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Michael Dutter and Todd Kluber NOAA/National Weather Service Marquette, MI

Using Fractional Lake Ice and Variable Ice Thickness in the WRF-ARW to improve Great Lakes Forecasting. Michael Dutter and Todd Kluber NOAA/National Weather Service Marquette, MI 2014 Great Lakes Operational Meteorology Workshop – Ann Arbor, MI. Motivation.

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Michael Dutter and Todd Kluber NOAA/National Weather Service Marquette, MI

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  1. Using Fractional Lake Ice and Variable Ice Thickness in the WRF-ARW to improve Great Lakes Forecasting Michael Dutter and Todd Kluber NOAA/National Weather Service Marquette, MI 2014 Great Lakes Operational Meteorology Workshop – Ann Arbor, MI

  2. Motivation • Despite Lake Superior being completely (or nearly completely) ice covered for much of Feb-April 2014, lake effect bands were still occasionally observed. Some of these proved to be relatively significant. • Various NWP (as well as local forecasters) struggled to identify when/where LES would occur, especially during changing ice cover or when the lake surface was not fully ice covered.

  3. Main Goal of Research • Preliminary look at whether improved ice cover analysis/initialization will improve upon NWP forecasts of lake effect processes (especially precipitation) by: • Using ice concentration, coverage and thickness analyses from GLERL Nowcast as primary inputs into a local WRF-ARW for the Upper Great Lakes • Leveraging PolarWRF modifications (fractional ice and variable ice thickness parameters) within the WRF-ARW

  4. Discussion Points • Operational NWP sea ice implementation • Background Research • Laird and Kristovich – Studied LES Morphology • Gerbush et al. – Heat Flux Variations on Lake Erie • Hines et al. – Polar enhancements for the WRF (Polar WRF) • Methodology/Modeling • Case Studies

  5. Ice In Operational NWP • NAM and RAP uses a binary ice coverage (0 or 1) Any ice coverage >= 50% is assigned 1. • Fixed ice thickness of 1 m (split into 4 equal .25m slabs) for flux calculations • The GFS uses fractional sea ice, however the course horizontal resolution in the Great Lakes limits the effectiveness. • Variable ice thickness for flux calculations • GEM also uses fractional ice. • Variable ice thickness for flux calculations

  6. Ice in Operational NWP(5/2/2014) NAM GLERL Analysis GFS GEM

  7. Laird and Kristovich (2004) • Modeled numerous cases across the Great Lakes to resolve LES mesoscale morphology • Noted ice cover was present during many LES events, and that some events saw ice concentrations over 80% across the entire lake. • Two cases in Lake Erie had 95% ice coverage • Their study showed that accounting for ice cover in their model only led to a small improvement in hindcast accuracy of LES events. • However, it was noted that different concentrations of lake ice cover remains an important yet unknown challenge when forecasting lake effect processes (heat fluxes, etc).

  8. Gerbush et al. (2008) • Conducted aerial study of Heat Flux variations over Pack Ice-Covered Lake Erie during the Great Lakes Ice Cover Atmospheric Flux (GLICAF) experiment • Found that sensible heat fluxes decreased nonlinearly with increasing ice concentrations • In fact, the majority of SHF decreases occurred with ice concentrations greater than 70% • Latent heat fluxes displayed a more linear decrease with increase ice concentrations

  9. Gerbush et al. (2008) SHF and LHF regressions Sensible HF Latent HF

  10. Granite Island Flux Data Feb 2014 (Data courtesy Dr. John Lenters and NMU)

  11. Polar WRF (Hines et al. 2014) • Developed by the Polar Meteorology Group at Ohio State mainly for sea ice over the polar regions (Hines and Bromwich 2008) • Implements fractional sea ice, variable sea ice thickness and snow depth in WRF (specifically the Noah LSM) • Not a great deal of information (if any) found on using these enhancements on the Great Lakes. • Obviously 2014 was an excellent year for initial testing

  12. Fractional Ice in PolarWRF When fractional sea ice is turned on surface layer routines are called twice: • Open water • Ice Cover The resulting values are then averaged, then weighted by the sea ice fraction. Problem is at least over the Great Lakes, it has been noted that most of the reduction of sensible fluxes occur when ice cover is more than 70% (Gerbush et al 2008).

  13. Ice Thickness in WRF • Heat flux depends on the depth of snow/ice which heat flows. In the Noah LSM, this term is inversely proportional to the sum of half the thickness of the upper ice layer(Hines et al. 2014) As expected, heat fluxes increase with decrease of ice thickness

  14. Modeling Experiment Details • WRF 5.3.1 with PolarWRF modifications • ARW Core • 5km horizontal resolution/40 vertical levels • Explicit Convection • WRF Single Moment MP • Explicit Cumulus Parameterization • RRTM LW Radiation • Dudhia SW Radiation • NOAH Land Surface

  15. Case Study Runs • Control – No Ice (noice) • GLERL Ice (0 or 1 Ice Concentration (>70%) and 0.3 m Thickness) (binice) • GLERL Ice (Fractional Ice) (fractice) • GLERL Ice (Fractional Ice and Variable Thickness) • Full Ice Each run used the NAM as Initial and Boundary Conditions, using the run valid time of 12 hours before the “height” of the event. SST input are from GLERL.

  16. Case Studies • Feb 23-24, 2014 – Whitefish Point into areas of Ontario NW of Sault Ste. Marie • Mar 12, 2014 – Duluth, MN Area

  17. Feb 23 2014 • Heavy snow close to Whitefish Point, MI • 11 inches at the Paradise observing site • An west-east band of very persistent LES snow developed in an area of lower concentrated ice 11

  18. Feb 23 2014 – Radar (WGJ) 2/23/2014 – 00z  2/24/2014 – 06z

  19. Feb 23 2014 – Ice Cover Ice Concentration – GLERL Ice concentrations were generally 90+ percent across all of Lake Superior, except the extreme SE where concentrations were as low as 20 percent. Thickness was in 15-30cm range. Ice Thickness (cm) - GLERL NIC Analysis

  20. Feb 23 2014 – 15Z fractice_0.3m fractice_0.1m Note how there is very little difference in reflectivity structure

  21. Feb 23 2014 – 15Z binice_0.3m fractice_0.3m noice

  22. Feb 23 2014 – 18Z binice_0.3m fractice_0.3m noice

  23. Feb 24 2014 – 03Z binice_0.3m fractice_0.3m noice

  24. Granite Island Flux Data Feb 23 2014 (Data courtesy Dr. John Lenters and NMU) Note that at Granite Island despite the analysis showing 90% ice cover, there are still plenty of open areas, thus 6 hr mean fluxes are higher than the fractice model run.

  25. Mar 12 2014 – Duluth Area • Band of heavy snow extended NE-SW into areas between Duluth and Two Harbors, MN • Most of this snow fell in the early morning hours of Mar 12

  26. Mar 12 2014 - Radar 02z Mar 12 2014  15z Mar 12 2014

  27. Mar 12 2014 – Ice Cover Ice Concentration – GLERL Note the open ice just off of Duluth and NW Wisconsin. Ice Thickness is 10-25 cm across much of the lake Ice Thickness (cm) - GLERL

  28. Mar 12 2014 – 06Z binice_0.3m fractice_0.3m noice

  29. Mar 12 2014 – 11Z binice_0.3m fractice_0.3m noice

  30. Preliminary Observations • Current operational NWP can be improved on with regards to ice analysis and forecasting of fluxes with ice cover • Incorporate findings from Gerbush et al (2008) • Importance of an accurate ice analysis (even if it is a simple yes/no answer for coverage) is critical in improving fluxes and identifying where LES bands may occur. • Ingest GLERL ice analysis/nowcasts into local real time runs. • Fractional ice may even hurt the forecast at times • Ice thickness may help, but is perhaps not the most critical factor, at least with regards to forecasting placement/intensity of LES bands • If even a small part of the lake was open, the LES bands behaved more like the entire lake was open. • Local real time “no ice” runs through the winter (for worst case)?? • Need to investigate more subtle cases and look closer at fluxes at Granite Island.

  31. michael.dutter@noaa.gov Thank You!Questions?

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