Radars in Helsinki Testbed Elena Saltikoff, FMI 9.5.2019

Tutkia tutkia – Radars to find out Where’s precipitation How much ? 5 min, 1 km res. Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

A radar does not measure precipitation, just scattering of microwaves P= Measured reflected power (watts 10-13) Dual Pol can improve QPE by improving these Clutter cancellation Z=Reflectivity by precipitation (dBZ) Assume precipitation type Z=aRb, assume a and b R=Rainfall intencity (mm/h) Not so easy for gauges either Integrated rainfall in N hours (mm) Rainfall in river catchment area (m3) Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Reflectivity and velocity Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Total dBZ Velocity Filtered dBZ Rho Clutter can be defined as Microwaves scattered by unwanted objects Total dBZ Velocity Filtered dBZ Rho Hills Hill speed zero m/s No hills Sea clutter Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Profile measurement volume The bad news: we live on a spherical globe. For FMI standard products, we compensate as much as we can... Profile measurement volume h r Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019 1(2)

Weather Radars in Helsinki Testbed Ready made datasets – gif images dBZ: Reflectivity images every 15 minutes are composites of 4 FMI radars: Vantaa in the centre, Ikaalinen in Northwest, Korpo in Southwest and Anjalankoski in east vpr: Vertical profiles of reflectivity separately from each above mentioned individual radar. Also as text files. Rho and ZDR: dual polarization parameters hourly from Kumpula radar at Helsinki University Campus Data archived as IRIS raw files (typically 2-8 Mb) At FMI process in Jordan or in Harry At University, process in Analysis Possible to convert to other formats

Radar data parameters FMI data is the same from all radars, all campaigns Kumpula radar data is different for each campaign August 2005: 5 tasks repeated every 10 minutes Nov 2005 and May 2005: two different schedules alternating, some tasks the same all month Tasks described in a pdf at the testbed website Inventory of datasets available too Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Excercise: What is this ? Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Radar scanning geometry in 3D Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

acceptable for convection research) Kumpula August 2005 The task schedule consists of 5 subtasks, repeated every 10 minutes (10 minute interval longest acceptable for convection research) Task Main purpose Range/km Elevations /deg Mode Moments PRF/Hz Max wind PRO_A Good dBZ 150 0.8 1.7 2.7 FFT Z, T, V,W, SQI 1000 13.3 m/s PRO_B Dual pol low part 0.3 1.2 3.6 7.0 16 PPP ZDR, KDP, RhoHV, PhiDP PRO_C Dual pol upper air 120 2.2 4.6 11.0 22 45 90 As above 1200 16 m/s D_PRO Horizontal transmission, H+V receiving (for LDR) 2.2 4.6 45 (top to down) Z,T,V,W,SQI LDR, RhoH, PhiH E_PRE Dual PRF, 8-bit (for mesocyclone winds) 3.0 8.0 Z, T, V, W 1200/ 800 32 m/s Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

FMI tasks 1991-2006 Task Main purpose Range/km Elevations /deg Mode The task schedule consists of 3 subtasks, repeated every 5 minutes during campaigns Task Main purpose Range/km Elevations /deg Mode Moments PRF/Hz Max wind VOL_A Good dBZ 250 0.3 0.8 1.7 2.7 PPP Z, T, V 570 7m/s VOL_B Middle part 120 4 5.5 8 As above 850/567 Hz 22 m/s VOL_C Upper air 80 13 25 1200/800 32 m/s Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Hydrometeor classification is not possible with dBZ only DBZ rain hail snow sleet insects birds clutter -20 -10 0 10 20 30 40 50 60 Overlap of hail and heavy rain Overlap of snow and insects Help from dual pol parameters ZDR rain hail snow sleet insects birds clutter -5 … 0 1 3 5 RHO rain hail snow sleet insects birds clutter 0.2 0.4 0.8 0.9 0.95 0.99 1 Draft Draft Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Three ways to collect dual-pol data Alternating H and V ”Old-fashioned mode” Transmit H, receive H and V ”LDR mode” Z,V and LDR Linear Depolarization Ratio More sensitivity Transmit H and V, receive H and V ”Star mode” Z, V and ZDR, Rho, KdP, PhiDP ZDR - Differential Reflectivity Rho - Correlation Coefficient PhiDP - Differential Phase KDP - Specific Differential Phase Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

ZDR=10Log(Zh/Zv) V %Zv %Zh H courtesy of Timo Puhakka, HU ZDR < 0 Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

ZDR=10Log(Zh/Zv) generally, for hydrometeors ZDR -3..+3 dB (ratio 1:2) Increases with the sizes of liquid drops Small with dry snow Positive with horizontally oriented plate-crystals Negative with vertically oriented ”needles” Small or negative with hail Indicates presence of frozen precipitation Indicates super cooled water in updrafts Indicates the onset of melting With Zh can detect hail Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

ZDR in showers, sea clutter and birds Non-met Weather Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Correlation coefficient rhv Correlation coefficient = 1 for spheres and oriented spheroids courtesy of Timo Puhakka, HU Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Decrease of correlation Rho indicates Variety of hydrometeor types Mixture of liquid and frozen hydrometeors (”Snöblandat regn”) Hydrometeors with irregular shape Wide distribution of hydrometeor orientation Presence of large hail Correlation coefficient <0.95 for hail, hail/rain mixture and for wet aggregates courtesy of Timo Puhakka, HU Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

RHO sea clutter and birds: pink > 0.94 precipitation Inter-ference Birds Sea clutter Anaprop Showers Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

RHO in elevation 7 deg - melting layer 0.94-0.99 Ice and snow Melting snow Water Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Linear Depolarization Ratio LDR Shv=0 Shv=0 Shv > 0 courtesy of Timo Puhakka, HU Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Linear Depolarization Ratio LDR Dry snow LDR<-30 dB Rain LDR<-27 dB Dry aggregates, small hail,graupel LDR<-20 dB Wet aggregates, small hail,graupel -20<LDR<-10 dB Hail, rain/hail mixture LDR>-20 dB courtesy of Timo Puhakka, HU Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

High resolution RHI’s of melting layer dBZ, Rho, LDR Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

PhiDP The anisotropy of the medium leads to phase difference between horizontal and vertical waves (when horizontal waves go through more water) The detection of this phase difference is the basis for PhiDP. More often, range derivative of PhiDP known as KDP, is used. courtesy of Timo Puhakka, HU Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Kdp example Attenuation ! Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Attenuation visible in ZDR horizontal waves more attenuated Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Datasets are huge - Recommended procedure Select situation from Weather Diary Browse ready-made images Select and limit the dataset you want Read readme.files Get data Process Make conclusions For reporting, consider whether you want to use ready-made images or draw your own Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019

Lake effect snow last Tuesday evening Ilmatieteen laitos / PowerPoint ohjeistus 9.5.2019