Regime-Dependent Characteristics and Predictability of Cold-Season Precipitation Events in the St. Lawrence River Valley

被引:0
|
作者
Inters, Andrew C. [1 ]
Assill, Nick P. [2 ]
Yakum, John R. [3 ]
Inder, Justin R. [4 ]
机构
[1] Univ Colorado, Dept Atmospher & Ocean Sci, Boulder, CO 80309 USA
[2] SUNY Albany, State Weather Risk Commun Ctr, Albany, NY USA
[3] McGill Univ, Dept Atmospher & Ocean Sci, Montreal, PQ, Canada
[4] SUNY Albany, Dept Atmospher & Environm Sci, Albany, NY USA
基金
加拿大自然科学与工程研究理事会; 美国国家科学基金会;
关键词
Extratropical cyclones; Freezing precipitation; Forecasting; Clustering; FREEZING RAIN EVENTS; 1998 ICE STORM; EXTRATROPICAL CYCLONES; PHASE; CLIMATOLOGY; IMPACTS; SNOW; TEMPERATURE; PREDICTION; FORECASTS;
D O I
10.1175/WAF-D-23-0218.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The St. Lawrence River Valley experiences a variety of precipitation types (p-types) during the cold season, such as rain, freezing rain, ice pellets, and snow. These varied precipitation types exert considerable impacts on aviation, road transportation, power generation and distribution, and winter recreation and are shaped by diverse multiscale processes that interact with the region's complex topography. This study utilizes ERA5 reanalysis data, surface cyclone climatology, and hourly station observations from Montr & eacute;al, Qu & eacute;bec, and Burlington, Vermont, during October-April 2000-18 to investigate the spectrum of synoptic-scale weather regimes that induce cold-season precipitation across the St. Lawrence River Valley. In particular, k-means clustering and self-organizing maps (SOMs) are used to classify cyclone tracks passing near the St. Lawrence River Valley, and their accompanying thermodynamic profiles, fi les, into a set of event types that include a U.S. East Coast track, a central U.S. track, and two Canadian clipper tracks. Composite analyses are subsequently performed to reveal the synoptic-scale environments and the characteristic p-types that most frequently accompany each event type. Global Ensemble Forecast System version 12 (GEFSv12) reforecasts are then used to examine the relative predictability of cyclone characteristics and the local thermodynamic profile fi le associated with each event type at 0-5-day forecast lead times. The analysis suggests that forecasted cyclones near the St. Lawrence River Valley develop too quickly and are located left-of-track relative to the reanalysis on average, which has implications for forecasts of the local thermodynamic profile fi le and p-type across the region when the temperature is near 0 degrees C. degrees C. SIGNIFICANCE STATEMENT: Diverse precipitation types are observed when near-surface temperatures approach 0 degrees C degrees C during the cold season, especially across the St. Lawrence River Valley in southern Qu & eacute;bec. This study classifies fi es cold-season precipitation events impacting the St. Lawrence River Valley based on the track of storm systems across the region and quantifies fi es the average meteorological characteristics and predictability of each track. Our analysis reveals that forecasted low pressure systems develop too quickly and are left of their observed track 0-5 days prior to an event on average, which has implications for forecasted temperatures and the type of precipitation observed across the region. Our results can inform future operational forecasts of cold-season precipitation events by providing a storm focused perspective on forecast errors during these impactful events.
引用
收藏
页码:1353 / 1375
页数:23
相关论文
共 2 条
  • [1] Investigation of stability characteristics of cold-season convective precipitation events by utilizing the growth rate parameter
    Melick, Christopher J.
    Market, Patrick S.
    Smith, Larry L.
    Pettegrew, Brian P.
    Becker, Amy E.
    Lupo, Anthony R.
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2008, 113 (D8)
  • [2] Synoptic-Scale Characteristics and Precursors of Cool-Season Precipitation Events at St. John's, Newfoundland, 1979-2005
    Milrad, Shawn M.
    Atallah, Eyad H.
    Gyakum, John R.
    WEATHER AND FORECASTING, 2009, 24 (03) : 667 - 689