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

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Presentation on theme: "© Crown copyright Met Office Radar data from cold air outbreak during Constrain Kirsty McBeath, Paul Field."— Presentation transcript:

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

2 © Crown copyright Met Office Table of Contents Introduction Overview of radar observations Variations applied to UM Cluster analysis of data

3 © Crown copyright Met Office 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 31 st 2010 which coincides with flight b507 of the BAe-146 research aircraft MODIS 31 st Jan 2010 Introduction

4 © Crown copyright Met Office Overview of Radar Observations

5 © Crown copyright Met Office 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°: km 1.0°: 54-85km 1.5°: 32-64km 2.5°: 30-42km 150km 1.91 ±0.36km

6 © Crown copyright Met Office Reflectivity and rain rate Conversion from radar reflectivity (dBz) in to rainrate (mm/h), is typically approximated by: Z = 200R 1.6 This relation includes assumptions about drop size distributions and phase of precipitation This conversion can introduce additional uncertainties into the radar data 10dBz4mm/day 20dBz16mm/day 30dBz66mm/day 5dBz1mm/day

7 © Crown copyright Met Office Model data

8 © Crown copyright Met Office Model data Region examined is too far North for UKV (edge effects close to boundaries) Nested version of UKV model set up to cover the region without any edge effects Covered region from 10.16W,48.45N to 3.54E,59.18N

9 © Crown copyright Met Office Model Reflectivity Reflectivity values for UKV model computed using model microphysics data Reduces processing done on radar data Removes assumptions used when converting reflectivity to rain- rate

10 © Crown copyright Met Office 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

11 © Crown copyright Met Office 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 ( T nuc =-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

12 © Crown copyright Met Office No ice All ice processes switched off by setting T nuc =-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

13 © Crown copyright Met Office Model variations JobSh. Dom. B.L. T nuc = -18CAcE = 0.1No IceField P.S.D3D Smag. dimsh dimsp X dimsq X dimsn X dimsk X dimsi XX dimsz XX dimsy XXX dimsu XXXX dimsw XXX

14 © Crown copyright Met Office Cluster analysis

15 © Crown copyright Met Office Cluster Analysis 10dBz (~4mm/day) threshold used to select regions of precipitation in both datasets

16 © Crown copyright Met Office Cluster Analysis Identified cells tracked in time for both datasets Whole frame advected to find overlap between cells Fractional overlap for calculated for each overlapping pair of cells Overlap threshold used to determine if identified cells are the same Cells excluded from dataset if they moved outside the region of interest, or were only seen to decay 147 cells tracked in radar data 62 cells tracked in model data

17 © Crown copyright Met Office 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

18 © Crown copyright Met Office Cell Size with lifetime Radar RMSE (from std dev) = km dimsi fails to capture growth/decay of cells very well dimsz captures cell growth/decay quite well (has low RMSE value)

19 © Crown copyright Met Office Cell lifetime Radar mean lifetime = 69±3mins dimsu ( Sh. Dom. B.L., T nuc =-18°C, AcE=0.1 & Field P.S.D. ) has mean lifetime within 1 of radar Other runs with all do worse than control run for mean cell lifetime values

20 © Crown copyright Met Office Cell reflectivity Radar mean reflectivity = 16.9±1.4 dBz dimsh (ctrl), dimsq ( AcE=0.1 ) and dimsz ( Sh. Dom. B.L. and T nuc =-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

21 © Crown copyright Met Office 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

22 © Crown copyright Met Office Size and reflectivity Symbol sizes increase with cell lifetime

23 © Crown copyright Met Office JobBetter than controlWorse 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 reflectivity with lifetime mean cluster reflectivity mean cluster lifetime mean cluster reflectivity dimsi mean cluster size* size with lifetime mean cluster lifetime mean cluster reflectivity reflectivity with lifetime dimsz mean cluster size size with lifetime reflectivity with lifetime mean cluster reflectivity mean cluster lifetime mean cluster reflectivity dimsy reflectivity with lifetime mean cluster lifetime mean cluster reflectivity size with lifetime dimsu mean cluster lifetime*mean cluster reflectivity reflectivity with lifetime 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 (T nuc = -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

24 © Crown copyright Met Office Effect of Changing Cluster Threshold

25 © Crown copyright Met Office Impact of threshold on Cell Size Cluster analysis repeated using a range of reflectivity thresholds from 5-30dBz (1mm/day - 66mm/day) Both radar and model data show a decrease in cell size as reflectivity threshold increases seen in enclosing circle diameter and in pixel area

26 © Crown copyright Met Office Impact of reflectivity threshold on fill fraction Model fill fraction shows little variation with reflectivity threshold compared to radar fill fraction

27 © Crown copyright Met Office Next steps

28 © Crown copyright Met Office Questions


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