Software Open Access
Meteorologists typically characterise weather in terms of features, like cyclones or blocking high pressure systems. The instantaneous distribution of these features provides a very condensed summary of the atmospheric state. Consequently, monthly distributions of these features detected in the instantaneous fields retain much more relevant information about weather events than monthly averages of conventional meteorological variables, such as sea- level pressure. Weather events have been shown to provide a conceptual link between short- lived weather events and climate variability over longer time scales. This software project implements an optional automatic post-processing step the authors implemented for simulations based on the Norwegian Earth System Model (NorESM) and on the Norwegian Climate Prediction Model (NorCPM) to calculate monthly weather feature distributions.
Documentation for the MIND the KAP project is available as Technical Report 401 of the Nansen Environmental and Remote Sensing Center, doi: 10.13140/RG.2.2.13048.60167/3.
MIND the KAP is based on dynlib, which contains the weather feature detection algorithms used here.