convective parameterization in nwp models

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Convective Convective Parameterization in Parameterization in NWP Models NWP Models Jack Kain Jack Kain And And Mike Baldwin Mike Baldwin

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Convective Parameterization in NWP Models. Jack Kain And Mike Baldwin. What is convective parameterization?. - PowerPoint PPT Presentation

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Page 1: Convective Parameterization in NWP Models

Convective Parameterization in Convective Parameterization in NWP ModelsNWP Models

Jack KainJack KainAnd And

Mike BaldwinMike Baldwin

Page 2: Convective Parameterization in NWP Models

What is convective What is convective parameterization?parameterization?

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

Page 3: Convective Parameterization in NWP Models

Why do NWP models need to Why do NWP models need to worry about it?worry about it?

Direct Concern:Direct Concern: To Predict convective To Predict convective precipitationprecipitation

Feedback to larger Scales: Feedback to larger Scales: Deep convection Deep convection “overturns” the atmosphere, strongly affecting “overturns” the atmosphere, strongly affecting mesoscale dynamicsmesoscale dynamics- Changes vertical stability- Changes vertical stability- generates and redistributes heat- generates and redistributes heat- removes and redistributes moisture- removes and redistributes moisture- makes clouds, strongly affecting surface heating - makes clouds, strongly affecting surface heating and atmospheric radiationand atmospheric radiation

Page 4: Convective Parameterization in NWP Models

A convective parameterization A convective parameterization must decide 3 things:must decide 3 things:

• Activation? Trigger function

• Intensity? Closure Assumptions

• Vertical Distribution? Cloud model or specified profile

Page 5: Convective Parameterization in NWP Models

Trigger Functions 

CAPECloudDepth

CIN

Moist.Conv.

Sub-cloudMass conv.

Cloud-layerMoisture ∂(CAPE)/∂t

BMJ(Eta)

     

 

Grell(RUC, AVN) 

     

KF

(Research) 

 

   

Bougeault(Meteo FR)

   

     

Tiedtke(ECMWF) 

 

     

Bechtold(Research) 

 

   

Emanuel(Research)

 

       

Page 6: Convective Parameterization in NWP Models

Closure Assumptions (Intensity)

  CAPE Cloud-layermoisture

MoistureConverg.

∂(CAPE)/∂t SubcloudQuasi-equil.

BMJ(Eta)

 

     

Grell(RUC, AVN)

 

   

 

KF(Research)

 

       

Bougeault(Meteo FR)

 

   

   

Tiedtke(ECMWF)

 

       

Bechtold(Research)

 

       

Emanuel(Research)

       

Page 7: Convective Parameterization in NWP Models

Vertical Distribution of Heat, Moisture  Entraining/Detraining

Plume 

Convective Adjustment

Buoyancy SortingCloud Model

BMJ(Eta)

 

 

 

Grell(RUC, AVN)

 

   

KF(Research)

   

Bougeault(Meteo FR)

 

   

Tiedtke(ECMWF)

 

   

Bechtold(Research)

 

   

Emanuel(Research)

   

Page 8: Convective Parameterization in NWP Models

How is the parameterized How is the parameterized information fed back to the information fed back to the

model?model?Consider the Temperature-Tendency Equation in a model:Consider the Temperature-Tendency Equation in a model:

sfcvmixhmixevapcondconvraddtd PPPPPP /

Where the convective term is simply

c

initadj

convconv t

P

Page 9: Convective Parameterization in NWP Models

Consider two very different Consider two very different approaches:approaches:

1)1) BMJ Scheme (convective adjustment)BMJ Scheme (convective adjustment)

2)2) KF scheme (mass flux scheme)KF scheme (mass flux scheme)

Page 10: Convective Parameterization in NWP Models

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)

Page 11: Convective Parameterization in NWP Models

The Next Step is an The Next Step is an EnthalpyEnthalpy AdjustmentAdjustment

First Law of Thermodynamics: vvp dqLdTCdH

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.

dpqqLdpTTC vvref

P

P v

P

P refpt

b

t

b

)(

Page 12: Convective Parameterization in NWP Models

Enthalpy is not conserved for first-guess profiles for this sounding!

Must shift Tref and qvref to the left…

Page 13: Convective Parameterization in NWP Models

Imposing Enthalpy Adjustment:Imposing Enthalpy Adjustment:

Page 14: Convective Parameterization in NWP Models

Adjusted Enthalpy Profiles:Adjusted Enthalpy Profiles:

Page 15: Convective Parameterization in NWP Models

Suppose the cloud layer was drier…reduce RH by 15%:Suppose the cloud layer was drier…reduce RH by 15%:

Page 16: Convective Parameterization in NWP Models

Enthalpy is conserved, but the net temperature Enthalpy is conserved, but the net temperature change is change is negativenegative, and the net moisture , and the net moisture

change is change is positivepositive: : Negative Precipitation!Negative Precipitation!

Page 17: Convective Parameterization in NWP Models

If we systematically change cloud-layer RH in this sounding, If we systematically change cloud-layer RH in this sounding, it can be shown that precipitation rate generated by the it can be shown that precipitation rate generated by the

scheme is very sensitive to deep-layer moisture:scheme is very sensitive to deep-layer moisture:

Page 18: Convective Parameterization in NWP Models

If the environment is too dry or CAPE layer is less If the environment is too dry or CAPE layer is less than ~ 200 mb deep, the scheme attempts to initiate than ~ 200 mb deep, the scheme attempts to initiate

shallow (non-precipitating) convectionshallow (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.

Page 19: Convective Parameterization in NWP Models

With Shallow Convection, there is no With Shallow Convection, there is no netnet temperature or moisture change:temperature or moisture change:

t

b

P

P refp dpTTC 0)( t

b

P

P vvrefv dpqqL 0)(and

Page 20: Convective Parameterization in NWP Models

Consider the impact of parameterized BMJ shallow Consider the impact of parameterized BMJ shallow convection in a “normal” diurnal cycle…convection in a “normal” diurnal cycle…

Model Initial Condition

Raob

BMX 12 Z 11 May 2000

Page 21: Convective Parameterization in NWP Models

Convective Adjustment Profiles…Convective Adjustment Profiles…

Initial time 1 h forecast

Page 22: Convective Parameterization in NWP Models

Convective Adjustment Profiles…Convective Adjustment Profiles…

3 h forecast

6 h forecast: BMJ convection inactive because “convective entropy change” would be negative. Sounding characteristics that lead to negative entropy change are not easily identified.

Page 23: Convective Parameterization in NWP Models

Other constraints that cause BMJ Other constraints that cause BMJ shallow convection to “abort”:shallow convection to “abort”:

- - qqrefref gives an increase in gives an increase in qq with height with height- - qqrefref gives a negative gives a negative qq at some level at some level

- - TTrefref is super-adiabaticis super-adiabatic

- Net entropy change in cloud layer would be - Net entropy change in cloud layer would be negativenegative

- - TTrefref is isothermal is isothermal

- - qqrefref gives super-saturated gives super-saturated qq at some level at some level

Page 24: Convective Parameterization in NWP Models

Back to the convective Back to the convective adjustment profiles…adjustment profiles…

9 h forecast – 2100 UTC

Page 25: Convective Parameterization in NWP Models

Compare with raob at 00 Z: 12 h forecastCompare with raob at 00 Z: 12 h forecast

Model forecast

Raob

BMX 00Z 12 May 2000

Page 26: Convective Parameterization in NWP Models

Consider a transition from shallow to deep convection…Consider a transition from shallow to deep convection…

Model Initial Condition

Raob

FWD 00Z 20 April 2001

Page 27: Convective Parameterization in NWP Models

Convective Adjustment Profiles…Convective Adjustment Profiles…

1h Forecast

Page 28: Convective Parameterization in NWP Models

Compare with raob at 12 Z: 12 h forecastCompare with raob at 12 Z: 12 h forecast

Model forecast

Raob

FWD 12Z 20 April 2001

Page 29: Convective Parameterization in NWP Models

More Convective Adjustment Profiles…More Convective Adjustment Profiles…

16 h forecast 17 h forecast

Page 30: Convective Parameterization in NWP Models

Continuing to work on the sounding…Continuing to work on the sounding…

18 h forecast 21 h forecast

Page 31: Convective Parameterization in NWP Models

Compare with raob at 00 Z: 24 h forecastCompare with raob at 00 Z: 24 h forecast

Raob

Model Forecast

FWD 12Z 20 April 2001

Page 32: Convective Parameterization in NWP Models

BMJ Deep convection activated only briefly at FWD, but BMJ Deep convection activated only briefly at FWD, but 100 miles to the north (ADM), BMJ deep convection was 100 miles to the north (ADM), BMJ deep convection was

more persistent and strongly modified soundings:more persistent and strongly modified soundings:

EtaKF Model Forecast

Model Forecast

ADM 22 Z 20 April 2001

Page 33: Convective Parameterization in NWP Models

OK, consider the KF scheme, a “Mass-flux” OK, consider the KF scheme, a “Mass-flux” parameterizationparameterization

Page 34: Convective Parameterization in NWP Models

Basic procedures…Basic procedures…1) Starting at the surface, mix ~ 50 mb deep layers, lift to LCL2) 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

Page 35: Convective Parameterization in NWP Models

KF adjustment profilesKF adjustment profiles

Page 36: Convective Parameterization in NWP Models

Focus on deep convection…what is the Focus on deep convection…what is the Updraft Mass Flux (UMF*)?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

Page 37: Convective Parameterization in NWP Models

How is UMF How is UMF determined?determined?

Page 38: Convective Parameterization in NWP Models
Page 39: Convective Parameterization in NWP Models
Page 40: Convective Parameterization in NWP Models

What is UMF* sensitive to?What is UMF* sensitive to?

ee of downdraft air of downdraft air Lapse rates in cloud layerLapse rates in cloud layer

Page 41: Convective Parameterization in NWP Models

Increasing humidity in the 900 – 550 mb layer increases downdraft e. This makes stabilization of the boundary layer less efficient and UMF* increases.

Page 42: Convective Parameterization in NWP Models
Page 43: Convective Parameterization in NWP Models
Page 44: Convective Parameterization in NWP Models

SummarySummary

Parameterized shallow convection can Parameterized shallow convection can distort sounding structures, significantly distort sounding structures, significantly affecting CIN and CAPE; more problematic affecting CIN and CAPE; more problematic with BMJ than with KFwith BMJ than with KF

BMJ deep convection very sensitive to BMJ deep convection very sensitive to cloud-layer RHcloud-layer RH

KF mass flux particularly sensitive to lapse KF mass flux particularly sensitive to lapse rates in lower half of cloud layer. rates in lower half of cloud layer.