A Synoptic Climatological Approach to the Identification of January Temperature Anomalies in the Uni


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A Synoptic Climatological Approach to the
Identification of January Temperature Anomalies
in the United States

• Melissa Malin
• Katrina Frank
• Steven Quiring
• Richard Boutillier
• Laurence Kalkstein
• Center for Climatic Research
• Department of Geography
• University of Delaware

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January Temperature AnomalyThe January Thaw

• an anomalous warm spell that occurs during the
  coldest time of year
• a singularity a characteristic meteorological
  condition that tends to occur on or near a
  specific calendar date. American
  Meteorological Society
• has roots in New England weather folklore
• discrepancies exist as to the timing of the
  singularity
• possible causal mechanisms include
• oceanic forcings Hayden 1976
• atmospheric patterns Wahl 1953
• extra-terrestrial events sunspots meteor
  showers
• Bowen 1956 Newman 1965

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Goal of the Project

• identify winter temperature singularities across
  the United States and the inter- and intra-
  regional variability of the events
• assess the potential that changes in air mass
  frequency are a causal mechanism for the events

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Study Area
West
Mountain
East
Great Plains
Midwest
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MethodsData

• Study Period
• December 1February 28 19482000
• Air Temperature Data
• 4 a.m. 4 p.m. Average Daily Air Temperature
• National Climatic Data Center
• Spatial Synoptic Classification Air Mass Data
• Dry Moderate DM / Dry Moderate DM
• Dry Polar DP / Dry Polar - DP-
• Dry Tropical DT
• Moist Moderate MM
• Moist Polar MP / Moist Polar MP
• Moist Tropical MT
• Transition TR

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MethodsWindowing
Philadelphia Pennsylvania
Window Number

• daily average temperature data plotted for each
  station
• standardized using a five-day moving window

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MethodsIdentification of Singularities
Window Number

• second-order polynomial curve fit for winter
  trendline
• upper/ lower bounds set at two standard
  deviations

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MethodsIdentification of Singularitiesexample
at Mountain Region station
Cheyenne Wyoming
Upper Bound
Thaw singularity at January 16-18
Lower Bound
Winter Trendline
Freeze singularity at January 2- 4
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ResultsIdentification of SingularitiesDecember
25
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ResultsIdentification of SingularitiesDecember
26
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ResultsIdentification of SingularitiesDecember
27
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ResultsIdentification of SingularitiesDecember
28
13
ResultsIdentification of SingularitiesDecember
29
14
ResultsIdentification of SingularitiesDecember
30
15
ResultsIdentification of SingularitiesDecember
31
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ResultsIdentification of SingularitiesJanuary 1
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ResultsIdentification of SingularitiesJanuary 2
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ResultsIdentification of SingularitiesJanuary 3
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ResultsIdentification of SingularitiesJanuary 4
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ResultsIdentification of SingularitiesJanuary 5
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ResultsIdentification of SingularitiesJanuary 6
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ResultsIdentification of SingularitiesJanuary 7
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ResultsIdentification of SingularitiesJanuary 8
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ResultsIdentification of SingularitiesJanuary 9
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ResultsIdentification of SingularitiesJanuary 10
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ResultsIdentification of SingularitiesJanuary 11
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ResultsIdentification of SingularitiesJanuary 12
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ResultsIdentification of SingularitiesJanuary 13
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ResultsIdentification of SingularitiesJanuary 14
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ResultsIdentification of SingularitiesJanuary 15
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ResultsIdentification of SingularitiesJanuary 16
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ResultsIdentification of SingularitiesJanuary 17
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ResultsIdentification of SingularitiesJanuary 18
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ResultsIdentification of SingularitiesJanuary 19
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ResultsIdentification of SingularitiesJanuary 20
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ResultsIdentification of SingularitiesJanuary 21
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ResultsIdentification of SingularitiesJanuary 22
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ResultsIdentification of SingularitiesJanuary 23
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ResultsIdentification of SingularitiesJanuary 24
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ResultsIdentification of SingularitiesJanuary 25
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ResultsIdentification of SingularitiesJanuary 26
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ResultsIdentification of SingularitiesJanuary 27
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ResultsIdentification of SingularitiesJanuary 28
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ResultsIdentification of SingularitiesJanuary 29
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MethodsAir Mass Frequency AnalysisSecond-Order
Polynomial Fit
Bismarck North Dakota Dry Polar -

• fit trendline to winter air mass frequency
• found differences to winter air mass trendline

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MethodsAir Mass Frequency AnalysisLinear Fit
Philadelphia Pennsylvania Moist Polar

• correlated air mass frequency differences with
  temperature singularities
• r 0.8 strong correlation 0.8 ? r ? 0.5
  moderate correlation r correlation

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ResultsJanuary Thaw

• Mountain
• no clear signal
• character rather than frequency of air masses
  may be changing?
• Plains
• increased DP and decreased DP- frequency
• suggests character change
• Midwest
• increased MT and decreased DT suggests
  circulation pattern change

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ResultsJanuary Freeze

• West
• increased polar frequency
• decreased moderate frequency
• Plains
• decreased DP and increased DP- frequency
• suggests character change

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Conclusionsand Directions for Future Research

• this research offers strong support for the
  existence of cohesive January Thaw and January
  Freeze events
• show signs of systematic movement across the
  United States
• suggests potential of circulation as causal
  mechanism
• air mass analysis shows . . .
• Freeze associated with less frequent warm air
  masses more frequent cold air masses
• Thaw not clearly associated with air mass
  frequency
• need for an investigation of air mass character
• and upper level flow patterns