24
A Conceptual Model for the Hydrometeor Structure of Mesoscale Convective Systems during the MJO Active Stage Hannah C. Barnes Robert A. Houze, Jr. University of Washington 31 st Conference on Hurricanes and Tropical Meteorology Town & Country Resort and Conference Center, San Diego, CA 2 April 2014 Funded by NSF –Grant AGS 1059611 and DOE Grant DE- SC0008452

Funded by NSF –Grant AGS 1059611 and DOE Grant DE-SC0008452

  • Upload
    simeon

  • View
    52

  • Download
    0

Embed Size (px)

DESCRIPTION

A Conceptual Model for the Hydrometeor Structure of Mesoscale Convective Systems during the MJO Active Stage Hannah C. Barnes Robert A. Houze, Jr. University of Washington 31 st Conference on Hurricanes and Tropical Meteorology Town & Country Resort and Conference Center, San Diego, CA - PowerPoint PPT Presentation

Citation preview

Page 1: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

A Conceptual Model for the Hydrometeor Structure of Mesoscale Convective

Systems during the MJO Active Stage

Hannah C. BarnesRobert A. Houze, Jr.

University of Washington

31st Conference on Hurricanes and Tropical Meteorology Town & Country Resort and Conference Center, San Diego, CA

2 April 2014Funded by NSF –Grant AGS 1059611 and DOE Grant DE-SC0008452

Page 2: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Objective

Characterize hydrometeor structure of MCSs

Composite with respect to kinematic structure

Page 3: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Kinematic Structure of Mesoscale Convective Systems (MCSs)

Convective Stratiform

Moncrieff (1992): Layer airflowKingsmill and Houze (1999): 3D structure

Page 4: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

• Addu Atoll• Dual wavelength

– Only using S-Band• Single Doppler • Dual-polarimetric

– Particle Identification Algorithm (Vivekanandan et al., 1999)

• RHI sector and within 100 km

NCAR SPolKa Radar

Page 5: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Case Selection

• SPolKa data during active phases

• Subjectively identify cases • SPolKa radial velocity• Layer lifting• One per storm

• 25 Convective Cases• 37 Stratiform Cases

Convective: 24 Oct 2011

Stratiform: 23 December 2011

dBZ Vr profile

Vr profiledBZ

Page 6: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Composite Structure

X Scale FactorZ Scale Factor

Radar Data

1.) Map kinematics and hydrometeors using radial velocity and PID

2.) Composite around layer lifting model

Compositing Methodology

Page 7: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Heavy Rain Moderate Rain Light RainGraupel

Rimed Aggregates

Wet Aggregates Dry Aggregates Small Ice Crystals Horz. Oriented Ice

Convective Updraft Composites

Page 8: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Dry Aggregates

Graupel/Rimed Aggregates

Heavy Rain

Wet Aggregates Moderate Rain

Small Ice Crystals

Light Rain

Hydrometeor Organization in Convective Updrafts

Page 9: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Stratiform

Stratiform with leading line Stratiform without leading line

23 December 2011 18 November 2011

dBZ dBZ

Page 10: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Stratiform with Leading LineComposites

Heavy Rain Moderate Rain Light RainGraupel

Rimed Aggregates

Wet Aggregates Dry Aggregates Small Ice Crystals Horz. Oriented Ice

Page 11: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Stratiform without Leading LineComposites

Heavy Rain Light RainModerate RainGraupel

Rimed Aggregates

Wet Aggregates Dry Aggregates Small Ice Crystals Horz. Oriented Ice

Page 12: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Light Rain

Graupel / Rimed Aggregates

Wet Aggregates

Horizontally Oriented Ice

Dry Aggregates

Small Ice Crystals

0˚C

Moderate Rain

Heavy Rain

Hydrometeor Organization in Stratiform

Page 13: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Conclusions

• Hydrometeor organization consistent across MCS types• Heating similar with and without leading line

• Interpretation of microphysical processes• Comparison of model output and radar observations

Convective Stratiform

Page 14: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Questions ?

Page 15: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Frequency of OccurrenceConvective Updraft

InflowStratiform with

Leading LineStratiform without

Leading Line

Graupel/Rimed Aggregates 88% 66% 64%

Heavy Rain 92% 11% 14%

Moderate Rain 100% 55% 60%

Light Rain 72% 100% 100%

Wet Aggregates 92% 100% 100%

Dry Aggregates 100% 100% 100%

Small Ice Crystals 92% 100% 89%

Horizontally-Oriented Ice Crystals 20% 44% 53%

Page 16: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Areal CoverageConvective Updraft

InflowStratiform with

Leading LineStratiform without

Leading Line

Graupel/Rimed Aggregates 2% 0.3% 0.5%

Heavy Rain 12% 4% 1%

Moderate Rain 16% 5% 6%

Light Rain 13% 28% 31%

Wet Aggregates 3% 1% 4%

Dry Aggregates 22% 12% 18%

Small Ice Crystals 12% 26% 18%

Horizontally-Oriented Ice Crystals - 2% 2%

Page 17: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Distribution of Convective Polarimetric VariablesReflectivity

Differential Reflectivity

Temperature

Linear Differential Reflectivity

Correlation CoefficientDifferential Reflectivity

Specific Differential Phase

GA HR MR LR WA DA SI HI

GA HR MR LR WA DA SI HI

GA HR MR LR WA DA SI HI

GA HR MR LR WA DA SI HI

GA HR MR LR WA DA SI HI

GA HR MR LR WA DA SI HI

Page 18: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Distribution of Mid-Level Polarimetric VariablesReflectivity

Temperature

Linear Differential Reflectivity

Correlation CoefficientDifferential Reflectivity

Specific Differential Phase

GA HR MR LR WA DA SI HI

GA HR MR LR WA DA SI HI

GA HR MR LR WA DA SI HI

GA HR MR LR WA DA SI HI

GA HR MR LR WA DA SI HI

GA HR MR LR WA DA SI HI

Page 19: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Confidence of PID

• PID interest value• Likelihood of particle

type• Highest interest

value chosen

• PID confidence• Difference of 1st and

2nd largest interest values

• Larger difference = more confidence

Convective UpdraftMid-Level Inflow with Leading Line

Page 20: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Mesoscale Modeling of Squall Line• WRF 3.4.1• Resolution: Outer – 9km, Inner – 3km• Cu Param: Outer – KF, Inner – None• MP Param: Both - Goddard• PBL Param: Both – UW• Forcing: ERAi• 00 UTC 23 Dec – 00 UTC 25 Dec

Reflectivity

Zonal Wind

Page 21: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Distribution of Hydrometeor Mixing Ratio Zonal Wind and Reflectivity

Rain Mixing Ratio

Snow Mixing Ratio

Cloud Mixing Ratio

Graupel Mixing Ratio

Ice Mixing Ratio

Page 22: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Convective Example Oct 24

Page 23: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Squall Example Nov 18

Page 24: Funded by NSF –Grant AGS 1059611 and DOE  Grant  DE-SC0008452

Differences in Graupel/Rimed Aggregates and Wet Aggregates in Mid-Level Inflow Cases

Graupel Wet Aggregates Only