Simple physics-based adjustments reconcile the results of Eulerian and Lagrangian techniques for moisture tracking in atmospheric rivers

Abstract

The increase in the number and quality of numerical moisture tracking tools has greatly improved our understanding of the hydrological cycle in recent years. However, the lack of observations has prevented a direct validation of these tools, and it is common to find large discrepancies among the results produced by them, especially between Eulerian and Lagrangian methodologies. Here, we evaluate two diagnostic tools for moisture tracking, the Sodemann et al. (2008) and the Dirmeyer and Brubaker (1999) methodologies, using simulations from the Lagrangian model FLEXPART. We assess their performance against the Weather Research and Forecasting (WRF) model with Eulerian Water Vapor Tracers (WRF-WVTs). Assuming WRF-WVTs results as a proxy for reality, we explore the discrepancies between the Eulerian and Lagrangian approaches for five precipitation events associated with atmospheric rivers (ARs) and assess some physics-based adjustments to the Lagrangian tools. As in previous studies, we find a negative bias in the contribution of remote sources, such as tropical ones, and an overestimation of local contributions. Quantitatively, the mean absolute error skill score (MAESS) with respect to WRF-WVTs for contributions from selected source regions is 0.74 for the Sodemann et al. (2008) methodology and 0.77 for the Dirmeyer and Brubaker (1999) diagnostic tool. The implementation of simple and logical corrections leads to a significant improvement in both methodologies, as the skill score improves to 0.84 and 0.87, respectively. Although these modifications may need to be adjusted for other types of precipitation events, our results demonstrate that Lagrangian techniques are a viable and compatible alternative to Eulerian water vapor tracers, and that the main discrepancies between the different methodologies can be derived from the obviation of basic physical considerations that may be easily straightened out.