Evaluation of three-dimensional cloud structures in DYMECS

Robin HoganJohn NicolRobert PlantPeter Clark

Kirsty HanleyCarol HalliwellHumphrey Lean

Thorwald Stein (t.h.m.stein@reading.ac.uk)www.met.reading.ac.uk/~dymecs

(UK Met Office)

50-km 50-km domaindomain• 200-m

model

• 1.5-km model

1:1 aspect ratio

What we want to know What we want to know about cloud structuresabout cloud structures

How does cloud top height relate toa. Time (life time or time of day)b. Surface area

2

3 What is the probability of an anviland what are typical anvil factors?

1How does the typical storm widthvary with height?

z

R4How do ice cloud reflectivities

relate to the precipitation rate?

Storm structure from radarStorm structure from radar

Distance east (km)

Distance north

(km)

Radar reflectivity

(dBZ)

40 dBZ

0 dBZ

20 dBZ

1. Median equivalent 1. Median equivalent radius with height – radius with height –

all 2012all 2012

Obs

erva

tions

UKV

150

0m

Model storms too wide (or not enough

small storms)

Observed cores are

deeper (40dBZ in ice part)

“Shallow”

“Deep”

Observations UKV 1500m 200m

1. Median equivalent radius 1. Median equivalent radius with height – 25with height – 25thth August August

20122012

Lack of anvils? (see

3)

500m

Drizzle from nowhere? (see

4)

Convergence?

✔

✖

2a. Cloud top height 2a. Cloud top height evolution with time of evolution with time of

dayday

Models fail to reproducesharp increase in mediancloud top height at noon.

Tallest storms (90th pct)are not deep enoughcompared to observations.

2b. Cloud top height 2b. Cloud top height variation with storm variation with storm

sizesizeObservations UKV 1500m

200m 500m

Models and observations show larger storms havehigher cloud tops.

Models have too manymedium-sized stormswith low cloud tops.

Median height25th/75th percentile

Observations UKV 1500m 200m

3. Anvil probability3. Anvil probability• Define anvil as cloud above 6km with

diameter larger than storm diameter at 3km.

• More than 40% of storms above 6km have anvil (model and observations).

A selection of individual profiles shows anvil factors will be small (close to 1)

6

3

z

T=0oC

R

3. Anvil probability3. Anvil probability

PDF of anvil factorDmax/D3km

6

3

z

T=0oC

D

• Define anvil as cloud above 6km with diameter larger than storm diameter at 3km (500m above the melting layer).

Dmax

Suggests exponential distribution of anvil factors for the UK in

model and observations

4. Ice cloud and4. Ice cloud andprecipitationprecipitation

1.5-km 1.5-km + graupel

200-m 1.5-km new PSD Observations

Conditioned on average reflectivity at 200-1000m below 0oC.

Reflectivity distributions forprofiles with thismean Z 40-45 dBZ are shown.

Model:High rainfall rate from storms lacking

ice or have ice cloud

dBZ<0

Discussion pointsDiscussion points

• Are microphysics parameterisation schemes fit for high-resolution (200m or less)?

• What are the appropriate regions for evaluation of convective cloud features (e.g. anvil – tropics) and do we have the observations?

• What are the observational needs for high-resolution model evaluation?

• Should we monitor convection for relatively rare events e.g. hail, and how (new dual-pol radars in network)?

• Should a radar forward operator Z(IWC,T) adopt model assumptions on particle size distributions, or adopt a physical or empirical based approach? “is 0 dBZ really 0 dBZ”