The Convective Storm Initiation Project:

Large eddy model studies of initiation processes

With thanks to: Cyril Morcrette and Keith Browning (University of Reading), Peter Clark, Richard Forbes and Humphrey Lean (Joint Centre for Mesoscale Meteorology), Ulrich Corsmeier, Norbert Kalthoff and Martin Kohler (IMK), Emily Norton (University of Manchester) and the rest of the CSIP team.

John Marsham, Doug Parker and Alan Blyth (The University of Leeds, UK).

Talk Outline Background - CSIP and its

motivation Two well forecast CSIP IOPs

• Upper level forcing, coastal effects and cold pools

Process studies using the large eddy model (LEM)

Motivation Poor forecasts of convective

precipitation in the UK – especially initiation of convection

Flood prediction – extreme events The new generation of high-

resolution non-hydrostatic numerical weather prediction models

• 1.5 km resolution for UK in 2010

ExeterMet Office Unified Model Forecasts

HerstmonceuxMet Office Radiosonde

ThruxtonUFAM/Manchester Cessna

IMK Dornier 128

95 km range ring

40 km range ring

AberystwythMST Wind Profiler

DunkeswellMet Office Wind Profiler

SwanageUFAM/Aberystwyth Radiosonde

Preston FarmUFAM/Leeds Radiosonde

CamborneMet Office RadiosondeMet Office Wind Profiler

ReadingForecast Centre JCMMUFAM/Reading RadiosondeUFAM/Leeds Sodar 2 and AWSPotsdam GPS WV

ChilboltonUFAM/Reading 1275 MHz Radar35 GHz Radar3 GHz Radar905 nm LidarRadiometer (RAL)WV LidarUFAM/Aberystwyth Ozone LidarBath GPS WVUFAM/Leeds Sodar 3IMK Radiosonde 1IMK Energy Balance Station 1IMK Doppler Lidar

FaccombeUFAM/Salford Doppler LidarUFAM/Salford RadiometerSalford AWS

BathIMK Radiosonde 2

IMK Energy Balance station 2Potsdam GPS WV

LinkenholtUFAM/Aberystwyth Wind ProfilerPotsdam GPS WVMet Office RadiometerMet Office CeilometerMet Office Radiosonde

Met Office Cardington Mobile Radiosonde Facility

16 Leeds AWSs

Alice HoltUFAM/Leeds Sodar 1Potsdam GPS WV

LarkhillMet Office RadiosondePotsdam GPS WV

NERC Dornier 228(based in Oxford)

(Cyril Morcrette, University of Reading, 2006)

CSIP field campaign (2005)

200 km

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Processes of convective initiation

Coastlines and orography (<300 m in CSIP area, < 1500 m in UK) contrasts with IHOP and COPS regions

Results from CSIP

18 Intensive Observation Periods (IOPs) 7 “α” IOPs, 7 “β” IOPs and 4 “γ” IOPs Convection originated above the boundary layer in only one IOP

IOP 1 Coastal convergence and a PV anomaly

Radar rainrate

Meteosat (visible)

Meteosat: water vapour200 km

200 km200 km

11 UTC Rainrates

(Cyril Morcrette (University of Reading), Pete Clark and Richard Forbes (JCMM)).

1.5 km UM captures: (1) Convergence along peninsula (2) Storm deepening from upper level PV anomaly

Radar1.5 km UM

Map of height of the capping inversion derived from 20 RHIs.

The lid has been raised by the convergence line.

Map of height of the capping inversion in 1.5 km version of the Met Office Unified Model.

Cyril Morcrette, University of Reading, 2006

12 UTC 1.5km model (Humphrey Lean, JCMM, Met Office, UK)

Effect of Dartmoor hills on final shower

Normal Orography Without Dartmoor

Rain rate (mm/hour) Rain rate (mm/hour)

Downstream hole in cloud

Humphrey Lean, JCMM, Met Office, UK

Cloud fraction: normal Orography

Cloud fraction: without Dartmoor

Cloud fraction Cloud fraction

Downstream hole in cloud (Vis image)

Humphrey Lean, JCMM, Met Office, UK

CSIP IOP 181.5 km UM 06Z

from 12 km analysisMeteosat IR

NIMROD Rain

JCMMJoint Centre

for Mesoscale Meteorology

(Richard Forbes, JCMM)

IOP 18: Cold pool and bow

echo(Richard Forbes and Peter Clark,

JCMM)

JCMMJoint Centre

for Mesoscale Meteorology

The sensitivity to the model microphysics is being explored

7

K

Process Studies Observational and large eddy

modelling (LEM) studies to understand processes

• Secondary initiation (pilot campaign case)• Role of cirrus shading (IOP 5)

The Met Office large eddy model (LEM)

1D, 2D or 3D non-hydrostatic model

Bulk microphysics• Single moment cloud water & rain• Double moment ice, snow and

graupel• Edwards-Slingo or Fu-Liou radiation• Periodic lateral boundary conditions

Pilot campaign: secondary initiation

Arc 1a

(Observations from Morcrette et al, 2006).

Arc 1

Primary storm

Arc 2Arc 3

Arc 1

Primary storm

08:45 UTC

09:45 UTC

150 km

150 km

Could Arcs 2 and 3 have been triggered by a convectively generated gravity wave?

Modelled WavesPotential temperature perturbations in large eddy model runs

N=1N=2

N=1 N=2

N=3N=3Cold pool Wind

Tropopause

Boundary layer depth

Modelled effects of waves on CIN

9:15 UTC MSG image

Arc 2 Arc 3Arc 1

(Marsham and Parker, QJRMS, 2006)

CIN at surface in LEM

Observed cloud

Observed cloud and modelled CIN

Contours: Modelled CIN

• N=1 & N=2 mode inhibit convection.• N=3 mode initiates arcs.

Waves in the Unified ModelVertical velocities at

850 hPa in the Unified Model.(From Richard Forbes, JCMM, The University of Reading).

Summary

• The fastest waves inhibit convection• The slower N=3 mode initiates convection• We need a high-resolution non-hydrostatic NWP model to represent this, but implicit time-step of UM damps waves.• Initial results from the main CSIP campaign suggest that this case is by no means unique.

10th July 2004 case(pilot campaign)

IOP 5 – Role of cirrus shading

Pale blue: thin high cloudPale green: low cloudWhite: thick high cloud

~ 200 km

(Marsham et al, Parts I and II, submitted to QJRMS, 2006).

IOP 5Role of cirrus

shading

Pale blue: thin high cloudPale green: low cloud White: thick high cloud

Radar rainrate

MSG: 13:00 UTC (false colour)

MSG: 12:00 UTC (false colour)

~ 200 km ~ 200 km

How significant is variable cirrus shading for convective initiation?

Questions to be addressed

What effect does cirrus have on surface fluxes?

• Observations What effect do surface flux variations

have on convective initiation? • Observations and modelling

What effects do we see in the boundary layer (BL)?

• Observations and modelling

Fluxes at Chilbolton

(Surface flux data are from Ulrich Corsmeier, Norbert Kalthoff and Martin Kohler (IMK). Solar flux data are from The Chilbolton Facility for Atmospheric and Radio Research).

6 8 10 12 14 16 18 UTC

Observed surface sensible heat flux and solar

irradiance Clear sky, 12:00 UTC~ 200 W/m2

Cloudy sky, 12:00 UTC ~0 to 50 W/m2

Observed transmission and Meteosat infrared brightness

temperatures (BTs)

So, Meteosat infrared BTs -> surface fluxes

Sensible flux estimated from visible MSG data

Sensible heat fluxes from the 4 km Unified Model

(UM data from Richard Forbes, JCMM, The University of Reading)

Estimated surface fluxes

Flux (W/m2)

2000 15050 100

LEM – moving warm anomaly

t=0 t=T Distance

Heat

ad

ded

(Q

)

Q2

Q1

D M.F Fv S

urf

ace

Pre

ssure

Location of convective initiation

13:00 UTC (false colour)

Cloud-top height: 1100 m, 1600 m, 3000m

LEM results

200 km

Timing of convective initiation

12:00 UTC observations(D=25 km, v=15 m/s, M=4)

Tim

e t

o level of

free c

onvect

ion (

16

00

m)

/ hours

Straight line for:(i) No horizontal mixing(ii) No convergence effects

Extra heat added by “hot spot” / unperturbed flux = (M-1)D/v

Observed convective initiation(Cyril Morcrette and Keith Browning, University of

Reading)

Grey-scale infrared BTs at time of start of tracks (black= cold)

11:30 UTC 12:00 UTC Rain Cumulus

(26 tracks in total)

25 start at rear edge of gaps/leading edge of cirrus/clear-sky A significant fraction start near edge of 250 K cirrus-mask 24 tracks start at BTs > 250 K

Effects on the boundary-layer

Profiles: • Radiosondes (one hour, ~50 km

spacing)• Windprofiler (15 min)

Boundary-layer:• Aircraft (1 s, 60 m)

BL growth: Linkenholt

windprofiler(Emily Norton, University of

Manchester)

Colours: 1290 MHz windprofiler (Emily Nortin, University of Manchester)

Contours: Chilbolton potential temperature : Chilbolton surface sensible heat flux

(Windprofiler 20 km north of Chilbolton site)

Windprofiler

TKE in LEM

Colours: TKEContours: Potential temperature :Estimated Linkenholt surface fluxes

Time (UTC)

Effects of Cirrus on WVMR

Aircraft (IMK Dornier-128) WVMR at ~500 m (colour) on Meteosat 11 μm BT (greyscale, black=cold)

240 K 300 K240 K 300 K

Infrared brightness temperature Infrared brightness temperature

WV

MR W

VM

R

Effects of cirrus on the BL

Drier, warmer and less turbulent under cirrus

Latent/sensible ratio increases with cirrus cover

Positive latent flux for zero sensible Entrainment proportional to sensible flux How does cirrus lead to drying?

LEM simulations3D, 5 km by 5 km, 50 m grid-spacingWVMR

TKE

Contoured potential temperature. Coloured WVMR

Contoured potential temperature. Coloured TKE

Contoured potential temperature. Coloured WVMR

Time (hours)

Time (hours)

TKE lags flux change more than WVMR

Time-dependence of the observed correlation between BL variables

and the cirrusMSG-σ(w)MSG-MSGMSG- σ(wvmr)MSG-WVMR

WVMR is a faster response than σ(w) and σ(wvmr)

MSG-MSG

MSG - σ(w)

MSG-wvmr

MSG - σ(wvmr)

Meteosat data after BL data

Meteosat data before BL data

Drying at 500 m due to cirrus

(1a) Entrainment lags surface flux – dries upper boundary-layer (fast response)

(1b) Stable layer created at surface – traps moist thermals (fast response)

(2) Cirrus induces circulations (maximum at rear edge of cirrus)

Evidence of cirrus induced circulations

Colours: WVMR

Contours: potential temperature

White line: Meteosat infrared BT

8 10 14 1612

Pdfs of BL variablesCirrus (coldest 25% of Meteosat BTs)Clear-skies (warmest 25% of Meteosat BTs)

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MSG: 1300 UTC, false colour

WVMR variations in the boundary-layer

Can cirrus explain BL differences?Chilbolton profile

Chilbolton flux

Reading flux

Reading profile

All contoured potential temperature, coloured WVMRTime (UTC)Time (UTC)

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Simulation using Reading profile is always moister, whichever flux is used

Variable cirrus cover cannot explain this difference

Summary Cirrus had significant effects on

surface fluxes (factor of 4 or more) Observed convective initiation

consistent with LEM simulations i.e. in gaps/at leading edge of cirrus

Cirrus shading led to drying in mid-boundary layer (suppression of warm wet thermals)

Differences in cirrus not responsible for wetter boundary-layer at Reading

Conclusions (I) Forecasting the larger scale is very

important, but not sufficient, for forecasting initiation

High resolution (~ 1km) NWP capture many of the low-level forcings which dominate in the UK (coastlines and low hills)

• Convergence from these frequently dominates the initiation. These are well resolved even if convection itself is not.

• This also allows some surprisingly accurate forecasts of secondary initiation from cold pools

Conclusions (II) Process modelling has allowed some

more subtle mechanisms to be explored

• Convectively generated gravity waves • Not well represented by the UM

• Variable shading from cirrus anvils • Hard to forecast – a challenge for data

assimilation• Complex effects on boundary layer

• Difficult for a forecast model?

• Pre-existing variations in WVMR are important

Ongoing work Much of the datasets from July 2004

and June/July/Aug 2005 are unexplored

Role of upper level lids and dry layers Primary initiation from cloud streets

and thermals Secondary initiation

• Role of microphysics and extent of control on convective organisation

Warm rain