Midwest Urban Heat Wave Climatology: What Constitutes the Worst Events?
A thesis presented to
the faculty of
the College of Arts and Sciences of Ohio University
In partial fulfillment
of the requirements for the degree
Master of Science
Alek J. Krautmann
June 2012
© 2012 Alek J. Krautmann. All Rights Reserved.
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This thesis titled
Midwest Urban Heat Wave Climatology: What Constitutes the Worst Events?
by
ALEK J. KRAUTMANN
has been approved for
the Department of Geography
and the College of Arts and Sciences by
Ryan Fogt
Assistant Professor of Geography
Howard Dewald
Interim Dean, College of Arts and Sciences 3
ABSTRACT
KRAUTMANN, ALEK J., M.S., June 2012, Geography
Midwest Urban Heat Wave Climatology: What Constitutes the Worst Events?
Director of Thesis: Ryan L. Fogt
The onset of heat waves can be subtle and do not result in structural damage like many other meteorological events. Components to consider that comprise a heat wave include: duration, daytime high and overnight low temperatures, other atmospheric conditions, human impacts, and location. Nonetheless, even with these deterministic factors, heat waves lack a meaningful uniform meteorological definition. This Thesis focuses on what constitutes summer heat waves in the Midwest by identifying the thresholds of high temperature that are representative of the most extreme events. Heat waves are classified based on surface observation records from Columbus, Indianapolis,
Kansas City, and St. Louis. The large-scale weather features are examined for the most significant events. In addition, changes manifest in the number and duration of past heat waves are presented. The historical significance and characteristics of the most extreme heat waves on record are also discussed.
Approved: ______
Ryan L. Fogt
Assistant Professor of Geography 4
In honor of my parents, Gary and Joanna,
for their love and support.
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ACKNOWLEDGMENTS
I extend my sincere thanks to Dr. Ryan L. Fogt for his mentorship and guidance as my graduate advisor, as well as for his partnership in Scalia Lab as my colleague. It is my pleasure to thank my other committee members, Dr. Timothy Anderson and Dr.
Harold Perkins for their collaboration and as stewards of the Thesis process. Dr.
Anderson, Dr. Fogt, and Dr. Perkins bring excellence to the Department of Geography through their work and I am grateful to have had their assistance.
I would like to thank the Department of Geography for providing the opportunity to receive a graduate education and for assistantship during my tenure at Ohio University.
Additionally, I am thankful for Scalia Lab as a place of work, research, teaching, learning, and activity.
I also thank my mentors and colleagues at the University of Oklahoma and in the
National Oceanic and Atmospheric Administration, for they instilled in me the confidence as a young adult that has allowed me to reach this point. I am also grateful for the fantastic friends and peers across the county I have met along the way.
I owe my deepest gratitude to my parents and family for providing me a steadfast foundation of love and the freedom to succeed. Finally, I thank my Grandfather Alex, who exemplified the principles of dedication, service, and responsibility that I will forever strive to match.
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TABLE OF CONTENTS
Page
Abstract……………………………………………………………………………………3 Dedication…………………………………………………………………………………4 Acknowledgments…………………………………………………………………………5 List of Tables……………………………………………………………………………...8 List of Figures……………………………………………………………………………..9 Chapter 1: Introduction…………………………………………………………………..12 Chapter 2: Literature Review…………………………………………………………….15 2.1 Defining Heat Waves……………………………………………………………...16 2.1.1 Background……………………………………………………………………16 2.1.2 Extreme Temperature Thresholds……………………………………………..17 2.1.3 Percentile Thresholds………………………………………………………….19 2.1.4 Temperature and Moisture Characterization………………………………….21 2.2 Heat Wave Impacts in the Midwest……………………………………………….23 2.3 Region of Interest: Urban Centers of the Midwest………………………………..26 2.4 Future Heat Waves………………………………………………………………...29 2.4.1 Background……………………………………………………………………29 2.4.2 Future Heat Wave Variability…………………………………………………29 2.4.3 Future Heat Wave Magnitude…………………………………………………31 2.5 Conclusions………………………………………………………………………..33 Chapter 3: Data and Methods……………………………………………………………35 3.1 Data Employed……………………………………………………………………35 3.1.1 Surface Stations……………………………………………………………….35 3.1.2 Station Temperatures………………………………………………………….38 3.1.3 Historical Records……………………………………………………………..39 3.1.4 Reanalysis Data………………………………………………………………..40 3.2 Methods Employed………………………………………………………………..42 7
3.2.1 Persistence and Percentile Threshold………………………………………….42 3.2.2 Event Statistics………………………………………………………………...44 Chapter 4: Results and Discussion……………………………………………………….46 4.1 Heat Wave Events…………………………………………………………………47 4.2 Heat Wave Frequency……………………………………………………………..53 4.3 Characterization of Major Events…………………………………………………57 4.3.1 July 1936………………………………………………………………………57 4.3.2 July 1934………………………………………………………………………66 4.3.3 July 1901………………………………………………………………………69 4.4.4 July 1999………………………………………………………………………73 4.4 1930s Heat Waves…………………………………………………………………77 4.5 Urban Mitigation and Response Techniques for Heat Waves…………………….83 4.6 Summary…………………………………………………………………………..85 Chapter 5: Conclusion……………………………………………………………………87 References………………………………………………………………………………..95 8
LIST OF TABLES Page
Table 3.1: Metadata information for each station………………………………………..36 Table 3.2: Warm temperature records for each city……………………………………..39 Table 4.1: Heat wave event information for each city by threshold……………………..46 Table 4.2: Number and mean duration of heat wave events per decade…………………49 Table 4.3: Probability tests for the number of heat wave events by decade……………..52
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LIST OF FIGURES
Page Figure 2.1: July 19-31, 1999 hourly temperatures (°C) from (a) Chicago O’Hare Airport and (b) St. Louis Lambert International Airport. The solid line represents the average daily temperature and the dashed line represents the minimum temperature for each city. Peak temperatures marked with “H” are the heat wave days (Palecki et al. 2001)……………………………………..18
Figure 2.2: The percent of days below the 10th (dashed lines) or above the 90th (solid lines) percentiles. The daily maximum temperatures are in red and minimum in blue. The smoothed bold lines represent a lowess filter applied to the time series. (Peterson et al. (2008)………………………………..20
Figure 2.3: The change in number of heat waves between the 1950s and the 1980s. Arrows indicate increasing or decreasing change, triangles show stations without heat waves in either decade, and crossed arrows indicate results for close stations (Robinson 2001)……………………………………….21
Figure 2.4: The total number of 1995-like heat wave events observed from 1970- 1999 and projected to occur for time periods in the future under A1fi higher and B1 lower emission scenarios (Hayhoe et al. 2010b)…………………25
Figure 2.5: Chicago mean number of heat waves per year (a) and mean duration (b). The blue diamond is the value computed from the NCEP/NCAR reanalysis data, the black line represents present day model simulation range, and the red line represents the future (2080-2099) model simulation range (Meehl and Tebaldi 2004)…………………………………………………30
Figure 2.6: Projected increase in summer (Jun-Jul-Aug) average temperature (°C) as simulated by the SRES A1fi higher (a) and B1 lower (b) emissions scenarios by the average of 3 AOGCMs for midcentury. Temperature projections are relative to the 1961-1990 average (Hayhoe et al. 2010a)……………………………………………………………………………32
Figure 3.1: The June through September 1981-2010 average high (red) and low (orange) temperatures for each city…………………………………………40
Figure 3.2: Threshold heat wave example……………………………………………….41
Figure 4.1: NCEP/NCAR reanalysis for the 1981 to 2010 June to September surface mean air temperature in Celsius across the Midwest……………………47
Figure 4.2: Consecutive separation of observed high and low temperatures 10
between 1930s heat waves for Columbus (a); Indianapolis (b); Kansas City (c); and St. Louis (d)………………………………………………………..50
Figure 4.3: Heat wave frequency plotted on varying vertical scales for Columbus (a); Indianapolis (b); Kansas City (c); and St. Louis (d)………………………....54
Figure 4.4: Heat wave frequency plotted on varying vertical scales for Columbus (a); Indianapolis (b); Kansas City (c); and St. Louis (d)…………………………55
Figure 4.5: The longest 99% heat waves for Columbus (a); Indianapolis (b); Kansas City (c); and St. Louis (d)………………………………………………..58
Figure 4.6: NOAA 20th century reanalysis composite anomalies based on the 1981 – 2008 climatology from over the Midwest for 700mb specific humidity in kg/kg for 7- 15 July 1936 (a); and 12 July 1936 (b) .……….…………………...59
Figure 4.7: NOAA 20th century reanalysis composite anomalies based on the 1981 – 2008 climatology from over the Midwest for 850mb geopotential height in m for 7-15 July 1936 (a); and 10 July 1936 (b)………………………..……...61
Figure 4.8: NOAA 20th century reanalysis composite mean from over the Midwest for 850mb wind in m/s for 7-15 July 1936 (a); and 10 July 1936 (b)…...... 62
Figure 4.9: Front page from the July 9 1936 Columbus Evening Dispatch………………………………………………………………………….64
Figure 4.10: Cartoon editorial from the July 11 1936 Columbus Evening Dispatch………………………………………………………………………….65
Figure 4.11: NOAA 20th century reanalysis composite anomalies based on the 1981 – 2008 climatology from over the Midwest for 700mb specific humidity in kg/kg for 17- 23 July (a); and 19 July (b)…………………………..67
Figure 4.12: NOAA 20th century reanalysis 2m air temperature in K composite maps from over the Midwest 17-23 July 1934 for the anomaly based on the 1981 – 2008 climatology (a); and mean (b).………………………………....68
Figure 4.13: NOAA 20th century reanalysis composite means from over the Midwest for 500mb geopotential height in m (a); and 2m air temperature in K (b)..………………………………………………………………….……....70
Figure 4.14: Front page from the St. Louis Post Dispatch July 22 1901………………...72
Figure 4.15: St. Louis July 1999 99% heat wave………………………………………..74 11
Figure 4.16: NCEP-NCAR reanalysis composite anomalies based on the 1981 – 2010 climatology from over the Midwest for 700mb specific humidity in kg/kg (a) and 500mb geopotential height in m (b)………………….75
Figure 4.17: NOAA 20th century reanalysis composite anomalies based on the 1981 – 2008 climatology from over the Midwest for the 2m air temperature in Celsius during July and August 1934 (a); and 1936 (b)………………………………………………………………………………...78
Figure 4.18: Historical SOI values during the 1930s. The monthly index derived by the Australian Bureau of Meteorology is plotted in blue, the three month mean is plotted in red, and the dashed lines in black at +8 (La Nina) and -8 (El Nino) represent the magnitude indicative of an ENSO event...... 81
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CHAPTER 1: INTRODUCTION
There is no uniform set of attributes that define a heat wave, but events involving persistent hot extreme temperatures can produce negative impacts on ecosystems, the local economy, and human morbidity and mortality. In 1995 a heat wave killed more then 800 people in the U.S. and the death toll from a long 2003 European summer heat wave is estimated to be over 70,000 (Changnon et al. 1996, Robine et al. 2008). Extreme heat waves in urban areas can be particularly harmful due to the environment in which they occur. There are different ways to describe heat waves, including daytime high and overnight low temperatures, duration, moisture, and relation to the climate variability observed at a given location.
A more representative definition of heat waves involving temperature, synoptic conditions for major events, and research identifying significant heat wave events in the observed records for a given city can improve the existing knowledge on heat waves.
One of the nation’s main climate objectives over the next five years as described by the
National Oceanic and Atmospheric Administration (NOAA) Next Generation Strategic
Plan is formulating, “Assessments of current and future states of the climate system that identify potential impacts and inform science, service, and stewardship decisions (NOAA
2011).” As such, this larger body of work that this Thesis fits within is clearly identified as a national climate science priority. A better understanding of heat waves in Midwest cities from past observations makes impacts from such events more apparent and meaningful to local stakeholders such as urban planners, government officials, and
13 private interests. Relevancy to interdisciplinary topics and professionals in other fields is the nature applied climate research.
The primary focus of this Thesis is to define and identify past heat wave events in the Midwest and investigate the variability of the events within the observations over time. Past heat waves have been identified from surface weather observations during the period 1900-2010. Analysis in this Thesis answers the following questions:
1) What thresholds of high temperature define the most severe heat waves in
Midwest cities? The most extreme temperature thresholds (1% and 5%) are
expected to represent significant heat waves, while lower thresholds would have
too many events.
2) What is the heat wave of record and historical context for the events in the
selected cities? The heat waves of record are expected to be in the earlier 20th
century, likely in the 1930s, as well as the most recent two decades and associated
with interesting societal impacts.
3) How do heat waves in the Midwest relate to large-scale weather and climate
conditions? Features such as a ridge of high pressure and high moisture at mid
levels are expected to be associated with the most severe heat waves.
4) What are some mitigation and response strategies to heat waves? It is expected
that increased urban vegetation coverage and organized city response plans could
be successful in reducing heat wave impact.
A broad goal of this Thesis is to provide the best information possible to inform public and private decision makers and stakeholders at local levels of past information 14 regarding heat waves that can be used as guidance when considering possible future events. Such information is relevant because extreme heat events in urban areas can have high impacts on public health through increasing rates of morbidity and mortality, threatening utility infrastructure, and straining municipal resources. Further, heat waves increase energy consumption through an increase demand on cooling systems. Gaining an understanding of past records offers meaningful comparisons to future events and potential changes in climate extremes.
Knowledge of heat wave occurrence from recent and historical records is necessary for local stakeholders and decision makers to prepare appropriate adaption and mitigation plans for large urban areas so that the multifaceted negative impacts of heat wave events can be best prepared for and reduced. Historical benchmarks are important for learning from past impacts of weather events and for knowledge of current weather and climate conditions. If most parts of the world are entering an era of new climate extremes, then understanding the characteristics of past natural climate variability will give context to otherwise unknown future events. In this Thesis a multi-city, long-term climatological record of heat waves represented by measures of temperature, historical context, and synoptic description has been compiled for the Midwest. This Thesis contributes to previous research by developing a better definition for heat waves and by identifying features and major events in the observed occurrence of heat waves that have already taken place. Such knowledge is beneficial for at least understanding the likely multi-sector impacts of future events in real-time, if not also the prediction and subsequent impact to allow mitigation of these events in advance. 15
CHAPTER 2: LITERATURE REVIEW
Summer heat waves are a relatively common feature during the warm season in the United States. An intense heat wave impacts public health, utility infrastructure, and human activities. The severity and frequency of heat wave events are a representation of large-scale climate patterns in the Midwest and may be related to overall changing climate conditions (Hayhoe et al. 2010a). This Thesis defines what constitutes summer heat waves in the Midwest by identifying the large-scale weather features and thresholds primarily of high temperature but also other atmospheric conditions that characterize the most extreme events. Heat waves are examined by compiling a synoptic climatology from surface observation records for select large urban areas of the Midwest. Past heat waves are identified as events represented by the highest observed temperature and other atmospheric conditions and any patterns or warming signals are investigated.
Summer heat waves and their impacts have a storied history in the Midwest.
Henry (1900) discusses the widespread hot weather in August of 1900 over much of the central and eastern U.S. Church (1913) details the hot summer of 1913, which occurred during a season of drought, and an intense August heat wave accompanied by hot winds that damaged fruit and forest trees in Indiana. The same summer a stretch of high temperatures in Iowa damaged pollen in the corn crop during a critical time and prevented fertilization (Chappel 1913). Articles from the early 1900s generally name periods of very hot weather as hot waves or hot spells (Henry 1900 and Church 1913).
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2.1 Defining Heat Waves
2.1.1 Background
Somewhat surprisingly, heat waves lack a meaningful uniform meteorological definition, perhaps due to the fact that a uniform definition is difficult to determine since the onset of an event can be subtle and does not result in structural damage like other meteorological events. Components to consider that comprise a heat wave include: duration, daytime high and overnight low temperatures, atmospheric moisture, human impacts, and location. Nonetheless, even with these deterministic factors, current heat wave definitions are often vague, ambiguous, and very subjective. As examples, the
American Meteorological Society defines a heat wave as “a period of abnormally and uncomfortably hot and unusually humid weather” (American Meteorological Society
2011), leaving one wondering just how long is a ‘period’ and what is meant by
‘abnormal’ or ‘uncomfortable’.
Robinson (2001) defined a heat wave as an extended period of unusually high atmosphere related heat stress. Likewise, one again must question what is unusual and what is meant by heat stress. Souch and Grimmond (2004) relate heat stress to the temporary modification of lifestyles that may have adverse health consequences, which could include enhanced discomfort or even an increase in mortality, for the affected population. This sense of relativity portrays a heat wave as a social construction, based on interpretation of the event and related impacts.
Two theoretical aspects of heat waves have supported the use of thresholds for heat waves in the past (Robinson 2001). First, a heat wave can be identified based on 17 exceeding fixed absolute values. However, the fixed value selected would really only be relevant to the climate in the given local area. Second, a heat wave can be identified as a deviation from normal, such as a fixed percentile threshold of all observed values. This second method is more reliable for a whole station record, or comparison between stations. Such varying definitions have made comparison of heat wave studies and past events challenging.
2.1.2 Extreme temperature thresholds
Since heat waves lack a rigorous and consistent definition, past research varies in the selection criteria of how past heat waves are determined. Some studies just investigate extreme values in temperature and often within the context of a case study over an individual event. Specifically, Kunkel et al. (1996) investigated the July 1995
Midwest heat wave within a climatic perspective by comparing the most extreme temperatures during the event with other very warm maximum temperatures from past events in the records. The article detailed the heat wave in Chicago by ranking the four- day length of the event with other most intense past four-day heat events. Regarding past observations from other events Kunkel et al. noted the added difficulty station moves and localized influence the lake breeze (from Lake Michigan) provide when comparing past events. The article identified high dewpoint temperatures and the urban heat island as central weather factors relating to the severity of the heat wave, but did not explicitly represent these influences in the analysis.
Palecki et al. (2001) is another study that analyzed maximum temperature observations during two heat waves in the 1990s, making a case study between 18 observations in Chicago and St. Louis. The study compares and contrasts the two events, but does not place the occurrence in context with a historical climate record for the cities.
Since the heat wave was a modern event the details can be characterized with hourly data depicting nuances of the event (Fig. 2.1). The long duration of the July 1999 event, despite a brief cooler interlude, was believed to play a major role in the number of
Figure 2.1: July 19-31, 1999 hourly temperatures (°C) from (a) Chicago O’Hare Airport and (b) St. Louis Lambert International Airport. The solid line represents the average daily temperature and the dashed line represents the minimum temperature for each city. Peak temperatures marked with “H” are the heat wave days (Palecki et al. 2001).
19 fatalities. The St. Louis area observed 36 fatalities and the Chicago area observed 114, with most fatalities occurring on or shortly after the peak heat days of July 29 and 30.
Interestingly, the paper also discusses the influence preparedness and responsiveness of municipalities may have had in differing death tolls between the events for the two cities in addition to the physical nature of the heat wave.
2.1.3 Percentile thresholds
Other studies have employed percentile thresholds on air temperature records in order to define heat waves. Lyon (2009) investigated the possible future behavior of drought and heat waves in South Africa both separately and together. Even though the study was for conditions in South Africa, some important components can be applied to this research. Lyon defined heat waves as when the daily maximum temperature values exceeded the 90th percentile for at least three consecutive days during the Southern
Hemisphere summer months of December, January, and February. Interestingly it was noted that maximum temperatures exceeding the 95th percentile for at least five consecutive days were also investigated, but the scope of classified heat waves were not all that different and therefore not included in the article. Percentiles were used in favor of direct maximum temperature values due to the disparity in temperature experienced at different locations. A uniform temperature threshold for all locations would not be as meaningful as a percentile threshold since the climatology of a given station can vary across a region. Lyon justifies the three-day definition threshold since just a few days of extreme temperature can have major consequences on people, livestock, plant, and other animal life. Kunkel et al. (2010), when studying U.S. summer heat waves identified heat 20 waves events based on a minimum three-day duration period as well, along with a 97.5 percentile threshold during that time.
Peterson et al. (2008) also investigated the warmest temperature days exceeding the 90th percentile for maximum and minimum temperatures, but this time for surface observation data. This study analyzed anywhere from about 800 to over 1200 stations depending on the year across North America, and found an increase in the number of days exceeding the 90th percentile over time, and also noted relative similarities if the 95th percentile threshold were used. Figure 2.2 depicts the percent of daily maximum and minimum days below the 10th percentile or above the 90th percentile. Very clearly an
Figure 2.2: The percent of days below the 10th (dashed lines) or above the 90th (solid lines) percentiles. The daily maximum temperatures are in red and minimum in blue. The smoothed bold lines represent a lowess filter applied to the time series. (Peterson et al. (2008).
21 increase in the number of days exceeding the 90th percentile is shown as nearly equal in magnitude to the decrease in the number of days below the 10th percentile. Therefore, the warming in both extreme hot and cold temperatures is occurring at about the same rate.
Another study (Chen and Konrad 2006) on the conditions characterizing extreme hot and humid events for a region of North Carolina similarly employed a 90th percentile threshold for identifying heat wave events.
2.1.4 Temperature and moisture characterization
Less common is past research that thoroughly examines both temperature and moisture variables as constituting a heat wave. Temperature and humidity are the main
Figure 2.3: The change in number of heat waves between the 1950s and the 1980s. Arrows indicate increasing or decreasing change, triangles show stations without heat waves in either decade, and crossed arrows indicate results for close stations (Robinson 2001). 22 environmental parameters that can impede the human body from cooling by transfer of heat through the skin (Robinson 2001). A heat index, such as what is in use by the
National Weather Service, is an abstract value resulting from a combination of ambient temperature and humidity that approximates realized temperature by the human body, estimating onset of physiological stress due to heat. Robinson bases heat wave frequency and duration analysis for the U.S. on the heat index measurements. An interesting application of Robinson’s study depicts trends of heat wave frequency in the U.S. using the difference in the decadal number of heat waves in the 1950s and 1980 (Fig. 2.3).
Most stations of the Midwest show increasing frequency of heat waves during this time.
When investigating extended heat wave-drought conditions that existed over much of the U.S. during the summers of 1980 and 1988, Lyon and Dole (1995) discussed dynamic forcing and local boundary conditions accounting for the heat waves. The study had a large spatial scope and utilized national gridded data from radiosonde observations in order to analyze the upper level large-scale ridge over the central U.S. during these summers. Lyon and Dole identified the anomalous stationary wave trains as associated with initial hot conditions and drought development, but by the middle of the summer wave activity became very weak. Therefore anomalous stationary waves do not account for later stages of hot weather and drought seasons. Surface and low level moisture parameters like evapotranspiration and horizontal moisture transport values were analyzed in order to examine the effect surface forcing has on the progression of the event. For later stages of hot weather and drought seasons the anomalous surface conditions had greater importance. 23
2.2 Heat Wave Impacts in the Midwest
The Global Climate Change Impacts in the United States (Karl et al. 2009) report is a comprehensive summary of the state of knowledge on climate change science and the present and future impacts of climate change. In this assessment, Karl et al. identify the
Midwest as potentially vulnerable to increased severity and frequency of summer heat waves. Since the Midwest is in the middle of the continent and away from the moderating temperature effects of oceans, the region experiences large seasonal swings in temperature. Even within these strong variations, a noticeable increase in average temperatures has been observed in the Midwest over the past several decades, along with overall increased precipitation (Hayhoe et al. 2010a). The past observed trend and projected warmer average annual temperatures are manifest in the winter by extending the frost-free season and reducing winter ice coverage on the Great Lakes, and in the summer with more frequent heat waves (Hayhoe et al. 2010a).
Also common to the Midwest region is the mix of land use, having both largely agricultural areas and major urban centers. Therefore, as a region, the Midwest is sensitive to the effects of climate change unique to both urban and rural areas. For example, in urban areas a warming climate would shift the seasonal energy demand by decreasing the number of warming degree days in the winter and increasing the number of cooling degree days in the summer. In rural areas, where agricultural interests are more represented, a main concern would be changes in the length of the frost-free season and the ability of crop damaging pests to survive the winters. 24
The past 30 years have included more frequent large heat waves in the Midwest than other times in the past 100 years, with the exception of the 1930s (Kunkel et al.
2008). Particularly dangerous to residents of urban areas is when the nighttime temperatures remain abnormally high. Abnormally high diurnal and nocturnal temperatures characterize the more frequent heat waves of recent decades (Kunkel et al.
2008). There is a lack of previous research combining high temperature and other atmospheric conditions to define heat waves. In addition, many past assessments have only been case studies of individual events and lack a full record.
When discussing an intense heat wave that occurred in the Midwest during July
1995, Changnon et al. (1996) identified many factors at fault for causing the extremely high number of heat related deaths. The factors include power failures, questionable health assessments, inadequate hospital facilities, an aging population, and people unable to properly ventilate their homes. Multi-day weather events like heat waves are more difficult to attribute loss of life since the affected individuals also often suffer from other health problems. Changnon et al. stated that the 1995 event highlights the need for investigation of the societal impacts of abnormally hot weather conditions in American cities since heat related deaths appear to be increasing over time. In fact, their assessment made the assertion that, “The short term extremes of summer weather conditions are the most severe weather events affecting human life in the United States”
(emphasis as used in original manuscript) (Changnon et al. 1996.) Elevated heat stress can aggravate one’s preexisting cardiovascular and respiratory conditions. The portions of the population with preexisting conditions are even more susceptible during heat 25 waves simply as a product of living in a city, resulting in a unique geographic vulnerability for residents.
A study by Borden and Cutter (2008) determined heat to be the leading cause of weather related deaths in the U.S. from 1960-2005. Hayhoe et al. (2010b) also studied the Chicago 1995 heat wave that is estimated to have killed more than 700 people. While some of the deaths may be ascribed to a phenomenon known as “harvesting,” where the event causes the portion of the population facing death in the sort term to be killed sooner
Figure 2.4: The total number of 1995-like heat wave events observed from 1970-1999 and projected to occur for time periods in the future under A1fi higher and B1 lower emission scenarios (Hayhoe et al. 2010b).
26 rather than slightly later, only about a quarter of the deaths were attributed to this.
Emergency department visits were also significantly above average during the heat wave.
Due to the significant human health impact of the event, the frequency of future 1995 like heat waves were investigated. The study defined a 1995-like Chicago heat wave as one that involves at least 7 consecutive days with high temperatures greater than 32°C (90°F) and nighttime low temperatures greater than 21°C (70°F), where at least two of those days observed daytime temperatures over 38°C (100°F) and nighttime low temperatures over 27°C (80°F). Figure 2.4 depicts that towards the end of the century such events are projected to occur once every other year under a low emissions scenario or up to three times a year under a higher emissions scenario (Hayhoe et al. 2010b).
The emissions scenarios referenced in the Hayhoe et al. study were developed by the Intergovernmental Panel on Climate Change (IPCC). The lower emission scenario represents worldwide high economic growth, a population that peaks midcentury then declines, and includes introduction of clean and resource-efficient technologies. The higher emission scenario represents worldwide fossil fuel intensive economic growth as well as a population that peaks midcentury then declines.
Kalkstein and Greene (1997) attempt to address the question of acclimatization to possible future warmer climates and more severe extreme heat events when it comes to mortality rates for large U.S. cities. It is concluded in the study that human induced climate change would increase summer mortality despite the development of acclimatization. In the study an analog city that best represents the future estimated climate regime of the city in question by the global circulation models was selected for 27 each evaluated city. In one of the scenarios, future New York City climate is similar to present St. Louis climate conditions. Therefore the weather/mortality algorithm developed for St. Louis climate is applied to future New York City climate projections to account for acclimatization. Even accounting for acclimatization, Kalkstein and Greene estimate total excess mortality for an average summer season to be from a 70% increase to more than double present day excess summer mortality rates for major U.S. cities.
2.3 Region of Interest: Urban Centers of the Midwest
During the summer increasing heat waves, often associated with reduced air quality, would adversely impact public health in cities. Extreme heat events are often intensified by urban areas due to factors like loss of vegetation and therefore evapotranspiration, dark surfaces that absorb and reradiate heat, and building configurations effective at trapping heat (Oke 1982). A documented result of this convergence of factors is that most heat wave deaths occur in cities (Clarke 1972). The proximity of the Midwest to the Southern Great Plains region of the U.S. often allows the extreme heat conditions that are a hallmark of Great Plains summer climate to spread into the Midwest during heat waves.
Recent climate studies have defined the Midwest as the states bounded by the
Mississippi River to the west and Ohio River to the south to include the states of Illinois,
Indiana, Iowa, Michigan, Minnesota, Missouri, Ohio and Wisconsin (Wuebbles and
Hayhoe 2004). Even though the geographical boundaries of the rivers are often used to define the region, climatic commonalities ensure the region to be an accurate representation as a whole. 28
The major urban centers within the Midwest are Chicago, Detroit, Minneapolis, and St. Louis and respectively have the 3rd, 11th, 16th, and 18th largest metropolitan area populations in the U.S. ranging from 2.8 million to 9.6 million residents (U.S. Census
2010). Other significant urban centers in the region include Cincinnati, Cleveland,
Kansas City, Columbus, and Indianapolis.
This Thesis investigates the occurrence of heat waves in and around St. Louis,
Kansas City, Columbus, and Indianapolis. Surface stations within cities with a longer and more complete observational record and with the fewest past station location changes have been favored. In terms of relative impacts and significance, the largest cites in the region are the most meaningful to include, but other determining factors have been considered. For example, Minneapolis was determined not well suited for this study due to its northerly location and possible less overall extreme heat occurrence. Similarly,
Detroit is also rather far north and near the temperature moderating effects of the Great
Lakes. Chicago would have been an appropriate candidate, however there is a large body of previous heat wave research for the city already due to a particularly deadly 1995 heat wave (Hayhoe et al. 2010b, Karl and Knight 1997, and Palecki et al. 2001).
Major urban areas are the select focus in the study since already warm temperatures during a heat wave are compounded by the urban heat island phenomenon, which is where the air temperatures within a city are warmer than surrounding rural areas. The physical elements of an urban environment, such as asphalt and concrete, have a greater capacity for heat storage than surrounding rural areas and natural vegetation settings (Gallo et al. 1993). During daytime heating the buildings and roads absorb heat 29 energy due to their low surface albedo. Urban structures retain heat energy effectively and there is a large net gain of heat energy. That heat energy is slowly re-emitted through the latter part of the day and nighttime hours into the surrounding urban environment.
Climate change in cities due to overall global temperature increases combined with local climate change caused by urban development and the existing heat island further intensifies urban heat stress (Fruh et al. 2011).
2.4 Future Heat Waves
2.4.1 Background
Many studies have focused on future projections of heat wave events. The frequency and magnitude of current heat wave events already have negative impacts on the socioeconomic state of an affected population, as discussed earlier in (Section 2.2).
The IPCC (2007) has stated it is very likely that heat waves will increase in frequency over most land areas based on projections for the 21st century using SRES scenarios.
Related impacts of this projected trend indentified by the IPCC include reduced crop yields in warm regions, increased danger of wildfire, increased water demand, reduced quality of life and even increased risk of heat-related mortality for people in warm areas without proper housing. Therefore projection of future heat waves is a significant component of current research on the topic.
2.4.2 Future heat wave variability
Meehl and Tebaldi (2004) compiled research that demonstrates projections of more intense, frequent, and longer lasting heat waves by the end of the 21st century. The
30
Figure 2.5: Chicago mean number of heat waves per year (a) and mean duration (b). The blue diamond is the value computed from the NCEP/NCAR reanalysis data, the black line represents present day model simulation range, and the red line represents the future (2080-2099) model simulation range (Meehl and Tebaldi 2004).
study used both National Centers for Environmental Prediction- National Center for
Atmospheric Research (NCEP-NCAR) reanalysis and projections from the NCAR
Parallel Climate Model to assess heat wave occurrence. Two definitions of heat waves already shown to be associated with substantial societal impacts to economics and human health in previous studies were implemented. The first definition identified heat waves 31 by the severity of the three consecutive warmest nights each year. When recent reanalysis was plotted based on this and compared to projected future differences, the areas of the U.S. currently most susceptible to heat waves were shown to be even more susceptible at the end of the century, 2080-2099. The other definition involved exceeding thresholds, which allows for analysis of heat wave duration and frequency.
The two thresholds used were the 97.5 percentile and the 81st percentile. In this case a heat wave was identified when the daily maximum temperature was above a combination of those two percentiles for at least three days. For the point location of Chicago, both the frequency and duration of heat waves were shown to increase from current values to higher levels at the end of the century (Fig. 2.5). The ensemble mean heat wave occurrence per year is projected to increase by 25% over present day values by the end of the 21st century, while heat wave duration is projected to be at the edge or longer than the range of present day heat wave duration.
2.4.3 Future heat wave magnitude
In addition to Meehl and Tebaldi (2004) discussed above, Hayhoe et al. (2010a) also sought to quantify the projections of warmer future temperatures based on both high and low range possible emission scenarios. By midcentury they expect average annual
Midwest temperatures to increase by 3°C (±1°C) under a lower emission scenario and
5°C (±1.2°C) under a higher emission scenario from the historical reference period 1961-
1990 (Fig. 2.6). However even before discussing future regional climate projections the authors reference a list of significant observed trends that are consistent with increasing temperatures. The indicators utilized are temperature, precipitation, stream/lake 32
hydrology, and temperature extremes with examples like first bloom dates earlier in
spring, increasing lake effect snow, increasing heavy rain events, and decrease in Great
Lakes ice cover. In another study, Kunkel et al. (2010) also compared climate model
simulations to projected changes in heat wave characteristics. Under a high range
possible emissions scenario, the annual three-day heat wave temperatures are projected to
Figure 2.6: Projected increase in summer (Jun-Jul-Aug) average temperature (°C) as simulated by the SRES A1fi higher (a) and B1 lower (b) emissions scenarios by the average of 3 AOGCMs for midcentury. Temperature projections are relative to the 1961- 1990 average (Hayhoe et al. 2010a).
33 increase by 3-8°C and the number of heat wave days projected to increase by 30-60 days per year over much of the U.S. The study’s conclusions based on a high emissions scenario indicating a high probability of future heat waves of exceptional severity by the end of the 21st century.
Wuebbles and Hayhoe (2004) introduce the concept of a migrating climate, where
Midwest summers acquire climate characteristics more similar to that of other regions.
As Midwest summers become warmer with more frequent heat waves, the climate will become like that of current climates in the southern Great Plains, where extended heat waves are more often observed. The most extreme hot temperature records from events in the 1930s and 1990s are expected to be much more regular occurring in coming decades by the middle of this century. The article also details the impacts of climate change in the Midwest through discussions about agriculture, ecosystems, water resources, and human health and welfare sectors.
2.5 Conclusions
In order to build on previous research focusing on heat wave events in recent decades outlined in this chapter, heat wave climatologies reaching to the early 20th century are needed. This Thesis contributes to this need by investigating heat wave events going back to 1900. Further, the current study employs a uniform minimum heat wave length and a percentile-based threshold, which will help to move forward with developing a more explicit definition and identifying specific events. To round out the analysis, heat wave events are better understood with an assessment of other atmospheric conditions as well as temperature. 34
The enhancement of heat waves in cities due to the urban heat island makes large urban areas of the Midwest key places to study. Implications of increasing heat wave make further analysis of past frequency and magnitude, and possible changes already manifest in the climatology, paramount.
Further identification of any trends or patterns for specific locations in the observed occurrence of heat waves that have already taken place is also needed. A better understanding of heat waves in Midwest cities from a past observation climatology would provide a better historical representation of past recent events and potential changes in climate extremes. The research detailed in the following chapters is a multi-city, long- term climatological record of heat waves represented by measures of temperature and other atmospheric conditions for the Midwest, which altogether greatly expands knowledge gaps on this threatening meteorological phenomenon.
35
CHAPTER 3: DATA AND METHODS
3.1 Data Employed
3.1.1 Surface stations
Surface weather observations for Columbus, Indianapolis, and St. Louis were accessed through the Applied Climate Information System (ACIS). Surface weather observations for Kansas City were accessed from the Missouri Climate Center. The important meteorological variables included in the analysis were those that relate to air temperature. Both daily maximum and minimum temperatures were significant to examine as well as the regional mean surface temperature anomaly for specific events.
Regional plots of mid level atmospheric moisture and geopotential height for individual events were also investigated.
The temporal scope of the study is 1900 through 2010. The 1930s were a decade of drought and extreme temperatures for much of the nation, so it was important for the climatology to begin prior to this period of time, in order to place it in a broader historical context. Even though national surface observation records are not the most consistent during the earlier timeframe in terms of the oversight of the observations, national coordination of record keeping, and station relocation, the longer history is beneficial; available metadata have been examined to understand past changes in the station sites.
Many early century National Weather Service Cooperative Observer Program (COOP) sites in and around each city were either only active for a short number of years or had large gaps in the records. A single best COOP station for the early 20th century was difficult to locate, but each city did have a combined station COOP dataset that 36 consistently took the records back to at least 1900. The surface data therefore come from two general groups: manual surface observations from the COOP for earlier year records and from the Automated Surface Observing Systems (ASOS) sites once they became implemented at the location.
For Columbus threaded Columbus COOP station and KCMH Port Columbus
International Airport records were used (Table 1). Continuous observations from the
KCMH station used in this study began in 1948 and observations from the Columbus
COOP station used in this study were from 1900-1947. The KCMH station is located seven miles to the east of downtown Columbus at the Port Columbus International
Airport. Since 1948 the specific placement of the station has been at three different spots, but all located in the immediate vicinity of the airport. The metadata location given for the COOP station is in current downtown Columbus.
For Indianapolis threaded Indianapolis Monument City COOP station and KIND
Indianapolis International Airport records were used (Table 1). Continuous observations
Table 3.1: Metadata information for each station.
37 from the KIND station used in this study began in 1943 and observations from the
Indianapolis Monument City COOP station used in this study were from 1900-1943. The station is located seven miles to the southwest of downtown Indianapolis at the airport.
Since 1943 the specific placement of the station has been at three different spots, but all located in the immediate vicinity of the airport. The metadata location given for the station is in current downtown Indianapolis.
For Kansas City threaded Downtown Airport COOP station and KMCI Kansas
City International Airport records were used (Table 1). Continuous observations from the KMCI station used in this study began in 1973. The station is located 19 miles to the northwest of downtown Kansas City at the airport. Since 1973 the specific placement of the station has been at three different spots, but all located in the immediate vicinity of the airport. Observations from the Downtown Airport COOP station used in this study were from 1900-1972. The metadata location given for the station is immediately north of current downtown Kansas City at the Downtown Airport. The elevation change between the Kansas City COOP and KMCI sites is significant and may have some influence on the observations not corrected for in the study.
For St. Louis threaded St. Louis Eads Bridge COOP station and KSTL St. Louis
Lambert International Airport records were used (Table 1). Continuous observations from the KSTL station used in this study began in 1930 and observations from the St.
Louis Eads Bridge COOP station used in this study were from 1900-1930. The station is located 14 miles to the northwest of downtown St. Louis at the airport. Since 1930 the specific placement of the station has been at three different spots, but all located in the 38 immediate vicinity of the airport. The Metadata location given for the station is in current downtown St. Louis at Eads Bridge over the Mississippi River. As is often the case for combined station COOP records, the exact location the observations were measured for all four cities may have changed location and been unrecorded or lost in the early 20th century, but is accepted by NCDC as being in close range of the current coordinates listed in Table 1.
Due to urban heat island effects, changes in the size of the city and built environment have had impacts on the meteorological observations. Davey and Pielke
(2005) discuss that near-surface observation stations should be as representative of the free-air conditions over as large of an area as possible since microclimate exposures can have an impact on the assessment of long-term temperature trends. Even sites with a long period of record, low percentage of missing data, and few station moves can have influences from microclimate exposure in the overall records. This is a limitation of the study and introduces a bias that is not quantifiable, but likely does not effect my total number of events over the 110 year period. Since microclimate influences are unlikely to change the frequency and number of extreme events, this was not pursued further.
3.1.2 Station temperatures
After identifying the most consistent COOP site for each city for the early 20th century records, the two data sources (COOP and ASOS) were combined for records since 1900. All cold season dates were removed, initially leaving the warm season, May through October, for analysis. 39
The differences in the daily temperature between the two stations were assessed
by taking the average of all high or low temperatures from overlapping years between the
two data sets for each city. Due to the inherent spatial variability of temperature and
early century station site moves, the observations from each data set were accepted as is
and an attempt for a broad brushed adjustment was not made. Since the records are from
over 110 years, the hot temperature thresholds are true extremes over the time period and
not bias toward a particular year.
In order to represent the typical temperatures for each city during the months of
the study, Figs. 3.1a-d depict the June through September 1981-2010 average minimum
and maximum temperatures for the cities. Displayed in Table 3.2 are the record highs
and highest record lows for each city from the entire study period, 1900-2010.
3.1.3 Historical records
Supplemental historical research was conducted for some of the notable heat
wave events. Old newspaper articles were located in the periodical and microfilm
department of the St. Louis City Public Library regarding historical oppressive heat
waves. The news articles accessed were from the still active St. Louis Post-Dispatch in
Table 3.2: Warm temperature records for each city.
40
Figure 3.1 a-d: The June through September 1981-2010 average high (red) and low (orange) temperatures for each city.
1901, the 1930s, and 1999. Newspaper articles from the no longer in print Columbus
Evening Dispatch on microfilm at the Ohio University Alden Library were researched regarding a 1936 event. Lastly, articles from the New York Times were accessed through
Ohio University electronic resource for 1901, 1934, and 1936 events.
3.1.4 Reanalysis data
In order to gain a more spatially congruent understanding of how significant heat wave events at the discrete surface observation sites fit within larger scale atmospheric conditions, model reanalysis was utilized. This Thesis used both National Centers for 41
Environmental Prediction—National Center for Atmospheric Research (NCEP-NCAR)
reanalysis and NOAA 20th century reanalysis to investigate other atmospheric parameters
associated with heat wave events accessed online through the NOAA Earth System
Research Laboratory (ESRL), Physical Science Division.
The NOAA 20th century reanalysis uses historical observations of surface and sea
level pressure to produce an estimate of the state of other atmospheric parameters both at
the surface and aloft (ESRL 2012a). The 20th century reanalysis is especially useful for
the investigating early century events, such as in this Thesis, and includes observations
Figure 3.2: Threshold heat wave example.
42 dating back to 1871. The NCEP-NCAR reanalysis uses more integrated observations including station data, satellite observations, and information from weather balloons to reproduce the complete atmospheric state (ESRL 2012b). The NCEP-NCAR reanalysis dataset begins in 1948 and is used in this Thesis for further assessment of a modern heat wave event.
3.2 Methods Employed
3.2.1 Persistence and percentile threshold
A primary purpose of the present study was to investigate the number and length of past heat waves and the changes manifest in the extreme, top 5% (95th percentile event), 2.5% (97.5 percentile event), and 1% (99th percentile event), thresholds over time.
Even though the top 1% of extreme temperature events represent the most severe heat waves most explicitly, the top 2.5% and 5% analysis were included for comparison, to better represent the frequency of events, sample size, and robustness of statistical measures. A persistence threshold was included to identify heat wave events, since one hot record alone does not signify a heat wave. The threshold employed follows previous research by exceeding three consecutive days or nights of the threshold as signifying a heat wave (Meehl and Tebaldi 2004, Lyon 2009, and Robinson 2001). Site specific thresholds helped identify the outlier events that constitute heat waves unique for each location.
Heat wave length was defined as a period of three consecutive high or low temperatures at or above the given threshold since even that short of a period of extreme temperature can have major consequences on people, livestock, plant, and other animal 43 life (Lyon 2009). Figure 3.2 demonstrates the selection of heat wave events by the three consecutive high or low temperature threshold definition. Displayed are 12 days from St.
Louis in July 1999 where three 95% threshold heat wave events (blue and green) and one
99% event (green) occurred. The 99% and 95% thresholds were selected to show top 1% and 5% extreme heat wave events. Consecutive heat wave events that were only separated by one high or low temperature reading a single degree below threshold were combined to make one heat wave event.
After completing the heat wave analysis at 99% and 95% there were no heat wave events identified in May or October. Therefore those months were removed from the climatology and the thresholds were calculated only using annual observations from June through September. The month of September was included, as opposed to just the June-
July-August summer season because heat wave events at threshold were present. The observation dates were formatted consistently and the observations were quality assured by checking for outliers, zeros, or other mistakes.
Also investigated for was the 90% threshold, but so many events were being produced that it was determined the threshold was too low for identifying extreme heat events. Therefore 90% was not completed for the cities in the study. Another method of identifying percentile threshold by day was considered, but this process resulted in falsely high percentile days during the cooler parts of the summer in early June and late
September and was determined irrelevant for identifying discrete extreme heat events.
Having site specific thresholds helped identify the outlier observations that constitute 44 heat waves. A universal definition would not have been as appropriate since that would have included influence from outliers in one city on the thresholds of another city.
3.2.2 Event statistics
In order to investigate the occurrence of heat wave events in each decade, a two- tailed t-test was used. The t-test compares the mean between two samples. The t-test used is as follows:
(1)
where and are the sample means, and are the hypothesized population means, is the pooled sample standard deviation, and n and m are the sample size of each group. The pooled sample standard deviation is defined as:
(2)
If the observed variance of each dataset is comparable, then a homoscedastic two-sample equal variance test is used. If the observed variance of each dataset is not comparable, then a heteroscedastic two-sample unequal variance test is used. Both of these kind of t- tests are for unpaired datasets, so the degrees of freedom in (1) is . If the variance is unequal, then the degree of freedom portion is adjusted for the difference. The resulting p-value from the t-test determines whether the two means are comparable. 45
An F-test is based on a continuous probability distribution, or F-distribution. The
F-test is used for the analysis of variance since it is sensitive to non-normality. The F-test is the ratio of the first sample variance to the second sample variance and is used approximately as follows:
(3)
where s1 and s2 are the variance, or standard deviation squared, of each sample. The resulting values indicate the two-tailed probability that the variances of the two datasets are significantly different. For this Thesis, if the resulting value is less that .1, then the variances are significantly different and the heteroscedastic t-test listed above is used.
46
CHAPTER 4: RESULTS AND DISCUSSION
The threshold method of identifying heat waves allows for events over the entire period of study for each city to be compared. The frequency of heat wave observations and the number of heat wave events are examined. Major heat wave events are represented by relevant atmospheric conditions and the historical context in which they occur. The 1930s central U.S. climate is investigated further since the most frequent heat waves on record occurred during that decade. Lastly, urban mitigation and response techniques for heat waves are discussed.
Table 4.1: Heat wave event information for each city by threshold.
47
4.1 Heat Wave Events
Information on the temperature thresholds, total number of events, longest events, and mean duration is presented in Table 4.1. Kansas City has the highest temperature thresholds and Columbus has the lowest, which follows the climatology for the region.
Figure 4.1 depicts the mean surface air temperature for Midwest during the months of
June, July, August, and September 1981-2010 in order to represent the 30-year climatology for the warm season months of study. The area around Kansas City and St.
Figure 4.1: NCEP/NCAR reanalysis for the 1981 to 2010 June to September surface mean air temperature in Celsius across the Midwest.
48
Louis observes warmer mean surface temperatures than further east near Indianapolis and
Columbus. Therefore it follows that the higher temperature thresholds are for Kansas
City and St. Louis towards the west, and lower for Indianapolis and Columbus towards the east. The longest and mean duration counts for heat waves are the number of consecutive high and low temperatures at or above the given threshold. For example, a heat wave lasting 14 observations is 7 days/nights long. The number and mean duration of events per decade are displayed in Table 4.2.
Even though St. Louis has 33 events at the 99% threshold over the 110 years, 13 of them were in the 1930s, which is a little over one third of all the events (Table 4.1 and
Table 4.2). Eight of the events were in the 1980s, where 1980 was a very hot summer with brief separation between heat waves. A similar pattern is noticeable at the 95% threshold for St. Louis. Out of 144 events total, 29 were in the 1930s, 22 in the 1980s and 12 were just in the years 1952-1954.
Similar distributions of the heat waves events are observed for the other cities.
Out of 18 total events at the 99% threshold in Columbus, nine were in the 1930s and there were none from 1945-1987 (Table 4.1 and Table 4.2). At the 95% threshold for
Columbus, out of 155 events 29 were in the 1930s, 25 in the 1940s, and 20 were in the
1990s. For Kansas City out of 19 events at the 99% threshold, 12 were in the 1930s and there has been only one 99% event since 1954. At the 95% threshold in Kansas City out of 152 events there were 50 in the 1930s, 22 in the 1940s, and 23 in the 1950s.
Individual observations of both high and low temperatures at threshold still occur each summer over recent decades, but do not as often consecutively to form heat wave events. 49
Table 4.2: Number and mean duration of heat wave events per decade.
50
a
b
c
d
Figure 4.2: Consecutive separation of observed high and low temperatures between 1930s heat waves for Columbus (a); Indianapolis (b); Kansas City (c); and St. Louis (d). 51
For Indianapolis out of 31 events at the 99% threshold 13 were in the 1930s. At the 95% threshold there were 144 events with 34 in the 1930s and 18 in the 1910s. The longest heat wave at each threshold for Indianapolis overlapped during the same time in
July 1936. The 155 events for Columbus at 95% are the most out of all the cities. This is interesting because the number of observations at each threshold is fixed, and the greatest proportion of the observations consecutively to form heat waves is in Columbus.
Likewise Indianapolis and St. Louis have a greater proportion of heat waves than
Columbus and Kansas City at 99%.
The summers of 1934 and 1936 were very hot for all cities with only brief separation between the heat wave events. Figures 4.2a-d plot the number of consecutive high and low observations separating 99% heat wave events during the 1930s for each city. For example, a separation count of 10 would be a break in the heat wave threshold for about five days. There must be two or more heat waves in a summer to be a separation count. For example, Columbus observed four heat waves in 1936, so three periods of separation are represented on the plot and 1934 had three heat waves, so two periods of separation are represented (Fig. 4.2a). The summers with only one heat wave do not have a separation count.
For some decades the number of heat waves observed are very unique. Table 4.3 lists the p-values, or the probability that the mean recorded heat waves in each decade is equal to the mean over the period of study, under the t-test column. The F-test values compare how different the variance is between each decade and the overall period of study. For this study, F-test values less than .1 imply there is a less than 10% chance the 52 two sample variances are equal. Thus, a two-sample unequal variance t-test is necessary when the F-test values are less than .1. For F-test values greater than .1 a homoscedastic t-test is used, since both number sets are of comparable variance.
Table 4.3: Probability tests for the number of heat wave events by decade.
53
The red values in Table 4.3 indicate that the mean number of heat waves in a decade is very unique, when compared to the mean over the 110-year period of study.
Some decades have a low probability due to many events observed and others due to very few events. The 1960s and 1970s were unique for all cities (except the 1970s for
Indianapolis), due to only a few events occurring in the decade. The 1930s was also unique for nearly all cities due to a high number of events and will be discussed later in more detail. All of the heat wave event counts in the decades with a p-value colored in red are significantly more or less heat waves than would be expected if the number of heat waves were evenly distributed over the time period.
4.2 Heat Wave Frequency
The heat wave frequency plotted on varying vertical scales is depicted in Figs.
4.3a-d for Columbus, Indianapolis, Kansas City, and St. Louis respectively over the 110- year period of study. Plotted in red (orange) are the number of heat wave highs and lows each year based on the 99% (95%) temperature thresholds. The black line on the charts represents the 11-year running mean of the 95% heat wave high and low temperatures.
Plotting the moving average smoothes out high and low points for individual years in order to better show decadal and other low-frequency variability. All cities depict the exceptionally numerous heat wave observations of the 1930s, as well as frequent heat waves in 1901 and the 1910s. Another relative maximum is present using the 95% threshold in the 11-year moving average line for Indianapolis, Kansas City, and St. Louis in the early 1950s (Figs. 4.3b-d), suggesting that multiple heat waves commonly occurred in consecutive years in this decade. 54
a
b
c
d
Figure 4.3: Heat wave frequency plotted on varying vertical scales for Columbus (a); Indianapolis (b); Kansas City (c); and St. Louis (d).
55
a
b
c
d
Figure 4.4: Heat wave frequency plotted on varying vertical scales for Columbus (a),; Indianapolis (b); Kansas City (c); and St. Louis (d).
56
The past 30 years as a whole for Columbus and St. Louis appear to have included more numerous heat wave days than other times since the 1930s (Figs. 4.3a and d).
However, that same feature is not as apparent over recent decades for Indianapolis and
Kansas City (Figs. 4.3b and c). Since 1980 at the 95% threshold Columbus has observed
45 events and St. Louis 55 events, with 23 of the events coinciding for both cities. For
Kansas City and Indianapolis since 1980, there are still several days each summer with temperatures at or above the 95% threshold temperatures for both high and low for temperatures, but they do not occur as often consecutively to produce heat wave events as defined in Chapter 3.
Figures 4.4a-d depict the heat wave frequency plotted on varying vertical scales the cities with red (yellow) being the number of heat wave highs and lows each year based on the 99% (97.5%) temperature thresholds. The black line on Figs. 4.4a-d represents the 11-year running mean of the 97.5% heat wave high and low temperatures.
At this slightly higher threshold of 97.5%, a non-extreme heat wave regime is observed since the 1950s (Figs. 4.4b and c). As depicted in Fig. 4.4c, Kansas City has the lowest frequency over recent decades, perhaps due to the exceptionally warm years in the early
20th century resulting in a slightly higher threshold temperature over the period of study.
The other maxima in the 1930s and 1910s are still slightly represented by observations at the 95%, but with a fewer number of heat wave highs and lows due to the higher threshold level (Figs. 4.4a-d).
57
4.3 Characterization of Major Events
Figures 4.5a-d depict the most intense heat wave on record since 1900 for
Columbus, Indianapolis, Kansas City, and St. Louis respectively in terms of length of consecutive high and low temperatures at the 99% threshold. The red bars are daily high temperatures and the orange bars are daily low temperatures. Only observations included at or above the 99% threshold (Table 4.1) are plotted. The only city with the longest 99% heat wave not in the 1930s is St. Louis with the event in 1901. In fact, St. Louis observed the most 99% in the 1930s (Table 4.2) and the most heat wave high and low observations for a single year was in 1936 (Fig. 4.3d), but none matched or exceeded the nine consecutive high or low observations in 1901, which was the longest. The following subsections discuss each event and provide historical context.
4.3.1 July 1936
The 99% longest heat waves for Columbus and Indianapolis covered nearly the same time period in July 1936. The Columbus event shown in Fig. 4.5a contains a high temperature of 106°F on 14 July 1936, which is tied for the all-time highest on record
(with July 21, 1934). The low temperatures on 9 and 10 July 1936 are tied with several other dates as the third warmest on record over the 110-year period of study. There have been only three 99% events in Columbus since 1944, with the most recent lasting two and a half days in 1999. The Indianapolis event depicted in Fig. 4.5b also includes a high temperature of 106°F on 14 July 1936, which is tied for the highest on record with 22
July 1901 and 21 July 1934. The Indianapolis low temperature on 10 July 1936 of 82°F is the all time warmest on record tied with four other dates. There have been seven 99% 58
a
b
c
d
Figure 4.5: The longest 99% heat waves for Columbus (a); Indianapolis (b); Kansas City (c); and St. Louis (d).
59
a
b
Figure 4.6: NOAA 20th century reanalysis composite anomalies based on the 1981 – 2008 climatology from over the Midwest for 700mb specific humidity in kg/kg for 7- 15 July 1936 (a); and 12 July 1936 (b).
60 events in Indianapolis since 1942 and all have been short with only three or four consecutive high and low observations at threshold. Much of July and August 1936 were during 95% heat waves for Indianapolis and Columbus as well.
The NOAA 20th century reanalysis plots for 700mb specific humidity (the mass of water vapor per mass of air containing the water vapor) during the July 1936 event are presented in Fig. 4.6a and b. Figure 4.6a depicts the composite anomaly from 7-15 July and Fig. 4.6b is the composite anomaly from just 12 July during the heat wave. The
700mb plots identify anomalously moist conditions at mid-levels of the atmosphere over much of the Midwest. Moist atmospheric conditions aloft are often key for the warm minimum temperatures at night observed during heat waves. More moisture (i.e. water vapor) aloft at low levels decreases the efficiency of radiational cooling at night. The
700mb moisture increases the nighttime downward longwave radiation flux and provides an insulating effect on temperatures.
The NOAA 20th century reanalysis plots for 850mb geopotential height (elevation above mean sea level adjusted for variations in gravity) during the July 1936 event are presented in Fig. 4.7a and b. Figure 4.7a depicts the composite anomaly from 7-15 July and Fig. 4.7b is the composite anomaly from 10 July during the heat wave. The 850mb plots identify anomalously high geopotential height centered over the Midwest, which is indicative of a strong high pressure in place and the warm thermal nature of the lower atmosphere during the event. High pressure also likely resulted in clearer skies allowing for maximum radiation. The ridge was strongest and centered over Indianapolis and
61
a
b
Figure 4.7: NOAA 20th century reanalysis composite anomalies based on the 1981 – 2008 climatology from over the Midwest for 850mb geopotential height in m for 7-15 July 1936 (a); and 10 July 1936 (b).
62
a
b
Figure 4.8: NOAA 20th century reanalysis composite mean from over the Midwest for 850mb wind in m/s for 7-15 July 1936 (a); and 10 July 1936 (b).
63
Columbus 10 July (Fig. 4.7b). Such dominant low-level conditions can partly account for the long duration of the July 1936 event.
Reanalysis plots for 850mb vector wind during the July 1936 event are shown in
Fig. 4.8a and b. Figure 4.8a depicts the composite mean from 7-15 July and Fig. 4.8b is the composite mean from 10 July during the heat wave. Generally calm winds are present coinciding with the 850mb ridge. The light wind on the periphery of the ridge again reinforces the persistent nature of the conditions.
Newspaper articles from the New York Times during the highlighted Columbus and Indianapolis heat waves (Fig. 4.5a and b) in July 1936 detail a drought nearly nationwide that summer, urban water shortages, wildfires, grasshopper plagues, farm loss, and high grain prices due to a poor or threatened crop from the harsh conditions (8,
11, and 12 July 1936). The extreme heat in many parts of the country exacerbated already severe drought conditions prompting President Roosevelt to take direct leadership of federal drought relief through his appointed Drought Committee and by expanding
Works Progress Administration projects (New York Times, 7 July 1936). The large size and scope of hot conditions from the Plains to New England also made headlines (New
York Times, 10 and 11 July 1936). The long lasting extreme drought and heat was already being compared as nearly equal or worse than the summer just two years prior in
1934. Newspaper columns about the heat ended with long lists of deaths and
“prostrations,” or heat exhaustion, due to the hot weather (New York Times, 10, 13 and 15
July 1936). 64
The New York Times also reported the July 1936 heat wave as the worst natural disaster of the year, despite harsh cold, a major tornado, and floods that killed many people earlier in the year (12 July 1936). St. Louis and Kansas City also observed extreme heat waves during this time, since hot weather affected the majority of the U.S. east of the Rocky Mountains. At the end of the extreme heat wave on July 15, as observed in Indianapolis and Columbus, the nationwide death count due to heat over the previous two weeks was at 3,848 and the estimated damage from the related drought to crops, livestock, and dairy was believed to be producing a $1 billion disaster (New York
Times, 15 and 16 July 1936). The $1 billion assessment from 1936 would be over 16.5 billion in 2012, based solely on the U.S. Consumer Price Index inflation adjustment.
Frequently mentioned within news of the heat and drought conditions were updates from the Dust Bowl region in the High Plains, which had been experiencing extreme soil erosion since the early 1930s and was seen as the region suffering the worst drought impact based on livestock, crop and farm loss (New York Times, 14 July 1936).
Figure 4.9: Front page headline from the July 9 1936 Columbus Evening Dispatch.
65
Figure 4.10: Cartoon editorial from the July 11 1936 Columbus Evening Dispatch.
The Columbus Evening Dispatch reported during July 1936 that the mayor requested city residents to conserve water and regular doses of table salt was promoted in preventing heat prostration (Columbus Evening Dispatch, 8 and 9 July 1936). One of the
Columbus Evening Dispatch front-page headlines from 9 July 1936 during the heat wave is presented in Fig. 4.9. Several occurrences of local “road blasts” were detailed, which was when concrete and asphalt roads buckle or explode at the hottest past of the day 66
(Columbus Evening Dispatch, 10 July 1936). Interestingly, most news columns beginning on the front page were continued directly on the obituary page of the paper, again ending with the latest list of deaths and prostrations (Columbus Evening Dispatch,
8 July 1936). Perhaps the cartoon editorial portion of the newspaper best got the point across to readers as the forecasts from Weather Bureau did not provide hope for relief
(Fig 4.10).
4.3.2 July 1934
The July 1934 Kansas City event shown in Fig 4.5c contains a high temperature of 109°F on 19 and 20 July 1934, which is tied for the fifth highest on record with several other dates. The Kansas City low temperature on 21 July 1936 of 85°F is tied with several other dates as the third warmest on record. Additionally, three fourths of the days from 23 June through 11 Augusy 1934 were part of 95% heat waves. Since 1945 Kansas
City has observed only one 99% event, which lasted two and a half days in 1980.
The NOAA 20th century reanalysis plots for 700mb specific humidity during the
July 1934 event are presented in Fig. 4.11a and b. Figure 4.11a illustrates the composite anomaly from 17-23 July and Fig. 4.11b is the composite anomaly from just 19 July during the heat wave. Both the 700mb plots from during the entire event and a single day in the middle depict very moist anomalous conditions at mid-levels of the atmosphere over Kansas City, which can lead to warm minimum temperatures at night as first mentioned in 4.3.1.
67
a
b
Figure 4.11: NOAA 20th century reanalysis composite anomalies based on the 1981 – 2008 climatology from over the Midwest for 700mb specific humidity in kg/kg for 17- 23 July (a); and 19 July (b).
68
a
b
Figure 4.12: NOAA 20th century reanalysis 2m air temperature in K composite maps from over the Midwest 17-23 July 1934 for the anomaly based on the 1981 – 2008 climatology (a); and mean (b).
69
The reanalysis plots for 2m air temperature during the July 1934 event are shown in Fig. 4.12a and b. The composite anomaly for temperature is represented in in Fig.
4.12a and the mean temperature in Fig. 4.12b. Strong warm temperature anomalies from
Kansas City northward across the central U.S. represent the widespread heat across the central U.S. (Fig. 4.12a). Indeed the warmest mean temperatures during the event are centered almost directly over Kansas City as well (Fig. 4.12b). St. Louis, also near the warmest temperatures, observed a 99% threshold heat wave during part of the same time period as well. Indianapolis and Columbus observed 95% threshold heat waves during part of the period, but not 99% threshold.
The drought and heat wave of July 1934 were also national news, as reported in the New York Times. During the week before 25 July the paper reported more than 1,200 people killed nationwide, with the most being in Missouri at 312 (New York Times, 23 and 26 July 1934). In Kansas City alone 92 people died. The damage in Missouri was described as vast due to the drought effects compounded by extreme temperatures, with hay and corn crops most harmed by the heat (New York Times, 23 July 1934). Dead livestock in Missouri and Kansas numbered in the thousands and the extreme heat hastened the need for a massive drive of 200,000 cattle in Kansas to more reliable water sources (New York Times, 24 July 1934).
4.3.3 July 1901
The St. Louis heat wave presented in Fig. 4.5d occurred during an exceptionally hot summer in 1901 for St. Louis where 29 days from the end of June to the end of July were part of four only slightly separated heat wave events at the 95% threshold. The low 70
a
b
Figure 4.13: NOAA 20th century reanalysis composite means from over the Midwest for 500mb geopotential height in m (a); and 2m air temperature in K (b).
71 temperature on 24 July 1901 of 86°F is the warmest of any day on record for St. Louis.
The high temperature readings of 107°F are tied with other dates for the sixth warmest all time. St. Louis has observed more recent 99% heat waves than the other cities, with eight during the 1980s and two more since then.
The NOAA 20th century reanalysis plots for 500mb mean geopotential height and mean 2m air temperature during the July 1901 event are presented in Fig. 4.13a and b.
The 500mb plot depicts very high geopotential heights of more than 590dm, which is representative of a large ridge of high pressure over the central U.S. during the event
(Fig. 4.13a). Such a large summertime synoptic scale ridge is generally persistent and accompanied by stagnant air at the surface under strong subsidence. Such widespread sinking air leads to compressional warming at low levels. A subsidence inversion that often forms under the ridge acts as a stable layer in the atmosphere and is also effective at trapping any moisture present and heat at low levels by preventing mixing aloft. The warmest mean 2m temperatures are centered under the ridge and over St. Louis as well, which corresponds with the extreme heat wave observed (4.13b).
During July 1910 the St. Louis Post-Dispatch (22 and 24 July 1901) reported the
“torrid” conditions that summer with articles detailing news of 101 people in the city dying from the heat during July and a proclamation issued by the Missouri Governor for citizens to pray for relief. Near the end of the heat wave the New York Times reported that public officials and private businesses in the city were taking actions by instating an early close of business as the heat continued, in part due to news that 40 of the deaths directly attributed to the heat occurred in just a 24 hour period (25 July 1901). The article 72
Figure 4.14: Front page from the St. Louis Post Dispatch July 22 1901.
73 also dramatically described the city’s environment by saying, “Persons dropped on the sidewalks and horses fell to the pavement, unable to move” (New York Times, 24 July
1901).
An interview was published with “inventor” Alexander Graham Bell on a potential device to dispel heat from homes in the summer, similar to the function of a furnace in providing heat during the winter (St. Louis Post-Dispatch, 18 July 1901).
Another article discussed that the city’s more refined restaurants were breaking with tradition and allowing men to dine without their coats (St. Louis Post-Dispatch, 4 July
1901). The paper reported that the 106°F temperature on 21 July was hot enough to set the new record at the time, but this was only to be tied or exceeded the next three days
(St. Louis Post-Dispatch, 22 July 1901). Long lists of the dead with a short description of each case at the end of the news articles were common during the event as well, with one of the notes about a 21 year old man that fell from his second floor window sill to his death while falling asleep there during the night and another man that broke his arms after falling out of a window for the same reason (St. Louis Post-Dispatch, 23 July 1901).
Figure 4.14 includes the front page of the St. Louis Post-Dispatch from Monday evening
22 July during the heat wave, where one of the top stories featured a sketch of a city judge holding court without his robes.
4.4.4 July 1999
One of the more recent extreme heat waves occurred in St. Louis during late July
1999. The 99% duration of the event is presented in Fig. 4.15. The red bars are daily high temperatures and the orange bars are daily low temperatures. Only observations 74
Figure: 4.15: St. Louis July 1999 99% heat wave.
included at or above the 99% threshold (Table 4.1) are plotted. The event in Fig. 4.15 was the most extreme portion of a hot stretch of weather in St. Louis immediately following two 95% events from 23-24 July and 25-27 July. July 1999 represents one of the most significant heat waves for the cities of interest over recent decades.
The NCEP-NCAR reanalysis plots for 500mb geopotential height and specific humidity during the July 1999 event are presented in Fig. 4.16a and b. The 850mb plot depicts very moist anomalous conditions at low-levels of the atmosphere over St. Louis, which can lead to warm minimum temperatures at night (Fig. 4.16a). The 500mb plot depicts anomalously high geopotential height centered near St. Louis, which is indicative of a ridge of high pressure over the central U.S. during the event (Fig. 4.16b).
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a
b
Figure 4.16: NCEP-NCAR reanalysis composite anomalies based on the 1981 – 2010 climatology from over the Midwest for 700mb specific humidity in kg/kg (a) and 500mb geopotential height in m (b).
76
The extended heat caused pavement to buckle in spots along interstate highways through the city (St. Louis Post-Dispatch, 27 and 30 July 1999). Most of the deaths listed in the paper were from people at homes without air conditioning or with the units not in use. Related impacts reported were the regional electric utility operating at capacity and air quality in the city exceeding federal standards for ozone and other low-level pollutants. Water main breaks for the St. Louis water utility were about double the average as drying soil could shift and break lines (St. Louis Post-Dispatch, 28 July 1999).
The smaller water utilities outside the city were restricting use for nonessential purposes, such as yard watering, since higher use during hot weather reduces needed water pressure. Extreme heat had associated impacts on farming as well as damage to crops approaching maturity, hogs stop putting on weight, and milk production from dairy cows drops (St. Louis Post-Dispatch, 29 July 1999).
The deputy St. Louis medical examiner cited the brick buildings with black tar- paper roofs as a specific local concern (St. Louis Post-Dispatch, 28 July 1999). The vast majority of people dying from the heat due to hyperthermia were the elderly. Public health officials for the city were reported as frustrated that reports of additional heat deaths come to the office daily despite measures to alleviate impacts such as high publicity of the deadly heat, public cooling centers, and door-to-door checks as part of the city’s Operation Weather Survival Plan (St. Louis Post-Dispatch, 29 July 1999).
Palecki et al. (2001) wrote a case study on the July 1999 heat wave discussing that the severe impacts for St. Louis could have been worse if not for effective municipal heat wave response. There were 309 heat related deaths across the central and eastern U.S. 77 during the event in late July and 36 in St. Louis. The average age of the people who died in St. Louis was 74. The article identified high municipal preparedness in 1999 due to awareness from the large death toll in Chicago’s exceptional 1995 heat wave and previous experience in coordinating heat response from hot weather events in the 1980s in St. Louis. The 1995 heat wave that impacted Chicago also caused 27 deaths St. Louis.
The 1999 total in St. Louis was slightly higher most likely due to the warmer conditions of the 1999 heat wave. During the 1999 event the state of Missouri issued a hot weather health statement based on the National Weather Service forecast, which had an accompanying emergency declaration once heat related mortality was observed. This also prompted the City of St. Louis to open cooling centers and the mayor to send out 220 city employees to residences checking on the elderly. Palecki et al. say the death toll in
St. Louis would likely have been higher without the state and city effective response.
Additionally, city officials had meetings after the event to assess the response and improve the plan for future years.
4.4 1930s Heat Waves
The 1930s had numerous heat waves for each city with the most events of all the decades during the period of study at every threshold. Furthermore, within this prolific heat wave era the summers of 1934 and 1936 stand out as especially hot. The strong warm surface temperature anomalies across the Midwest from the NOAA 20th century reanalysis plots during July and August of 1934 and 1936, the months when most of the events occurred, are depicted in Fig. 17a and b. The eastern extent of the warm temperature was further into Ohio in 1936 (Fig. 17b). Indeed the summer of 1936 was 78
Figure 4.17: NOAA 20th century reanalysis composite anomalies based on the 1981 – 2008 climatology from over the Midwest for the 2m air temperature in Celsius during July and August 1934 (a); and 1936 (b).
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the worst of the two, with the most 99% heat wave high and low temperatures observations in the period of study for each city.
The dominant climate event across the central U.S. during the 1930s and related to the summertime warming is commonly referred to today as the Dust Bowl drought
(Seager et al. 2008, Fye et al. 2004, and White and Gershunov 2008). However, the Dust
Bowl event specifically refers to the extreme soil erosion on the High Plains since that is where the dust originated. The Dust Bowl term was coined on April 15, 1935 in an
Associated Press article by Robert Geiger after he was overcome near Boise City, OK the day before by the Black Sunday Dust Storm (National Weather Service Norman OK, cited 2012). During the decades leading up to the Dust Bowl, settlers in the High Plains plowed through the native prairie grasses to plant wheat (McManus 2004). Tractors and better plows came into common use and since the grasslands were already so open, plowing more and more land for making more money as wheat prices fell was common.
As drought developed the wheat died and soil was exposed to the wind creating massive dust storms. The resulting adverse conditions led to a large-scale human migration out of the High Plains as well since the lands could no longer support settlement. Even though the actual soil erosion of the Dust Bowl occurred only on the High Plains, the impact on the rest of the country was profound and the larger storms, like Black Sunday, blew well eastward.
In order to identify potential causes of 20th century droughts in the U.S., Fye et al.
(2004) investigate Pacific sea surface temperature patterns. For the Dust Bowl drought 80 they discuss the weak and poorly defined sea surface temperature (SST) regime during the 1930s. Tropical SST anomalies were especially weak during winter and spring where
ENSO is often observed. However, in the slight variability weak La Niña , when present, may have contributed to drought development. Slight northwestern Pacific cooling and northeastern Pacific warming SSTs were observed during the decade. This may have contributed to higher geopotential heights over the central U.S. in the spring and summer indicative of a high pressure ridge. However, the possible forcing was still so weak that
Fye et al. state it is possible the Dust Bowl drought and resulting warm conditions may have arisen from a coincidental sequence of dry years compounded by the human induced environmental degradation.
The SOI during the 1930s is plotted in Fig. 4.18 from the Australian Bureau of
Meteorology archives. To be classified as an ENSO event, the three month index mean, in red, must exceed either +8 or -8 for a sustained period of time, indicated by the horizontal dashed lines in Fig. 4.18. Despite subtle seasonal changes, nearly all of the index variability is within ±8 index.
White and Gershunov (2008) also describe western pacific PDO like cooling in the 1930s as the PDO transitioned from east Pacific 1930 warm phase to east Pacific
1955 cool phase. The study investigated further that the 1930s occurred during the interface of cool phases of the Pacific quasi-decadal oscillation (QGO), interdecadal oscillation (IDO) and pentadecadal activity. White and Gershunov also determined
ENSO was too weak to cause or break the drought in 1930s and that the longer pentadecadal signal in the Pacific seemed to dominate. However, limiting the simulation 81
Figure 4.18: Historical SOI values during the 1930s. The monthly index derived by the Australian Bureau of Meteorology is plotted in blue, the three month mean is plotted in red, and the dashed lines in black at +8 (La Nina) and -8 (El Nino) represent the magnitude indicative of an ENSO event.
to the Northern Hemisphere north of the tropics (20N and higher) loses the ability to represent the multiyear 1930s drought, so tropical forcing must still be important despite limited variability. White and Gershunov argue that even though the changes in SSTs they believe caused the 10-year Dust Bowl drought were very subtle, a drought of similar magnitude could occur again when the cool phases of the Pacific SST oscillations next happen concurrently.
A study by Seager et al. (2008) attempts to determine if the Dust Bowl drought can be predicted with ensemble model simulations forced with the historically observed 82
SSTs from the 1930s. The models successfully produced a severe drought over multiple years, but centered further south than the observed drought impacts from the 1930s in the central U.S. Importantly, the models did not reproduce the nationwide surface air temperature warming that occurred. Comparatively, the models were able to reproduce the precipitation patterns and surface air temperature warming of 1950s drought accurately, which indicates prediction skill is possible. Tree ring records indentify three events over the previous 1000 years as analogs to a 1930s type drought, indicating that more northerly centered droughts have the precedent of occurring naturally, although rare. Therefore Seager et al. observe that factors such as the human induced land surface degradation, dust storms, heavy aerosol loading from suspended dust particulate matter, and the impact this had on land-atmosphere interactions could have resulted in the further north occurring 1930s observed drought.
Cook et al. (2009) also discuss the unusual nature of the continental warming and northerly centered location of the Dust Bowl drought. The study demonstrates that inclusion of forcing from human induced land impacts due to crop failure is necessary to produce the anomalous features of the Dust Bowl era. Reduction of vegetation cover and the addition of a soil dust aerosol source in addition to 1930s SSTs in the general circulation models simulate the 1930s warmer temperatures and drought. The study concluded that a modest SST forced drought amplified by the human induced land degradation formed the Dust Bowl environmental disaster. It is therefore not surprising that the resulting warmer summer climate during the Dust Bowl included many extreme heat waves. 83
4.5 Urban Mitigation and Response Techniques for Heat Waves
In anticipation of future extreme heat waves there are actions that can be successful in reducing the impact to urban areas such as increased urban green space and coordinated city response plans during events.
Stone et al. (2010) investigated the association between urban form and extreme heat events. Through analyzing components of urban form such as density, land-use, and city centeredness, the relative urban footprint of U.S. cities were characterized. The study utilized a low 85% heat wave threshold, in order to capture many events, and found that the occurrence of heat events is increasing in large metropolitan regions across the
U.S. Importantly, the rate of increase in events is higher in more spread out cities than compact ones. That increase is independent of city population and rate of population growth. Stone et al. state that despite the increased warmth, heat illness in the U.S. has been overall about level since 1980, likely due to increased protective factors like air conditioning. However, there may be some point in the future when impacts from urban form outpace protective factors
Even though the Stone et al. (2010) study was unable to assess the relative contribution to the urban heat island by factors like low albedo, sparse green space, and increased thermal loads, the dominant source of warmer urban conditions is believed to be loss of vegetative cover. In addition to identifying the advantages of compact urban design, Stone et al. argue their findings highlight the need for preservation of regional green space, installation of street trees, green roofs, and reflective surfaces. 84
Indeed a study by Silva et al. (2010) determines that heat related health impacts could be reduced by vegetation enhancement. In the studied city of Phoenix, more heat related emergency calls occur on higher temperature days. Silva et al. demonstrate, using an urban energy model, that increasing the percentage of the city’s vegetated area reduces the urban heat island. Since vegetation has such a strong effect of reducing increased urban temperatures, the study concluded that more vegetated area could therefore reduce the number of heat related emergency calls.
In addition to reducing the impact of heat waves, more compact cities with increased green space could reduce a population’s exposure to other adverse factors like poor air quality, poor water quality, and obesity. Stone et al. (2007) state that a compact urban area can greatly reduce vehicle travel and emission, which is a significant source of near surface ozone and fine particulate matter that produce poor air quality in large U.S. cities. With better air quality and expanded green space, physical activity for city residents increases as discussed by Younger et al. (2008). Another study identified low density urban form over a large area has a greater impact on overall watershed quality than more compact central cities (Tu et al. 2007). Water quality, runoff, and flooding can be better managed in a central built environment than over larger areas.
The best plans to mitigate urban heat health related impacts would be those that specifically address vulnerable populations as well as urban form improvement. Bernard and McGeehin (2004) recommend city heat wave planning should be organized around the following fundamental components: determining a lead agency and participating organizations, use of a standardized warning system activated based on weather 85 conditions, public outreach and education, response activities targeting high risk populations, evaluating information, and revising the plan. The most at risk people are people without access to air conditioning, the chronically ill, elderly, very young, socially isolated people and urban residents. Of the city heat plans that Bernard and McGeehin reviewed, only a few had targeted outreach to reach the socially isolated, addressed people with mental or chronic illness, and the disabled. Cities that prepare to assist the vulnerable parts of the population will be more capable of making it through a heat wave with reduced negative human impacts.
Heat waves in the Midwest have a long history of creating negative impacts to residents, especially in urban areas. By taking actions to help people at risk during heat waves as well as planning to create a healthier urban environment to live in, cities will have a better chance to reduce heat related morbidity and mortality in the next extreme event.
4.6 Summary
Even though there has been a lot of variability in heat wave events, the early 20th century stands out as having the most frequent events. Surprisingly, there are few 99% heat wave events in recent decades, though St. Louis and Columbus do observe more frequent 95% events over the past 30 years than any other time since the 1930s. In addition to heat wave frequency, some of the most extreme events investigated historically provide an interesting perspective, including on the 1930s as a whole. In terms of heat waves, the climate of the 1930s was unlike any other period in the study. 86
Also discussed are urban mitigation and response techniques to reduce the impacts of heat waves when they occur.
87
CHAPTER 5: CONCLUSION
The goal of this Thesis was to define a method for identification of past heat wave events for urban areas of the Midwest and to investigate the variability of events in the observations over time. For the research surface weather observations were compiled going back to 1900 for Columbus, Indianapolis, Kansas City, and St. Louis. Discussed were the heat waves of record with historical context for the selected cities, how Midwest heat waves relate to other weather and climate features, and mitigation and response strategies to reduce heat wave impacts. Since only regional extreme heat waves with high decadal variability were researched, more general relations or representation of potential global climate change was not investigated and is beyond the scope of this
Thesis.
Heat waves are best described broadly as a period of unusually high atmosphere related heat stress, but lack a meaningful uniform meteorological definition (Robinson
2001). The idea of heat stress, which is a temporary lifestyle modification that may have adverse health consequences for those involved, represents the subtle onset characteristic of consequences to heat waves (Souch and Grimmond 2004). Some common ways to represent heat waves are with extreme temperature thresholds for a single event, percentile thresholds, and both temperature and moisture characterization for more recent events. Theoretically, heat waves can be identified based on exceeding preset absolute values, or as a deviation from the normal. The second method of a deviation from normal represented by a fixed percentile threshold of all observed values is more reliable for a long station record and comparison between cities. 88
The Midwest has been identified as potentially vulnerable to increased severity and frequency of summer heat waves by the Global Climate Change Impacts in the
United States (Karl et al. 2009) report. The proximity of the Midwest to the southern
Great Plains often results in the extreme heat conditions typical of the Plains summer climate impacting the Midwest during heat waves. Furthermore, extreme heat waves are often intensified in urban areas due to the heat island phenomenon.
The IPCC (2007) has indicated based on climate projections that it is very likely heat waves will increase in frequency over most land areas by the end of the 21st century.
Impacts of this projected trend include reduced crop yields in warm regions, increased danger of wildfire, increased water demand, reduced quality of life and even increased risk of heat-related mortality for people in warm areas without proper housing. Research by Meehl and Tebaldi (2004) and Hayhoe et al. (2010) also support observing more frequent and intense heat waves in the Midwest by the end of the 21st century. The lack of a rigorous heat wave definition, compounding nature of the events in urban areas, climate conditions of the Midwest, and potential for increased heat waves in the future motivated the study completed in this Thesis.
The adopted threshold framework investigates the number and length of past heat waves and the changes manifest in the extreme thresholds of the study, namely the top
5% (95th percentile event), 2.5% (97.5 percentile event), and 1% (99th percentile event).
The temperature thresholds for each city are presented previously in Chapter 4.1. The temperature thresholds were warmest to the west in Kansas City and St. Louis, and coolest to the east in Indianapolis and Columbus. This feature is a product of the climate 89 from west to east across the central U.S. The 99% resulted in only about 18 or 31 events for each city, whereas the 95% classified about 150 events over the period of study. A persistence threshold of at least three consecutive high or low temperatures at the given percentile or above was included to provide a minimum duration for events. Even that short of duration of extreme temperature can have major consequences on people, livestock, plant, and other animal life (Lyon 2009). Heat waves as defined in this Thesis by duration and percentile threshold temperatures do not provide a strict and uniform definition for all heat wave events, but compare the sensitivity of different percentile thresholds in representing heat waves.
The analysis of past frequency indicates that despite variability year to year and between cities, there are some evident features and patterns. The 1930s stand out as the period in the study with the most heat waves, but numerous heat wave observations still occurred at other times, like during the summer of 1901 and during the 1910s for all cities. In fact, the mean number of heat waves in the 1930s was unique, compared to the mean over the 110-year period of study. Likewise, the 1960s and 1970s were also unique compared to the mean, but due to the occurrence of very few events. For Columbus and
St. Louis it appears that the past 30 years as a whole have included more numerous heat wave days than other times since the 1930s. Indianapolis and Kansas City have observed comparatively few heat waves in recent decades, as the single heat wave high or low observations at threshold do not occur as often consecutively for these two cities.
The heat wave of record for each city in the study has been determined as the longest consecutive stretch of daily high and low temperature observations at or above 90 the 99% threshold. These events are 8-15 July 1936 for Columbus, 7-15 July 1936 for
Indianapolis, 17-23 July 1934 for Kansas City, and 21-25 July 1901 for St. Louis. All cites had the longest 99% heat wave during the 1930s except for St. Louis. Nonetheless, the 1930s was exceptional for all cities with regard to the number of heat waves, with
1934 and 1936 especially hot summers.
The longest 99% event on record for Columbus and Indianapolis was the same event in both cities. In addition to the extreme temperatures at the surface, the 850mb geopotential heights during the event were anomalously high over the Midwest. The
99% event represents the most extreme portion of a very hot summer, as much of July and August 1936 were during 95% heat waves for Indianapolis and Columbus as well.
Newspaper articles from during the event chronicle what was an exceptional time for the central U.S. Nationwide the heat was oppressive and the associated drought was severe enough to spur urban water shortages, wildfires, grasshopper plagues, farm loss, and high grain prices (New York Times 8, 11, and 12 July 1936). Even President Roosevelt directed one of his hallmark programs, the Works Progress Administration, to expand projects in places most impacted by the harsh conditions (New York Times, 7 July 1936).
Kansas City’s longest 99% event was earlier in the 1930s, but still associated with drought and extreme temperature concerns across the central U.S. On a slightly larger scale, 700mb specific humidity values were anomalously high over Missouri and parts of
Kansas during the event. Impacts reported in the New York Times during the event included human fatalities, dead livestock, and damaged crops (23 July 1934). 91
The 1930s heat waves occurred during an extraordinary climate event for U.S.
The regional event ongoing in the High Plains was referred to as the Dust Bowl, but the overall dry conditions during the 1930s for the central U.S. has become known as the
Dust Bowl drought. Studies trying to assess just what caused the Dust Bowl drought identified a relatively subtle SST regime at the time, but still one that in model simulations induces drought conditions across the south central U.S. (White and
Gershunov 2008, Seager et al. 2008, and Cook et al. 2009). However, the decade actually observed a drought centered further to the north and associated with drastic surface air temperature warming. Heavy aerosol loading from the massive dust storms of the time and feedback from human induced land degradation are plausible factors to account for the observed conditions not represented by SST forcing alone (Seager et al.
2008 and Cook et al. 2009). What started as a modest drought forced by SSTs developed into a large-scale environmental disaster due to the impacts from human induced land degradation.
During the longest 99% event for St. Louis in 1901 the new record high temperature for the city at the time was observed. In hindsight, the historical context of some of the impacts reported in the paper is very interesting. That summer the St. Louis
Post-Dispatch reported the “torrid” conditions in the city with articles detailing news of
101 people dying from the heat in July, a proclamation issued by the Governor for citizens to pray for relief, and an interview with “inventor” Alexander Graham Bell on a potential device to dispel heat from homes (St. Louis Post-Dispatch, 18, 22, and 24 July
1901). 92
More recently a July 1999 heat wave at the 99% threshold in St. Louis was part of a hot period immediately following two 95% events nearly back to back. Anomalously high specific humidity values at 850mb and a synoptic ridge at 500mb were over St.
Louis during the event contributing to the warmth. Similar to events decades earlier were lists of heat related deaths accompanying news articles during the event and updates on the latest locations of buckled interstate highway pavement, but different from the earlier century heat waves were impacts on city air quality and the electric utilities (St. Louis
Post-Dispatch, 27 and 30 July 1999). Also common of modern heat waves is the city and state government having a more active role in providing awareness and assistance to residents during dangerous heat.
This Thesis lastly considered some mitigation and response strategies to reduce the impact of extreme heat waves. Increased green space and vegetated area in cities not only reduce the impact of heat waves, but improve other measures of public health as well (Stone et al. 2010). Organized municipal heat wave response plans targeting at risk segments of the population, like the elderly and socially isolated, can reduce the human toll since such people are most likely to be adversely effected (Bernard and McGeehin
2004). Given that cities are a planned and built environment, actively ensuring that urban development has not resulted in a situation that is detrimental to citizens is important.
It remains unknown just how the frequency and magnitude of future heat waves will be manifest in a potentially changing climate. Will the apparent consistent occurrence of extreme heat waves over the past 30 years continue for St. Louis and
Columbus? Will Kansas City and Indianapolis begin to observe a more similar pattern or 93 are there specific factors that would prevent this feature from becoming present? Any rural stations with long records or other cities in the Midwest could be added to the climatology for comparison and to identify potential similar patterns. Lower thresholds such as 85% or 75% could be added to investigate patterns and variability of lower magnitude summertime heat waves and potential warming. Further, the parallels between the human induced Dust Bowl drought and extreme heat era and human induced global climate change should not go unnoticed. This is just another example on a basic level, that humans can and have had a profound impact on climate.
Interestingly, some components of human response to heat waves have not changed much as evidenced from the newspapers 70+ years ago. People experiencing a heat wave still complain, names of heat related deaths with details of their tragic demise are still listed, and humorous blame is still directed to atmospheric researchers and meteorologists. This may be due to a general understanding that these events happen and are still a product of a given location’s climate, no matter how rare individual events may be. However, research like this applied climatology Thesis is a powerful tool in providing information to better understand the environment in which people and commerce exist. Atmospheric scientists and local stakeholders such as urban planners, government officials, and private interests can use the work in this Thesis to better understand past climate and to contextualize and prepare for future similar heat wave events. Through active mitigation and evolving response plans a compounded human impact by heat wave events can be avoided. By recognizing that every natural disaster occurs foremost on a local level, and often with precedence in some form by a similar 94 event, understanding can be improved to reduce the negative consequences of the next extreme heat wave. There is no one way to developing better climate applications to represent issues surrounding heat waves, but it is through work like this Thesis as well as social and scientific discourse that lays the advancement.
95
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