Hurricane Model Transitions to Operations at NCEP/EMC 2009 IHC Conference, St. Petersburg, FL Robert Tuleya*, V. Tallapragada,Y. Kwon, Q. Liu, Zhan Zhang, Yihua Wu,J. O’Connor and N. Surgi * JHT sponsored

Project Goals and Emphasis Participate in the yearly operational implementation of HWRF Participate in the yearly operational implementation of HWRF Upgrade HWRF system Upgrade HWRF system Trouble shoot problems Trouble shoot problems Goal: increase both track and intensity skill Goal: increase both track and intensity skill Continued collaboration with URI, Florida State, GFDL, and others Continued collaboration with URI, Florida State, GFDL, and others

HWRF Hurricane Forecast System HWRF model Coupled with POM NHC storm message Position domain Synoptic fields for many variables Create file for track, intensity, etc Get OBS, Model Input initial & boundary conditions Ocean Initialization Initialize wake, loop currents & eddies Wrf si (used for topographical parameters) Wrf real : replace with interpolations from native model data storm analysis and data ingest 6hr 1st guess vortex relocation 3DVAR gsi for both nests Next cycle

HWRF – GFDL HWRF – GFDL Grid configuration 2-nests (coincident) 3-nests(not coincident) NestingForce-feedback Interaction thru intra-nest fluxes Interaction thru intra-nest fluxes Ocean coupling POM (atlantic only) POM Convective parameterization SAS mom.mix. Explicit condensation FerrierFerrier Boundary layer GFS non-local Surface layer GFDL..(Moon et. al.) Land surface model GFDL slab/ NOAH GFDL slab Dissipative heating Based on D-L Zhang Based on M-Y tke 2.5 Gravity wave dragYESNO Radiation GFDL (cloud differences) GFDL

HWRF 2008 Skill

Hourly intensity Hourly model data Model atcf data Model variability may be important ?

Season statistics not affected

Sfc Temperatures Problems in HWRF remaining b.c. noise?? (fixed)

Fay Impact of Tsfc fix: (improved track, more intense) HWRF prod Tsfc fix HWRF prod Hwrf

Gustav Impact of Tsfc fix: (improved track, same intensity) Tsfc fix HWRF prod Tsfc fix Hwrf

Other potential improvements  Surface flux formulations  Land surface modeling  Gravity wave drag  High resolution

Reduced Surface Drag

Noah LSM studies - Background Noah LSM studies - Background GFDL Slab LSM 1) One level, only predicts surface temperature, wetness is fixed, no runoff Noah LSM 1) The operational LSM in NCEP's operational mesoscale forecast model (Ek et al., 2003) 2) Multiple soil layers (usually 4 layers: 0-10,10-40, and cm depth) with a one-layer vegetation canopy 3) Spatially varying root depth and seasonal cycle of vegetation cover 4) Frozen soil physics for cold regions, and improved soil and snowpack thermal conductivity. 5) The Noah LSM predicts soil moisture, soil temperature, land surface skin temperature, land surface evaporation and sensible heat flux, and total runoff. 6) The HWRF runoff prediction using the Noah LSM can then be used as forcing input to EMC's Streamflow Routing Scheme (Lohmann et al., 2004). Additionally, 7) The HWRF-Noah forecasts of soil moisture and runoff are good spatial indicators of soil moisture saturation (water logging) and flooding.

HWRF Predicted Tracks of Katrina Obs With/without NOAH LSM Other sfc & bl physics

12 Hour Accum. Rainfall (mm) Observed rainfall is the rain gauge measurement Observed rainfall spreads in larger area than NAM and HWRF rainfall did HWRFNAMOBS 48h 72h

Forecasted Stream Flow (m 3 s -1 )

Influence of orography on the atmosphere Create obstacles and additional turbulence Generation of vertically propagating gravity waves Gravity wave drag Change the large scale flows Change the track of hurricanes

1.Track forecast skills of HWRF on Eastern Pacific storms are not as good as those on Atlantic storms 2.Diagnotics of HWRF indicates the anomalous flows developed over Mexican Plateau seems to cause the less skillful track forecast of HWRF 3.Proper GWD representation might improve the track forecast of HWRF 4. GWD improved NAM Motivations Results NEXT PAGE

No GWD GWD ~ 50nm improvement at t=120hr

High Resolution HWRF Experiment  Resolution - Control: 0.18, 0.06 (~27km, ~9km) - Control: 0.18, 0.06 (~27km, ~9km) - High Res: 0.09, High Res: 0.09, 0.03  Domain - Control: 216x432, 60x100 - Control: 216x432, 60x100 - High Res: 432x862, 118x198 - High Res: 432x862, 118x198  Time Step - Control: 54, 18 (sec) - Control: 54, 18 (sec) - High Res: 27, 9 (sec) - High Res: 27, 9 (sec)  Ocean Coupling - Coupled with HYCOM (resolution remains the same) - Coupled with HYCOM (resolution remains the same) - Coupling time: every 9 minutes - Coupling time: every 9 minutes  Case Study - Hurricane RITA, starting from Hurricane RITA, starting from

9 km 4.5 km More banding

4.5km (HRES) HWRF somewhat more accurate

HWRF Accomplishments  HWRF severely test in the active Atlantic Season. HWRF ran in a robust, timely fashion. HWRF competitive with best operational guidance.  HWRF installed GWD and fixed sfc temperature issues  HWRF working on LSM, sfc parameterizations, and higher resolution. HWRF Plans  Upgrade physics, initialization and test ensembles  More extensive & quantitative diagnostics  Implement new ocean & wave model

The NMM-WRF Modeling System  Regional-Scale, Moving Nest, Atmospheric Modeling System.  Non-Hydrostatic system of equations formulated on a rotated latitude-longitude, Arakawa E-grid and a vertical, pressure hybrid (sigma_p-P) coordinate.  Advanced HWRF,3D Variational analysis that includes vortex reallocation and adjustment to actual storm intensity.  Uses SAS convection scheme, GFS/GFDL surface, boundary layer physics, GFDL/GFS radiation and Ferrier Microphysical Scheme.  Ocean coupled modeling system (POM GFDL).

Technical Details of Operational HWRF POM Coupled System run by NCEP Central Operations Total No. of working Scripts (.sh, *.scr, *.pl files) (.sh, *.scr, *.pl files)34 NCO Job Scripts (trigger and queue the scripts through schedule maintenance software SMS) 29 NCO SMS scripts (driver scripts that provide arguments for *.sh) 27 Parameter files (namelist files) 25 Working space required for running one 126- hr HWRF coupled forecast ~50 GB Output volume (archived) ~4.5 GB Total run time for end-to-end HWRF forecast ~110 min. per forecast Max. Resources required per forecast 80 processors (5 nodes on NCEP production machine) for 60 min. Maximum Number of Forecasts 4 per cycle

Sporadic SLP noise  Sea level pressure diagnostic  Model or post processing ??  Traced to grid movement Noise

Eliminate SLP Noise  Modify topographic smoothing zone  Adjust mass fields  No more Noise !

LGM Background (2) The GFDL Slab LSM is the default in HWRF: 1.The initial soil moisture remains fixed in time during the HWRF forecast. 2.Moreover, the initial conditions of soil moisture in the Slab LSM are a fixed field that never change throughout the year and thus are unable to capture antecedent soil moisture conditions. 3.The Slab LSM does not predict the runoff response to HWRF precipitation forecasts, thus cannot predict streamflow from HWRF forecasts.

Why do we need GWD parameterization? NWP models use grid-averaged (smoothed) terrain data Coarse resolution models ( > 4km) cannot resolve the GWD caused by subgrid scale topography

HWRF Track Skill  Competitive with other guidance  Better than GFDL & NGAPS  GFS & UKMET quite good  Few long lasting storms in 2007  EPAC HWRF not as good HWRF

HWRF Intensity Skill  Competitive with other guidance  Some improvement over GFDL at early times  Not a good year for dynamic models after accounting for landfall  EPAC intensity degraded-no ocean coupling HWRF