Entrainment as the main controling parameter of convective activity in the 3MT moist-physics

unifying scheme. Trials for an extension towards a 'cold-pool

mechanism’-oriented ‘memory of entrainment’

J.-F. Geleyn, D. Banciu, R. Brožková and L. Gerard(with strong reference to ideas of J.-M. Piriou)

26/3/09, Prague, CHMI

A few words about 3MT

GoalsMain choices

Implementation characteristicsGrey-zone results

Why 3MT? (i) Attacking, within a long-term perspective, the challenge of the

horizontal scales (δx ~ 5 km) where precipitating convection is neither fully resolved nor likely to be correctly parameterised in a ‘classical’ way.

(ii) Insisting on stable (for longer t) and cost-efficient algorithmic solutions (bulk model for the drafts for instance).

(iii) Having a ‘NWP-controlled’ progress (novelty AND ascending compatibility).

(iv) Modularity-flexibility as the essential tool to obtain a multi-scale character (being able to swap and/or tune the ‘processes description’ without touching the structuring algorithmic).

(v) Using a prognostic orientation for reconciliation of ideas about complex microphysics and mass-flux-type parameterisation (neither CRM nor QE).

3MT, the acronym

Three ideas/concepts: Modular, because of the ALARO-0 effort made in

order to stay compatible with a general phys-dyn interfacing while searching proximity with the AROME concepts (R. Brozkova, I. Stiperski, J.-F. Geleyn, B. Catry, D. Banciu);

Multi-scale, because a great deal of the architectural constraint comes from the ‘grey-zone’ oriented work, initiated in 2001 by L. Gerard;

Microphysics & Transport, to underline the decisive catalysing role played by the central proposal of J.-M. Piriou’s PhD work, made in 2004.

Microphysics AND Transport (M-T) It is the basic idea behind all what follows. Allows to rethink around two trivial facts:

‘Detrainment’ here = ‘Entrainment’ somewhere else. ‘Cloud+precipitation microphysics’ is anything but

instantaneous (fall speed of drops ~ propagation speed of convective structures).

CONSEQUENCES 3MT gets away from assumptions of a stationary

cloud (neither in size nor in properties). 3MT fully takes into account the fact that

microphysics has a rather long lag-time and is not only happening ‘within the drafts’.

One key equation

• If we set– Mc from two independent prognostic equations for c and up

– up as constant (in the cloud) along the vertical => 2D-only closure

– E from ‘something’ (see later in the presentation)

• Then D cannot be ‘parameterised’ (overdetermination otherwise) and it is obtained from all other computations. Piriou et al. (2007) showed that it is in fact mainly constrained by the microphysical activity => a justification for using the M-T decomposition.

)( upcccupup MDE

p

M

pt

Time- and space-scale issue

Basically, 3MT is a way to do ‘as if’ deep convection was resolved but without needing to go to scales where this is true.

This is thanks to: Prognostic and diagnostic ‘memory’ of convection; A unique micro-physical treatment beyond all

sources of condensation. But, owing to the peculiar role of entrainment in

the M-T concept, this requires to better understand what one means when ‘specifying’ entrainment in one way or the other.

3MT

The nice sides … NWP orientation: bulk mass-flux but fully prognostic

handling of the mass-flux AND of the 2D closure. With M-T, the 2D closure and a prognostic equation for

the mass-flux, no need to parameterise anymore detrainment.

Facility to work on ‘modularity for flexibility’. One single microphysical-type computation, except for the

condensation/re-evaporation, the latter being obtained from the sum of a ‘resolved’ contribution and of a ‘convective’ one.

Lot of freedom for a complex fully prognostic micro-physics => more ‘memory’ of past convective events.

The ‘cold-pool’ effect’s parameterisation should happen quite naturally in this framework.

But … The handling of the ‘cascade’ (neither sequential nor

parallel treatment of individual contributions) is not always easy: Avoiding ‘double-counting’ for updraft and downdraft closure

is not trivial; The sedimentation aspect of the downdraft impact must be

treated heuristically; In order not to be forced to iterate expensive computations, one

must make judicious choices about which information to pass or not to pass to the next time-step (and on how to best use it).

Not enough effort was devoted to the closure formulation, especially in view of its ‘multi-scale’ impact.

For a ‘deep’ framework, a vertically constant area fraction for drafts is OK; but this does not hold anymore in the ‘shallow’ case.

Modularity for flexibility. Where? Updraft (and downdraft):

Ascent computation (including the prognostic handling of an in-ascent vertical velocity); Closure (leading to a 2D field of active area fractions, also prognostic); M-T equations => (non-negociable).

Microphysics:

General organisation (explicit need of fall-speeds, non-advective sedimentation, geometrical overlap’s impact, protection of convective condensates at the ensuing time steps, …) => (non-negociable);

Type of sedimentation’s handling; choice of the computation (or set-up) of fall-speeds; Auto-conversion type processes; Collection type processes; Evaporation, Sublimation, Melting, Freezing of falling species.

‘Resolved’ adjustment:

Choice of critical relative humidity; Formulation of cloud-cover; Condensation/Evaporation rate => (separation from the other items is non-negociable;

but the choice of the formulation is free).

3MT, the backbone

Convective equations in Microphysics-Transport form (Piriou et al., JAS, 2007)

Mcu/d(p)=-u/d(p).u/d(p), both prognostic (Gerard & Geleyn, QJRMS, 2005)

Prognostic, barycentric and conservative phys-dyn interfacing (Catry et al., Tellus-A, 2007)

Sequential handling of both condensation sources, but summing of their inputs for a unique‘microphysics’ call

This ‘microphysics’ is sandwiched between up- et downdrafts’ computations (Gerard, QJRMS, 2007)

Unique vertical loop for the microphysics, made purely ‘local’ thanks to ‘PDF-based sedimentation’ (Geleyn et al., Tellus-A, 2008)

And it works quite like expected … The next viewgraph presents the structure of 6h cumulated

precipitation amounts over the Alps for 4 forecasts valid at 18h range for the initial date 21/6/06 00UTC: Two with 9km mesh-size (left column) and two with 4.7km

mesh-size (right column); Two with ALARO-0-minus-3MT (upper row) and two with

ALARO-0 [i.e. with 3MT] (lower row). One notices the strong ‘grey zone syndrome’ when trying

to apply the ‘classical diagnostic convection scheme’ at the 4.7km mesh-size (upper-right diagramme).

On the contrary, when using the 3MT ensemble of novelties, the precipitation patterns ‘scale’ correctly from one resolution to the other (bottom row).

Scalability of precip. patterns

Operational implementations

At ~9km mesh-size: Cz (4/6/08) Si (16/6/08) Sk (19/8/08) At soon (already in LAEF set-up) Interest in Hr, Ro, Pt, Tr

At ~4.5 km resolution Be (15/1/09) Interest in No

Now about entrainment

(no need to speak about detrainment in 3MT; it is ‘decided’ by microphysics)

Role with respect to the novelties of 3MTEmpiricism of the ‘diagnostic’ set-up value of

its ‘tuning’A prognostic alternative?

Some model-run diagnostics

Two constatations Apart from the autoconversion time scales for

microphysics, the parameters controlling the entrainment rate for the convective ascent’s computation were the only ones which needed retuning whan introducing 3MT in ALARO-0: Doubling of the min and max entrainment rates (to

respectivly 0.00005 and 0.0016 m-1) Dividing by 1.5 the sensitivity to ‘free ascent buoyancy’

(which regulates the maxmin adjustment) Diminishing by a factor 2.5 the account taken of

‘ensembling entrainment’ All this goes in the direction of higher entrainment

rates (more realistic but still below ‘measurements’)

Entrainment matters more for convection in 3MT than in the equivalent ‘static’ scheme

qv

T

Standard ‘static’entrainment

‘Doubled’Entrainment

Max / Min rates=> 3MT choice

Standard ‘static’entrainment

‘Doubled’Entrainment

Max / Min rates=> 3MT choice

STATIC 3MT

Reduction of the difference to the ‘static’ reference via the retuning (3 aspects in it)

qv

T

BEFORE AFTER

Total Total

Total Total

Reduction of the difference to the ‘static’ reference via the retuning (3 aspects in it)

Entr.

Detr.

‘Diagnostic’ / weak entr.

‘3MT’ / strong entr.

‘3MT’ / weak entr.

Structure of the ‘static’ entrainment rate computation (Gerard & Geleyn, 2005)

surf

dhhI eplumeentrnonb )()( .

)(4/14/3

)( surfnxenxn

)(/1

1

)(/1

1

maxmin

bx

bn II

)](1/[,'' .._

cplumeentrnonsurfentrnontop

surfc hhusehobtainingfor

Very heuristic but ‘fine tuned’ by more than 10 years of operational use

Cold pool mechanism Basic entrainment is by nature strong and prevents

immediate deep penetration of convective clouds But the evaporation of first convective precipitation amounts

creates density currents, cold pools and thus ascent-favourable conditions at the edge between the latter ones

Quickly raising plumes entrain relatively less (a mechanism already parameterised by ‘’ in our ‘static algorithm’)

So the idea is to encompass the effect in an hysteresis-like link between past evaporation of precipitations and current entrainment rates; the ‘time-lag’ aspect calls for a prognostic algorithm, with all the associated risks and difficulties.

In his PhD thesis, Piriou proposed and tested the above in a demo-fashion. 3MT in principle allows to go to a more concrete test.

Equations of J.-M. Piriou’s proposal

)/(])1([ max_min_ surfsurfsurf ppf

g

dpvapEpI precconv

p

evap _

0

)(

cpupdraft

evapIc

t

3MT-linked change of variable of L. Gerard

...)/(])1([ max_min_ surfsurfsurf ppf

cp

downdraftE

t

downdraft is treated prognostically like its updraft equivalent and ‘integrates’ all effects of previous evaporation (but resolved +

convective, since the distinction disappears in 3MT)

Improvements by D. Banciu

Replacing f(p/psurf) by an adimensional scaling (inspired by Met-Office’s LES estimates) in (-surf)

‘Observed’ value 3.5. Our min/max bracket [0.3-3.] NB: this quite useful scaling will also be used for the

presentation of the results Quitting the linear relationship Advecting and reinitialising it to the ‘static’ tuning

when no convection is present

Our current equations

]/)(,0max[])1([ maxmin upuponacceleratiE

cp

downdraftE

t 22)1(

downdraft is treated prognostically like its updraft equivalent and ‘integrates’ all effects of previous evaporation (but resolved +

convective, since the distinction disappears in 3MT)

is a fully prognostic quantity

Tuning => cp=5000 s E=2cp

)( surf Hysteresis-control Mironov-type term

First results with ‘prognostic entrainment’

Diagnostic 3MT computation. Histogramme at all model levels of the (admimensional) product of the entrainment rate by the height above the ground

The same but for the ‘best’ tuning (so far) of Piriou’s proposal for a treatment of entrainment with cumulated influence of the past evaporation rates.

=> Correct histogramme structure but too little convective activity!

First results with ‘prognostic entrainment’

Downdraft Mass FluxDivergence

Updraft Mass FluxDivergence

Diagnostic entrainment Prognostic entrainment

(Preliminary) lessons

Prognostic entrainment can mimick the ‘well-tuned’ statistical structure of the ‘static’ case

The space- and time-averaged mass fluxes agree quite well after this ‘tuning’

But the frequency of convective activation is diminished => more intermittency for the ‘prognostic’ case

Unfortunately, we did not get closer to ‘observed’ entrainment rates (our upper bound is still just below the ‘truth’) => the problem stays!

Two ways to look at entrainment (1/3)• First definition: the positive contribution to the

vertical change of mass-flux with height

• Second definition: the rate of mixing of ‘cloud’ and ‘environment’ conservative properties

• In 3MT, both physical processes, though not completly disconnected, are really treated separately => one may try and diagnose them independently of each other

)/,0max(1 pME c

ce

cc pME

/2

Two ways to look at entrainment (2/3)

General agreement, except where the ‘plumes’ start, but details differ, in fact rather significantly for an horizontal average

E1 E2

Case without the ‘’ parameterisation(forget the units)

Two ways to look at entrainment (3/3)

Distinction between the two regimes is even more marked but details elsewhere match better (let us have a closer look)!

E1 E2

Case with the ‘’ parameterisation(forget the units)

‘Pseudo mass-flux’ integrals of E1 and E2

(comparison ‘diagnostic’ vs. ‘prognostic’)

1E

Diagnostic

Prognostic

2E

Diagnostic

Prognostic

Tuning not so bad!

‘Pseudo mass-flux’ integrals of E1 and E2

(comparison of the two methods)

PrognosticDiagnostic

E1E1

E2 E2

Hidden constraint?

Better parallelism

Conclusions

With the additional degrees of freedom of 3MT, the role of entrainment is increased

Retuning of the ‘static’ entrainement rates without touching the algorithm delivers what we believe to be a good reference target for the ‘prognostic entrainment scheme’

The latter delivers some first promising results (more freedom, better dissociation between the two sources of ‘ascent’)

We are very sorry that we did not manage to push the assesment any further before the workshop !