Consensus and Disagreement in Atmospheric River Detection: ARTMIP Global Catalogues
The Science
From a climatological perspective, the average frequency of AR occurrence among the catalogs and its associated standard deviation indicate significant disagreement that warrants caution. However, the frequency of catalog majority-consensus AR conditions suggests a high degree of agreement in extratropical areas. The ensemble of methods shows that AR conditions robustly occur along five tracks over the extratropical oceans, with some extension into extratropical continents. Outside of these regions, AR detections are highly method dependent and should be treated with care. Two case studies of AR conditions over the North Pacific and the southern Indian Ocean in November 2006 illustrate when and where methods tend to agree or disagree. The main sources of discrepancy come from marginal features—that is, regions of modest IVT that may or may not be filamentary in structure and which tend to be associated with weak, decaying, or areas where the IVT gradients are shallow. Strong ARs, however, are robustly detected by the algorithms, and there is even general consensus on AR shape and inland penetration when IVT gradients are sufficiently sharp.
With a wide range of ARDTs represented in the literature, quantifying where methods agree and disagree, globally, is valuable for interpreting AR metrics and their context. With ARTMIP, we find that most methods tend to agree quantitatively for the frequency of occurrence when detecting moderate and stronger features. Disagreement typically occurs for regions with slightly enhanced vapor transport or weak ARs.
Atmospheric rivers (ARs) constitute an important mechanism for water vapor transport, but research on their characteristics and impacts has relied on a diverse assortment of detection methodologies, complicating comparisons. The AR Tracking Method Intercomparison Project (ARTMIP) provides a platform for comparing such methodologies, but analysis of ARTMIP catalogs has heretofore focused primarily on specific regions. Here we investigate ARs as detected by an ensemble of algorithms with global coverage. We find that the frequency of occurrence of the majority-consensus ARs produces a robust distribution, featuring five hot spots over the extratropical oceans, against which we compare individual algorithm results. We further explore the underlying similarities and differences via two case studies of AR evolution. The dominant source of disagreement between detection methodologies globally consists of detections (or lack thereof) of weak features, and the algorithms otherwise tend to agree remarkably well on the footprints of ARs.