1. Clouds Liquid water mixing ratio Liquid water density of clouds
Cloud droplet distribution
Number density N (D):
the number of droplets per nit
volume (concentration) in an
interval D + ΔD

2. Liquid water content
Cloud distribution is skewed

3. Normal distribution
PDF
CDF
PDF
CDF

4. Skewed distribution
Skewness
Normal distribution
Kurtosis
Normal distribution

5. Beta distribution

6. Beta distribution

7. Gamma distribution

8. Gamma distribution
CDF
PDF

9. Lognormal distribution

10. Lognormal distribution

11. Satellite View of Clouds
Global Cloud system
Satellite View of Clouds
Polar orbit satellite
Geostationary Satellites

12. subsidence St & Sc Cu St & Sc Stratus and stratocumulus Transition
Trade wind inversion
Stratus and stratocumulus
Transition
Trade cumulus
Intertropiccal Convergence Zone (ITCZ)

14. Deep convective clouds (cumulus clouds)

15. Stratocumulus clouds

16. Vertical structure of stratocumulus cloudsLW
radiative
cooling
evaporative
cooling

17. Cloud-Radiation-climate feedback
Cooling effect
Warming effect

18. NASA: The Earth Radiation Budget Experiment (ERBE)
It measures the energy budget at the top of the atmosphere.
Energy budget at the top of atmosphere (TOA)
Incoming solar radiation 340 W/m2
Incoming solar radiation 340 W/m2
Reflected SW radiation
Q1= W/m2
Reflected SW radiation
Q= W/m2
Fictitious
climate
system
shortwave cloud forcing
dQ=Q1-Q=-50 W/m2 (cooling)
Present
climate
system
Emitted LW radiation
F1= 270 W/m2
Emitted LW radiation
F= 240 W/m2
with clouds
No clouds
longwave cloud forcing
dF=F1-F=30 W/m2 (warming)

19. SW cloud forcing = clear-sky SW radiation – full-sky SW radiation
LW cloud forcing = clear-sky LW radiation – full-sky LW radiation
Net cloud forcing (CRF) = SW cloud forcing + LW cloud forcing
Current climate: CRF = -20 W/m2 (cooling)
But this does not mean clouds will damp global warming! The impact of clouds on global warming depends on how the net cloud forcing changes as climate changes.
Direct radiative forcing due to doubled CO2, G = 4 W/m2

20. e.g.
If the net cloud forcing changes from -20 W/m2 to -16 W/m2 due to doubling CO2, the change of net cloud forcing will add to the direct CO2 forcing. The global warming will be amplified by a fact of 2.
Cloud radiative effects depend on cloud distribution, height, and optical properties.
Low cloud
High cloud
SW cloud forcing dominates
LW cloud forcing dominates

21. In GCMs, clouds are not resolved and have to be parameterized empirically in terms of resolved variables.
water vapor (WV) cloud surface albedo lapse rate (LR) WV+LR ALL

22. Aerosol feedback
Direct aerosol effect: scattering, reflecting, and absorbing solar radiation by particles.
Primary indirect aerosol effect (Primary Twomey effect): cloud reflectivity is enhanced due to the increased concentrations of cloud droplets caused by anthropogenic cloud condensation nuclei (CNN).
Secondary indirect aerosol effect (Second Twomey effect):
1. Greater concentrations of smaller droplets in polluted clouds reduce cloud precipitation efficiency by restricting coalescence and result in increased cloud cover, thicknesses, and lifetime.

23. 2. Changed precipitation pattern could further
affect CCN distribution and the coupling between diabatic processes and cloud dynamics.

24. How precipitation forms
Frictional force
Frictional force = Gravitational force
Terminal velocity
Gravitational force

25. Bergeron Process Mixed phase clouds
Supercooled water: To make the transition from a liquid to the lattice structure of ice, some foreign particles, ice nuclei, are needed to initiate freezing. Until the nuclei form, liquid water can exist far below the freezing point. In fact, pure water droplets can remain in liquid form near -40F.
Mixed phase clouds
Ice crystal: molecules more
organized, difficult to escape
Supercooled droplet: molecules less organized, easy to escape
evaporate
condensate
At a certain condition, cloudy air is unsaturated to supercooled water droplet, but is saturated to ice crystal, leading to evaporation of supercooled water droplet and growth of ice crystal.

26. 1. Supercooled water droplets are readily to freeze if they impact an object.
2. Enlarged crystals are easy to break up into fragments serving as freezing nuclei.

27. Collision-Coalescence Process
(a) Collision
-Larger drops fall faster than smaller drops, so as the drops fall, the larger drops overtake the smaller drops to form larger drops until rain drops are formed.
-In a cloud with cloud droplets that are tiny and uniform in size:
-The droplets fall at a similar speed and do not Collide.
-The droplets have a strong surface tension and never combine even if they collide.

28. (b) Coalescence
-The merging or "sticking together" of cloud droplets as they collide.
Droplets may:
1.Stick together/Merge
2.Bounce off one another
3. Airstream repelling
4. Coalescence is enhanced when droplets have opposite electrical charges.

29. Cloud microphysics Clouds & precipitation Radiative & diabatic heating
Circulation
Shapiro and Willoughby 1982 first showed that the evolution for a balanced symmetric TC-like vortex may be understood from the transverse circulation induced by the heat and momentum sources via Sawyer-Eliassen equation. Here we are going to use this method to demonstrate that SEF and ERC in 3d full physics simulations can be well understood from a balanced symmetric perspective. This figure compares the vertical velocities directly simulated by WRF and those diagnosed by Sawyer-Eliassen equation before and during the ERC. There is a very good agreement between them. To provide a quantitative evaluation of how well the Sawyer-Eliassen diagnoses can represent the WRF simulated transverse circulation, we computed the correlation coefficients between the WRF simulations and Sawyer-Eliassen diagnoses for the ERC period from 50 h to 90 h. As you can see, below 16km and above the boundary layer, the correlation coefficients exceed 0.8. Even in the boundary layer, the correlation coefficients are still greater than 0.6. Similar good correlations are also found in radial flow. This gives us the confidence that the Sawyer-Eliassen equation provides a useful analytical tool for investigating ERC in realistic 3d full physics simulations.

30. Microphysical Parameterization
Shapiro and Willoughby 1982 first showed that the evolution for a balanced symmetric TC-like vortex may be understood from the transverse circulation induced by the heat and momentum sources via Sawyer-Eliassen equation. Here we are going to use this method to demonstrate that SEF and ERC in 3d full physics simulations can be well understood from a balanced symmetric perspective. This figure compares the vertical velocities directly simulated by WRF and those diagnosed by Sawyer-Eliassen equation before and during the ERC. There is a very good agreement between them. To provide a quantitative evaluation of how well the Sawyer-Eliassen diagnoses can represent the WRF simulated transverse circulation, we computed the correlation coefficients between the WRF simulations and Sawyer-Eliassen diagnoses for the ERC period from 50 h to 90 h. As you can see, below 16km and above the boundary layer, the correlation coefficients exceed 0.8. Even in the boundary layer, the correlation coefficients are still greater than 0.6. Similar good correlations are also found in radial flow. This gives us the confidence that the Sawyer-Eliassen equation provides a useful analytical tool for investigating ERC in realistic 3d full physics simulations.

31. Microphysical Parameterization
1. Spectral Bin Microphysics
Divide cloud particles into bins for different sizes and explicitly compute the evolution of each bin separately.
The particle size distribution (PSD) is an output not an input
Too expensive for operational use.
Shapiro and Willoughby 1982 first showed that the evolution for a balanced symmetric TC-like vortex may be understood from the transverse circulation induced by the heat and momentum sources via Sawyer-Eliassen equation. Here we are going to use this method to demonstrate that SEF and ERC in 3d full physics simulations can be well understood from a balanced symmetric perspective. This figure compares the vertical velocities directly simulated by WRF and those diagnosed by Sawyer-Eliassen equation before and during the ERC. There is a very good agreement between them. To provide a quantitative evaluation of how well the Sawyer-Eliassen diagnoses can represent the WRF simulated transverse circulation, we computed the correlation coefficients between the WRF simulations and Sawyer-Eliassen diagnoses for the ERC period from 50 h to 90 h. As you can see, below 16km and above the boundary layer, the correlation coefficients exceed 0.8. Even in the boundary layer, the correlation coefficients are still greater than 0.6. Similar good correlations are also found in radial flow. This gives us the confidence that the Sawyer-Eliassen equation provides a useful analytical tool for investigating ERC in realistic 3d full physics simulations.

32. 2. Bulk Microphysics
Predict one or more bulk cloud quantities (e.g., cloud water mixing ratio, rain water mixing ratio).
Do not consider details of cloud particles. Particle size distributionism is assumed (e.g., beta, gamma distribution).
Shapiro and Willoughby 1982 first showed that the evolution for a balanced symmetric TC-like vortex may be understood from the transverse circulation induced by the heat and momentum sources via Sawyer-Eliassen equation. Here we are going to use this method to demonstrate that SEF and ERC in 3d full physics simulations can be well understood from a balanced symmetric perspective. This figure compares the vertical velocities directly simulated by WRF and those diagnosed by Sawyer-Eliassen equation before and during the ERC. There is a very good agreement between them. To provide a quantitative evaluation of how well the Sawyer-Eliassen diagnoses can represent the WRF simulated transverse circulation, we computed the correlation coefficients between the WRF simulations and Sawyer-Eliassen diagnoses for the ERC period from 50 h to 90 h. As you can see, below 16km and above the boundary layer, the correlation coefficients exceed 0.8. Even in the boundary layer, the correlation coefficients are still greater than 0.6. Similar good correlations are also found in radial flow. This gives us the confidence that the Sawyer-Eliassen equation provides a useful analytical tool for investigating ERC in realistic 3d full physics simulations.

33. Simple liquid microphysics – Kessler (1969)
Separate liquid into cloud water and rain
Shapiro and Willoughby 1982 first showed that the evolution for a balanced symmetric TC-like vortex may be understood from the transverse circulation induced by the heat and momentum sources via Sawyer-Eliassen equation. Here we are going to use this method to demonstrate that SEF and ERC in 3d full physics simulations can be well understood from a balanced symmetric perspective. This figure compares the vertical velocities directly simulated by WRF and those diagnosed by Sawyer-Eliassen equation before and during the ERC. There is a very good agreement between them. To provide a quantitative evaluation of how well the Sawyer-Eliassen diagnoses can represent the WRF simulated transverse circulation, we computed the correlation coefficients between the WRF simulations and Sawyer-Eliassen diagnoses for the ERC period from 50 h to 90 h. As you can see, below 16km and above the boundary layer, the correlation coefficients exceed 0.8. Even in the boundary layer, the correlation coefficients are still greater than 0.6. Similar good correlations are also found in radial flow. This gives us the confidence that the Sawyer-Eliassen equation provides a useful analytical tool for investigating ERC in realistic 3d full physics simulations.
Accretion of cloud water by existing rain
Autoconversion of cloud water to form rain
Growth of cloud water
Sedimentation

34. Ice microphysical processes
Why ice microphysical processes are important?

35. However, ice microphysics is significantly more complicated because of the wide variety of ice particle characteristics
Shapiro and Willoughby 1982 first showed that the evolution for a balanced symmetric TC-like vortex may be understood from the transverse circulation induced by the heat and momentum sources via Sawyer-Eliassen equation. Here we are going to use this method to demonstrate that SEF and ERC in 3d full physics simulations can be well understood from a balanced symmetric perspective. This figure compares the vertical velocities directly simulated by WRF and those diagnosed by Sawyer-Eliassen equation before and during the ERC. There is a very good agreement between them. To provide a quantitative evaluation of how well the Sawyer-Eliassen diagnoses can represent the WRF simulated transverse circulation, we computed the correlation coefficients between the WRF simulations and Sawyer-Eliassen diagnoses for the ERC period from 50 h to 90 h. As you can see, below 16km and above the boundary layer, the correlation coefficients exceed 0.8. Even in the boundary layer, the correlation coefficients are still greater than 0.6. Similar good correlations are also found in radial flow. This gives us the confidence that the Sawyer-Eliassen equation provides a useful analytical tool for investigating ERC in realistic 3d full physics simulations.

36. Shapiro and Willoughby 1982 first showed that the evolution for a balanced symmetric TC-like vortex may be understood from the transverse circulation induced by the heat and momentum sources via Sawyer-Eliassen equation. Here we are going to use this method to demonstrate that SEF and ERC in 3d full physics simulations can be well understood from a balanced symmetric perspective. This figure compares the vertical velocities directly simulated by WRF and those diagnosed by Sawyer-Eliassen equation before and during the ERC. There is a very good agreement between them. To provide a quantitative evaluation of how well the Sawyer-Eliassen diagnoses can represent the WRF simulated transverse circulation, we computed the correlation coefficients between the WRF simulations and Sawyer-Eliassen diagnoses for the ERC period from 50 h to 90 h. As you can see, below 16km and above the boundary layer, the correlation coefficients exceed 0.8. Even in the boundary layer, the correlation coefficients are still greater than 0.6. Similar good correlations are also found in radial flow. This gives us the confidence that the Sawyer-Eliassen equation provides a useful analytical tool for investigating ERC in realistic 3d full physics simulations.

37. Different ice species have very different characteristics
Shapiro and Willoughby 1982 first showed that the evolution for a balanced symmetric TC-like vortex may be understood from the transverse circulation induced by the heat and momentum sources via Sawyer-Eliassen equation. Here we are going to use this method to demonstrate that SEF and ERC in 3d full physics simulations can be well understood from a balanced symmetric perspective. This figure compares the vertical velocities directly simulated by WRF and those diagnosed by Sawyer-Eliassen equation before and during the ERC. There is a very good agreement between them. To provide a quantitative evaluation of how well the Sawyer-Eliassen diagnoses can represent the WRF simulated transverse circulation, we computed the correlation coefficients between the WRF simulations and Sawyer-Eliassen diagnoses for the ERC period from 50 h to 90 h. As you can see, below 16km and above the boundary layer, the correlation coefficients exceed 0.8. Even in the boundary layer, the correlation coefficients are still greater than 0.6. Similar good correlations are also found in radial flow. This gives us the confidence that the Sawyer-Eliassen equation provides a useful analytical tool for investigating ERC in realistic 3d full physics simulations.
Different ice are typically parameterized by partitioning ice into different species whose characteristics (e.g., number of concentration, particle density, fallspeed) are determined a priori.

38. Multi-moment versus single-moment schemes
Single-moment Microphysics: only predict mass variables of hydrometeors, such as clouds (Qc), rain (Qr), ice(Qi), snow(Qs), and graupel (Qg).
Multi-moment Microphysics: predict additional quantities for each species (e.g., number concentration, reflectivity).
Two-moment Microphysics: provides both mass variables of hydrometeors, such as clouds (Qc), rain (Qr), ice(Qi), snow(Qs), and graupel (Qg), and particle number of concentration, Nc, Nr, Ni, Ns, Ng.
Key impacts of single- vs. double-moment schemes
Shapiro and Willoughby 1982 first showed that the evolution for a balanced symmetric TC-like vortex may be understood from the transverse circulation induced by the heat and momentum sources via Sawyer-Eliassen equation. Here we are going to use this method to demonstrate that SEF and ERC in 3d full physics simulations can be well understood from a balanced symmetric perspective. This figure compares the vertical velocities directly simulated by WRF and those diagnosed by Sawyer-Eliassen equation before and during the ERC. There is a very good agreement between them. To provide a quantitative evaluation of how well the Sawyer-Eliassen diagnoses can represent the WRF simulated transverse circulation, we computed the correlation coefficients between the WRF simulations and Sawyer-Eliassen diagnoses for the ERC period from 50 h to 90 h. As you can see, below 16km and above the boundary layer, the correlation coefficients exceed 0.8. Even in the boundary layer, the correlation coefficients are still greater than 0.6. Similar good correlations are also found in radial flow. This gives us the confidence that the Sawyer-Eliassen equation provides a useful analytical tool for investigating ERC in realistic 3d full physics simulations.
Sedimentation and evaporation of rain droplets

39. Cloud measurement
FSSP (forward scattering spectrometer probe)
The FSSP is of the general class of instruments called optical
particle counters (OPCs) that detect single particles and size
them by measuring the intensity of light that the particle scatters
when passing through a light beam.

40. Chart of FSSP Prism Scattering Photodetector Module Dump spot Airflow
He-Ne Hybrid Laser

41. FSSP

42. Optical Array probe
It uses an array of photodiodes to measure the size of hydrometeors
from the maximum width of their shadow as they pass through a
focused He-Ne laser beam. The shadow is cast onto a linear diode
array and the total number of occulted diodes during the airflow's
passage represents the size of droplets. The size is categorized into
one of 60 channels and this information is sent to the data system
where the number of particles in each channel is accumulated over
a preselected time period. The optical array probe is a particle sizing
instrument, not a liquid water content probe. If liquid water content
information is desired, some fairly loose assumptions must be made
with regard to the phase, habit, and density of the particles.

44. Optical Array probe

46. Older techniques
Use a slide with oil, such as vaseline, on it, expose it to air flow. The
soft oil captures the water droplets. Then, one may take photos and
read through a microscope to obtain the droplet size distribution.
Droplet impinging
on this wire
Hotwire probes
The hotwire will cause the water droplet impinging on the wire to
evaporate, which will cool the hot wire. To keep the probe at a
constant temperature, an electric current must be applied that will
be proportional to the liquid water content evaporated.

47. Ceilometer is an instrument for the measurement of cloud base.
The device works day or night by shining an intense beam of light
(often ultraviolet) at overhead clouds. Reflections of this light
from the base of the clouds are detected by a photocell in the
receiver of the ceilometer. The height can be determined using
the emitted and received light.
Two basic types of ceilometers:
Scanning receiver
The transmitter fixed to direct its
beam vertically. The receiver is
stationed a known distance away.
The parabolic collector of the
receiver continuously scans up
and down the vertical beam,
searching for the point where the
light intersects a cloud base

48. Rotating transmitter ceilometer
The transmitter rotates while the receiver is pointing vertically
and coplanar with the rotating projector beam. Clouds
encountered with the light beam produce a backscattered
signal, which is detected by the receiver. Cloud height is then
determined by
triangulation.

49. Laser ceilometer
It has a transmitter and a receiver, and it measures the
time of return from scattering of the laser off from the
cloud; it’s ideal because it can work during the day and
night, but it only gives cloud observations from overhead.
Low power laser ceilometer
It uses an eye-safe, low-power laser to transmit light pulses to
the cloud base, up to 40,000 feet (13 km).

50. Atmospheric Radiation Measurement Program

51. Instrumentation
Latest version W-band (95 GHz)cloud radar
Millimeter Wave Cloud Radar (35 GHz)

52. X-band scanning ARM precipitation radar
Vaisala Ceilometer