects of the wind direction and speed are then discussed. Section 4 summarizes the main results and conclusions of this study.
The cloud microphysics instrumental intercomparison was performed at the
Puy-de-Dôme atmospheric measurement station (PUY, 45.46
The PUY station is located on the top of an inactive volcano at an altitude
of 1465 m rising above the surrounding area, where fields and forest are
dominant. The main advantage of the site is the high frequency of the cloud
occurrence (50 % of the time on average throughout the year). Westerly and
northerly winds are dominant. Meteorological parameters, including the wind
speed and direction, temperature, pressure, relative humidity and radiation
(global, UV and diffuse), atmospheric trace gases (O
The ROSEA intercomparison campaign took place from 16 to 28 May 2013 (see Table 1 for the details). Eleven cloudy episodes
were sampled, each for several hours. Temperatures were always positive,
thus preventing freezing from affecting the measurements. The wind
parameters were measured with a Vaisala sonic anemometer and a vane
anemometer. Typically, the weather conditions were dominated by westerly
winds with speeds ranging from 1 to 22 m s
Data availability for each instrument used during ROSEA.
A number of instruments were operated simultaneously on the PUY station roof
top sampling platform and in the wind tunnel, providing a description of
cloud droplets with diameters ranging from a few micrometers up to 50 Size resolution limits due to Mie resonance: since the same scattered energy can match
with several particle sizes, the sizing resolution is limited. For this reason, the cloud
particle sizing has an uncertainty of one size bin, which corresponds to values between 2
and 3 Electronic delays: the dead time, necessary for the electronic system to treat the
data has to be taken into account for some SPCs. The sampling duration Coincidence: it occurs when two or more droplets are in the sampling volume at the
same time. It is thus strongly concentration dependent and is the most important uncertainty
for high concentrations. Splashing and shattering: during in-flight experiments, a particle can be broken on
the inlet and results in a false increase in smaller droplets. The uncertainty associated
with splashing/shattering is low for measurements in clouds having small droplets. Particle velocity: the TAS is approximated by the speed of droplets passing through
the laser beam. Uncertainties in droplet velocity lead to errors in the computation of the
sampling volume. Changing velocity acceptance ratio (VAR) (Wendisch, 1998): this stems from the fact
that only a part of the laser beam diameter is used to calculate the sampling volume because
drops passing the laser beam near its edges are undersized. Theoretically, by electronic
procedure consisting in a threshold in the transit time, only 62 % of the laser beam
diameter is used to accept a particle. This value has to be taken into account in the
sampling-surface calculation and it can change with time. Thus, the VAR has to be
measured and the actual value has to be used in the data processing. Sampling volume assessment: this is affected by errors in the sampling speed,
the laser width, and the depth of field (DOF). Usually, all these errors are very difficult
to quantify and extreme uncertainty can be very high. For example, Burnet and
Brenguier (2002) reported that the DOF of the FSSP could be significantly
different from the value given by the manufacturer; this difference may reach a factor 2.
The SPCs used during the intercomparison campaign are a Forward Scattering
Spectrometer Probe (PMS FSSP-100), a Fast FSSP (SPP-100), a Fog Monitor (DMT
FM-100) and two Cloud Particle Probes (DMT CDP).
The Forward Scattering Spectrometer Probe (FSSP-100) initially manufactured
by Particle Measuring Systems (PMS), Inc. of Boulder, Colorado is the oldest
instrument still in use for measuring cloud droplet size distribution. It
uses a laser at the wavelength of
The SPP-100 is a modified model of the FSSP-100 (manufactured by Droplet Measurement Technologies DMT, Inc., Boulder, USA) with 40 size bins and a revised signal-processing package (fast-response electronic components). Brenguier et al. (1998, 2011) have shown that the SSP-100 noticeably improves the accuracy of the size distribution assessment compared to the FSSP-100 version. The electronic system of the SPP-100 is fast enough to neglect the electronic delay; but the data processing still needs regular VAR corrections.
The Fog Monitor (FM-100) is a Forward Scattering Spectrometer Probe
(
The CDP is a forward-scattering optical spectrometer (
The second type of instruments used during the intercomparison campaign is the ensemble-of-particles probes (EPP). These instruments sample a large number of particles and measure bulk-average parameters. Particle size distributions are not available. The EPP instrumentation of the campaign was composed of a Particle Volume Monitor (PVM-100) and a Present Weather Detector (PWD-22).
The Particle Volume Monitor (PVM-100, manufactured by Gerber Scientific,
Inc., Reston, Virginia) is a ground-based forward-scattering laser
spectrometer for particulate volume measurements (Gerber, 1984, 1991). It is
designed to measure the LWC, the particle surface area (PSA) and to derive the
droplet effective radius (
The Present Weather Detector (PWD22) is a multi-variable sensor for
automatic weather observing systems. The sensor combines the functions of a
forward scatter visibility meter and a present weather sensor. PWD22 can
measure the intensity and the amount of both liquid and solid precipitation.
As the detector is equipped with a background luminance sensor, it can also
measure the ambient light (Vaisala, 2004). This instrument provides the
visibility or Meteorological Optical Range (MOR), which is a measure of the
distance at which an object or light can be clearly discerned and from which
we can deduce the extinction coefficient
The FSSP-100, the FM-100, the PWD and the PVM-100 were operated on the roof of the station, at approximately 2 m above the platform level (see Fig. 1a). The FSSP and the FM-100 were mounted on a tilting and rotating mast, allowing them to be moved manually in the dominating wind direction. The proper alignment of their inlet with the flow was based on the wind direction measurements performed by a mechanical and ultrasonic anemometer placed on a separate mast fixed on the terrace of the PUY station. The data availability of these instruments is shown in Table 1.
In addition to the continuous measurements performed on the roof of the
station, the PUY research station is also equipped with an open wind tunnel
located on the west side of the building. The wind tunnel consists of a sampling section, 2 m in length, with an adjustable airflow up to
17 m
During the campaign, instruments collected data at a frequency of 1 Hz. In order to synchronize measurements from multiple instruments, data have been averaged over 10 s or 1 min. The length of the averaging time depends on the duration of the experiment, and cloud heterogeneity. The PVM measurements are provided with routine protocol which averaged data over 5 min; thus any comparison with this instrument has to be carried out with 5 min average data. The FSSP shows incoherent measurements from 23 to 26 March, probably due to electronic interferences. An overview of the data availability during the campaign is shown in Table 1. The SPCs were calibrated in size using glass beads, between the 22 and 29 April 2013 before the campaign, and between the 8 and 30 November 2013 after the campaign. The EPPs were calibrated using opaque disk a few days before the beginning of the campaign. The data unavailability is caused by the absence of experiments in the wind tunnel and instrumental problems on the roof. A summary of the instrument characteristics, with uncertainties in normal and extreme conditions, is reported on Table 2.
The purpose of this section is to give an overview of the microphysical measurement strategy performed during the campaign with a focus on the instrument variability. During the 16 May a large number of instruments were deployed simultaneously on the station platform and in the wind tunnel (see Table 1).
Instrumental set-up during the ROSEA intercomparison campaign at the Puy-de-Dôme. Uncertainties in normal and extreme conditions are presented. Reff is the effective radius.
Figure 2 provides an example of the temporal evolution of the parameters
measured the 16 May. On this graph, we choose to represent only
the time series of the cloud properties averaged over 10 s when the
wind tunnel was actually functioning. According to Table 1, the PVM did not
properly function on this particular day. The wind speed outside and inside
the wind tunnel is shown in Fig. 2a. The outside wind speed varied from 2
to 7 m s
The values and the variability of the effective diameter measured by the instruments are in good agreement with a correlation coefficient close to 0.9 (Fig. 2b).
Time series of the 16 May experiment of the main measured
parameters:
Although the microphysical properties' variability is well captured by all
the instruments (correlation coefficient close to 0.9), the temporal
evolution of the number concentration exhibits systematic differences among
the instruments (Fig. 2c). The number concentration measured by the FM-100
is systematically lower than that one derived from the other instruments,
while the FSSPs (SPP and FSSP-100) show the highest values. The ratio
between the concentration measured by the FM and the FSSPs reaches values up
to 5. As for the CDPs installed in the wind tunnel, the concentration
measurements lie between the values obtained by the FSSPs and the FM-100.
The two CDPs have a ratio of 1.35 and the CDP 1 has values close (ratio of
1.6) to those of the FM-100. Similarly, the LWC and extinction coefficient
values show significant discrepancies. The measured cloud droplet
extinctions vary up to a factor of 2.5 (FSSP) and 0.55 (FM-100) compared to
the PWD. The bias between the instruments is potentially very important (up
to 5 when comparing the FSSPs extinction to the FM-100). However, the
temporal variability of the data shows good correlation(
The red-framed parts of the time series displayed in Fig. 2 correspond to additional experiments where the orientation of the instruments on the mast was changed (the FM-100 and the FSSP). Those orientation changes lead to a sudden decrease of all the microphysics parameters of the instruments installed on the mast, especially of the FSSP. The data corresponding to those orientation experiments are removed for the following analysis and will be discussed in the Sect. 3.4. On the example of 16 May, we observe that the differences in concentrations measured with different probes seem to vary, and may be a function of wind speed and direction.
This example illustrates that the probes' adequate sizing of cloud droplets is subject to a systematic bias when particle counting (number concentration) is involved. This can be clearly seen in Fig. 3 where the average particle size distributions (PSDs) in concentration, surface and LWC measured by the different spectrometer probes are displayed. It should be noted that these average PSDs were obtained when the probe orientations were coaxial with the wind direction. The PSDs in number is a good indicator of the small droplets concentration while the PSDs in surface and volume are more representative of droplets with intermediate and large sizes, respectively.
The PSDs show similar trends and shapes, with size modes from 10 to 14
Averaged size distribution in concentration, with
In this section, we focus on measurements performed in the wind tunnel and on the roof of the station when the wind was isoaxial to the sampling probes inlets, over the whole campaign. Microphysical changes, due to the orientation of the instruments, observed in Fig. 2, will not be analyzed here. The data are averaged over 10 s for the wind tunnel measurements and over 1 min for ambient conditions in order to make the measurements comparable (see Sect. 2.3).
Figure 4 displays the scatter plots of the effective diameter for the
instruments deployed on the PUY platform. The dashed lines show the
uncertainties applied to the linear fit; the errors considered for each
instrument are given in Table 2 for normal conditions. There is a good
agreement between the FM-100 and the FSSP with a high linear correlation
coefficient value (
The comparison between the number concentrations measured coaxially to the
wind direction by the FSSP and the FM-100 over the whole campaign is
displayed in Fig. 5. The concentration measurements are slightly less
correlated than the effective diameter measurements but the correlation
remains acceptable (
A comparison between the 5 min averaged extinction coefficients measured
by the PVM and the PWD, two instruments that do not need active ventilation,
is shown in Fig. 6. There is a good agreement (
One minute averaged concentration in cm
Scatter plot of the PWD and PVM 5 min average extinction coefficients. The bold dashed lines show the instrumental errors applied to the fit. The 99 % confidence interval of the slope value was estimated to be [1.156, 1.184].
Therefore, the fact that there is a systematic constant bias (factor of 6 in Fig. 5) in the intercomparison of the droplet number concentration and of the LWC, measured by the different probes, could be indicative of the inaccurate assessment of the probe sampling volume directly linked to the air flow speed measurement accuracy. In order to discuss this issue, the measurements performed under ambient conditions are compared with the measurements in the wind tunnel where the sampling speed is recorded more accurately than in ambient air.
Figure 7a presents the results of the effective diameter as the
intercomparisons for the three instruments installed in the wind tunnel.
Good agreement is observed among the probes, with correlation coefficients
The measured droplet concentrations (Fig. 7b) also show high correlation
coefficients (
Scatter plots of the 10 s averaged concentrations measured by the FM-100 (left) and the FSSP (right), in ambient conditions, with the wind tunnel SPP. The colors reveal the ambient wind speed. The bold dashed lines show the instrumental errors applied to the fit. The 99 % confidence interval of the slope value was estimated to be [0.251, 0.269].
The bias between the instruments results from systematic errors of the assessment of the sampling volume. The single particle counters (SPCs) have uncertainties in optical parameters such as the DOF and in corrections like the activity. In addition, the data of the ground-based FM and FSSP are affected by errors of the sampling speed assessment. In order to evaluate the consistency of measurements performed in ambient air (on the mast) with those performed in a wind-controlled environment, we characterized the relative sensitivity of the droplet concentration measurements to different wind speeds. As already discussed, all the instruments in the wind tunnel are very well correlated. Since only the slope of the linear regression differs from one instrument to another, we chose to compare the FSSP and the FM-100 sampling on the roof, with the SPP100 sampling in the wind tunnel. These instruments are based on the same measurement principle.
Figure 8 displays the scatter plots of the number concentration measured by
the instruments on the mast against the SPP observations performed during
the four wind tunnel experiments (the 16, 22, 24 and
28 May with the 10 s average measurements). The
concentrations measured by the FM-100 are well correlated to the SPP
observations even though the wind speeds are quite different, ranging from 2
to 21 m s
However, the 10 s average FSSP measurements exhibit a high variability and show no correlation with the SPP observations. Both, the inter- and intra-experiment variability is significant, meaning that correction of global data is not possible. Additionally, due to some instrument data availability (see Table 1), the correlation plots relative to the FSSP and the FM-100 are not directly comparable. The 24 May experiment is not available for the FSSP but shows a large variability in concentration, which results in an increase in the correlation of the FM-100 compared to the FSSP. However, as the FM-100 was designed for ground-based measurements, it is not surprising that the FM-100 measurements are more in agreement with the other instruments of the wind tunnel than the FSSP. On the contrary, anisokinetic sampling of the FSSP leads to higher discrepancies when this instrument is compared to other ones.
The droplet diameter and concentration intercomparisons show that the uncertainties linked to the calibration and to the calculation of the sampling volume lead to systematic biases similar to the measurement of concentration, extinction and LWC. The agreement observed between the FM-100, the SPP and the CDP measurements indicates that these data could be standardized on the basis of a reference instrument, with a simple relation of proportionality that would be valid for the entire campaign. However, particular attention should be addressed to the FSSP measurements which were shown to be sensitive to wind conditions. Therefore, the remainder of this study will focus on the standardization of the results, on biases correction for isoaxial measurements as well as on the study of the effect of the air speed (wind speed or suction in the wind tunnel) on the measurements.
To summarize this section, the comparisons showed good correlations between the deduced parameters, that is, good sizing for all the instruments. At the same time, the instruments displayed large discrepancies in their capability to assess the cloud droplet number concentrations. As the FSSP is aspirated with no flow straightener in front of it, turbulent flow and distortion of the size distributions can be expected. Anisokinetic sampling and errors in the sampling volume can explain the concentration overestimation. For the other instruments, the biases were constant during the campaign and independent of the wind speed and the droplet size (not shown). They are attributed to the assessment of the sampling volume. This includes errors in the sampling speed, the laser width and the DOF. The listed uncertainties are very difficult to quantify and they can reach rather high values. Thus, it seems to be a more productive approach to correct the measured data without computation of all the errors related to the sampling volume. The approach is discussed in the following section.
The instrument concentration biases observed in Sect. 3.2 lead to the need to standardize the recorded data. The most natural way is to standardize the measurements with instruments which are not based on single particle counting but on the measurements of an ensemble of particles (i.e., from an integrated value). Such measurements are performed by the PVM-100 and the PWD.
Since good agreement was found between the extinction coefficients measured by the PVM and the PWD (Fig. 6), these two instruments can be used as absolute reference of the extinction of cloud particles. As the PWD was the only instrument working during the entire campaign, all recorded data are standardized according to this instrument. Hence, the data of other instruments were averaged over 1 min according to the PWD time resolution.
Figure 9 presents the comparison between 1 min averaged PWD extinctions
and the data obtained in the wind tunnel for all the experiments, as a
function of the wind tunnel air speed. The results show good correlations
(
One minute averaged SPP, CDP 2 and CDP 1 extinctions, compared with the PWD extinction for the four wind tunnel experiments. The air speed applied in the wind tunnel is shown on the color bar. The bold dashed lines show the instrumental errors applied to the fit. The confidence intervals with a confidence level of 99 % are given in square brackets.
One minute averaged
In a similar way Fig. 10 presents the comparison of the PWD extinctions
with the instruments placed on the mast during the campaign, as a function
of the external wind speed (right panels). The FM-100 and PWD measurements
are correlated, even though the FM-100 extinction is underestimated by a
factor of 2 compared to the PWD reference measurements. This factor is of the
same order of magnitude as the bias found when comparing the PWD to the
instruments positioned in the wind tunnel (Fig. 9). On the other hand, Fig. 10 shows only a poor correlation between the FSSP and the PWD extinction
coefficient measurements. Additionally, the wind speed seems to have an
influence on the FSSP measurements. Several points, corresponding to low
wind speeds, show a large overestimation of the extinction measured by the
FSSP. Removing the data corresponding to a wind speed lower than 5 m s
Table 3 presents the summary of the instrumental intercomparison during the
ROSEA campaign in terms of the instrumental bias (slope
Appendix A presents experiments devoted to the assessment of the particle
speed inside the FSSP inlet as a function of the wind and suction speed. To
summarize briefly, the variations of the particle transit speed was found to
not directly depend of the suction speed of the pump. Our measurements
showed that the ramming effect (Choularton et al., 1986) was not
significant. However, it is shown that the inertial concentration effect
(Gerber et al., 1999) can be significant. In addition, average transit speed
was found to be dependent of the droplets diameter (see Fig. 13a), with a
larger dispersion for small particles (
Up to now we have investigated the coherence of performed measurements using the different probes sampling isoaxially to the main wind stream and showed a way to correct and standardize the data. In the following section, we will investigate the effect of non-isoaxial sampling on the measurements.
FSSP
In this section we focus on experiments where the mast was oriented in different directions with respect to the main wind stream. Each position was maintained during 5 min and the orientation was regularly moved back and forth to an isoaxial position to check if the cloud properties remained unchanged during the experiment. Four measurement series were carried out during 22 May. The wind was blowing west all day long and the cloud properties were rather stable. Despite the sampling anisotropy of the FSSP, the orientation experiments for a given wind speed are reliable.
Summary of the cloud extinction coefficient intercomparison
performed during ROSEA. The coefficient
FSSP concentration loss in percentage compared to the
isoaxial measurement concentration, as a function of the wind speed and the
angle between wind direction and instrument orientation. For each angle and
wind speed value, this percentage is computed for the entire size range (2
to 45
FSSP size distribution averaged for each angle
Figure 11 presents the temporal evolution of the FSSP and FM-100 size
distributions along with the wind speed and the deviation angle between the
instrument orientation and the wind direction. First, for the measurement
with an angle equal to 0
The impact of the combination of both wind speed and direction on the
probe's efficiency to sample cloud droplets is clearly illustrated in Fig. 12, which shows the cloud droplet size distribution, averaged for each angle
Same as Table 4, for the FM-100.
However for a wind speed of approximately 3 m s
Table 5 shows the results for the FM-100. For the same wind speed and
direction, the values of the FM-100 concentration loss are systematically
lower than for the FSSP. This means that the FM-100 undergoes a weaker loss
of measured particles when the instruments are not facing the wind. The
variations of the FM-100 concentration loss with the wind speed and the
angle are less obvious than variations of the FSSP. Moreover, the amplitude of these
variations is much weaker than for the FSSP, with a minimum of 15 % and a
maximum of 68 %. This confirms that the FM-100 is less sensitive to the
wind speed and orientation than the FSSP-100. The experimental data
presented in Table 5 corroborate with the modeling results by Spiegel et al. (2012) who investigated the particle losses caused by increasing sampling
angle for the wind-velocity range from 0.5 to 6.2 m s
SPP average transit time as a function of the ambient wind
speed
Accurate measurements of cloud microphysical properties are crucial for a better understanding of cloud processes and their impact on the climate. A large number of cloud instruments have been developed since the late 1970s. However, accurate comparisons between instruments are still scarce, in particular comparisons between ground-based and airborne sampling conditions. To address this problem, we performed intercomparisons of both ground-based and wind tunnel measurements performed with various instrumentations during the ROSEA campaign at the station of the Puy-de-Dôme (central France, 1465 m a.s.l.) in May 2013. This instrumental intercomparison includes a FSSP, a Fog Monitor 100, a PWD and a PVM-100, used during ground-based conditions, and two CDPs and a SPP-100 used in the wind tunnel.
Extinction ratio between the FSSP and the PWD as a function of effective radius of cloud droplets and ambient wind speed during the ROSEA campaign.
Our results show very good correlations between the measurements performed by the different instruments, especially, for the shape of the size distribution and the effective diameter values. Absolute effective diameter values show good agreement within the 10 % average instrument uncertainty, however total concentration values can diverge up to a factor of 5. This result can be explained by the errors in the sampling volume and speed. Comparisons between ground-based and controlled wind measurements show good correlations. However the concentration values biases still remain. As all the uncertainties are often difficult to assess, we thus propose to standardize data with a PWD. This is a reliable instrument, which does not use a sample volume. The data were normalized based on the bulk extinction coefficient measurements performed by the PWD. Except for the FSSP, the results show that the measurements do not depend significantly on the air speed (wind speed or wind tunnel suction speed) or droplet size. Moreover, the measurements can be standardized with a simple relation of proportionality, with a coefficient comprised between 0.43 and 2.2, which is valid for the entire campaign. This is not applicable to the ground-based FSSP measurements which showed anisokinetic sampling and a high sensitivity to the wind speed and direction. Indeed, data from these measurements are highly variable when the wind speed was lower than the theoretical air speed through the inlet. The overestimation of extinction measured by the FSSP, compared to the PWD, showed agreements with the Gerber et al. (1999) study, which highlights the inertial concentration effects.
Moreover, as the FSSP and the FM were installed on a mast, which can be
oriented manually; this system allowed us to highlight the effect of an
increasing angle between instrument orientation and wind direction on the
FSSP and Fog Monitor data. The mast orientation was modified with an angle
ranging from 30 to 90
Finally the high dispersion of the ground-based FSSP measurements compared to the other instruments is explained as follows. The transit speed of droplets in the FSSP sampling volume was investigated using the SPP measurements on the mast. The ground-based SPP observations showed a strong variability in the transit speed of the cloud droplets. This variability did not depend on the variations of the pump aspiration or the wind speed. As this effect was more pronounced for small particles, the concentration effect of the mean flow and the presence of turbulent flow inside the FSSP inlet could be a plausible explanation of the discrepancies of the measurements based on particle counting.
In order to investigate the influence of the wind speed on the FSSP response, three additional experiments were performed with the SPP-100 installed on the mast along with the FSSP (from 13 to 15 November 2013).
The SPP has an internal estimation of the droplet speed within the sampling
volume: the so-called transit speed. We maintain that ideally the transit
speed through the laser beam should be the same as the SPP sampling speed.
In addition, this also allows us to estimate the values and the variations
of the sampling volume, needed in the computation of the concentration, when
assuming that the air speed is close to the particle speed. The SPP was
installed in the position of the FSSP. Its theoretical sampling speed in the
instrument's inlet is 9 m s
Over the period of 13–15 November, the wind speeds ranged
from 0 to 15 m s
In order to explain the variations of the SPP transit time, it can be
compared to the wind speed and the pumping speed. Figure 13 presents the
comparisons of 1 min averaged data. In the Fig. 13a, the effective
diameter measured by the SPP is also shown on the color bar. We observe that
the SPP transit time is not dependent on the wind speed. It should be
pointed out that the effective diameter values higher than 20
Choularton et al. (1986) compared the FSSP volume sampling rate
This ramming effect was not observed during our November 2013 experiments.
First, the sampling air speed within the FSSP inlet was higher than expected
(
Gerber et al. (1999) compared the LWC measurements of the FSSP and the
PVM-100 during ground-based experiments. This study highlights the need of
accurate ambient wind speed measurements and information on instrument
orientation with respect to the wind direction. In addition, this study
suggests that the FSSP overestimates the concentration due to the droplet
trajectories inside the flow accelerator when the ambient air speed is
inferior to the velocity near the position of the laser. A simple trajectory
model was used to understand if the suction used to draw droplets into the
sampling tube of the FSSP can cause changes in the droplet concentration at
the point where the laser beam interacts with the droplets. The modeling was
performed for a sampling velocity of 25 m s
To compare our results with Gerber et al. (1999), Fig. 14 displays the
ratio between the FSSP and PWD extinctions as a function of the effective
radius provided by the FSSP and the wind speed, for the entire ROSEA
campaign. The lowest values of the PWD extinction were removed in order to
avoid unrealistic ratio values. The ratio of extinction or LWC (used in
Gerber et al., 1999) is the same within the hypothesis that it is due to an
inaccurate assessment of the sampling volume. As we selected the PWD as the
reference instrument, this ratio is similar to the enhancement factor
Thus, a relatively good agreement is observed between the inertial concentration effect shown by Gerber et al. (1999) and our results. As a consequence, we have indications which tend to show that the FSSP measurements with a wind speed that is too low have to be removed if the variations do not correlate with data of other instruments.
This work was performed within the framework ROSEA (Réseau d'Observatoires pour la Surveillance et l'Exploration de l'Atmosphère) and ACTRIS (Aerosols, Clouds and Trace gases Research Infra Structure Network). It was also supported by the French ANR CLIMSLIP. The authors are grateful to the OPGC (Observatoire de Physique du Globe de Clermont) for monitoring at the PdD station and Evelyn J. Freney, D. Baumgardner, C. Towhy and H. Gerber for their help in improving the manuscript. G. Guyot is grateful to Conseil Général de l'Allier for the financial support of his work. Edited by: P. Herckes