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DYnamical and Microphysical Evolution of Convective Storms Thorwald Stein, Robin Hogan, John Nicol DYMECS.

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Presentation on theme: "DYnamical and Microphysical Evolution of Convective Storms Thorwald Stein, Robin Hogan, John Nicol DYMECS."— Presentation transcript:

1 DYnamical and Microphysical Evolution of Convective Storms Thorwald Stein, Robin Hogan, John Nicol DYMECS

2 Overview Analysis of storm regions in Nimrod and UKV 3Z forecast Tracking storm regions in rainfall data Prioritizing storms to scan with the Chilbolton radar A few interesting wet summer days

3 Nimrod data 16 UK C-band radars ( GHz, 5cm wavelength) 1x1 km grid, 5min intervals Study 400x400 km region centered on Chilbolton

4 Rainfall region analysis Set rainfall threshold (1mm/hr) and minimum area (4km 2 ) for regions to be labelled Study daily statistics from hourly snapshots for model (UKV 3Z forecast) and observations

5 Observations (Nimrod) Normalised time Normalised area Obtain mean evolution of area Model (UKV 3Z)

6 Combine area and rainfall for mean storm life cycle Observations (Nimrod) Normalised mean rainfall Normalised area Model (UKV 3Z) Modelled storms stay too long at peak area Modelled storms all have peak rainfall at the same time Normalised area

7 Tracking storms At T+1, compare image with previous time step Use TITAN overlap method to check for storm movement: K1(T) L1(T+1) U B= (K1,L1) If OV(K1,L1) = A(B)/A(K1) + A(B)/A(L1) > threshold (e.g. 0.6) Then L1(T+1) is same storm as K1(T)

8 Tracking storms L1 gets a new label (no overlap) L2 gets a new label (OV(K1,L2) < threshold) L3 gets label of K1 (OV(K1,L3) > OV(K1,L4)) and defined as “parent” L4 gets a new label, but defined as “child” L5 gets label of K2 (OV(K2,L5) > OV(K3,L5)) and property “accreted K2, K3” K1 L1 L2 L3 L4 K2 K3 L5 K4

9 Tracking storms What if K4 were fast-moving? – Use velocity information… Taking velocity as displacement of centroid brings trouble for breaking/merging events. Use FFT method to track displacement between rainfall images at larger scale K1 L1 L2 L3 L4 K2 K3 L5 K4

10 Per storm, store: – Area – Azimuth – Range – [u,v] – Centroid – Bounding box – Et cetera... Local rainfall maxima within storm (core, cell) work in progress Prioritizing Storms

11 Prioritizing storms Too near: Miss tops of storm or takes too long to finish RHI Too far: Miss low-level precipitation and coarser resolution Get rainfall maxima to study convection and convergence

12 Scan scheduler: – Read nimrod scene – Prioritize storms – Issue radar commands Scan strategy: – 4 RHI scans through each core in (clockwise- most) storm 1 – PPI volume scan (10 PPIs) through storm 1 – Repeat for next storm (anti-clockwise) – Finish with low-level PPI back to Prioritizing Storms

13 Met Office 1.5 km model Nimrod on 26 August 2011 Rain rate (mm h -1 ) Chilbolton radar 3D Volume Scans Study evolution of: -Storm area (using different IWC and rainfall thresholds) -Storm height (id.) -Different storm features (identification of convective core, anvil, stratiform)

14 Obtain ice water content in anvils and convective towers Obtain precipitation (rain and hail) from low-level PPI scans Derive W from analysis of consecutive RHI, monitoring advection of turbulent structures Radial velocity Reflectivity Nimrod rainfall


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