1. A Statistical Analysis and Synoptic Climatology of U.S. Heat Waves Scott C. Runyon and Lance F. Bosart Department of Earth and Atmospheric Sciences, University at Albany, State University of New York

2. Introduction: Why study heat waves? Heat waves are a major contributor to weather–related fatalitiesHeat waves are a major contributor to weather–related fatalities Understanding the characteristics of heat waves would lead to improved forecastsUnderstanding the characteristics of heat waves would lead to improved forecasts These forecasts may become more critical given the possibility of an increase in the frequency and intensity of heat wavesThese forecasts may become more critical given the possibility of an increase in the frequency and intensity of heat waves

3. Introduction (cont.): Previous work has largely focused on specific heat wave events (e.g. July 1995) or extended “heat wave-droughts” (e.g. 1980 & 1988)Previous work has largely focused on specific heat wave events (e.g. July 1995) or extended “heat wave-droughts” (e.g. 1980 & 1988) Published synoptic climatologies have been limited in scope to the Midwest or Great Plains (e.g. Chang & Wallace, 1984)Published synoptic climatologies have been limited in scope to the Midwest or Great Plains (e.g. Chang & Wallace, 1984)

4. Purpose: Document differences in heat waves as a function of both season and regionDocument differences in heat waves as a function of both season and region Understand both the dynamical and thermo- dynamical contributions to regional heat wavesUnderstand both the dynamical and thermo- dynamical contributions to regional heat waves Resolve annual and decadal trends in heat wave frequencyResolve annual and decadal trends in heat wave frequency

5. Overview: Methodology/DefinitionsMethodology/Definitions ResultsResults –Skewed datasets –Northeast heat wave statistics –Case Study: 7-11 June 1984 SummarySummary –Conclusions –Future Work

6. Methodology: Temperature data was extracted from the National Climatic Data Center’s (NCDC) high resolution surface datasetTemperature data was extracted from the National Climatic Data Center’s (NCDC) high resolution surface dataset Database contains daily high temperatures for 54 stations over a 54-year period (1948- 2001)Database contains daily high temperatures for 54 stations over a 54-year period (1948- 2001) Surface stations were selected on the basis of dataset continuity and geographical coverageSurface stations were selected on the basis of dataset continuity and geographical coverage

7. Methodology (cont.): Stations in Database

8. Methodology (cont.): Definitions:Definitions: –An anomalously hot day was initially defined as a day having a high temperature at least 2 standard deviations (σ) above the normal high temperature for the date –This definition was later changed to a day having a high temperature above the climatological 97.5 percentile threshold for the date –A heat wave was defined as three or more consecutive anomalously hot days – no matter the season

9. Methodology (cont.) Regions mirror the NCDC Standard Regions for Temperature and PrecipitationRegions mirror the NCDC Standard Regions for Temperature and Precipitation Heat waves were considered regional when two or more stations within that region had overlapping warm daysHeat waves were considered regional when two or more stations within that region had overlapping warm days All anomalously hot days, heat waves, and regional heat waves were identified for each station and each region across the countryAll anomalously hot days, heat waves, and regional heat waves were identified for each station and each region across the country

10. Results “Skewness” of Daily High Temperature Data Initially using a 2σ high temperature anomaly to define a hot day  a surprising amount of variability in number of heat waves identified from one city to the nextInitially using a 2σ high temperature anomaly to define a hot day  a surprising amount of variability in number of heat waves identified from one city to the next A serendipitous discovery: a discrepancy between number of anomalously cold days and the number of anomalously hot days for most stations in the datasetA serendipitous discovery: a discrepancy between number of anomalously cold days and the number of anomalously hot days for most stations in the dataset

11. Results: Top Ten “Skewed” Cities Positively Skewed Negatively Skewed

12. Most Negatively Skewed City: Denver In 54-year dataset, only 49 days met old criteria as anomalously hot days (T≥2σ)In 54-year dataset, only 49 days met old criteria as anomalously hot days (T≥2σ) Only 2 heat waves were identified in the entire datasetOnly 2 heat waves were identified in the entire dataset

13. March 1 – May 31 – Denver, CO Daily High Temperatures – Spring Mean Mean + 2σ Mean - 2σ

14. – Denver, CO Daily High Temperatures – Summer June 1 – August 31

15. – Denver, CO Daily High Temperatures – Fall September 1 – November 30

16. – Denver, CO Daily High Temperatures – Winter December 1 – February 29

17. Most Positively Skewed City: Los Angeles In 54-year dataset, 989 days met old criteria as anomalously hot days (T≥2σ)In 54-year dataset, 989 days met old criteria as anomalously hot days (T≥2σ) Hence, over 130 heat waves were identified in the datasetHence, over 130 heat waves were identified in the dataset

18. – Los Angeles, CA Daily High Temperatures – Spring March 1 – May 31

19. – Los Angeles Daily High Temperatures – Summer June 1 – August 31

20. – Los Angeles, CA Daily High Temperatures – Fall September 1 – November 30

21. – Los Angeles, CA Daily High Temperatures – Winter December 1 – February 29

22. New Method: An anomalously hot day is now defined as a day having a high temperature above the daily climatological 97.5 percentile thresholdAn anomalously hot day is now defined as a day having a high temperature above the daily climatological 97.5 percentile threshold Heat wave definitions remained unchangedHeat wave definitions remained unchanged Updated Figures:Updated Figures: –DNR: 736 Days, 41 Heat Waves –LAX: 669 Days, 66 Heat Waves

23. Stat. Analysis of Northeast Heat Waves

32. Results: A trend toward more Winter and Spring heat waves with timeA trend toward more Winter and Spring heat waves with time A trend toward fewer Summer and Autumn heat waves with timeA trend toward fewer Summer and Autumn heat waves with time Decades of the 1950’s, 1980’s and 1990’s had the highest frequency of heat wavesDecades of the 1950’s, 1980’s and 1990’s had the highest frequency of heat waves

33. A Case Study: 7-11 June 1984 A long-lasting, region-wide Northeast heat waveA long-lasting, region-wide Northeast heat wave Both thermodynamic and dynamic signatures can be seenBoth thermodynamic and dynamic signatures can be seen

34. June 4, 1984 ALB: 80° F LGA: 85° F BOS: 85° F

35. June 5, 1984 ALB: 84° F LGA: 88° F BOS: 89° F

36. June 6, 1984 ALB: 81° F LGA: 88° F BOS: 70° F

37. June 7, 1984 ALB: 89° F LGA: 93° F BOS: 89° F

38. June 8, 1984 ALB: 93° F LGA: 96° F BOS: 97° F

39. June 9, 1984 ALB: 93° F LGA: 95° F BOS: 96° F

40. June 10, 1984 ALB: 91° F LGA: 95° F BOS: 95° F

41. June 11, 1984 ALB: 90° F LGA: 96° F BOS: 98° F

42. June 12, 1984 ALB: 82° F LGA: 84° F BOS: 85° F

43. June 4, 1984 ALB: 80° F LGA: 85° F BOS: 85° F

44. June 5, 1984 ALB: 84° F LGA: 88° F BOS: 89° F

45. June 6, 1984 ALB: 81° F LGA: 88° F BOS: 70° F

46. June 7, 1984 ALB: 89° F LGA: 93° F BOS: 89° F

47. June 8, 1984 ALB: 93° F LGA: 96° F BOS: 97° F

48. June 9, 1984 ALB: 93° F LGA: 95° F BOS: 96° F

49. June 10, 1984 ALB: 91° F LGA: 95° F BOS: 95° F

50. June 11, 1984 ALB: 90° F LGA: 96° F BOS: 98° F

51. June 12, 1984 ALB: 82° F LGA: 84° F BOS: 85° F

52. Case Study Results Origin of hot air: Rockies (elevated heat source)Origin of hot air: Rockies (elevated heat source) Downsloping plays a role:Downsloping plays a role: –Westward extension of the Bermuda High into Southeast allowed for west-northwesterly flow throughout period –Warm air coming off Rockies Anticylonic shear side of jet: subsidenceAnticylonic shear side of jet: subsidence June 9 th : Northeast located in the equator- ward jet exit region: enhanced subsidenceJune 9 th : Northeast located in the equator- ward jet exit region: enhanced subsidence

53. Conclusions: From initial heat-wave identifying methodology: daily max temperatures are not normally distributedFrom initial heat-wave identifying methodology: daily max temperatures are not normally distributed Stations located adjacent to cool (warm) water seem to have positively (negatively) skewed high temperature dataStations located adjacent to cool (warm) water seem to have positively (negatively) skewed high temperature data Most stations have a cool biasMost stations have a cool bias

54. Conclusions (cont.) : From Northeast statistics :From Northeast statistics : –Positive heat wave trend in Winter and Spring –Negative heat wave trend in Summer and Autumn From case study :From case study : –Heat waves can have both dynamic and thermodynamic aspects –Local wind direction is important

55. Conclusions (cont.): Future Work:Future Work: –Apply statistical methods to other regions Create composite analyses to: –Illustrate typical synoptic signatures of heat waves in each season –Determine regional “flavor” of heat waves