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Numerical Weather Prediction Parametrization of diabatic processes Cloud Parametrization Adrian Tompkins.

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Presentation on theme: "Numerical Weather Prediction Parametrization of diabatic processes Cloud Parametrization Adrian Tompkins."— Presentation transcript:

1 Numerical Weather Prediction Parametrization of diabatic processes Cloud Parametrization Adrian Tompkins

2 Outline LECTURE 1: Introduction to Cloud Issues –Physical processes to represent –What are the potential problems in GCMs? –History of cloud schemes LECTURE 2: Cloud Cover in GCMs LECTURE 3: The ECMWF cloud scheme LECTURE 4: Validation of cloud schemes

3 GCMs: Issues and approaches

4 Clouds in GCMs - What are the problems ? Many of the observed clouds and especially the processes within them are of subgrid-scale size (both horizontally and vertically) GCM Grid cell km

5 ~500m ~100km Macroscale Issues of Parameterization VERTICAL COVERAGE Most models assume that this is 1 This can be a poor assumption with coarse vertical grids. Many climate models still use fewer than 30 vertical levels currently, some recent examples still use only 9 levels

6 ~500m ~100km Macroscale Issues of Parameterization HORIZONTAL COVERAGE, a

7 ~500m ~100km Macroscale Issues of Parameterization Vertical Overlap of cloud Important for Radiation and Microphysics Interaction

8 ~500m ~100km Macroscale Issues of Parameterization In cloud inhomogeneity in terms of cloud particle size and number

9 ~500m ~100km Macroscale Issues of Parameterization Just these issues can become very complex!!!

10 Clouds in GCMs - What are the problems ? convection Clouds are the result of complex interactions between a large number of processes radiation turbulence dynamics microphysics

11 Clouds in GCMs - What are the problems ? Many of these processes are only poorly understood - For example, the interaction with radiation Cloud-radiation interaction Cloud macrophysicsCloud microphysicsExternal influence Cloud fraction and overlap Cloud top and base height Amount of condensate In-cloud conden- sate distribution Phase of condensate Cloud particle size Cloud particle shape Cloud environment

12 What do we want to represent? Ice mass Ice number small ice Medium ice Large ice Most GCMs only have simple single-moment schemes Ice Mass Liquid Mass Cloud Mass Complexity Single Moment Schemes Double Moment Schemes Spectral/Bin Microphysics

13 Clouds in GCMs - How ? Main variables: Cloud fraction, a - refers to horizontal cover since cloud fills vertical Cloud condensate mass (cloud water and/or ice), q l. Diagnostic approach Prognostic approach NOT DISTINCT - CAN HAVE MIXTURE OF APPROACHES

14 Cloud microphysical processes We would like to include into our models: –Formation of clouds –Release of precipitation –Evaporation of both clouds and precipitation Therefore we need to describe –the change of phase from water vapour to water droplets and ice crystals –the transformation of small cloud droplets/ice crystals to larger rain drops/ice particles –the evaporation/sublimation of cloud and precipitation size particles

15 Microphysical processes and water substances Nucleation of particles Diffusion growth Collision-Coalescence Collection Breakup of drops Sedimentation Ice enhancement Melting Evaporation/sublimation Involving: Water vapour Cloud liquid water Precipitation liquid water Cloud ice Precipitation ice Processes Uncertain - Parameterization often highly simplified Reference: Microphysics of Clouds and Precipitation by H.R.Pruppacher and J. D. Kett and A short course in Cloud Physics by Rogers and Yau (all subsequent diagrams from latter text unless otherwise stated)

16 Microphysics: Complex System! Overview of (1)Warm Phase Microphysics T>273K (2)Mixed Phase Microphysics 235K

17 Droplet Classification

18 Nucleation of Water: Homogeneous Nucleation Drop of pure water forms from vapour Kelvins formula for critical radius for initial droplet to be survive strongly dependent on supersaturation requires several hundred percent supersaturation (not observed in the atmosphere),

19 Nucleation of Water: Heterogeneous Nucleation Collection of water molecules on a foreign substance, RH > ~80% (Haze particles) (Note, not same when drying) Particles are called Cloud Condensation Nuclei (CCN) CCN always present in sufficient numbers in lower and middle troposphere Activation at supersaturations of <1% Therefore we assume that condensation occurs if RH>100% (n.b. deep convection)

20 Heterogeneous Nucleation Curvature term Small drop – high radius of curvature easier for molecule to escape Solution term Reduction in vapour pressure due to dissolved substance e/e s equilibrium

21 Diffusion growth (water) Nucleation small droplets once droplet is activated, water vapour diffuses towards it = condensation reverse process = evaporation droplets that are formed by diffusion growth attain a typical size of 0.1 to 10 m rain drops are much larger than that –drizzle: 50 to 100 m –rain: >100 m other processes must also act in precipitating clouds For r > 1 m and neglecting diffusion of heat D=Diffusion coefficient, S=Supersaturation Note inverse radius dependency

22 Parameterizing Nucleation and droplet growth Nucleation: Since Activation occurs at supersaturations less than 1% most schemes assumes all supersaturation is immediately removed as liquid water Note that this assumption means that models can just use one prognostic equation for the total water mass, the sum of vapour and liquid Usually, the growth equation is not explicitly solved, and in single-moment schemes simple (diagnostic) assumptions are made concerning the droplet number concentration when needed (e.g. radiation)

23 Collision-Coalescence Drops of different size move with different fall speeds - collision and fusion large drops grow at the expense of small droplets Collection efficiency low for small drops process depends on width of droplet spectrum and is more efficient for broader spectra - Paradox large drops can only be produced in clouds of large vertical extent – Aided by turbulence and entrainment important process for low latitudes where deep clouds of high water content are present

24 Parameterizating Autoconversion of cloud drops to raindrops Autoconversion (Kessler, AMS monogram 1969) qlql q l crit GpGp Sundqvist, QJRMS, 1978 qlql q l crit GpGp Non-local collection P=Precipitation Flux what are the issues for data assimilation?

25 Heterogeneous Nucleation RH>78% (Haze) Schematic of Warm Rain Processes CCN ~10 microns RH>100.6%ActivationDiffusionalGrowth Different fall speeds Coalescence

26 Ice Nucleation Ice processes complex and poorly understood Droplets do not freeze at 0 o C! Can also be split into Homogeneous and Heterogeneous processes Processes depend on temperature and history of cloud Homogeneous freezing of water droplet occurs between –35 and –40 o C (often used assumption in microphysical schemes). Frequent observation of ice above these temperatures indicates role for heterogeneous processes

27 Ice Nucleation Spontaneous freezing of liquid droplets smaller than 5 m requires temperature less than - 40 o C. Observations of liquid in cloud are common at - 20 o C. Ice crystals start to appear in appreciable numbers below around -15 o C. Heterogenous Nucleation responsible: Process less clear Ice nuclei: Become active at various temperatures less than 0 o C, many fewer Observations: –< -20 o C Ice free clouds are rare – > 5 o C ice is unlikely –ice supersaturation ( > 10% ) observations are common Fletcher 1962

28 Heterogeneous Nucleation

29 Ice Habits Ice habits can be complex, depends on temperature: influences fall speeds and radiative properties

30 Mixed Phase clouds: Bergeron Process (I) The saturation water vapour pressure with respect to ice is smaller than with respect to water A cloud, which is saturated with respect to water is supersaturated with respect to ice !

31 Bergeron process (II) Ice particle enters water cloud Cloud is supersturated with respect to ice Diffusion of water vapour onto ice particle Cloud will become sub-saturated with respect to water Water droplets evaporate to increase water vapour Ice particles grow at the expense of water droplets

32 Modification of Sundqvist to take Bergeron Process into account Sundqvist, QJRMS, 1978 qlql q l crit GpGp Collection Bergeron Process Otherwise, most schemes have neglected ice processes, removing ice super- saturation al la Warm rain – See Lohman and Karcher JGR 2002(a,b) for first attempts to include ice microphysics in GCM

33 Aggregation Ice crystals can aggregate together to form snow Temperature dependent, process increases in efficiency as temperature exceeds –5C, when ice surface becomes sticky Also a secondary peak between –10 and –16C when dendrite arms get entangled

34 Riming If vapour exceeds the water saturation mixing ratio, water can condense on ice crystal, and then subsequently freeze to form graupel: Round ice crystals with higher densities and fall speeds than snow dendrites Graupel and Hail are also formed by aggregating liquid water drops in mixed phased clouds (riming) –If the Latent heat of condensation and fusion keeps temperature close to 273K, then high density hail particle forms, since the liquid water spreads out before freezing. Generally referred to as Hail – The higher fall speed (up to 40 m/s) imply hail only forms in convection with strong updraughts able to support the particle long enough for growth snowcrystals/

35 Aggregation and Riming: Simple stratified picture

36 Ice Habits Ice habits can be complex: influences fall speeds and radiative properties From Fleishauer et al 2002, JAS Note shape/diameter distribution not monotonic with height, Turbulence!

37 Falling Precipitation Need to know size distribution For ice also affected by ice habit Poses problem for numerics From R Hogan Courtesy: R Hogan, U. Reading

38 Pure ice Phase: Homogeneous Ice Nucleation At cold temperature (e.g. upper troposphere) difference between liquid and ice saturation vapour pressures is large. If air mass is lifted, and does not contain significant liquid particles or ice nuclei, high supersaturations with respect to ice can occur, reaching 160 to 170%. Long lasting contrails are a signature of supersaturation Institute of Geography, University of Copenhagen

39 Homogeneous/heterogeneous nucleation However even in polluted NH air, homogeneous nucleation can dominate in strong updraughts However wind fluctuations can occur on mesoscale length-scales comparible or smaller to grid length. –Upscale cascade from turbulence –Gravity waves –Subgrid instabilities (cloud top instabilities)…… It is clear that models are deficient in representing these E.g: Lohmann shows inadequacy of ECMWF model, and how enhancement of turbulence activity can produce improved spectra From haag and Kaerchner ECMWF resolved motions only aircraft

40 Limb Sounder and Mozaic Data (Pictures courtesy of Klaus Gierens and Peter Spichtinger, DLR) Recent observations (e.g. Mozaic aircraft and Microwave sounders) have revealed such values are common km supersaturated segment observed ahead of front

41 Heteorogeneous Nucleation On the other hand, in air polluted by organic and mineral dust, supersaturation achieve perhaps 130%. Research is ongoing to determine the nature of ice nuclei at these colder temperatures This process probably more prevalent in NH where air is less clean 22 nd April 2003: Modis Image from

42 Summary: Warm Cloud E.g: Stratocumulus Condensation (Rain formation - Fall Speeds - Evaporation of rain) Evaporation

43 Summary: Deep Convective Cloud Precipitation Falls Speeds Evaporation in Sub-Cloud Layer Heteorogeneous Nucleation of ice Splintering/Bergeron Process Melting of Snow and Graupel

44 Summary: Cirrus cloud Homogeneous Nucleation (representation of supersaturation) Heterogeneous Nucleation (representation of nuclei type and concentration) Sedimentation of Ice crystals? Size distribution and formation of snow?

45 Cloud Schemes - A Brief History

46 Simple Bulk Microphysics VAPOUR (prognostic) CLOUD (prognostic) RAIN (diagnostic) WHY? Evaporation Autoconversion Evaporation Condensation

47 Microphysics - a complex GCM scheme Fowler et al., JCL, 1996 Similar complexity to many schemes in use in CRMs Mostly treated as instant No supersaturation assumption Threshold linear or exponential terms with efficiency adjustments

48 Cloud Cover: Why Important? In addition to the influence on radiation, the cloud cover is important for the representation of microphysics Imagine a cloud with a liquid condensate mass q l The incloud mass mixing ratio is q l /a a large a small GCM grid box precipitation not equal in each case since autoconversion is nonlinear Reminder: Autoconversion (Kessler, 1969 ) Complex microphysics perhaps a wasted effort if assessment of a is poor

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