In recognition that the human thermal environment cannot be represented adequately with just a single parameter, air temperature, over the last 150 years or so more than
100 simple thermal indices have been developed, most of them two-parameter indices. For warm conditions such indices usually consist of combinations of T and different measures for humidity, while for cold conditions the combination typically consists of Ta combined in some way with v. Simple indices are easy to calculate and therefore, easy to forecast. In addition they are readily communicated to the general public and stakeholders such as health service providers (Koppe et al. 2004). However, due to their simple formulation of the human heat balance as represented in Eq. (2.1) (i.e. neglecting significant fluxes or variables), these indices can never fulfil the essential requirement that for each index value there must always be a corresponding and unique thermo physiological state (strain), regardless of the combination of the meteorological input values. Thus their use is limited, results are often not comparable and additional features such as safety thresholds etc. have to be defined arbitrarily. Comprehensive reviews on simple indices can be found e.g. in Fanger (1970), Landsberg (1972), Driscoll (1992), and Parsons (2003).
Another approach based on synoptic climatology starts by identifying the various broad-scale weather types characterising a given locality. Several studies have identified that specific weather types (air masses) adversely affect mortality. Kalkstein et al. (1996) successfully extended this approach to heat health warning systems (HHWSs). The synoptic procedure classifies days that are considered to be meteorologically similar by statistically aggregating days in terms of a selection of meteorological variables such as air temperature, dew point, cloud cover, air pressure, wind speed and direction. The classification must be specifically derived for each particular locality where the synoptic approach is to be applied (see also Chapter 3).
Comprehensively characterising the thermal environment in thermo physiologically significant terms requires application of a complete heat budget model that takes all mechanisms of heat exchange into account, as described in Eq. (2.1). Such models (Fig. 2.3) possess the essential attributes that enable them to be universally utilised in virtually all biometeorological applications, across all climates zones, regions, and seasons.
This is certainly true for MEMI (Hoppe 1984, 1999), and the Outdoor Apparent Temperature (Steadman 1984, 1994). However, it is not the case for the simple Indoor AT, which forms the basis of the US Heat Index, often used in outdoor applications by neglecting the prefix "Indoor". Other comprehensive heat balance indices include the Standard Effective Temperature (SET*) index (Gagge et al. 1986), and OUT_SET* (Pickup and De Dear 2000; De Dear and Pickup 2000), which translates Gagge's indoor version of the index to an outdoor setting by simplifying the complex outdoor radiative environment down to a mean radiant temperarture. Blazejczyk (1994) presented the man-environment heat exchange model MENEX, while the extensive work by Horikoshi et al. (1995, 1997) resulted in a Thermal Environmental Index.
Fanger's (1970) PMV (Predicted Mean Vote) equation can also be considered among the advanced heat budget models if Gagge's et al. (1986) improvement in the description of latent heat fluxes by the introduction of PMV* is applied. This approach is generally the basis for the operational thermal assessment procedure Klima-Michel-model (Jendritzky et al. 1979, 1990) of the German national weather
Descriptive term Thermophysiology Meteorology
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