Investigating physics sensitivity multi scale predictability and model performance UAlbany Massey Bartolini Justin Minder lead faculty Ryan Torn Dan Keyser NWS Focal Points David ID: 590507
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High-resolution numerical simulations of lake-effect snowstorms: Investigating physics sensitivity, multi-scale predictability, and model performance
UAlbany:Massey Bartolini,Justin Minder (lead faculty),Ryan Torn,Dan KeyserNWS Focal Points:David Zaff (BUF),Joseph Villani (ALY)NOAA-ESRL:Stan Benjamin (GSD, HRRR dev.),Joseph Olson (GSD, HRRR dev.)Slide2
Overall Research GoalsSlide3
10-12 December 2013 Case Study (OWLeS IOP2b)Major lake-effect snow event for the typical snow belts downwind of Lake Erie and Lake OntarioSnow accumulations as much as 101.5 cm on the Tug Hill Plateau
500 hPa winds (barbs), vorticity (fill),and heights (contours)Surface / 850 hPa winds (black/blue barbs), surface convergence (contours), and surface–850 hPa temperature difference (fill)Slide4
10-12 December 2013 Case Study (OWLeS IOP2b)Major lake-effect snow event for the typical snow belts downwind of Lake Erie and Lake OntarioSnow accumulations as much as 101.5 cm on the Tug Hill Plateau
500 hPa winds (barbs), vorticity (fill),and heights (contours)Surface / 850 hPa winds (black/blue barbs), surface convergence (contours), and surface–850 hPa temperature difference (fill)Slide5
10-12 December 2013 Case Study (OWLeS IOP2b)Slide6
10-12 December 2013 Case Study (OWLeS IOP2b)KTYX radar-estimated liquid precipitation equivalent (LPE) from 0000 UTC 11 December 2013 to 0000 UTC 12 December 2013, Campbell et al. 2016Slide7
10-12 December 2013 Case Study (OWLeS IOP2b)KTYX radar-estimated liquid precipitation equivalent (LPE) from 0000 UTC 11 December 2013 to 0000 UTC 12 December 2013, Campbell et al. 2016
Time series of automated weighing precipitation gauge LPE measurementsSlide8
WRF Configuration: 10–12 December 2013 Case StudyTriple-nested two-way WRF simulations (12-, 4-, and 1.33-km horizontal grid spacing)Initialized at 1200 UTC 10 December 2013, run for 42 hoursWRF v3.7.1,
experimental HRRR version from Joseph Olson (ESRL)Slide9
WRF Configuration: 10–12 December 2013 Case StudyModel physics: Experimental HRRR (Sept. 2016 version)Initial/boundary conditions: RAP, augmented with NAM soil data and Great Lakes lake-surface temperature and ice cover analysesSlide10
Control Simulation ResultsSlide11
Control Simulation Results:0300 UTC, 11 December 2013Observed ReflectivityWRF Simulated ReflectivitySlide12
Control Simulation Results:1200 UTC, 11 December 2013Observed ReflectivityWRF Simulated ReflectivitySlide13
Control Simulation Results:2000 UTC, 11 December 2013Observed ReflectivityWRF Simulated ReflectivitySlide14
Control Simulation Results:Accumulated Precipitation (snow + graupel)Observed LPE (radar-derived),Campbell et al. 2016
WRF Control LPE (Exp. HRRR)Slide15
Microphysics EnsembleSlide16
Accumulated Precipitation (snow + graupel)Observed LPE (radar-derived),Campbell et al. 2016
WRF Control LPE, MP= Thompson aerosol-aware (THOM AERO)WRF LPE, MP=Morrison (MORR)
WRF LPE, MP=Goddard (GDRD)
WRF LPE, MP=
Milbrandt
-
Yau
(MYAU)
WRF LPE, MP=NSSL 2-momentSlide17
Accumulated Precipitation (snow + graupel)WRF Control LPE, MP=Thompson aerosol-aware (THOM AERO)
WRF LPE, MP= Thompson, no aerosols (THOM ORIG)WRF LPE, MP=WDM6WRF LPE, MP=WSM6
WRF LPE, MP=Stony Brook Univ. – Lin (SBUL)
Observed
LPE (radar-derived),
Campbell et al. 2016Slide18
Precipitation Time SeriesSlide19
Precipitation Time SeriesSlide20
Orographic Enhancement, Downstream Hydrometeor AdvectionMore Tug Hill Precipitation (e.g., WDM6)Less Tug Hill Precipitation (e.g., GDRD)
Lake Ontario
Tug Hill Plateau
Adirondack Mountains
Lake Ontario
Tug Hill Plateau
Adirondack MountainsSlide21
Lake Ontario Snow Band Precipitation StatisticsSlide22
Lake Ontario Snow Band Precipitation StatisticsSlide23
Lake Ontario Snow Band Precipitation StatisticsSlide24
Multi-scale Uncertainty due to Initial/Boundary ConditionsSlide25
Hypotheses for IC/BC SensitivitySlight variations in the position and timing of shortwave trough features, modulating LeS band positionResolution of lake-breeze front location and strength, perhaps a critical mechanism for focusing axis of strongest convection in some LeS cases (e.g., 10-12 Dec. 2013)Land/lake temperature contrast, shoreline resolution
10-12 Dec. 2013 lake-breeze front schematic, Steenburgh and Campbell 2017Slide26
Future WorkSlide27
NCAR Ensemble SimulationsWorking with Craig Schwartz (NCAR) to analyze retroactive NCAR Ensemble simulations for the entire OWLeS field campaign (December 2013 – January 2014)Hope to understand range of synoptic and mesoscale lake-effect snowstorm uncertainty for several case studiesSlide28
Extra SlidesSlide29
WRF Control SimulationNCEI NOMADS server archive is missing soil data (temperature and moisture), so I had to fill these fields from the corresponding NAM filesModified Great Lakes lake-surface temperature (“SKINTEMP”) and fractional ice cover (“SEAICE”) variables in met_em filesUsed Great Lakes Coastal Forecasting System analysis dataset (as in Campbell et al. 2016)
Initial/boundary conditions: RAP, augmented with NAM soil data and Great Lakes lake-surface temperature and ice cover analysesSlide30
Modified Lake Surface TemperaturesSlide31
WRF Control Simulation PhysicsWRF Control: Experimental HRRR, Sept. 2016 versionCopied all namelist.input physics and dynamics settings from Joe Olson’s code repositoryOriginal WRF v3.7.1 MYNN (option 60) performs slightly better than Joe’s MYNN modifications as of Sept. 2016, for this case studyNamelist ParameterOption
mp_physics28 (Thompson aerosol-aware)ra_lw_physics4 (RRTMG)ra_sw_physics4 (RRTMG)sf_sfclay_physics60 (MYNN v3.6)sf_surface_physics3 (RUC LSM)bl_pbl_physics60 (MYNN v3.6)cu_physics1 (Kain-Fritsch, only for 12-km domain)Slide32
Synoptic-scale Uncertainty: 1800 UTC, 11 December 2013RAP: 500 hPa VorticityNARR: 500 hPa VorticitySlide33
Mesoscale Uncertainty,10-12 December 2013 Case StudySteenburgh and Campbell 2017 (MWR, Early Online Release)