Climate data for moisture simulations: producing a Danish moisture reference year and comparison with previously used reference year locations

Abstract

Buildings comprise of complex systems, and various materials in combination. Different materials have different expected service life, and degradation processes start as soon as a building is put into operation. Degradation processes are often accelerated with the presence of moisture. To build robust and moisture safe buildings, hygrothermal simulations are used to predict hygrothermal conditions in constructions, and especially areas of risk. Simulations are useful tools for prediction of moisture accumulation, and results can further help predict the risk of moisture damage, i.e., frost damage or mould growth. The external climate can therefore have a significant impact on the service life of constructions. Due to the lack of a sufficient Danish climate reference year, including precipitation, hygrothermal simulations of Danish constructions are currently performed with either Danish climate data without precipitation (primarily for energy and indoor climate conditions), or with climate data from closest locations in either Sweden or Germany which include rain. Therefore, a complete Danish reference year, including precipitation, will inevitably enhance the value of hygrothermal simulations of buildings in Denmark. This paper presents the method used to develop full climate datasets based on Danish conditions, including precipitation. To integrate the climate datasets in the hygrothermal simulation programs, the climate datasets contain the following parameters: temperature, relative humidity, wind direction and speed, solar radiation, rain, as well as estimations for cloud cover and longwave radiation based on the other climate parameters. The climate datasets generated and presented in this paper, represent a Typical Meteorological Year (TMY), without extreme events, generated according to EN ISO 15927-4:2006. The climate datasets are based on Danish climate data from the period 2001-2019, provided by the Danish Meteorological Institute, DMI. By prioritizing climate parameters, and through statistical analysis, representative 1-year reference climate datasets were generated based on Danish climate conditions. The climate parameters of the 1-year reference climate datasets are compared with the traditionally used Swedish and German datasets, and a Danish Design Reference Year (DRY) from 1995.