Improving Understanding and Predictions of Extreme Events: The Climate Weather Connection

Transcription

1 Improving Understanding and Predictions of Extreme Events: The Climate Weather Connection Randall Dole NOAA Earth System Research Laboratory Physical Sciences Division Boulder CO M. Hoerling, A. Kumar, J. Eischeid, J. Perlwitz, X. Quan, G. Kiladis, R. Webb, D. Murray, M. Chen, K. Wolter, T. Zhang February 11, 2014 International Conference on Subseasonal to Seasonal Prediction 1 Outline Identify factors that contributed to making an event extreme (record warm US temperatures in March 2012) Consider contributions across time scales from long term climate trends to short term weather variations Examine how the probability for an extreme event evolved as different phenomena became predictable Overarching theme: Connecting climate and weather to advance understanding and predictions of extreme events 2

2 An extreme event: March Madness! 3 March

3 March 2012 For the contiguous U.S. March 2012 was 4.8 o C (8.6 o F) above normal, 0.3 o C (0.5 o F) warmer than March 1910 (NCDC). 5 Global Temperature Anomalies March 2012 and March 1910 Evidence of similar features outside the U.S. Compared with March 1910, March 2012 was 0.9 o C warmer. 6

4 Contribution of Long term Trend 7 SST and OLR anomalies DJF SST OLR 8

5 Event time scale Zero crossings March 10 April 6 ~ 27 days Most intense anomalies ~ March What was the proximate cause for the extreme warm temperatures? March 2012 T sfc T 850 T clim, V 850 Intense and sustained poleward heat transports 10

6 What is the proximate cause for the extreme warm temperatures? March March 1910 T sfc T 850 Tclim, V 850 Intense and sustained poleward heat transports 11 What factors led to the anomalous winds associated with the heat wave? Strong wavetrain emanating from the Pacific June 4,

7 What is the source for this anomalous wavetrain? Peng and Whitaker (1999) Simple linear baroclinic model experiments forced by idealized heating suggest a tropical Pacific wave source June 4, MJO and Rossby Wave Dispersion OLR Z

8 Was There Evidence of Predictability? NCEP CFSv2 40 member Ensemble Forecasts for March 2012 initialized in Dec, Jan, and Feb all show a warm signal over the eastern US What was the Role of Anomalous Boundary Conditions? March 2012 AMIP Simulations with GFS Model, 50 member ensemble T Z

9 CFS Forecasts by Lead Time 17 Contributions from various factors 18

10 Contributions from various factors 19 Contributions from various factors 20

11 How about other factors? Snow cover Soil moisture, vegetation Sea ice Stratospheric circulation Mid latitude dynamical interactions 21 Putting the Pieces Together While the U.S. experienced exceptionally warm temperatures in March 2012, a March that occurred over a century earlier was nearly as warm. The superposition of a strong natural climate variation similar to March 1910 together with a long term warming of the magnitude observed would be sufficient to account for the record warm March 2012 U.S. temperatures. Coupled model forecasts and AMIP simulations show that forcing from anomalous SSTs increased the probability of extreme warmth in the eastern US above that anticipated from the long term warming trend. Forcing associated with a strong MJO further increased the probability for extreme U.S. warmth and provided important additional predictive information on the timing and spatial pattern of the temperature anomalies. 22

12 Conclusion Factors from centennial climate trends to weather all contributed to making this event extreme. Phenomena evolving from longer to shorter time scales successively added predictive information for anticipating the potential for extreme US warmth in March Bridging predictions from climate to weather, especially to anticipate extreme events, will be essential for meeting many societal needs, from improving early warnings on potential disasters to providing information needed for longer term adaptation to a changing climate. The WWRP WCRP Subseasonal to Seasonal Prediction Project can provide major contributions toward achieving this important goal. 23 Is the variability changing? 24