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Atmospheric Teleconnections and Climate Change

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Presentation on theme: "Atmospheric Teleconnections and Climate Change"— Presentation transcript:

1 Atmospheric Teleconnections and Climate Change
Mike Blackburn National Centre for Atmospheric Science, University of Reading Talk for Lighthill Research Network 2 May 2008 © University of Reading 2008

2 Teleconnections - Outline
Well known examples: El Niño, North Atlantic Oscillation Processes – atmospheric response to heating – wave propagation Spatial correlations: linked regions of variability; patterns of variability Downstream developments on jet Tropical convection – MJO Climate change: potential methodology; ENSO, NAO examples

3 El Niño and La Niña (global teleconnections)
NOAA, Climate Prediction Center

4 El Niño impacts (northern winter)
La Niña impacts (northern winter) NOAA, Climate Prediction Center

5 El Niño / La Niña Changes in the location of tropical clouds over the Pacific Atmospheric response during El Niño (schematic) Pressure and flow in the upper troposphere La Niña - opposite sign to a first approximation, but weaker over N. America David Neelin, UCLA

6 Propagation of Rossby waves
from a region of tropical convection (schematic) Horel and Wallace (1981) Trenberth et al. (1998)

7  Propagation of Rossby waves
Model response to steady heating DJF Meridional wind ~250hPa After 10 days Climatological winds (DJF) 32ºN Stationary phase (trough/ridge) fast eastward group propagation Ambrizzi and Hoskins (1997)

8   Propagation of Rossby waves
Model response to steady heating DJF Meridional wind ~250hPa After 9 days After 15 days Model gives good agreement with theory Great circle paths + refraction by the climatological winds Jet streams are preferential paths for propagation (waveguides) Ambrizzi and Hoskins (1997)

9 Taxonomy of Teleconnections
50 years of daily global atmospheric analyses One-point correlation maps → “centres of action”, associated patterns of variability Originally by Wallace & Gutzler (1981): correlations of monthly mean 500hPa height PNA Pacific North-American pattern NAO North Atlantic Oscillation * * The PNA (left) and NAO (right) teleconnection patterns, shown as one-point correlation maps of 500 hPa geopotential heights for boreal winter (DJF) over 1958 to In the left panel, the reference point is 45°N, 165°W, corresponding to the primary centre of action of the PNA pattern, given by the + sign. In the right panel, the NAO pattern is illustrated based on a reference point of 65°N, 30°W. Negative correlation coefficients are dashed, and the contour increment is 0.2. Adapted from Hurrell et al. (2003). IPCC: from Hurrell et al (2003)

10 The North Atlantic Oscillation
(an example of regional teleconnections) NAO+ NAO- From by Martin Visbeck

11 The North Atlantic Oscillation
Sea level pressure pattern Dec-March The North Atlantic Oscillation Now associated with breaking Rossby waves Winter NAO index based on Portugal – Iceland pressure difference Hurrell (1995), Science

12 Summer 2007 UK floods - jet stream
- strength of wind at 250hPa - Average from 12 June to 25 July Climatology 2007 (ms-1) Persistent pattern of waves on the jet stream – trough (low pressure) over UK Jet “joins up” over Europe – possible continuous waveguide & stationary free wave

13 (potential temperature on the tropopause)
Summer 2007 UK floods (potential temperature on the tropopause) 15 June 25 June 20 July Air moving equatorwards from the cold polar reservoir becomes cyclonic Repeated pattern of waves associated with each flooding event Slow-moving cyclonic anomalies over UK, forcing air to ascend and rain

14 THORPEX International Science Plan
Impacts of severe weather associated with four Rossby wave-trains that encircled the globe during November 2002 THORPEX International Science Plan

15 Global tropopause trough-ridge pattern (Rossby Waves)

16 Time/longitude diagram 250hPa meridional wind (ms-1); 35-60ºN 6-28 November 2002
Alan Thorpe

17 On 1 August 2002, a Rossby wave train was excited by cyclogenesis east of Japan, followed by rapid downstream development of high-amplitude Rossby waves, culminating in severe flooding in Central Europe on 11 August 2002. Prague Hovmöller diagram of 250-mb meridional wind component (ms-1) 28 July -14 August 2002 (40-60ºN) Mel Shapiro, NOAA

18 Madden-Julian Oscillation (MJO)
Main mode of intraseasonal variability in tropical convection and rainfall Rainfall Composite life-cycle (DJF) mm/day Adrian Matthews, University of East Anglia

19 MJO teleconnections (1)
Acts as a moving source of extra-tropical wave-trains cloudy clear Source: U.S. CLIVAR

20 MJO teleconnections (2)
Modulation of Atlantic hurricane activity in Summer, especially strongest (cat. 3-5) Source: U.S. CLIVAR

21 Madden-Julian Oscillation (MJO)
Main mode of intraseasonal variability in tropical convection and rainfall Propagates eastwards from Indian Ocean to west Pacific ● time lagged correlations along the equator ● a moving source of waves propagating into mid-latitudes Modulation of the Asian Summer monsoon (active/break cycle) Poorly simulated in models (latest ECMWF model much improved) Potential for extended predictability in both tropics and extra-tropics (few weeks)

22 Teleconnections and climate change
Increasing analysis of variability in models (IPCC, AR4) El Niño Southern Oscillation (ENSO) NAO and Northern Annular Mode (NAM) Other possible changes: jet stream waveguide characteristics; triggering More understanding of present day variability is needed to underpin this e.g. apparent phase locking; persistence of anomalies Assess simulations of present day variability and teleconnections

23 Climate Change - El Niño
Weak tendency for change in mean Pacific state to be “El Niño like” No agreement on El Niño variability Weaker teleconnections over N. America Figure Base state change in average tropical Pacific SSTs and change in El Niño variability simulated by AOGCMs (see Table 8.1 for model details). The base state change (horizontal axis) is denoted by the spatial anomaly pattern correlation coefficient between the linear trend of SST in the 1% yr–1 CO2 increase climate change experiment and the first Empirical Orthogonal Function (EOF) of SST in the control experiment over the area 10°S to 10°N, 120°E to 80°W (reproduced from Yamaguchi and Noda, 2006). Positive correlation values indicate that the mean climate change has an El Niño-like pattern, and negative values are La Niña-like. The change in El Niño variability (vertical axis) is denoted by the ratio of the standard deviation of the first EOF of sea level pressure (SLP) between the current climate and the last 50 years of the SRES A2 experiments (2051–2100), except for FGOALS-g1.0 and MIROC3.2(hires), for which the SRES A1B was used, and UKMO-HadGEM1 for which the 1% yr–1 CO2 increase climate change experiment was used, in the region 30°S to 30°N, 30°E to 60°W with a five-month running mean (reproduced from van Oldenborgh et al., 2005). Error bars indicate the 95% confidence interval. Note that tropical Pacific base state climate changes with either El Niño-like or La Niña-like patterns are not permanent El Niño or La Niña events, and all still have ENSO inter-annual variability superimposed on that new average climate state in a future warmer climate. Oldenborgh et al (2005) in IPCC, AR4 (2007)

24 Climate Change - NAO

25 Climate Change – Annular Indices
Figure (a) Multi-model mean of the regression of the leading EOF of ensemble mean Northern Hemisphere sea level pressure (NH SLP, thin red line). The time series of regression coefficients has zero mean between year 1900 and The thick red line is a 10-year low-pass filtered version of the mean. The grey shading represents the inter-model spread at the 95% confidence level and is filtered. A filtered version of the observed SLP from the Hadley Centre (HadSLP1) is shown in black. The regression coefficient for the winter following a major tropical eruption is marked by red, blue and black triangles for the multi-model mean, the individual model mean and observations, respectively. (b) As in (a) for Southern Hemisphere SLP for models with (red) and without (blue) ozone forcing. Adapted from Miller et al. (2006). Average change projects onto Northern Annular Mode (NAM) Recent variability not captured (NAM) Caveat on methodology Miller et al (2006) in IPCC, AR4 (2007)

26 Teleconnections - Conclusions
Remote effects of modes of variability, e.g. El Niño, NAO Wave propagation – tropics; great circles; jet streams as waveguides Downstream developments on the jet stream: examples of linked weather, e.g. November 2002, August 2002 triggering: storm growth; tropical cyclone transitions persistent anomalies, e.g. Summer 2007 (Autumn 2000) Tropical convection – MJO: eastward propagation - time lagged correlations in tropics moving source of waves for extra-tropics (predictability) Climate change: uncertainty, even for El Niño and NAO potential methodology

27 - End -

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