A Poisson Regression Model to Estimate the Occurrence of Heat Index Extreme Events in Mesoamerica and Caribbean Region

Hourly data collected from ground stations were used to study the maximum heat index in the Mesoamerica and Caribbean (MAC) region for a 35-year period (1980-2014). The heat index is the combination of air temperature and relative humidity (RH) and is an attempt to estimate what humans feel as an apparent temperature.

In the MAC region, it is common to find places with extreme hot behavior during daytimes. However, the critical weather condition occurs when the hot conditions are also maintained during night times. Therefore, the HIEE in the MAC region is defined as an extraordinary hot event where the maximum-daytime heat index and the minimum-nighttime heat index both exceed the corresponding 97^th percentiles and this hot event must persist for at least two consecutive days.

Usually the extreme values of heat index are used for advising heat warning events, and it was found that 45 heat index extreme events (HIEE) occurred during the studied period. The average duration of HIEE was 2.4 days, and the average relative intensity (excess over the threshold) was 2.4 °C (4.3 °F). It was found that 82 % of HIEE lasted 2 or 2.5 days, and 80 % exhibited relative intensity of 3 °C (5.4 °F) or less.

It was found that extreme events in the MAC region mostly occur during the rainy season and apparently the increment in tropical disturbances are associate to increment in HIEE. It was also found that the annual frequency has intensified since 1991 with the highest incidences occurring in 1995, 1998, 2005 and 2010; and these years coincide with the cool phase of El Niño Southern Oscillation (ENSO). However, ENSO occurred in 1982 and 1987 did not reflect significant increments in HIEE during these years. Therefore, the occurrences of HIEE in the MAC region appear to be at least partially influenced by ENSO episodes.

It is known that ENSO cycle cause global changes of both temperatures and rainfall and modified variables that control tropical disturbances such as Vertical Wind Shear (VWS; Gray 1968), Sahel rainfall index (SRI; Janowiak 1988), North Atlantic Oscillation Index (NAO; Hurrell 1995), and Geopotential High at 250 hPa (GH250). An empirical analysis was conducted to show that these variables are the major factors that develop the conditions for the occurrence of HIEEs. Further research it is needed to study the mechanism of how these variables control the occurrence of HIEEs in the MAC region. Thus, a Poisson regression model is proposed to represent the frequency of HIEE, and this model shows that 87% of the variability of the HIEE is explained by the following meteorological variables: El Niño 3 (WGSP, 2017), SRI, VWS, NAO, and GH250. A Poisson regression model was used because HIEE is a rare event and the sample size approaches to infinity; i.e., the HIEE is a discrete random variable that follows a Poisson probability distribution. Thus, conventional regression cannot be applied, because the t- and F-statistics may be misleading.