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.

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 Assimilating C-Band Radar Data for High-Resolution Simulations of Precipitation: Case Studies over Western Sumatra

2021 ◽  
Vol 14 (1) ◽  
pp. 42
Author(s):  
Bojun Zhu ◽  
Zhaoxia Pu ◽  
Agie Wandala Putra ◽  
Zhiqiu Gao
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Wrf Model ◽  
Active Phase ◽  
Radar Data ◽  
Skill Score ◽  
Moist Convection ◽  
Simulated Precipitation

Accurate high-resolution precipitation forecasts are critical yet challenging for weather prediction under complex topography or severe synoptic forcing. Data fusion and assimilation aimed at improving model forecasts, as one possible approach, has gained increasing attention in past decades. This study investigates the influence of the observations from a C-band Doppler radar over the west coast of Sumatra on high-resolution numerical simulations of precipitation around its vicinity under the Madden–Julian oscillation (MJO) in January and February 2018. Cases during various MJO phases were selected for simulations with an advanced research version of the weather research and forecasting (WRF) model at a cloud-permitting scale (~3 km). A 3-dimensional variational (3DVAR) data assimilation method and a hybrid three-dimensional ensemble–variational data assimilation (3DEnVAR) method, based on the NCEP Gridpoint Statistical Interpolation (GSI) assimilation system, were used to assimilate the radar reflectivity and the radial velocity data. The WRF-simulated precipitation was validated with the Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation data, and the fractions skill score (FSS) was calculated in order to evaluate the radar data impacts objectively. The results show improvements in the simulated precipitation with hourly radar data assimilation 6 h prior to the simulations. The modifications with assimilation were validated through the observation departure and moist convection. It was found that forecast improvements are relatively significant when precipitation is more related to local-scale convection but rather small when the background westerly wind is strong under the MJO active phase. The additional simulation experiments, under a 1- or 2-day assimilation cycle, indicate better improvements in the precipitation simulation with 3DEnVAR radar assimilation than those with the 3DVAR method.

Pathways to the Production of Precipitating Hydrometeors and Tropical Cyclone Development

2016 ◽  
Vol 144 (6) ◽  
pp. 2395-2420 ◽  
Author(s):  
J.-W. Bao ◽  
S. A. Michelson ◽  
E. D. Grell
Keyword(s):  
Tropical Cyclone ◽  
Wrf Model ◽  
Cloud Microphysics ◽  
Weather Research And Forecasting ◽  
Rapid Intensification ◽  
Latent Heating ◽  
Vertical Distributions ◽  
Double Moment ◽  
Microphysical Processes ◽  
Definition Of

Abstract Pathways to the production of precipitation in two cloud microphysics schemes available in the Weather Research and Forecasting (WRF) Model are investigated in a scenario of tropical cyclone intensification. Comparisons of the results from the WRF Model simulations indicate that the variation in the simulated initial rapid intensification of an idealized tropical cyclone is due to the differences between the two cloud microphysics schemes in their representations of pathways to the formation and growth of precipitating hydrometeors. Diagnoses of the source and sink terms of the hydrometeor budget equations indicate that the major differences in the production of hydrometeors between the schemes are in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes, such as accretion growth and sedimentation. These differences lead to different horizontally averaged vertical profiles of net latent heating rate associated with significantly different horizontally averaged vertical distributions and production rates of hydrometeors in the simulated clouds. Results from this study also highlight the possibility that the advantage of double-moment formulations can be overshadowed by the uncertainties in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes.

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

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 Effect of Logarithmically Transformed IMERG Precipitation Observations in WRF 4D-Var Data Assimilation System

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1918
Author(s):  
Jiaying Zhang ◽  
Liao-Fan Lin ◽  
Rafael L. Bras
Keyword(s):  
Data Assimilation ◽  
Weather Prediction ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Regular Space ◽  
Observation Error ◽  
Central United States ◽  
Precipitation Estimates ◽  
Constant Observation

Precipitation estimates from numerical weather prediction (NWP) models are uncertain. The uncertainties can be reduced by integrating precipitation observations into NWP models. This study assimilates Version 04 Integrated Multi-satellite Retrievals for the Global Precipitation Measurement (GPM) (IMERG) Final Run into the Weather Research and Forecasting (WRF) model data assimilation (WRFDA) system using a four-dimensional variational (4D-Var) method. Three synoptic-scale convective precipitation events over the central United States during 2015–2017 are used as case studies. To investigate the effect of logarithmically transformed IMERG precipitation in the WRFDA system, this study reports on several experiments with six-hour and hourly assimilation windows, regular (nontransformed) and logarithmically transformed observations, and a constant observation error in regular and logarithmic spaces. Results show that hourly assimilation windows improve precipitation simulations significantly compared to six-hour windows. Logarithmically transformed precipitation does not improve precipitation estimations relative to nontransformed precipitation. However, better predictions of heavy precipitation can be achieved with a constant error in the logarithmic space (corresponding to a linearly increasing error in the regular space), which modifies the threshold of rejecting observations, and thus utilizes more observations. This study provides a cost function with logarithmically transformed observations for the 4D-Var method in the WRFDA system for future investigations.

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