Climate Simulation of an Attic Using Future Weather Data Sets - Statistical Methods for Data Processing and Analysis
The effects of possible climate changes on a cold attic performance are considered in this work. The hygro-thermal responses of the attic to different climate data sets are simulated using a numerical model, which has been made using the International Building Physics Toolbox (IBPT).
Cold attic, which is the most exposed part of the building to the environment, is classified as a risky construction in Sweden. Mould growth on internal side of the attic roof, due to condensation of water vapor from the surrounding environment has been increasing over the last decade, and thereby the risk for degrading the performance of construction.
The attic studied in this work is a naturally ventilated space under a pitched roof on top of a 2 storey building. Climate inside the attic has been simulated using different weather data sets for the period of 1961-2100 in four cities of Sweden: Gothenburg, Lund, Stockholm and Östersund. The weather data sets, which are the results of climate simulations, enclose different uncertainties. The uncertainties related to differences in spatial resolutions, global climate models (GCMs), CO2 emission scenarios and initial conditions are considered here. At the end enormous climate data sets are used in this study.
Analysis of the long term climate data demands suitable statistical methods. Two methods have been applied from meteorology: a nonparametric method for assessing the data without tracking of time, and a parametric method for decomposition of the parameter variabilities into three constructive parts. Looking into the decomposed components of the parameter and its variabilities enables to analyze the data with different time resolutions.
Applying the selected statistical methods helps in understanding of the importance of different uncertainties of the weather data and their effects on the attic simulation.