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Near-Surface Climate Extremes in the Past 50+ Years

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. ...Now the wind grew strong and hard, it worked at the rain crust in the corn fields.

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Near-Surface Climate Extremes in the Past 50+ Years

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  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

  3. From NCDC/NOAA

  4. From NCDC/NOAA 1931  present

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

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

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

  8. 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)

  9. 10 Land Surface Datasets: • 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 2. Four 50+ Year Retrospective Offline Runs • 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 3. Four Reanalysis Datasets • 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

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

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

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

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

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

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

  16. T2m -- Decadal variation of cold extreme (anom<30C, 2*sd) 1950s 1980s 1960s 1990s 1970s 2000s

  17. T2m -- Decadal variation of warm extreme (anom>30C, 2*sd) 1950s 1980s 1960s 1990s 1970s 2000s

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

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

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

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

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

  23. 1948  present Tucson, Arizona A special thanks to the Bakers in Tucson for the above photo Mammoth, Arizona A special thanks to Raymond Prax for the above photo

  24. Concluding Remarks 1) We are only beginning2) 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 Tucson, Arizona A special thanks to the Bakers in Tucson for the above photo Mammoth, Arizona A special thanks to Raymond Prax for the above photo

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

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