Numerical Weather Prediction Parametrization of Diabatic Processes Clouds (1) Cloud Microphysics

1. Numerical Weather Prediction Parametrization of Diabatic ProcessesClouds (1)Cloud Microphysics Richard Forbes and Adrian Tompkins forbes@ecmwf.int

3. Outline • LECTURE 1: Cloud Microphysics • Overview of GCM cloud parametrization issues • Microphysical processes 2.1 Warm phase 2.2 Cold phase • Summary • LECTURE 2: Cloud Cover in GCMs • LECTURE 3: The ECMWF Cloud Scheme • LECTURE 4: Validation of Cloud Schemes

4. 1. Overview of GCM Cloud Parametrization Issues

5. The Importance of Clouds 1. Water Cycle 2. Radiative Impacts 3. Dynamical Impacts

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

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

8. Cloud Parametrization Issues: • Microphysical processes • Macro-physical • subgrid heterogeneity • Numerical issues

9. Cloud Parametrization Issues:Which quantities to represent ? • Cloud water droplets • Rain drops • Pristine ice crystals • Aggregate snow flakes • Graupel pellets • Hailstones • Note for ice phase particles: Additional latent heat. Terminal fall speed of ice hydrometeors significantly less (lower density). Optical properties are different (important for radiation).

10. Small ice Ice Mass Ice mass Medium ice Liquid Mass Ice number Large ice Cloud Parametrization Issues:Complexity ? Complexity Cloud Mass “Single Moment” Schemes “Double Moment” Schemes “Spectral/Bin” Microphysics Most GCMs only have simple single-moment schemes

11. Cloud Parametrization Issues:Diagnostic or prognostic variables ? Cloud condensate mass (cloud water and/or ice), ql. Diagnostic approach Prognostic approach Sources Sinks Advection + sedimentation CAN HAVE MIXTURE OF APPROACHES

12. Simple Bulk Microphysics VAPOUR (prognostic) Evaporation Condensation CLOUD (prognostic) Evaporation Autoconversion RAIN (diagnostic) Why ?

13. Microphysics - a “complex” GCM scheme Fowler et al., JCL, 1996 Similar complexity to many schemes in use in CRMs

14. 2. Microphysical Processes

15. 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 • Nucleation of water droplets and ice crystals from water vapour • Diffusional growth of cloud droplets (condensation) and ice crystals (deposition) • Collection processes for cloud drops (collision-coalescence), ice crystals (aggregation) and ice and liquid (riming) leading precipitation sized particles • The advection and sedimentation (falling) of particles • the evaporation/sublimation/melting of cloud and precipitation size particles

16. Microphysics: A complex system! • Overview of • Warm Phase Microphysics T > 273K • Mixed Phase Microphysics ~250K < T < 273K • Pure ice Microphysics T < ~250K

17. 2. Microphysical Processes 2.1 Warm Phase

18. Droplet Classification

19. Nucleation of cloud droplets:Important effects for particle activation Planar surface: Equilibrium when e=es and number of molecules impinging on surface equals rate of evaporation Surface molecule has fewer neighbours Curved surface: saturation vapour pressure increases with smaller drop size since surface molecules have fewer binding neighbours.

20. Nucleation of cloud droplets:Homogeneous Nucleation • Drop of pure water forms from vapour • Small drops require much higher super saturations • Kelvin’s formula for critical radius for initial droplet to “survive” • Strongly dependent on supersaturation • Would require several hundred percent supersaturation (not observed in the atmosphere).

21. Nucleation of cloud droplets:Heterogeneous Nucleation • Collection of water molecules on a foreign substance, RH > ~80% (Haze particles) • These (hydrophilic) soluble particles are called Cloud Condensation Nuclei (CCN) • CCNalways present in sufficient numbers in lower and middle troposphere • Nucleation of droplets (i.e. from stable haze particle to unstable regime of diffusive growth) at very small supersaturations.

22. Nucleation of cloud droplets:Important effects for particle activation Planar surface: Equilibrium when e=es and number of molecules impinging on surface equals rate of evaporation Surface molecule has fewer neighbours Curved surface: saturation vapour pressure increases with smaller drop size since surface molecules have fewer binding neighbours. Effect proportional to 1/r (curvature effect) Dissolved substance reduces vapour pressure Presence of dissolved substance: saturation vapour pressure reduces with smaller drop size due to solute molecules replacing solvent on drop surface (assuming esollute<ev) Effect proportional to 1/r3 (solution effect)

23. “Curvature term” Small drop – high radius of curvature easier for molecule to escape “Solution term” Reduction in vapour pressure due to dissolved substance Nucleation of cloud droplets:Heterogeneous Nucleation Haze particle in equilibrium e/es equilibrium

24. Diffusional growthof cloud water 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 mm • Rain drops are much larger • drizzle: 50 to 100 mm • rain: >100 mm • Other processes must also act in precipitating clouds For r > 1 mm and neglecting diffusion of heat D=Diffusion coefficient, S=Supersaturation Note inverse radius dependency

25. CollectionCollision-coalescence of water drops Drops of different size move with different fall speeds - collision and coalescence Large dropsgrow 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 (differential evaporation), giant CCNs ? Rain drop shape Chuang and Beard (1990)

26. 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). These often assume more CCN in polluted air over land.

27. Microphysical Parametrization “Autoconversion” of cloud drops to raindrops Gp qlcrit ql Gp ql qlcrit Kessler • Linear function of ql (Kessler, 1969) • Function of ql with additional term to avoid singular threshold and non-local precipitation term (Sundqvist 1978) • Or, for example, for a more complex double-moment parametrization (Seifert and Beheng,2001), derived directly from the stochastic collection equation. Sundqvist Microphysics - ECMWF Seminar on Parametrization 1-4 Sep 2008 27

28. RH>100.6% “Activation” Diffusional Growth CCN ~10 microns Coalescence Different fall speeds Schematic of Warm Rain Processes Heterogeneous Nucleation RH>78% (Haze)

29. 2. Microphysical Processes2.2 Cold Phase

30. Kepler (1611) “On the Six-Cornered Snowflake”

31. “The Six-Cornered Snowflake” www.snowcrystals.com Ken Libbricht

32. Ice Microphysical Processes • Ice nucleation • Depositional Growth (and sublimation) • Collection (aggregation/riming) • Splintering • Melting

33. Ice Nucleation Droplets do not freeze at 0oC ! Ice nucleation processes can also be split into Homogeneous and Heterogeneous processes, but complex and not well understood. Homogeneous freezing of water droplets occurs below about -38oC, Homogeneous nucleation of ice crystals dependent on a critical relative humidity (fn of T, Koop et al. 2000). Frequent observation of ice between 0oC and colder temperatures indicates heterogeneous processes active. Number of activated ice nuclei increases with decreasing temperature. • Observations: • < -20oC Ice free clouds are rare • > -5oC ice is unlikely (unless ice falling from above!) • ice supersaturation ( > 10% ) observations are common Fletcher 1962

34. Ice Nucleation:Heterogeneous nucleation I will not discuss heterogeneous ice nucleation in great detail in this course due to lack of time and the fact that these processes are only starting to be tackled in Large-scale models. See recent work of Ulrike Lohmann for more details aerosol Supercooled drop

35. 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

36. Diffusional growth of ice crystalsDeposition Equation for the rate of change of mass for an ice particle of diameter D due to deposition (diffusional growth), or evaporation • Deposition rate depends primarily on • the supersaturation, s • the particle shape (habit), C • the ventilation factor, F • The particular mode of growth (edge growth vs corner growth) is sensitive to the temperature and supersaturation

37. Diffusional growth of ice crystalsIce Habits Ice habits can be complex, depend on temperature: influences fall speeds and radiative properties http://www.its.caltech.edu/~atomic/snowcrystals/

38. Diffusional growth of ice crystalsAnimation

39. 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 ! Homogeneous Freezing Temperature Ice Saturation Water Saturation Diffusional growth of ice crystalsMixed Phase Clouds: Bergeron Process (I)

40. Diffusional growth of ice crystalsMixed phase cloud Bergeron process (II) Ice particles grow at the expense of water droplets Ice particle enters water cloud Cloud is supersaturated 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

41. Ice crystals can aggregate together to form “snow” “Sticking” efficiency increases as temperature exceeds –5C Irregular crystals are most commonly observed in the atmosphere (e.g. Korolev et al. 1999, Heymsfield 2003) Collection processes:Ice Crystal Aggregation CPI Model Westbrook et al. (2008) 500 mm Field & Heymsfield ‘03 T=-46oC Lawson, JAS’99

42. Parametrization of ice crystal diffusion growth and aggregation • Some schemes represent ice processes very simply, removing ice super-saturation (as for warm rain process). • Others, have a slightly more complex representation allowing ice supersaturation (e.g. current ECMWF scheme). • Increasingly common are schemes which represent ice, supersaturation and the diffusional growth equation, and aggregation represented as an autoconversion to snow or parametrization of an evolving particle size distribution (e.g. Wilson and Ballard, 1999). See Lohmann and Karcher JGR 2002(a,b) for another example of including ice microphysics in a GCM. 42

43. Collection processes:Riming – capture of water drops by ice Graupel formed by collecting liquid water drops in mixed phased clouds (“riming”), particulaly when at water saturation in strong updraughts (convection). Round ice crystals with higher densities and fall speeds than snow dendrites Hail forms if particle temperature close to 273K, 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

44. Rimed Ice Crystals http://www.its.caltech.edu/~atomic/snowcrystals

45. Rimed Ice Crystal emu.arsusda.gov

46. Heavily Rimed Ice Crystal emu.arsusda.gov

47. Parametrization of rimed ice particles • Most GCMs with parametrized convection don’t explicitly represent graupel or hail (too small scale) • In cloud resolving models, traditional split between ice, snow and graupel and hail but this split is rather artificial. • Degree of riming can be light or heavy. • Alternative approach: • Morrison and Grabowski (2008) have three ice prognostics, ice number concentration, mixing ratio from deposition, mixing ratio from riming. • Avoids artificial thresholds between different categories. 47

48. Other microphysical processesSplintering, Shedding Evaporation, Melting Other processes include evaporation (reverse of condensation), ice sublimation (reverse of deposition) and melting. Shedding: Large rain drops break up – shedding to form smaller drops, places a limit on rain drop size. Splintering of ice crystals, Hallet-Mossop splintering through riming around -5°C. Leads to increased numbers of smaller crystals.

49. Particle Size Distributions Size Distribution Mass Distribution From Fleishauer et al (2002, JAS) Field (2000), Field and Heymsfield (2003)

50. Falling Precipitation • Need to know size distribution • For ice also affected by ice habit • Poses problem for numerics Courtesy: R Hogan, U. Reading From R Hogan www.met.rdg.ac.uk/radar