Heather Archambault Advisors: Lance Bosart and Daniel Keyser NWS Focal Point: Rich Grumm

1. Large-Scale Regime Transition and Its Relationship to Significant Cool Season Precipitation Events in the Northeast Heather Archambault Advisors: Lance Bosart and Daniel Keyser NWS Focal Point: Rich Grumm Department of Earth and Atmospheric Sciences, University at Albany, State University of New York

2. Research Motivation • Meteorological wisdom: increased threat of major storm during large-scale regime change • Past research points to a possible connection between synoptic-scale cyclogenesis and reconfiguration of the planetary-scale flow • Dave Groenert (CSTAR, 2002) documented an apparent tendency for an increased number of precipitation events in the Northeast during phase transitions of the NAO

3. Presentation Overview • Research goals • Climatology of PNA/NAO tendency • Time series of NAO/PNA tendency [d(INDEX)/dt] • Correlations with NE domain-average daily precipitation • Correlations with 1000 hPa NE Height Anomaly Index (HAI) • Major regime change / NE precipitation correlation • Major regime change / NE height anomaly correlation • Future work

4. Focus of Research: • Review literature that documents individual cases of reconfiguration of the planetary-scale flow in association with major precipitation events in the Northeastern United States • Relate previous work to modern definitions of regime change • Determine and quantify an objective definition for a significant large-scale regime change • Phase change of teleconnection index (PNA, NAO) greater than 2 standard deviations over a 7-day period

5. Focus (cont): • Determine whether more storms/precipitation can be expected during regime changes as compared to climatology in the Northeast • Construct composite analyses to identify characteristic signatures of significant large-scale regime changes • Use composite analyses and results from case studies to determine whether possible regime change/precipitation relationships are associative or cause and effect

6. Positive PNA – Thickness Anomalies Courtesy: Anantha Aiyyer & Eyad Atallah

7. Negative PNA – Thickness Anomalies Courtesy: Anantha Aiyyer & Eyad Atallah

8. Positive NAO – Thickness Anomalies Courtesy: Anantha Aiyyer & Eyad Atallah

9. Negative NAO – Thickness Anomalies Courtesy: Anantha Aiyyer & Eyad Atallah

10. Climatology of Teleconnection Tendencies PNA Tendencies (1948-2001, 7 Day Interval) NAO Tendencies

11. Daily Index Tendency / NE Precipitation Time Series Correlations • Daily time series of NAO/PNA tendency were created • Seven-day tendency: Index on Day (t + 3) – Index on Day (t - 3) • Correlated with time series of daily NE precipitation • Standardized domain-average precipitation values calculated from the Unified Precipitation Dataset (UPD) from 1954 - 1998 • Seven-day NAO tendency / precipitation correlation: • Correlation Coefficient: -0.04, R2 value: 0.0 • Seven-day PNA tendency / precipitation correlation: • Correlation Coefficient: 0.04, R2 value: 0.0 • Conclusion: No correlation between daily teleconnection index tendency and Northeast daily precipitation values

12. 1000 hPa Height Anomaly Index (HAI) • Purpose: correlate with daily NAO/PNA tendency as an alternative to daily precipitation values • 1000 hPa height anomalies calculated from NCEP/NCAR Reanalysis (1951 – 2001) • Height anomalies are normalized according to climatology of the 15-day period centered around each day • This accounts for the higher mean/smaller standard deviation in the height field that exists in summer vs. winter

14. 48.2 % of days had HAI < 0 (8,970 of 18,628 days)

15. Daily Index Tendency / NE Height Anomaly Time Series Correlations • Time series of daily tendency of the NAO/PNA were correlated with time series of daily 1000 hPa Northeast Height Anomaly Index (HAI) • Seven-day NAO tendency / HAI correlation: • Correlation Coefficient: -0.06, R2 value: 0.00 • Seven-day PNA tendency / HAI correlation: • Correlation Coefficient: -0.23, R2 value: 0.05 • Conclusion: No significant correlation between daily index tendency and daily Northeast 1000 hPa height anomaly index

16. Major Regime Change / NE Precipitation Correlations • Based on definition of major regime change: created a subset of days for further correlations with precipitation • Index change during major regime transition was correlated with daily precipitation • Major regime transition: phase change of greater than 2 standard deviations

17. Overall NAO regime change / precipitation correlation: Correlation Coefficient: -0.07, R2 value: 0.01

18. Overall PNA regime change / precipitation correlation: Correlation Coefficient: 0.11, R2 value: 0.01

19. Major Regime Change / 1000 hPa NE Height Anomaly Correlations • Index tendency for the days where a major regime change was ongoing was correlated with daily 1000 hPa height anomalies

20. Overall NAO regime change / HAI correlation: Correlation Coefficient: -0.15, R2 value: 0.02

21. Overall PNA regime change / HAI correlation: Correlation Coefficient: 0.0, R2 value: 0.0

22. Preliminary Results • No correlation between daily time series of index tendency & NE precipitation / 1000 hPa height anomalies • Major NAO swings / NE precipitation: • Weakening jet (+NAO to–NAO) : possible enhanced precipitation in winter • Strengthening jet (–NAO to +NAO): possible enhanced precipitation in summer • For major swings in the NAO, a slight negative correlation with 1000 hPa height anomalies can be found in the summer months: • negative height anomalies are correlated with a strengthening of the North Atlantic jet (negative to positive NAO) • approximately 10% of height anomaly variability can be attributed to major swings in the NAO during summer months

23. Preliminary Results (cont.) • For major swings in the PNA, the largest correlation with precipitation can be found in March (R2 = 0.29) and April • Ridge building in west/troughing in SE: enhanced precipitation • No overall correlation between major swings in the PNA and 1000 hPA height anomalies • Slight positive correlation is found in May-June • PNA change from positive to negative corresponds with heights lowering in western Canada/Pacific NW, ridge amplification over SE US • Slight negative correlation is found in July-August • PNA change from negative to positive corresponds with building ridge in western Canada/Pacific NW and lower heights in the southeastern US

24. What’s Next • Determine whether a “significant” precipitation event is more likely during a major PNA or NAO swing as compared to climatology • Lag correlations: storm at end, beginning of regime change? • Create correlation maps using top NAO and PNA transitions • Find best correlation between transitions and 1000 hPa height anomalies/precipitation for the United States