Can a real-time 3-km model of the Alps region help decipher observed complex phenomena and improve numerical weather prediction of heavy precipitation? D uring the Special Observation Period (SOP; 7 Sep-15 Nov 1999) of the Mesoscale Alpine Programme (MAP) (Bougeault et al. 2001), the Canadian Mesoscale Compressible Community Model (MC2) was run in a real-time Numerical Weather Prediction (NWP) mode. The goals of this effort were (i) to provide real-time high-resolution forecasts in support of the field phase, and (ii) to gain early experience with a next-generation nonhydrostatic numerical model in a forecast mode.

Just as in other state-subsidized service areas, in the field of aviation weather there is political pressure as well as a growing economic need to substantiate or at least evaluate the economic benefits of meteorological information. The research presented in this paper has been conducted as part of a broad study concerning the economic benefits of the meteorological services in the Swiss transport sector. For the aviation sector, interviews revealed that meteorological information is a pivotal input factor in the decision-making process of airlines: In addition to security and safety purposes, airlines use meteorological information to optimize the economic efficiency of daily operations as well as for strategic decisions regarding flight routes and flight planning. In this paper a decision-making model is used to evaluate at least part of the economic benefits of the meteorological services to Switzerland’s domestic airlines by analyzing the use of terminal aerodrome forecasts (TAF) at Zurich Airport (Switzerland). By lowering the probability of costly wrong decisions, meteorological information generates direct economic benefits for the airlines. The total benefits for all domestic airlines at Zurich Airport amount to between 11 and 17 million Swiss francs per year [12 to 18 million USD; 1 U.S. dollars (USD) = 0.934 Swiss francs (CHF), average exchange rate 2012]. By extrapolating the results based on the number of flights, the total economic benefits of TAF to Switzerland’s domestic airlines at both main Swiss airports (Zurich and Geneva) add up to somewhere between 13 and 21 million Swiss francs per year (14 to 22 million USD).

Meteorological services involve the provision of information on the state of the atmosphere and the ground surface. They provide data, information, forecasts and various related products, which are important for the smooth functioning of many aspects of the economy, government and society. The economic value or benefit of weather forecasts consists in generally improving financial and related outcomes resulting from the use of such forecasts. The merit of meteorological services cannot directly be deduced from the consumption of services. Rather, it emerges from the improvement of decisions made by economic stakeholders thanks to weather-related information. This is the first empirical study on this topic for Switzerland which includes economic data from interviewed users. The results show that the use of meteorology in the road transportation sector in Switzerland generates an economic benefit to the national economy of 65.7-79.77 million Swiss francs (1 Swiss franc ∼0.90 ¤, 1.20 US$ as of August 2011). In relation to its budget the overall benefit to the national meteorological service might be several times that amount, considering that many other economic sectors such as agriculture, aviation, construction, energy, media and tourism were not included in this study. Furthermore, climate services were not taken into account in this study and, therefore, the economic benefit for the road traffic sector alone might in fact be even higher.

<p>At the Swiss Federal Office of Meteorology and Climatology MeteoSwiss, the main goal of our warning system is to support the affected population and organizations in the best possible way to take the necessary measures to reduce the impact of extreme weather events. How can we measure whether our warnings achieve this goal and create societal value? A classical way of assessing the success of a warning system is to calculate the hit rate and false alarm rate. While this is very important, it is just a first step in measuring the value of the warning. Even the most perfect warning is not a guarantee for a reduction of the impact of the warned extreme event. A next step would be to assess how many individuals of the target group were reached and whether they were satisfied with the warnings and understood the information. However, the number of people reached and their average satisfaction alone still do not indicate how successful our warnings are. What we ultimately would like to know is whether our warnings lead to improved risk assessment, behavioural change and finally, to reduced costs and damages through extreme weather.</p><p>This contribution presents a concept for a standardized population survey that aims to provide quantifiable measures on the social impact of the warning. By drawing from methods of impact assessment in the non-profit sector, we differentiate between output, outcome and impact of our warnings and derive indicators for each of these levels. Data for these indicators will be collected through representative population surveys in the affected regions a few days after an extreme weather event occurred. During a pilot phase to be launched in fall of this year, we will assess the potential of these indicators and of different data collection methods (representative online survey vs. representative telephone interviews vs. online survey with users of our channels). Although data will not be available yet at the time of the conference, the presentation aims to present our approach and discuss opportunities as well as challenges and limits of measuring the value of our warnings by using event-based surveys.</p>

At MeteoSwiss, we are currently developing a modular framework to automatically identify extreme weather events that will allow us to generate a broad range of user-tailored warning products. Here, we introduce this Extreme Weather Identifier (EWI) framework in the context of public warnings, namely warning polygon proposals for forecasters to support them in issuing public warnings of high quality in a timely manner. The EWI translates NWP ensemble forecasts into warning products – in our case, warning polygon proposals – by employing a pre-defined sequence of processing steps with configurable parameters. By applying grid-point-specific warning thresholds to each NWP ensemble member, it obtains local-scale warning information and by aggregating the underlying information in space and time, it accounts for spatio-temporal representativeness issues and facilitates communication. In a first aggregation step, the spatio-temporal representativeness issues are addressed by employing neighborhood approaches to detect extreme weather in each ensemble member individually. Subsequently, all members are evaluated jointly in order to assess the probability that the extreme weather actually takes place. Afterwards, areas exceeding a minimal probability threshold are grouped together into individual regionally-valid warning polygons. At this point, the communication-motivated aggregation to the visual scale of interest starts and all further changes simply serve the goal to produce warning products that can be easily communicated to their target audience without any additional physical justifications. To allow the forecasters to obtain an in-depth understanding of the EWI’s proposals and thoroughly assess their quality, not only the proposals themselves will be distributed but also outcomes of key intermediate steps of the EWI’s processing sequence. Products covering the EWI’s processing steps until the communication-motivated aggregation starts are intended to be made available to forecasters in real-time towards the end of this year and we will illustrate them in this contribution with examples from past warning events.