© Crown copyright Met Office Radar data from cold air outbreak during Constrain Kirsty McBeath, Paul Field.

© Crown copyright Met Office

Radar data from cold air outbreak during ConstrainKirsty McBeath, Paul Field


• Looking at cases of cold air outbreak in the Northwest approaches

• 4 flights during Constrain examined these conditions during January 2010

• Radar data from these cases used for comparisons with UKV model

•This data is from a case on January 31st 2010 which coincides with flight b507 of the BAe-146 research aircraft

MODIS 31st Jan 2010

Introduction


Overview of Radar Observations


Composite radar data

• Data available every 5 minutes for 24 hour period

•Scans performed at a range of elevation angles: 0.5°, 1.0°, 1.5°, 2.5°

• 4 scan angles intercept cells at different distances from radar

• Data from 4 scan angles combined to produce one dataset which captures all cells

• 0.5°: 75-150km

• 1.0°: 54-85km

• 1.5°: 32-64km

• 2.5°: 30-42km

150km

1.91 ±0.36km


Model data


Radar Model

Reflectivity values for UM computed using model microphysics data, this reduces processing done on radar data and removes assumptions used when converting reflectivity to rain-rate


• Shear dominated boundary layer• Local Richardson number used as indicator of shear dominating

convection: if so then boundary layer diagnoses stratocumulus topped boundary layer (see Bodas-Salcedo et al. 2011)

• Reducing ice nucleation temperature (Tnuc=-18°C)

• Changing the primary hetrogemeous ice nucleation temperature from -10°C to -18°C. This inhibits ice production until the boundary layer top approaches 4km

• Reducing autoconversion efficiency (AcE = 0.1)

• The autoconversion efficiency is usually set to 0.55 (using the Cotton formulation of autoconversion), this is reduced to 0.1 to reduce the transfer if cloud water to precipitation

Changes made to model


• No ice• All ice processes switched off by setting Tnuc=-50°C and

converting any existing ice to liquid

• Field PSD• Snow representation changed from standard exponential (Wilson

and Ballard 1999) to representation of Field et al. (2007)

• 3D Smagorinsky• Vertical mixing done explicitly using 3D Smagorinsky approach

rather than boundary layer scheme

Changes made to model


Model variations

Job Sh. Dom. B.L.

Tnuc = -18C AcE = 0.1 No Ice Field P.S.D 3D Smag.

dimsh

dimsp X

dimsq X

dimsn X

dimsk X

dimsi X X

dimsz X X

dimsy X X X

dimsu X X X X

dimsw X X X


Cluster analysis


Cluster Analysis

10dBz (~4mm/day) threshold used to select regions of precipitation in both datasets


Cell Size

Radar mean size = 10.82±0.26km

dimsq (AcE=0.1) and dimsi (Sh. Dom. B.L. and AcE=0.1) produce mean sizes within 1 of radar mean


Cell Size with lifetime

Radar RMSE (from std dev) = 0.617 km

dimsi fails to capture growth/decay of cells very well

dimsz captures cell growth/decay quite well (has low RMSE value)


Cell lifetime

Radar mean lifetime = 69±3mins

dimsu (Sh. Dom. B.L., Tnuc=-18°C, AcE=0.1 & Field P.S.D.) has mean lifetime within 1of radar

Other runs with all do worse than control run for mean cell lifetime values


Cell reflectivity

Radar mean reflectivity = 16.9±1.4 dBz

dimsh (ctrl), dimsq (AcE=0.1) and dimsz (Sh. Dom. B.L. and Tnuc=-18°C) produce mean reflectivity within 1 of radar mean

None of the variation runs produce mean cell reflectivity values closer to the radar mean than the control run


Cell reflectivity with lifetime

Radar RMSE (from std dev) = 1.42 dBz

Runs which do well for mean reflectivity, also do well when examining reflectivity with cell lifetime

dimsq and dimsz both out-perform control when looking at RMSE over cell lifetime


Job Better than control Worse than control

dimsp mean cluster size

size with lifetime

mean cluster lifetime

mean cluster reflectivity

reflectivity with lifetime

dimsq mean cluster size*

size with lifetime


mean cluster reflectivity†



dimsi mean cluster size*

size with lifetime




dimsz mean cluster size

size with lifetime


mean cluster reflectivity†



dimsy reflectivity with lifetime




size with lifetime

dimsu mean cluster lifetime* mean cluster reflectivity


mean cluster size

size with lifetime

dimsq (AcE = 0.1) and dimsz (Sh. Dom. B.L. and Tnuc= -18°C) out-perform the control run over 3 variables

dimsk (Sh. Dom. B.L.), dimsn (3D Smag.) and dimsw (Tnuc= -18°C) all perform worse than the control run across all variables examined here

* Within 1 of radar mean and better than control† Within 1 of radar mean but worse than control


Questions

© Crown copyright Met Office Radar data from cold air outbreak during Constrain Kirsty McBeath, Paul Field.

Documents

model slide

radar reflectivity dbz

introduction slide

model microphysics data

lifetime radar rmse

rain rate slide

rainrate slide

paul field slide