Na#onal Hurricane Center Official Intensity Errors

Similar documents
PSU HFIP 2010 Summary: Performance of the ARW-EnKF Real-time Cloud-resolving TC Ensemble Analysis and Forecasting System.

Convection-permitting Ensemble Data Assimilation of Doppler Radar Observations for Hurricane Prediction

Assimilate W88D Doppler Vr for Humberto 05

Tropical Cyclone Modeling and Data Assimilation. Jason Sippel NOAA AOML/HRD 2018 WMO Workshop at NHC

Impact of Assimilating Aircraft Reconnaissance Observations in Operational HWRF

DA/Initialization/Ensemble Development Team Milestones and Priorities

A pseudo-ensemble hybrid data assimilation system for HWRF

Mesoscale Ensemble Data Assimilation: Opportunities and Challenges. Fuqing Zhang Penn State University

Retrospective and near real-time tests of GSIbased EnKF-Var hybrid data assimilation system for HWRF with airborne radar data

Discussion on HFIP RDITT Experiments. Proposal for extending the life of RDITT for one more year: Future Plans from Individual Groups

Development and research of GSI based hybrid EnKF Var data assimilation for HWRF to improve hurricane prediction

Assimilation of Airborne Doppler Radar Observations Using the Unified GSI based Hybrid Ensemble Variational Data Assimilation System for HWRF

2014 real-time COAMPS-TC ensemble prediction

ARW/EnKF performance for the 2009 Hurricane Season

Overview of HFIP FY10 activities and results

University of Miami/RSMAS

The Use of GPS Radio Occultation Data for Tropical Cyclone Prediction. Bill Kuo and Hui Liu UCAR

COAMPS-TC 2015 Version, Performance, and Future Plans

Recent COAMPS-TC Development and Future Plans

Testing and Evaluation of GSI Hybrid Data Assimilation for Basin-scale HWRF: Lessons We Learned

Tropical Cyclone Mesoscale Data Assimilation

Numerical Weather Prediction: Data assimilation. Steven Cavallo

Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

Ensemble Data Assimilation and Predictability of Tropical Cyclones

Ensemble Data Assimilation and Predictability of Tropical Cyclones

PSU WRF-EnKF Realtime Performance for Sandy 60-member 3-km cloud-resolving ensemble analysis forecast from 00Z Oct 26

AHW Ensemble Data Assimilation and Forecasting System

Intensity Forecasting Experiment (IFEX) 2012 Hurricane Field Campaign. Paul Reasor Assistant HFP Director Hurricane Research Division

Impact of Assimilating Airborne Doppler Radar Velocity Data Using the ARPS 3DVAR on the Analysis and Prediction of Hurricane Ike (2008)

TC forecasting with variable resolution in CAM-MPAS

Hybrid Variational Ensemble Data Assimilation for Tropical Cyclone

Hurricane Forecast Improvement Project (HFIP) Bob Gall HFIP Development Manager

HFIP ENSEMBLE TEAM UPDATE

2012 AHW Stream 1.5 Retrospective Results

Radiance Data Assimilation with an EnKF

Motivation & Goal. We investigate a way to generate PDFs from a single deterministic run

Ensemble Prediction Systems

Hurricane Structure: Theory and Application. John Cangialosi National Hurricane Center

OPERATIONAL CONSIDERATIONS FOR HURRICANE MODEL DIAGNOSTICS / VERIFICATION

NHC Activities, Plans, and Needs

An Overview of COAMPS-TC Development and Real-Time Tests

Evaluation and Improvement of HWRF PBL Physics using Aircraft Observations

PUBLICATIONS. Geophysical Research Letters

Improving Tropical Cyclone Forecasts by Assimilating Microwave Sounder Cloud-Screened Radiances and GPM precipitation measurements

The impact of assimilation of microwave radiance in HWRF on the forecast over the western Pacific Ocean

Forecast Challenges of the 2017 Hurricane Season and NHC Priorities for 2018

The Properties of Convective Clouds Over the Western Pacific and Their Relationship to the Environment of Tropical Cyclones

Performance and Verification of HWRF/HMON Ensemble Prediction System in 2017 Real time Parallel Experiment. Zhan Zhang, Weiguo Wang

The Developmental Testbed Center: Update on Data Assimilation System Testing and Community Support

Enhancing information transfer from observations to unobserved state variables for mesoscale radar data assimilation

Flow and Regime Dependent Mesoscale Predictability

Comparing Variational, Ensemble-based and Hybrid Data Assimilations at Regional Scales

Ensemble 4DVAR for the NCEP hybrid GSI EnKF data assimilation system and observation impact study with the hybrid system

Ting Lei, Xuguang Wang University of Oklahoma, Norman, OK, USA. Wang and Lei, MWR, Daryl Kleist (NCEP): dual resolution 4DEnsVar

Expansion of NCEP Operational Hurricane Weather Research and Forecast (HWRF) Model Forecast Guidance to all Global Tropical Cyclones

Zorana Jelenak Paul S. Chang Khalil Ahmed (OPC) Seubson Soisuvarn Qi Zhu NOAA/NESDIS/STAR-UCAR

Introduction to the HWRF-based Ensemble Prediction System

NHC Ensemble/Probabilistic Guidance Products

Toward improved initial conditions for NCAR s real-time convection-allowing ensemble. Ryan Sobash, Glen Romine, Craig Schwartz, and Kate Fossell

GFDL Hurricane Model Ensemble Performance During the 2012 Hurricane Season

Hybrid Variational-Ensemble Data Assimilation at NCEP. Daryl Kleist

The Impacts of GPS Radio Occultation Data on the Analysis and Prediction of Tropical Cyclones. Bill Kuo, Xingqin Fang, and Hui Liu UCAR COSMIC

Convection-Resolving NWP with WRF. Section coordinator Ming Xue University of Oklahoma

Bias Correction of Satellite Data in GRAPES-VAR

Ensemble 4DVAR and observa3on impact study with the GSIbased hybrid ensemble varia3onal data assimila3on system. for the GFS

The Nowcasting Demonstration Project for London 2012

COSMIC GPS Radio Occultation and

NCEP Operational Hurricane Modeling System. HWRF Performance Verification in 2015

Objectives for meeting

Thunderstorm-Scale EnKF Analyses Verified with Dual-Polarization, Dual-Doppler Radar Data

Ensemble Kalman Filter Assimilation of HIWRAP Observations of Hurricane Karl (2010) from the Unmanned Global Hawk Aircraft

Tropical Cyclone Atmospheric Forcing 1 for Ocean Response Models: Approaches and Issues

The Atlantic Hurricane Database Reanalysis Project

The EMC Mission.. In response to operational requirements:

Structure & Intensity Change: Future Directions IWTC VI, Topic 1

Tropical cyclone simulations and predictions with GFDL s prototype global cloud resolving model

Challenges and Advances related to TC Rainfall Forecast. WOO Wang-chun Hong Kong Observatory IWTCLP-III, Jeju, Korea 10 Dec 2014

Experiments of Hurricane Initialization with Airborne Doppler Radar Data for the Advancedresearch Hurricane WRF (AHW) Model

Transitioning Physics Advancements into the Operational Hurricane WRF Model

Assimilation of GPS RO Data for Tropical Cyclone Prediction with HWRF Chunhua Zhou1, Hui Shao1, Bill Kuo1 and Ligia Bernardet2

Operational Hurricane Modeling at NCEP/EMC

Aircraft-based Observations: Impact on weather forecast model performance

HFIP ENSEMBLE PLAN. Jun Du (EMC/NCEP), presenting on behalf of the HFIP Ensemble Team:

AMERICAN METEOROLOGICAL SOCIETY

Development of 3D Variational Assimilation System for ATOVS Data in China

Jun Mitch Goldberg %, Pei Timothy J. Schmit &, Jinlong Zhenglong and Agnes

Assimilation of Satellite Infrared Brightness Temperatures and Doppler Radar Observations in a High-Resolution OSSE

GSI Data Assimilation System Support and Testing Activities: 2013 Annual Update

Tropical Cyclone Reconnaissance with the Global Hawk: Opera9onal Requirements, Benefits, and Feasibility

Performance of the 2013 Operational HWRF

Application of Radio Occultation Data in Analyses and Forecasts of Tropical Cyclones Using an Ensemble Assimilation System

Hurricane Structure: Theory and Diagnosis

Near-surface weather prediction and surface data assimilation: challenges, development, and potential data needs

Impact of assimilating the VIIRS-based CrIS cloudcleared radiances on hurricane forecasts

Advancements in Operations and Research on Hurricane Modeling and Ensemble Prediction System at EMC/NOAA

Advanced diagnostics of tropical cyclone inner-core structure using aircraft observations

Some Applications of WRF/DART

PUBLICATIONS. Journal of Advances in Modeling Earth Systems

Developmental Testbed Center (DTC) Project for the Hurricane Forecast Improvement Program (HFIP)

The NOAA Operational Numerical Guidance System: Recent Changes and Moving Forward. William. M. Lapenta Acting Director Environmental Modeling Center

Transcription:

Na#onal Hurricane Center Official Intensity Errors

Assimilate Airborne Doppler Winds with WRF-EnKF Available for 20+ years but never used in operational models due to the lack of resolution and/or the lack of efficient data assimilation methods Superobservations: 1. Separate forward and backward scans; 2. treat every 3 adjacent full scans as one fixed-space radar (translation<5km); 3. thinning ---one bin for 2 km in radial distance and 3 degree in scanning angle; 4. use medium as SO after additional QC checking These SOs are generated on flight of NOAA P3 s; transmitted to ground in real-time WRF-EnKF: 3 domains (40.5, 13.5&4.5km), 60-member ensemble (Weng and Zhang 2012 MWR)!

WRF- EnKF Performance with Airborne Vr for 2008-2010!!)# %,!!!*$ %,!!!+# %,!!!"$ %,!!!!# %!!! 1@ 1N M" MK M+ M* -JK##L!K#"#!$'!1@7!M4=/= @4>>A!!!!! @%..A!!!!! 12%!!!!!!! B4A!!!!!!! I4.%<4!!!! CD=E4F!!!! 789:45;!!! -./0!!!!!! 645.!!!!!! 2008 (26) 2009 (10) 2010 (23) Storms P3 Missions Dolly 6 Fay 6 Gustav 6 Ike 5 Paloma 3 Ana 1 Bill 4 Danny 5 Alex 1 Two 3 Earl 11 Karl 4 Richard 1 Tomas 3 GH/!!!!!!! ->4!!!!!!!?8..!!!!!! 345.!!!!!! 1%<4=!!!!!!"#$ % &!!!'# % &!!!($ % &!!!)# % &!!!*$ % &!!!+# % &!!!"$ % &!! (Zhang et al. 2011 GRL)

WRF-EnKF Performance Assimilating Airborne Vr Mean absolute track (km) & intensity (kts) error for all 2008-2010 P3 missions Interpolated WSP(t) = WSP(t) - # % $ 36h - t 36h Bias(6h) & ( ' (Zhang et al. 2011 GRL)

PSU WRF- EnKF HFIP Stream1.5 Model and Filter Configura#ons for 2012 D01: 379x244x27km D02: 304x304x9km, centered by tcvitals D03: 304x304x3km, centered by tcvitals Ø WRF V3.3.1 Ø YSU PBL Ø Monin- Obukov Surface Layer Ø PSU Cd (Green & Zhang 2012) Ø Garret Ck Ø EnKF: 60 members Ø Radius of Influence: SCL Ø Covariance relaxa#on: 0.6 43 full levels with model top at 50 mb Ø ICs & BCs: GFS analysis and its forecasts Key differences from 2011: high resolu#on (4.5 3km), more ver#cal levels (30 43), surface flux (PSU Cd, Garret Ck)

Improvement of Wind-Pressure Relationship 2008-11 from 2011 to 2012 PSU WRF-EnKF Stream1.5 system 0 20 40 60 80 100 120 140 160 920 940 960 980 1000 1020 BEST A4PS 2011system APSU Garratt(2012)

WRF-EnKF Performance Assimilating Airborne Vr Mean track (km) & intensity (kts) error for all 93 P3 missions over 2008-2012 No Bias Error of maxwsp (kts) for 2008 2012 20 18 16 14 12 10 8 6 4 2 0 79 79 76 74 66 53 37 23 Interpolated WSP(t) = WSP(t) - # % $ 36h - t 36h Bias(6h) & ( OFCL ' HWRF GFDL APSU 0 12 24 36 48 72 96 120

PSU WRF-EnKF Performance for Superstorm Sandy 60-member 3-km cloud-resolving ensemble analysis forecast from 00Z Oct 26 Best Track NHC APSU GFDL model 90 75 60 Best Track H3 NHC APSU GFDL model H2 H1 45 30 TS 15 0 00Z26 024h 048h 072h 096h 120h

PSU WRF-EnKF Performance for Superstorm Sandy EnKF analysis vs. independent observations from SFMR and flight-level obs SFMR wind speed (m/s) Flight-level q (k/kg)

PSU WRF-EnKF Performance for Superstorm Sandy EnKF analysis vs. independent observations from SFMR and flight-level obs SFMR wind speed (m/s) Flight-level q (k/kg)

PSU WRF-EnKF Performance for Superstorm Sandy 10-m maximum wind swath from the 3-km deterministic forecast Hourly 10m wind composite

PSU WRF-EnKF Performance for Superstorm Sandy 60-member 3-km cloud-resolving ensemble analysis forecast from 00Z Oct 26 TS (>32kts) and Hurricane (>64kts) Strength Wind Probability

PSU WRF-EnKF Performance for Superstorm Sandy 60-member 3-km cloud-resolving ensemble analysis forecast from 00Z Oct 26 Forecasted Probability of 96h accumulated rainfall >25&100mm

PSU WRF-EnKF Performance for Superstorm Sandy 108-h 3-km cloud-resolving deterministic precipitation forecast from 00Z Oct 26 HPC Observa#on 12Z/26-30 Oct PSU WRF- EnKF determinis#c forecast

PSU WRF-EnKF Performance for Irene (2011) 3-km cloud-resolving deterministic hindcast of precipitation from 00Z Aug 24 120h accumulated rainfall observa#on PSU WRF- EnKF 120h determinis#c forecast

Concluding Remarks Hurricane intensity forecast can be greatly improved through using advanced DA techniques and a cloud resolving NWP model with assimilation of high-resolution inner-core observations Average over nearly 100 NOAA P3 Doppler missions, the PSU WRF- EnKF forecasts with assimilation of Vr has the day 1 to 5 mean intensity forecast error 20-40% smaller than NHC official forecasts The PSU WRF-EnKF experimental system performed well for all landfalling hurricanes during 2008-2012. It also shows great promise in predicting hurricane-induced rainfalls, as well as uncertaintues Future of hurricane prediction: better inner-core observations, better data assimilation, better forecast model, better computing resources

Our Ongoing EnKF Efforts not to be Reported Today Assimilation of satellite observations for hurricane prediction (satellite derived innercore wind, cloudy radiance, GPS RO, etc.) (Jerry Zhang) Assimilation of Global Hawk observations: HAMSR, HIRAS, etc. (Scott Sieron) Fully cycled realtime WRF-EnKF hurricane prediction system for NOAA/HFIP in 2013 (Yonghui Weng) Multiscale regional ensemble reanalysis of radar and other observations of MJOS during DYNAMO (Michael Ying) Multiscale regional reanalysis for the Arctic and Tibetan Plateau regions (Hans Chen) Development of COAMPS-based EnKF system towards eventually for the fully coupled system that includes the ocean (Chris Melhauser) Development of CMA GRAPES-based EnKF system (Jidong Gao) Development of an WRF-EnKF based storm scale analysis and forecast system for China FAA (CAAC) for aviation safety (Aimin Liang) EnKF storm-scale verification (Dan Stern) and ensemble sensitivity (Erin Munsell)

Best OFCL APSU d2012 APSU FZflux 105 90 75 60 45 30 15 0 Best OFCL APSU d2012 APSU FZflux 26 27 28 29 30 31 01

Courtesy of Chris Landsea and James Franklin

Sandy 20121026H2 Flt wind speed SFMR wind speed Flt t Flt q

PSU WRF-EnKF Performance for Superstorm Sandy 60-member 3-km cloud-resolving ensemble analysis forecast from 00Z Oct 26 Flt wind speed SFMR wind speed Flt t Flt q

WRF- EnKF Performance with Airborne Vr for 2008-2012 (Zhang et al. 2011 GRL)

PSU WRF-EnKF Performance for Superstorm Sandy 60-member 3-km cloud-resolving ensemble analysis forecast from 00Z Oct 26 HWind hourly 2012 10 26 01:30 >2012 10 30 07:30 40 APSU 00Z/26 2012 10 30 07:30 >2012 10 30 07:30 10mWSP 40 40 o N 35 40 o N 35 30 30 35 o N 25 35 o N 25 20 20 30 o N 15 30 o N 15 25 o N 10 25 o N 10 5 5 85 o W 80 o W 75 o W 70 o W 65 o W 60 o W 85 o W 80 o W 75 o W 70 o W 65 o W 60 o W Hourly 10m wind composite

2024 © sciencedocbox.com Privacy Policy | Terms of Service | Feedback