scholarly journals Multiscale Analysis of the 7 December 1998 Great Salt Lake–Effect Snowstorm

2001 ◽  
Vol 129 (6) ◽  
pp. 1296-1317 ◽  
Author(s):  
W. James Steenburgh ◽  
Daryl J. Onton
Keyword(s):  
Multiscale Analysis ◽  
Salt Lake ◽  
Great Salt Lake ◽  
Lake Effect

scholarly journals Great Salt Lake–Effect Precipitation: Observed Frequency, Characteristics, and Associated Environmental Factors

2012 ◽  
Vol 27 (4) ◽  
pp. 954-971 ◽  
Author(s):  
Trevor I. Alcott ◽  
W. James Steenburgh ◽  
Neil F. Laird
Keyword(s):  
Environmental Factors ◽  
Temperature Difference ◽  
Large Scale ◽  
Salt Lake ◽  
Great Salt Lake ◽  
Threshold Value ◽  
Substantial Improvement ◽  
Lake Area ◽  
Lake Effect ◽  
The Difference

Abstract This climatology examines the environmental factors controlling the frequency, occurrence, and morphology of Great Salt Lake–effect (GSLE) precipitation events using cool season (16 September–15 May) Weather Surveillance Radar-1988 Doppler (WSR-88D) imagery, radiosonde soundings, and MesoWest surface observations from 1997/98 to 2009/10. During this period, the frequency of GSLE events features considerable interannual variability that is more strongly correlated to large-scale circulation changes than lake-area variations. Events are most frequent in fall and spring, with a minimum in January when the climatological lake surface temperature is lowest. Although forecasters commonly use a 16°C lake–700-hPa temperature difference (ΔT) as a threshold for GSLE occurrence, GSLE was found to occur in winter when ΔT was only 12.4°C. Conversely, GSLE is associated with much higher values of ΔT in the fall and spring. Therefore, a seasonally varying threshold based on a quadratic fit to the monthly minimum ΔT values during GSLE events is more appropriate than a single threshold value. A probabilistic forecast method based on the difference between ΔT and this seasonally varying threshold, 850–700-hPa relative humidity, and 700-hPa wind direction offers substantial improvement over existing methods, although forecast skill is diminished by temperature and moisture errors in operational models. An important consideration for forecasting because of their higher precipitation rates, banded features—with a horizontal aspect ratio of 6:1 or greater—dominate only 20% of the time that GSLE is occurring, while widespread, nonbanded precipitation is much more common. Banded periods are associated with stronger low-level winds and a larger lake–land temperature difference.

scholarly journals Climatology of Lake-Effect Snowstorms of the Great Salt Lake

2000 ◽  
Vol 128 (3) ◽  
pp. 709-727 ◽  
Author(s):  
W. James Steenburgh ◽  
Scott F. Halvorson ◽  
Daryl J. Onton
Keyword(s):  
Salt Lake ◽  
Great Salt Lake ◽  
Lake Effect

scholarly journals Impact of Microphysics Parameterizations on Simulations of the 27 October 2010 Great Salt Lake–Effect Snowstorm

2015 ◽  
Vol 30 (1) ◽  
pp. 136-152 ◽  
Author(s):  
John D. McMillen ◽  
W. James Steenburgh
Keyword(s):  
Salt Lake ◽  
Weather Prediction ◽  
Great Salt Lake ◽  
Wrf Model ◽  
Moist Convection ◽  
Lake Effect ◽  
Simulated Precipitation ◽  
Precipitation Estimates ◽  
Double Moment ◽  
Microphysical Processes

Abstract Simulations of moist convection at cloud-permitting grid spacings are sensitive to the parameterization of microphysical processes, posing a challenge for operational weather prediction. Here, the Weather Research and Forecasting (WRF) Model is used to examine the sensitivity of simulations of the Great Salt Lake–effect snowstorm of 27 October 2010 to the choice of microphysics parameterization (MP). It is found that the simulated precipitation from four MP schemes varies in areal coverage, amount, and position. The Thompson scheme (THOM) verifies best against radar-derived precipitation estimates and gauge observations. The Goddard, Morrison, and WRF double-moment 6-class microphysics schemes (WDM6) produce more precipitation than THOM, with WDM6 producing the largest overprediction relative to radar-derived precipitation estimates and gauge observations. Analyses of hydrometeor mass tendencies show that WDM6 creates more graupel, less snow, and more total precipitation than the other schemes. These results indicate that the rate of graupel and snow production can strongly influence the precipitation efficiency in simulations of lake-effect storms, but further work is needed to evaluate MP-scheme accuracy across a wider range of events, including the use of aircraft- and ground-based hydrometeor sampling to validate MP hydrometeor categorization.

Utah's Great Salt Lake a classic Lake Effect Snowstorm

Weatherwise ◽  
1985 ◽  
Vol 38 (6) ◽  
pp. 309-311
Author(s):  
David M. Carpenter
Keyword(s):  
Salt Lake ◽  
Great Salt Lake ◽  
Lake Effect

scholarly journals Contributions of Lake-Effect Periods to the Cool-Season Hydroclimate of the Great Salt Lake Basin

2013 ◽  
Vol 52 (2) ◽  
pp. 341-362 ◽  
Author(s):  
Kristen N. Yeager ◽  
W. James Steenburgh ◽  
Trevor I. Alcott
Keyword(s):  
Snow Water Equivalent ◽  
Salt Lake ◽  
Great Salt Lake ◽  
Hypersaline Lake ◽  
Lake Basin ◽  
Cool Season ◽  
Lake Effect ◽  
Precipitation Estimates ◽  
Radar Imagery ◽  
Precipitation Gauge

AbstractAlthough smaller lakes are known to produce lake-effect precipitation, their influence on the precipitation climatology of lake-effect regions remains poorly documented. This study examines the contribution of lake-effect periods (LEPs) to the 1998–2009 cool-season (16 September–15 May) hydroclimate in the region surrounding the Great Salt Lake, a meso-β-scale hypersaline lake in northern Utah. LEPs are identified subjectively from radar imagery, with precipitation (snow water equivalent) quantified through the disaggregation of daily (i.e., 24 h) Cooperative Observer Program (COOP) and Snowpack Telemetry (SNOTEL) observations using radar-derived precipitation estimates. An evaluation at valley and mountain stations with reliable hourly precipitation gauge observations demonstrates that the disaggregation method works well for estimating precipitation during LEPs. During the study period, LEPs account for up to 8.4% of the total cool-season precipitation in the Great Salt Lake basin, with the largest contribution to the south and east of the Great Salt Lake. The mean monthly distribution of LEP precipitation is bimodal, with a primary maximum from October to November and a secondary maximum from March to April. LEP precipitation is highly variable between cool seasons and is strongly influenced by a small number of intense events. For example, at a lowland (mountain) station in the lake-effect-precipitation belt southeast of the Great Salt Lake, just 12 (13) events produce 50% of the LEP precipitation. Although these results suggest that LEPs contribute modestly to the hydroclimate of the Great Salt Lake basin, infrequent but intense events have a profound impact during some cool seasons.

scholarly journals Capabilities and Limitations of Convection-Permitting WRF Simulations of Lake-Effect Systems over the Great Salt Lake

2015 ◽  
Vol 30 (6) ◽  
pp. 1711-1731 ◽  
Author(s):  
John D. McMillen ◽  
W. James Steenburgh
Keyword(s):  
Salt Lake ◽  
Numerical Models ◽  
Great Salt Lake ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Grid Spacing ◽  
Convective Storm ◽  
Lake Effect ◽  
Object Based ◽  
The Right

Abstract Although previous studies suggest that the Weather Research and Forecasting (WRF) Model can produce physically realistic banded Great Salt Lake–effect (GSLE) precipitation features, the accuracy and reliability of these simulations for forecasting applications remains unquantified. The ability of the WRF to simulate nonbanded GSLE features is also unknown. This paper uses subjective, traditional, and object-based verification to evaluate convection-permitting (1.33-km grid spacing) WRF simulations of 11 banded and 8 nonbanded GSLE events. In all simulations, the WRF was configured with the Thompson microphysics and the Yonsei University (YSU) planetary boundary layer parameterizations. Subjectively, a majority of the simulations of banded GSLE events produce physically realistic precipitation features. In contrast, simulations of nonbanded GSLE events rarely produce physically realistic precipitation features and sometimes erroneously produce banded precipitation features. Simulations of banded GSLE events produce equitable threat scores (ETSs) comparable to other convective-storm verification studies, whereas simulations of nonbanded events exhibit lower ETSs. Object-based verification shows that the WRF tends to generate precipitation to the right (relative to the flow) and downstream of observed. These results, although based on a specific WRF parameterization suite, suggest that deterministic prediction of GSLE using convection-permitting models will prove challenging in practice with current numerical models. In addition, identifying and addressing the causes of the rightward and downstream precipitation bias is necessary to achieve optimal performance from future probabilistic and/or deterministic high-resolution forecast systems.

scholarly journals Orographic Influences on a Great Salt Lake–Effect Snowstorm

2013 ◽  
Vol 141 (7) ◽  
pp. 2432-2450 ◽  
Author(s):  
Trevor I. Alcott ◽  
W. James Steenburgh
Keyword(s):  
Snow Water Equivalent ◽  
Salt Lake ◽  
Great Salt Lake ◽  
Salt Lake Valley ◽  
Wasatch Mountains ◽  
Lake Effect ◽  
Thermally Driven ◽  
Precipitation Band ◽  
Northern Utah ◽  
Snow Water

Abstract Although several mountain ranges surround the Great Salt Lake (GSL) of northern Utah, the extent to which orography modifies GSL-effect precipitation remains largely unknown. Here the authors use observational and numerical modeling approaches to examine the influence of orography on the GSL-effect snowstorm of 27 October 2010, which generated 6–10 mm of precipitation (snow-water equivalent) in the Salt Lake Valley and up to 30 cm of snow in the Wasatch Mountains. The authors find that the primary orographic influences on the event are 1) foehnlike flow over the upstream orography that warms and dries the incipient low-level air mass and reduces precipitation coverage and intensity; 2) orographically forced convergence that extends downstream from the upstream orography, is enhanced by blocking windward of the Promontory Mountains, and affects the structure and evolution of the lake-effect precipitation band; and 3) blocking by the Wasatch and Oquirrh Mountains, which funnels the flow into the Salt Lake Valley, reinforces the thermally driven convergence generated by the GSL, and strongly enhances precipitation. The latter represents a synergistic interaction between lake and downstream orographic processes that is crucial for precipitation development, with a dramatic decrease in precipitation intensity and coverage evident in simulations in which either the lake or the orography are removed. These results help elucidate the spectrum of lake–orographic processes that contribute to lake-effect events and may be broadly applicable to other regions where lake effect precipitation occurs in proximity to complex terrain.

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