@Ronnie and you could complete that list with the lambda versions for
heat index (requiring T / H as inputs
return ((id(t).state)+5/9*(6.112*pow(10,7.5*(id(t).state)/(237.7+(id(t).state)))*(id(h).state)/100-10));
the humi index (also requiring T / H as inputs
return (-8.784695 + 1.61139411*(id(t).state) + 2.338549*(id(h).state) - 0.14611605*(id(t).state)*(id(h).state) - 0.012308094*(id(t).state)*(id(t).state) - 0.016424828*(id(h).state)*(id(h).state) + 0.002211732*(id(t).state)*(id(t).state)*(id(h).state) + 0.00072546*(id(t).state)*(id(h).state)*(id(h).state) - 0.000003582*(id(t).state)*(id(t).state)*(id(h).state)*(id(h).state));
and last not least the summersimmer index (also T / H required)
return ((1.98 * ((id(t).state * 1.8 + 32) - (0.55 - 0.0055 * id(h).state) * ((id(t).state * 1.8 + 32) - 58)) - 56.83) - 32) * 5/9;
what’s missing though is that some of these are limited means they don’t should b calculated across the most common temperature ranges since they only do make sense within a limited bandwidth.
have I missed one? Of course the “feels-like temperature”, but this does require wind-speed which isn’t given by the bme sensors.