Model Diagnostics HRD Activities and Plans HFIP Diagnostics
- Slides: 18
Model Diagnostics: HRD Activities and Plans HFIP Diagnostics Workshop Friday, August 10, 2012 Joe Cione, Rob Rogers, Eric Uhlhorn, Tomi Vukicevic, and Jun Zhang
Outline • HWRF surface-layer evaluations (Cione, Uhlhorn) • Preliminary HWRF vortex- and convective-scale evaluations during RI (Rogers) • Preliminary HWRF PBL evaluations (J. Zhang) • New low-wavenumber verification metric (Vukicevic)
What is the dominant thermodynamic factor impacting TC surface moisture flux? Ocean (qs(SST))…or…Atmosphere (q 10) TCBD (observations) HWRF V 3. 2
How well does HWRF represent low-order structure of an intensifying TC? • Composites of inner-core structure from airborne Doppler for intensifying and steady-state TC’s indicate distinct differences in inner-core structure • How well do HWRF forecasts of intensifying and steady-state TC’s depict this structure? Can it capture these differences? • First step: start with a single HWRF forecast of an intensifying TC (Earl 2010) 3 -km HWRF (initialized 12 UTC 27 August) forecast track and intensity
Intensifying (I) Intensity traces HWRF Earl forecast Steady-state (SS)
I height (km) 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 0. 5 1 1. 5 2 2. 5 3 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 SS 0. 5 1 1. 5 2 r/RMW 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 HWRF 0. 5 1 1. 5 r/RMW 33 30 27 24 21 18 12 9 6 5 4 3 r/RMW height (km) Axisymmetric vertical vorticity (x 10 -4 s-1) 2 2. 5 3 33 30 27 24 21 18 12 9 6 5 4 3 2. 5 3
Locations of convective bursts # of burst grid points (> 5. 5 m/s) = 749 # of burst grid points (> 5. 5 m/s) = 342 I SS # of burst grid points (> 3 m/s) = 300 HWRF
Radial distribution of convective bursts SS frequency (%) I r/RMW frequency (%) HWRF r/RMW
HFIP proposal PI: Jun Zhang, David Nolan and Sylvie lorsolo Collaborators: Robert Rogers and Paul Reasor Objectives: To develop metrics for evaluating the inner-core structure simulated by the HWRF model in order to improve the intensity and track forecast. 1) vortex-scale structure 2) convective-scale structure 3) boundary layer structure Year 1: 1) develop metrics for model evaluation through analyzing observational data (i. e. , Doppler radar and dropsonde data) 2). Test the structural metrics using case study 9
Height of Vtmax model Black dashed line represents the height of maximum tangential wind speed 10
Inflow layer depth model Black line represents the height of 10% peak inflow 11
Mixed layer depth model Black line represents dθv/dz=3 K/km 12
Future work Test other metrics using the Earl run: 1. eyewall slope 2. TKE 3. CFADs of vertical velocity 4. Metrics for asymmetric structure …… 13
A new metric for intensity forecast verification Tomi Vukicevic, Erick Uhlhorn, Paul Reasor and Brad Klotz NOAA/AOML/HRD
Maximum intensity decomposition • Without approximation, the maximum intensity of a wind field at 10 m (or any height) in coordinate system could be expressed by the following decomposition and are amplitudes of azimuthal wave number 0 and 1, respectively • is total contribution from higher harmonics • • Maximum intensity = deterministic + stochastic component • By definition because
Maximum intensity verification using the decomposition • is characterized by a non-Gaussian pdf • Verification of the maximum intensity consists of – Verification of PDF and – Deterministic amplitude • Data used for verification – Observations: BT, SFMR (P-3/NOAA and AF), TDR (P-3) Model : HWRFx forecasts and HEDAS analyses • Cases from 2008 -2011 seasons
Verification of stochastic component : comparison of HEDAS V 0, V 1 and Vmax FORECAST V 0, V 1 and Vmax All PDFs show stochastic nature of with small mean, standard deviation compatible with the BT error estimate (~4 -5 m/s), and positive skewness Forecast- and observation-based PDFs are compatible implying that the forecast has good skill for the stochastic component of the intensity PDFs HEDAS V 0 and V 1 USING BT Vmax OBSERVATIONS ONLY SFMR V 0+V 1 and BT Vmax OBSERVATIONS ONLY TDR V 0 and V 1 and BT Vmax
Verification of deterministic component • So far have forecast decomposition results Examples of Wave 0 RI, while stochastic component is negative • Working on verification against SFMR based decomposition – Need to match SFMR and Forecast dates for verification of wave 0 and 1 amplitudes
- Strategically oriented cycle of hrd activities
- Training and hrd process model
- Hrd subsystem
- Group these activities into indoor and outdoor activities
- Primary and support activities
- Primary activities and tertiary activities
- Project appraisal
- Implementing hrd programs
- Steps in designing hrd programs
- Characteristics of ihrm
- Hrd design
- Operating activities vs investing activities
- Erd commander 2010
- Mitel 5000 hx
- Hrd strategy towards 2030
- Task analysis in hrd
- Role of personnel management
- Hrm vs hrd
- Hrd for workers