Comparison of spatio-temporal evolution of extreme precipitation events between two high-resolution models in a northern Europe case study
- 1Department of Environmental Engineering, Technical University of Denmark, Denmark (edth@env.dtu.dk)
- 2Danish Meteorological Institute, Denmark
- 3Visiting scientist at Met Office Hadley Centre, UK
- 4Met Office Hadley Centre, UK
- 5Newcastle University, UK
Convection Permitting Models (CPM) are believed to improve the representation of precipitation extremes at sub-daily scale compared to coarser spatial scale Regional Climate Models (RCM). This study seeks to compare how the spatio-temporal characteristics of precipitation extremes differ between a 2.2km CPM and a 12km RCM from the UK Met Office with a pan-European domain.
Storm data have been re-gridded to a common 12km grid and all events in the period from 1999-2008 are tracked with the DYMECS tracking algorithm. A peak-over-threshold method is used to sample extreme events within a northern European case area. Maximum intensity and maximum area of extremes are sampled based on the maximum intensity and maximum size reached within their lifetime. Evolution in size and intensity, track patterns, and seasonal occurrence of extreme events are compared between the two models.
For the top 1000 extreme events with the highest maximum intensities, the two models show disagreement in movement direction and spatial and temporal occurrence. While the CPM data are dominated by south-north moving events occurring in summer over central Europe, the RCM data are dominated by west-east moving events occurring over UK and more uniformly distribution over the year. The CPM and RCM however show good agreement in these variables for extreme events instead selected based on largest spatial area. A comparison with the COSMO REA6 reanalysis model continuously nudged towards observations indicates a similar spatial and seasonal distribution of extreme events sampled by maximum intensity as in the CPM. Analysis of the evolution of storms over their lifetime shows on average higher intensities and spatial areas of the most intense storms in the RCM data compared to the most intense storms in the CPM data. Sampling of maximum intensity extreme events in each of the four seasons show larger disagreement between the two models in the evolution in intensity and size in autumn (SON) and winter (DJF) than in spring (MAM) and summer (JJA).
How to cite: Thomassen, E. D., Kendon, E., Sørup, H. J. D., Chan, S., Langen, P. L., Christensen, O. B., and Arnbjerg-Nielsen, K.: Comparison of spatio-temporal evolution of extreme precipitation events between two high-resolution models in a northern Europe case study, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18467, https://doi.org/10.5194/egusphere-egu2020-18467, 2020.
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Hi Emma,
Your study (and presentation) looks really interesting. I didn't have time to ask during your time slot, but I have two questions about it.
If I got it right, you define events based on grid percentile thresholds. Right?This means that if the climatology of a grid cell is composed of larger extremes (e.g., when using CPMs rather than RCMs) then the storms you follow should have (almost by definition) larger intensities.Did you try to somehow normalize the intensities of the different models to their climatology (e.g., the intensity of a storm divided by the percentile it was defined by or something in that spirit)?
Furthermore, do you have an idea why are differences greater in winter/autumn than in summer/spring?
Thanks,
Koko (Moshe) Armon
Hi Koko
Thank you very much!
We define events based on the DYMECS tracking algorithm, which tracks all events with intensities above 1 mm/hr. To define extreme or heavy precipitation event we looked at all tracked events and sampled the e.g. 99th percentile events with the highest 1-hour intensity. The maximum 1-hour intensity for a storm is defined as the maximum intensity registered for a single grid cell within the event). We have looked at other ways of sampling extreme events in order to see if the difference between CPM and RCM events are persistent, but we have kept events defined as spatial events based on a threshold using the tracking algorithm.
Regarding the largest difference in winter/autumn, we found this to be true only for the highest percentile (99.99), where we expect grid point storms to dominate the sampled RCM events. For lower percentiles summer/autumn events showed to be most different between the two models which are more aligned with the difference in the nature of the two models (convection parametrised or not).
I hope this answered your questions. Please feel free to ask further question if some things are still unclear :)
Kind regards,
Emma