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An Evaluation of Aspects of Tropical Precipitation Forecasts

An Evaluation of Aspects of Tropical Precipitation Forecasts from the ECMWF & NCEP Model Using CMORPH. John Janowiak 1 , M.R.P. Sapiano 1 , P. A. Arkin 1 , F.J. Turk 2 1 Cooperative Institute for Climate and Satellites (CICS) Earth Systems Science Interdisciplinary Center (ESSIC)

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An Evaluation of Aspects of Tropical Precipitation Forecasts

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  1. An Evaluation of Aspects of TropicalPrecipitation Forecasts from the ECMWF & NCEP ModelUsingCMORPH John Janowiak1, M.R.P. Sapiano1, P. A. Arkin1, F.J. Turk2 1Cooperative Institute for Climate and Satellites (CICS) Earth Systems Science Interdisciplinary Center (ESSIC) University of Maryland, College Park, Maryland, USA 2Jet Propulsion Laboratory Pasadena, California, USA

  2. Outline • What is CMORPH? • The Diurnal Cycle in GFS Precipitation • MJO-related convective precipitation from: - CMORPH (observations) - ECMWF forecasts (5-, 10-day) - GFS forecasts (5-, 10-, 15-day) • Conclusions

  3. CMORPH* NOAA/CPC “Morphing” technique Provides quantitativeestimates of precipitation for 0.07o x 0.07o lat/lon / ½ hr ( ~ 8 km @ equator) Uses geostationary IR to propagate & ‘morph’ (interpolate/smooth in time and space) precipitation estimated from passive microwave observations Dec 2002 – present; extending back to ~1998 Hourly Precipitation Loops: 15Z 8Jun2008 – 06Z9Jun2008 RADAR CMORPH 0.25o lat/lon 0.07o lat/lon * See Joyce et al. (J. Hydromet 2004)

  4. CMORPH mm/hr CMORPH looks quite realistic over water, maybe less so over land Probably related to fact that microwave estimates are better over water than land

  5. Outline • What is CMORPH? • The Diurnal Cycle in GFS Precipitation • MJO-related convective precipitation from: - CMORPH (observations) - ECMWF forecasts (5-, 10-day) - GFS forecasts (5-, 10-, 15-day) • Conclusions

  6. 1 day fcst GFS CMORPH 09 12 15 18 21 00 03 06 LST

  7. 1 day fcst GFS CMORPH 09 12 15 18 21 00 03 06 LST

  8. 1 day fcst GFS CMORPH 09 12 15 18 21 00 03 06 LST

  9. 1 day fcst CMORPH GFS 09 12 15 18 21 00 03 06 LST

  10. 1 day fcst CMORPH GFS 07 10 13 16 19 22 01 04 LST

  11. CMORPH 12 15 18 21 00 03 06 09 LST

  12. Outline • What is CMORPH? • The Diurnal Cycle in GFS Precipitation • MJO-related convective precipitation from: - CMORPH (observations) - ECMWF forecasts (5-, 10-day) - GFS forecasts (5-, 10-day) • Conclusions

  13. 15N-15S Case Study: Moderate-Strong MJO Nov 2007 – Feb 2008 CMORPH Precipitation from Indian Ocean across the Pacific to Greenwich Seasonal mean removed MJO signatures clearly evident Diagonal lines subjectively drawn to identify axis of MJO (and intervening dry periods) eastward progression

  14. 15N-15S Case Study: Mod-Stg MJO Nov 2007 – Feb 2008 CMORPH These lines identify westward moving elements within MJO envelope

  15. Line are same as previous slides; on model plots, lines represent observed features

  16. ~10days

  17. Difference from Nov 2007 – Feb 2008 Period Mean Dec 4-15, 2007 Dec 16 – Jan 3 Jan 5-20, 2008

  18. Difference from Nov 2007 – Feb 2008 Period Mean Dec 4-15, 2007 Dec 16 – Jan 3 Jan 5-20, 2008

  19. CMORPH GFS 10 dy ECMWF 10 dy Difference from Nov 2007 – Feb 2008 Period Mean Dec 4-15 A (5 dy smoothed) B C

  20. A CMORPH GFS 10 dy ECMWF 10 dy B C Difference from Nov 2007 – Feb 2008 Period Mean (5 dy smoothed) Dec 16-Jan 3

  21. A CMORPH GFS 10 dy ECMWF 10 dy B C Difference from Nov 2007 – Feb 2008 Period Mean (5 dy smoothed) Jan 5-20

  22. 1 0 0 2 3 4 5 6 10 14 7 13 8 9 11 12 15 These show pattern correlations over the region between forecasts and observations for different lags (the different colored lines) and for different forecast lead time (the horizontal axis) The green line labeled “1” represents the correlation between forecasts initialized one day later than the observations they are compared to “Interesting if true” – we are working to figure out what this might mean

  23. Conclusions • GFS precipitation forecasts over the tropical oceans do exhibit a diurnal cycle • But the peak occurs earlier than observations • And the amplitude decreases with forecast lead, at least in the central Pacific • Both GFS and ECMWF exhibit a reasonably realistic MJO precipitation pattern and variability • At longer leads, both models lose details and seem to lag behind the observations • Possible that the initialization is imperfect and some spin-up is required to attain a more realistic precipitation field? • Results, particularly for ECMWF, indicate that useful skill in predicting MJO-related precipitation is close to being attained

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