View
227
Download
0
Category
Tags:
Preview:
Citation preview
Initial Experiments on Simulation of Windshear and Significant Convection Events using Aviation Model (AVM)
Wai-Kin Wong1, C.S. Lau2 and P.W. Chan1
1- Hong Kong Observatory2- Hong Kong Polytechnic University
CMOS 2012 / General NWP-WAF Part 2
29 May 2012 (1E3.2 ID 5345 16:45-17:00H)
Operational Mesoscale NWP System in HKO
2
Meso-NHM- 10 km horizontal res.- 585x405x50 7.3 - 42.2 N; 89.9-
146.6E model top: 22.7 km- 72 hour forecast- 3-hourly update
RAPIDS-NHM- 2 km res., 305x305x60- 19.5 - 25.0 N; 111.2 -
117.1 E- model top: 20.3 km- 15 hour forecast- hourly update
Atmospheric Integrated Rapid-cycle (AIR) Forecast Model Systembased on JMA Non-Hydrostatic Model (NHM) and 3DVAR
Development of Aviation Model (AVM)
• Sub-kilometre resolution NWP to enhance support in aerodrome forecasts and development:
• Wind and windshear forecast guidance
• Windshear alerting service
• Headwind changes encountered by aircrafts under terrain-induced and sea-breeze windshear conditions
• Forecast techniques on:
• Significant convection• Visibility
Pearl River Delta (PRD) domain dx = 600 mForecast range = 9 hr
HK Airport (HKA) domain dx = 200 mForecast range = 6-9 hr
HK Airport (HKA) domain dx = 200 mForecast range = 6-9 hr
HK International
Airport
Target completion time for PRD+HKA = 1 hour
Update frequency = 1 hr
Initial and boundary conditions: RAPIDS-NHM (dx=2km)
Feasibility Study
• WRF-ARW (ver. 3.2.1) and JMA-NHM for PRD and HKA domains
• Estimate computation requirement for running AVM in real-time basis
• Numerical experiments• sea-breeze convergence• terrain-induced windshear• significant convection• low visibility (fog)
• Performance of two models are similar and WRF-ARW has higher code running efficiency
WRF T+4h forecast
Sea-breeze simulation
NHM forecast
Headwind profile “simulator” (PRD-AVM)- Simulated headwind change / windshear “encountered” by the flight during descending
Headwind profile simulator (HKA-AVM)
WRF T+6 h Forecast
Terrain-induced windshear2009-12-26 21 UTC
LIDAR
NHM Forecast
Surface AWS
HKIA
Headwind profile simulator (PRD-AVM)- Terrain-induced windshear
Headwind profile simulator (HKA-AVM)- Terrain-induced windshear
Significant convectionPRD-AVM WRF T+4 h forecast
NHM T+4 h forecastN.B. model forecast at a time lag of about 1.5 hr on the passage of squall line
Late evening thunderstorms and organized convections developed inland and passed over HK
(8-9 September 2010)
Widespread convection blocking airspace and traffic near HKIA on 18 September 2011
Rapid development of convection over airspace to the south
Radar seq. 06:00-16:00 HKT
Please refer to 3B2.4
09-18 02:00 UTC 02:30 UTC 03:00 UTC 03:30 UTC
04:00 UTC 04:30 UTC 05:30 UTC05:00 UTC
Simulated maximum reflectivity for model run at 2011-09-17 23:00 UTC
Selecting optimal physics scheme and parameters to simulate sea-breeze convergence and low-level windshear near take-off/landing zone
Expt. Model Physics
Original (a) CAM LW and SW radiation scheme(b) Eta similarity (used in Eta Model) based on Monin-Obukhov with Zilitinkevich
thermal roughness length and standard similarity functions from look-up tables(c) Mellor-Yamada-Janjic PBL (d) “simple” diffusion (gradient term taken along coordinate surfaces) for turbulence
and mixing(e) Eddy coefficient option (km_opt) using 2d deformation – horizontal diffusion
from horizontal deformation, vertical from PBL scheme
Test3 (a) RRTMG LW and SW radiation process(b) MM5 similarity surface layer based on Monin-Obukhov with Carslon-Boland
viscous sub-layer and standard similarity functions from look-up tables(c) LES PBL using model computed momentum flux u*, heat flux and moisture flux(d) “full” diffusion treatment (gradients using full-metric terms) (e) km_opt using 3d prognostic equation of TKE (1.5 order TKE closure)
“Optimal” physics options (for sea-breeze simulation)
And the effect of model tuning
Original “Test3”
On-going development
• Sensitivity tests on the physics options and new version of WRF codes
• Data assimilation techniques to ingest high resolution observations (surface AWS and LIDARs etc).
Thank you very much
Recommended