Beranova, Kysely: Links between the NAO Index and temperatures in Europe in climate models

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Beranova, Kysely: Links between the NAO Index and temperatures in Europe in climate models

  1. 1. Links between the NAO Index andtemperatures in Europe in climate models Romana Beranová, Jan Kyselý Technical University of Liberec Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic
  2. 2. Introduction Motivation: Is NAO index a useful covariate for a nonstationary statistical model?Outline: Data The North Atlantic Oscillation index (NAOI) Relationship between NAOI and seasonal temperature and temperature extreme indices Conclusions
  3. 3. Observed / Model data• NCEP/NCAR reanalysis, which represents the observed data• Ensemble of 10 Global Climate Models (GCM) with 14 runs• Simulations for 1961-2000, performed with forcing agents as specified by the IPCC protocol for the 20C3M experiment• 2071-2100 - sresA1B scenario centre/model resolution [°] runs source MPI / ECHAM5-MPI 1.875 x 1.875 3 http://www.mad.zmaw.de DMI / ECHAM5-MPI 1.875 x 1.875 1 http://www.mad.zmaw.de GFDL / CM2.1 2.5 x 2.0 1 http://nomads.gfdl.noaa.gov CCCMA / CGCM3 (T63) 2.8 x 2.8 1 https://esg.llnl.gov:8443 BCCR / BCM2.0 2.8 x 2.8 1 http://www.mad.zmaw.de CNRM / CM3 2.8 x 2.8 1 https://esg.llnl.gov:8443 IPSL / CM4 V1 2.5 x 3.75 1 https://esg.llnl.gov:8443 UKMO / HadCM3 2.75 x 3.75 1 http://cera-www.dkrz.de UKMO / HadGEM2AO 1.25 x 1.875 1 http://cera-www.dkrz.de FUB / EGMAM 3.75 x 3.75 3 http://cera-www.dkrz.de
  4. 4. Data• Temperature data: daily temperature maxima (Tx) and minima (Tn)• Temperature extreme indices: • cold extremes – Q10 and Q1 of Tn • warm extremes – Q90 and Q99 of Tx• Data cover European Area (15°W-40°E, 30-70°N)• Winters (December- January- February) for recent climate 1961-2000 and future time slice 2071-2100• Pressure data: daily mean sea level pressure (SLP)
  5. 5. The North Atlantic OscillationThe NAO is the dominant mode of winter climate variability in the North Atlantic region. The NAO is a large scale seesaw in atmospheric mass between the subtropical high and the polar lowPositive NAO Index:• A stronger than usual subtropical high pressure centre and a deeper than normal Icelandic low• The increased pressure difference results in more and stronger winter storms crossing the Atlantic Ocean on a more northerly track• This results in relatively warm and wet winters in northern and western EuropeNegative NAO Index:• A weak subtropical high and a weak Icelandic low• The reduced pressure gradient results in fewer and weaker winter storms• They bring moist air into the Mediterranean and cold air to northern Europe
  6. 6. The North Atlantic Oscillation in GCMsObserved NAO as the 1st leading empirical orthogonal function for the winter SLP field
  7. 7. Definition of NAO index• Daily NAO Index is based on the difference of thenormalised SLP between Ponta Delgada (37.7°N a 25.7°W,Azores) and Stykkisholmur (65.1°N, 22.7°W, Iceland) • Daily mean SLP values for the two stations were interpolated from the four nearest grid points for every GCM
  8. 8. Definition of NAO index• NAO index was classified as negative (-) when below the 25% quantile and positive (+) when above the 75% quantile of its distribution over 1961-2000
  9. 9. MethodsWe focus on identification of areas in which the NAO index islinked to temperature extremes (on the daily time scale)• We identified days with positive NAOI (NAO+ days) and negative NAOI (NAO- days)• We calculated mean, Q90, Q99 of Tx for NAO+ and NAO- days; and mean, Q10, Q1 of Tn for NAO+ days and NAO- days• We displayed differences in these variables between the NAO+ and NAO- days
  10. 10. Results – mean temperature Mean of TnObserved Fig.: Differences between mean of Tn for days with NAO+ index and NAO- index
  11. 11. Results – mean temperature Mean of TxObserved Fig.: Differences between mean of Tx for days with NAO+ index and NAO- index
  12. 12. Results – mean temperature• NAO index influences Tx and Tn in large parts Europe• Positive difference in the area of 45°N-75°N• Negative difference in north Africa, in south of the Iberian peninsula and in Turkey• The majority of the GCM simulations depict almost the same pattern as reanalysis• In nearly all GCMs the area of positive differences is reduced• Some GCMs (CM21, BCM2, CM3, CM4 and EGMAM) show an extended area with negative differences• Intra-model variability for EGMAM runs is larger than for ECHAM runs
  13. 13. Results – cold extremes Q10 of TnObserved Fig.: Differences between Q10 of Tn for days with NAO+ index and NAO- index
  14. 14. Results – cold extremes Q1 of TnObserved Fig.: Differences between Q1 of Tn for days with NAO+ index and NAO- index
  15. 15. Results – cold extremesQ10:• For all GCMs the area with positive differences is extended to the south and the differences of Q10 between NAO+ and NAO- days are larger in comparison with mean Tn• In some models and some areas (e.g. HadGEM2AO in Denmark) the difference for Q10 is >8°C• The inter-model variability is larger for Q1 than Q10• The ability of models to simulate relationships between NAOI and temperature extremes is worse for Q1 than Q10• Some grids with negative differences (ECHAM5 run1, BCM2, HadCM2) appear inside the north area with positive differences of Q1
  16. 16. Results – warm extremes Q90 of TxObserved Fig.: Differences between Q90 of Tx for days with NAO+ index and NAO- index
  17. 17. Results – warm extremes Q99 of TxObserved Fig.: Differences between Q99 of Tx for days with NAO+ index and NAO- index
  18. 18. Results – warm extremes• NAO affects smaller area of Europe for warm extremes than for cold extremes, and this is reproduced by most GCMs• For all GCMs the area with positive differences is smaller and the area with negative differences tends to be larger than for mean Tx• Spatial patterns of projected differences in Q90 are much more coherent compared to those of Q99
  19. 19. Results – future climate (2071-2100)Mean of Tn• Majority of GCMs presents similar relationships as for recent climate (exception – model CM3)
  20. 20. Results – future climate (2071-2100)Q1 of Tn• For majority of GCMs the area with positive differences is extended in comparison with recent climate
  21. 21. Results – future climateQ99 of Tx• Similar results as for recent climate• Some models simulate larger area with negative differences (CM2.1 and BCM2)
  22. 22. Conclusions1. The NAO index represents a useful covariate that explains an important fraction of variability of temperature extremes in winter in large parts of Europe. It is more important for cold than warm temperature extremes2. Differences between NAO+ and NAO- days in Q1 exceed 5°C in large parts of northern, western and central Europe3. The GCMs reproduce the observed spatial patterns reasonably well, although better for means than extremes4. The inter-model and intra-model variability is larger towards tails of temperature distributions5. Although the NAO index based on two fixed points is not able to detect spatial structure of NAO, we show that the index can be used in extreme value models as variable which affects temperature extremes
  23. 23. Future workCentral European Zonal Index (CEZI) as a covariate for summertemperature extremesCEZI is defined as the difference Fig.: Differences betweenof the normalised SLP between Q90 of Tx for days withNorthern Europe (60-65°N a CEZI+ and CEZI-,0-20°E) and Southern Europe(35-40°N, 0-20°E) 1961-1990, JJA

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