Interactive comment on “ Ice phase in altocumulus clouds over Leipzig : remote sensing observations and detailed modelling ” by M . Simmel

Abstract. The present work combines remote sensing observations and detailed cloud modeling to investigate two altocumulus cloud cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather high temperatures of −6 °C. For comparison, a second mixed phase case at about −25 °C is introduced. To further look into the details of cloud microphysical processes, a simple dynamics model of the Asai-Kasahara (AK) type is combined with detailed spectral microphysics (SPECS) forming the model system AK-SPECS. Vertical velocities are prescribed to force the dynamics, as well as main cloud features, to be close to the observations. Subsequently, sensitivity studies with respect to ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity), whereas the ice phase is much more sensitive to the microphysical parameters (ice nucleating particle (INP) number, ice particle shape). The choice of ice particle shape may induce large uncertainties that are on the same order as those for the temperature-dependent INP number distribution.


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In contrast to other Asai-Kasahara model studies, updrafts are not initialized by a heat and/or humidity pulse in certain layers for a given period of time.Instead, :: As ::::::::: mentioned resulting in the time-and height-dependent function and w(h, t) = 0 otherwise, defining w mid (t) as the updraft 335 velocity at h mid .In order to match the observed wind field distributions rather closely, w mid (t) is chosen as a stochastic function where w ave is the average ('large-scale') updraft velocity at Due to the height dependent vertical velocity w, a horizontal transport velocity u k (exchange between inner and outer cylinder) is induced in the Asai-Kasahara formulation for a given model layer k.
) describe values at level interfaces.f r = 2/r i is a geometry parameter with the radius r i = 1000 ::::::: r i = 100 m of the inner cylinder.
The prescribed velocity field leads to the following effects 360 (all descriptions are related to the inner cylinder if not stated otherwise explicitly): -In the updraft phase: In the upper part (between h mid and h top ) of the updraft, mixing occurs from the inner to the outer cylinder whereas in the lower part (between 365 h low and h mid ), horizontal transport is from the outer cylinder into the inner one -For downdrafts it is the other way: This means that below h mid drops and ice particles are transported from the inner cylinder to the outer one and are therefore re-370 moved from the inner cylinder below h low or above h top , no horizontal exchange takes place.
The question arises to which extent this dynamical behaviour reflects the real features of the observed clouds and whether this is critical for the topics aimed at in this study.Prescribing vertical velocity in any way also means that a feedback of microphysics on dynamics due to phase changes (e.g., release of latent heat for condensing water vapor or freezing/melting processes) is not considered by the model.

Model results: Dynamics
In a first step, the aim is to achieve a sufficient agreement concerning macroscopic cloud features as well as (liquid phase) microphysics as far as they were observed.The following parameters describing model dynamics (updraft velocity) are varied to identify a 'best case' which in the second step can be used to perform sensitivity studies with respect to (ice) microphysics (see also Tables 1 and 2).
h low : ranging from 3800 m to 4100 m for the warmer and from 7000 m to 7300 m for the colder case.This parameter influences the vertical cloud extent and, therefore, liquid water content and liquid water path.
w ave : ranging from 0.1 m/s to 0.4 m/s.Higher average updraft also leads to higher LWC.Due to the lateral mixing processes the model setup requires a positive updraft velocity in average to form and maintain clouds.
δ: Four different realizations of the stochastic process are used.This influences the timing of the cloud occurence as well as LWC and LWP but not systematically.
All model results shown refer to the inner cylinder.
Figs. 11 (lower panel) and 12 (right) show that different realizations of the stochastic process (as explained above in section 3.2.1)lead to different temporal cloud evolutions.However, differences in maximum LWP and LWMR :::: LWC are much smaller than those discussed above.Variations in maximum IWP and IWMR :::: IWC : as well as CDN and IPN are in the range of about 30 %.This is also true for average LWP ranging from 18 g/m 2 for W r1 to 26 g/m 2 for W r3.However, despite the different maxima and temporal evolutions of IWP, average IWP is almost identical for the different stochastic realizations (0.023 g/m 2 ).This shows that changing the stochastic realization influences cloud evolution in detail (timing) but does not change the overall picture.
With maximum values between 17 and 57 g/m 2 the modeled liquid water path is in the same range as the observed values (20-50 g/m 2 ), especially for the 'wetter' runs (smaller h bot , larger w ave ).Average LWP typically is about half (40-60 %) of the maximum value for most of the runs which also fits well into the observations.Ice forms within the liquid layer and sediments to about 3800 m for most runs which is less than for the observations.The (maximum) modeled ice mixing ratio is in the same order of magnitude as the observed one (about 10 −7 kg/m 3 ).The same holds for the ice water path with values of about 0.01 g/m 2 for both, model and observation.For the other values, no observational data is available for comparison.

Sensitivity studies
In the previous section it could be shown that dynamical parameters can be chosen in a way that the model results (in terms of LWP, IWP as well as cloud geometry) are in good 540 agreement with the observations.This allows to perform sensitivity studies with respect to cloud microphysics.To cover the proper sensitivities we have to answer the question which microphysical parameters are expected to have a large influence on mixed phase microphysics and are rather uncertain ally is easier to observe in most cases.A second parameter is the shape of the ice particles which does not influence the primary freezing process but the subsequent growth by water vapor deposition onto existing ice particles and, therefore, the total ice mass produced.Their relative importance shall 555 be quantified and also be compared to the influence of dynamics discussed above.INP : number rises by about 65 % for a tenfold increase of N AP,r>250 nm .This shows that for those rather warm :::: high : temperatures consid-570 ered for case 1, a massive change in N AP,r>250 nm leads to relatively small changes in N IN ::::: N IN P : and only a small effect on the ice phase can be expected.This is confirmed by Fig. 17 (left) showing liquid and ice water mixing ratios ::::::: contents for W in6. Ice mass :::: IWC : is enhanced by less than 575 60 % for W in6 and by about 160 % for W in7 which is consistent for the given temperature range (see Tab. 3).Similar values are obtained for the change in IPN.This directly leads to the conclusion that the individual ice particles grow independently from each other.Their individual growth history is (in contrast to drop growth) only influenced by thermodynamics as long as their number is low enough which seems to be the case here.This is confirmed by Fig. 18 showing drop and ice particle size distributions at the time when the maximum IWP is 585 reached (16 min for case 1, 17 min for case 2).For case 1 (upper panel), the liquid phase (contours) is unaffected by the IN :::

IN
INP : enhancement.Despite the increase of ice particle number and mass the shape of the ice particle size distribution (colors) is not changed.The smallest ice particles can be observed at three discrete height (and temperature) levels caused by the temperature resolved parameterization of the potential IN ::: INP : described in section 3.1.1.In reality this part of the spectrum showing rather freshly nucleated and fast growing ice particles should be continuous over the 595 height range from about 4100 m to 4400 m.Nevertheless, the total number of ice particles formed is described correctly.
One can conclude that increasing IN ::: INP : number therefore increases ice particle number as well as ice mass proportionally.Generally, the ice mass remains small and the liquid phase is not affected by the ice mass increase.Those results are supported by Fig. 19 (left) showing an unchanged LWP and a proportionally growing IWP for increased IN ::: INP numbers.
For the colder case 2 the parameters are varied in the 605 same way.However, one big difference is that a tenfold increase of N AP,r>250 nm at T = −25 • C results in a much larger change in active IN ::: INP.Their number rises by 300 % from about 0.5 per liter to about 2 per liter following the parameterization.This is reflected by the IPN values in Table ::: Tab. 4. Fig. 17 (right) and Table ::: Tab. 4 show that ice mass increases in such a way that liquid water is depleted partially (C in6 by about 50 %) or almost totally (C in7) due to the Bergeron-Findeisen :::::::::::::::::::::::: Wegener-Bergeron-Findeisen process.Compared to C base, ice is enhanced by a factor of 3-4 for C in6 and about 10 for C in7 whereas IPN increases by a factor of 12.This can also be seen in the IWP (Fig. 19, right, red lines) showing a limited increase for C in7, especially for the first maximum after 17 min.This means that the results for C in6 are still consistent with an independent growth of 620 the individual ice particles (as described above) despite the relatively high ice occurence.This is verified by the size distributions in Fig. 18 (lower panel).As in case 1 the ice particle size distributions only differ by the number/mass, but not by shape.Additionally, the decrease in the liquid phase is reflected also in the drop spectrum showing a more shallow liquid part of cloud as well as droplet distribution shifted to smaller sizes.

Ice particle shape
As discussed previously, for most of the cases (except for C in7) changing the parameters in the section above does 650 neither influence the ice particles themselves nor their individual growth.Additionally, due to their low number, there is almost no competition of the ice particles for water vapor, and, therefore, ice water content scales linearly with ice particle number.In contrast to this, changing the ice parti-655 cle shape from quasi-spherical (ar=1) to columns or plates with size-dependent axis ratios deviating from unity results in an increase of water vapor deposition on the individual ice particles leading to enhanced ice water content due to larger individual particles when ice particle numbers remain 660 unchanged.This is due to (i) enhanced relative capacitance resulting in faster water vapor deposition and (ii) lower terminal velocities of the ice particles leading to longer residence times in vicinity of conditions with supersaturation with respect to ice.
665 Fig. 20 (left) shows the results for the runs using hexagonal columns (W col) as prescribed ice particle type.Compared to the previous results (W base, W in6, W in7) more ice mass is produced (see Table ::: Tab. 3) but still the liquid part of the cloud remains unaffected (compare also LWP and IWP in Fig. 19,left).Similar results are obtained for the assumption of plate-like ice particles (W pla).The mass increase results from the larger ice particle size due to the reasons discussed above which can be seen from Fig. 21 showing the size distributions for W col at different times.On the upper left panel 675 W col is shown after 16 min corresponding to Fig. 18.Compared to W base, larger ice particles are produced leading to more ice mass (equivalent radius up to 300 µm compared to 189-238 µm for the base case).Additionally, due to the lower fall speed of the columns (1.03 m/s vs. 1.75-2.24m/s), the 680 maximum of the ice is at about 4200 m compared to 4100 m for the base case.On the upper right panel, size distributions after 21 min are shown corresponding to the IWP maximum of W col. Ice particles have grown larger (equivalent radius up to 378 µm, length of the columns increases from about 3 mm to 4.5 mm) and sedimentation has developped further with increasing terminal velocity (1.13 m/s).Similar results are obtained for plates (W pla) with terminal velocities of 0.89-1.21m/s, equivalent radii of 300-476 µm and maximum dimension of 1.8-3.2mm.

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The lower terminal velocity of columns and plates despite their larger size is leading to the stronger tilting of the virgae.Additionally, ice particle number IPN is enhanced by about 30 % although ice nucleation is identical to W base.This can be attributed to the lower fall velocities, too, leading 695 to an accumulation of ice particles.The differences between W col and W pla are caused by both, the higher relative capacitances of and lower terminal fall velocities of plates compared to columns (at least when their axis ratios are chosen following Mitchell (1996)).
For case 2 (C col and C pla), the liquid water reduction due to the Bergeron-Findeisen process is similar to C in6 (see Fig. 20,right,and Table ::: Tab. 4).In contrast to the respective case 1 runs, less ice is produced than for C in7.The tilting of the virgae is not as strong as in W col which is 705 due to the larger ice particle sizes leading to higher terminal fall velocities (1.43-1.60 m/s).Additionally, the lower air density leads to an increase of terminal velocity of more than 10 % independently from shape.

Conclusions
The model system AK-SPECS was applied to simulate dynamical and microphysical processes within altocumulus clouds.Sensitivity studies on relative contributions on cloud evolution as well as comparisons to observations were made.
Variation of the dynamic parameters as it was done in section 4 leads to systematic differences mainly in the liquid phase (LWMR :::: LWC, LWP) which can easily be explained.

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More liquid water is produced when either cloud base is lowered (corresponding to a larger vertical cloud extent) or vertical wind velocity is increased.However, the effects of the dynamics on the ice phase are surprisingly small, at least smaller than those on the liquid phase.Increasing vertical ve-735 locity leads to an accumulation of the smaller ice particles in the enhanced updraft.
On the other hand, much larger differences in terms of IWMR :::: IWC : and IWP were found when microphysical parameters like IN ::: INP number or ice particle shape were var-740 ied under identical dynamic conditions.This is valid for both cases studied.However, at least for the ice nucleation parameterization used, sensitivity of IN ::: INP : number strongly increased with decreasing temperature.This means that relatively large differences concerning 745 the ice phase can only be reached when either IN ::: INP number differs considerably or ice particle shape is different (which should not be the case for relatively similar thermodynamical conditions).After Fukuta and Takahashi (1999) for case 1 with temperatures of about −6 • C 750 column-like ice particles with ar = 0.1 could be expected (corresdponding ::::::::::: corresponding : to W col) whereas for case 2 (T < −24 • C : ) : hexagonal particles with ar = 1 are most likely (e.g., C base).Those ice shapes were observed in laboratory studies at water saturation which was also valied decreases.: These ice shapes can also explain why a depletion of the liquid phase was not observed in case 2 as it 760 was predicted by the sensitivity studies using either columns or plates as prescribed shape.Generally, the liquid phase is affected considerably only when enough ice particles are present which typically is the case for cold conditions with a sufficient amount of IN   Cloudnet ::::::: derived :::: water ::::::: contents : for case 1. Left: derived from radar observations (valid for large particles; virgae) ::::: Liquid :::: water :::::: content, right: :: ice ::::: water :::::: content :::: (both :: in :::::::: logarithmic :::::: scale).Vertical velocity for case 2, derived from radar observations.contours) and ice water mixing ratio :::: IWC (contours ::::: colors, logarithmic scale).Results for changing ice particle shape to hexagonal columns for case 1 (W col, left) and case 2 (C col, right).contours) and ice water mass per bin (contours ::::: colors, ::: both logarithmic scale) for case 1 (upper panel) and case 2 (lower panel) assuming columns as ice particle shape at IWP maximum of the respective base case (left) and at IWP of the run (right).

Fig. 8 .
Fig.8.Vertical velocity field of the inner cylinder for case 1. Left: Height dependence (red line) and temporal evolution of one realization of the stochastic vertical velocity field (black line) for wave = 0.3 m/s at h mid .Right: Histogram of velocity field.Vertical velocity for case 2 is identical but for heights between 7100 m and 7700 m.

Fig. 12 .
Fig. 12. Liquid (lower panels) and ice water paths (upper panels) for case 1.Comparison of the different values for wave (left) and the different stochastic realizations (right).

Fig. 16 .
Fig. 16.Liquid (lower panels) and ice water paths (upper panels) for case 2. Comparison of the different values for wave (left) and the different stochastic realizations (right).

Fig. 19 .
Fig. 19.Liquid (lower panel) and ice water paths (upper panel) for case 1 (left) and case 2 (right).Comparison of the sensitivities with respect to IN number and ice particle shape.
The center of this interval is given by h mid = (h top + h bot )/2 and its half-depth by h depth = (h top − h bot )/2.h bot ranges from 3800 m to 4100 m for case 1 and from 7000 m to 7300 m for case 2. The respective values for h top are 4500 m and 7700 m.The vertical dependency(compare Fig. 8, left) ::::: above, : vertical velocity (updrafts and downdrafts) in the in-ner cylinder is prescribed at cloud level ranging from h bot to 325 h top .330 is given by

Table 2 .
Overview of the model results for the dynamic sensitivity runs for the colder case 2 (maximum values of L/IWMR :::: IWC: liquid/ice water mixing ratio :::::: content, L/IWP: liquid/ice water path, CDN: cloud drop number, IPN: Ice particle number).

Table 3 .
Overview of the model results for the microphysical sensitivity runs for the warmer case 1 (maximum values of L/IWMR :::