An evaluation and comparison of microphysics fields in Dennis (2005) at various lifecycle stages

1. An evaluation and comparison of microphysics fields in Dennis (2005) at various lifecycle stages Eric Meyers Atlantic Oceanographic and Meteorological Laboratory Hurricane Research Division Millersville University Eric.C.Meyers@noaa.gov Dr. Robert Rogers 01 August 2006

2. OUTLINE • Background – A Brief Look Back at Dennis (2005) • An Incentive – Modeled v. Observed INTENSITY • Motivation • Methodology • Analysis/Findings • A qualitative comparison between OBSERVATIONS and MM5 SIMULATION of Dennis (2005) • A closer look at the microphysical evolution in the MM5 SIMULATION • A peek at a quantifiable comparison between OBSERVATIONAL precipitation probe data and MM5 SIMULATION • Summary • Future Assignments • Acknowledgements

3. Background – Dennis ‘05 • MM5 Simulation • Auto-moving inner nest capability • Goddard 3-class ice bulk microphysical parameterization scheme • Kain-Fritsch convective parameterization for 45- and 15-km grid meshes • No convective parameterization for 5- and 1.67-km grid meshes • NOAA P-3 Missions • Dropsondes • LF radar • Precipitation imaging probe Visible satellite imagery courtesy NRL-Monterey

4. INTENSITY ISSUE - DENNIS ‘05

5. Motivation • Advent of high-resolution models mandates a statistical means of comparing modeled microphysics with observations • To initiate the effort to improve: • Microphysical parameterization schemes • Simulated distributions of latent heat release (spatial and temporal) • Tropical cyclone intensity forecasts • Rainfall predictions • NOAA’s Strategic Plan Mission Goal 3 • “To serve society’s needs for weather and water information” • “Understand, Describe, Assess, & Predict”

6. Methodology • Qualitative Comparison • Attempt to validate model thermodynamics • Hypothesis • MM5 simulation exhibits various temporal differences in the distributions, averages, and gradients of microphysics fields during the organizational stage of Dennis (2005) • These quantifiable differences in microphysics can be statistically compared with observed fields of vertical velocity, reflectivity, and hydrometeor concentrations, with the intent to detect biases in the model • Statistical Model Analysis • Compare structural features and statistical distributions of hydrometeor mixing ratio, reflectivity, and vertical motion • “EARLY” - 18:00 Z 05 July 2005 through 00:00 Z 06 July 2005 (Tropical Storm Dennis – best track) • “LATE” – 06:00 Z 07 July 2005 through 12:00 Z 07 July 2005 (Hurricane Dennis – best track) • “Convective”, “Stratiform”, and “Other” • A Preliminary Quantitative Comparison • Precipitation imaging probe data v. simulated precipitation • Sampling volume v. model resolution

7. Qualitative comparison 13 dropsondes derived equivalent potential temperature 20:38-22:30 UTC 05 July 2005 950 hPa NOAA P-3 LF reflectivity 21:59 UTC 05 July 2005 650 hPa OBSERVATIONS MM5 derived equivalent potential temperature 21:00 UTC 05 July 2005 950 hPa MM5 reflectivity 22:00 UTC 05 July 2005 700 hPa SIMULATION

8. A LIMITED PERSPECTIVE… EARLY 22:00 UTC 05 July 2005 convective region 0°C Rainwater mixing ratio Graupel mixing ratio LATE convective region 09:00 UTC 07 July 2005

9. REFLECTIVITY EARLY bin size: 5 dBZ 11 km 18:00 UTC 05 July 2005 – 00:00 UTC 06 July 2005 Contoured Frequency by Altitude Diagrams (CFADs) CONVECTIVE REGIONS LATE bin size: 5 dBZ 11 km 06:00 UTC 07 July 2005 – 12:00 UTC 07 July 2005 Contoured Frequency by Altitude Diagram (CFAD)

10. Vertical Velocity EARLY 18:00 UTC 05 July 2005 – 00:00 UTC 06 July 2005 CONVECTIVE bin size: 1 m/s LATE 06:00 UTC 07 July 2005 – 12:00 UTC 07 July 2005 GRAUPEL CONVECTIVE REGIONS

11. INITIAL Quantitative comparison 01:58:49 Z - 02:01:23 Z 7 July 2005 mean T = 1.67 °C median T = 1.61 °C OBSERVATIONS SIMULATION ICE Precipitation Imaging Probe 6.4 mm RAIN

12. Summary • Set out to explore, both qualitatively and statistically, differences in the evolution of simulated microphysics fields • “EARLY” • “LATE” • Employed a unique statistical (and thus representative) framework for evaluating modeled microphysical parameterization schemes • Contoured Frequency by Altitude Diagrams (CFADs) • Mean profiles • Independent from observational data, determined that the MM5 simulation exhibits significant temporal variability in microphysics fields, through a unique vertical evolution of hydrometeor concentrations • Distributions of reflectivity and vertical motion are broader during “early” than during “late” period, especially above the melting level • Isolated “early” convective cores likely contribute to the majority of vertical mass transport, lofting super-cooled raindrops to higher levels and increasing graupel mixing ratio

13. Future assignments • To determine the statistical significance of differences evident in the prepared statistical analyses of modeled microphysics fields • To perform statistical analyses of observations: • Post-processed dropsonde data • Reliable microphysical probe measurements • Coordinated NOAA P-3 and NASA ER-2 Doppler velocities • To compare the temporal evolution of microphysics fields in the MM5 simulation (manifested in the statistical analyses I have prepared) with these observations • To pinpoint biases in the model • To evaluate the microphysical parameterization schemes • To continue simulations of Dennis (including an extension to the mature stage, when Dennis was over the eastern Gulf of Mexico), with specific efforts to improve the simulation of intensity • Ultimately, to use an enhanced modeling of microphysics to improve forecasts of tropical cyclone intensity and rainfall, an obvious benefit to public safety

14. Acknowledgements • Collaborators • Black, Robert - researcher HRD • Feuer, Steve - researcher HRD • Marks, Frank, PhD - director HRD • Ortt, Derek - graduate student RSMAS • Rogers, Robert, PhD - mentor and researcher HRD • Uhlhorn, Eric – researcher HRD • Valde, Krystal – CIMAS research associate • Papers • Cifelli, R., Peterson, W. A., Carey, L. D., & Rutledge, S. A. (2002). Radar observations of the kinematic, microphysical, and precipitation characteristics of two MCSs in TRMM LBA. J. of Geophysical Research, 107, 44-1-44-15. • Rogers, R. F., Black, M. L., Chen, S. S., Black, R. A. (2006). An evaluation of microphysical fields from mesoscale model simulations of tropical cyclones. Part I: Comparisons with observations. J. of Atmospheric Sciences, in review. • Yuter, S. E. & Houze, R. A. (1994). Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part III: Vertical mass transport, mass divergence, and synthesis. Mon. Wea. Rev., 123, 1946-1983.

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