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This study examines climate extreme events and their spatial distribution, hydrological response, and the capabilities and uncertainties of current land surface data analysis systems. It provides insight into measuring and defining climate extreme events using various thresholds and datasets.
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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. 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
From NCDC/NOAA 1931 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
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?
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
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)
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
Driest Precipitation (1948-present) Wettest Location Time
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
Precipitation -- Decadal variation of dry extreme (anom < -2mm, 2*sd) 1950s 1980s 1960s 1990s 1970s 2000s # of ‘rare’ events
Precipitation -- Decadal variation of wet extreme (anom>2mm, 2*sd) 1950s 1980s 1960s 1990s 1970s 2000s # of ‘rare’ events
Coldest T2m (1948-present) Warmest Location Time
Cold T2m Warm 2.0*sd 2.0*sd 2.5*sd 2.5*sd 3.0*sd 3.0*sd
T2m -- Decadal variation of cold extreme (anom<30C, 2*sd) 1950s 1980s 1960s 1990s 1970s 2000s
T2m -- Decadal variation of warm extreme (anom>30C, 2*sd) 1950s 1980s 1960s 1990s 1970s 2000s
Driest Soil Moisture from CPC Leaky Bucket Wettest (1948-present) Location Time
Dry Soil Moisture Wet 2.0*sd 2.0*sd 2.5*sd 2.5*sd 3.0*sd 3.0*sd
SM -- Decadal variation of dry extreme (anom<-10mm, 2*sd) 1950s 1980s 1990s 1960s 1970s 2000s
SM -- Decadal variation of wet extreme (anom>10mm, 2*sd) 1950s 1980s 1960s 1990s 1970s 2000s
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
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
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
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