Assessing the predictability of Medicanes in ECMWF ensemble forecasts using an object‐based approach

Abstract

The predictability of eight southern European tropical‐like cyclones – seven Medicanes and the first‐ever documented case of such a storm in the Bay of Biscay – is studied evaluating European Centre for Medium‐Range Weather Forecasts (ECMWF) operational ensemble forecasts against operational analysis data. Forecast cyclone trajectories are compared with the cyclone trajectory in the analysis by means of a dynamic time warping technique, which allows one to find a match in terms of their overall spatio‐temporal similarity. Each storm is treated as an object and its forecasts are analysed using parameters that describe intensity, symmetry, compactness and upper‐level thermal structure. This object‐based approach allows one to focus on specific storm features, while tolerating their shifts in time and space to some extent. The high compactness and symmetry of the storms are generally poorly predicted, especially at long lead times. However, forecast accuracy tends to improve strongly at short lead times, indicating that the ECMWF ensemble forecast model can adequately reproduce Medicanes, albeit only a few days in advance. In particular, late forecasts which have been initialised when the cyclone has already developed are distinctly more accurate than earlier forecasts in predicting its kinematic and thermal structure, confirming previous findings of high sensitivity of Medicane simulations to initial conditions. Findings reveal a markedly non‐gradual evolution of ensemble forecasts with lead time, which is often far from a progressive convergence towards the analysis value. Specifically, a rapid increase in the probability of cyclone occurrence (a “forecast jump”) is seen in most cases, generally with lead times between 5 and 7 days. Jumps are also found for the forecast distribution of storm thermal structure. This behaviour is consistent with the existence of predictability barriers. On the other hand, storm position forecasts often exhibit a consistent spatial distribution of storm position uncertainty and bias between consecutive forecasts.

How an uncertain short-wave perturbation on the North Atlantic wave guide affects the forecast of an intense Mediterranean cyclone (Medicane Zorbas)

“…This indicates that other synoptic-scale aspects related to the PV streamer, for example uncertainty in its position, shape, or intensity, limited the predictability of the medicane (similar to Maier-Gerber et al, 2019, for a tropical transition over the North Atlantic). The existence of several "stages" in cyclone predictability is consistent with the systematic analysis of the predictability of recent medicanes by Di Muzio et al (2019), which showed that such "forecast jumps" occur with different lead times for different forecast parameters. For example, rapid increases in the probability of cyclone occurrence can be found with longer lead times (4-7 d before the mature phase of the medicane) than rapid decreases in the spread of cyclone position (2-5 d) and of the strength of the upper-level warm core (initializations after cyclogenesis).…”

“…According to the CPS (Fig. 3b), Zorbas formed as a cold-core cyclone and within 18 h acquired a deep warm core that was sustained for more than 3 d. This is comparable to the January 1982 case investigated by Picornell et al (2014) but substantially longer than for all eight recent medicane cases investigated by Di Muzio et al (2019) using the same dataset. Zorbas reached its maximum intensity (992 hPa) only 12 h after cyclogenesis.…”

Multi-Physics Ensemble versus Atmosphere–Ocean Coupled Model Simulations for a Tropical-Like Cyclone in the Mediterranean Sea

“…However, despite the scientific efforts emerging in a variety of sensitivity studies, even now NWP models suffer from a significant forecast skill reduction in the simulation of MTLCs, as they sometimes intensify the cyclone in an unrealistic way, or fail to foresee its development and evolution accurately. This predictability limitation depends on many factors and varies from case to case [13]. In some events, a large sensitivity to the location of the model domain and to the horizontal grid resolution [14] is observed, while in other cases parameterization schemes play a fundamental role [15][16][17].…”

Mediterranean Tropical-Like Cyclones (Medicanes)

“…Recent papers have clarified some peculiar aspects of Medicanes, from the mechanisms of development to their predictability [15], including the sensitivity of numerical simulations to different parameterization schemes. However, additional studies are necessary to provide a comprehensive picture for this particular category of cyclones.…”