TC forecasting with variable resolution in CAM-MPAS

Transcription

1 TC forecasting with variable resolution in CAM-MPAS Sang-Hun Park Bill Skamarock, Chris Davis, Jimy Dudhia and Michael Duda collaborators (CGD) :: Peter Lauritzen, Andrew Gettelman and Stephen Yeager National Center for Atmospheric Research 06/22/2016

2 TC forecasting using CAM-MPAS Why test CAM-MPAS for TC forecasting? 10km is overlapping area between global NWP and climate experiments (GFS is running 15km vs. climate simulations are running 1/4 or 1/8 ) We want to (or should) test our physics suite (or a scheme) at high resolution. Sometimes NWP tests are better option for evaluative testing than long-term simulations (Our goals should be similar!! [e.g., mesoscale convective system, terrain effect] ) Maybe (or hopefully), a good step toward seamless predictions

3 MMM efforts for TC forecasting TC 2015 WP region EP region AL region Using variable meshes with MPAS, 10-day simulations are being tested in summer for three different regions

4 Global TC forecasting: CAM-MPAS & WRF-MPAS a mesh for simulations (WP region) variable resolution (15 60km) 16km 20km 25km 55km 40km CAM-MPAS WRF-MPAS Initial Data GFS 15km F00 Analysis SST POP2 hindcast* GFS 15km Skin temp. Run Time 5 Days 10 Days Model Top 45km (30 lev.) 30km (55 lev.) Mesh Size Cells** dt (dyn.) 60s 90s dt (phys.) 1800s 90s (30m for LW/SW) * POP2 hindcast :: from Stephen Yeager ** uniform 30km :: Cells ** uniform 15km :: Cells CAM-MPAS WRF-MPAS Deep Conv. ZM Tiedtke Shallow Conv. PARK Tiedtke PBL BRETHERTON-PARK YSU Macro PARK WSM6 Micro MG1 WSM6 Aerosol MAM3 none

5 CAM-MPAS MPAS TC Forecasting CAM TC bias CAM-MPAS with POP2 Global TC forecasting - CASE courtesy :: digital-typhoon 1511 NANGKA 1509 CHANHOM nmsc.kma.go.kr CAM5.5-MPAS Summary

6 MPAS Track forecasing CHANHOM ( ) NANGKA ( ) best track WRF-MPAS CAM-MPAS 1st 5-day forecasting 2nd 5-day forecasting 3rd 5-day forecasting 4th 5-day forecasting 5th 5-day forecasting

7 MPAS TC intensity CHANHOM ( ) NANGKA ( ) best track WRF-MPAS CAM-MPAS 1st 5-day forecasting 2nd 5-day forecasting 3rd 5-day forecasting 4th 5-day forecasting 5th 5-day forecasting

8 MPAS TC intensity CHANHOM ( ) What can cause these intensity biases? strong surface flux (coupled system will be helpful?) wrong mixing in the PBL not enough stabilization of CPS interaction between physics best track WRF-MPAS CAM-MPAS

9 Coupled System in TC sst cooling from coupled system has important role for TC intensity Bender & Ginis (2000) many operational center are using coupled system: HWRF, GFDL, COAMPS-TC Kim et al. (2014) HWRF only HWRF + HYCOM

10 Coupled simulations (POP2) for CAM-MPAS CHANHOM ( ) NANGKA ( ) best track CAM-MPAS CAM-MPAS with POP2 *atm : MPAS 15-60km *ocn : gx1v6 1st 5-day forecasting 2nd 5-day forecasting 3rd 5-day forecasting 4th 5-day forecasting 5th 5-day forecasting

11 Surface flux in TC strong sensitivity to C k /C d in maximum hurricane (see - Emanuel, 1995 & 2004) Bryan (2012) Emanuel (1995) C d : exchange coefficient for momentum C k : for entalphy

12 CAM-MPAS MPAS TC Forecasting CAM TC bias CAM-MPAS with POP2 CAM5.5-MPAS Summary Surface Flux in CAM MPAS U 10 vs. Ck /Cd h +36h h +36h Differences are mainly from low winds cases But, the ratios between Cd and Ck are comparable specially in high-winds. These are very consistent during other simulations

13 CAM-MPAS with CLUBB CHANHOM ( ) NANGKA ( ) best track CAM-MPAS CAM-MPAS with CAM5.5 1st 5-day forecasting 2nd 5-day forecasting 3rd 5-day forecasting 4th 5-day forecasting 5th 5-day forecasting

14 CAM-MPAS with CLUBB composite analysis from OBS. CAM5.3 RMW 55km CAM5.5 RMW 100km Zhang et al. (2011) tangential, 5/ms radial, 4/ms Note that real TC size is smaller in UW-PBL.

15 CAM-MPAS with CLUBB CAM5.3 K m, w For r/rmw 3.5, very small amount of vertical diffusion in UW-PBL (inflow can be strong with shallow depth) CAM5.5 K m, w PBL height Both results show larger K m than observation (CBLASAT), but in UW-PBL, maximum value is too high. Overall, all of these can support strong inflow with shallow depth in UW-PBL, which create strong and small TC.

16 Conclusions and Future Study Current CAM (CAM5.3) has bias toward stronger TC in CAM-MPAS simulations. The ratio between C d and C k are comparable in CAM and WRF physics even with strong TC bias in CAM. Coupling with POP2 can mitigate these strong TC. Role of UW-PBL in global TC forecasting is unclear (not enough mixing? or too much mixing?) CAM5.5 (mainly for CLUBB) is very helpful in this study to have reasonable BL structure of TC. We will try to run using CAM6 and coupled with POP2. It will be a good option to perform these in non-hydrostatic scales ( 10km in MPAS) to get more scientific issues.

17 Conclusions and Future Study We are also very interested in long-term climate simulation using CAM-MPAS We will investigate energy balance issues (mainly from different vertical coordinate with other dycores) (working with Peter Lauritzen)