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Grey Zone committee: Pier Siebesma , Martin Miller, Andy Brown, Jeanette Onvlee. Royal Netherlands Meteorological Institute Technical University Delft The Netherlands [email protected] The Grey Zone The Project Massive GPU computing. The Grey Zone.

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Grey Zone committee: Pier Siebesma, Martin Miller, Andy Brown, Jeanette Onvlee

Royal Netherlands Meteorological Institute

Technical University Delft

The Netherlands

[email protected]

The Grey Zone

The Project

Massive GPU computing



  • Or, as a good approximation, the variances and covariances:

  • as a function of the used resolution (especially in the grey zone)

x= y=4 km

x= y=2 km

x= y=1 km


A posteriori coarse graining
A posteriori coarse graining evolve around finding the subgrid pdf of:

  • Use a reference (LES) model that resolves the desired phenomenum ( x << lphen)

  • Has a domain size much larger than the desired phenomenum ( L >> lphen)

  • Coarse grain the (co)variances across these scales

resolved

subgrid

l = L all subgrid

l = x all resolved


Example 1: A posteriori analysis for LES for shallow convection

Standard deviation of subgrid fluxes

1000m

Subgrid flux

Resolved flux

Coarsed grained length scale l

Dorrestijn, Siebesma, Crommelin, Jonker, 2012


Example 2: A priori analysis for LES for shallow convection convection

  • a posteriori (static) coarse graining : coarse graining the output of one high-res run

  • A priori (dynamic) coarse graining : repeat runs at coarser resolution

Subgrid Flux:

Up to 800m similar results as with the a posteriori analysis.


Example 2: A priori analysis for LES for shallow convection convection

  • a posteriori coarse graining: statically coarse graining the output of one high-res run

  • A priori coarse graining: repeat runs at coarser resolution

  • Turbulent flux is overestimated at resolutions x>1000km

  • Due to an overestimation of the subgrid (parameterized) fluxes.

  • Due to the fact that in LES subgrid flux parameterization is designed to work for large eddy-resolving scale l< 1000m and not beyond!


Example 2: A priori analysis for LES for shallow convection convection

6.4km resolution

100m resolution


Conclusions
Conclusions convection

Each phenomenum has its own “grey zone” typically centered around its typical spatial scale

Stochastic effects are most important within the “grey zone” but extend to scales beyond the grey zone.

Static (a posteriori) coarse graining is instructive but should not be confused with dynamic (a priori) coarse graining.


The project
The Project convection


Proposal (from WGNE 2010 Japan meeting ) convection

  • Project driven by a few expensive experiments (controls) on a large domain at a ultra-high resolution (x=100~500m).

  • Coarse grain the output and diagnostics (fluxes etc) at resolutions of 0.5, 1, 2, 4, 8, 16, 32 km. (a posteriori coarse graining: COARSE)

  • Repeat CONTROLS with 0.5km 1km, 2km, 4km, 8km, etc without convective parametrizations etc (a priori coarse graining: NOPARAMS)

  • Run (coarse-grain) resolutions say 0.5, 1km, 2km, 4km and 8km with convection parametrizations (a priori coarse graining: PARAMS)


Aims convection

  • Gain systematic insight and understanding how models behave in the grey zone with without convential convection parameterizations

  • Provide guidance and benchmark for the design of scale-aware convection parameterizations that could operate in the grey zone


Case Proposal: a cold air outbreak convection

Thanks to: Paul Field, Adrian Hill (Met Office), S. de Roode Technical University Delft Netherlands)

  • The Mesoscale Community is interested to start with an extra-tropical case

  • Cold-air outbreaks are of general interest for various communities

  • Proposal: “Constrain” cold-air outbreak experiment

    31 January 2010

  • Participation of global models, mesoscale models but also from LES models !!

  • Domain of interest: 750X1500 km

  • Fast Transition : ~ 14 hours


Case Proposal: a cold air outbreak convection

3 Different Flavours

  • Global Simulations (at the highest possible resolution up to 3~10 km)

  • Mesoscale Models (Eulerian) at various resolutions LAM-set up

  • Mesoscale/LES Models (Lagrangian). Idealized with periodic BC. highest resolution (~200m)


Attacking the Cloud Feedback Problem convection

Large interest from all modeling communities


Pro’s/Cons of the case convection

  • Cold air outbreak has been on the wishlist of the NWP community for many years

  • Excellent opportunity to bring the mesoscale and the LES community together.

  • It’s only now that high resolution models are able to faithfully reproduce the observed mesoscale structures associated with a cold air outbreak in a turbulence resolving mode.

  • There is a well observed case available (CONSTRAIN)

  • Case is complicated because of the (ice) microphysics .

  • Institutes who could do the Eulerian Case in a turbulent resolving resolution are encouraged to do so. (4000X7500X128 points) see next section

  • Might not have been the first obvious choice for a grey zone perspective from the point of view of global models (Deep convection might have been a more obvious choice for global modelers, but different cases can be considered in the Grey Zone Project)


Status convection

Extensive tests have been done for all 3 flavours over the last year.

Case Description is on the web now:

http://www.knmi.nl/~samenw/greyzone

http://appconv.metoffice.com/cold_air_outbreak/constrain_case/home.html

Volunteers for coordinating/analysing the subprojects have been identified:

Global Model runs : Axel Seifert (MPI Hamburg)

Mesoscale model runs (Eulerian) : Paul Field/Adrian Hill (Met Office)

LES/Mesoscale model runs (Lagrangian): Stephan de Roode/Pier Siebesma ( TU Delft)


Time Line and concluding remarks convection

Submission deadline: April 2013

Meeting on discussion results : second half 2013

Grey Zone should also consider other cases.

Further info: [email protected]

Website: www.knmi.nl/samenw/greyzone


3 high resolution computing
3. High Resolution Computing convection

or, can we do the Eulerian version of the cold air outbreak at a turbulent resolving scale (~100 m)?


Graphical Processor Unit (GPU) for Atmospheric Simulations convection

Jerome Schalkwijk

TU Delft

‘Acceleration’ approach

GPU-Accelerated code

CPU

GPU

Advection

Surface

All relevant data transferred back and forth!

Routine 3

Routine 4

Routine 5

50-100x promised speedup…

Routine 6


Advection convection

Surface

Routine 3

Routine 5

Routine 6

GALES

GPU-resident Atmospheric Large-Eddy Simulation

Acceleration

Residency

CPU

GPU

Large 3D datasets stay on the GPU – no transfer needed!

Routine 4


Increasing the problem size convection

Multi-GPU simulations: embarrassingly parallel



MPI scaling

Increasing the problem size

Multi-GPU simulations: multi-level parallel LES


Thank You ! scaling


Local workflow! scaling

Thank You !

Editing simulation settings

Interaction

while simulating!

Schalkwijk, Griffith, Post & Jonker

March 2012


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