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National Weather Association

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Title: National Weather Association


1
Simulation of Lake Effect snow using the
Workstation WRF model
  • National Weather Association
  • Annual Meeting
  • 16 October 2006
  • Daniel Leins Robert LaPlante (NWS WFO CLE)

2
Overview
  • Brief discussion of LES generation,
    characteristics, and Northeast Ohio snowfall
    climatology
  • WRF model application to LES in the CLE CWA
  • Discussion of model sensitivity to changes in
    horizontal resolution, convective
    parameterization, cloud microphysics, and
    boundary layer scheme
  • The utility of creating and analyzing Simulated
    Reflectivity
  • Optimal model configuration for simulating LES

3
Mean Land vs. Lake Temperatures for Lake Erie at
Buffalo, NY.
Unstable
Unstable

  • from Eichenlaub
    (1979)
  • Lake-effect occurs during the unstable season
    when mean lake temperatures exceed mean land
    temperatures

4
Conceptual Model of Lake-Effect
  • Heat and moisture from lake frictional
    convergence upslope flow clouds and
    lake-effect precipitation

5
The vertical scale of convectivelake effect snows
6
Snow Band Types
Multiple
Single
Meso-Vortex
Multi Lake
7
(No Transcript)
8
Using the WRF at NWS CLE
WRF Model domain
9
Using the WRFmodel terrain
6km Terrain
3km Terrain
10
Using the WRF
1km Terrain (via AWIPS)
11
Model Sensitivity study
  • Reanalyzed four cases from 2005-2006 winter
    season using the ARW core at 6km 3km grid
    spacing and compared results to observations
  • Made several changes to the default model
    configuration for each case and re-ran model
    after each change
  • Only varied configurations that we felt would
    have the greatest impact on LES processes
  • Initialized model runs using NAM tile12 initial
    conditions and 1/12º Real Time Global Sea
    Surface Temp data

12
Model Sensitivity studyFindings
  • Change to the horizontal model resolution had
    the largest effect by far of any other changes
    made
  • 3km grid spacing yielded results that were
    superior to those of the 6km model
  • Modification to cloud microphysics scheme also
    had a substantial impact
  • Convective scheme vs. no Convective scheme
    produced noticeable changes
  • Change to boundary layer scheme produced
    favorable results, although effect was minimal

13
Model Sensitivity StudyOptimal configuration
  • Results from each case were consistent with each
    otherleading to high confidence of an optimal
    configuration for modeling LES
  • Model grid spacing 3km (or less)
  • Convective Parameterization None
  • Cloud Microphysics scheme Lin et. al.
  • Boundary Layer scheme (MYJ) Mellor-Yamada-Janjic

14
Importance of Simulated Reflectivity
  • Simulated reflectivity acts as a conceptual model
    and helps convey more details of LES structure
    and evolution than just the more familiar fields
    of QPF and omega
  • Will help forecasters determine whether
    single/multi/combined band event is expected
  • Determine how cellular the bands will be, which
    will affect snowfall rates and visibilities

15
24-26 November 2005Multi-lake LES event
16
24-26 November 2005Multi-lake LES event
25 Nov 2005 Regional Reflectivity Mosaic 06Z -
15Z
17
24-26 November 2005Multi-lake LES event
25 Nov 2005 06Z 15Z Simulated Reflectivity
18
24-26 November 2005Multi-lake LES event
19
24-26 November 2005Multi-lake LES event
20
24-26 November 2005Multi-lake LES event
21
2 December 2005Multi-lake LES event
22
2 December 2005Multi-lake LES event
23
2 December 2005Multi-lake LES event
24
2 December 2005Multi-lake LES event
25
2 December 2005Multi-lake LES event
26
2 December 2005Multi-lake LES event
27
Conclusions
  • Workstation WRF has utility in forecasting lake
    effect snow
  • Default configuration must be modified for
    optimal LES simulations
  • Grid spacing should be less than 6km for more
    realistic placement of orographically generated
    pcpn
  • Utilization of simulated reflectivity will aid
    in forecaster interpretation of precipitation
    character

28
Acknowledgements
Robert A. Rozumalski NOAA/NWS SOO Science and
Training Resource Coordinator Mark
Hjelmfelt Professor South Dakota School of
Mines and Technology
29
Configurations Tested(in order of effect)
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