  In building studies dealing about energy efficiency and comfort, simulation
software need relevant weather files with optimal time steps. Few tools
generate extreme and mean values of simultaneous hourly data including
correlation between the climatic parameters. This paper presents the C++
Runeole software based on typical weather sequences analysis. It runs an
analysis process of a stochastic continuous multivariable phenomenon with
frequencies properties applied to a climatic database. The database analysis
associates basic statistics, PCA (Principal Component Analysis) and automatic
classifications. Different ways of applying these methods will be presented.
All the results are stored in the Runeole internal database that allows an easy
selection of weather sequences. The extreme sequences are used for system and
building sizing and the mean sequences are used for the determination of the
annual cooling loads as proposed by Audrier-Cros (Audrier-Cros, 1984). This
weather analysis was tested with the database of the French weather forecast
utility Meteo France. Reunion Island experiences a lot of different
micro-climates due to the high altitude (3069m), specific relief, and
geographic situation (Tropic of Capricorn). Furthermore Reunion Island has the
densest meteorological network in France and is an ideal place to validate the
methodology with different climates. To test the efficiency of such analysis,
simulations using the resulting weather sequences were carried out with the
building simulation software CODYRUN. This analysis is the first step of a more
global research concerning weather data generation. Future work will permit
whole hourly typical meteorological year generation using neural networks.
