El Niño-Southern Oscillation and snow level in the western United States

Abstract

The relationship between El Niño–Southern Oscillation and the elevation of snow level in the western United States is established. Snow level variability is quantified from records of (1) wet‐bulb zero heights at ten rawinsonde sites (1957–2010), (2) empirically estimated snow levels over ten adjacent watersheds from precipitation and snowfall observations (∼1924–2009), and (3) 850–700 hPa thicknesses (1948–2010). The statistical relationship between these variables and the Southern Oscillation Index is established through the examination of the change in the empirical probability density function from moderate values of the Southern Oscillation Index to extreme values of the Southern Oscillation Index. For all data sources, results suggest that El Niño events are linked to higher snow levels across much of the western United States. Considering the known effects of El Niño on airflow over the western United States, the elevated snow levels are likely due to the more maritime characteristics of midlatitude cyclones. The strength of this signal decreases with distance from the Pacific Ocean and the southern Rockies display slightly decreased snow levels during El Niño events, likely due to the transition of maritime air masses to continental air masses. A snow covered area analysis derived from the Terra MODIS observations supports this El Niño signal in snow level. There is little evidence for a significant and spatially coherent La Niña relationship with snow level. This ENSO signal in snow level is apparent in the data with trend removed and for the cold and warm phases of the Pacific Decadal Oscillation.

Long Island Sound temperature variability and its associations with the ridge–trough dipole and tropical modes of sea surface temperature variability

“…More recently, a second study by Schulte et al (2018) found the EP-NP pattern to be a dominant pattern governing LIS water temperature variability. The EP-NP pattern was shown to be strongly correlated with LIS water tem-perature unlike the well-known North Atlantic Oscillation (NAO; Hurrell, 1995), Pacific North American (PNA; Wallace and Gutzler, 1981;Svoma, 2011), Arctic Oscillation (AO; Thompson and Wallace, 1998), and West Pacific (WP; Barston and Livezey, 1987;Linkin and Nigam, 2008) patterns. In fact, Schulte and Lee (2017) found that the EP-NP pattern is more strongly related to temperature variability across the northeast US than the AO, which is often associated with colder-than-normal conditions across the region (Wettstein and Mearns, 2002).…”

Long Island Sound Temperature Variability and its Associations with the Ridge-trough Dipole and Tropical Modes of Sea Surface Temperature Variability

“…The EP-NP pattern was shown to be strongly correlated with LIS water tem-J. A. Schulte and S. Lee: Long Island Sound temperature variability perature unlike the well-known North Atlantic Oscillation (NAO; Hurrell, 1995), Pacific North American (PNA; Wallace and Gutzler, 1981;Svoma, 2011), Arctic Oscillation (AO; Thompson and Wallace, 1998), and West Pacific (WP; Barston and Livezey, 1987;Linkin and Nigam, 2008) patterns. In fact, Schulte and Lee (2017) found that the EP-NP pattern is more strongly related to temperature variability across the northeast US than the AO, which is often associated with colder-than-normal conditions across the region (Wettstein and Mearns, 2002).…”

Mesoscale Variations of the Atmospheric Snow Line over the Northern Sierra Nevada: Multiyear Statistics, Case Study, and Mechanisms

“…Mountain snow line elevations, and hence the partitioning between rainfall and snowfall, are known to be sensitive to modes of interannual climate variability (e.g., Svoma 2011; Abatzoglou 2011) and show long-term trends (e.g., Knowles et al 2006;Svoma 2009) that have been attributed in part to anthropogenic climate change (Pierce et al 2008). The elevation of the surface transition between snowfall and rainfall-the mountainside snow line-plays a central role in determining roadway navigability, river runoff, freshwater resources, and hazards from landslides, avalanches, and floods.…”