a simple parameterization for detrainment in shallow cumulus hirlam results for rico
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A simple parameterization for detrainment in shallow cumulus Hirlam results for RICO. Wim de Rooy & Pier Siebesma Royal Netherlands Meteorological Institute (KNMI). Hirlam 1D. Hirlam but with: Statistical cloud scheme Tiedtke mass flux convection scheme with updates:

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a simple parameterization for detrainment in shallow cumulus hirlam results for rico

A simple parameterization for detrainment in shallow cumulusHirlam results for RICO

Wim de Rooy & Pier Siebesma

Royal Netherlands Meteorological Institute (KNMI)

hirlam 1d
Hirlam 1D

Hirlam but with:

  • Statistical cloud scheme
  • Tiedtke mass flux convection scheme with updates:
    • Mass flux closure at cloud base (Neggers et al. 2002)
    • Triggering (Jacob & Siebesma 2003)
    • versions with a conventional or a new lateral mixing concept
slide3

Fixed  and :

  • No dependence on environmental
  • humidity conditions

Mass flux concept

  • Buoyancy sorting concept
  • Complex, fundamental problems

M

M

M

Courtesy: Stephan de Roode

Fraction of environmental air

conventional fixed z 1 and 0 00275 m 1 okay for bomex but for rico
Conventional fixed =z-1 and =0.00275 m-1 okay for BOMEX but for RICO?

What’s going on?

les results for bomex arm and rico show
LES results for BOMEX, ARM and RICO show:
  • Not much variation in . For a correct simulation of the Mass flux profile, =z-1 is good enough.
  • Much more variation in . The value of  mainly depends on:

- Cloud Layer Height

- Environmental conditions

slide6

Cloud Layer Height dependence

Cloud ensembles

Mass flux profiles with =z-1 and =0.00275

ztop

Cloud layer

depth=1000m

z

(e.g. BOMEX)

zbot

M

ztop

Cloud layer

depth=200m

zbot

M

ztop

Cloud layer

depth=2000m

e.g. RICO

z

zbot

M

slide7

Dependence on environmental conditions

Eliminate cloud height dependence by looking at a non-dimensionalized mass flux profile

LES Non-dimensionalized mass flux profiles

ARM case LES

z*

slide8
Suppose we would know the non-dimensionless mass flux m* halfway the cloud layer at height z*

Ztop

Z*

Zbot

slide12

Conclusions

  • The proposed detrainment parameterization is simple but includes two important dependencies:
  • Cloud layer height dependence
    • Current mass flux schemes ignore this dependence which evidently can lead to large discrepancies with observed mass flux profiles.
  • Environmental conditions
    • With the c dependence the new scheme can be seen as an alternative for more complex buoyancy sorting schemes (without some of the disadvantages)
conclusions
Conclusions
  • Good results for a wide range of shallow convection cases (BOMEX, ARM, RICO)
  • Easy to incorporate in existing mass flux schemes

(and will be incorporated in an EDMF dual mass flux environment)

slide16

Dependence on environmental conditions

Eliminate cloud height dependence by looking at a non-dimensionalized mass flux profile

LES Non-dimensionalized mass flux profiles

ARM case

Non-dimensionalized mass

flux profiles with fixed  and 

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