Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High‐Resolution Global Warming Experiment

Abstract

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth's hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.Plain Language Summary Atmospheric rivers (ARs) are long and narrow weather features often referred to as "rivers in the sky." They often transport water from lower latitudes to higher latitudes typically across climate zones and produce precipitation necessary for local climates. Understanding ARs in a warming climate is challenging because of the variety of ways an AR can be defined on gridded data sets. Unlike weather features such as tropical cyclones where identification methodologies are similar, algorithms that determine the characteristics of ARs vary depending on the science question posed. Because there is no real consensus on AR identification methodology, we aim to quantify the algorithmic uncertainty in AR metrics and precipitation. We compare 16 different ways of defining an AR on gridded data sets and present the range of possibilities in which an AR could change under global warming. Generally, ARs are projected to increase but the amount SHIELDS ET AL.

Recreating the California New Year's Flood Event of 1997 in a Regionally Refined Earth System Model

“…We used TempestExtremes (TE; namely the SpineARs and StitchBlobs algorithms) to detect the primary AR that made landfall during the 1997 flood on 1 January 1997 (Ullrich & Zarzycki, 2017; Zarzycki & Ullrich, 2017). AR detectors (ARDTs) are broadly categorized as either absolute or relative threshold approaches (O'Brien et al., 2022; Shields et al., 2023). Fixed threshold ARDTs use a target variable (e.g., integrated vapor transport) and a threshold of exceedance (e.g., ≥250 kg/m/s) to identify if an AR emerges from background atmospheric conditions.…”

Polar Aerosol Atmospheric Rivers: Detection, Characteristics, and Potential Applications

“…This trend makes it hard to untangle changes in circulation from changes in atmospheric water vapor content when exploring current and future trends in ARs (Bintanja et al, 2020;Rinke et al, 2019). In addition, the AR response to future climate change is highly dependent on the chosen detection tool (O'Brien et al, 2022;Shields et al, 2023). For natural aerosols, the emission sources are not expected to feature strong trends in future scenarios, although more sea salt (Lapere et al, 2023) and possibly slightly more dust (Zhou et al, 2023) can be expected under a changing climate.…”

Large‐Scale Circulation Context for North American West Coast Atmospheric Rivers: Influence of the Subseasonal NPO/WP Teleconnection

“…It is noted that AR characteristics may be sensitive to the AR detection method used (Collow et al, 2022;O'Brien et al, 2022;Rutz et al, 2019;Shields et al, 2018Shields et al, , 2023, and AR detection methods could be sensitive to the input data product, including its resolution. The detection method used in the current AR database is found to be particularly robust to the input data (Collow et al, 2022, their Figures 3 and 4), as will also be illustrated here.…”