1. Near-Surface Climate Extremes in the Past 50+ Years Yun Fan & Huug van den Dool CPC/NCEP/NOAA NOAA 32th Annual Climate Diagnostic & Prediction Workshop 22-26 October, 2007, Tallahassee, FL

2. ...Now the wind grew strong and hard, it worked at the rain crust in the corn fields. Little by little the sky was darkened by the mixing dust, and the wind felt over the earth, loosened the dust and carried it away....from The Grapes of Wrath, written by John Steinbeck. From NCDC/NOAA

5. 1931  present

6. Mammoth, Arizona A special thanks to Raymond Prax for the above photo Tucson, Arizona A special thanks to the Bakers in Tucson for the above photo

8. a.What is a climate extreme event? b.How about the spatial distribution of extreme events? c.How do hydrological extremes respond to observed P & T extremes? d.What are the capability and uncertainty of current land surface data analysis systems to faithfully describe extreme events? Motivation

9. A climate extreme event is an anomalous event that departs significantly from its normal state in frequency, magnitude, temporal and spatial extent What is a climate extreme event?

10. How to measure a climate extreme event? Goal: to establish an objective definition based on some thresholds WMO climatology to define “anomaly” Frequency <= N of recurrence Rarity or small probability of occurrence Amplitude => N * STD maxima or minima, exceed threshold, break record Temporal extent => N*Months time duration or lasting time Spatial extent => # grid boxes impacted area or region Severity, …… impact (harder: such as loss of life and properties)

11. 10 Land Surface Datasets: 2.Four 50+ Year Retrospective Offline Runs 3.Four Reanalysis Datasets 1.Observations CPC Monthly Global Land Surface Air Temperature Analysis (1948- present)  Y. Fan & H. van den Dool, 2007 CPC Monthly Global Land Surface Air Temperature Analysis (1948- present)  Chen et al 2003 RR - North American Regional Reanalysis (1979 - present)  F. Mesinger et al, 2003, 2005 R1 – NCEP-NCAR Global Reanalysis I (1948 - present)  E. Kalnay et al, 1996 & R. Kistler et al 2001 R2 – NCEP-DOE Global Reanalysis II (1979 - present)  M. Kanamitsu et al, 2002 ERA40 – ECMWF Reanalysis 40 Project (1957-2002)  S. Uppala et al 2005 Noah - Noah LSM Retrospective N-LDAS Run (1948-2002) – present  Y. Fan, H, van del Dool, D. Lomann & K. Mitchell, 2003 VIC - VIC LSM Retrospective N-LDAS Run (1950-2000)  E. Maurer, A. Wood, J. Adam, D. Lettenmaier & B. Nijssen, 2002 LB - CPC Leaky Bucket Soil Moisture Datasets  US_CD: 1931-present: J. Huang, H. van den Dool & K. Georgakakos, 1996,  Globe: 1948-present: Y. Fan & H. van den Dool, 2004

12. Driest Precipitation (1948-present) Wettest Time Location

13. Dry Precipitation Wet Increase threshold # of ‘rare’ events 2.0*sd 3.0*sd 2.5*sd 3.0*sd 2.5*sd 2.0*sd

14. Precipitation -- Decadal variation of dry extreme (anom < -2mm, 2*sd) # of ‘rare’ events 1950s 1960s 1970s 1980s 1990s 2000s

15. # of ‘rare’ events Precipitation -- Decadal variation of wet extreme (anom>2mm, 2*sd) 1950s 1960s 1970s 1980s 1990s 2000s

16. Coldest T2m (1948-present) Warmest Location Time

17. Cold T2m Warm 2.0*sd 3.0*sd 2.5*sd 2.0*sd

18. T2m -- Decadal variation of cold extreme (anom<3 0 C, 2*sd) 1950s 1960s 1980s 1990s 2000s1970s

19. T2m -- Decadal variation of warm extreme (anom>3 0 C, 2*sd) 1950s 1960s 1970s2000s 1990s 1980s

20. Driest Soil Moisture from CPC Leaky Bucket Wettest (1948-present) Location Time

21. Dry Soil Moisture Wet 2.0*sd 2.5*sd 3.0*sd 2.0*sd 2.5*sd 3.0*sd

22. SM -- Decadal variation of dry extreme (anom<-10mm, 2*sd) 1950s 1960s 1970s 1980s 1990s 2000s

23. SM -- Decadal variation of wet extreme (anom>10mm, 2*sd) 1950s 1960s 1970s 1980s 1990s 2000s

24. Mammoth, Arizona A special thanks to Raymond Prax for the above photo Tucson, Arizona A special thanks to the Bakers in Tucson for the above photo 1948  present SM anom: shaded Disaster right now Temp increase is a factor! Most Deadly heat wave in European history

25. Mammoth, Arizona A special thanks to Raymond Prax for the above photo Tucson, Arizona A special thanks to the Bakers in Tucson for the above photo 1948  present

26. Mammoth, Arizona A special thanks to Raymond Prax for the above photo Tucson, Arizona A special thanks to the Bakers in Tucson for the above photo Concluding Remarks 1) We are only beginning 2) Climate extreme  weather extremes 3) Timing is everything! 4) Due to climate change: +ve T anomalies stronger recently in general 5) Reliability + length of data sets is obviously important

27. Mammoth, Arizona A special thanks to Raymond Prax for the above photo Tucson, Arizona A special thanks to the Bakers in Tucson for the above photo Thanks!