Increases in Future AR Count and Size: Overview of the ARTMIP Tier 2 CMIP5/6 Experiment

O’Brien, T. A.; Wehner, Michael; Payne, Ashley E.; Shields, Christine A.; Rutz, Jonathan J.; Leung, L. Ruby; Ralph, F. Martin; Collow, Allison B. Marquardt; Gorodetskaya, Irina; Guan, Bin; Lora, Juan M.; McClenny, Elizabeth; Nardi, Kyle M.; Ramos, Alexandre M.; Tomé, Ricardo; Sarangi, Chandan; Shearer, E. J.; Ullrich, P. A.; Zarzycki, Colin M.; Loring, Burlen; Huang, Huanping; Díaz, Héctor Alejandro Inda; Rhoades, Alan M.; Yang, Zhiyong

doi:10.1029/2021jd036013

Cited by 56 publications

(70 citation statements)

References 109 publications

(214 reference statements)

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“…One should note that the use of time-dependent thresholds can automatically remove the effect of increased background moisture caused by global warming, because the IVT threshold is defined by percentile calculated in space rather than in time. O'Brien et al (2021) found that the ARs detected by these two algorithms behave differently from other algorithms in a warmer climate (see discussion in Section 3.4). While the main focus is the fixed IVT threshold used in Mundhenk et al (2016), we also discuss ToE sensitivity to these different algorithms and the impact of time-dependent thresholds in Section 3.4.…”

Section: Ar Detectionmentioning

confidence: 94%

When Will Humanity Notice Its Influence on Atmospheric Rivers?

et al. 2022

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Atmospheric rivers (ARs), river-like plumes of intense atmospheric moisture transport (Newell et al., 1992) typically associated with extratropical cyclones (Zhang et al., 2019), are known for their great socioeconomic impacts worldwide. ARs occur less than 10% of the time but account for more than 30% of the annual precipitation over some populated mid-latitude regions, such as the West Coast of the United States and Western Europe, which indicates both their water resource value and the potential hazards of landfalling ARs (Dettinger, 2013;Slinskey et al., 2020). For example, in 2016-2017, a series of AR events terminated a multi-year drought in California (White et al., 2019). However, ARs also contribute to more than 84% of flash flood damage in the West Coast of the United States (Corringham et al., 2019), which is one of the most costly natural disasters. In addition to the local impacts, ARs play an important role in global climate. ARs determine about 90% of pole-ward moisture transport (Zhu & Newell, 1998), which is one potential driver of Arctic amplification through modulation of the energy and moisture budgets around polar regions (Nash et al., 2018). Due to the important role of ARs

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Section: Ar Detectionmentioning

confidence: 94%

When Will Humanity Notice Its Influence on Atmospheric Rivers?

et al. 2022

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“…Although global metrics are presented in this work, the primary purpose is to provide quality control between Tier 1 (MERRA‐2 Reanalysis, herein referred to as T1‐MERRA‐2) and Tier 2 (T2‐HR model simulations) as well as context for other ARTMIP experiments, both reanalysis and CMIP5/6 experiments (O’Brien et al., 2022; Collow et al., 2022). Although O’Brien et al.…”

Section: Data and Approachmentioning

confidence: 99%

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

Shields

Payne

Shearer

et al. 2023

Geophysical Research Letters

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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.

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“…Furthermore, we acknowledge that AR statistics may depend on detection algorithms, and IVT-magnitude-based methods have limitations to detect and track ARs globally. Various AR detection algorithms show different pros and cons (Collow et al, 2022;O'Brien et al, 2022;Shields et al, 2018). To examine the detection algorithm dependency issue, we also tracked ARs using the TEMPEST algorithm (McClenny et al, 2020), which is one of the algorithms in the AR tracking method intercomparison project (ARTMIP) (Shields et al, 2018).…”

Section: Ars Detection Algorithmmentioning

confidence: 99%

Improved Simulations of Atmospheric River Climatology and Variability in High‐Resolution CESM

Liu

Chang

et al. 2022

J Adv Model Earth Syst

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Atmospheric rivers (ARs), referring to long and narrow filamentary bands of intense water vapor transport in the atmosphere, can cause extreme precipitation, floods, and drought events. Their variability has been linked to various climate modes, such as El Niño/Southern Oscillation, Pacific Decadal Oscillation, and Pacific‐North America pattern. Understanding and improving simulation of this linkage can provide the potential to predict ARs at subseasonal‐to‐decadal timescales. Up to now, the extent to which climate model simulations of ARs are dependent on model resolutions has not been fully assessed. Here, we compare and evaluate ARs in a pair of high‐resolution (HR) and a low‐resolution (LR) Community Earth System Model (CESM) simulations against the observations. The results show that within this CESM framework, climatological AR strength and associated precipitation are severely underestimated by LR compared to the observations, and their relationships with major modes of climate variability are also poorly reproduced. These deficiencies in LR are alleviated to a significant extent in HR. Using a linear regression analysis, we show that HR is able to capture with high fidelity the observed relationships between ARs and major climate modes in the Northern Hemisphere at seasonal‐to‐decadal time scales. These results suggest that the use of HR CESM may potentially lead to an improved forecast skill of ARs at season‐to‐decadal time scales.

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Increases in Future AR Count and Size: Overview of the ARTMIP Tier 2 CMIP5/6 Experiment

Cited by 56 publications

References 109 publications

When Will Humanity Notice Its Influence on Atmospheric Rivers?

When Will Humanity Notice Its Influence on Atmospheric Rivers?

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

Improved Simulations of Atmospheric River Climatology and Variability in High‐Resolution CESM

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