A method to diagnose surface precipitation types is suggested. Most cases of freezing rain and ice pellets occur with a layer warmer than 0ЊC extending above a surface-based layer of air colder than 0ЊC. The procedure uses predictors proportional to the product of the mean temperature of a layer and its depth. These predictors can be seen as areas on aerological diagrams. A positive area is associated with a layer warmer than 0ЊC, conversely a negative area is associated with a layer colder than 0ЊC. The same predictor is used to discriminate snow from rain. A statistical analysis was applied using the North American aerological stations network to determine a set of criteria for discriminating freezing rain, ice pellets, snow, and rain. Once the criteria are known, the precipitation type can be easily diagnosed using temperature profiles from upper-air observations or from numerical weather prediction models. The method has been in operational use at the Canadian Meteorological Centre since 1995.

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Three radiological dispersal devices were detonated in 2012 under controlled conditions at Defence Research and Development Canada's Experimental Proving Grounds in Suffield, Alberta. Each device comprised a 35-GBq source of (140)La. The dataset obtained is used in this study to assess the MLCD, ADDAM, and RIMPUFF atmospheric dispersion models. As part one of a two-part study, this paper focuses on examining the capabilities of the above three models and evaluating how well their predictions of air concentration and ground deposition match observations from the full-scale RDD experiments.

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