5. 2019 Halloween Storm

The 2019 Halloween storm struck the eastern U.S. cities with wind gusts, thunderstorms, and flash flooding.

5.1. Model Configuration and Datasets

The UFS Medium-Range Weather (MRW) Application (App) is used to prepare initial conditions, compile and run the UFS model, and post process the raw model outputs. Two model configuration compsets (GFSv15p2 and GFSv16beta) are tested using the C768 (~13km) spatial resolution with 64 vertical levels (default).

The case runs are initialized at 12z Oct 25, 2019 with 120 hours forecasting. The corresponding namelist options that need to be changed are listed below. The app uses ./xmlchange to change the runtime settings. The settings that need to be modified to set up the start date, start time, and run time are listed below.

./xmlchange RUN_STARTDATE=20191025,START_TOD=43200,STOP_OPTION=nhours,STOP_N=120

Warning

The model run time step is reduced from the default 225s to 150s in this case due to the model instability in GFSv16beta. To set the time step, add dt_atmos=150 to user_nl_ufsatm

Initial condition (IC) files are created from GFS operational dataset in NEMSIO format. The GFS reanalysis dataset are used as ‘truth’ to compare with simulation results.

5.2. Case Results

5.2.1. Synoptic Dynamics

_images/MSLP_MRW_v1.0_2019HalloweenStorm_trim.png

Mean sea-level pressure (MSLP, hPa)

  • MRW_GFSv15p2 simulates the sea level pressure structure more reasonably than MRW_GFSv16beta.

_images/500mb_MRW_v1.0_2019HalloweenStorm_trim.png

500 hPa geopotential heights (dam) and absolute vorticity (10 -5/s)

  • MRW_GFSv15p2 generates a progressive synoptic pattern compared with reanalysis data.

  • MRW_GFSv16beta alleviates the progressiveness of synoptic pattern.

5.2.2. Surface Temperature and Wind Speed

_images/2mT_MRW_v1.0_2019HalloweenStorm_RAP_trim.png

2-m temperature (F) valid at 00z 1 Nov 2019

  • Colder 2-m T in MRW_GFSv15p2 along the U.S. east coast compared with RAP_ANL.

  • Colder 2-m T at New England and warmer 2-m T at the Southeast in MRW_GFSv16beta.

_images/GUST_MRW_v1.0_2019HalloweenStorm_RAP_trim.png

Surface gust (m/s) valid at 00z 1 Nov 2019

  • Negative biases of surface gust over the eastern U.S. for both MRW_GFSv15p2 and MRW_GFSv16beta compared with RAP_ANL.

5.2.3. Moisture/Precipitation

_images/2mRH_MRW_v1.0_2019HalloweenStorm_RAP_trim.png

2-m relative Humidity (RH,%) valid at 00z 1 Nov 2019

  • Dryline across the central U.S. is not simulated well in the two physics compsets.

_images/Refc_MRW_v1.0_2019HalloweenStorm_RAP_trim.png

Composite reflectivity (dB) valid at 00z 1 Nov 2019

  • The precipitation location lags behind the MRW_GFSv16beta compared with RAP_ANL, while the precipitation location moves further northeastwards in MRW_GFSv15p2 compared with RAP_ANL.

5.3. Summary and Discussion

MRW_GFSv15p2 generates a progressive synoptic pattern during the 2019 Halloween Storm, while MRW_GFSv16beta generates a regressive synoptic pattern compared with GFS analysis data. GFS.v16.0.10 alleviates the progressiveness of MRW_GFSv15p2 but still generates a cold bias along the U.S. east coast. Major changes in GFS.v16 from GFS.v15 can be referred to Yang (2020).

References

Yang F. (2020). Development and evaluation of NCEP’s Global Forecast System Version 16. Unified Forecast System Community Webinar, Oct 22, 2020. [Link]