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Convective-Parameterization-in-NWP-Models

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					Convective Parameterization in
        NWP Models
           Jack Kain
              And
          Mike Baldwin
            What is convective
            parameterization?

   A technique used in NWP to predict the
    collective effects of (many) convective
    clouds that may exist within a single grid
    element…As a function of larger-scale
    processes and/or conditions.
     Why do NWP models need to
          worry about it?

   Direct Concern: To Predict convective
    precipitation
   Feedback to larger Scales: Deep convection
    “overturns” the atmosphere, strongly affecting
    mesoscale dynamics
    - Changes vertical stability
    - generates and redistributes heat
    - removes and redistributes moisture
    - makes clouds, strongly affecting surface heating
    and atmospheric radiation
A convective parameterization
    must decide 3 things:

• Activation?  Trigger function


• Intensity?  Closure Assumptions


• Vertical Distribution?  Cloud model or specified profile
                                Trigger Functions
                    Cloud   C     Moist.   Sub-cloud    Cloud-layer
             CAPE   Depth   I     Conv.    Mass conv.   Moisture      ∂(CAPE)/∂t
                            N
  BMJ
   (Eta)                                                 
  Grell
(RUC, AVN)                                                           
   KF
(Research)                                 
Bougeault
(Meteo FR)                         
Tiedtke
(ECMWF)                           
Bechtold
(Research)                                 
Emanuel
(Research)                 
                    Closure Assumptions (Intensity)
             CAPE   Cloud-layer   Moisture   ∂(CAPE)/∂t   Subcloud
                    moisture      Converg.                Quasi-equil.

  BMJ
  (Eta)                
  Grell
(RUC, AVN)                                     
   KF
(Research)   
Bougeault
(Meteo FR)                          
 Tiedtke
(ECMWF)      
Bechtold
(Research)   
Emanuel
(Research)                                                    
              Vertical Distribution of Heat, Moisture
              Entraining/Detraining Convective Buoyancy
                     Plume          Adjustment Sorting
                                               Cloud Model
  BMJ
   (Eta)                                   
  Grell
(RUC, AVN)             
   KF
 (Research)            
Bougeault
(Meteo FR)             
 Tiedtke
 (ECMWF)               
Bechtold
 (Research)            
Emanuel
 (Research)                                             
      How is the parameterized
     information fed back to the
               model?
Consider the Temperature-Tendency Equation in a model:

     d
         Prad  Pconv  Pcond / evap  Phmix  Pvmix  Psfc
     dt
 Where the convective term is simply

                                   adj   init
              Pconv              
                      t     conv        c
Consider two very different
       approaches:



1)   BMJ Scheme (convective adjustment)
2)   KF scheme (mass flux scheme)
Procedure followed by BMJ scheme…

                              1) Find the most unstable air in lowest ~ 200 mb

                                     2) Draw a moist adiabat for this air

                                            3) Compute a first-guess temperature-
                                            adjustment profile (Tref)




4) Compute a first-guess dewpoint-
adjustment profile (qref)
       The Next Step is an Enthalpy
              Adjustment
 First Law of
 Thermodynamics:
                         dH  C p dT  Lv dqv

With Parameterized Convection, each grid-point column is treated in
isolation. Total column latent heating must be directly proportional to
total column drying, or dH = 0.


               C p Tref  T dp   Lv (qvref  qv )dp
          Pt                          Pt
       Pb                           Pb
Enthalpy is not conserved for
first-guess profiles for this
sounding!
Must shift Tref and qvref to the
left…
Imposing Enthalpy Adjustment:
Adjusted Enthalpy Profiles:
Suppose the cloud layer was drier…reduce RH by 15%:
Enthalpy is conserved, but the net temperature
   change is negative, and the net moisture
 change is positive: Negative Precipitation!
If we systematically change cloud-layer RH in this sounding,
    it can be shown that precipitation rate generated by the
        scheme is very sensitive to deep-layer moisture:
  If the environment is too dry or CAPE layer is less
 than ~ 200 mb deep, the scheme attempts to initiate
         shallow (non-precipitating) convection
1) Set cloud-top height as the level within 200 mb of LCL where
RH falls off most rapidly with height.

2) Find LCL of cloud-top air; line connecting LCLs of subcloud and
cloud-top air is a “mixing line”.

                               3) Assume Tref has same slope as
                               mixing line; first-guess Tref is
                               anchored on ambient temperature
                               curve.
                With Shallow Convection, there is no net
                    temperature or moisture change:

    Pt

                                                Pt

Pb
         C p (Tref  T )dp  0   and        
                                            Pb
                                                     Lv (qvref  qv )dp  0
Consider the impact of parameterized BMJ shallow
    convection in a “normal” diurnal cycle…

                          Model Initial Condition
                          Raob
                          BMX 12 Z 11 May 2000
Convective Adjustment Profiles…


Initial time            1 h forecast
  Convective Adjustment Profiles…
                 6 h forecast: BMJ convection
                 inactive because “convective
                 entropy change” would be negative.
3 h forecast     Sounding characteristics that lead
                 to negative entropy change are not
                 easily identified.
Other constraints that cause BMJ
 shallow convection to “abort”:
 - Net entropy change in cloud layer would be
       negative
 - Tref is super-adiabatic
 - Tref is isothermal
 - qref gives a negative q at some level
 - qref gives an increase in q with height
 - qref gives super-saturated q at some level
Back to the convective
adjustment profiles…


    9 h forecast – 2100 UTC
Compare with raob at 00 Z: 12 h forecast




               Model forecast
               Raob
               BMX 00Z 12 May 2000
Consider a transition from shallow to deep convection…

                                    FWD 00Z 20 April 2001




                                  Model Initial Condition
                                  Raob
Convective Adjustment Profiles…



          1h Forecast
Compare with raob at 12 Z: 12 h forecast




                            Model forecast
                            Raob
                            FWD 12Z 20 April 2001
More Convective Adjustment Profiles…




 16 h forecast            17 h forecast
Continuing to work on the sounding…




18 h forecast            21 h forecast
Compare with raob at 00 Z: 24 h forecast




                           Raob
                           Model Forecast
                           FWD 12Z 20 April 2001
BMJ Deep convection activated only briefly at FWD, but
100 miles to the north (ADM), BMJ deep convection was
   more persistent and strongly modified soundings:




                              EtaKF Model Forecast
                              Model Forecast
                              ADM 22 Z 20 April 2001
OK, consider the KF scheme, a “Mass-flux”
             parameterization
               Basic procedures…
                 1) Starting at the surface, mix ~ 50 mb deep layers, lift to LCL
                  2) Give parcel a boost based on low-level convergence. Can
                  it reach the LFC?
                  3) If parcel makes it to LFC, allow it to rise and overshoot
                  equilibrium level.

                          4) Form downdraft from air within ~ 200 mb of
                          cloud base

                                  5) Overturn mass in updraft, downdraft, and
                                  surrounding environment until stabilization is
                                  achieved.

                                       If cloud depth  3 km,
                                       parameterize shallow convection
Updraft Source Layer
KF adjustment profiles
     Focus on deep convection…what is the
         Updraft Mass Flux (UMF*)?




The mass of air that goes through cloud base divided by the
initial mass in the ~ 50 mb updraft source layer:


                      UMF* = Mu/Musl
How is UMF
determined?
     What is UMF* sensitive to?


   e of downdraft air
   Lapse rates in cloud layer
Increasing humidity in the 900 – 550 mb layer increases
downdraft e. This makes stabilization of the boundary layer
less efficient and UMF* increases.
                Summary
 Parameterized shallow convection can
  distort sounding structures, significantly
  affecting CIN and CAPE; more problematic
  with BMJ than with KF
 BMJ deep convection very sensitive to
  cloud-layer RH
 KF mass flux particularly sensitive to lapse
  rates in lower half of cloud layer.

				
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posted:11/30/2009
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