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No matter how heat waves are defined, the human influence on them is clear (Collins et al., 2013; IPCC, 2011; Min et al., 2013). As the climate continues to warm due to increasing fossil fuel emissions, the severity and frequency of deadly heat waves will continue to increase (Kharin et al., 2013; Wehner et al., 2018). The effect of high temperatures on human beings and other animals is exacerbated by moderate to high humidity (Mora et al., 2017) and a variety of different indices are used to quantify the combined effect of temperature and humidity during heat waves (Wehner et al., 2017).

Heat waves in California are often hot and dry due to stagnant wind conditions. However, some California heat waves, such as the particularly deadly 2006 event, are characterized by more humid conditions, sometimes due to moisture transport from the ocean and gulf waters near Baja California into the Central Valley (Gershunov et al., 2009; Ostro et al., 2009). The widely used Steadman’s heat index (HI; Dahl et al., 2019; Wehner et al., 2017) is a measure of combined extreme heat and humidity (Steadman, 1979a, 1979b). The following bi‐cubic function of surface air temperature (T) and relative humidity (R) is a good fit to tabular data provided by the National Oceanic and Atmospheric Agency (https://www.weather.gov/safety/heat‐index) and valid for T > 80^oF (27°C) and R > 40% (Weather.gov, 2019):

Here, the units of the HI are ^oF. In California, relative humidity in the hot seasons rarely exceeds 40%. In these cases, we use the following “unofficial” biquadratic formula as a fit to the NOAA tabular values (Anderson et al., 2013):

As an example of the relationship of temperature to relative humidity, Figure 2.1 shows a scatterplot of temperature and relative humidity at the hottest time of day in Fresno. Colors are coded according to the NOAA heat index categories of risk to human health (Weather Service, 2020). Here and throughout this chapter, the heat index is calculated using weather station data in the HadISD data base (Dunn et al., 2016). We categorized the heat wave severity of the agricultural season by counting the number of days at each station when HI exceeds selected thresholds of 90^oF, 95^oF, and 100^oF. We then averaged these counts for all stations within a county. Furthermore, as specified in the empirical section, we tailored the estimated HI for specific crops during harvesting season for each of the counties under analysis.

Figure 2.1 Scatterplot of temperature and relative humidity at the Fresno, California airport weather station (HadISD station #723890 93193) at the time of the daily maximum heat index on hot days. Colors indicate the NOAA heat index categories.