VO 5+6 Parameterization II

What does microphysics describe?

the description of the formation, growth and sedimentation of hydrometeors

Main tasks of microphysics

• phase transition with accompanying release of latent heat

• determining the quantity and nature of hydrometeors for electromagnetic calculations (radiation, radar, satellite comparisons)

• type and amount of precipitation

• aerosol interactions (zb washout of condensation nuclei)

Theoretical foundations of microphysics

• no universally valid method

• scales are mostly below 1 cm

• difficult to fain insight from high-resolution simulation (no pure subgrid)

Important approaches from microphysics

• one and two-moment bulk schemes

• bin schemes

Thermodynamic phase transitions - basics, simplest assumption, reality

• 3 phases → 6 transitions

• in the model it must be decided how the total amount of H2O is divided into water vapor, water and ice

Simplest assumption:

• saturation water vapor depends only on temperature and pressure

• T>0 water

• T<0 ice

• T=0 water+ice

• thermal equilibrium

Reality:

• saturation water vapor depends on droplet radius, ice crystal shape and condensation nuclei

• mixed-phase clouds exist for T<0 → no thermal equilibrium

Kessler parameterization

• only considers water vapor, cloud water, rain (no ice)

Five processes:

1. Condensation: Water vapor to cloud water

2. Evaporation: Cloud water to water vapor

3. Autoconversion: Cloud droplets collide and become raindrops

4. Accretion: Falling raindrops collect cloud droplets through

   collisions.

5. Evaporation: Cloud droplets to water vapor

Autoconversion as a function

\frac{dM}{\differentialD t}=k_1\left(m-a\right)

with M rain and m cloud water

Two tuning parameters:

• a: at what amount of cloud water autoconversion begins, when m<a the term is turned off

• k_1: how quickly cloud water is converted into rain

Autoconversion and Accretion as a function

\frac{dM}{\differentialD t}=-\frac{dm}{\differentialD t}=k_1\left(m-a\right)+k_2^{^{\prime}}mM^{\frac78}

another tuning parameter:

• k’_2: collection efficiency, how effectively raindrops collect cloud droplets

even this simple parameterization has many tuning parameters that are difficult to determine!

Bulk microphysics schemes

→ assume an analytical particle-size distribution (because total mass of cloud water and rain is not enough)

• one-moment: only the mass of each hydrometeor category is calculated (zb 1kg of cloud water)

• two-moment: mass and number of hydrometeors are determined (zb 1kg of cloud water and 1,000,000 droplets)

  

Bin microphysics schemes

approximate the distribution through several bins

→ also called spectral

usually 30-45 bin (ice and water) are used (expensive)

What else do microphysics depend on?

other parameterizations

• vertical updrafts: they determine how long and quickly precipitation objects can grow before they falls (often from convection parameterizations)

• turbulent mixing leads to evaporation at cloud edges

• aerosols from the BL act as condensation nuclei

Example of a Bulk two-moment scheme with 6 hydrometeors:

cloud water, rain, cloud ice, snow, graupel, hail

• 12 prognostic variables: 6×2 (two-moment)

• can predict hail prognostically

• since 2015 part of COSMO/ICON at DWD

• complex because many processes must be formulated using tuning parameters and closures

• need so solve: many coupled PDGLs

• hydrometeors always >0

Explain formation, growth and sedimentation of hydrometeors

Formation:

• hydrometeors form through phase transitions

• zb: water vapor condenses into cloud droplets or deposits onto ice particles

• in reality depends on temperature, pressure, condensation nuclei droplet radius, ice crystal shape

Growth:

• condensation or depositition

• autoconversion

• accretion

• other ice-related processes can form snow, graupel, hail

• vertical updrafts important - keep particles inside the cloud longer → more time to grow

Sedimentation:

• hydrometeors fall under gravity

• larger and heavier particles fall faster

• when they become large enough, they leave the cloud as a form of precipitation

• during the fall they can continue growing, melt or evaporate

Common hydrometeor categories

• cloud water

• drizzle

• rain

• cloud ice

• snow

• graupel

• hail

Must microphysics be parameterized?

Yes. Even at very high model resolution, there is no general fundamental theory!

What types of precipitation are determined by microphysics?

All forms of precipitation

How does microphysics influence model dynamics?

Direct influence through latent energy (zb moist adiabatic processes)

With which parameterizations is microphysics closely linked?

• Radiation

• Convection

• Aerosols

Radiation in NWP models

1. Warming/cooling of the surface, the driver of the daily cycle

2. Warming/cooling of the air layers directly

3. Forecast for photovoltaic performance

Radiation in gases

• scattering and absorption of radiation (zb Rayleigh, Mie)

• scattering and absorption depend on wavelength and angle

Radiation and hydrometeors interaction

• highly dependent on the geometry and properties of the hydrometeors

• radius of cloud droplets has enormous influence on radar (different effect if many small or many large droplets)

• if the distribution of droplet sizes is not considered → biases

• interaction dependent on wavelength and angle

Why is cloud geometry important for radiation?

• Cloud geometry determines the optical path of radiation through the cloud

• in a 1D column different overlap assumptions with the same cloud fraction lead to different cloud cover

overlap assumptions:

1. random overlap

2. exponential-random overlap

3. maximum-random overlap

   

Why is radiation difficult to parameterize?

• wavelength and angle dependent

• 3D

• sensitive to the number, size and type of hydrometeors

• affected by aerosols

• cloud geometry important

• non-trivial interactions with the earths surface

What kind of radiation approaches are there?

• spectral bands

• 2-stream approach

• effective radius of cloud droplets

these approaches reduce computational effort for radiation

What is the spectral bands approach?

• instead of calculating each wavelength individually, closely correlated wavelengths are calculated together

• number of groups is conceptually closely related to grid resolution → the more groups the better the result

• individual groups can be calculated independently of each other

What is the 2-stream approach?

we reduce everything to two radiation fluxes, one upward one downward

• for each band/group only one upward and one downward calculation is performed

• each direction represents an integral over all angles in a hemisphere (also nur hoch oder runter)

• each column can be calculated separately as no horizontal exchange occur (kein Austausch zwischen 2 Säulen)

What is the effective radius approach?

• instead of considering the full droplet distribution, a single radius is used that is supposed to achieve the same result (r_eff)

How does ECMWF solve radiation?

via EcRad

5 main components:

• surface

• gas

• aerosols

• clouds (with cloud generator)

• solver (5 different ones)

→ Gas, aerosol, cloud and surface optical properties are calculated and passed to a radiative-transfer solver

→ radiation is evaluated on a coarser spatial grid and at longer time intervals than the dynamical core

→ the resulting fluxes are interpolated back to the model grid.

What is a cloud generator?

it creates several possible 1D cloud profiles, called sub-columns, from the modeled cloud cover in the individual atmospheric layers

you draw a line at every start/end of a cloud

picture right : 10 sub-columns with clouds, one with clear sky

What is a stochastic cloud generator?

• Randomly generates several subprofiles from average profiles of cloud cover, cloud water, and ice

• distinguishes not only between cloudy and clear but also varies the amount of moisture

• Assumptions about overlap probability and assumed distributions of water and ice in each layer are taken into account

• In the example, 25 cloud profiles were generated, of which 5 have no clouds at all and some are identical.

  

Rayleigh and Mie scattering

• Rayleigh scattering: particles are much smaller than the wavelength

• Mie scattering: particles are approximately the same size as, or larger than, the wavelength

for clouds and aerosols, Mie scattering is often especially important because the particle sizes are comparable to visible wavelengths

Wavelength of green light vs fine dust (PM 2.5)?

Green light has a wavelength of approximately

λ≈550 nm=0.55 μm

PM2.5 particles have diameters of up to

2.5 μm

PM2.5 particles can be several times larger than the wavelength of green light. Therefore, their interaction with visible light is mainly in the Mie-scattering regime

Red light:

λ≈633 nm=0.633 μm

What is the output