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
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