Extreme Temperature Regimes during the Cool Season Robert X. Black Rebecca Westby School of Earth and Atmospheric Sciences Georgia Institute of Technology,

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Presentation transcript:

Extreme Temperature Regimes during the Cool Season Robert X. Black Rebecca Westby School of Earth and Atmospheric Sciences Georgia Institute of Technology, Atlanta, Georgia DOE/BER Regional and Global Climate Modeling Program

Presentation Overview  General project objectives & research approach  Preliminary statistical results for cold air outbreaks: Focus on Atlanta  Illustrative synoptic & dynamic analyses: Jan 2004 Case Study Considerations of recent cold air outbreak behavior: Winters of 2009/2010 & 2010/2011  Summary & future research directions

Project Overview  General project objectives & research approach:  Quantify the modulation of extreme temperature regimes (ETRs) by low frequency modes (LFMs)  Assess the representation of ETRs and ETR-LFM linkages in global coupled climate models (CMIP5) Assess likely future changes in regional ETR behavior and ETR-LFM linkages (CMIP5)

General Approach and Datasets  Identify extreme temperature regimes (ETRs) in terms of local anomalies in either temperature or wind chill index (e.g., Walsh et al 2001; Osczevski and Bluestein 2005)  Basic data: Daily averaged reanalysis data (NCEP/NCAR, ERA-40 & NASA-GMAO MERRA) Top 15 winter wind-chill events for Albany, NY ( ) and relative ranking for temperature- only criterion. Asterisks denote events in which the peak wind- chill amplitude occurred on a slightly different day than peak temperature amplitude.

Interannual Variability in Cold Air Events in Atlanta Relationship with the Arctic Oscillation  Downward trend in cold air events until last 2-3 winters  Greatest number of cold days occurred in 2009/2010 (!)  Significant negative correlation with the AO (r = -0.55)

 Cold front passes through Atlanta ~12Z January 5, 2004  Highs in the 70s Jan 5 -> Lows in the 10s on Jan 7 1/05/20041/07/2004 Cold Air Outbreak: 12Z Jan 5, 2004 (NOAA/HPC)

Cold Air Outbreak: 12Z Jan 5, 2004 (Winds/EPV) 1/05/20041/07/2004

p Remote Influence of Local PV Anomalies (‘Charges’)  Poisson-like PV balance condition indicates nonlocal effects analogous to induction of electric field by localized charges x,y Spheroids of constant Z’ associated with isolated q anomalies [e.g., Hoskins et al. 1985] Vertical extent related to L/N; Large scales & weak N favor a downward influence

Piecewise PV Inversion: Quasi-Geostrophic Form

Cold Air Outbreak: Jan 5, 2004 (QGPV Anomalies)  Diagnose contributions of PV anomalies within different vertical layers to the northerly flow in lower troposphere  Anomalies defined as deviations from monthly mean flow  Divide PV anomaly field into three parts: 1) Upper tropospheric PV ( hPa) 2) Lower tropospheric PV ( hPa) 3) Surface theta at lower boundary ( hPa)

QGPV Inversions: Invert Entire PV Anomaly Field  Generally excellent quantitative correspondence over most regions  Notable errors near base of trough where strong curvature exists  Actual wind is subgeostrophic due to locally large Rossby number Supergeostrophic flow in ridge 300 hPa vector wind anomalies

QGPV Inversions: Invert Entire PV Anomaly Field  Generally excellent quantitative correspondence over most regions (including over midwest US)  Some errors near cold front  No differences where 925 hPa surface dips below ground Proceed to piecewise PV inversion 925 hPa vector wind anomalies

QGPV Inversions: Invert PV “Pieces”  Upper tropospheric PV induces southwesterly flow over midwest  Lower tropospheric PV induces northeasterly flow over midwest  Strong cancellation among the contributions of interior PV Surface theta induces northerlies 925 hPa vector wind anomalies

QGPV Inversions: Invert Surface PV “Pieces”  Isolate cold surface theta anomalies over the western US/Canada  Invert cold surface theta anomalies  Provides a large contribution to northerly flow over midwest US Cold anomalies east of Rockies promote northerlies to the east 925 hPa vector wind anomalies

Average surface air temperature anomalies 12/15 – 01/14 1/07/2004 Winters of 2009/10 & 2010/11: Unusual Behavior! AO index → (NOAA/CPC) Composite T Anomalies → (NOAA/ESRL)

Winters of 09/10 & 10/11: North Atlantic Jet Structure  Climo characterized by two jets: Subtropical jet & eddy-driven jet  North-South jet anomaly dipole found during 2009/10 with strong westerly anomalies near 30N  Net impact: Effective merger of the climatological jet features Similar behavior during 2010/11 Zonal wind averaged from 300W-360W (12/15 – 1/14)

2010/11: Nov 1 to Jan /10: Nov 1 to Jan hPa Zonal Wind Evolution over North Atlantic  Eddy driven jet strengthens during Fall and early winter  Subtropical jet develops beginning in January  Eddy driven jet abruptly collapses during Spring onset Climo: July 1 to June 30Climo: Nov 1 to Jan 20

Composite 500 hPa Geopotential Height Field Total heights: Left: climo Right: 2009/10 (12/15 – 1/14) Stationary eddies: Left: climo Right: 2009/10 (12/15 – 1/14)

Composite 500 hPa Geopotential Height Field Total heights: Left: climo Right: 2010/11 (12/15 – 1/14) Stationary eddies: Left: climo Right: 2010/11 (12/15 – 1/14)

Summary and Future Research Directions  Cold Air Outbreaks are evidently alive and well  Cold Air Outbreaks strongly modulated by AO/NAO  January 2004 case study: Southward surge of cold air through the midwest is primarily effected by cold surface theta anomalies positioned east of Rocky Mountains Recent winter behavior: Possible alterations in the seasonal cycle of the North Atlantic jetstream?  Future work: More fully explore the low frequency modulation of ETRs in different geographical regions  Future work: Examine the behavior of ETRs and their low frequency modulation in coupled climate models

PV Balance Condition:  Large-scale atmospheric disturbances are governed by the linear balance condition:  Poisson-like => nonlocal response in Z’ [e.g., Black 2002]

Boundary Conditions  Polar Continuity  Longitudinally cyclic  Z’ = 0 at low latitude boundary (10 0 N)  Upper and lower boundaries: a)Boundary q’ not included: b)If boundary q’ is included: [Black 2002]

EAS Quasi-Geostrophic Theory  Given a 3-D distribution of q’ and boundary conditions for  ’, one can invert the QG balance to infer the 3-D  ’ distribution. (From which the temperature and horizontal windfields can be deduced via hydrostatic & geostrophic balance, respectively)  Note: Laplacian-like operator  localized q anomalies are associated with a  anomaly distribution that may extend horizontally and vertically away into the far field (from q’).  Permits dynamic interaction of spatially separated q anomalies Quasi-Geostrophic Potential Vorticity