  We present the new R package CoinCalc for performing event coincidence
analysis (ECA), a novel statistical method to quantify the simultaneity of
events contained in two series of observations, either as simultaneous or
lagged coincidences within a user-specific temporal tolerance window. The
package also provides different analytical as well as surrogate-based
significance tests (valid under different assumptions about the nature of the
observed event series) as well as an intuitive visualization of the identified
coincidences. We demonstrate the usage of CoinCalc based on two typical
geoscientific example problems addressing the relationship between
meteorological extremes and plant phenology as well as that between soil
properties and land cover.
