# Presentation: 079065

## Andrew L. Molthan1,2, Jonathan L. Case3, Scott R. Dembek4, 

- Andrew L. Molthan1,2, Jonathan L. Case3, Scott R. Dembek4,
- Gary J. Jedlovec1 and William M. Lapenta5

- American Meteorological Society
-  24th Conference on Severe Local Storms, Savannah, GA

**Science Mission Directorate**
- National Aeronautics and Space Administration

## Introduction

- Use of these schemes is increasingly widespread.
- Accessible to research, operational centers and WFOs.
- SPoRT program emphasis:
- Improving regional forecasts in the 0-48h time frame.
- The “Super Tuesday Outbreak” includes several high impact events:
- Extensive severe weather outbreak.
- Widespread moderate to heavy precipitation.
- Goals:
- Examine sensitivities within model QPF.
- Verify accurate simulation of radar reflectivity characteristics.

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## The Super Tuesday Outbreak

- mm

**NCEP Stage IV Precipitation Accumulation**
**36 h, ending 2008/02/06 at 12 UTC**

- L

**2008/02/05 12 UTC (HPC)**

- L

- Event Total Precipitation

## The Super Tuesday Outbreak

- SPC Preliminary Storm Reports

- Storm Reports

## Methodology

- Performed three simulations of the Super Tuesday event on the domain of the 2008 NSSL Spring Experiment.
- 36 hours, resolution of 4 km, 35 vertical levels.
- Initialized from NAM grids on 00 UTC February 5.
- Same parameterizations as NSSL (see abstract).
- Varied single-moment, six-class microphysics:
- WSM6 (Hong and Lim 2006).
- NASA Goddard with graupel (GSFC6G, Tao et al. 2008).
- NASA Goddard with hail (GSFC6H, Tao et al. 2008).

- Simulations of the Super Tuesday Outbreak

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## Forecast Performance

- Two precipitation objects of interest:
-   Cold frontal and squall line.
-   Central Plains convection.

- Cold frontal precipitation and squall line:
- Lagged northwestward but reasonable intensity.
- Central Plains convection:
- Some initiation of cells, coverage under forecast.

**1-Hr. Precipitation (mm) Ending 1400 UTC February 5 2008**

|  |  | STAGE IV | GSFC6G | GSFC6H |
| --- | --- | --- | --- | --- |
| Cold Front | (pts) | 18199 | 26642 | 25320 |
| Median Intensity | (mm) | 2.63 | 2.05 | 2.04 |
| 90th Percentile | (mm) | 7.37 | 6.49 | 6.90 |
| Convection | (pts) | 8774 | 4618 | 5720 |
| Median Intensity | (mm) | 3.74 | 1.21 | 1.17 |
| 90th Percentile | (mm) | 9.50 | 5.09 | 5.43 |

## Methodology

- Comparisons of Radar Characteristics

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- All model forecasts were capable of simulating a squall line from Illinois to Pennsylvania on February 5.
- Model hydrometeor and temperature profiles within the line were extracted from each forecast.
- WSR-88D equivalent (assumed Rayleigh) reflectivity is calculated based on scheme DSD characteristics.
- In reality, the squall line was displaced to the southeast of the model forecast.
- Observed by four WSR-88D radars: KLVX, KIND, KILN and KPBZ.
- Obtained volume scans for the period of 1330-1430 UTC to compare to the model simulations valid at 1400 UTC.
- Volume scans were gently pruned to remove extraneous returns not associated with the squall line (SoloII).
- Interpolated to a Cartesian grid through REORDER/CEDRIC tools.

## WSR-88D Characteristics

- Adopting the methodology of Yuter and Houze (1995) as in Lang et al. (2007) and others:
- _C_ontoured _F_requency with _A_ltitude _D_iagrams (CFAD) of radar reflectivity.
- Observed radar CFADs obtained from WSR-88D on a 4x4x1km Cartesian grid.
- Simulated radar CFADs calculated on WRF model vertical levels.

- KLVX

## WSR-88D Characteristics

- KIND

- KLVX

## WSR-88D Characteristics

- KIND

- KLVX

- KILN

## WSR-88D Characteristics

- KIND

- KLVX

- KILN

- KPBZ

## WSR-88D Characteristics

- KIND

- KLVX

- KILN

- KPBZ

- RADAR

## Model Comparisons

- WSM6

- GSFC6G

- GSFC6H

- RADAR

## Model Comparisons

- Three apparent differences in CFAD character:
-   Excessive reflectivity aloft.
-   Occurrence of mode [~30dBZ] up to 4-6km AGL.
-   Delayed lapse in dBZ with altitude.

- WSM6

- GSFC6G

- GSFC6H

- RADAR

## Snow Distribution Parameters

- Qualitatively, the CFAD of the WSM6 scheme gives *some* improved fit versus GSFC6G/H.
- WSM6: Snow intercept is f(Tcloud).  GSFC6G/H: Snow intercept is fixed.
- Mean hydrometeor profiles contain snow and graupel where dBZ errors are largest.

- Ryan (2000) promotes the parameterization of the snow slope parameter, λ(Tcloud).

- Applying λ(Tcloud) to GSFC6G improves versus radar.
- Mitigates dBZ mode and some dBZ errors aloft.

- Figure 2 of Ryan (2000)

**-30****o****C (KILX)**

**0****o****C **
**(KILX)**

- N(D) = noe(-λD)

**GSFC6G**

**RYAN ****λ****(T)**

## Conclusions

- QPF Sensitivities:
- In operational use, forecasts of event total QPF could be highly sensitive to scheme selection.
- Radar Characteristics:
- No particular scheme provided an ideal match.
- Potential improvements are observed when snow mass is redistributed in size, based on Ryan (2000).
- Current and Future Work:
- Implementation of λ(T) within the NASA Goddard scheme.
- Verify match of DSD characteristics within other parameterizations.
- Examine results from an additional Super Tuesday forecast.
- Verify microphysics output against field campaign observations.
- Apply NASA Earth Observing Satellite constellations (e.g. A-Train) and appropriate simulators to verify and improve cloud representation.

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## Acknowledgments

- Dr. Wei-Kuo Tao (NASA GSFC)
- Provided guidance related to GSFC microphysics.
- Dr. Roger Shi and Dr. Toshi Matsui (GEST/UMBC)
- Additional guidance regarding microphysics code, integration within WRF and installation.
- NASA Center for Computational Sciences
- Simulations performed on the NASA Discover cluster.
- NSSL Spring Experiment (2008) & NSSL/SPoRT Collaborations
- Andrew Molthan, Jonathan Case, Brad Zavodsky, Scott Dembek
- NASA MSFC Cooperative Education Program/Earth Science Office
- Provides lead author with academic support and professional development opportunities.

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## Selected References

- Hong, S.-Y., and J.-O. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6).  *Journal of the Korean Meteorological Society*, **42**, 129-151.
- Lang, S., W.-K. Tao, R. Cifelli, W. Olson, J. Halverson, S. Rutledge, and J. Simpson, 2007: Improving simulations of convective systems from TRMM LBA: Easterly and westerly regimes. *J. Atmos. Sci.*, **64**, 1141-1164.
- Ryan, B. F., 2000: A bulk parameterization of the ice particle size distribution and the optical properties in ice clouds.  *J. Atmos. Sci.*, **57**, 1436-1451.
- Tao, W.-K., J. Shi, S. Chen, S. Lang, S.-Y. Hong, C. Peters-Lidard, S. Braun and J. Simpson, 2008: Revised bulk-microphysical schemes for studying precipitation processes. Part I: Comparisons with other schemes.  *Mon. Wea. Rev., submitted*
- Yuter, S. E. and R. A. Houze, Jr., 1995: Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part II: Frequency distributions of vertical velocity, reflectivity, and differential reflectivity.  *Mon. Wea. Rev., ***123**, 1921-1940.

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## Questions?

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