Download
1 / 45
450 likes | 549 Vues
DFI Launching(DFL) Verification KMA domain 10km cycle. 2006. 8. 8 Ju-Won Kim KMA. DFI Launching (DFL). The DFI integration involves only forward integration and the forecast is started half way of the DFI integration.
E N D
DFI Launching(DFL) VerificationKMA domain 10km cycle 2006. 8. 8 Ju-Won Kim KMA
DFI Launching (DFL) • The DFI integration involves only forward integration and the forecast is started half way of the DFI integration. • The DFL design avoids the questionable backward integration step as applied in ADFI, DDFI options.
Design for experiment • cycle period : 12UTC MAY 4th ~ 12UTC May 11th 2006 • grid interval : 30km – 10km 1way nesting • number of grid : 17816031 (for 10km) • nfilt : Dolph-Chebyshev Window • tspan : 3hr (for DFL) • cutoff : 1hr (for DFL) • dt : 60secs • restart time : 100mits • microphysics : WSM6 • surface physics : LSM • pbl physics : YSU • cumulus physics : KF • km_opt : horizontal Smagorinsky first order closure
Observation Numbers : 12UTC 04 May ~ 12UTC 11 May 2006 Averages from 6hr to 24hr 6hrly
Precipitation Skill Scores : 7 days average on 73 observation points • Hit (H) : event forecast to occur, AND did occur • Miss (M) : event forecast NOT to occur, BUT did occur • False_alarm (F) : event forecast to occur, BUT did NOT occur • Correct_negative (C) : event forecast NOT to occur, AND did NOT occur • total = H + M + F + C • h_random = ( H + M ) ( H + F ) / total • Bias Score = ( H + F ) / ( H + M ) • Threat Score = H / ( H + M + F ) • Equitable Threat Score = ( H – h_random ) / ( H + M + F – h_random ) • Accuracy = ( H + C ) / total • Probability of detection = H / ( H + M ) • False alarm ration = F / ( H + F )
Precipitation Equitable Threat Score : ( H-h_random ) / ( H+M+F-h_random)
Precipitation Accuracy Score : ( H + C ) / ( H + M + F + C )
Precipitation Probability Of Detection Score : H / ( H + M )
