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Tzu-Chin Tsai and Jen-Ping Chen National Taiwan University, Taiwan

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Presentation on theme: "Tzu-Chin Tsai and Jen-Ping Chen National Taiwan University, Taiwan"— Presentation transcript:

1 Tzu-Chin Tsai and Jen-Ping Chen National Taiwan University, Taiwan
Mixed-phase processes and ice crystal shape effects on cloud microphysics and radiation in WRF Tzu-Chin Tsai and Jen-Ping Chen National Taiwan University, Taiwan Workshop on Aerosol, Cloud, Climate and Chemistry RCEC, Taipei 2011/11/6

2 Ice Radiative Properties Ice Microphysical Processes
Ice Shape (Habit) Ice Radiative Properties Extinction Cross Section Scattering Phase-function Asymmetry Factor (effective radius) Radiation Budgets Ice Microphysical Processes Ice Volume (Density) Initialization, Splintering, & Other Processes (Indirect Effects) Precipitation Deposition Growth Riming Collection Autoconversion (Aggregate) Terminal Velocity (maximum dimension, cross section) (surface area) (maximum dimension) ※ Solid line means completed while dash line means under development (deposition density) (riming density) (aggregate density) Single-scattering Albedo (solar zenith angle)

3 Ice Shape in WRF ? (Microphysical schemes) ‧Milbrandt and Yao scheme (Only for snow particles) The constants of c and d are and based on Brandes et al. (2007) ‧The other schemes (assumed ice as spherical particles) ※ So far, no scheme can predict the ice shape. The constants of c and d are and 3.0 current regional models: no shape (spherical) or specified shape (like RAMS)

4 Our approach oblate prolate Finally, diagnose a new
According to observation and theory, one typical form of two axes (c and a) (Ono 1969, 1970; ……….) and are for specific crystal types oblate prolate (aspect ratio) relate C/r to particle size (volume) C is the electrostatic capacitance and Finally, diagnose a new

5 Ice bulk aspect ratio Ice growth ratios Inherent growth ratio
G(T) Inherent growth ratio Ice growth ratios Chen and Lamb (1994) Inherent growth ratio Adaptive growth ratio Chen and Lamb (1994) and observations This study 2-moment scheme; no memory 3 or 4-moment; has shape memory only temperature dependent can be adjusted by environment

6 Offline Calculation-1 Black and red lines were represented in different initial radius of 1 mm and 10 mm, respectively. ‧ More exaggerated shapes are shown to result when the initial crystals are small, whereas more isometric shapes are found to result from initially large crystals. It is quite consistent to the conclusion of (Sheridan et al., 2009)

7 Offline Calculation-2 growth at 10% △S
G(T) = 0.5 before 300 s = 2.0 after s M-P size distribution

8 A study case during DIAMET
DIAMET (DIAbatic influences on Mesoscale structures in ExTratropical storms), a project involving University groups from Manchester, Leeds, Reading and East Anglia, together with the Met Office as well as NCAS and the National Centre for Earth Observation. Synoptic situation: Cold front case undergoing ocean to land transition on 29th Nov. 2011 During the IOPs, a number of flights have already taken place providing a comprehensive set of in-situ measurements.

9 WRF Model Setup Version 3.3.1 Simulation Period (18 hrs)
Initial/Boundary Condition ECMWF reanalysis data Domains Setup Domain1 110 x 75 (30 km) Domain2 231 x 176 ( 6 km) Domain3 301 x 250 ( 2 km) Vertical 40 layers Physical Options Cumulus Kain-Fritsch Microphysics Morrison scheme PBL YSU scheme SW rad GSFC scheme LW rad Sfclay Monin-Obukhov Surface Thermal diffusion WRF Model Setup Version 3.3.1 Simulation Period (18 hrs) 2011/11/29 00Z - 18Z

10 Microphysical scheme (Morrison)
‧Ice group particles with 2-moment Marshall-Palmer size distribution 2-Moment scheme Qi/Ni Qs/Ns Qr/Nr Qv Qc Qg/Ng Mass / Number = Size ‧Deposition growth C is electrostatic capacitance Spherical Non-spherical ‧Autoconversion a. threshold diameter > 125 micron ‧Riming (Collection) a. threshold diameter > 100 micron ; b. cross section; c. (collection efficiency) Not presented this time

11 Radiation scheme (Goddard)
‧Effective radius Effective radius Original This study Cloud dropplet fixed value R = 10 The values were calculated in microphysical scheme and also coupled with radiation scheme Ice drop R = 125+(T )*5 Snow drop ‧Single-scattering properties The extinction coefficient, single-scattering albedo, and asymmetry factor for individual ice crystals with various habits and sizes at wavelengths covering 0.2–5 mm were computed by using an improved version of the geometric optics method developed by Yang and Liou [1996a], Yang et al. [2000].

12 Initial results (1) ‧Bulk Ice Shape
Transects back and forth through the frontal cloud over land to characterize the microphysics and the cloud environment A Aspect ratio (shaded) ; Air temperature (contour) B Mixing ratios of Cloud Ice (shaded) ; Snow (contour) planar columnar

13 Initial results (2) ‧Bulk Ice Shape
WRF Model Simulation In-Situ Measurement Planar Columnar Evidence of large ice crystal in column shape from observation. Domain-averaged of ice adaptive growth within observation period and area. (Provided by Chris Dearden)

14 Initial results (3) ‧Precipitation
There was no significant difference between the simulations of control run (L) and ice_shape (R) run.

15 Initial results (4) ‧Ice Deposition Heating Rate In-Situ Measurement
WRF Model Simulation Instantaneous heating rates can up to ~9K/hr Due to Ice_Shape effect ? Blue line is CTRL run; Red line is Ice_Shape run (Provided by Chris Dearden)

16 Simulation results (5) ‧Effective radius ‧Radiation flux Ice Radius
TOA SW Surface ↓SW Snow Radius TOA LW Surface ↓LW micron ‧Effective radius ‧Radiation flux

17 Conclusion and Future Work
‧The adaptive growth ratio bulkwater scheme is developed to simulated ice crystal shape effects on cloud microphysics and radiation, as well as adding one aspect ratio moment. ‧Ice shape effect significantly affects cloud microphysical properties, which lead to large variations in cloud radiation but not in surface precipitation for the particular case. ‧Adding another surface moment which allows the tracking of ice crystal apparent density ─ a. Treatment of snow and graupel shape b. Parameterization of ice crystal optics

18 Thank you!

19 How do we derive the heating rates from in-situ data?
- In mixed-phase cloud → assume water saturation based on ambient air temperature and pressure measurements; - In ice cloud – use available hygrometer data (WVSS-II, Buck CR2, GE) to calculate RH wrt ice; Latent heat of sublimation Specific heat of moist air at constant pressure Mass growth rate by deposition (calculated from in-situ data using bulk and/or bin method) Latent heating rate due to deposition Once we have calculated the instantaneous growth rates, obtaining the associated latent heating/cooling is trivial. In this talk, we will show results for deposition heating.


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