1. ECMWF Training Course Adrian Tompkins
May 2001
Numerical Weather Prediction Parametrization of diabatic processes Cloud Parametrization
Adrian Tompkins
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2. Outline LECTURE 1: Introduction to Cloud Issues
ECMWF Training Course
May 2001
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
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3. GCMs: Issues and approaches

4. Clouds in GCMs - What are the problems ?
ECMWF Training Course
May 2001
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
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5. Macroscale Issues of Parameterization
ECMWF Training Course
May 2001
Macroscale Issues of Parameterization
VERTICAL COVERAGE
Most models assume that this is 1
~500m
~100km
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
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6. Macroscale Issues of Parameterization
ECMWF Training Course
May 2001
Macroscale Issues of Parameterization
HORIZONTAL COVERAGE, a
~500m
~100km
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7. Macroscale Issues of Parameterization
ECMWF Training Course
May 2001
Macroscale Issues of Parameterization
Vertical Overlap of cloud
Important for Radiation and Microphysics Interaction
~500m
~100km
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8. Macroscale Issues of Parameterization
ECMWF Training Course
May 2001
Macroscale Issues of Parameterization
In cloud inhomogeneity in terms of cloud particle size and number
~500m
~100km
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9. Macroscale Issues of Parameterization
ECMWF Training Course
May 2001
Macroscale Issues of Parameterization
Just these issues can become very complex!!!
~500m
~100km
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10. Clouds in GCMs - What are the problems ?
ECMWF Training Course
May 2001
Clouds in GCMs - What are the problems ?
radiation
convection
microphysics
turbulence
dynamics
Clouds are the result of complex interactions between a large number of processes
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11. Clouds in GCMs - What are the problems ?
ECMWF Training Course
May 2001
Clouds in GCMs - What are the problems ?
Many of these processes are only poorly understood - For example, the interaction with radiation
Cloud top and base height
Cloud fraction and overlap
Amount of condensate
Cloud-radiation interaction
In-cloud conden-sate distribution
Cloud environment
Phase of condensate
Cloud particle shape
Cloud particle size
Cloud macrophysics
Cloud microphysics
“External” influence
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12. What do we want to represent?
Complexity
small ice
Medium ice
Large ice
Ice Mass
Liquid Mass
Ice mass
Ice number
Cloud
Mass
“Single Moment”
Schemes
“Double Moment”
Schemes
“Spectral/Bin”
Microphysics
Most GCMs only have simple single-moment schemes

13. NOT DISTINCT - CAN HAVE MIXTURE OF APPROACHES
ECMWF Training Course
May 2001
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), ql.
Diagnostic approach
Prognostic approach
NOT DISTINCT - CAN HAVE MIXTURE OF APPROACHES
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14. Cloud microphysical processes
ECMWF Training Course
May 2001
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
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15. Microphysical processes and water substances
ECMWF Training Course
May 2001
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)
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16. Microphysics: Complex System!
Overview of
Warm Phase Microphysics T>273K
Mixed Phase Microphysics 235K<T<273K
Pure ice Microphysics T<235K

17. Droplet Classification

18. Nucleation of Water: Homogeneous Nucleation
ECMWF Training Course
May 2001
Nucleation of Water: Homogeneous Nucleation
Drop of pure water forms from vapour
Kelvin’s formula for critical radius for initial droplet to be “survive”
strongly dependent on supersaturation
requires several hundred percent supersaturation (not observed in the atmosphere),
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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
equilibrium
e/es
“Solution term”
Reduction in vapour pressure due to dissolved substance

21. Diffusion growth (water)
ECMWF Training Course
May 2001
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 mm
rain drops are much larger than that
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
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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
ECMWF Training Course
May 2001
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
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24. Parameterizating “Autoconversion” of cloud drops to raindrops
ECMWF Training Course
May 2001
Parameterizating “Autoconversion” of cloud drops to raindrops
Autoconversion (Kessler, AMS monogram 1969) ql
qlcrit Gp
Sundqvist, QJRMS, 1978
what are the issues for data assimilation? ql
qlcrit Gp
“Non-local” collection
P=Precipitation Flux
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25. Schematic of Warm Rain Processes
Coalescence
~10 microns
RH>100.6%
“Activation”
Diffusional
Growth
Heterogeneous Nucleation
RH>78% (Haze)
CCN
Different fall speeds

26. Ice Nucleation Ice processes complex and poorly understood
Droplets do not freeze at 0oC!
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 –40oC (often used assumption in microphysical schemes).
Frequent observation of ice above these temperatures indicates role for heterogeneous processes

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

28. Heterogeneous Nucleation

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

30. Mixed Phase clouds: Bergeron Process (I)
ECMWF Training Course
May 2001
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 !
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31. Ice particles grow at the expense of water droplets
ECMWF Training Course
May 2001
Bergeron process (II)
Ice particle enters water cloud
Ice particles grow at the expense of water droplets
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
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32. Modification of Sundqvist to take Bergeron Process into account
ECMWF Training Course
May 2001
Modification of Sundqvist to take Bergeron Process into account
Sundqvist, QJRMS, 1978 ql
qlcrit Gp
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
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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

35. Aggregation and Riming: Simple stratified picture

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

37. 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

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
aircraft
ECMWF resolved motions only

40. 3000 km supersaturated segment observed ahead of front
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.
3000 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’
22nd April 2003: Modis Image from

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

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

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
ECMWF Training Course
May 2001
Cloud Schemes - A Brief History
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46. Simple Bulk Microphysics
ECMWF Training Course
May 2001
Simple Bulk Microphysics
VAPOUR (prognostic)
Evaporation
Condensation
CLOUD (prognostic)
Evaporation
Autoconversion
RAIN (diagnostic)
WHY?
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47. Microphysics - a “complex” GCM scheme
ECMWF Training Course
May 2001
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
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48. Cloud Cover: Why Important?
ECMWF Training Course
May 2001
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 ql
The incloud mass mixing ratio is ql/a
a small
GCM grid box
a large
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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