Comparing Model and Measured Ice Crystal Concentrations in Orographic Clouds During the INUPIAQ Campaign R

Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , 1 1 , M. J. Flynn 1 . Previous literature has pro- 1 − L 3 , and T. W. Choularton , K. N. Bower 1 1 25648 25647 , G. Lloyd 1 , C. Dearden 2,3 , P. R. Field , P. J. Connolly 1 1 ce, Exeter, UK ffi This discussion paper is/has beenand under Physics review (ACP). for Please the refer journal to Atmospheric the Chemistry corresponding final paper in ACP if available. School of Earth, Atmospheric and Environmental Sciences, The UniversityMet of O Manchester, ICAS, University of Leeds, Leeds, UK Abstract This paper assesses the reasonsgraphic for clouds high by ice comparing numberInvestigation concentrations in-situ And observed measurements in Quantification from oro- field theland campaign (3570 Ice ma.s.l.) (INUPIAQ) NUcleation with at Process thetions Jungfraujoch, over Weather real Research Switzer- terrain and surrounding Jungfraujoch. Forecastingbetween During model the the (WRF) 2014 20 winter simula- field January campaign, dicted and the 28 observed February, ice the number model concentration simulations by regularly 10 underpre- and cloud microphysics all influence the lifetime and extent of orographic clouds, as 1 Introduction Orographic clouds, and the precipitation theybetween produce, the play a atmosphere key and role the in land thement surface relationship (Roe, of2005). each The orographic formation and cloudflow develop- event over varies the considerably. Variations orography, the in size the large-scale and shape of the orography, convection, turbulence 1 Manchester, UK 2 3 Received: 17 July 2015 – Accepted: 30Correspondence August to: 2015 R. – J. Published: Farrington 21and ([email protected]) September P. J. 2015 Connolly ([email protected]) Published by Copernicus Publications on behalf of the European Geosciences Union. posed several processes for theincluding high an ice increased number ice concentrationsthe in nuclei advection orographic (IN) clouds, of concentration, secondary surfaceIN ice ice concentrations multiplication in crystals the and into modelwere prevents orographic the witnessed clouds. simulation during of Weclusion the the find mixed-phase of INUPIAQ that clouds secondary campaign that increasing ice atcannot production upwind Jungfraujoch. consistently of Additionally, produce Jungfraujoch the enoughtions. into in- A the ice surface WRF splinters flux simulations of toice hoar concentrations match comparable crystals to the was the included measured observedpleting ice in the concentra- number the liquid concentrations, water WRF without content de- model, (LWC)suggest simulated which in that simulated the high model. Our ice simulations concentrationsare therefore caused observed by in a mixed-phase flux clouds of at surface Jungfraujoch hoar crystals into the orographic clouds. M. W. Gallagher Comparing model and measured ice crystal concentrations in orographic clouds during the INUPIAQ campaign R. J. Farrington Atmos. Chem. Phys. Discuss., 15, 25647–25694,www.atmos-chem-phys-discuss.net/15/25647/2015/ 2015 doi:10.5194/acpd-15-25647-2015 © Author(s) 2015. CC Attribution 3.0 License. 5 25 10 15 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | C, ◦ C in 5 ◦ − 10 − C(Sassen ◦ 5 − C(Ansmann et al., ◦ 20 − erent freezing mechanisms: depo- ciencies, compositions and concen- C most ice nucleation in orographic ff ◦ ffi 38 − ering e ff 25650 25649 C via homogeneous nucleation (Koop et, al. 2000). However, it C. Mossop and Hallett(1974) indicated that one splinter is pro- ◦ ◦ 8 38 − − C, the presence of supercooled liquid water has consistently been found to ◦ 3 and − 25 min) and weak updrafts (Mason, ).1996 More recently Lawson et al.(2015) 38 − > ering IN and ice number concentrations (Harris-Hobbs and Cooper, 1987; Hogan ff ciency of clouds, (Twomey 1974; Albrecht, ; 1989 Lohmann and, Feichter ). 2005 IN concentrations alone are not enough to explain ice number concentrations wit- The influence of aerosols on the cloud microphysical processes is thought to be im- Despite much uncertainty existing over the concentrations and distributions of IN in In particular, the role of aerosols in the production of ice in the atmosphere is poorly ffi has shown fragmentation of freezing drops can also act as a secondary ice multiplica- duced for every 160greater than droplets 20 µm accreted in toincrease diameter, ice the and number suggested ice concentrations thatexamples crystal, by several have as rime-splinter been providing presented much cycles the in as could theing droplets five literature di orders of are the of Hallett–Mossop magnitude. processet Several explain- al., ; 2002 Huang etprocess is al., limited; 2008 toCrosier specific ethave regions, al., large which2011; concentrations areLloyd within of et thetimes supercooled, al. ( required liquid temperature2014). droplets, range, However, the and in clouds with long life- sition, condensation freezing,Above immersion freezing and contact freezing, (Vali 1985). the atmosphere (Boucher et al., posed),2013 particular to aerosol nucleate particle ice. typesatmosphere have Several been (e.g. studies pro- DeMott suggest et thatthreshold al., mineral below which2003; dust dustCziczo nucleates aerosols et nucleates icewith ice al., some in varies suggesting2013), significantly the between dust although studies, could the act temperature as IN at temperatures as high as be a requirement of2011, significant2013; heterogeneous nucleationde (Westbrook Boerfreezing and et modes Illingworth, to al., dominate2011), ice causing productionField at the et these al., immersion, temperatures2012). (de contact Boer and et al., condensation 2011; clouds takes place heterogeneously on IN via di et al., ),2003 whilst others found dust IN to be inactive above 2008). Laboratory measurements of ice nucleation on desert dust aerosols have linked Mossop and Hallett, 1974),ticles, which has produces been ice suggested splintersatures as during a of the dominant riming ice of multiplication ice process between par- temper- nessed in some clouds. Ice concentrationsice in multiplication the processes. atmosphere can The also Hallett–Mossop be process increased by (Hallett and Mossop, 1974; the varying nucleation thresholdparticles temperatures (Connolly to et the al., mineralet composition2009; al., ofMurray; 2012 the etAtkinsonsuggested dust al., et that mineral al., 2011; dust is2013; Broadley unlikelyEmersic et to act et al., as al., an2012; IN2015).Niemand at Generally temperatures as the high as literature has the atmosphere (Hoose and, Möhler biological2012), aerosols there in remains ice an nucleation uncertainty at in higher the temperatures. role of which has led to ongoingate research ice into at whether higher other temperaturesor than aerosol pollen mineral components have dust. can Biological nucle- beengeneously aerosols suggested (Möhler such as as et bacteria potentially(Prenni al., et being2007 ), al., suitable2009; whichPratt tosuggesting has et nucleate that al. , been2009). ice certain However, supported despite hetero- bacteria some by nucleate laboratory in-situ experiments ice observations at temperatures greater than portant in understanding the variabilityinteract of orographic with clouds clouds and by precipitation. acting Aerosols condenses as on to, cloud or condensation ice nuclei nuclei (CCN) (IN). The which di water vapour well as the intensity ofstanding precipitation these they variations produce in (Rotunno orographicof and a clouds, wide-range Houze is of2007). important geophysical Under- hazards asand are, the Raymond heavily; 1993 influenced intensity byGalewsky and precipitation and extent (Conway Sobel, 2005). trations of both CCN ande IN in the atmosphere influence the lifetime and precipitation understood. Ice can nucleateperatures below in the atmosphereis without thought that the for presence temperatures greater of than IN at tem- 5 5 15 20 25 10 15 25 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 25652 25651 C. By using measured aerosol concentrations in the parame- ◦ 15 . However, they suggested that a flux of particles from the surface, 1 − − at 1 − 100 L > 2000 L ect could not fully explain the high ice concentration events where concentra- ff ∼ By drawing on previous research into orographic clouds using modelling, this paper With aerosol and cloud particle measurements limited over mountainous regions, re- Despite considerable improvement in the understanding of ice production processes (WRF). In Sect.2, we outline theused characteristics to of the measure field cloud site microphysicalimplementation and of properties, the the instrumentation before WRF providing model. ameteorological In description Sect.3, data of we from provide the stations validationber of throughout concentrations the the are model then model using compared domain. withthe the The processes WRF in-situ proposed model ice in in Sect.4, num- previousgraphic before clouds literature analysing using for further increasing WRF icegested simulations. concentrations processes Finally, in in that oro- Sect.5, cause weconclusions high evaluate from the ice our sug- results. concentrations in orographic clouds, and draw aims to assess thecomparing reasons the in-situ for measurements high of Lloydwith ice et simulations al.(2015) number from over concentrations the real INUPIAQ at campaign terrain mountain from sites the by Weather Research and Forecasting model perturbations of dust and blackphase carbon on clouds. the The cloud simulations microphysicalcoupled processes were aerosol in run mixed- and using cloud microphysicsLohmann(2009) a and suggested two-moment 3-D mesoscale that idealised model aerosols orography. orographicMuhlbauer with clouds. are and However critical the inized strength terrain initiating of used ice their in in the conclusions model, are mixed-phase and limited for to the specific the aerosol ideal- data from 2009. search into orographic clouds hasthe been complexity of driven the by atmospheric theled dynamics, modelling to cloud community. However, microphysics a and restricted2006; terrainBarstad approach has et often in al., investigating; 2007 vide orographic aCannon clouds more et accurate al., (Kunz representation2014).generates, and of the Whilst computational, Kottmeier the 3-D expense complex has atmospheric airflow generally modelsteractions limited which in studies pro- mountainous orographic of terrain clouds aerosol-cloud to in- 2-Dor simulations (Lynn idealised et terrain al., (Xiao; 2007 Zubler etformed et 3-D al., al., simulations2011) 2014). over Recently, idealisedMuhlbauer orography and to Lohmann(2009) investigate the per- influence of aerosol tals being blownclouds, into which the are cloud. formedsupersaturatedVali by environment, et snow were) al.(2012 blown responsible trations. proposed up forTargino the from that et increased al.(2009) the ground-layer found ice surfacejoch snow two number in and cases Switzerland, concen- growing and of in suggested highcaused that an ice the by concentrations ice high mineral at ice dust concentrations Jungfrau- was were IN, observed. unlikely as They to no be suggestedIN that significant and polluted increase increased aerosol, in the such ice dustProcess as concentration Investigation aerosol close black And concentrations to carbon, Quantification the field actedthe surface. campaign as During (INUPIAQ) winter undertaken the of Ice during 2013 NUcleation over and 2014, Lloyd et(2015) al. found ice number concentrations of in the atmosphere, much confusionsured remains in in orographic understanding clouds. theconcentrations sources Several at of studies mountain ice have sites mea- when found)(1987 Vali compared frequently significantly to found high aircraft ice ice observations. concentrationsthreeRogers number close orders and to of the magnitude surface higherthe of than mountain. concentrations Elk The measured Mountain increased by of concentrations aircraftice could 1 km not multiplication, above be leading explained them by Hallett–Mossop to suggest the possibility of surface ice or snow crys- tion mechanism in thewith absence active of warm rain the processes. Hallett–Mossop process, particularly in cumuli terisation of DeMott et al.(2010), theyas predicted 3 IN orders concentrations which of were magnitudeings as smaller suggested much blowing than snow the contributed icethe to number the e concentration. ice Whilst number concentrations, theirtions they find- were found such as surface hoar crystals,number could concentrations provide witnessed enough in ice their crystals field to campaign. match the high ice 5 5 25 20 15 10 15 20 10 25 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 25654 25653 3 m high tall mast, which was automatically rotated ∼ Droplet concentrations and liquid water content (LWC) were measured by the For- Ice concentrations were primarily measured using an aspirated Three-View Cloud To compare with the measurementsjoch, made version 3.6 by of cloud the microphysics WRFdomain probes model was was at set used up Jungfrau- (Skamarock surrounding et Jungfraujoch, al., with).2008 a A horizontal single resolution model of 1 km, cov- a Metek sonic anemometer, whichtion. measured Additionally, meteorological the data temperature, was windstation available speed at from and the Jungfraujoch direc- MeteoSwiss forfound observation comparison. in FurtherLloyd et details al.(2015). of the instrumentation2.3 can be Model setup ward Scattering Spectrometerwhich Probe use the (FSSP), forward scattering and ofdiameters light of the from between a 2 Cloud laser and to 50recorded Droplet µm count with (Lance and Probe a et size Vaisala al., water probe, (CDP) droplets2010). which Meteorological of measured conditions temperature were and relative humidity, and diode laser beams (Lawson etparticles in al., the).2006 cross-section The ofcentrations arrays both and allow laser size images beams, distributions in in of addition 2data particles to dimensions in provided providing the of was number size then con- range(OASIS) processed of to using 10–1260 µm. segregate the The ice Optical raw that and Array had droplets Shadow shattered Imaging based on Software on theof their 2D-S shape, the from and 2D-S the to analysis datasetrecorded remove (Crosier particles on are et both provided, al. arrays by 2011 ).CPI of FurtherLloyd photodiodes images details et on the the al.(2015). particleparticle 2D-S, When onto motion the particle a CPI using 1024 images probe ahas by is are 20 1024 a activated. ns array. size The The pulsed range CPIimages laser, of has casting of a between an crystals pixel 10–2000 µm resolution image andto (Lawson of be of processing 2.3 et estimated. µm the of al., However, and the correctionsand2001). thus must for raw CPI particles be data produces below made enables clear 50particles to µm, the (see include as habitConnolly out-of-focus the et particles sample of al., volume the2007). has crystals a size dependency for small 2 Methodology 2.1 Jungfraujoch Cloud particle numberJungfraujoch concentrations high-alpine and research sizeJungfraujoch station, distributions is located were an in measured idealthe Bernese location at altitude to of the Alps measureof the in the microphysical site Switzerland. time properties (3570 ma.s.l.) (Baltensperger ofwhich limits et allows clouds, the, al. measurements as influence1998). to ofJungfraujoch local The be (Baltensperger anthropogenic site et within emissions is al., on cloudand measurements1997). only aerosol 37 taken The % accessible research at by site by groups has from electricTechnology, University regularly the of train, Paul been Scherrer Manchester used Instistute, and Karlsruhe for other1997, Institute cloud ; 1998 institutions of Verheggen (e.g., etBaltensperger al., et; 2007 etChoularton al. , al., et2015). al., 2008; Targino et al., 2009; Lloyd 2.2 Instrumentation at Jungfraujoch Several cloud physics probesfor using measuring a cloud variety particle ofcampaign. measurement number The techniques concentrations probes were and werea used size mounted on rotating distributions the during wing roof the attached terrace to of the a Sphinx laboratory on arrays, with a pixel resolution of 10 µm, as they pass through the cross-section of two Particle Imager (3V-CPI) by Stratton Park Engineeringbination Inc (SPEC). of This probe is twoStereo a com- Hydrometeor previously Spectrometer (2D-S) separately andS packaged a Cloud produces instruments: Particle shadow Imager the (CPI). imagery The Two-Dimensional of 2D- particles by illuminating them onto 128 photodiode and tilted to face intosampling the issues. wind based on the measured wind direction to minimize inlet 5 5 25 20 10 15 10 15 25 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 0 C. (1) ◦ 10 − at 1 − orographic data cause CFL stability cient detail to resolve clouds at grid- 00 20 km. A time-step of 3 s was used, to ffi C. ◦ ∼ 8 − 25656 25655 , is defined using the Cooper equation (Cooper, i N C), the parameterisation predicts ice concentrations ◦ is the temperature in K. The equation is based on in- 15 ) − T T − 0 T ( below water saturation using a portable ice nucleation chamber 1 258.15 K ( − 0.304 = . Chou et al.(2011) measured IN concentrations at Jungfraujoch of ap- T 1 273.15 K and − = 0 C, whilst Conen et al.(2015) measured concentrations of 0.01 L T ◦ 0.005exp 29 = − Figures1–4 show that the meteorological data compares favourably with the meteo- The short-wave and long-wave radiation are parametrised in the model using the Several WRF simulations were run as part of our investigation, and these are sum- The orography in the model is interpolated from surface data with a resolution of To model the cloud microphysics, the Morrison two-moment scheme was used, which , with the height of Jungfraujoch in the model being 3330 ma.s.l. The resolution of 2 i 0 closely follows the observedobserved temperature data throughout was the available. campaign At at other all sites, times the where temperature is less accurate, with pe- rological variables simulated in the WRF control simulation. At Jungfraujoch, the model As the Cooper parameterisation predictsparameterisation IN can concentrations between be these usedconditions values, which the to the assess parameterisation the isfrom usedThompson ice were et concentration adapted al.(2004), for at andrespect the hence to Jungfraujoch. Morrison is ice The Scheme is active greater eitherand than when the 1.08 the temperature or saturation of when ratio the the with model model is is saturated below with respect to water to assess the validitysimulations adjusted of to the include additional model, microphysical as processes. well as allowing a3 basis for comparison Model validation with To assess the validityobserved of meteorological the model, datathroughout the the from WRF domain, a control listed in simulationdirection,2. number Table was Each temperature of site compared and provided MeteoSwiss with relative datathe humidity, for control observation which wind simulation speed, in is stations 1–4. wind Figs. compared with the output from Goddard scheme (Chou and Suarez, 1999).as No the cumulus resolution parameterisations of were used, the model should provide su marised in1. Table Each simulationpaign, was between run the 20 for January thepleted 2014 time 00:00 in period Z a and of single, 28 thein February continuous INUPIAQ 2014 model our cam- 00:00 simulation research. Z, with and The com- no initial re-initialised WRF simulations simulation used for INUPIAQ formed a control simulation at scale. proximately 10 L situ measurements of heterogeneousfreezing. ice At nucleation by depositionof 0.4779 and L condensation 1986; Rasmussen et al., 2002): N where ering 149 grid pointsdirection. in The the higher north-southcomplicated spatial direction than resolution and the 99 was idealised grid99 required topography vertical points used as levels in were by the used, theMuhlbauer whichspacing real east-west and follow of the(2009). Lohmann orography terrain between as is 58 “sigma”220 more levels, m and providing at a 68 the m level model close top, which to was the situated at terrain surface, and between 165 and 2 satisfy the Courant–Friedrichs–Lewy (CFL) stability criterion,surrounding as Jungfraujoch the can complex orography cause CFL violations. is described in Morrisonduced et from heterogeneous al.(2005, freezing, 2009). The number of ice crystals per litre pro- was used as the steep gradientsproblems, present which in the prevent 30 thefor model the simulation duration from of runningdata the over from field the the campaign. European Jungfrau Centre The region model for and model Medium-range provide Weather was boundary Forecasting run conditions to atevery using initialise the 6 the edge operational h. of analysis The the model domain,vertical which simulations wind were were updated field found that to was output have a from the spin-up simulation. time of 40 h using the 5 5 25 20 15 10 25 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | er- ff respectively. 3 erence in height . Taken in isola- ff 3 280 m), so the di ∼ erences between modelled and ff 25658 25657 (Chou et al., ; 2011 Conen et al., 2015 ). Whilst the erences between the simulation and observations at generally causes the LWC to decrease to zero, with 1 ff − 3 erence between modelled and measured ice concentrations ff fewer ice crystals than measured by the 2D-S at Jungfraujoch, similar to the 3 observed ice number concentrations To test this hypothesis, two further WRF simulations were run with increased IN con- A better comparison between the model ice number concentrations and the 2D-S However, increasing the IN concentration in the Morrison scheme generally causes Findesen process. The greater INsmall concentration ice in crystals the produced modeling increases at the the the number onset IN of of concentration freezing. by Figure5b 10 indicates that multiply- centrations. The IN concentrations werelitre increased from by multiplying the the Cooper numbertions, equation of IN-1 (Cooper, IN and)1986 per IN-3, by the a IN constant concentrations value. were In multiplied the by two 10 simula- and 10 concentrations is found when the number of IN is multiplied by 10 the LWC in thephase simulation clouds, to decrease ice (see crystals Fig.5b). grow When at freezing the occurs in expense mixed of liquid droplets by the Bergeron– previously measured IN concentrationsthan have the varied, ice they areHence number there still concentrations is considerably measured a lower pled at possiblity by that Jungfraujoch the other instruments (Lloyd aerosols measuringTargino et et IN are al.(2009). concentrations al., nucleating at ice). 2015 Jungfraujoch, which as are proposed by not sam- The ice number concentrations simulatedWRF at simulations Jungfraujoch are in compared the with control, the IN-1 2D-S and concentrations IN-3 in Fig.5a. tion, the ice numberCooper concentration equation simulated used in in the thecentrations Morrison IN-3 scheme in significantly simulation orographic underestimates suggests the cloudsenvironment. that IN and con- the that additional IN are present in a mountainous 4.1 Sensitivity of simulation to INWe concentration first examine if theis di explained by additional IN infrom the model. previous As field touched campaigns upon intions at Sect. of Jungfraujoch2.3, measurements have between suggested 10 varying and IN 0.01 L concentra- between the model and reality is much smaller at Jungfraujoch ( riods during the campaign whereperatures observations and at relative Titlis humidities, showed and significantlyfrom higher lower wind the tem- speeds, WRF than simulation. the The values di determined 4 Comparison and explanations for di Titlis relate to themodel close is proximity more of sensitive the tothe station the control to boundary simulation conditions, the and causing edge theis the at of meteorological discrepancy the observations. the centre between However, domain, of as theresolution where Jungfraujoch model of the domain, the it orography is not causesThe sensitive the to height height boundary at of conditions. Also, the Titlis(3040 the ma.s.l.) sites in in of the the the model model site.the to location As is of be a Titlis 2234 reduced. result, ma.s.l., in the the much model temperature is in lower lower the than inence model altitude. the In in will contrast, actual temperature be the is warmer height di model considerably as provides less. a Hence good the representation MeteoSwiss offor the our data atmospheric research. shows conditions that over Jungfraujoch the around 10 discrepancies found in the literature betweensites ice concentrations and measured at on mountain predicted aircraft IN (Rogers concentrations and (Lloydthe, Vali et discrepancy1987), al., between and2015). theconcentrations between measured We ice at ice will number Jungfraujoch. concentrations now concentrations and examine simulated the in cause WRF of and the For the duration of2D-S the were campaign, compared the withsimulation ice (see ice number red and concentrations number blue recorded concentrations lines in using simulated Fig.5a). the The in control simulation the regularly WRF produced control 5 5 25 10 15 20 10 15 25 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (2) was calculated i ¯ r i N . For the modelled ice concen- is the mean radius of ice crys- t throughout the field campaign. , i z ¯ r z u u . The updraft speeds measured by the sonic 25659 25660 t , z u , which was then compared with the simulated updraft speeds ti , was calculated from the first moment of the ice, snow and graupel z i u ¯ r are thermodynamic variables dependant on the pressure and tem- i ∗ i N b and i ¯ , such that the threshold is approximately two orders of magnitude smaller r 0 t i , is the number concentration of ice crystals, 0 a z N i a erent field campaigns agree on the presence of both high ice concentrations ∗ i u ff N b = t The threshold updraft speed was calculated for both the measured and modelled For the control WRF simulation, Fig.6b shows the low ice concentrations significantly Figure6b indicates that, when the IN concentrations are increased, the updraft speed For the majority of the campaign, the updraft speed measured at Jungfraujoch was The IN-3 WRF simulation implies that concentrations similar to the measured ice , z ice concentration. For the measured ice concentrations, the term using the 2D-S size distribution,Jungfraujoch with measurements also of used temperature and to pressure calculate from reduce threshold increases significantly to values close to where tals, and perature of the parcel, as defined in Korolev and Mazin(2003). anemometer at Jungfraujoch were then comparedtrations, to the term size distributions from the control andtribution IN-3 parameters WRF from simulations, the using Morrison the scheme gammaThe (see size snow Appendix dis- of andMorrison graupel et size al., of2005). distributions both are snow and included graupel inAdditionally, also the the depletes simulated calculation, the temperature as LWC and thein by pressure growth the the from calculation Bergeron–Findeisen each of process. simulation were used updraft threshold reinforces the measurementscoexist in in suggesting clouds that at droplets Jungfraujoch, andFig.5a as ice and indicated can by b. the 2D-S and CDP measurements in than the updrafts simulatedmodel at are Jungfraujoch. increased, When more thedeposition ice IN onto crystals concentrations the in are additional the produced,saturation IN. WRF which ratio The is in the vapour caused model. deposition bysaturation, To the a results maintain greater vapour a in updraft saturation a speed ratioin reduction is WRF which of increases required. is the Hence the greater updraft increasing than speed the liquid threshold for IN the concentration existence of mixed-phase clouds. During some periods, the simulated updraft speed is lower than the updraft speed greater than the thresholdwhich updraft velocity is for consistent mixed-phase with cloudJungfraujoch. the conditions Assuming coexistence (Fig.6a), that of liquid the water atmosphere and is ice saturated crystals with witnessed respect at to liquid, the from the two simulations. number concentrations are not possiblethe in measurements mixed-phase made clouds, at whichfrom is Jungfraujoch. di in However, as contrast to multiple ice and liquid probes u liquid water absent at Jungfraujochments for most from of several the liquid IN-3measurements simulation. and made However, ice measure- in previous cloud field probesis campaigns during at present Jungfraujoch, the even suggest field liquid when2009; water campaign, largeLloyd as ice et well al., number2015). as concentrations are measured (Targino et al. , and liquid water atet Jungfraujoch al., (Choularton2015), it et isthe al. , observed unlikely; 2008 ice thatTargino number increasing et concentrations IN at al., in Jungfraujoch. 2009; the modelLloyd Validation of is mixed the phase correct cloud explanation at for Jungfraujoch To confirm that mixed-phasemeasured clouds and are modelled ice possibleexistence of number at mixed-phase concentrations, Jungfraujoch clouds derived weKorolev with by used and theKorolev and the Mazin(2003) both Mazin(2003). conditions providephase the In conditions for an their in paper, the updraft a speed cloudbased on can threshold, the be above assumptions maintained of which byfor a droplets the parcel mixed- to model, updraft exist and speed. in that The a clouds. threshold cloud The is must threshold be updraft water speed saturated is defined by 5 5 25 25 15 20 10 10 15 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (4) (3) . As the 1 − is defined as η C. During the INU- ◦ 8 − 3 to − denoting the area swept out by , the production rate of splinters A ice n ciently large enough to cause splinter ffi erences between the constant temperature ff 25662 25661 following Mossop and Hallett(1974), whilst the ice crystals C. The extended range was to prevent the splinter concentra- 1 ◦ − the number of splinters produced per µg of rime. 10 η and ice number concentration − l ice at the initial output time was constant along the back trajectory, the q t ∆ ijk Aηn f 30 is the time step in seconds. At each point along the trajectories, the u V ijk l splinters kg − = u q t 6 − denoting the fall speed of the ice particle, = ∆ 10 f = V × C or less than C, ruling out secondary ice production at the site via the Hallett–Mossop process ,hm t ◦ ◦ ijk i To establish if splinters were transported to Jungfraujoch from cloud base, back tra- The absence of the observed mixed-phase clouds in the IN-3 simulation implies d x 2 8 n d back trajectories were calculated using ∆ 350 were assumed to be spherical with diameters of 500 µm, and falling at 2 ms with model resolution is finiteare we produced, define conservatively using the a temperatureMossop(1974), slightly thresholds with wider temperature within the range which production than − splinters rateHallett and set to 0tion if being the underestimated temperature duefield was to in greater any the than di modelduced and along the each back real trajectoryof temperature. was splinters The that then could cumulative calculated, be number to producedconcentration of along provide of the a splinters ice back maximum trajectory. splinters pro- The number along calculationproduced the of along the back total trajectory the assumes back that trajectory every ice is splinter transported to Jungfraujoch and measured as the ice crystal and jectories were calculated usingwind the field WRF control simulation output. By assuming the ture range, and a strong updrafttowards must Jungfraujoch. be present to advect the newly produced splinters where WRF output fields wereUsing interpolated the from LWC nearest WRF output variables to the point. formed by the Hallett–Mossop process was calculated using clouds. 4.2 Hallett–Mossop process upwind of Jungfraujoch Ice multiplication processes such as1974) the have Hallett–Mossop been process suggested (Hallett as andtals an, Mossop in important mechanism mixed-phase in clouds. Mountain the thatRogers production the of Hallett–Mossop and ice is(1987) Vali centrations crys- not suggested responsible as for in the the increased theirproduction. droplet ice study In number sizes con- at addition are they Elk are not suggested outside that su the temperatures Hallett–MossopPIAQ witnessed campaign, the temperature at temperatures range observed Elk at of − Jungfraujoch Mountain were generally colder than (Lloyd et al., 2015). generally However, Targino above et cloud al. (2009) base, the suggestedjoch Hallett–Mossop that at process as higher could Jungfraujoch temperatures, occur is increase and below ice Jungfrau- that number splinters could concentrationsoccur be at at lifted cloud the from base, summit.In the supercooled addition, For cloud liquid the secondary temperature water base at ice and to cloud ice production base must crystals to be must within both the Hallett–Mossop be tempera- present. that increasing the INconcentrations concentration at alone Jungfraujoch. can Results notphysical from processes explain our the are modelling measured important suggest ice additional in number micro- the production of ice in orographic mixed-phase threshold from the IN-3which simulation. would During other prevent periods,speed mixed-phase there is conditions is either no from lowerthe updraft being Korolev than present, and sustained. the Mazin analysis As thresholdthese predicts during the periods. that mixed-phase these The updraft clouds analysis periods,Fig.5a will supports and or not b. occur the not during findings present of at the all, IN-3 simulation indicated in 5 5 15 25 20 10 15 20 25 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | er ff erence ff erent times of ff er by 3 orders of mag- usion to sizes greater ff ff C throughout the ascent of ◦ 10 − erent altitudes or at di ff C after 20 min, producing a significantly ◦ 10 − 25664 25663 However, during certain periods splinter production may contribute to the di However, as indicated in7 Fig. the case on the 1 February is not representative of The total number concentration of splinters produced along the back trajectory was To assess whether the discrepancy between the measured and modelled ice number 4.3 Inclusion of snow concentration inThe ice concentration ice numbersentation concentration of simulated some in ice WRFrison crystals may scheme as be snow when crystals. reduced ice Ice by size is the converted distributions misrepre- to grow snow by in the vapour Mor- di between the modelled and measuredsecondary ice number ice concentrations. production Also, the on influence the of ice concentration in mountainous regions maythe di year, if the temperatures inregime these regions more are frequently within than the witnessed Hallett-Mossop temperature at Jungfraujoch. than a threshold meaneter diameter. The of Morrison 125 scheme µm(2014) uses following a impliedHarrington threshold that mean et thegesting diam- al.(1995). threshold threshold However, diameters diameterSchmitt of can 150the and and vary threshold Heymsfield 250 significantly µm diameter for in two fora real separate simulated autoconversion case clouds, ice studies. in sug- number Raising thesurements concentration at which microphysics Jungfraujoch. is scheme more may representative provide of the 2D-Sconcentrations mea- is caused bycentration ice was calculated being by incorrectly adding thetogether. converted modelled Whilst to snow the and snow, snow ice the number numberlarge concentrations frozen concentration ice, this con- will is include only falling significantice snow if number the in concentration. frozen addition concentration to is greater than the measured tal concentration at Jungfraujoch forprocess the occurring 26 below January cloud case.between base Hence, the is the measured not Hallett–Mossop and the modelled ice main number reason concentration for during the this large period. discrepancy due to seasonal orhance spatial ice number variations. concentrations Secondary in ice regions at production di may significantly en- the whole campaign, withJungfraujoch only throughout most small of concentrations thewhere campaign. of the9 Figure splinters observedillustrates simulated and that modelled on upwind ice 26 of January, number concentration di larger concentration of ice splinterslation. than The simulated conditions at along Jungfraujoch the inWRF back the model trajectory control simu- suggest underpredicts that the duringMossop concentration process this quite case of considerably. Viewing study ice the the ters case crystals in produced produced isolation, at the cloud by inclusion base the ofconcentrations in splin- Hallett– observed the at model Jungfraujoch. would allow a better representation of the ice nitude, no splinters are simulated. Thetory absence is of a secondary response ice to alongthe the the air temperature back towards remaining trajec- Jungfraujoch, below causing noof splinters both to supercooled be water produced and despite ice the crystals. presence As a result, there is no increase in ice crys- tory from 1 February 2014was at south-easterly. 19:00 The Z, high plotted number followingis the due of direction to splinters of the calculated the constantpresence along wind, presence of the which of a back liquid suitable water trajectory andstops temperature ice when for crystals, splinter the in production. temperature addition The falls to simulation below the of initial splinters added to the icenumber number concentrations concentration produced by at the Jungfraujoch WRFincluding and control the run is splinters and calculated compared the using 2D-SWRF with Eq. in control the7. Fig. 4), ( simulation ice When increases the significantly iceas during number indicated certain concentration by periods from the of the greytion the shaded campaign, of areas splinters in increases Fig.7.of the For the example WRF 2D-S on ice ice 1 number number February, concentration concentration the at addi- to Jungfraujoch. Figure8 withinshows a the factor back trajec- of 10 an ice crystal, whichtrajectory is by sedimentation unlikely or as collisions the with ice sedimenting particles. crystals would be reduced along the back 5 5 10 15 20 25 20 15 25 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | C ◦ (5) (Hachikubo and , 2003; Alvarez- erence between C(Na and, Webb ff ff 1 ◦ − ect on surface hoar de- ff ect provided only a minor contribution ff was calculated using φ 25666 25665 0.84 − is the horizontal wind speed. The surface crystal flux was applied to the h u h u 0.24 e = We adapted the aerosol flux from Xu et al.(2013) for inclusion in our simulations to The increase in ice number concentration with the addition of snow is not significant However, the atmospheric influence of frost flowers, a similar phenomena to surface to the ice numbera concentration surface at ice Jungfraujoch. generationber However, mechanism concentrations they witnessed was also at potentially Jungfraujoch. suggested thespeculated Along that with source thatRogers of and it(1987), Vali thethe they was high mountain possible ice to for num- benumber blown surface by concentration. hoar surface Surface winds crystals hoar intoonto or growing the the hoarfrost snow on atmosphere forms surface and in the by supersaturated influence deposition surface air the of at of ice temperatures water below vapour 0 2003; Polkowska et al., velopment,2009). with Wind also ideal has wind, Akitaya a1997). speedsStossel significant for et e ) al.(2010 formation discovereding that between clear surface 1–2 nights hoar ms formation with occurs humidhas dur- air, mostly and can been survive motivatedcused throughout by on the understanding the day. Previous formation avalanche research , (Colbeck 2003) formation, and1988; with spatialHachikubo variability research and of, fo- Akitaya and the1997; phenomena, Jamieson Na (Helbig2010; and and Van, Galek Webb Herwijnen, surface2012; hoar etShea have, al. been limited. ).2015 The research intohoar, atmospheric is impacts the of subjectform of on freshly much formed research. sea Frost ice that flowers is are significantly highly warmer saline than the crystals atmosphere which above where first level of theeverywhere model, where assuming the surface air hoar temperature crystals in sizes the of first 10 level µm. of The the flux model acts is less than 0 assess if the discrepancy betweencan modelled and be measured found. ice The number surface concentrations ice crystal flux Aviles et al., 2008). ofXu the et atmospheric al.(2013) flux provided ofponential an dependency aerosol observation-based on from parameterisation wind frost speed, flowers.et and The al.(2013) was parameterisation found included has the in anment inclusion the ex- between WRF-Chem of modelled model. frost andXu measured flowersis sea in salt of the aerosol sea-salt model concentrations. Whilst enabled aerosol,aerosol the a concentration flux the better or flux the agree- frost equationis only flower does dependant density, on and not wind-speed. essentiallyFeick requireinfluence et provides on al. (2007) the a suggested surface flux that definition hoar the which destruction of mostare is important removed either wind, by implying the the that windderived the blowing by crystals theXu on crystals et the into(2013) al. strongly surface the and dependent atmosphere. the As on removal the wind, of aerosolfrom the hoar flux the flux crystals surface. can from Hence, be the antial used surface adaptation assessment to are of on both model the the hoar aerosolorographic flux crystals influence clouds. is of being suitable blown surface to hoar provide on an the ini- ice number concentrations in φ (Perovich and Richter-Menge, hoar,1994; theyStyle require and thesurface, Worster presence (Rankin).2009 et of Similarly, al. supersaturatedAtmospheric to2002), scientists air have surface and with shown grow particular respectproduction by interest to of vapour in ice sea the deposition role above salt (Domine of the aerosol et frost in flowers al., in the2005). the atmosphere (Rankin and Wol enough to match thesuggests ice the number concentrations number observed of at snow Jungfraujoch. crystals Figure 10 is small compared to the di the modelled and observed iceice number number concentrations. concentrations The fails inclusionmagnitude to of required snow increase to into the match the the concentrations observed by concentrations. the three4.4 orders of Surface crystal flux After careful analysis, Lloyd et al.(2015)ice suggested that number whilst concentrations blowing snow periodically, influenced the e 5 5 25 10 15 20 10 15 20 25 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ects ff following Geever et(2005) al. and Xu et al. 1 − 25668 25667 s 2 erences between the model and measurements − ff m 6 . Figure 11a indicates that the Surf-3 provides much better agreement 1 − s 2 − m 3 ers by approximately a factor of 100 throughout the campaign. The increase in con- Nonetheless, the results of the Surf-3 simulation suggest that the aerosol flux of Xu Whilst the inclusion of the surface crystal flux in Surf-3 provides a good comparison Figures 12 and 13 show the ice number concentration and LWC from the Surf-3 sim- Two WRF simulations were run including the surface crystal flux. Firstly, Surf-6, which As the surface crystal flux is high, a large number of small ice crystals are ejected As the Surf-6 simulation overestimated the ice number concentration and underesti- ff et al.(2013) can be adaptedof into a a surface surface crystal crystal fluxand flux and measured into used ice WRF in number WRF. provides The concentrations. a inclusion In good addition, agreement the between Surf-3 the simulation simulated suggests isation. Firstly, the surfacesurface crystal hoar flux crystals. As is the independentin surface of of distribution the the mountains of surface upwind surfacependent concentration of on Jungfraujoch hoar of the will crystals vary distribution of presentspatial surface and hoar on temporal variations crystals, the of in surfaceneed surface, hoar addition suggested to to the by be theStossel flux included et wind in al. (2010) speed. willAlso, would the The whilst parameterisation vary to the de- better magnitude representcrystal the of flux surface the is crystal adapted flux. flux fromflux, is an measurements aerosol calibrated of flux. based To surface accurately onunderstanding crystal assess of our the flux the results, magnitude process would of the of be the the surface required advection to of hoar improve crystals the into physical the cloud. with the measured ice concentrations, the flux used is still a very simple parameter- with the ice number concentration measuredIn at addition, Jungfraujoch throughout Fig. the campaign. 11bwith shows the the CDP LWC than simulated Surf-6, with in the Surf-3 di also compares much better trations aloft were much lowerto than at be the a surface. The strongmixed-phase LWC sustained in clouds Fig. cloud at13 Jungfraujoch. byis the also indicated model, which further supports the presence of ulation during a period where bothindicate ice the ice and concentration liquid is are heavily presentthat increased at the by Jungfraujoch. the surface Figure surface ice12 ice is concentration,surface concentrations and not supports carried the from findings the of Rogers surface and high(1987) Vali into that ice the concen- atmosphere. The high to 10 no greater than a factor of 3, and for the most part of the campaign within a factor of 2. and the air is supersaturated with respect to ice, with no dependence on diurnal e assumed the flux magnitude of 10 or variations in surface snow cover. (2013). The flux magnitudeber assumes of in surface the hoar Surf-6 crystalsflowers simulation blown in into assumesXu the that et atmosphereare the al.(2013). is compared The num- with equal ice the to number 2D-S thea ice concentration number number good from of concentration the in frost agreement Fig. Surf-6 withthan11a. simulations The measured the Surf-6 at 2D-S, provides Jungfraujoch. althoughdi The with 2D-S concentrations and higher the in Surf-6 the WRF model simulation generally in the Surf-6 simulationagree is with scavenged LWC measured by by thetration the ice CDP blown number at into Jungfraujoch. concentration, the The atmosphere andJungfraujoch large from in does ice the the number not surface concen- model, rapidly suggestingthe depletes magnitude the the of magnitude liquid the of flux water theconcentration would at at flux need Jungfraujoch, is to and be unrealistic. to prevent reduced Hence, atmosphere liquid to to water better agree from represent with being the depleted the ice from measurements number the taken at Jungfraujoch. mated the LWC, a second simulation, Surf-3, was run with the flux magnitude reduced centration is unsurprising, asconcentrations the emitted from flux frost is flowers.tration, adapted As the from the magnitude an surface of crystal the equationet flux flux based al.(2013), is is which on likely an was aerosol to ice for be concen- an smaller aerosol than concentration. the magnitudefrom used the by Xu surface inice supersaturated the conditions. model. Inice These order crystals crystals to scavenge continue grow vapour tofrom rapidly from the grow any by model by droplets by vapour vapour the present, deposition deposition, Bergeron–Findeisen and the process. in deplete As the indicated in liquid Fig. water 11b, the LWC 5 5 20 25 15 10 10 25 15 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 25670 25669 Whilst aerosols acting as IN are important in initiating the production of ice in oro- To evaluate if surface hoar crystals influence the ice concentrations in orographic Previous literature also suggested secondary ice production might contribute to an Whilst increasing IN concentrations in the model produced a better representation graphic clouds, theyserved. alone There remains cannot uncertainty on explain the the exact causes high of the ice high ice number number concen- concentrations ob- the existence of such a fluxcraft may explain measurements why of surface ice measurements number are concentrationThe higher than surface witnessed crystal air- by fluxRogers parameterisation and(1987). included Vali eterisation, in and our independent simulations of is a thespatial simple surface and param- concentration temporal of variations surface of hoar surfaceas crystals. hoar varying suggested The hoar by Stossel frost et concentrationsformation al.(2010), on such and the removal, snow need surface tocuracy and be of the included the periods surface in flux. of the Nevertheless, hoarpaper parameterisation the frost surface to provides crystal improve a flux the good parameterisation ac- in comparisonwe this with suggest the the observed increase iceinfluenced number in by concentrations, a ice and surface concentrations flux in of hoar orographic crystals. clouds is predominately clouds, a flux of hoarflux crystals from and the introduced surface was intoagreement adapted with from the the a WRF ice frost flower number model. aerosol concentrations The measured inclusion at Jungfraujoch, of suggesting the flux provided a good paign. increased ice number concentrationpaign in temperatures observed orographic were outside clouds. theand During temperature(1974), Mossop range the suggested implying INUPIAQ by iceHallett cam- number multiplication concentrations. was Following notTargino responsible etproduction for al.(2009), could increasing we ice occur analysed whether closeusing splinter back to trajectories that cloud splinter base concentrationsice only and number infrequently concentrations. be matched Whilst observed blown secondarygraphic into clouds ice the at production warmer may cloud, temperatures,influence be and secondary important on found ice in the appears oro- ice to number have concentrations only observed a limited during the INUPIAQ field cam- existence of the mixed-phaseare clouds regularly witnessed witnessed at at Jungfraujoch.hence Mixed-phase Jungfraujoch an clouds (Choularton accurate representation et ofinfluence al., LWC is of2008; requiredLloyd these to etprimary orographic understand al., the clouds. ice formation2015), nucleation Our and may simulationscreasing contribute the suggest to IN that ice concentrationconcentrations whilst concentrations observed. is additional in not orographic likely clouds, to in- be responsible for the high ice number of the observed ice numbercaused concentrations, by the removal the of IN liquid water concentration from suggested the high model IN concentrations would prevent the that the inclusion ofice a number surface concentrations crystal without flux depletingjoch, provides from the the a LWC, model. which good The is agreement presencefurther observed of with suggests the at measured LWC Jungfrau- that at Jungfraujoch theJungfraujoch in high the can Surf-3 ice be simulation concentrations representedmodel. in by The mixed-phase including simulation clouds a results observed fluxing support at of that the surface surface suggestions hoar hoar of Jungfraujoch. crystals crystalsLloyd into et advected the al.(2015), into propos- cloud increases the ice concentration at 5 Conclusions In this paper, ice numberwith concentrations from ice WRF number model simulations concentrationsthe were INUPIAQ measured compared campaign. in The orographicsignificantly ice clouds number lower concentrations Jungfraujoch than simulated during thehigh in concentrations ice the number measured model concentrations in-situ, were in to which previous the field showed concentrations campaigns similarly witnessed (Rogersfor and in the, Vali orographic1987; high clouds Targino ice etusing number al., the concentrations2009). model Suggestions witnessed simulations. in orographic clouds were explored 5 5 20 25 15 10 25 20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ect, an improved represen- ce. The data from this project ff ffi 25672 25671 at Jungfraujoch for access to their site and for their ff The authors wish to express gratitude to colleagues from KIT, MPIC, PSI e, E., and Neve, L.: Immersion mode heterogeneous ice nucleation by an illite rich ff and Seibert, P.:Aerosol climatology atphys. the Res., high-alpine 102, site Jungfraujoch, 19707–19715, Switzerland, doi:10.1029/97JD00928, J. 1997. Geo- 25653 Scavenging of atmosphericJungfraujoch part constituents I: in Basic3975–3983, concept mixed, doi:10.1016/S1352-2310(98)00051-X and 1998. aerosol phase25653 scavenging clouds by clouds, at Atmos. Environ.,graphic the precipitation: 32, evaluation high-alpine of linear model site ,doi:10.1016/j.jhydrol.2007.04.005 in 2007. idealized problems,25652 J. Hydrol., 340, 78–90, Kondo, Y., Liao, H.,and Lohmann, Zhang, U., X. Rasch, Y.: Clouds P.,sis. and Satheesh, Contribution aerosols, of in: S. Working Climate Group K., Change IPanel Sherwood, 2013: on to Climate the The S., Change, Fifth Physical Stevens, edited Assessment Science by: Report B., Boschung, Ba- Stocker, of J., T., Qin, Nauels, the D., A., Intergovernmental Plattner, Xia, G.-K., Y.,bridge, Tignor, Bex, M., V., UK and Allen, and Midgley, S., P.,Cambridge New University York,25649 NY, Press, USA, Cam- 571–657, doi:10.1017/CBO9781107415324.016, 2013. Condli powder representative ofdoi:10.5194/acp-12-287-2012, atmospheric 2012. 25650 mineral dust, Atmos. Chem.cipitation Phys., model 12, with 287–307, doi:10.1002/qj.2269, 2014. embedded25652 convection, Q. J. Roy.properties within Meteor. a Soc., Saharan dustPhys., 140, event 11, at 4725–4738, 1997–2012, the doi:10.5194/acp-11-4725-2011, Jungfraujoch 2011. in25655, the25658 Swiss Alps, Atmos.Tech. Rep. Chem. June, NASA/TM-1999-104606, 1999. 25656 Crosier, J., Connolly,heggen, P., B., Targino, Cozic, A., J., and Alfarra, Gysel, M. M.: The R., influence Baltensperger, of small U., aerosol Sjogren, particles on S., the Ver- proper- 1230,, doi:10.1126/science.245.4923.1227 1989. 25649 Frost flower chemical compositionand during growth bromine and activation, its J.2008. implications Geophys.25666 for Res.-Atmos., aerosol 113, production 1–10, doi:10.1029/2008JD010277, Wiegner, M., Pisani, G., Knippertz,glaciation P., in and southern Dubovik, O.: MoroccoRes., Influence 113, during of D04210, the Saharan doi:10.1029/2007JD008785, dust Saharan 2008. on Mineral25649 cloud Dust Experiment,Dobbie, J. S., Geophys. O’Sullivan,for D., Malkin, ice T.doi:10.1038/nature12278, L., nucleation 2013. and25650 by O’Sullivan, D.: mineral The importance dust of in feldspar mixed-phase clouds, Nature, 498, 355–358, Cannon, D. J., Kirshbaum, D. J., and Gray, S. L.: A mixed-phase bulk orographicChou, M.-D. pre- and Suarez, M. J.: A solar radiation parameterization for atmospheric studies, Chou, C., Stetzer, O., Weingartner, E., Jurányi, Z., Kanji, Z. A., and Lohmann, U.: Ice nuclei Choularton, T. W., Bower, K., Weingartner, E., Crawford, I., Coe, H., Gallagher, M. W., Flynn, M., Baltensperger, U., Gäggeler, H. W., Jost, D. T., Lugauer, M., Schwikowski, M., Weingartner, E., Baltensperger, U., Schwikowski, M., Jost, D. T., Nyeki, S., Gäggeler, H. W., and Poulida, O.: Barstad, I., Grabowski, W. W., and Smolarkiewicz, P. K.: CharacteristicsBoucher, of O., Randall, large-scale D., oro- Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Broadley, S. L., Murray, B. J., Herbert, R. J., Atkinson, J. D., Dobbie, S., Malkin, T. L., Alvarez-Aviles, L., Simpson, W. R., Douglas, T. A., Sturm, M., Perovich, D., and Domine,Ansmann, F.: A., Tesche, M., Althausen, D., Müller, D., Seifert, P., Freudenthaler, V., Heese, B., Atkinson, J. D., Murray, B. J., Woodhouse, M. T., Whale, T. F., Baustian, K. J., Carslaw, K. S., and University of Frankfurt who workedduring as part the of field CLACE 2014 campaign; for their to support and the assistance sta Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227– tation of the fluxcurrent can field be measurements. provided using the newAcknowledgements. dataset and can be verified with the assistance and cooperation with our research.at The the lead author University also of wishedsupported to by Manchester thank a for colleagues NERC standard theirby grant support award a NE/K006002/1, NERC and whilst studentship the assistance. andcan lead The author be CASE is INUPIAQ obtained funding supported by campaign from contacting the is the UK authors Met of O this article. References trations in orographic clouds; however,for we by suggest a flux the of uncertaintya hoar may crystals flux be from of accounted the surface surface hoarof of the crystals the flux on mountain. are To orographic required. verify clouds, If the observations the influence and measurements of confirm measurements the e 5 5 10 15 20 25 30 20 25 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ciency of mineral par- ffi erent desert dust samples, Atmos. Chem. ff , H., Burgess, R., Choularton, T., and Gallagher, ff 25674 25673 ciency and chemistry in Wroclaw, Poland, Atmos. Res., ffi ect of wind on surface hoar growth on snow, J. Geophys. ff , M., Polkowska, Z., Cichala-Kamrowska, K., and Walaszek, K.: Dew ś ticles, Atmos. Chem.25650 Phys. Discuss., 15, 887–929, doi:10.5194/acpd-15-887-2015, 2015. hoar at the25666 basin scale, J. Geophys. Res., 112,Stith, 1–16, J., doi:10.1029/2006JF000587, and 2007. Prather,teristics K. of A.: heterogeneous Ice ice in,doi:10.1175/JAS-D-11-026.1 formation 2012. clouds in25649 experiment–layer lee clouds. wave clouds, Part J. II: Atmos. Testing Sci., charac- and 69, hoarfrost 1066–1079, frequency, formation e Res., 102, 4367, doi:10.1029/96JD03456, 1997. 25665 Nature, 249, 26–28, doi:10.1038/249026a0, 1974. 25650, 25661, , 25662 25670 conversion processes due to vapor deposition for mesoscale models using double-moment son, M. S.,distributions Eidhammer, and T., and their,doi:10.1073/pnas.0910818107 Rogers, impacts 2010. 25651 D. on C.: climate, Predicting P. global Natl.area, atmospheric Acad. ice Sci. density nuclei USA,doi:10.1029/2005GL023245, 2005. 107, and25666 11217–11222, microstructure ofbetween wet-suspension frost and dry-dispersion derived flowers, ice nucleation e Geophys. Res. Lett., 32, 1–4, 151, 120–129,, doi:10.1016/j.atmosres.2014.05.006 2015. 25665 tral California during thedoi:10.1175/MWR2943.1, New 2005. Year’s25649 Flood of 1997, Mon. Weatherand Rev., 133, 1594–1612, Rannik,doi:10.1029/2005GL023081, 2005. 25667 U.: Submicron sea spray fluxes, Geophys. Res. Lett., 32, 2–5, M.: Studies of heterogeneous freezingPhys., by 9, three 2805–2824, di , doi:10.5194/acp-9-2805-2009 2009. 25650 25649 21.43.29, 1986. 25655, 25658, 25680 Crawford, I. P., Capes,lagher, G. L., M. Coe, W., H.,tive and Dorsey, cell J. Blyth, embedded R., A.doi:10.5194/acp-11-257-2011, Williams, in 2011. M.: P. supercooled I.,25650, Observations25654 Illingworth, mid-level A. of stratus, J., Atmos. ice Gal- Chem. multiplicationTwohy, C. H., Phys., in and 11, Murphy, a D. 257–273, cloud M.: weakly formation, Clarifying Science, the convec- 340, dominant 1320–1324, sources, doi:10.1126/science.1234145 and 2013. mechanisms25649 of cirrus nucleation in high-latitudeLett., stratiform 38, clouds L01803,, doi:10.1029/2010GL046016 from 2011. surface25649 remote sensors,Prenni, Geophys. A. Res. J., and Kreidenweis,phys. S. Res. M.: Lett., African 30, dust 1732, aerosols doi:10.1029/2003GL017410, as 2003. atmospheric25649 ice nuclei, Geo- ties of water and ice, 25653 clouds,25659 , Faraday Discuss.,25669 137, 205–222,, doi:10.1039/b702722m 2008. Bound.-Lay. Meteorol., 44, 1–12,, doi:10.1007/BF00117290 1988. 25665 Atmospheric ice nuclei at67, the 1–10, high-altitude 2015. observatory25655, Jungfraujoch,25658 Switzerland, Tellus B, Bower, K. N.:and Calibration ice of crystal,doi:10.1175/JTECH2096.1 2007. the analogs:25654 cloud the particle depth imager of probes field, using J. calibration Atmos. beads Ocean. Tech., 24, 1860–1879, Feick, S., Kronholm, K., and Schweizer, J.: Field observations on spatial variabilityField, of P. surface R., Heymsfield, A. J., Shipway, B. J., DeMott, P.Galek, J., G., Sobik, Pratt, M., K. Bla A., Rogers, D. C., Hallett, J. and Mossop, S. C.: Production of secondaryHarrington, ice J. particles Y., Meyers, during M. P., the Walko, R. riming L., process, and Cotton, W. R.: Parameterization of ice crystal DeMott, P. J., Prenni, A. J., Liu, X., Kreidenweis, S. M., Petters, M. D., Twohy, C. H.,Domine, Richard- F., Taillandier, A. S.,Emersic, Simpson, C., J. Connolly, W. P., Boult, S., R., Campana, M., and and Li, Z.: Severin, Investigating the discrepancy K.: Specific surface Galewsky, J. and Sobel, A.: Moist dynamics and orographic precipitation in Northern and Cen- Geever, M., O’Dowd, C. D., van Ekeren, S.,Hachikubo, Flanagan, A. R., and Nilsson, Akitaya, E.: E. E D., de Leeuw, G., Conway, H. and Raymond, C. F.: SnowCooper, stability W. A.: during Ice initiation rain, in natural J. clouds, Glaciol., Meteor. Mon., 39, 21, 29–32,Crosier, 635–642, doi:10.1175/0065-9401- J., 1993. Bower, K. N., Choularton, T. W., Westbrook, C. D., Connolly, P. J., Cui,Cziczo, Z. D. Q., J., Froyd, K. D., Hoose, C., Jensen, E.de J., Boer, Diao, G., M., Morrison, Zondlo, H., M. Shupe, A., M. Smith, D., J. and B., Hildner,DeMott, R.: P. J., Evidence of Sassen, liquid K., dependent Poellot, ice M. R., Baumgardner, D., Rogers, D. C., Brooks, S. D., Colbeck, S. C.: On the micrometeorology of surface hoar growthConen, on F., snow Rodrìguez, in S., mountainous Hüglin, area, C., Henne, S., Herrmann, E., Bukowiecki, N., and Alewell, C.: Connolly, P. J., Flynn, M. J., Ulanowski, Z., Choularton,Connolly, P. J., Möhler, T. O., Field, W., P. R., Saatho Gallagher, M. W., and 5 5 15 30 10 25 20 15 30 20 25 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ects of aerosols on precipitation from ff ects: a review, Atmos. Chem. Phys., 5, ff 25676 25675 715–737,, doi:10.5194/acp-5-715-2005 2005. 25649 orographic clouds, J. Geophys. Res.-Atmos.,25652 112, 1–13, doi:10.1029/2006JD007537, 2007. Soc., 122, 357–365, doi:10.1256/smsqj.53002, 1996. 25650 role of biological particles4-1059-2007, in 2007. cloud physics,25650 Biogeosciences, 4, 1059–1071,10.5194/bg- doi: rameterization for application in cloud62, and climate 1665–1677, models., doi:10.1175/JAS3447.1 Part 2005. I:25655, Description,25660 J. Atmos. Sci., erties of Arctic clouds106, observed 14989–15014, in 2001. May25654 and July 1998 during FIREson, ACE, J. H.: Geophys. The Res., speed, 2D-S high-resolution (stereo) probe: particledoi:10.1175/JTECH1927.1, design 2006. imaging and25654 probe, preliminary J. tests Atmos. of Ocean. ament in Tech., new tropical 23, airborne, cumulus clouds, 1462–1477, high- 14-0274.1, J. 2015. Atmos.25650 Sci., 72, 150310071420004, doi:10.1175/JAS-D- origin and distributionAMET of campaign, ice Mon. in2014. Weather cold,25650 Rev., warm, 142, and 4230–4255, occluded doi:10.1175/MWR-D-13-00396.1, frontalrington, systems R., during Crosier, the J.,crystals DI- Schlenczek, measured O., in Fugal, mixedPhys. J., phase Discuss., and 15, clouds Henneberger, 18181–18224, at25653, J.:, doi:10.5194/acpd-15-18181-2015 High-Alpine25654, The 2015. site, 25657 origins25658, Jungfraujoch,, 25651 , 25659 of Atmos.25652, 25661, ice Chem. 25665, 25669 basis functions. Part I: Basic4366, formulation,10.1175/1520-0469(1995)052<4344:POICCP>2.0.CO;2 doi: and 1995. parcel25664 model results, J. Atmos. Sci., 52,tions 4344– of Secondary,0469(1987)044<1071:FESQPO>2.0.CO;2 1987. Ice25650 Production, J. Atmos.plex topography, Cold Sci., Reg. Sci. 44, Technol.,2012. 82, 68–74, 1071–1082,25665 , doi:10.1016/j.coldregions.2012.05.008 doi:10.1175/1520- of embedded convectionric in radar, Q. warm-frontal J. mixed-phase Roy.25650 Meteor. cloud Soc., 128, from 451–476, aircraft, doi:10.1256/003590002321042054 2002. and polarimet- results from laboratory experiments, Atmos.12-9817-2012, Chem. 2012. Phys., 12,25650 9817–9854,10.5194/acp- doi: Jones, H., Latham, J.,over Cui, southwest Z., England, and Carslaw, New K.:2008. J. The Phys.,25650 development 10, of 105021, ice, doi:10.1088/1367-2630/10/10/105021 in a cumulusice cloud nucleation in25649 aqueous solutions, Nature, 406, 611–614, doi:10.1038/35020537,60, 2000. 2957–2974,, doi:10.1175/1520-0469(2003)060<2957:SOWVIC>2.0.CO;2 2003. 25687 25659, ranges. Part II: SimulationsMeteorol. of Clim., heavy 45, precipitation 1041–1055, events, doi:10.1175/JAM2390.1 over 2006. southwest25652 Germany, J. Appl. Droplet Probe (CDP) and in-flightARCPAC, Atmos. performance Meas. in Tech., 3, liquid, 1683–1706, ice doi:10.5194/amt-3-1683-2010, and 2010. mixed-phase25654 clouds during Lynn, B., Khain, A., Rosenfeld, D., and Woodley, W. L.: E Mason, B. J.: The rapid glaciation of slightlyMöhler, O., supercooled DeMott, cumulus P. J., clouds, Vali, Q. G., and J. Levin, Roy. Z.: Meteor. Microbiology and atmospheric processes:Morrison, the H., Curry, J. A., and Khvorostyanov, V. I.: A new double-moment microphysics pa- Lawson, R., Baker, B., Schmitt, C. G., and Jensen, T. L.: AnLawson, overview of R. microphysical prop- P., O’Connor, D., Zmarzly, P., Weaver, K.,Lawson, R. Baker, P., Woods, S., and B., Morrison, H.: Mo, The microphysics of Q., ice and and precipitation develop- Lloyd, Jons- G., Dearden, C., Choularton, T. W., Crosier, J., and Bower, K. N.: Observations ofLloyd, the G., Choularton, T. W., Bower, K. N., Gallagher, M. W., Connolly, P. J., Flynn, M., Far- Lohmann, U. and Feichter, J.: Global indirect aerosol e Harris-Hobbs, R. L. and Cooper, W. A.:Helbig, N. Field and Evidence Van Herwijnen, Supporting A.: Quanitative Modeling the Predic- spatialHogan, distribution R. of J., surface Field, hoar P. R., in Illingworth, com- A. J., Cotton, R. J., and Choularton,Hoose, C. T. and W.: Möhler, Properties O.: Heterogeneous ice nucleation on atmospheric aerosols: a review of Huang, Y., Blyth, A. M., Brown, P. R. A., Choularton, T.Koop, T., W., Luo, Connolly, B., Tsias, P., A., Gadian, and A. Peter, T.: Water M., activity as theKorolev, determinant A. for homogeneous V. and Mazin, I. P.: Supersaturation ofKunz, Water M. Vapor in and Clouds, Kottmeier, J. C.: Atmos. Orographic Sci., enhancement ofLance, S., precipitation Brock, C. over A., low Rogers, D., mountain and Gordon, J. A.: Water droplet calibration of the Cloud 5 5 25 30 20 15 10 20 10 15 25 30 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ecting frost nucleation, Int. ff 25678 25677 , E. W.: A year-long record of size-segregated aerosol composition at , E. W., and Martin, S.: Frost flowers: implications for tropo- ff ff ects on clouds: CRYSTAL-FACE results, Geophys. Res. Lett., 30, 1633, ff doi:10.1029/2003GL017371, 2003. 25649 simple anddoi:10.1002/2013GL058781, complex 2014. atmospheric25664 ice particles,Hazards Geophys. Earth Syst. Res. Sci., 10, Lett., 1317–1330, doi:10.5194/nhess-10-1317-2010, 2010. 41,25665 X.-Y., Wang, 1301–1307, W., and Powers,3, J. NCAR G.: Technical A Note, Description 2008. of25654 the Advanced Researchphological WRF observations Version of surface hoarRes., dynamics 46, on 1–11, a doi:10.1029/2009WR008198, mountain 2010. snow cover,25665, Water25668, Resour. 25670 Lett., 36, 20–23, doi:10.1029/2009GL037304, 2009. 25666 Allan, J., Verheggen, B., Weingartner, E.,particle Baltensperger, chemical U., composition and on the Choularton, phase T.: of Influence cold of clouds at a high-alpine site in Switzerland, spheric chemistrydoi:10.1029/2002JD002492, and 2002. 25666 ice core interpretation,zle formation J. in stably Geophys.cloud stratified condensation layer nuclei, Res.-Atmos., clouds: and ice the 107,0469(2002)059<0837:FDFISS>2.0.CO;2, initiation, role 2002. J. of Atmos. 4683, 25655 Sci., radiative 59, cooling 837–860, of doi:10.1175/1520- cloud droplets, ,doi:10.1146/annurev.earth.33.092203.122541 2005. 25648 26, 1152–1168, doi:10.1175/1520-0450(1987)026<1152:ICPBMS>2.0.CO;2, 1987. 25657, 25661, 25651 , , 25665 25668, , 25669 25670 Programme, Q. J. Roy. Meteor. Soc., 133, 811–830, doi:10.1002/qj.67, 2007. direct25649 aerosol e J. Heat Mass Tran., 46, 3797–3808,, doi:10.1016/S0017-9310(03)00194-7 2003. 25665 DeMott, P. J., Skrotzki, J., andimmersion Leisner, freezing T.: on A desert particle-surface-area-based dust parameterization particles,D-11-0249.1, of J. 2012. Atmos. Sci.,25650 69, 3077–3092, doi:10.1175/JAS- 99, 16341–16350,, doi:10.1029/94JC01194 1994. 25666 and rime chemistry inAtmos. Poland Chem., – 62, an 5–30, introductory doi:10.1007/s10874-009-9141-6, analysis 2009. from25665 meteorological perspective, J. Twohy, C. H., Prenni,cloud A. ice-crystals, Nat. J., Geosci., and 2, 398–401, Prather,, doi:10.1038/ngeo521 K. 2009. A.:25650 land, In R. M., situ Wollny, A. detectiondust G., and of as Pöschl, biological U.: ice Relative particles2009. nuclei roles of25650 in in biogenic the emissions and Amazon Saharan basin, Nat.Halley, Geosci., Antarctica, J. 2, Geophys. Res., 402–405, 108, doi:10.1038/ngeo517, 1–12, doi:10.1029/2003JD003993, 2003. 25666 ment of trailing stratiformtwo-moment schemes, precipitation Mon. in Weather a2009. Rev., 137, simulated25655 991–1007, squall, doi:10.1175/2008MWR2556.1 line: comparison of one-spectrum, Science, and 186, 632–634,, doi:10.1126/science.186.4164.632 1974. , 25650 25662 phase orographic precipitation, J. Atmos. Sci.,2009. 66,25652, 2517–2538,25655 , doi:10.1175/2009JAS3001.1 freezing of water droplets containing kaolinite,doi:10.5194/acp-11-4191-2011 particles, 2011. Atmos. Chem.25650 Phys., 11, 4191–4207, Schmitt, C. G. and Heymsfield, A. J.:Shea, C. Observational and Jamieson, quantification B.: Spatial distribution of of the surfaceSkamarock, hoar W. crystals separation C., in Klemp, of sparse J. forests, B., Nat. Dudhia, J., Gill, D. O.,Stossel, Barker, F., Guala, D. M., M., Fierz, Duda, C., M. Manes, G., C., Huang, and Lehning, M.:Style, Micrometeorological R. W. and and mor- Worster, M. G.: Frost flower formationTargino, A. on sea C., Coe, ice H., and lake Cozic, ice, J., Geophys. Crosier, Res. J., Crawford, I., Bower, K., Flynn, M., Gallagher, M., Rasmussen, R. M. R., Geresdi, I., Thompson, G., Manning, K., and Karplus, E.: Freezing driz- Roe, G. H.:Rogers, D. C. and Orographic Vali, G.: Ice crystal precipitation, production by mountain surfaces, J. Annu. Clim. Appl. Meteorol., Rotunno, Rev. R. and Houze, Earth R. A.: Lessons on Pl. orographicSassen, precipitation from K., Sc., the DeMott, Mesoscale Alpine P. J., 33, Prospero, J. M., 645–671, and Poellot, M. R.: Saharan dust storms and in- Rankin, A. M., Wol Niemand, M., Möhler, O., Vogel, B., Vogel, H., Hoose, C., Connolly, P.J., Klein, H., Bingemer, H., Perovich, D. K. and Richter-Menge, J. A.: Surface characteristics ofPolkowska, lead Z., ice, Sobik, J. M., Geophys. Res., Blas, M., Klimaszewska, K., Walna, B., and Namiesnik, J.: Hoarfrost Pratt, K. A., DeMott, P. J., French, J.Prenni, A. R., J., Wang, Petters, M. Z., D., Westphal, Kreidenweis, S. D. M., L., Heald, Heymsfield, C. L., A. Martin, J., S.Rankin, T., A. Artaxo, M. P., and Gar- Wol Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics on the develop- Mossop, S. C. and Hallett, J.: Ice crystal concentration inMuhlbauer, cumulus A. clouds: influence and of the Lohmann, drop U.: Sensitivity studies of aerosol–cloudMurray, interactions B. J., in Broadley, mixed- S. L., Wilson, T. W., Atkinson, J. D., andNa, Wills, B. R. and Webb, H.: R. Heterogeneous L.: A fundamental understanding of factors a 5 5 20 25 30 10 15 15 20 25 30 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ects on Arctic ff ects on orographic ff C, Geophys. Res. Lett., 38, L14808, ◦ 27 − > 25680 25679 1 1 − − s s 2 2 − − 3 m m 6 3 ects on simulated mixed-phase clouds and precipitation in the Alps, J. Atmos. by 10 by 10 10 10 ff Summary of WRF simulations used in this paper. Name Details ControlIN-1 Control simulation IN-3 Simulation with IN concentration increased by multiplying the Cooper SimulationSurf-6 equation with (Cooper, IN) 1986 concentration increased by multiplying Simulation the including Cooper a equation fluxSurf-3 (Cooper, of) 1986 surface crystals adapted from Xu Simulation et including al.(2013), a multiplied flux by of surface crystals adapted from Xu et al.(2013) multiplied by J. Geophys. Res., 114,, 25659 D18206,25661 , ,10.1029/2008JD011365 doi: , 25669 2009. 25670 25651, 25653, 25658, ing an improved bulk microphysicsWeather scheme. Part Rev., 132, I: Description 519–542, and, doi:10.1175/1520-0493(2004)132<0519:EFOWPU>2.0.CO;2 2004. sensitivity analysis,25656 Mon. 8502(85)90009-6, 1985. 25649 1507–1525, doi:10.1002/qj.1882, 2012. 25651 Flynn, M., Choularton,stitial T., and and the Baltensperger,,doi:10.1029/2007JD008714 condensed U.: 2007. phase Aerosol25653 in partitioning mixed-phase between clouds, the J. Geophys.cooled inter- Res., 112, liquid D23202, clouds at temperatures ,doi:10.1029/2011GL048021 2011. 25649 cloud, Q. J. Roy. Meteor. Soc., 139, 2209–2221, doi:10.1002/qj.2096, 2013. clouds and25649 precipitation using WRFSci. model Lett., with 15, a 134–139, detailed doi:10.1002/asl2.480, bin 2014. microphysics25652 scheme, Atmos. wintertime longwave cloud radiativedoi:10.1002/2013JD020554, forcing, 2013. J.25666, Geophys.25667, Res.-Atmos.,25668, 118,25680 13282–13291, aerosol e Sci., 68, 1474–1492,,10.1175/2011JAS3632.1 doi: 2011. 25652 Table 1. Thompson, G., Rasmussen, R. M., and Manning, K.: Explicit forecasts of winter precipitation us- Twomey, S.: Pollution and the planetaryVali, albedo, Atmos. Environ., G.: 8, 1251–1256, 1974. Nucleation25649 Vali, G., terminology, Leon, D., and J. Snider, J. R.: AerosolVerheggen, Ground-layer B., snow clouds, Cozic, Sci., Q. J., J. Weingartner, Roy. E., 16, Meteor. Bower, Soc., K., 138, 575–576, Mertes, S., Connolly, doi:10.1016/0021- P., Gallagher, M., Westbrook, C. D. and Illingworth, A. J.: Evidence that ice forms primarily in super- Westbrook, C. D. and Illingworth, A. J.: TheXiao, formation H., of Yin, ice Y., in Jin, a L., long-lived Chen, supercooled Q., layer and Chen, J.:Xu, Simulation L., Russell, of L. aerosol M., Somerville, e R. C. J., and Quinn, P.K.: Frost flower aerosol e Zubler, E. M., Lohmann, U., Lüthi, D., Schär, C., and Muhlbauer, A.: Statistical analysis of 5 10 15 20 25 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

02/23 (d) Titlis (a) JFJ (b) Eggishorn (c) Grimsel Hospiz

02/16 Observed E Altitude, m Model Altitude, m ◦

02/09 Time Model 25682 25681

N Longitude 02/02 ◦

01/26

0 0 0 0

A comparison of the air temperature at 4 MeteoSwiss observation stations with the −10 −20 −10 −20 −10 −20 −10 −20

C T,

Locations of Meteoswiss stations used to obtain Meteorological data throughout the ° SiteJungfraujochEggishornGrimsel HospizTitlis 46.55 Latitude, 46.57 46.43 7.99 8.33 8.09 46.77 3580 1980 2893 8.43 3330 2186 3040 2320 2337 WRF control simulation during the INUPIAQ ﬁeld campaign. Figure 1. Table 2. INUPIAQ campaign. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

02/23 02/23 (d) Titlis (a) JFJ (b) Eggishorn (c) Grimsel Hospiz (d) Titlis (a) JFJ (b) Eggishorn (c) Grimsel Hospiz

02/16 02/16 Observed Observed

02/09 02/09 Time Time Model Model 25684 25683

02/02 02/02

01/26 01/26

0 0 0 0 0 0 0 0

50 50 50 50

20 40 20 40 20 40 20 40

A comparison of the wind speed at 4 MeteoSwiss observation stations with the WRF A comparison of the Relative Humidity at 4 MeteoSwiss observation stations with the

100 100 100 100 Wind Speed, ms Speed, Wind

2DS CDP

IN−3 02/23 IN−3 23−Feb (d) Titlis (a) JFJ (b) Eggishorn (c) Grimsel Hospiz IN−1 IN−1

02/16 16−Feb Control Control Observed

a) b) 02/09 09−Feb Time Model 25686 25685

02/02 02−Feb Comparison of the CDP LWC measured at Jungfraujoch during (b)

26−Jan 01/26 Comparison of 2D-S ice number concentration measured at Jungfraujoch during

3 0 −3

0 0 0 0 0.9 0.6 0.3 1.2

A comparison of the wind direction at 4 MeteoSwiss observation stations with the gm LWC, 10 10 10

180 180 180 180

Number of Ice Crystals, l Crystals, Ice of Number −3 Wind Direction, Direction, Wind

−1 ° Figure 5. (a) the INUPIAQ campaign with the LWC from the Control, IN-1 and IN-3 WRF model simulations. the INUPIAQ campaignWRF with model the simulations. ice number concentration from the Control, IN-1 and IN-3 Figure 4. WRF control simulation during the INUPIAQ ﬁeld campaign. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

3 z,t − u compares the for IN z z,t u u (b) 23−Feb 23−Feb ) with the Korolev and z u for Control 2DS z,t u 16−Feb 16−Feb z u a) b) 09−Feb 09−Feb Control + Splinters ) with the updraft threshold calculated using the ) from the control and IN-3 WRF simulations. z t 25688 25687 , u z u Control Ice ) based on the 2D-S size distribution. 02−Feb 02−Feb z u 26−Jan 26−Jan

0 5

−2 −4 2 0

4 2 0 −2 −4 20 15 10

Updraft Speed, ms Speed, Updraft compares the updraft speeds measured at Jungfraujoch (

10 10 10 10

−1 10 10 10 10 10

Analysis of updraft speed with the updraft threshold required for the presence of Updraft Speed, ms Speed, Updraft

Number of Ice Crystals, l Crystals, Ice of Number Comparison of ice number concentrations from the WRF control simulation, the con- −1 −1 (a) Figure 7. trol simulation with the additionculated using of Eq. rime (4), splinters and producedgrey the shaded by 2D-S areas the probe indicate Hallett–Mossop at periods process Jungfraujochis where during cal- at the the least ice INUPIAQ a Campaign. number factor The concentration of including 10 the greater splinters than the concentration from the WRF control simulation. Mazin(2003) updraft thresholdsimulated ( updraft speed at Jungfraujoch ( mixed-phase cloud, as(2003). deﬁned by Eq. (2), which is adapted taken from ﬁrstKorolev moment and of the Mazin ice size distributions ( Figure 6.

Altitude, m Altitude,

Splinters, l Splinters,

−1

IWC, gm IWC, IWC, gm IWC,

−4 −3 −3 −3 4000 3000 2000 4 2 0 0.3 0.2 0.1 0 2 1 0 100 50 0 3500 3000 2500 x 10 x 10 JFJ JFJ 09:00 19:00 Liquid water content and (b) (c) (d) (a) (a) (d) (b) (c) (b) 08:54 18:54 C isotherm. Temperature and altitude along the back ◦ 8 08:48 18:48 − (a) Ice number concentration from the WRF con- Time Time (c) 25690 25689 Vertical wind velocity along the back trajectory. 08:42 18:42 (d) 08:36 18:36

0 2 1 0 5 0 1 0 3 2 1 0 5 0 1

18:30 08:30

ice

−5 ice −5

−5

0.5

, l ,

Upwind n , l ,

Upwind n

−10 −15 z

−10 −15 −20

LWC, gm LWC,

−1 −1 , ms , u

, ms , u

C Temperature,

Temperature, Temperature, C

−3 Variations in dynamical and microphysical properties along a back trajectory of air −3 −1

−1 As for Fig.8 but from the WRF simulation of 26 January 2014 at 09:00 Z. ° ° Figure 9. ice water content alongtrol the run back along trajectory. thetrajectory, back calculated using trajectory, and Eq. (4). the cumulative number of splinters produced along the Figure 8. between a point upwindassuming of a the measurement constant site windlation and ﬁeld. output Jungfraujoch The itself of constant on the wind 1 1 ﬁeld February February is 2014, 2014 taken at from 19:00 the Z. WRF control simu- trajectory, with the red dashed line illustrating the Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

2DS CDP 23−Feb 23−Feb Surf−6 Surf−6 Surf−3 Surf−3 2DS 16−Feb 16−Feb Control Control a) b) Control Frozen 09−Feb 09−Feb 25692 25691 Control Ice 02−Feb 02−Feb Comparison of measured LWC at Jungfraujoch during the INUPIAQ 26−Jan 26−Jan (b)

Comparison of measured 2D-S ice number concentration at Jungfraujoch during

0 0 −3 6 3 3 0 −3

1.2 0.9 0.6 0.3 Comparison of measured 2D-S ice number concentration at Jungfraujoch during

10 10 10 10 gm LWC,

10 10 10 Number of Ice Crystals, l Crystals, Ice of Number

−3 Number of Ice Crystals, l Crystals, Ice of Number

−1 −1 Figure 11. (a) the INUPIAQ campaign with theSurf-3 concentration from and the Surf-6 control simulations WRFculated model which using simulation, included Eq. and the (5). the addition of crystals from a surface flux cal- Campaign with the LWCsimulations, which from included the the control additionindicates of WRF the crystals time-period model from of simulation, a the surface and cross flux. sections the The plotted black-dashed Surf-3 in lines and Figs. 12 Surf-6 and . 13 the INUPIAQ campaign with theby ice the concentration control and WRF the model total simulation frozen concentration at measured Jungfraujoch. Figure 10. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | represents (a) represents an east-west represents a north-south (b) (c) . (b, c) 25694 25693 Latitude, with red dashed line indicating the horizontal cross- Longitude, with red dashed line indicating the horizontal cross- ◦ ◦ , and blue contours indicating isotherms in kelvin. , and blue contours indicating isotherms in kelvin. In all 3 figures the location of Ice number concentrations at 20:00 Z on 13 February 2014 from WRF model sim- As Fig. 12 except for LWC at 20:00 Z on 13 February 2014. (a) (a) Figure 13. a horizontal cross-section atdashed the lines height representing of the Jungfraujoch vertical in reality cross-sections (3570 in ma.s.l.), with the red section in Jungfraujoch is represented by the red star. Figure 12. ulation including the addition of crystals from the surface crystal flux in 3vertical views. cross-section at 46.55 vertical cross-section at 7.98 section in