This paper documents the atmospheric-moisture-tracking model WAM2layers v3 (Water Accounting Model – 2 layers, version 3). WAM2layers may be used to gain an understanding of atmospheric dynamics and to study rainfall patterns and extremes by mapping their sources or sinks, often in the context of climate and land-use changes. To this end, WAM2layers solves a prognostic equation for tagged moisture in gridded atmospheric datasets such as reanalysis data or climate model output. WAM2layers can be used in forward mode, to determine where evaporated water eventually precipitates, or in backward mode, to determine where precipitation originally evaporated.

WAM2layers v3 represents a complete rewrite of the WAM2layers model originally introduced in 2010 and subsequently used in more than 60 academic studies. This latest version incorporates performance optimizations to cope with the increased resolution of input data and introduces various best practices aimed at improved user-friendliness and software sustainability. As an increasing number of researchers are using the code, this paper is intended as an updated description and reference in the academic literature. After describing the history, model formulation, and numerical implementation, we present and evaluate two example cases to illustrate the use and skill of WAM2layers v3. We then discuss best practices, some important assumptions, and directions for future development.

This manuscript documents the atmospheric moisture tracking model WAM2layers v3 (Water Accounting Model – 2 layers – version 3). WAM2layers may be used to gain understanding of atmospheric dynamics and to study rainfall patterns and extremes by mapping their sources or sinks, often in the context of climate and land-use changes. To this end, WAM2layers solves a prognostic equation for tagged moisture in gridded atmospheric datasets such as reanalysis data or climate model output. WAM2layers can be used in forward mode to determine where evaporated water eventually precipitates, or in backward mode to determine where precipitation originally evaporated.

WAM2layers v3 represents a complete rewrite of the WAM2layers model originally introduced in 2010 and subsequently used in more than sixty academic studies. This latest version incorporates performance optimisations to cope with the increased resolution of input data, and introduces various best practices aimed at improved user-friendliness and software sustainability. Since an increasing number of researchers is using the code, this manuscript is intended as an updated description and reference in the academic literature. After describing the history, model formulation, and numerical implementation, we present and evaluate two example cases to illustrate the use and skill of WAM2layers v3. We then discuss best practices, some important assumptions, and directions for future development.