Consensus and Disagreement in Atmospheric River Detection: ARTMIP Global Catalogues

Abstract

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 catalogues 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. Plain Language Summary Atmospheric rivers-filamentary structures in the atmosphere in which water vapor is concentrated and transported-have received increasing attention over the past decade, but studies of their occurrence have relied on many disparate methods for objectively detecting them in various data sets. Here we explore the results of fourteen different such methods applied to the same data set, to better understand the resulting consensus or disagreement on atmospheric river occurrence, using both statistics from 37 years and two specific case studies. We find that most methods tend to agree quantitatively when detecting moderate and stronger features (in which the water vapor transport is high), and what appears to be significant disagreement is simply due to regions of only slightly enhanced vapor transport that are obviously disputable as true atmospheric rivers.

Uncertainties in Atmospheric River Lifecycles by Detection Algorithms: Climatology and Variability

“…This same finding is corroborated in Lora et al. (2020) who show that CONNECT500 detects the most false positives in the tropics compared to the community of ARTMIP ARDTs. They also show that the CONNECT and Tempest families exhibit a high level of disagreement with the ARDT ensemble mean in the mid‐latitudes due to more restrictive AR thresholds (see their Figure 3).…”

“…The climatological AR frequencies of these ARDTs are often larger within the tropics, which indicates that these ARDTs may include tropical features such as the Inter Tropical Convergence Zone (ITCZ) and other tropical disturbances (Figure ; also Figure 2 in Lora et al. (2020)).…”

“…The highest count is from CONNECT500 (#2), which captures some tropical disturbances that may not be associated with ARs or are entrained by ARs over their lifecycle (e.g., tropical cyclones) (Figure ; also in Lora et al. (2020)).…”

“…An example of the changes in object shape during an AR lifecycle is shown in Lora et al. (2020) (see their Figure 4). Guan_Waliser shows the largest spread in lifecycle intensity because of the use of a relative percentile threshold, which detects objects that possess weaker |IVT| over land and the polar regions.…”

Winter And Spring Atmospheric Rivers In High Mountain Asia: Climatology, Dynamics, And Variability

“…The latest version of this algorithm includes tracking capabilities from one 6-hour time step to the next (Guan and Waliser, 2019). This AR catalog has been used in many studies and is particularly useful in this study due to the global spatial scale and the application of relative methods for IVT intensity thresholds (Shields et al, 2018;Rutz et al, 2019;Lora et al, 2020). The European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses of the global climate (ERA5) is used here to examine geopotential height, winds, temperature at multiple pressure levels, as well as IVT and precipitation (Hersbach et al, 2020).…”