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Teleconnections and interannual variability of the atmosphere

Teleconnections and interannual variability of the atmosphere. Franco Molteni European Centre for Medium-Range Weather Forecasts. Outline. Teleconnection patterns: Definition from observational datasets Dynamical origin and interpretation

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Teleconnections and interannual variability of the atmosphere

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  1. Teleconnections and interannual variability of the atmosphere Franco Molteni European Centre for Medium-Range Weather Forecasts

  2. Outline • Teleconnection patterns: • Definition from observational datasets • Dynamical origin and interpretation • Explaining interannual variability through teleconnections: • Partition of variance: • interannual vs. intraseasonal variability • Internal atmospheric dynamics vs. boundary forcing/coupling • Are teleconnection patterns generated by internal variability and boundary forcing/coupling the same? • Predictability of teleconnection/low fr. variability indices • Can we predict tropical rainfall? • Linear indices: examples from the ECMWF System-3 hindcasts

  3. Teleconnections: definitions and examples Teleconnection: Relationship between anomalies of opposite sign (and/or different variables) in different regions of the world Teleconnection pattern: Regional or planetary scale pattern of correlated anomalies Teleconnections may be induced either by internal atmospheric dynamics or by coupling with other components of the climate system (mainly the tropical oceans)

  4. Teleconnections: definitions and examples The Southern Oscillation (and its links to El Niño) Walker and Bliss (1932); Bjerknes (1969) SOI: Tahiti – Darwin SLP Nino3.4 SST

  5. ENSO teleconnections: rainfall and temperature

  6. Teleconnections: definitions and examples The North Atlantic Oscillation Walker and Bliss (1932) Van Loon and Rogers (1978) Positive NAO phase Negative NAO phase

  7. Teleconnections: definitions and examples The Indian Ocean Zonal Mode(or I.O. Dipole) Saji et al. (1999), Saji and Yamagata (2003) Webster et al. (1999)

  8. Seminal papers: Wallace and Gutzler 1981 The Pacific / North American (PNA) pattern: correlations

  9. Seminal papers: Wallace and Gutzler 1981 The Pacific / North American (PNA) pattern: composites

  10. Seminal papers: Wallace and Gutzler 1981 Eastern Atlantic (EA) pattern: composites

  11. Seminal papers:Horel and Wallace 1981 Correlation of 700hPa height with a) PC1 of Eq. Pacific SST c) SOI index Schematic diagram of tropical-extratropical teleconnections during El Niño

  12. Seminal papers: Gill 1980 Atmospheric response to near-equatorial heating a) Near-surface wind and vertical motion b) Near-surface wind and sea-level pressure c) Motion in x-z plane along the Equator

  13. Seminal papers:Hoskins and Karoly 1981 Response to a tropical heat source (15N): • height (lon, z) at 18N • 300hPa vorticity • 300hPa height

  14. Seminal papers:Simmons Wallace Branstator 1983 First barotropic normal mode at four times during a half-cycle: East. Atlantic phase PNA phase

  15. Seminal papers: Sardeshmukh and Hoskins 1988 Definition of Rossby wave source generated by near-equatorial heating

  16. Seminal papers: Sardeshmukh and Hoskins 1988 Response to heating in trop. West Pacific Rossby wave source and abs. vorticity

  17. Non-linear models:Charney and DeVore 1979 Multiple steady states of very-low-order barotropic model with wave-shaped bottom topography

  18. Partition of variability in an ensemble of time-evolving atmospheric fields A (t, m) = A (t’, k, m) S (t, m) ≈ S0 (t’, k) k = 1, N (no. of years) m = 1, M (no. of ens. members) t’ = time within year Climatology: Acl(t’) = {A (t’, k, m)}k, m Anomaly: A’ (t’, k, m) = A (t’, k, m) - Acl(t’) Seasonal mean anomaly: As(k, m) = {A’ (t’, k, m) }t’ Ens./seas. mean anomaly: Aes(k) = {A’ (t’, k, m) }t’, m Note : for an observation/analysis dataset, m =1 !

  19. Partition of variability in an ensemble of time-evolving atmospheric fields Anomaly: A’ (t’, k, m) = A (t’, k, m) - Acl(t’) Seasonal mean anomaly: A’s(k, m) = {A’ (t’, k, m) }t’ Ens./seas. mean anomaly: A’es(k) = {A’ (t’, k, m) }t’, m Total variability: var [A’ (t’, k, m)] Interannual variability: var [A’s(k, m)] Intraseasonal variability: var [A’ (t’, k, m) – A’s(k, m)] Forced/coupled variability: ≈ var [A’es(k) ] Internal variability: ≈var [A’ (t’, k, m) – A’es(k) ]

  20. ECMWF Seasonal forecast system (Sys-3) IFS 31R1 1.1 deg. 62 levels HOPE 1.4 deg. lon 1.4/0.3 d. lat. OASIS-2 TESSEL Ens. Forecasts Initial Con. 4-D variational d.a. Gen. of Perturb. System-3 CGCM Multivar. O.I.

  21. Variability of Z 200hPa in DJF from S3 hindcasts System-3 11-member ensembles, init. on 1 nov. 1981/2005

  22. ‘Forced’ vs. internal variability in S3 hindcasts System-3 11-member ensembles, init. on 1 nov. 1981/2005 Z 200 hPa El Niño composite La Niña composite 5-day-mean EOF 1 EOF 2

  23. Variability of rainfall from S3 hindcasts S-3 11-member ensembles, init. on 1 may/nov. 1981/2005

  24. Can we predict tropical rainfall teleconnections?

  25. Why is it difficult (outside the E trop. Pacific) ? Tropicalconvection tends to occur over warm SST and warm-and-wet land surface, but it induces a number of feedbacks: • Convective clouds decrease solar radiation at the surface • Anomalous divergent winds tend to reduce evaporation to the east/west of the convective region when the climatological near-surface winds are westerly/easterly • The strength of the feedback depends on the heat capacity of the “interactive” surface layer and the phase of the day

  26. Predictability of teleconnection/EOF indices in S-3 Rainfall: East. Tropical Indian Ocean pattern (JJA)

  27. Predictability of teleconnection/EOF indices in S-3 Rainfall: South Asian monsoon pattern (JAS)

  28. Predictability of teleconnection/EOF indices in S-3 Rainfall: Sahel / Guinea coast dipole (JJA)

  29. Predictability of East Africa short rains: EOF filtered OND Unfiltered CC = 0.04 EOF proj. CC = 0.39

  30. Predictability of teleconnection/EOF indices in S-3 Z 500 hPa: Pacific / North American pattern (DJF)

  31. Predictability of teleconnection/EOF indices in S-3 Z 500 hPa: North Pacific dipole (DJF)

  32. Predictability of teleconnection/EOF indices in S-3 Z 500 hPa: North Atlantic Oscillation (DJF)

  33. Conclusions • Teleconnections may be induced either by internal atmospheric dynamics or by coupling with other components of the climate system (mainly the tropical oceans). • Although a linear interpretation of teleconnection is adequate in most cases, non linear effects should not be neglected. • Teleconnections related to ENSO are well modelled in the tropical and extra-trop. Pacific region, fairly well over South America, less so over South Asia and Africa. • Prediction of tropical rainfall telecon. requires accurate modelling of heat-flux feedbacks from the ocean mixed layer and land surface. • Predictability over Europe/Atlantic: mostly limited during winter, higher in other seasons when internal variability is reduced.

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