The Swedish Weather Radar Production Chain Daniel Michelson Swedish Meteorological and Hydrological Institute Focus on: Higher-order products Quality improvements Quality characterization

SWERAD Operated jointly between SMHI and Swedish Armed Forces 12 Ericsson C-band Doppler radars Almost complete national coverage Vilebo, formerly Norrköping

NORDRAD Finland, Sweden, Norway Estonia associate member Special arrangement with Denmark Established in late 1980's Organized as an operational NORDMET activity R&D internationally organized as NORDMET Radar Applications (NORA) activity Constitutes the backbone of Swedish production http://nordrad.net/

BALTRAD NORDRAD+ All of POLRAD Peripheral German radars Netherlands (wind profiles) Baltic Sea Experiment BALTEX Radar Data Centre at SMHI R&D only Test environment for operational implementations

QC using operational satellite products* Meteosat 8 (MSG) Cloud type product from NWC SAF: 4 km, 15 min 4 cloud-free classes No surrogate for good Doppler, but better than nothing Operational since March 1 Improvements possible using quality flags in satellite product? *Spin-off from: Michelson D.B. and Sunhede D., 2004: Spurious weather radar echo identification and removal using multisource temperature information. Meteorol. Appl. 11, 1-14 last Tuesday, 18 UTC

QC using operational satellite products* Meteosat 8 (MSG) Cloud type product from NWC SAF: 4 km, 15 min 4 cloud-free classes No surrogate for good Doppler, but better than nothing Operational since March 1 Improvements possible using quality flags in satellite product? *Spin-off from: Michelson D.B. and Sunhede D., 2004: Spurious weather radar echo identification and removal using multisource temperature information. Meteorol. Appl. 11, 1-14

Accumulated precipitation Generated using filtered composites Simplified version of the BALTRAD gauge- adjustment technique* 1 hour, 2 km, 32 bits Uses 12-hour SYNOP gauge accumulations at 6 and 18 UTC thesholded at 0.1 mm *Koistinen J. and Michelson D.B., 2002: BALTEX weather radar-based precipitation products and their accuracies. Boreal Env. Res. 7(3), 253-263

Operational gauge- radar relations Derived every 12 hours, using systematically corrected SYNOP gauge observations* F = 10 x log(G/R) 2nd-order polynomial fit against surface distance, with some QC Coefficients are archived and can be used with reflectivities, rainrates, and accumulations *Michelson D.B., 2004: Systematic correction of precipitation gauge observations using analyzed meteorological variables. J. Hydrol. 290, 161-177 The arrival of spring!

Swedish-Norwegian mountains 30 July 2006 Östersund Trondheim Photo: Banverket 1-hr accumulation ending 15:00 UTC

OPERA Quality Framework Quality indicator image stored in HDF5 product file along with coefficients, allows fully reversible adjustment procedure for quality characterization.