Objective weather types of Deutscher Wetterdienst derived from different Reanalysis and Global Climate Model simulations for the control run (1951-2000) and the projection period (2000-2100). On the one hand, the dataset is useful for evaluation of representative circulation statistics in Central Europe, on the other hand, for the analysis of future weather types due to climate change. Added temperature and precipitation data allow to study the weather type effectiveness for these important climate parameters.
Objective weather types of Deutscher Wetterdienst derived from different Reanalysis and Global Climate Model simulations for the control run (1951-2000) and the projection period (2000-2100). Forthermore, the NAO-index is also provided. On the one hand, the dataset is useful for evaluation of representative circulation statistics in Central Europe, on the other hand, for the analysis of future weather types due to climate change. Added temperature and precipitation data allow to study the weather type effectiveness for these important climate parameters.
Objective weather types of Deutscher Wetterdienst derived from different Reanalysis and Global Climate Model simulations for the control run (1951-2000) and the projection period (2000-2100). Furthermore, the NAO-index is also provided. On the one hand, the dataset is useful for evaluation of representative circulation statistics in Central Europe, on the other hand, for the analysis of future weather types due to climate change. Added temperature and precipitation data allow to study the weather type effectiveness for these important climate parameters.
Provided here are daily historical weather pattern classifications covering the period from 1950 to 2020, where the observed weather patterns are valid at 1200 UTC daily. The observed weather pattern on each day is given as a number from 1 to 30, which matches up to the weather pattern numbers described in Neal et al. (2016). The method used to generate this updated classification is the same as used in Neal et al. (2016), with the exception of using ERA5 for both the daily pressure fields and daily climatology. The daily climatology is used to calculate the pressure anomalies before they are matched up to weather pattern definitions and uses ERA5 between 1951 and 2019. This daily climatology has also been filtered by applying a 3-, 15- and 31-day rolling mean. Column 1 of this dataset gives the date [YYYY-MM-DD] and column 2 of this dataset gives the observed weather pattern classification [#].