  A thermodynamic device placed outdoors, or a local ecosystem, is subject to a
variety of different temperatures given by short-tem (daily) and long-term
(seasonal) variations. In the long term a superstatistical description makes
sense, with a suitable distribution function f(beta) of inverse temperature
beta over which ordinary statistical mechanics is averaged. We show that
f(beta) is very different at different geographic locations, and typically
exhibits a double-peak structure for long-term data. For some of our data sets
we also find a systematic drift due to global warming. For a simple
superstatistical model system we show that the response to global warming is
stronger if temperature fluctuations are taken into account.
