WWOSC 2014 Thursday, August 21, 2014 Montreal, Canada Advancing Microphysics Parameterizations in the Hurricane Weather Research and Forecasting (HWRF) System Christina Holt1,2,3, Ligia Bernardet1,2,3, Mrinal Biswas1,4 1Developmental Testbed Center 2NOAA ESRL Global Systems Division, Boulder CO 3University of Colorado CIRES , Boulder CO 4National Center for Atmospheric Research, Boulder, CO Acknowledgements: Rob Fovell, UCLA

Outline The role of the DTC The Community HWRF Implementation tests performed at DTC Current collaboration with research community Ongoing & preliminary findings Future work 2

The Developmental Testbed Center …is a distributed facility (NCAR and NOAA) where the NWP community can test and evaluate models and techniques for use in research and operations DTC’s Goals Link Research and Operational Communities Speed transition of research results in operations Accelerate improvement in NWP Develop and test promising new NWP techniques Provide an opportunity for NWP community to perform cycled tests of model and data assimilation systems 3

DTC Strategies to promote HWRF R2O Code Management Create and sustain a framework for NCEP and the research community to collaborate and keep HWRF code unified User and developer support Support the community in using an operational hurricane model DTC Visitor Program – some approved projects involving HWRF Development of an HWRF diagnostics module to evaluate intensity and structure using synthetic flight paths through tropical cyclones (J. Vigh - NCAR) Diagnosing tropical cyclone motion forecast errors in HWRF (T. Galarneau - NCAR) Improving HWRF track and intensity forecasts via model physics evaluation and tuning (R. Fovell - UCLA) Evaluation of two HWRF microphysics/radiation configurations with remote-sensing data (S. Bao – CCU) Testing and Evaluation Perform tests to assure integrity of community code and evaluate new developments for potential operational implementation 4

HWRF: NOAA operational hurricane model HWRF Components WRF-NMM model (NMM) Pre-Processor (WPS and prep_hybrid) Vortex improvement Data assimilation (Gridpoint Statistical Interpolation) Coupler (NCEP) Ocean (Princeton Ocean Model for Tropical Cyclones-TC) Post-Processor (UPP) Vortex Tracker (GFDL) POM-TC Atmospheric preprocessors Ocean initialization Post processing Vortex tracker NCEP coupler Vortex initialization WRF atmosphere GSI Community version released each year in August Reflects the current year’s operational HWRF capabilities 5

HWRF v3.5a Atmospheric Configuration Introduced an empirical scaling factor, gfs_alpha, that reduces mixing by limiting the momentum eddy viscosity POM-TC 3 km 9 km Introduced an empirical dependency of BL height on Critical Richardson Number 27 km Physics Parameterization Cumulus (d01 and d02) Simplified Arakawa Schubert with shallow convection Microphysics Ferrier for the tropics Planetary Boundary Layer GFS (Hong and Pan 1996,Vickers and Mahrt 2004, Gopal et al 2013) (90:90:30 s) Surface Layer GFDL (modified) Land Surface Model GFDL slab model Radiation GFDL (60:60:60 min)

HWRF T&E: Thompson/RRTMG Thompson vs. Ferrier RRTMG vs. GFDL Advects individual species Advects total condensate Partial Double Moment Single Moment 6-classes w/ graupel Cloud, rain, and snow Coupled with RRTMG (mixing ratio & concentration) Supplies only MR to radiation scheme Tested for HWRF: red. int. bias at long lead times in ATL Used in Operational HWRF Uses internal assumptions to compute concentrations given MR Uses assumptions consistent with Thompson to compute concentrations given MR Interacts with clouds Interacts with clouds* Tested for HWRF: red. int. bias at long lead times in the ATL Used in Operational HWRF * Inconsistencies between Ferrier and GFDL radiation: clouds too transparent to radiation -Rob Fovell, UCLA, HFIP Participant Thompson mp for Hurricane Sandy improved track forecasts -A. Chakraborty, India CAOS, NCAR/RAL visitor DTC: Coupling of the Thompson with RRTMG 7

Track error Intensity Bias North Atlantic Eastern North Pacific T/RRTMG F/GFDL Track error T/RRTMG improves track for AL but degrades for EP North Atlantic Eastern North Pacific Intensity Bias In 2013, the DTC ran a test changing the microphysics and radiation to T/RRTMG over several hundred cases in both the ATL and EP and found that, although we expected improvement from the more physical parameterizations, there were degradations in the track and creation of a negative intensity bias in the EP. This became the focus of a case study at the DTC and for visiting scientists. T/RRTMG increases intensity for shorter lead times, decreases for longer lead times T/RRTMG creates negative intensity bias in EP 8

Case study: Daniel 04E Thompson too fast and northward; reason under investigation Ferrier runs similar at 5-day lead time Bulk statistics for Daniel 04E and case study show that Thompson takes track to N Storms are in area of strong SST gradient Northern tracks leads to cool SST under storm and low bias SST (C) 9

DTC VSP: Rob Fovell and Peggy Bu, UCLA HWRF’s GFDL radiation scheme is deficient with respect to cloud-radiative forcing (CRF)… see Bu et al. (2014) With proper CRF, the horizontal extent of the near surface wind field increases Storms with larger wind fields advect more planetary vorticity northward (beta drift) and move faster Westerly moving storms pull northward, and are ahead of the observed storm Working Hypotheses: CRF and gfs_alpha work together to broaden the wind field too much, causing increased beta drift northward Once the storms are over cold water to the north, they lose intensity

Results from DTC visit Courtesy of Rob Fovell T/RRTMG has broader/weaker storm T/RRTMG has narrower/weaker storm F/RRTMG has slightly weaker, broader storm 72-96 hr 30-36 hr gfs_alpha = 0.7 11

New DTC Physics Experiments Series of forecasts started from the same initial conditions using HWRF v3.5a Varying microphysics scheme and gfs_alpha Assess storm size and track changes Are the forecasts with real storm settings consistent with the working hypotheses from the ideal studies? gfs_alpha Microphysics Radiation 0.7 Ferrier GFDL 0.4 Thompson RRTMG

Storm Tracks for Daniel (EP 2012) Thompson 0.4 Thompson 0.7 Ferrier 0.4 Ferrier 0.7 Ferrier/GFDL/0.7 Best Track Tracks diverge around 60 hrs Thompson fcsts take a northward track gfs_alpha = 0.4 has a more accurate track Ferrier is less sensitive to gfs_alpha

Average Radial Velocity Averaged over first 60 hrs Averaged over 60 -126 hrs Thompson 0.4 Thompson 0.7 Ferrier 0.4 Ferrier 0.7 Ferrier/GFDL/0.7 Observed

Summary The findings in the real case study reflect the idealized findings obtained by DTC Visiting Scientists CRF + larger gfs_alpha broaden the wind field at shorter lead times Broader wind field (all else equal) leads to northward track Investigation of other factors is needed to determine the intensity/size relationships with physics Further testing would be necessary to identify potential alternatives for operational implementation Rapid Radiative Transfer Model - Global

Moving forward DTC will continue to work with visiting scientists Assess the impact of gfs_alpha, radiation, and microphysics combinations on forecasts Provide resources to assess the potential for future R20 Look at radiation budgets, and the sensitivity of track, intensity, and structure to CRF Community Support by DTC Model freely available and supported Upcoming release this month 2014 operational capability Idealized capability Support for all basins Unified Python scripts with EMC Improved model for 2014 Updated moving nests, ocean, and initialization improved forecast Opened opportunities for major future developments Ongoing development Framework: multiple moving nests Physics for high-resolution LSM, storm surge, inundation DA / Initialization