Status:Ongoing analysis Material from: Linus, Ervin, Esti


 


1. Impact

The Emilio-Romagna region of Italy received an exceptional amount of rainfall on 15-16 May as a result of the low-pressure system called Minerva. Just as this area happened to have a similar event just 2 weeks ago.

The media reports that over 20 rivers and streams have burst their banks, with flooding in 37 municipalities causing at least 8 fatalities. The source also reports 250 landslides across 48 municipalities.

https://en.wikipedia.org/wiki/2023_Emilia-Romagna_floods

2. Description of the event

The slide below includes some preliminary data about the event.


The plots below show analyses of MSLP and 6 hour rainfall from 12 May 12UTC to 17 May 00UTC, every 12th hour.

The plots below show analyses of z500 and T850 from 12 May to 17 May 00UTC, every 24 hour.



3. Predictability

  

3.1 Data assimilation

 

3.2 HRES

The plots below show 48-hour precipitation (15 May 00UTC - 17 May 00UTC) in observaions (first plot, more obs to be added later) concatenated short forecasts (second plot) and o-suite HRES forecasts with different lead times.


The plots below show the same as above but for e-suite (the concatenated analysis is still o-suite).

3.3 ENS

The plots below shows EFI and SOT for 3-day  precipitation on 15-17 May, from different initial dates.


The plot below shows the forecast evolution plot for 48-hour precipitation (15 May 00UTC - 17 May 00UTC)   for 0.5 degree box outlined in the plots above. Mean of observations - green hourglass, concatenated 6-hour forecasts - green dot, HRES –red, ENS control - purple, ENS blue box-and-whisker, Model climate – red box-and-whisker. Ensemble median as black box and ensemble mean as black diamonds. Triangle marks the maximum in the model climate based on 1200 forecasts. 48r1 e-suite is included in cyan (ENS distribution).


3.4 Monthly forecasts

The plot below shows the weekly anomalies in precipitation (the title of the figure is wrong) for 15-22 May, in analysis and forecasts with different lead times.

3.5 Comparison with other centres



4. Experience from general performance/other cases


5. Good and bad aspects of the forecasts for the event


6. Additional material