29/08/2015FINNISH METEOROLOGICAL INSTITUTE Carpe Diem WP7: FMI progress report Jarmo Koistinen, Heikki Pohjola Finnish Meteorological Institute

29/08/2015FINNISH METEOROLOGICAL INSTITUTE ·Area 1/WP3: Development of a variational assimilation scheme for doppler winds (FMI + SMHI, responsible persons at FMI Heikki Järvinen, Kirsti Salonen) ·Area 2/WP7: Advanced surface precipitation estimate from radars and a NWP model (HIRLAM) (Jarmo Koistinen, Heikki Pohjola) ·Objective: Improve the accuracy and quality of operational real time precipitation measurements

29/08/2015FINNISH METEOROLOGICAL INSTITUTE End Users ·1. Finnish Road Authority ·Applies observed and nowcast distributions of rain, sleet and snow (EUMETSAT Atmospheric Motion Vector software for dBZ- fields implemented for operational use at FMI) and ·Accumulated snow ·Average snow clearing and road salting costs ~ 100 million euros/winter => The end user is very motivated to require continuous improvements in the accuracy of radar products

29/08/2015FINNISH METEOROLOGICAL INSTITUTE ·2. Kemijoki hydroelectric power company ·Applies instantaneous precipitation images from radar to river control ·Applies accumulated rain to a flow model (~ km2, grid 1 · 1 km2 ) together with Finnish Environment Institute (involved in COST 717) ·Applies accumulated snow from radar to estimate spring flood due to melting snow ·Applies existing radar products and improved ones from CARPE DIEM ·3. FMI (we are working in the Operative Services) ·Continuous and urgent need to improve radar products.

29/08/2015FINNISH METEOROLOGICAL INSTITUTE WP 7.1: Attenuation correction based on 3D water phase diagnosis from NWP model quantities Deliverables: " Large attenuation statistics for rain-only (assumed in most existing radar systems) and variable water phase statistics " Improvement in surface precipitation " Limitation: Applies single polarization radar data => overestimation of attenuation possible in cases of hail

29/08/2015FINNISH METEOROLOGICAL INSTITUTE WP 7.2 Elimination of overhanging precipitation (OP) from surface estimates Altostratus: 13 % of all VPR in Finland in 2001

29/08/2015FINNISH METEOROLOGICAL INSTITUTE WP 7.3 Vertical reflectivity profile correction applying radars and NWP Deliverables: Automatic classification of VPR above each radar based on radar, soundings, NWP: " Precipitation " OP " Clutter " Clear air echo Bright Band: " Amplitude " Thickness " Height

29/08/2015FINNISH METEOROLOGICAL INSTITUTE The original WP order has been rearranged ·New order: 7.3 begins first and continues during the whole 36 months. WPs start later and feed 7.3. ·Reasons for change: 1. End users, including FMI, continuously demand a working VPR correction. 2. HIRLAM-data difficult to get at the moment as the group is very busy due to version change and platform change in autumn Practical result: We have developed a VPR correction for a network based on radar VPRs and radio soundings. It will be semi-operational in July 2002.

29/08/2015FINNISH METEOROLOGICAL INSTITUTE VPR correction at FMI 1(2) 3D polar volume measured VPR 7 radars every 15 minutes layer thickness 200 m range km max bin count 5000 / layer IRIS

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2)

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2)

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) Classification and QC of each VPR representativity rain bright band snow clutter clear air echo overhanging precipitation unphysical gradient Statistics Reference dBZ at ground level Calculation of the correction Freezing level (FL) from radio soundings (later: from HIRLAM too) Climatological profile adjusted to freezing level

29/08/2015FINNISH METEOROLOGICAL INSTITUTE Profile diagnostics tree 1(2)

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) Profile diagnostics tree

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2)

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2)

29/08/2015FINNISH METEOROLOGICAL INSTITUTE OP and evaporation cases 1(2)

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) Clear air echo and clutterRain and bright band

29/08/2015FINNISH METEOROLOGICAL INSTITUTE Snow 1(2) Bright band at ground

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) Climatological profile

29/08/2015FINNISH METEOROLOGICAL INSTITUTE VPR CORRECTION IN A NETWORK, PRINCIPLES 1.dBZ at 500 m PsCAPPI surface is corrected to ground level. 2.Applies measured VPRs and climatological VPRs and time-space interpolated freezing level heights from 3 radio sounding stations. 3.The magnitude of the correction is: 10*log (the ground level reference Z from the profile/ convolution (Z-profile*beam)) at each range (height). Upper threshold for the correction is 30 dB.

29/08/2015FINNISH METEOROLOGICAL INSTITUTE VPR CORRECTION IN A NETWORK, MAIN STEPS 1.Calculation of the single radar correction factor at each range based on the measured and classified VPR from each polar volume. 2.Calculation of the single radar correction factor at each range based on the climatological, temperature- adjusted VPR for each polar volume. 3.Weighted average of factors 1 and 2 is derived based on the quality of factor 1. 4.Space smoothing is applied: Actual correction at each composite pixel is a distance-weighted average of factor 3, from all radars closer than 300 km from the pixel. 5.Time smoothing is applied: Factor 4 is linearly averaged during the past 6 hours. 6.Post-correction tresholding is applied: The corrected dBZ may not exceed preselected values.

29/08/2015FINNISH METEOROLOGICAL INSTITUTE Snow 1(2) Profile correction for 500 m PsCAPPI

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) Snow and clutterProfile correction

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) RainProfile correction

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) RainProfile correction

29/08/2015FINNISH METEOROLOGICAL INSTITUTE STEP 1: SINGLE RADAR CORRECTION FACTOR ·The reference dBZ at ground level must be carefully selected to avoid spurious corrections: ·The reference dBZ at ground level (green dot in the previous example cases) is usually the measured dBZ at the lowest level (100 m) of the profile. ·Reference dBZ at ground is extrapolated from upper levels in two automatically classified cases: ·- bright band is diagnosed at ground level ·- clutter is diagnosed at ground level ·In the following images examples are shown.

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) RainProfile correction

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) RainProfile correction (no cutter)

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) Bright band at groundProfile correction

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) Profile correction (no extrapol.) Bright band at ground

29/08/2015FINNISH METEOROLOGICAL INSTITUTE STEPS 2-3: MIXING OF MEASURED AND CLIMATOLOGICAL VPR ·Each instantaneous, single radar VPR correction factor is a weighted mean of two factors, based on two simultaneous profiles: ·- The climatological VPR, adjusted to the actual freezing level, obtained from the time-space interpolated temperature soundings, weight=0.2. ·- The measured VPR, weight = 0-1 according to the quality of the profile (quality ~ height scaled precipitation volume).

29/08/2015FINNISH METEOROLOGICAL INSTITUTE 1(2) Climatological profileProfile correction

29/08/2015FINNISH METEOROLOGICAL INSTITUTE STEP 4: SPATIAL AVERAGING OF THE CORRECTION FACTOR ·Instantaneous correction factor at each composite pixel applies profiles from several surrounding radars: ·A composite pixel in a network is selected from the radar, whose measurement is closest to the ground (height h). ·Each instantaneous VPR correction factor at a composite pixel is a weighted mean of the simultaneous factors at each radar, within the range 300 km from the pixel; weight ~ distance to each radar squared/300**2. ·The factor from each radar is taken from the same height h. In this way we “borrow” the neighbouring profiles to the radar from which the actual pixel value is taken. ·Important effect: The correction does not introduce reflectivity steps along the seams of composites.

29/08/2015FINNISH METEOROLOGICAL INSTITUTE STEP 5: TIME AVERAGING ·So far we have only derived correction factors for each composite pixel at each time moment (time series). Small scale VPR variability is eliminated applying time-averaging: ·Each instantaneous VPR correction factor at a composite pixel is a linearly weighted average of the 24 instantaneous corrections during the last 6 hours; the older the correction the less is the weight. ·The correction factors derived in step 5 are the ones we actually apply for the 500 m PseudoCAPPI composite. The factors in steps 1-4 are only used for derivation of the final correction factor.

29/08/2015FINNISH METEOROLOGICAL INSTITUTE STEP 6: TRESHOLDING OF TOO LARGE CORRECTIONS ·In case that the resulting corrected dBZ is too large, e.g. embedded convection occurs at longer distances whereas the measured VPR represents shallow precipitation close to the radar, the final dBZ is not allowed to exceed preselected values. Treshold value at each pixel depends on the actual hydrometeor water phase analysis (rain, sleet, snow) at ground level. The phase analysis is based on linearly extrapolated 3-hourly analysis of T and RH at the height of 2 m.

29/08/2015FINNISH METEOROLOGICAL INSTITUTE FUTURE OF WP 7 ·WP 7.3 will continue 36 months (inclusion of HIRLAM) and apply all useful results from WPs 7.1 and 7.2 ·Deliverables from WP 7.3 at +13 months: ·- Statistics of VPRs and single radar VPR corrections in Finland, a large climatological data set (1 year, 7 radars, every 15 minutes). ·- VPR correction in a network, the method (tuning of the parameters still required) ·- validation of the method (applies radar pairs and gauges) ·- end user experience ·- 2 ERAD papers, textbook in radar meteorology, (peer reviewed paper around +18 months)

29/08/2015FINNISH METEOROLOGICAL INSTITUTE Original deliverables: " VPR correction at a single radar applying time-averaged (~6h) VPR corrections (TA) based on reflectivity profiles derived from the measured polar volumes every 15 minutes " VPR correction at a single radar applying TA-corrections and climatological VPR based on the actual freezing level height obtained from meteorological soundings and climatological profile shape statistics measured with the radars (TAC) " VPR correction in the radar network based on space-averaged TAC-corrections (TSAC) " VPR correction in the network based on TSAC-correction and VPRs estimated from a NWP model in co-operation with SMHI (Gunther Haase).

29/08/2015FINNISH METEOROLOGICAL INSTITUTE Validation of the deliverables from WP " Improvement in gauge-radar comparisons of 12 h accumulations " Improvement of long range dBZ from radar A, compared to the short range dBZ from radar B in the same overlapping region " Improved long range POD and FAR of precipitation at ground from radar compared to AWS/SYNOP (ON/OFF) " Improved POD and FAR in the precipitation nowcasts " Improved skill in the End User applications