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

Exeter Met Office Unified Model Forecasts Herstmonceux Met Office Radiosonde Thruxton UFAM/Manchester Cessna IMK Dornier km range ring 40 km range ring Aberystwyth MST Wind Profiler Dunkeswell Met Office Wind Profiler Swanage UFAM/Aberystwyth Radiosonde Preston Farm UFAM/Leeds Radiosonde Camborne Met Office Radiosonde Met Office Wind Profiler Reading Forecast Centre JCMM UFAM/Reading Radiosonde UFAM/Leeds Sodar 2 and AWS Potsdam GPS WV Chilbolton UFAM/Reading 1275 MHz Radar 35 GHz Radar 3 GHz Radar 905 nm Lidar Radiometer (RAL) WV Lidar UFAM/Aberystwyth Ozone Lidar Bath GPS WV UFAM/Leeds Sodar 3 IMK Radiosonde 1 IMK Energy Balance Station 1 IMK Doppler Lidar Faccombe UFAM/Salford Doppler Lidar UFAM/Salford Radiometer Salford AWS Bath IMK Radiosonde 2 IMK Energy Balance station 2 Potsdam GPS WV Linkenholt UFAM/Aberystwyth Wind Profiler Potsdam GPS WV Met Office Radiometer Met Office Ceilometer Met Office Radiosonde Met Office Cardington Mobile Radiosonde Facility 16 Leeds AWSs Alice Holt UFAM/Leeds Sodar 1 Potsdam GPS WV Larkhill Met Office Radiosonde Potsdam GPS WV NERC Dornier 228 (based in Oxford) (Cyril Morcrette, University of Reading, 2006) CSIP field campaign (2005) 200 km

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 vapour 200 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 OrographyWithout Dartmoor Rain rate (mm/hour)

Downstream hole in cloud Humphrey Lean, JCMM, Met Office, UK Cloud fraction: normal Orography Cloud fraction: without Dartmoor Cloud fraction

Downstream hole in cloud (Vis image) Humphrey Lean, JCMM, Met Office, UK

CSIP IOP km UM 06Z from 12 km analysis Meteosat IR NIMROD Rain JCMM Joint Centre for Mesoscale Meteorology (Richard Forbes, JCMM)

IOP 18: Cold pool and bow echo (Richard Forbes and Peter Clark, JCMM) JCMM Joint 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 2 Arc 3 Arc 1 Primary storm 08:45 UTC 09:45 UTC 150 km Could Arcs 2 and 3 have been triggered by a convectively generated gravity wave?

Modelled Waves Potential temperature perturbations in large eddy model runs N=1N=2N=1N=2 N=3 Cold 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 Model Vertical 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. 10 th July 2004 case (pilot campaign)

IOP 5 – Role of cirrus shading Pale blue: thin high cloud Pale green: low cloud White: thick high cloud ~ 200 km (Marsham et al, Parts I and II, submitted to QJRMS, 2006).

IOP 5 Role of cirrus shading Pale blue: thin high cloud Pale green: low cloud White: thick high cloud Radar rainrate MSG: 13:00 UTC (false colour)MSG: 12:00 UTC (false colour) ~ 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) UTC

Observed surface sensible heat flux and solar irradiance Clear sky, 12:00 UTC ~ 200 W/m 2 Cloudy sky, 12:00 UTC ~0 to 50 W/m 2

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)

LEM – moving warm anomaly t=0t=T Distance Heat added (Q) Q2Q2 Q1Q1 D M.F F v Surface Pressure

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) Time to level of free convection (1600 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: TKE Contours: 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 K 240 K 300 K Infrared brightness temperature WVMR

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 simulations 3D, 5 km by 5 km, 50 m grid-spacing WVMR TKE Contoured potential temperature. Coloured WVMR Contoured potential temperature. Coloured TKE Contoured potential temperature. Coloured WVMR Time (hours)  TKE lags flux change more than WVMR

Time-dependence of the observed correlation between BL variables and the cirrus MSG-σ(w) MSG-MSG MSG- 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

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

+ + 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 WVMR Time (UTC) + +  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