Real- Time Predic.on of the Tropics using the Model for Predic.on Across Scales (MPAS)

Transcription

1 Real- Time Predic.on of the Tropics using the Model for Predic.on Across Scales (MPAS) Chris Davis, Bill Skamarock, Joe Klemp, Dave Ahijevych, Wei Wang, and Michael Duda Na.onal Center for Atmospheric Research Boulder, CO

2 Global Modeling of Tropical Cyclones: Benefits from global models at high resolu.on Archambault et al. 2013, MWR

3 Based on unstructured centroidal Voronoi (hexagonal) meshes using C-grid staggering and selective grid refinement. Non-hydrostatic Jointly developed, primarily by NCAR and LANL/DOE MPAS infrastructure - NCAR, LANL, others. MPAS - Atmosphere (NCAR) MPAS - Ocean (LANL) MPAS - Ice, etc. (LANL and others) Project leads: Todd Ringler (LANL) Bill Skamarock (NCAR)

4 Global TC Predic.on Predic.on of TCs out to day 10 MPAS and GFS Tracks, genesis, misses and false alarms Variable vs. uniform resolu.on (MPAS) Genesis in global models: WP: Tsai et al. (2011): WAF AL: Halperin et al. (2013): WAF

5 Model Configura.on 15- km uniform MPAS versus 60/15 km variable resolu.on (MPS2) Ini.alized with 00 UTC GFS 52 forecasts 10 Aug. 30 Sep TCs during period Physics: Tiedtke cumulus WSM6 microphysics YSU PBL Noah LSM RRTMG l.w. and s.w. radia.on 41 levels: model top 30 km 15 km 60 km

6 Tropical Cyclone Forecasts and Verifica.on Track vor.city features in model (850 hpa) Greater than 1.5x10-5 s - 1 average vor.city (200 km rad.) Match based on separa.on from observed TC Usagi Pabuk Kochi University Archive

7 Track Matching: Goal: Determine whether the model is simula3ng a storm that exists Best Track Individual tracks defined separately Tracks match if there is at least one.me when both are TCs and within threshold distance Model Track Tracks match: Hits are assigned during period observed system is TC Tracks do not match: False alarm is assigned during period model system is TC

8 Example model tracks Gabrielle model tracks #138, #674, and #85 match Gabrielle interpola.on between end points

9 FA/Hits( FA/Hits( 5.00# 4.50# 4.00# 3.50# 3.00# 2.50# 2.00# 1.50# 1.00# 0.50# 0.00# 0# 48# 96# 144# 192# 240# 3.50# 3.00# 2.50# 2.00# 1.50# 1.00# 0.50# 0.00# False- Alarms- to- Hits Ra.o Time((h)( 0# 48# 96# 144# 192# 240# Time((h)( ATL MPAS# MPS2# GFS# WPAC MPAS# MPS2# GFS# Hits very similar among models, fall slowly with lead.me. MPAS has numerous false alarms in both basins ATL has rela.vely more false alarms: models s.ll struggle with subop.mal environments. MPS2 clearly best in WPAC: physics appropriate for resolu.on

10 False Alarms (MPAS) MPS2 MPS2 m/s m/s

11 2- m Water Vapor and PW: WPAC Rela.onship to TC errors??? Compared with GFS Analysis PBL too moist Tropics: N Extra- Trop: N MPS2 dries

12 West Pacific RMS Posi.on Errors Track Errors

13 Atlan.c RMS Posi.on Errors

14 Conclusions Developed automated tracking and genesis verifica.on for 10- day global forecasts For matched systems, MPAS and GFS similar in WPAC; GFS slightly more skillful in ATL Significant false alarm tendency at 15- km grid spacing in MPAS: numerous marginal storms Evidence that variable and fixed resolu.on give very similar results where resolu.ons are the same, at least out to day 7.

15 MPAS-Atmosphere Unstructured spherical centroidal Voronoi meshes Mostly hexagons, some pentagons and 7-sided cells. Cell centers are at cell center-of-mass. Lines connecting cell centers intersect cell edges at right angles. Lines connecting cell centers are bisected by cell edge. Mesh generation uses a density function. Uniform resolution traditional icosahedral mesh. C-grid Solve for normal velocities on cell edges. Solvers (1) hydrostatic equations (PEs) (2) Fully compressible nonhydrostatic equations (explicit simulation of clouds) Solver Technology Integration schemes are similar to WRF.

16 Matching and False Alarms

17 Matching and False Alarms