The monthly outlook is a forecast of temperature and precipitation trends for the next three weeks. Predictions are made on average weather development, as opposed to those made on individual weather events in forecasts for the next few days.
Monthly Outlook
The monthly outlook is generated for the three regions of northern and eastern Switzerland (Basel, Bern and Zurich stations), western Switzerland (Geneva Cointrin station) and southern Switzerland (Lugano). The outlook is updated twice a week, generally on a Tuesday and a Friday.
Temperature outlook for a week
The height of the coloured columns indicates the probability of the week in question being cool (blue), moderate (green) or warm (red) based on a comparison of the same week over many years. A probability of the weather being mild in northern and eastern Switzerland is shown as just under 60 percent for the week of 10th to 16th March 2014. In this case, the average temperature over seven days will be over 7.5 °C. The probability of moderate temperatures of between 4.4 °C and 7.5 °C occurring is around 40%, whereas lower temperatures are very unlikely. The additional error bars shown on each coloured bar show the variability range (uncertainty) for the forecast.
The temperatures ranges for three categories are determined on the basis of recorded temperatures over the past 20 years, and are calculated individually for each forecast week. For the selected forecast week in the middle of March, the long-term seven-day average temperature turned out to be between 4.4 °C and 7.5 °C. These values were determined so as to ensure that each of the three categories occured with equal frequency (shown by the grey horizontal line at 33.3 percent).
Technical information on long-range forecasting
In contrast to weather forecasts, long-range prognoses on climatic evolution are naturally beset by a high degree of uncertainty. Nevertheless, predictions can be made with regard to average values. This is done by running model simulations on high performance computers in order to quantify the range and probability of possible climatic conditions.