Nowcasting of Severe Weather from Satellite Images (for Southern

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Nowcasting of Severe Weather from Satellite Images (for Southern Europe) Petra Mikuš Jurković

Forecasting/ nowcasting of convective storms NWP models cannot well predict the exact location and intesity of convective storms Thunderstorms often produce large hail, severe wind, strong rain, tornadous, lightning For detection and monitoring of convection forecasters often use remote sensing data satellite, radar and lightning data

Benefits of using satellite imagery 30-45 min Courtesy: John Mecikalski to 75 min Pre-convective environment Providing information on the preconvective envirnment, identify general air mass properties Convective initiation Identify the convective initiation phase (before they are seen on radar) Mature convective storms Providing information about cloud tops process useful to estimate storm severity

Pre-convective environment Instability indices derived from satellite data (MPEF GII Global Instability Index) K Index (KI) KO Index (KO) Lifted Index (LI) Total Precipitable Water (TPW) Indicate the location with high potentional for convection development Usually describe a temperature or moisture differences between atmospheric levels Only possible over clear sky!!!

Physical Retrieval GII algorithm Optimal estimation algoritham NWP PROFILES SEVIRI RTTOV T 0 (p),q 0 (p) T 1 (p),q 1 (p) T n (p),q n (p) WV 6.2 WV 7.3 Bias correction Tb SEVIRI Tb RTTOV Tb SEVIRI - Tb RTTOV <threshold? IR 10.8 IR 12.0 IR 13.4 YES T 0 (p),q 0 (p) NO OPTIMAL ESTIMATION ALGORITHM

Courtesy: Ivan Smiljanić

Courtesy: Ivan Smiljanić

False alarm at the cloud edges retrievels is contaminated by non-detected clouds or cloud edges better spatial resolution provide more precise values of instability indices K - Index The high values of K- Index is produced by cloud contaminated pixels Courtesy: Marianne König

Convective initiation Interest fields Physical basis (Mecikalski et al., 2010) Critical value 10.8 µm TB Cloud-top height/glaciation 253-273 K 10.8 µm TB 15 min trend Cloud growth rate 50-5 C 10.8 µm TB 30 min trend Cloud growth rate <15 min cooling 6.2-7.3 µm difference Breaking of capping inversion/cloud depth 15-0 C 6.2-10.8 µm difference Cloud height relative to dry air aloft 25-0 C 6.2-10.8 µm 15 min trend Cloud growth towards dry air aloft 3-30 C 8.7-10.8 µm difference Cloud-top glaciation 10-0 C 8.7-10.8 µm30 min trend Cloud-top glaciation growth 1-10 C 12.0-10.8 µm difference Height relative to mid- to upper-troposphere 3-0.5 C 12.0-10.8 µm 15 min trend Cloud growth toward mid- to uppertroposphere 12.0-10.8 µm 30 min trend Cloud growth toward mid- to uppertroposphere Tri-channel difference [(8.7-10.8)-(10.8-12.0)] Cloud-top glaciation 0.5-10 C 0.5-10 C 10-0 C Tri-channel 15 min trend Cloud-top glaciation growth 0.5-10 C Tri-channel 30 min trend Cloud-top glaciation growth 1-10 C Critical values is not fixed need to be regionally tunned Courtesy: J. Mecikalski; Z. Kocsis

several pixels were detected with CI algorithm later a severe convective system was formed Day microphisic RGB orange colours small particles at the top indicate strong updraft Courtesy: Maria Putsay

Rapid developing thunderstorms (RDT) http://www.nwcsaf.org/products/safnwc_rdt_europe.html online, every 3 hours The output products life cycle stage: triggering growing trajectory of the system expected move for the next hour mature dissipating

Severe storms RGB R = WV6.2 - WV7.3 G = IR3.9 - IR10.8 B = NIR1.6 - VIS0.6 Convection monitoring and identifing CBs with small or large ice particles http://www.eumetrain.org/data/3/34/rgbcal_ch9.swf cold storms with small ice particles strong updraft cold Cbs with large ice particles normal updraft

HRV Severe Storms RGB OT, small ice particles, strong updraft 27.05.2014; 14:30 UTC Thick Ice Cloud (large ice) Thick Ice Cloud (small ice)

1 2 2 Courtesy: Daniel Rosenfeld Very strong updraft small ice particles yellowish colors in RGB images Distribution of hailstone maximum sizes and kinetic energy very large hailstones (20 25 mm) maximum kinetic energy of the hailstones > 200 J/m 2 causes heavy damages to all plants

Mature convective storms HRVIS usefull information about storm top processes Overshooring tops IR 10.8 µm

Sandwich product IR 10.8 micron blended by HRV image (Setvak et al, 2010)

OTs, cold ring and cold U/V are often associated with severe weather at the ground heavy rain, large hail, severe wind, tornadous CENTRAL WARM SPOT (CWS) COLD RING DISTANT WARM AREA (DWA) CLOSE-IN WARM AREA (CWA) COLD U Courtesy: Martin Setvak Very good indicator that some severe weather conditions could be expected Not a prove of the severity!

2.5 minute MSG rapid scan experiments http://essl.org/cwg/?p=417 to better understand storm top processes preparation for the MTG better temporal and spatial resolution can improve detection of potentionaly dengerous convective cells The Meteosat-8 2.5-minute rapid scan sessions: 17 May 2013 17 June 2013 20 June 2013 29 July 2013 Storms over northeast Italy: 12 September 2012, 06:00 08:55 UTC Meteosat-10 (MSG-3) experiment

HRV IR10.8 BT (200-240K) sandwich HRV & Storm RGB sandwich HRV & IR10.8 BT Courtesy: Martin Setvak

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Thank you!!! mikus@cirus.dhz.hr

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