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Adapting rain data for hygrothermal models
Authors:Steve Cornick  W Alan Dalgliesh
Affiliation:1. National Research Council of Canada, Institute for Research in Construction Building M-24, Montreal Road Campus, 1200 Montreal Road, Ottawa, Ontario, Canada K1A 0R6;2. National Research Council of Canada, Institute for Research in Construction (retired), 237 Valley Ridge Green N. W., Calgary AB, Canada T3B 5L6
Abstract:Design for moisture control has now become an established part of building envelope design. Hygrothermal modeling tools, capable of simulating moisture transfer in materials, are a key element of the design process. There are three principle methods of moisture transfer in envelopes. They are, in order of magnitude, capillary action, vapour convection, and vapour diffusion. Wind-driven rain has the potential to deposit large amounts of liquid water on the exterior surface, as well inside walls through rain penetration, providing a significant source for moisture transport. Most hygrothermal models are capable of handling wind-driven rain impinging on or penetrating the surface of the envelope. Correct results presuppose the availability of reliable rain intensity data. Many data sets, however, do not record hourly rain intensities but qualitative intensities such as light, moderate, or heavy. This paper examines several methods for assigning quantitative values to weather observations available in Canada. Real data, such as data from rain gauges, is preferable although the latter have shortcomings. Differences in catch can be up to 50% depending on gauge type, size, and exposure. When only rain codes are available the values recommended by the local meteorological service can provide adequate estimates. In case where there is observer bias a better estimate can be obtained by adjusting the value for light rainfall. If very little information is available stochastic modeling of rainfall is possible though the accuracy, especially for individual months is low.
Keywords:Hygrothermal-simulation  Modeling  Moisture  Building envelope  Wind-driven rain  Climate  Stochastic modeling
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