Transitioning Physics Advancements into the Operational Hurricane WRF Model

Transcription

1 Transitioning Physics Advancements into the Operational Hurricane WRF Model KATHRYN NEWMAN, MRINAL BISWAS, LAURIE CARSON N OA A / ESR L T EA M M E M B E RS: E. K ALINA, J. F RIMEL, E. GRELL, AND L. B ERNARDET CO L L A B O R ATO RS : G. TH O MPSO N ( RAL), G. GRELL ( NOAA/ ESRL ), R. FOV ELL ( U. ALBANY ), M. IACO NO ( AER), J. HENDERSO N ( AER), S. BAO ( C C U ), NOAA/EMC HU RRIC ANE TEAM

2 Overview of the DTC DTC purpose: Facilitate the interaction and transition of NWP technology between research & operations The DTC is a collaborative facility between NCAR & NOAA/ESRL/GSD Strong partnerships with operational partners & model developers is critical O2R: Support operational NWP systems to the community R2O: Partner with developers to get innovations into centralized code Perform diagnostics and T&E on promising NWP innovations for possible operational implementation Interaction between R&O: Workshops, visitor program, newsletter 2

3 DTC Strategies to promote HWRF O2R2O Role of Testbeds in NOAA 1. Code management Create and sustain a framework for NCEP and the research community to collaborate and keep HWRF code unified 2. User and developer support Support the community in using and providing improvements for HWRF 3. Independent testing & evaluation Funds the research community to partner with DTC in R2O 4. Visitor program Test and evaluate innovations for potential operational implementation 3 Ø DTC activities funded by NOAA (including HFIP), Air Force, NSF, and NCAR

4 Streamlining the Transition of New Developments into HWRF The DTC, in collaboration with EMC, provides support for HWRF developers / subject area experts Access to the unified HWRF code repository w/ experimental codes Support for inter-developers collaboration Training, assistance with developments, specialized helpdesk Oversight of code integration to avoid divergence Primary goal to facilitate R2O! Speeds transition of research into operations Allows for timely testing of promising new NWP innovations Accelerates improvement in weather forecasts 4

5 DTC Visitor Program Accepting proposals now! Providing support for visitors to work w/ the DTC to test new forecasting & verification techniques, models & model components for NWP Dev Niyogi & Subashini Subramanian Robert Fovell Shaowu Bao Ting-Chi Wu Michael Iacono & John Henderson Jun Zhang DTC Visitor Program Recent hurricane-related work Purdue Univ SUNY-Albany Coastal Carolina Univ Colorado State Univ AER U. Miami and HRD Developing Landfall Capability in Idealized HWRF for Assessing the Impact of Land Surface on Tropical Cyclone Evolution (2016) Impact of Planetary Boundary Layer Assumptions on HWRF Forecast Skill (2016) Evaluation of the microphysics scheme in HWRF 2016 version with remote-sensing data (2016) Evaluation of the Newly Developed Observation Operators for Assimilating Satellite Cloud Precipitation Observations in GSI within HWRF system (2017) Testing Revisions to RRTMG Cloud Radiative Transfer and Performance in HWRF (2016) Testing Variations of Exponential-Random Cloud Overlap with RRTMG in HWRF (2017) Evaluating the Impact of Model Physics on HWRF Forecasts of Tropical Cyclone Rapid Intensification (2017) 5

6 HWRF: a multi-component forecast system Atmospheric preprocessors Ø Ø Ø Ø Ø WRF NMM dynamic core Outer domain position based on storm location and projected path Storm-following inner nests Vortex relocation/improvement Data assimilation on D02/D03 Ø Regional Hybrid EnsDA for TDR/priority storms Vortex initialization GSI WRF atmosphere Post processing Vortex tracker u Operational at NOAA for 5-day forecasting u Used by NHC for AL and EP, available for all basins u A community model 6 Ocean initialization NCEP coupler MPI-POM-TC

7 Physics Advancements R2O RRTMG radiation & implementation of partial cloudiness Improvements to PBL physics complementary to use of RRTMG radiation Thompson microphysics & partial cloudiness modifications Grell-Freitas cumulus Partial cloudiness modifications and updated cloud overlap methodology for RRTMG Grell-Freitas cumulus (underway) Cloud overlap methodology enhancements for RRTMG (partnership with DTC visitor program) ü Physics updates delivered to EMC and included in 2015 HWRF ü Partial cloudiness modification implemented in 2016 HWRF ü Partial cloudiness modifications implemented in 2017 HWRF ü GF scheme, cloud overlap enhancements candidates for 2018 HWRF 7 Close interactions & support for developers is a critical component of T&E

8 DTC s role in HWRF development: connecting the pieces Forecast improvement HWRF implementation EMC tested partial cloudiness together with other (PBL) innovations Shortcomings in GFDL scheme identified by Fovell and Bu Cloud top cooling due to radiation RRTMG old RRTMG+partial cld GFDL radiation RRTMG radiation DTC developed and tested partial cloudiness scheme DTC/EMC tested RRTMG scheme Forecast degradation 8

9 Included in 2015 operational HWRF RRTMG & Partial Cloudiness EP Basin Intensity Bias 1000-hPa Temp RMSE Intensity Bias (kt) DIFF RMSE GFDL RRTMG + PC Difference Experiment Degrades Experiment Improves üposition error for both Atlantic and eastern North Pacific (EP) basin neutral ürrtmg + partial clouds alleviates negative intensity bias in EP basin 9 ü RRTMG+ Partial Clouds improves low-level T (& RH) biases

10 Grell-Freitas test 2016 T&E focus: Grell-Freitas cumulus HWRF with SASAS (H6CL) Cumulus Scale Aware SAS GF HWRF with GF (H6GF) Microphysics Ferrier-Aligo Ferrier-Aligo Surface layer HWRF HWRF Land surface Noah LSM Noah LSM PBL GFS Hybrid EDMF GFS Hybrid EDMF Radiation RRTMG RRTMG q Horizontal grid spacing: 18, 6, 2 km q Inner nests move to follow storm q Domain location varies from run to run depending on storm location q 61 vertical levels; top at 2 hpa 10

11 GF: track and intensity errors GF SASAS Difference Mean Track Error Mean Absolute Intensity Error Mean Intensity Error Storms included: Gonzalo (2014) Edouard (2014) Matthew (2016) Neutral to positive track forecasts improvements for GF scheme Negative intensity bias was alleviated for the GF scheme especially at longer lead times 11

12 GF: rapid intensification (RI)!! Model Forecast Model Forecast Control GF Observation RI No RI RI No RI Observation RI No RI RI No RI RI is defined as 20 kt intensity increase in 24 hr POD = 0.35 FAR = CSI = GF configuration more accurately predicts RI occurrence, but increases number of false alarms POD = FAR = CSI =

13 GF: precipitation Closed circle - GF Solid line - SASAS Time series of area-averaged accumulated precipitation Parent domain average Total precipitation Explicit precipitation Convective precipitation GF produces higher total precipitation than control Explicit precipitation higher than convective precipitation in GF HWRF-GF: Majority of precipitation from explicit precipitation. 13

14 GF: scale awareness 14 Both configurations exhibit scale-awareness o Convective temperature tendencies decrease from coarser to finer resolution o GF scheme less active

15 GF test summary EMC decided to retain the SASAS cumulus scheme as a component of the operational HWRF physics suite for GF scheme showed promise, but had reproducibility issues Updates and fixes made to GF scheme, now in HWRF repository Current T&E work focused on physics advancement Testing underway for GF cumulus scheme as candidate for 2018 operational implementation. Continued partnerships with DTC visitor program and subject area experts Iacono/Henderson (AER) enhancements to cloud overlap methodology within RRTMG candidate for 2018 operational implementation 15

16 Summary 16 DTC facilitates R2O through several mechanisms Developer support, DTC visitor program, independent T&E Focus on physics advancements Successful engagement in NOAA/EMC HWRF preimplementation process Promotes visibility of research community innovations Advancing forecast skill of operational hurricane model Resources The DTC is funded by NOAA, Air Force, and NCAR This work was supported by NOAA OAR, HFIP