  We analyse the probability densities of daily rainfall amounts at a variety
of locations on the Earth. The observed distributions of the amount of rainfall
fit well to a q-exponential distribution with exponent q close to q=1.3. We
discuss possible reasons for the emergence of this power law. On the contrary,
the waiting time distribution between rainy days is observed to follow a
near-exponential distribution. A careful investigation shows that a
q-exponential with q=1.05 yields actually the best fit of the data. A Poisson
process where the rate fluctuates slightly in a superstatistical way is
discussed as a possible model for this. We discuss the extreme value statistics
for extreme daily rainfall, which can potentially lead to flooding. This is
described by Frechet distributions as the corresponding distributions of the
amount of daily rainfall decay with a power law. On the other hand, looking at
extreme event statistics of waiting times between rainy days (leading to
droughts for very long dry periods) we obtain from the observed
near-exponential decay of waiting times an extreme event statistics close to
Gumbel distributions. We discuss superstatistical dynamical systems as simple
models in this context.
