@article{ZieglerPollingerBoelletal.2020,
  author    = {Ziegler, Katrin and Pollinger, Felix and B{\"o}ll, Susanne and Paeth, Heiko},
  title     = {Statistical modeling of phenology in Bavaria based on past and future meteorological information},
  series = {Theoretical and Applied Climatology},
  volume    = {140},
  journal   = {Theoretical and Applied Climatology},
  issn      = {0177-798X},
  doi       = {10.1007/s00704-020-03178-4},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-232717},
  pages     = {1467-1481},
  year      = {2020},
  abstract  = {Plant phenology is well known to be affected by meteorology. Observed changes in the occurrence of phenological phases arecommonly considered some of the most obvious effects of climate change. However, current climate models lack a representationof vegetation suitable for studying future changes in phenology itself. This study presents a statistical-dynamical modelingapproach for Bavaria in southern Germany, using over 13,000 paired samples of phenological and meteorological data foranalyses and climate change scenarios provided by a state-of-the-art regional climate model (RCM). Anomalies of severalmeteorological variables were used as predictors and phenological anomalies of the flowering date of the test plantForsythiasuspensaas predictand. Several cross-validated prediction models using various numbers and differently constructed predictorswere developed, compared, and evaluated via bootstrapping. As our approach needs a small set of meteorological observationsper phenological station, it allows for reliable parameter estimation and an easy transfer to other regions. The most robust andsuccessful model comprises predictors based on mean temperature, precipitation, wind velocity, and snow depth. Its averagecoefficient of determination and root mean square error (RMSE) per station are 60\% and ± 8.6 days, respectively. However, theprediction error strongly differs among stations. When transferred to other indicator plants, this method achieves a comparablelevel of predictive accuracy. Its application to two climate change scenarios reveals distinct changes for various plants andregions. The flowering date is simulated to occur between 5 and 25 days earlier at the end of the twenty-first century comparedto the phenology of the reference period (1961-1990).},
  language  = {en}
}
@article{PaethPollinger2019,
  author    = {Paeth, Heiko and Pollinger, Felix},
  title     = {Changes in mean flow and atmospheric wave activity in the North Atlantic sector},
  series = {Quarterly Journal of the Royal Meteorological Society},
  volume    = {145},
  journal   = {Quarterly Journal of the Royal Meteorological Society},
  number    = {725},
  doi       = {10.1002/qj.3660},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-208079},
  pages     = {3801-3818},
  year      = {2019},
  abstract  = {In recent years, the midlatitudes are characterized by more intense heatwaves in summer and sometimes severe cold spells in winter that might emanate from changes in atmospheric circulation, including synoptic-scale and planetary wave activity in the midlatitudes. In this study, we investigate the heat and momentum exchange between the mean flow and atmospheric waves in the North Atlantic sector and adjacent continents by means of the physically consistent Eliassen-Palm flux diagnostics applied to reanalysis and forced climate model data. In the long-term mean, momentum is transferred from the mean flow to atmospheric waves in the northwest Atlantic region, where cyclogenesis prevails. Further downstream over Europe, eddy fluxes return momentum to the mean flow, sustaining the jet stream against friction. A global climate model is able to reproduce this pattern with high accuracy. Atmospheric variability related to atmospheric wave activity is much more expressed at the intraseasonal rather than the interannual time-scale. Over the last 40 years, reanalyses reveal a northward shift of the jet stream and a weakening of intraseasonal weather variability related to synoptic-scale and planetary wave activity. This pertains to the winter and summer seasons, especially over central Europe, and correlates with changes in the North Atlantic Oscillation as well as regional temperature and precipitation. A very similar phenomenon is found in a climate model simulation with business-as-usual scenario, suggesting an anthropogenic trigger in the weakening of intraseasonal weather variability in the midlatitudes.},
  language  = {en}
}