From climate to weather reconstructions.

Climate reconstructions have contributed tremendously to our understanding of changes in the climate system and will continue to do so. However, in climate science the focus has partly shifted away from past seasonal and annual mean climate towards weather variability and extreme events. Weather events are more directly relevant for climate impacts and they capture the scale at which important processes take place. Weather reconstructions therefore help to better understand atmospheric processes, particularly during extreme events, to assess decadal-to-multidecadal climate variability through the lens of weather changes, and they allow impact modelling of past events. Consequently, attempts are currently undertaken to extend weather data sets far back into the past. In this review I discuss methods of weather reconstructions that are in use today. The methods range from expert analyses to data assimilation, from analog approaches to machine learning. Products range from weather types to four-dimensional fields. The methods complement each other as they are based on different assumptions and are based on different data sets. Weather reconstructions require more meteorological data than climate reconstructions. Additional data rescue efforts are therefore needed. [ABSTRACT FROM AUTHOR]