Contributed by Fredrik Wetterhall
In early June 2013, the Northern part of the Alps where hit with extreme rainfall that led to extensive flooding in Central Europe, with a death toll of 25 people and overall economic losses of €12bn. A classical synoptic weather pattern with a deep quasi-stationary low pressure system brought moist air towards the Northern side of the Alps. Orographic lifting led to very intense precipitation over a large area where the soils were already saturated due to earlier wet weather in May.
The location of the precipitation was accurately predicted by most global numerical weather prediction models (NWPs), however the magnitude was widely underestimated (Fig.1). The discharge in the affected areas was well predicted by EFAS, and a total of 14 flood warnings were sent out prior to the event (see example for Passau in Fig 2). The magnitude of the flooding was nevertheless underestimated, to a large extent as a consequence of the underestimation in precipitation.
The current ECMWF high resolution forecast runs on a grid size of about 16 km, and on that scale the synoptic circulation is well resolved, but intense precipitation associated with deep convection is parameterised. An increase in resolution as well as improving the model physics would potentially lead to improvements in the modelling of precipitation for extreme event. To assess the effect of resolution as well as model physics on precipitation, we ran a number of model experiments over the event to see which improvement would be most beneficial.
Experiments with increased resolution and improved cloud physics
The first hypothesis was that increased resolution would also mean a better described orography, whin in turn would increase the orographically enhanced precipitation. We therefore reran our latest model version (40R1) with resolutions T319, T639, T1279 and T2047, which translates to 64, 32, 16 and 10 km respectively. The high resolution model currently runs at T1279, but will increase to T2047 in 2015. We also ran an experimental model version at resolutoin T3999, which is about 5km. That is the resolution which is in the so called “grey zone”where the relationship between parameterized deep convection and explicit deep convection on the grid scale becomes less clear.
Not only resolution is important for precipitation, but also cloud microphysics, especially the formation of precipitation. Therefore the current formulation proposed by Sundquist (SQ, Sundquuist et al, 1978) was compared with a new scheme proposed by Khairoutdinov and Kogan (KK, 2000) for the resolutions T1279 (16 km) and T3999 (5 km). An experiment allowing deep conversion was also tested for the highest resolution. For a full description of the experimental setup, see Haiden et al. (2014).
The experiments were validated over a small box over the alps (47N-48N, 10W-14W) where most of the rain fell. This location was also chosen to fully investigate the effect of increased resolution on the orographically enhanced precipitation. Figure 3, left panel shows the increase in precipitation with increase in resolution, which can be attributed to a more detailed orography. However, there is still a substantial gap to the observed precipitation of the event. The impact of the new cloud physics is shown on the right hand side of Figure 3. The current operational model with the inclusion of the KK scheme (light green curve) shows a substantial improvement. The most impact of the improved cloud physics is with the highest model resolution. The KK scheme is better than the SQ scheme, but a tuning of the latter scheme gives an even higher precipitation intensity. Finally, the experiment allowing deep convection brings the precipitation very close to the observed intensities. The T3999 with deep convection also improved the spatial distribution of precipitation (not shown).
The discharge over the Alpine region were also better modelled, and Figure 4 shows how the improvements in precipitation translated into modelled discharge for Passau, which was one of the most severely hit locations. Even though the flood peak becomes closer to the hydrograph modelled with observed precipitation, it is still far off. However, this is result for one station for a single model run, and to really assess the impact of the model improvements, more cases are needed. It also highlights the importance of ensemble forecasting for specific watersheds; even it the precipitation over a large region is well captured, spatial variations in the precipitation field can mean the difference between a flood or not.
These experiments have shown that improvements in resolution and model physics will lead to also better forecasts of extreme events and we can expect that this will lead to better forecasts in the future. However, this is one case study, and one caveat of tuning the model for a specific event is that it can yield unwanted effects in other situations. More studies on similar events are called for to show the numerical weather modeling community the need to improve forecasts of extreme events.
Haiden, T., Magnusson, l., Tsonevsky, I., Wetterhall, F., Alfieri, L., Pappenberger, F., de Rosnay, P., Muñoz-Sabater, J., Balsamo, G., Albergel, C., Forbes, R., Hewson, T., Malardel, S., Richardson, D., 2014, ECMWF forecast performance during the June 2013 flood in Central Europe, ECMWF Technical Memoranda, 723, 34 pp, Reading, United Kingdom.
Khairoutdinov, M., and Y. Kogan, 2000: A new cloud physics parameterization in a large-eddy simulation model of marine stratocumulus. Mon. Wea. Rev., 128, 229-243.
Sundqvist, H., 1978: A parameterization scheme for non-convective condensation including prediction of cloud water content. Quart. J. Roy. Meteor. Soc., 104, 677-690.