1 / 25

T eleconnections in MINERVA experiments

T eleconnections in MINERVA experiments. Franco Molteni , Frederic Vitart , Linus Magnusson European Centre for Medium-Range Weather Forecasts. Outline. Predictive skill for NAO and PNA for seasonal (DJF) and month-2 (Dec) means

norris
Download Presentation

T eleconnections in MINERVA experiments

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Teleconnections in MINERVA experiments Franco Molteni, Frederic Vitart, Linus Magnusson European Centre for Medium-Range Weather Forecasts

  2. Outline • Predictive skill for NAO and PNA for seasonal (DJF) and month-2 (Dec) means • Predictive skill for Indo-Pacific rainfall and teleconnections with NH 500 hPa height • Blocking frequency (TM index) and SSW – NAO correlation (from L. Magnusson)

  3. PNA and NAO: EOF vs. covariance with 2-box index PNA EOF-1 160E-80W, 25-85N [120-90W, 50-65N] - [180-150W, 40-55N] NAO EOF-1 80W-40E, 25-85N [25W-5E, 30-45N] - [40-10W, 55-70N]

  4. PNA, DJF (m2-4) ac = 0.68 ac = 0.66

  5. NAO, DJF (m2-4) ac = 0.26 ac = 0.51

  6. NAO, Dec (m2) ac = 0.37 ac = 0.50

  7. Ensemble-mean NAO fc. for DJF

  8. Local correlation SST – precip, DJF 1981-2008

  9. Precip. teleconnections in DJF: GPCP 2.2

  10. Precip. teleconnections in DJF: System 4 (from Nov.)

  11. Z 500_hPavs.precip: ERA-Int. and System-4 ERA Sys4

  12. W. Indian Oc. teleconnections, ENSO removed Full precip anomaly Anomaly orthogonal to Nino3.4 SST

  13. Predictive skill for W.Ind and E.Ind-W.Pac SST/precip SST prec

  14. Western & Central Indian Ocean (wcio), DJF T319 T639

  15. Western & Central Indian Ocean (wcio), DJ T319 T639

  16. Eastern Indian – West Pacific (eiwp), DJF

  17. Eastern Indian – West Pacific (eiwp), DJ

  18. Nino-4, 10N-10S (nino4w), DJF T319 T639

  19. Correlations of Indo-Pac. rainfall and NAO (DJF)

  20. composites for below-average rainfall in WCIO DJF T319 T639 DJ T319 T639

  21. Blocking frequency (1 day or longer) DJF MAM SON JJA

  22. Blocking frequency (5 day or longer) MAM DJF JJA SON

  23. Sudden stratospheric warmings -> NAO DJF JJA

  24. Summary • On seasonal timescale, T639 has the same predictive skill as T319 for PNA, but a (notably) higher skill for NAO; the NAO skill improvement is also seen in month-2 means. • For Indo-Pacific rainfall, the MINERVA runs (as Sys-4) simulate stronger links between rainfall in Western/central Indian Ocean and over Maritime Continents and central Pacific than those found in GPCP data. As a result, extratropical teleconnections from these three tropical regions look more similar than in observation, and the NAO – Indian Ocean rainfall connection is underestimated. This problem is marginally alleviated in T639 wrt T319. • T639 shows a stronger signal than T319 in the North Atlantic associated with below-average rainfall in the W/C Indian Ocean, and a higher frequency of “Greenland blocking”. • At both resolutions, the lagged correlation between sudden stratospheric warmings and NAO is poorly represented. • So, why are the T639 NAO forecasts better?

  25. ECMWF seasonal fc. System 4: main features • IFS model cycle: 36r4 (op. Nov. 2010-May 2011), T255-L91 • Ocean model : NEMO (v. 3.0 + 3.1 coupling interface) • ORCA-1 configuration (~1-deg. resol., ~0.3 lat. near the equator) • 42 vertical levels, 20 levels with z < 300 m • Variational ocean data assimilation (NEMOVAR) • FGAT 3D-var, re-analysis (ORA-S4) and near-real-time system • Collaboration with CERFACS, UK Met Office, INRIA • Operational forecasts • 51-member ensemble from 1st day of the month, released on the 8th • 7-month integration • 13-month extension (with 15 ens. members) from 1st Feb/May/Aug/Nov • Re-forecast set • 30 years, start dates from 1 Jan 1981 to 1 Dec 2010 • 15-member ensembles, 7-month integrations • 13-month extension from 1st Feb/May/Aug/Nov

More Related