Atmospheric rivers (ARs) that reach the Antarctic Ice Sheet (AIS) transport anomalous moisture from lower latitudes and can impact the AIS via extreme precipitation and increased downward longwave radiation. ARs contribute significantly to the interannual variability of precipitation over the AIS and thus are likely to play a key role in understanding future changes in the surface mass balance of the AIS. Dronning Maud Land (DML) is one of four maxima in AR frequency over coastal East Antarctica, with AR precipitation explaining 77% of the interannual variability in precipitation for this region. We employ a 16‐node self‐organizing map (SOM) trained with MERRA‐2 sea‐level pressure anomalies to identify synoptic‐scale environments associated with landfalling ARs in and around DML. Node composites of atmospheric variables reveal common drivers of precipitation associated with ARs reaching DML including anomalous high‐low surface pressure couplets, anomalously high integrated water vapor, and coastal barrier jets. Using a quasi‐geostrophic framework, we find that upward vertical motion associated with the occlusion process of attendant cyclones dominates atmospheric lift in AR environments. We further identify mechanisms that explain the variability in AR precipitation intensity across nodes, such as the lift associated with the occlusion process of attendant cyclones and the spatial coincidence of ascent induced by the occlusion process and frontogenesis. The latter suggests that ARs making landfall during the mature phase of cyclogenesis result in higher precipitation intensity compared to landfalling ARs that occur during the occluded phase.
Antarctic atmospheric rivers (ARs) are driven by their synoptic environments and lead to profound and varying impacts along the coastlines and over the continent. The definition and detection of ARs over Antarctica accounts for large uncertainty in AR metrics, and consequently, impacts quantification. We find that Antarctic‐specific detection tools consistently capture the AR footprint inland over ice sheets, whereas most global detection tools do not. Large‐scale synoptic environments and associated ARs, however, are broadly consistent across detection tools. Using data from the Atmospheric River Tracking Method Intercomparison Project and global reanalyses, we quantify the uncertainty in Antarctic AR metrics and evaluate large‐scale environments in the context of decadal and interannual modes of variability. The Antarctic western hemisphere has stronger connections to both decadal and interannual modes of variability compared to East Antarctica, and the Indian Ocean Dipole’s influence on Antarctic ARs is stronger while in phase with El Nino Southern Oscillation.
more » « less- NSF-PAR ID:
- 10371923
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 49
- Issue:
- 16
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract The Antarctic ice sheet (AIS) is sensitive to short‐term extreme meteorological events that can leave long‐term impacts on the continent's surface mass balance (SMB). We investigate the impacts of atmospheric rivers (ARs) on the AIS precipitation budget using an AR detection algorithm and a regional climate model (Modèle Atmosphérique Régional) from 1980 to 2018. While ARs and their associated extreme vapor transport are relatively rare events over Antarctic coastal regions (∼3 days per year), they have a significant impact on the precipitation climatology. ARs are responsible for at least 10% of total accumulated snowfall across East Antarctica (localized areas reaching 20%) and a majority of extreme precipitation events. Trends in AR annual frequency since 1980 are observed across parts of AIS, most notably an increasing trend in Dronning Maud Land; however, interannual variability in AR frequency is much larger. This AR behavior appears to drive a significant portion of annual snowfall trends across East Antarctica, while controlling the interannual variability of precipitation across most of the AIS. AR landfalls are most likely when the circumpolar jet is highly amplified during blocking conditions in the Southern Ocean. There is a fingerprint of the Southern Annular Mode (SAM) on AR variability in West Antarctica with SAM+ (SAM−) favoring increased AR frequency in the Antarctic Peninsula (Amundsen‐Ross Sea coastline). Given the relatively large influence ARs have on precipitation across the continent, it is advantageous for future studies of moisture transport to Antarctica to consider an AR framework especially when considering future SMB changes.
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Abstract. Atmospheric rivers (ARs) transport large amounts of moisture from the mid- to high-latitudes and they are a primary driver of the most extremesnowfall events, along with surface melting, in Antarctica. In this study, we characterize the climatology and surface impacts of ARs on WestAntarctica, focusing on the Amundsen Sea Embayment and Marie Byrd Land. First, we develop a climatology of ARs in this region, using anAntarctic-specific AR detection tool combined with theModern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) atmospheric reanalyses. We find that while ARs are infrequent (occurring 3 % of the time), they cause intense precipitation in short periods of time and account for 11 % of the annual surface accumulation. They are driven by the coupling of a blocking high over the Antarctic Peninsula with a low-pressure system known as the Amundsen Sea Low. Next, we use observations from automatic weather stations on Thwaites Eastern Ice Shelf with the firn model SNOWPACK and interferometric reflectometry (IR) to examine a case study of three ARs that made landfall in rapid succession from 2 to 8 February 2020, known as an AR family event. While accumulation dominates the surface impacts of the event on Thwaites Eastern Ice Shelf (> 100 kg m−2 or millimeters water equivalent), we find small amounts of surface melt as well (< 5 kg m−2). The results presented here enable us to quantify the past impacts of ARs on West Antarctica's surface mass balance (SMB) and characterize their interannual variability and trends, enabling a better assessment of future AR-driven changes in the SMB.more » « less
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Abstract Atmospheric rivers (ARs) manifest as transient filaments of intense water vapor transport that contribute to synoptic‐scale extremes and interannual variability of precipitation. Despite these influences, the synoptic‐ to planetary‐scale processes that lead to ARs remain inadequately understood. In this study, North Pacific ARs within the November–April season are objectively identified in both reanalysis data and the Community Earth System Model Version 2, and atmospheric patterns preceding AR landfalls beyond 1 week in advance are examined. Latitudinal dependence of the AR processes is investigated by sampling events near the Oregon (45°N, 230°E) and southern California (35°N, 230°E) coasts. Oregon ARs exhibit a pronounced anticyclone emerging over Alaska 1–2 weeks before AR landfall that migrates westward into Siberia, dual midlatitude cyclones developing over southeast coastal Asia and the northeast Pacific, and a zonally elongated band of enhanced water vapor transport spanning the entire North Pacific basin that guides anomalous moisture toward the North American west coast. The precursor high‐latitude anticyclone corresponds to a significant increase in atmospheric blocking probability, suppressed synoptic eddy activity, and an equatorward‐shifted storm track. Southern California ARs also exhibit high‐latitude blocking but have an earlier‐developing and more intense northeast Pacific cyclone. Compared to reanalysis, Community Earth System Model Version 2 underestimates Northeast Pacific AR frequencies by 5–20% but generally captures AR precursor patterns well, particularly for Oregon ARs. Collectively, these results indicate that the identified precursor patterns represent physical processes that are central to ARs and are not simply an artifact of statistical analysis.
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