Heat Waves

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Introduction

This is a page to support heat wave research. This is originally developed for Winter 2008 to support student research projects. If there are documents that you want to assure are not seen by others, please post them as "Resources" on the ctools site.

ctools site: AOSS 499 018 W08

This is a start to develop the ideas for an open community as Kris Ebi and Ricky Rood are proposing. If you know this site is here you can find it. If you don't know it is here, it is very hard to find.

The participants are:

two students of meteorology

  • Evan Oswald (eoswald@umich.edu )
  • Ryan Donald (rydon@umich.edu )

two students of public health

  • Jalonne White-Newsome (jalonne@umich.edu )
  • Carina Gronlund (gronlund@umich.edu )

two professors

  • Marie O'Neill (marieo@umich.edu )
  • Ricky Rood (rbrood@umich.edu )

and with a little luck we have seduced from retirement the beloved professor

  • Bill Kuhn (wkuhn@umich.edu )


There are are group of people who might be interested in joining us. These are Jerry Meehl, Claudia Tebaldi, Larry McDaniel, and Kris Ebi. We'll get our act together, and then invite them to the party.

In November 2007 Marie and Ricky attended a conference on heat waves in Phoenix. At that meeting Ricky wrote up a personal view of the "heat wave system." That system diagram is here. A web page for a community to study urban climate change is here. Confronting Urban Climate Change

Vision

What are we trying to do?

We want to develop new methods to use environmental data to diagnose and predict heat events that are a danger to human health. This environmental information will then be combined with data that represents the vulnerability of people to heat stress. The goal is to combine these two sources of information to develop an optimal, verifiable system for heat wave warnings that can be widely and transparently implemented.

We seek to bridge the fields of public health, meteorology, and climate prediction. We aim to contribute to development of policy and strategies to adapt to extremes of environmental heat and mitigate the public health impact of that heat.

Human Heat-Health Warning Systems

This is a section working to define a systems view of how we determine that there is extreme heat, how that heat influences the local environment, and how to identify vulnerable populations. This is the quantitative part of the problem.
Figure 1: Schematic of Human Heat-Health Warning System

Figure 1 represents the elements of a human heat-health warning system.

Environmental information is represented by the components on the left of the figure. There are numerous environmental parameters (En). These parameters are characterized by high variability in time, but also being both well measured and predictable. They may not be fully representative of the environment on the human scale. There are basic parameters such as temperature, humidity and wind which directly affect the heating and cooling of the body. There are also a set of derived parameters such as persistent nighttime minima and a measure of a high-heat episode relative to some background or average. An important distinction that will need to be made is between instantaneous extreme heat, and the accumulation of heat in the environment.

In the center of the figure is geographical information, which is also measured by several parameters. These parameters are characterized by being independent of time on the time scale of an intense heat event (i.e. constant). Examples of geographical parameters are wooded versus cleared land or land with building or extensive roads. This will be called the cityscape (CS). Quantitative measures of the cityscape are based on the radiative characteristics of the materials at the surface and would include albedo, emissivity, and the ability to hold heat. There can be great complexity of the cityscape.

On the right of the figure is population information, which includes measures, in some aggregate way, of the characteristics of the population. The parameters are directly associated with people, and have tremendous complexity. There is no a priori reason for the characteristics of the population to organize into geographical patterns. The purpose of the population information is to assist in identifying people whose welfare is most vulnerable to intense heat.

The arrows on the figure represent an intuitive flow of information through the system as a whole. The environmental data provides a measure of heat, and the ability to determine if that heat is excessive. On one level the intensity of the heat can be determined in an absolute way. For example, the temperature might be two standard deviations removed from a long-term average or an absolute high temperature record. This absolute measure may not directly impact human health. Therefore, information other than temperature is needed to determine the health impact. Often humidity is used, i.e. the heat stress index, and experience shows that use of a variety of environmental information improves the usefulness of a human heat-health warning system (A variety of Kalkstein references.) One the other hand, experience shows that indicators in one environment, e.g. humid, are not the best indicators in other environments, e.g. arid. see Keim et al., 2007

There is, implicitly, in the environmental information component of the system an algorithm that combines information from the various geophysical parameters. The product of this algorithm is a measure of extreme heat and an extreme-heat warning flag(EW) is raised. It is useful to define two types of excess heat warning. The first type is an instantaneous measure of excess heat; i.e., it is hot. The second type of warning is based on accumulated heat, for instance, measured by a sustained increase in night time minima.

There is an array of information that is transmitted with the excess heat warning, for example, temperature, humidity, solar irradiance, cloudiness, wind vectors, etc. This information can be used to better define the local nature of the excess heat.

The geographical information can be combined with the environmental information to improve the efficacy of the excess heat warning. For example, if the heat event is one with low cloudiness and intense sunshine, the ability of the surface to absorb or reflect solar radiation is important. The Army field manual, for example, warns of a rocky desert environment being more than 30-40 degrees F warmer than the ambient air temperature. Similarly, as shown by Golden et al. (2004), the urban heat island of Phoenix, Arizona may be 10 higher than the air temperature at the airport. The geographical information identifies potential hot spots.

The ultimate goal of human heat-health warning system is to provide a useful warning to the population. At the human level there are both physiological and sociological parameters that contribute to vulnerable population (VP) groups. This introduces the full complexity of humans. From a physiological perspective it is useful to divide those who are put in risk by heat into two populations. The first are those who are generating heat internally because of physical activity. The second are those vulnerable to high ambient heat. In both cases the heating of the human body is balanced by the ability of the body to cool.

There are both correlated and independent paths by which the geographical and environmental information interacts with the population. As an example, those people who are at risk because of physical exertion are highly sensitive to high temperatures; that is, instantaneous extreme heat. Those more impacted by a sustained inability to cool their bodies are more impacted by accumulated heat. The geographical information that indicates hot spots is potentially important in both situations. The geographical information also carries an independent relation with the population. For example the location of large parks in, perhaps, where to go to find a cool place.

Research Plans

Meteorological Research

The meteorological research plan is:

Think of this all as a big generalized Taylor series. We are going to start with something simple and something that is "accepted." With this start we will verify that we can make some meaningful calculations.

Task 1: Specifics

  • We will start with the Integrated Surface Data set which we can get from NOAA's National Center for Climatic Data. Integrated Surface Data set

Here is the link for the actual data page.

  • We will choose a simple and straightforward way to calculate some indication of heat stress. For the first calculation we propose the method of [Karl and Knight, 1997]. This papers describes in words a simple technique to quantify heat intensity. Meehl and Tebaldi is, in fact, a better reference for this. Meehl and Tebaldi
  • We will make this calculation for the years of the great heat waves in Chicago (1995) and France (2003). In addition we will look at 2007, which had a more diffuse heat wave in the U.S. South.
  • We will define ways to validate that the heat wave indicators work or don't work.

From here there are numerous paths that we need to follow.

  • We need to extend the calculation to additional geophysical parameters to understand which environmental parameters are best predictors. (Evan and Ryan have been assigned to make a list geophysical parameters that have been shown to be useful in heat wave indicators.)
    • We need to understand the calculation and performance of the traditional Heat Stress Index (search NOAA for calculation.)
  • We need to investigate the use of other sources of observations. Ideas include:
    • Use of gridded analyses instead of or in concert with station observations. (This could vastly simplify the calculation.) Link to the NARR North American Regional Reanalysis
    • Use of regional network observations (e.g. Mesowest or wunderground.com to better define the urban heat island.)
    • Use of high resolution satellite observations to better define the urban heat island.

Temperature is first order indicator of heat. However, maximum temperature is not an especially robust indicator of human health stress. Other temperature information is needed. Sustained high nighttime minima have proven to be a simple indicator of urban heat danger.

Humidity is a more complex indicator as it can impact both the ability of the body to cool and dehydration.

There are other possible environmental variables of importance. Rather than speculate on these, can we identify them from first principles? Consider the heat budget of and object in the sun. Use the thermodynamic equation and analyze the problem.

Climate Change Research

Physiological Research

Heat-related illnesses are linked to

  • Internal heating of the body (exertion)
  • External heating of the body
  • Ability for the body to cool


What is the basic physiology of human cooling?

We need to search for physiological research that discusses human adaptation to heat. There are two questions to answer:

  1. Is there a physiological indicator of heat adaptation? If yes, does it give a time scale for human adaptation to heat?
  2. Is there a temperature threshold beyond which human adaptation is not possible?

Public Health Research

Resources

Reference Materials

This is a collection of reference materials.

Documents and Reports

Here is the convention for the archive of journal documents and reports.

Doc####_author_short_title_journal_yyyy.pdf


Reference Repository


Here is a categorization of Doc#### by subject.

Doc####

Doc0### Summary Documents

Doc1### Meteorologically oriented papers that have information about indices

Doc2### Climate change and human health

Doc3### Heat Health Warning Systems: Implementation and Efficacy

Doc4### Heat Health Danger Mitigation

Doc7### Epidemiology and Heat-related Health Problems

Doc8### Physiology and Heat

Doc9### Local Heat Environment (Urban Heat Islands)

Reference Repository

Data Descriptions and Sources

Integrated Surface Data set

Mesowest

Web Resources

Confronting Urban Climate Change

Detroit Urban Research Coalition

NCDC Heat Stress Index Overview

A Nice Local Heat Hazard Information Page

Phoenix Heat Waves on Climate Connections

Ryan's Page

Ryan's Link Page

Evan's Page