How Are Spring Snow Conditions in Central Canada Related to Early Warm-Season Precipitation?
被引:6
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作者:
Su, Hua
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Univ Texas Austin, Dept Geol Sci, John A & Katherine G Jackson Sch Geosci, Austin, TX 78712 USAUniv Texas Austin, Dept Geol Sci, John A & Katherine G Jackson Sch Geosci, Austin, TX 78712 USA
Su, Hua
[1
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Dickinson, Robert E.
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Univ Texas Austin, Dept Geol Sci, John A & Katherine G Jackson Sch Geosci, Austin, TX 78712 USAUniv Texas Austin, Dept Geol Sci, John A & Katherine G Jackson Sch Geosci, Austin, TX 78712 USA
Dickinson, Robert E.
[1
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Findell, Kirsten L.
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NOAA, Geophys Fluid Dynam Lab, Princeton, NJ USAUniv Texas Austin, Dept Geol Sci, John A & Katherine G Jackson Sch Geosci, Austin, TX 78712 USA
Findell, Kirsten L.
[2
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Lintner, Benjamin R.
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Rutgers State Univ, Dept Environm Sci, New Brunswick, NJ 08903 USAUniv Texas Austin, Dept Geol Sci, John A & Katherine G Jackson Sch Geosci, Austin, TX 78712 USA
Lintner, Benjamin R.
[3
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机构:
[1] Univ Texas Austin, Dept Geol Sci, John A & Katherine G Jackson Sch Geosci, Austin, TX 78712 USA
[2] NOAA, Geophys Fluid Dynam Lab, Princeton, NJ USA
[3] Rutgers State Univ, Dept Environm Sci, New Brunswick, NJ 08903 USA
The response of the warm-season atmosphere to antecedent snow anomalies has long been an area of study. This paper explores how the spring snow depth relates to subsequent precipitation in central Canada using ground observations, reanalysis datasets, and offline land surface model estimates. After removal of low-frequency ocean influences, April snow depth is found to correlate negatively with early warm-season (May-June) precipitation across a large portion of the study area. Achain of mechanisms is hypothesized to account for this observed negative relation: 1) a snow depth anomaly leads to a soil moisture anomaly, 2) the subsequent soil moisture anomaly affects ground turbulent fluxes, and 3) the atmospheric vertical structure allows dry soil to promote local convection. A detailed analysis supports this chain of mechanisms for those portions of the domain manifesting a statistically significant negative snow-precipitation correlation. For a portion of the study area, large-scale atmospheric circulation patterns also affect the early warm-season rainfall, indicating that the snow-precipitation feedback may depend on large-scale atmospheric dynamical features. This analysis suggests that spring snow conditions can contribute to warm-season precipitation predictability on a subseasonal to seasonal scale, but that the strength of such predictability varies geo-graphically as it depends on the interplay of hydroclimatological conditions across multiple spatial scales.
机构:
Penn State Univ, Ctr Adv Data Assimilat & Predictabil Tech, Dept Meteorol & Atmospher Sci, University Pk, PA 16801 USAPenn State Univ, Ctr Adv Data Assimilat & Predictabil Tech, Dept Meteorol & Atmospher Sci, University Pk, PA 16801 USA
Peng, Chin-Hsuan
Chen, Xingchao
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Penn State Univ, Ctr Adv Data Assimilat & Predictabil Tech, Dept Meteorol & Atmospher Sci, University Pk, PA 16801 USAPenn State Univ, Ctr Adv Data Assimilat & Predictabil Tech, Dept Meteorol & Atmospher Sci, University Pk, PA 16801 USA