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© Ragnar Ekker, The Norwegian Avalanche Warning Service | EAWS

Standards

EAWS Matrix

The EAWS Matrix is a tool introduced by the European Avalanche Warning Services with the goal of helping avalanche forecasters in determining the avalanche danger levels in a more objective way. The EAWS Matrix serves to standardize the avalanche danger level assessed and issued by the various warning services and is intended to exclude subjective influences as far as possible when forecasting avalanche danger.

matrix_workflow-EAWS Matrix matrix_workflow-EAWS Matrix

Figure 1: Updated EAWS Matrix (06/2022, General Assembly Davos).

The EAWS Matrix is used to determine the avalanche danger level based on the snowpack stability, frequency distribution of snowpack stability and avalanche size.

The forecaster first assesses snowpack stability and how frequent a specific class of snowpack stability (very poor, poor, or fair) is given by choosing a column  and a row (many, some, or few) that decribes combination of snowpack stability and frequency distribution for a specific avalanche problem best. Finally the forecaster assesses how large avalanches can become and chooses the corresponding chart within the current stability column and frequency row. See the workflow for a more detailed description of the assessment process.

The EAWS Matrix was obtained by a survey of numerous forecasters. Some fields contain two danger levels. The median danger level is indicated showing the integer value for each danger level (e.g., 1 for 1-Low)). If the distribution of responses was rather heterogeneous, a second value is shown in brackets, representing the interquartile range, if this value was different from the median danger level. When applying the EAWS Matrix (Figure 1), the forecaster should use the first danger level given in the cell. An optional danger level in parenthesis indicates that forecasters might disagree and a tendency towards a second danger level. These cells should be considered carefully and collected feedback on for future evaluation. For example, if the forecaster assessed that the dominant avalanche problem is best described by the factors poor stability on many slopes and avalanches up to size 3 are likely, the result would be danger level 4-High.

Please share your feedback, potential inconsitencies or disagreement with the Matrix with us.

For more details on the EAWS Matrix and its derivation see the explanations presented at the General Assembly in Davos 2022.

PDF files of the EAWS Matrix definitions as presented at general assembly in Davos (CH), 2022

Poster showing the derivation process and input from various warning services as presented at the general assembly in Davos (CH), 2022.