Lake Effect Snow: Assimilation and Prediction with WRF and ...€¦ · Lake Effect Snow: Assimilation and Prediction with WRF and EnKF Steven J. Greybush George Young, Christopher

Lake Effect Snow:Assimilation and Prediction with

WRF and EnKF

Steven J. GreybushGeorge Young, Christopher Melhauser,

Yonghui Weng, and Fuqing Zhang

PSU-UMD Data Assimilation Symposium, Dec 18, 2013

NEXRAD_3D_mosaic.201312101800.04kft_CAPPI.png

ops.GOES-13.201312101815.1km_gt_lakes_ch1_vis.jpg

Formation Factors

• Heat and moisture fluxes from lake.• Instability: difference in temperature from

lake surface to atmosphere (850 mb) of 13 °C.• Wind direction and shear.• Lake orientation / fetch.• Topography.

Impacts of Lake Effect Storms

December 2013-January 2014

Mission Statement from http://www.owles.org/:

The OWLeS project examines the formation mechanisms, cloud microphysics, boundary layer processes and dynamics of lake-effect systems (LeS) at unprecedented detail using X-band and S-band dual-polarization (dual-pol) radars, an aircraft instrumented with particle probes and profiling cloud radar and lidar, a mobile integrated sounding system, a network of radiosondes,and a surface network of snow characterization instruments.

Lake-effect systems form through surface-air interactions as a cold air mass is advected over relatively warm (at least partially) ice-free mesoscale bodies of water. The OWLeS project focuses on Lake Ontario because of its size and orientation, the frequency of LeS events (especially intense single bands), its nearby moderate orography, the impact of Lake Ontario LeS hazards in particular on public safety and commerce, and the proximity of several universities with large atmospheric science programs.

OWLeS: Ontario Winter Lake-effect Systems (LeS)

Dec 10 Flight Plan

Case Study: Dec 10, 2013

Data Assimilation System Design Considerations

• Interplay of hydrosphere (lake surface), cryosphere(surface ice, snow), lithosphere (topography) and atmosphere.

• Synoptic scale (winds) and mesoscale (precipitation bands) features.

• Short time scales (convective features).• Error propagation (IC, BC, model error).• Satellite and radar features: simulation, and

assimilation.• Runtime considerations: wall clock time less than

simulation time to enable near real time runs.

WRF Domains

• Outer: 27km, ensemble, analyzed

• Domain 2: 9km, ensemble, analyzed

• Hi-Res: 3km, deterministic, explicit convection

Domains and Topography

Experiment Design

GFS Deterministic

09Dec12Z 10Dec00Z 10Dec12Z 11Dec0Z 11Dec12Z

Observations

WRF Ensemble

WRF Deterministic

EnKF

2013-12-10 12:00

WRF Simulated DBZ:

WRF uses the GFS forecast initialized at 2013-12-09 12:00 for initial and boundary conditions.

Surface and rawinsonde observations are assimilated hourly from 00:00 to 12:00 on 2013-12-10 by the WRF-EnKFat resolution of 27 km and 9km.

2013-12-11 00:00WRF uses the GFS forecast initialized at 2013-12-09 12:00 for initial and boundary conditions.

Surface and rawinsonde observations are assimilated hourly from 00:00 to 12:00 on 2013-12-10 by the WRF-EnKFat resolution of 27 km and 9km.

A 3km nested deterministic run is initialized from the ensemble mean analysis at 2013-12-10 11:00.

WRF Simulated DBZ:

Future Work

• Verify against additional obs types (e.g. winds)• Lake Surface Temperatures, Ice Coverage• WSR-88D Radar Data Assimilation• Dual-Polarization Radar Data Assimilation• Tune / improve WRF physics (BL, microphysics).• Optimize DA system design.• Examine ensemble spread, predictability.• Use resulting simulations to advance OWLeS

science goals, including understanding the diurnal evolution of lake effect bands.