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Moisture Transport during Large Snowfall Events in the New Zealand Southern Alps: The Role of Atmospheric Rivers

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  • 1 School of Earth and Environment, University of Canterbury, Christchurch, New Zealand
  • | 2 National Institute of Water and Atmospheric Research, Christchurch, New Zealand
  • | 3 Rainfall.NZ, Christchurch, New Zealand
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Abstract

Synoptic-scale moisture transport during large snowfall events in the New Zealand Southern Alps is largely unknown due to a lack of long-term snow observations. In this study, records from three recently developed automatic weather stations (Mahanga, Mueller Hut, and Mt Larkins) near the Main Divide of the Southern Alps were used to identify large snowfall events between 2010 and 2018. The large snowfall events are defined as those events with daily snow depth increase by greater than the 90th percentile at each site. ERA-Interim reanalysis data were used to characterize the hydrometeorological features of the selected events. Our findings show that large snowfall events in the Southern Alps generally coincide with strong fields of integrated vapor transport (IVT) within a northwesterly airflow and concomitant deepening low pressure systems. Considering the frequency of large snowfall events, approximately 61% of such events at Mahanga were associated with narrow corridors of strong water vapor flux, known as atmospheric rivers (ARs). The contributions of ARs to the large snowfall events at Mueller Hut and Mt Larkins were 70% and 71%, respectively. Analysis of the vertical profiles of moisture transport dynamics during the passage of a landfalling AR during 11–12 October 2016 revealed the key characteristics of a snow-generating AR in the Southern Alps. An enhanced presence of low- and midlevel moisture between 700 and 850 hPa and pronounced increases of wind velocities (more than 30 m s−1) with high values of the meridional component between 750 and 850 hPa were identified over the Southern Alps during the event.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Rasool Porhemmat, rasool.porhemmat@pg.canterbury.ac.nz

Abstract

Synoptic-scale moisture transport during large snowfall events in the New Zealand Southern Alps is largely unknown due to a lack of long-term snow observations. In this study, records from three recently developed automatic weather stations (Mahanga, Mueller Hut, and Mt Larkins) near the Main Divide of the Southern Alps were used to identify large snowfall events between 2010 and 2018. The large snowfall events are defined as those events with daily snow depth increase by greater than the 90th percentile at each site. ERA-Interim reanalysis data were used to characterize the hydrometeorological features of the selected events. Our findings show that large snowfall events in the Southern Alps generally coincide with strong fields of integrated vapor transport (IVT) within a northwesterly airflow and concomitant deepening low pressure systems. Considering the frequency of large snowfall events, approximately 61% of such events at Mahanga were associated with narrow corridors of strong water vapor flux, known as atmospheric rivers (ARs). The contributions of ARs to the large snowfall events at Mueller Hut and Mt Larkins were 70% and 71%, respectively. Analysis of the vertical profiles of moisture transport dynamics during the passage of a landfalling AR during 11–12 October 2016 revealed the key characteristics of a snow-generating AR in the Southern Alps. An enhanced presence of low- and midlevel moisture between 700 and 850 hPa and pronounced increases of wind velocities (more than 30 m s−1) with high values of the meridional component between 750 and 850 hPa were identified over the Southern Alps during the event.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Rasool Porhemmat, rasool.porhemmat@pg.canterbury.ac.nz
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