1. CFMIP/GCSS BLWG workshop 2009/06/08-12 A comparison between bin and bulk models in the case of boundary layer clouds observed during RICO Kozo Nakamura, Yasushi Fujiyoshi, Kazuhisa Tsuboki, Naomi Kuba (JAMSTEC)

2. CFMIP/GCSS BLWG workshop 2009/06/08-12 Aim Aim : To improve the parameterization schemes used in warm bulk cloud microphysics model. Question?For the better simulation, Should we divide water drops into more than 2 categories including drizzle as one of the categories ? Should we use 3 (or more) variables for each group? Method : Using the results of a bin scheme model, we will develop a new bulk parameterization scheme. Case : RICO intercomparison case for the first case. (The scheme will be fitted for several cases in future. )

3. CFMIP/GCSS BLWG workshop 2009/06/08-12 Model setting （ RICO LES intercomparison ） grid size Δ ｘ＝ Δ ｙ＝ 100 ｍ, Δ ｚ＝ 40m number of grids 128 x 128 x 100 →Domain 12.8km×12.8km× 4.0km θ,qv,u,v : shown in following figures Horizontally cyclic B. C. Bottom B. C. SST 299.8 Ｋ＝Ｔ air ＋ 0.6 ℃ Forcing : subsidence ： w = -0.005 at 2260m constant divergence below. horizontal drying and heating. Analysis : t =20 ～ 24 hrs. １ moment bulk MESO-NH SAM JAMSTEC Utah EULAG 2DSAM ２ moment bulk DALES UCLA WVU COAMPS UKMO RAMS Bin AMS@NOAA SAMEX DHARMA Fields of trade wind congestus typical cloud base 600 m typical cloud top ~ 2000-3000 m Example RF-09 17 Dec 04 2004 From http://www.knmi.nl/samenw/rico/

4. CFMIP/GCSS BLWG workshop 2009/06/08-12 Results of RICO intercomparison (20-24hr) 15 models : Open circles 1-moment bulk models red circles variables : Q C, Q R 2-moment bulk models green circles var : Q C, Q R, N C, N R Bin models blue circles var : Q 1 - Ｑ ？, N 1 - Surface precipitation ( Ｗ ｍ -2 ) Integrated liquid water （ｇ ｍ -2 ） From http://www.knmi.nl/samenw/rico/

5. CFMIP/GCSS BLWG workshop 2009/06/08-12 falling rain from upper grid physical process in 1-moment bulk model water vapor Temp cloud droplets cloud amount evaporation condensation Ⅰ auto-conversion (without rain) 1. condensational growth 2. collision between clouds Ⅱ collision-coalescence Ｒ＋Ｃ⇒Ｒ heat Qsat falling rain to lower grid grid model liquid water is divided into two groups not falling cloud and falling rain rain drops

6. CFMIP/GCSS BLWG workshop 2009/06/08-12 Results of RICO intercomparison Autoconversion scheme red marks with numbers ２ moment bulk models green marks Bin models blue marks CReSS 1-moment bulk closed red marks with capital letters Surface precipitation ( Ｗ ｍ -2 ) Integrated liquid water （ｇｍ -2 ） From http://www.knmi.nl/samenw/rico/ Mod. Berry Kessler Berry cloud water （ g/kg ） Conversion rate （ mg/kg/s ）

7. CFMIP/GCSS BLWG workshop 2009/06/08-12 Model : CReSS the Cloud Resolving Storm Simulator developed by Dr. Tsuboki and his colleagues Basic equations non-hydrostatic, compressible equations advective form Spatial discretizationfinite difference scheme (2,4,3) Topographyterrain following coordinate Temporal scheme mode splitting Slow mode － explicit scheme Fast mode － Horizontal Explicit Vertical Implicit scheme Cloud physics – bulk scheme ⇒ bin scheme for warm rain vapor, cloud, rain, cloud-ice(2) snow(2) graupel(2). Turbulence - Smagorinsky scheme or Deardorff scheme Cloud physics – bulk scheme ⇒ bin scheme for warm rain 71 bins (radius of drops covers from 1μ ｍ to 3.5 mm) Ratio of mass between the adjacent bin is sqrt(2).

8. CFMIP/GCSS BLWG workshop 2009/06/08-12 1) PCASP data was used and assumed that the RH in the instrument was 0.8x the ambient RH 2) The measured wet sizes were converted to dry sizes using Kohler theory and an assumed composition of ammonium sulfate. 3) The dry size distributions were averaged over all sub-cloud legs on RF12 (Jan 11) 4) A bimodal lognormal was fitted to the spectra 5) rg1=0.03 μm, sig1=1.28, n1=90 (cm -3 ), rg2=0.14 μm, sig2=1.75 n2=15 (cm -3 ) By courtesy of Dr Hongli Jiang and Dr. Margreet van Zanten Aerosol size distribution and activated CCN. vertical velocityabS(%)N C (cm -3 ) w < 24.04710 x w 1.19 1090w + 33.20.217 24.0 < w < 50.011700 w-169010600 w -14800.455 50.0 < w < 100.04300 w 1.05 2760 w 0.755 0.575 100.0 < w < 300.0 7730 – 15800exp(-1.08w) 6030 – 24100 exp(-1.87w) 1.0104 300.0 < w1140 w -741909 w -56.22.0105 Parameterization by parcel model. Kuba and Fujiyoshi (2006) observed size distribution of CCN.

9. CFMIP/GCSS BLWG workshop 2009/06/08-12 １ moment bulk ２ moment bulk Bin CReSS-bin Q C Q R t=20 ～ 24hr （ 15 models+1 ） 雨水混合比 (g/kg) Rain water (mg/kg)Cloud water (mg/kg)

10. CFMIP/GCSS BLWG workshop 2009/06/08-12 Results of RICO intercomparison 1-moment bulk models red marks with numbers 2-moment bulk models green marks Bin models blue marks CReSS 1-moment bulk closed red marks with capital letters CReSS Bin model closed blue mark Surface precipitation ( Ｗ ｍ -2 ) Integrated liquid water （ｇ ｍ -2 ） From http://www.knmi.nl/samenw/rico/

11. CFMIP/GCSS BLWG workshop 2009/06/08-12 Vertical profiles of cloud processes 33/71 Cond. Eva. Auto1>0 C → R(cond) Too large? Auto1<0 C → R (eva) Auto2 C ＋ C→E Coalescence R ＋ C→R Cloud water (mg/kg/s*1.e5) height (km) Rain water (mg/kg/s*1.e6) t=20-24hr. boundary between C&R is 47.9μ ｍ. i<34

12. CFMIP/GCSS BLWG workshop 2009/06/08-12 Vertical Profiles of cloud processes Cond. Eva. Auto1>0 C → R(cond) Too large? Auto1<0 C → R (eva) Auto2 C ＋ C→E Collision R ＋ C→R Rain water (mg/kg/s*1.e6) t=20-24hr height (km) Mod. Berry model Rain water t=20-24hr. boundary between C&R is 47.9μ ｍ

13. CFMIP/GCSS BLWG workshop 2009/06/08-12 autoconversion2 in terms of Qc Color indicates the group of number concentration of cloud 。 Brown : the maximum number concentration group light blue, purple, blue, green Red : the smallest number concentration group. （ for the same mixing ratio, the small number concentration, the larger conversion rate) cloud water （ g/kg ） autoconversion2 （ mg/kg/s ）

14. CFMIP/GCSS BLWG workshop 2009/06/08-12 Autoconversion(Qc, Nc) Averaged over each group ⇒ Colors Brown : the maximum number concentration group light blue, purple, blue, green : the smallest number concentration group. Black : total average. cloud water （ g/kg ） autoconv （ mg/kg/s ） Autoconversion rate used in the bulk model. Kessler Berry Modified Berry

15. CFMIP/GCSS BLWG workshop 2009/06/08-12 Parameterization of each process １ independent variables (assuming 2-moment bulk scheme) cloud related ⇒ Qc, Nc, average mass of droplet, radius rain related ⇒ Q R, N R, average mass of drop, radius environment ⇒ T, θ, Qv 、 Qv-Q sat 、Ａ、 p 、 e 、 rh 、 w 。 Process （ mass & number ） variables condensation to cloudcloud & environment evaporation from cloudcloud & environment autoconv1( c -> r )cloud & environment autoconv1 ( r -> c )rain & environment autoconv2cloud (& environment) collision-coalescencecloud, rain & environment ：

16. CFMIP/GCSS BLWG workshop 2009/06/08-12 Parameterization of each process ２ An example autoconv( c -> r )cloud & general Previously proposed formula (examples). Assumed formula in this work ⇒ Searching the combination of variables which gives largest correlation coefficient.

17. CFMIP/GCSS BLWG workshop 2009/06/08-12 Parameterization of each process ３ Results of fitting parameters (few examples) Simulation results of the bulk model using these parameters ○Conversion from cloud to rain is very small, because the large number of small value occurrence determines the fitting parameter. ○Rain does not develop as in the bin model. ○We need some sophisticated technique to make a bulk parameterization scheme from the bin model results.

18. CFMIP/GCSS BLWG workshop 2009/06/08-12 Summary ○We applied CReSS-bin model to GCSS-BL ＷＧ RICO intercomparison case. ○Although the results show some difference from other model results, the results are within the range of the variation of the results of the models. (We need to compare the results with observational results and other bin model results. ) ○We need some sophisticated technique to make a bulk parameterization scheme from the bin model results. Future work ○to develop a 2 （ or more ） -moment bulk scheme. ○to apply the model to other cases and extend the model.

19. CFMIP/GCSS BLWG workshop 2009/06/08-12 Ｋ Ｂ N Integrated Liquid water(gm - 2 ) 100 0 Observational estimate 0 Surface precipitation(mm day -1 ) 1 Liquid water and surface precipitation DYCOMS Ⅱ t= ３～６ hr 。

20. CFMIP/GCSS BLWG workshop 2009/06/08-12 Physical process in bin model Liquid drops are divided into groups (bins). Size distribution of liquid drops is indicated by the number concentration of each bin equilibrium number remapping mass conserva tion coalescence remapping rain cloud autoconversion ： pink and orange (C+C->R) coalescence ： orange (R+C->R) boundary between cloud and rain Cond↑ Eva↓ radius Change of bin boundary