Assimilation of Airborne Doppler Radar Observations Using the Unified GSI based Hybrid Ensemble Variational Data Assimilation System for HWRF
|
|
|
- Raymond Hutchinson
- 5 years ago
- Views:
Transcription
1 Assimilation of Airborne Doppler Radar Observations Using the Unified GSI based Hybrid Ensemble Variational Data Assimilation System for HWRF Xuguang Wang University of Oklahoma, Norman, OK Yongzuo Li (OU), Ming Xue (OU), Mingjing Tong (NCEP) HFIP Teleconference, Sep. 26,
2 Background The GSI based hybrid DA system showed significant improvement for global compared to GSI (3DVAR) and became operational on May 22, 2012 for the Global Forecast System (GFS). GSI is a unified system which provides data assimilation for all operational global and regional system. GSI GFS NAM Rapid Refresh (RR) HWRF 2
3 Background Efforts are being conducted to integrate the same GSI based hybrid DA system with operational regional systems. Unifying GSI based hybrid DA system with operational regional systems facilitates faster transition to operations. The focus of the project is the extension, application, extensive testing and research of the GSI based hybrid data assimilation for the HWRF modeling system at high resolutions. Also motivated by encouraging results of ensemble based data assimilation for tropical cyclones. 3
4 Background 3DVAR Hybrid Li, Wang, Xue mb temperature increment after assimilating ground based radar radial velocity using WRF 3DVAR (a) and WRFVAR hybrid (b, Wang et al. 2008) 4
5 GSI based Hybrid ensemble VAR DA system 1 way coupling member 1 EnKF analysis 1 member 1 EnKF member 2 EnKF analysis 2 member 2 member k Ensemble covariance EnKF analysis k member k control GSI-ECV control analysis control data assimilation Wang et al First guess 5
6 GSI based Hybrid ensemble VAR DA system 2 way coupling member 1 member 2 member k EnKF Ensemble covariance EnKF analysis 1 EnKF analysis 2 EnKF analysis k Re-center EnKF analysis ensemble to control analysis member 1 analysis member 2 analysis member k analysis member 1 member 2 member k control GSI-ECV control analysis control data assimilation Wang et al First guess 6
7 Code changes related to Airborne radar data so far EnKF Add airborne radar wind observation assimilation capability GSI Separate the Fore and Aft scans during data thinning in GSI (TDR data transferred remain the same, changes made inside GSI code) option to assimilate TDR data based on leg 7
8 Experiment Setup IRENE IRENE Model: HWRF Δx=9 Observations: radial velocity from Tail Doppler Radar (TDR) Case: IRENE 2011 Initial and LBC ensemble: GFS global hybrid DA system Ensemble size: 40 8
9 DA cycling configuration GSI (3DVar) Hybrid (1 way coupling) EnKF 9
10 TDR data distribution 10
11 TDR data distribution m/s 11
12 700 mb wind increment GSI EnKF hybrid m/s m/s m/s 12
13 Verification against independent flight level wind speed First Leg GSI EnKF Hybrid 13
14 Verification against SFMR wind speed First Leg GSI EnKF Hybrid 14
15 Verification against independent flight level wind speed Last Leg GSI EnKF Hybrid 15
16 Verification against SFMR wind speed Last Leg GSI EnKF Hybrid 16
17 Vr RMSE vs. Spread during DA RMS fit to Vr Vr ensemble spread 17
18 MSLP during DA 18
19 Comparison with radar wind analysis HRD radar wind analysis GSI Hybrid/EnKF mb mb m/s m/s m/s 19
20 Comparison with radar wind analysis HRD radar wind mb 1000mb m/s m/s m/s 20
21 Comparison with radar wind analysis HRD radar wind 3 700mb 700mb m/s m/s m/s 21
22 Track EMC: HWRF official NoDA: no TDR assimilation GSI: assimilating TDR using GSI EnKF: assimilating TDR using EnKF Hybrid: assimilating TDR using hybrid 22
23 Intensity EMC: HWRF official NoDA: no TDR assimilation GSI: assimilating TDR using GSI EnKF: assimilating TDR using EnKF Hybrid: assimilating TDR using hybrid 23
24 Summary and ongoing work a. The GSI based hybrid EnKF Var data assimilation system was expanded to assimilate TDR data for HWRF. b. TDR data showed positive impact on TC track and intensity s and verification against independent observations. c. Various diagnostics and verifications suggested ensemblebased data assimilation (hybrid, EnKF) provided more skillful TC analysis and s than the GSI. d. Testing more missions/cases. e. Testing dual resolution 3/9 hybrid; 3 s own hybrid. f. Developing and testing GSI/EnKF hybrid with moving nests. g. Add and test more observations. h. Develop and research on various new capabilities for hybrid. 24
Retrospective and near real-time tests of GSIbased EnKF-Var hybrid data assimilation system for HWRF with airborne radar data
Retrospective and near real-time tests of GSIbased EnKF-Var hybrid data assimilation system for HWRF with airborne radar data Xuguang Wang, Xu Lu, Yongzuo Li University of Oklahoma, Norman, OK In collaboration
Development and research of GSI based hybrid EnKF Var data assimilation for HWRF to improve hurricane prediction
Development and research of GSI based hybrid EnKF Var data assimilation for HWRF to improve hurricane prediction Xuguang Wang, Xu Lu, Yongzuo Li School of Meteorology University of Oklahoma, Norman, OK,
Hybrid Variational Ensemble Data Assimilation for Tropical Cyclone
Hybrid Variational Ensemble Data Assimilation for Tropical Cyclone Forecasts Xuguang Wang School of Meteorology University of Oklahoma, Norman, OK Acknowledgement: OU: Ting Lei, Yongzuo Li, Kefeng Zhu,
Ting Lei, Xuguang Wang University of Oklahoma, Norman, OK, USA. Wang and Lei, MWR, Daryl Kleist (NCEP): dual resolution 4DEnsVar
GSI-based four dimensional ensemble-variational (4DEnsVar) data assimilation: formulation and single resolution experiments with real data for NCEP GFS Ting Lei, Xuguang Wang University of Oklahoma, Norman,
A pseudo-ensemble hybrid data assimilation system for HWRF
A pseudo-ensemble hybrid data assimilation system for HWRF Xuyang Ge UCAR visiting postdoctoral scientist at PSU/NCEP Contributors: Fuqing Zhang and Yonghui Weng (PSU) Mingjing Tong and Vijay Tallapragada
PSU HFIP 2010 Summary: Performance of the ARW-EnKF Real-time Cloud-resolving TC Ensemble Analysis and Forecasting System.
PSU HFIP 2010 Summary: Performance of the ARW-EnKF Real-time Cloud-resolving TC Ensemble Analysis and Forecasting System Fuqing Zhang Penn State University Contributors: Yonghui Weng, John Gamache and
Tropical Cyclone Modeling and Data Assimilation. Jason Sippel NOAA AOML/HRD 2018 WMO Workshop at NHC
Tropical Cyclone Modeling and Data Assimilation Jason Sippel NOAA AOML/HRD 2018 WMO Workshop at NHC Outline History of TC forecast improvements in relation to model development Ongoing modeling/da developments
Ensemble 4DVAR for the NCEP hybrid GSI EnKF data assimilation system and observation impact study with the hybrid system
Ensemble 4DVAR for the NCEP hybrid GSI EnKF data assimilation system and observation impact study with the hybrid system Xuguang Wang School of Meteorology University of Oklahoma, Norman, OK OU: Ting Lei,
Hybrid variational-ensemble data assimilation. Daryl T. Kleist. Kayo Ide, Dave Parrish, John Derber, Jeff Whitaker
Hybrid variational-ensemble data assimilation Daryl T. Kleist Kayo Ide, Dave Parrish, John Derber, Jeff Whitaker Weather and Chaos Group Meeting 07 March 20 Variational Data Assimilation J Var J 2 2 T
Development and Research of GSI-based EnVar System to Assimilate Radar Observations for Convective Scale Analysis and Forecast
Development and Research of GSI-based EnVar System to Assimilate Radar Observations for Convective Scale Analysis and Forecast Xuguang Wang, Yongming Wang School of Meteorology University of Oklahoma,
DA/Initialization/Ensemble Development Team Milestones and Priorities
DA/Initialization/Ensemble Development Team Milestones and Priorities Presented by Xuguang Wang HFIP annual review meeting Jan. 11-12, 2017, Miami, FL Fully cycled, self-consistent, dual-resolution, GSI
Testing and Evaluation of GSI Hybrid Data Assimilation for Basin-scale HWRF: Lessons We Learned
4th NOAA Testbeds & Proving Ground Workshop, College Park, MD, April 2-4, 2013 Testing and Evaluation of GSI Hybrid Data Assimilation for Basin-scale HWRF: Lessons We Learned Hui Shao1, Chunhua Zhou1,
Ensemble 4DVAR and observa3on impact study with the GSIbased hybrid ensemble varia3onal data assimila3on system. for the GFS
Ensemble 4DVAR and observa3on impact study with the GSIbased hybrid ensemble varia3onal data assimila3on system for the GFS Xuguang Wang University of Oklahoma, Norman, OK xuguang.wang@ou.edu Ting Lei,
Discussion on HFIP RDITT Experiments. Proposal for extending the life of RDITT for one more year: Future Plans from Individual Groups
Discussion on HFIP RDITT Experiments Proposal for extending the life of RDITT for one more year: Future Plans from Individual Groups 1 EMC: Modifications to one-way hybrid ensemble-variational data assimilation
Experiments of Hurricane Initialization with Airborne Doppler Radar Data for the Advancedresearch Hurricane WRF (AHW) Model
Experiments of Hurricane Initialization with Airborne Doppler Radar Data for the Advancedresearch Hurricane WRF (AHW) Model Qingnong Xiao 1, Xiaoyan Zhang 1, Christopher Davis 1, John Tuttle 1, Greg Holland
Mesoscale Ensemble Data Assimilation: Opportunities and Challenges. Fuqing Zhang Penn State University
Mesoscale Ensemble Data Assimilation: Opportunities and Challenges Fuqing Zhang Penn State University Mesoscale EnKF: some incomplete background 1 st proposed by Evensen (1994); Houtekamer and Micthell
Impact of Assimilating Aircraft Reconnaissance Observations in Operational HWRF
Impact of Assimilating Aircraft Reconnaissance Observations in Operational HWRF Mingjing Tong, Vijay Tallapragada, Emily Liu, Weiguo Wang, Chanh Kieu, Qingfu Liu and Banglin Zhan Environmental Modeling
Developmental Testbed Center (DTC) Project for the Hurricane Forecast Improvement Program (HFIP)
Developmental Testbed Center (DTC) Project for the Hurricane Forecast Improvement Program (HFIP) Final report documenting: Regional Application of the GSI- Hybrid Data Assimilation for Tropical Storm forecasts
Assimilate W88D Doppler Vr for Humberto 05
Assimilate W88D Doppler Vr for Humberto 05 WRF/EnKF Forecast vs. Observations vs. 3DVAR Min SLP Max wind The WRF/3DVAR (as a surrogate of operational algorithm) assimilates the same radar data but without
Comparing Variational, Ensemble-based and Hybrid Data Assimilations at Regional Scales
Comparing Variational, Ensemble-based and Hybrid Data Assimilations at Regional Scales Meng Zhang and Fuqing Zhang Penn State University Xiang-Yu Huang and Xin Zhang NCAR 4 th EnDA Workshop, Albany, NY
The Developmental Testbed Center: Update on Data Assimilation System Testing and Community Support
93rd AMS Annual Meeting/17th IOAS-AOLS/3rd Conference on Transition of Research to Operations, Austin, TX, Jan 6-10, 2013 The Developmental Testbed Center: Update on Data Assimilation System Testing and
GSI Data Assimilation System Support and Testing Activities: 2013 Annual Update
14Th Annual WRF Users Workshop, Boulder, CO, June 24-28, 2013 GSI Data Assimilation System Support and Testing Activities: 2013 Annual Update Hui Shao1, Ming Hu2, Chunhua Zhou1, Kathryn Newman1, Mrinal
Improving GFS 4DEnVar Hybrid Data Assimilation System Using Time-lagged Ensembles
Improving GFS 4DEnVar Hybrid Data Assimilation System Using Time-lagged Ensembles Bo Huang and Xuguang Wang School of Meteorology University of Oklahoma, Norman, OK, USA Acknowledgement: Junkyung Kay (OU);
University of Miami/RSMAS
Observing System Simulation Experiments to Evaluate the Potential Impact of Proposed Observing Systems on Hurricane Prediction: R. Atlas, T. Vukicevic, L.Bucci, B. Annane, A. Aksoy, NOAA Atlantic Oceanographic
Convection-Resolving NWP with WRF. Section coordinator Ming Xue University of Oklahoma
Convection-Resolving NWP with WRF Section coordinator Ming Xue University of Oklahoma Convection-resolving NWP Is NWP that explicitly treats moist convective systems ranging from organized MCSs to individual
Numerical Weather Prediction: Data assimilation. Steven Cavallo
Numerical Weather Prediction: Data assimilation Steven Cavallo Data assimilation (DA) is the process estimating the true state of a system given observations of the system and a background estimate. Observations
AHW Ensemble Data Assimilation and Forecasting System
AHW Ensemble Data Assimilation and Forecasting System Ryan D. Torn, Univ. Albany, SUNY Chris Davis, Wei Wang, Jimy Dudhia, Tom Galarneau, Chris Snyder, James Done, NCAR/MMM Overview Since participation
Development and Research of GSI- based Var/EnKF/EnVar/ Hybrid System to Assimilate Radar ObservaBons for ConvecBve Scale NWP
Development and Research of GSI- based Var/EnKF/EnVar/ Hybrid System to Assimilate Radar ObservaBons for ConvecBve Scale NWP Xuguang Wang School of Meteorology University of Oklahoma, Norman, OK D Acknowledgement
Overview of HFIP FY10 activities and results
Overview of HFIP FY10 activities and results Bob Gall HFIP Annual Review Meeting Miami Nov 9, 2010 Outline In this presentation I will show a few preliminary results from the summer program. More detail
Hybrid Variational-Ensemble Data Assimilation at NCEP. Daryl Kleist
Hybrid Variational-Ensemble Data Assimilation at NCEP Daryl Kleist NOAA/NWS/NCEP/EMC with acnowledgements to Kayo Ide, Dave Parrish, Jeff Whitaer, John Derber, Russ Treadon, Wan-Shu Wu, Jacob Carley, and
The Nowcasting Demonstration Project for London 2012
The Nowcasting Demonstration Project for London 2012 Susan Ballard, Zhihong Li, David Simonin, Jean-Francois Caron, Brian Golding, Met Office, UK Introduction The success of convective-scale NWP is largely
Assimilation of Radar Radial Velocity Data with the WRF Hybrid Ensemble-3DVAR System for the Prediction of Hurricane Ike (2008)
Manuscript (non-latex) Click here to download Manuscript (non-latex): Li-Wang-Xue_MWR-D-12-00043.doc 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Assimilation of
Chengsi Liu 1, Ming Xue 1, 2, Youngsun Jung 1, Lianglv Chen 3, Rong Kong 1 and Jingyao Luo 3 ISDA 2019
Development of Optimized Radar Data Assimilation Capability within the Fully Coupled EnKF EnVar Hybrid System for Convective Permitting Ensemble Forecasting and Testing via NOAA Hazardous Weather Testbed
GSI 3DVar-based Ensemble-Variational Hybrid Data Assimilation for NCEP Global Forecast System: Single Resolution Experiments
1 2 GSI 3DVar-based Ensemble-Variational Hybrid Data Assimilation for NCEP Global Forecast System: Single Resolution Experiments 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
Tropical Cyclone Mesoscale Data Assimilation
Tropical Cyclone Mesoscale Data Assimilation Sharan Majumdar (RSMAS / U. Miami) Chris Velden (CIMSS / U. Wisconsin) Acknowledgments: Ryan Torn (SUNY at Albany), Altug Aksoy and Tomislava Vukicevic (NOAA/AOML/HRD)
Na#onal Hurricane Center Official Intensity Errors
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
NCEP Operational Hurricane Modeling System. HWRF Performance Verification in 2015
1 NCEP Operational Hurricane Modeling System HWRF Performance Verification in 2015 The HWRF Team Environmental Modeling Center, NCEP NOAA/NCWCP, College Park, MD 20740, USA. Zhan Zhang, Samuel Trahan,
GSI 3DVar-Based Ensemble Variational Hybrid Data Assimilation for NCEP Global Forecast System: Single-Resolution Experiments
4098 M O N T H L Y W E A T H E R R E V I E W VOLUME 141 GSI 3DVar-Based Ensemble Variational Hybrid Data Assimilation for NCEP Global Forecast System: Single-Resolution Experiments XUGUANG WANG School
Assimilation of Radar Radial Velocity Data with the WRF Hybrid Ensemble 3DVAR System for the Prediction of Hurricane Ike (2008)
NOVEMBER 2012 L I E T A L. 3507 Assimilation of Radar Radial Velocity Data with the WRF Hybrid Ensemble 3DVAR System for the Prediction of Hurricane Ike (2008) YONGZUO LI, XUGUANG WANG, AND MING XUE School
Assimilation of GPS RO Data for Tropical Cyclone Prediction with HWRF Chunhua Zhou1, Hui Shao1, Bill Kuo1 and Ligia Bernardet2
Assimilation of GPS RO Data for Tropical Cyclone Prediction with HWRF Chunhua Zhou1, Hui Shao1, Bill Kuo1 and Ligia Bernardet2 1 National Center for Atmospheric Research (NCAR) 2 NOAA/ESRL/GSD Sixth FORMOSAT-3/COSMIC
Assimila'on of Radar Observa'ons with the GSI
Assimila'on of Radar Observa'ons with the GSI Jacob Carley I.M. Systems Group and NOAA/NWS/NCEP/EMC 2017 GSI Summer Tutorial Huge thanks to the following individuals who kindly provided material for this
Jidong Gao and David Stensrud. NOAA/National Severe Storm Laboratory Norman, Oklahoma
Assimilation of Reflectivity and Radial Velocity in a Convective-Scale, Cycled 3DVAR Framework with Hydrometeor Classification Jidong Gao and David Stensrud NOAA/National Severe Storm Laboratory Norman,
Impact of Assimilating Airborne Doppler Radar Velocity Data Using the ARPS 3DVAR on the Analysis and Prediction of Hurricane Ike (2008)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 Impact of Assimilating Airborne Doppler Radar Velocity Data Using the ARPS 3DVAR on the Analysis
Ensemble Kalman Filters for WRF-ARW. Chris Snyder MMM and IMAGe National Center for Atmospheric Research
Ensemble Kalman Filters for WRF-ARW Chris Snyder MMM and IMAGe National Center for Atmospheric Research Preliminaries Notation: x = modelʼs state w.r.t. some discrete basis, e.g. grid-pt values y = Hx
HMON (HNMMB): Development of a new Hurricane model for NWS/NCEP operations
1 HMON (HNMMB): Development of a new Hurricane model for NWS/NCEP operations Avichal Mehra, EMC Hurricane and Mesoscale Teams Environmental Modeling Center NOAA / NWS / NCEP HMON: A New Operational Hurricane
5.3 TESTING AND EVALUATION OF THE GSI DATA ASSIMILATION SYSTEM
5.3 TESTING AND EVALUATION OF THE GSI DATA ASSIMILATION SYSTEM Kathryn M Newman*, C. Zhou, H. Shao, X.Y. Huang, M. Hu National Center for Atmospheric Research, Boulder, CO Developmental Testbed Center
HFIP ENSEMBLE PLAN. Jun Du (EMC/NCEP), presenting on behalf of the HFIP Ensemble Team:
HFIP ENSEMBLE PLAN Jun Du (EMC/NCEP), presenting on behalf of the HFIP Ensemble Team: Sim Aberson (HRD) Sim.Aberson@noaa.gov Tom Hamill (ESRL) tom.hamill@noaa.gov Carolyn Reynolds (NRL) carolyn.reynolds@nrlmry.navy.mil
AMPS Update June 2016
AMPS Update June 2016 Kevin W. Manning Jordan G. Powers Mesoscale and Microscale Meteorology Laboratory National Center for Atmospheric Research Boulder, CO 11 th Antarctic Meteorological Observation,
Performance of the 2013 Operational HWRF
Performance of the 2013 Operational HWRF Vijay Tallapragada & HWRF Team Environmental Modeling Center, NCEP/NOAA/NWS, NCWCP, College Park, MD 20740. HFIP Annual Review Meeting, February 19, 2014 1 Outline
Some Applications of WRF/DART
Some Applications of WRF/DART Chris Snyder, National Center for Atmospheric Research Mesoscale and Microscale Meteorology Division (MMM), and Institue for Mathematics Applied to Geoscience (IMAGe) WRF/DART
Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania
MARCH 2012 W E N G A N D Z H A N G 841 Assimilating Airborne Doppler Radar Observations with an Ensemble Kalman Filter for Convection-Permitting Hurricane Initialization and Prediction: Katrina (2005)
P7.1 STUDY ON THE OPTIMAL SCANNING STRATEGIES OF PHASE-ARRAY RADAR THROUGH ENSEMBLE KALMAN FILTER ASSIMILATION OF SIMULATED DATA
P7.1 STUDY ON THE OPTIMAL SCANNING STRATEGIES OF PHASE-ARRAY RADAR THROUGH ENSEMBLE KALMAN FILTER ASSIMILATION OF SIMULATED DATA Ting Lei 1, Ming Xue 1,, Tianyou Yu 3 and Michihiro Teshiba 3 1 Center for
(Received November 7, 2012; in final form January 18, 2013)
NO.3 XUE Ming and DONG Jili 379 Assimilating Best Track Minimum Sea Level Pressure Data Together with Doppler Radar Data Using an Ensemble Kalman Filter for Hurricane Ike (2008) at a Cloud-Resolving Resolution
ABSTRACT 3 RADIAL VELOCITY ASSIMILATION IN BJRUC 3.1 ASSIMILATION STRATEGY OF RADIAL
REAL-TIME RADAR RADIAL VELOCITY ASSIMILATION EXPERIMENTS IN A PRE-OPERATIONAL FRAMEWORK IN NORTH CHINA Min Chen 1 Ming-xuan Chen 1 Shui-yong Fan 1 Hong-li Wang 2 Jenny Sun 2 1 Institute of Urban Meteorology,
COAMPS-TC 2015 Version, Performance, and Future Plans
COAMPS-TC 2015 Version, Performance, and Future Plans James D. Doyle, R. Hodur 1, J. Moskaitis, S. Chen, E. Hendricks 2, H. Jin, Y. Jin, A. Reinecke, S. Wang Naval Research Laboratory, Monterey, CA 1 IES/SAIC,
The NOAA Operational Numerical Guidance System: Recent Changes and Moving Forward. William. M. Lapenta Acting Director Environmental Modeling Center
AMS Future of the Weather Enterprise 11/27/12 1 N C E P The NOAA Operational Numerical Guidance System: Recent Changes and Moving Forward William. M. Lapenta Acting Director Environmental Modeling Center
Xuguang Wang and Ting Lei. School of Meteorology, University of Oklahoma and Center for Analysis and Prediction of Storms, Norman, OK.
1 2 3 GSI-based four dimensional ensemble-variational (4DEnsVar) data assimilation: formulation and single resolution experiments with real data for NCEP Global Forecast System 4 5 6 7 8 9 10 11 12 13
Univ. of Maryland-College Park, Dept. of Atmos. & Oceanic Science. NOAA/NCEP/Environmental Modeling Center
The Tangent Linear Normal Mode Constraint in GSI: Applications in the NCEP GFS/GDAS Hybrid EnVar system and Future Developments Daryl Kleist 1 David Parrish 2, Catherine Thomas 1,2 1 Univ. of Maryland-College
Convection-permitting Ensemble Data Assimilation of Doppler Radar Observations for Hurricane Prediction
Convection-permitting Ensemble Data Assimilation of Doppler Radar Observations for Hurricane Prediction Fuqing Zhang and Yonghui Weng Penn State University Sponsored by NOAA/HFIP, ONR, NASA and NSF National
Operational Hurricane Modeling at NCEP/EMC
Operational Hurricane Modeling at NCEP/EMC Avichal Mehra Hurricane Project Lead Environmental Modeling Center NOAA / NWS / NCEP ESCAP/WMO Typhoon Committee 49 th Session 21-24 February 2017, Yokohama,
Current and Future Experiments to Improve Assimilation of Surface Winds from Satellites in Global Models
Current and Future Experiments to Improve Assimilation of Surface Winds from Satellites in Global Models Sharan Majumdar, RSMAS/UMiami Bob Atlas, NOAA/AOML Current and Future Collaborators: Ryan Torn (SUNY
Report on EN6 DTC Ensemble Task 2014: Preliminary Configuration of North American Rapid Refresh Ensemble (NARRE)
Report on EN6 DTC Ensemble Task 2014: Preliminary Configuration of North American Rapid Refresh Ensemble (NARRE) Motivation As an expansion of computing resources for operations at EMC is becoming available
Improved analyses and forecasts with AIRS retrievals using the Local Ensemble Transform Kalman Filter
Improved analyses and forecasts with AIRS retrievals using the Local Ensemble Transform Kalman Filter Hong Li, Junjie Liu, and Elana Fertig E. Kalnay I. Szunyogh, E. J. Kostelich Weather and Chaos Group
A GSI-based convection-allowing EnKF and ensemble forecast system for PECAN
A GSI-based convection-allowing EnKF and ensemble forecast system for PECAN Aaron Johnson, Xuguang Wang, Samuel Degelia University of Oklahoma, Norman, OK 26 May 2016 7 th EnKF Data Assimilation Workshop,
On the assimilation of hyperspectral infrared sounder radiances in cloudy skies
On the assimilation of hyperspectral infrared sounder radiances in cloudy skies Jun Li 1, Pei Wang 1, Zhenglong Li 1, Jinlong Li 1 and Mitchell D. Goldberg 2 1 Cooperative Institute for Meteorological
Hurricane Forecast Improvement Project (HFIP) Bob Gall HFIP Development Manager
Hurricane Forecast Improvement Project (HFIP) Bob Gall HFIP Development Manager Boulder, Colorado June 26, 2012 2 The HFIP Project Vision/Goals Vision o Organize the hurricane community to dramatically
NOAA Report. John Gaynor US THORPEX Executive Committee 7 October 2009
NOAA Report John Gaynor US THORPEX Executive Committee 7 October 2009 1 EnKF testing NOAA-THORPEX funding supported development of EnKF algorithms at many locations (ESRL, UMD, CSU, NRL) from 2005-2007.
13A. 4 Analysis and Impact of Super-obbed Doppler Radial Velocity in the NCEP Grid-point Statistical Interpolation (GSI) Analysis System
13A. 4 Analysis and Impact of Super-obbed Doppler Radial Velocity in the NCEP Grid-point Statistical Interpolation (GSI) Analysis System Shun Liu 1, Ming Xue 1,2, Jidong Gao 1,2 and David Parrish 3 1 Center
Background Error, Observation Error, and GSI Hybrid Analysis
2015 GSI Community Tutorial August 11-13, 2013, NCAR, Boulder Background Error, Observation Error, and GSI Hybrid Analysis Ming Hu Developmental Testbed Center Outlines GSI fundamentals (1): Setup and
Motivation & Goal. We investigate a way to generate PDFs from a single deterministic run
Motivation & Goal Numerical weather prediction is limited by errors in initial conditions, model imperfections, and nonlinearity. Ensembles of an NWP model provide forecast probability density functions
Estimating Observation Impact in a Hybrid Data Assimilation System: Experiments with a Simple Model
Estimating Observation Impact in a Hybrid Data Assimilation System: Experiments with a Simple Model NOAA / NCEP / EMC College Park, MD 20740, USA 10 February 2014 Overview Goal Sensitivity Theory Adjoint
Evaluation and Improvement of HWRF PBL Physics using Aircraft Observations
Evaluation and Improvement of HWRF PBL Physics using Aircraft Observations Jun Zhang NOAA/AOML/HRD with University of Miami/CIMAS HFIP Regional Modeling Team Workshop, 09/18/2012 Many thanks to my collaborators:
CAPS Storm-Scale Ensemble Forecasting (SSEF) System
CAPS Storm-Scale Ensemble Forecasting (SSEF) System Fanyou Kong, Ming Xue, Xuguang Wang, Keith Brewster Center for Analysis and Prediction of Storms University of Oklahoma (collaborated with NSSL, SPC,
DISTRIBUTION STATEMENT A: Approved for public release; distribution is unlimited.
DISTRIBUTION STATEMENT A: Approved for public release; distribution is unlimited. Prediction and Predictability of Tropical Cyclones over Oceanic and Coastal Regions and Advanced Assimilation of Radar
Enhancing information transfer from observations to unobserved state variables for mesoscale radar data assimilation
Enhancing information transfer from observations to unobserved state variables for mesoscale radar data assimilation Weiguang Chang and Isztar Zawadzki Department of Atmospheric and Oceanic Sciences Faculty
The Use of GPS Radio Occultation Data for Tropical Cyclone Prediction. Bill Kuo and Hui Liu UCAR
The Use of GPS Radio Occultation Data for Tropical Cyclone Prediction Bill Kuo and Hui Liu UCAR Current capability of the National Hurricane Center Good track forecast improvements. Errors cut in half
Advances and Challenges in Ensemblebased Data Assimilation in Meteorology. Takemasa Miyoshi
January 18, 2013, DA Workshop, Tachikawa, Japan Advances and Challenges in Ensemblebased Data Assimilation in Meteorology Takemasa Miyoshi RIKEN Advanced Institute for Computational Science Takemasa.Miyoshi@riken.jp
伍先生专刊. University of Oklahoma, Norman, OK Nanjing University, Nanjing, China
伍先生专刊 Assimilating Best Track Minimum Sea Level Pressure Data together with Doppler Radar Data using an Ensemble Kalman Filter for Hurricane Ike (2008) at a Cloud-Resolving Resolution* XUE Ming 1,2,3+
HFIP ENSEMBLE TEAM UPDATE
HFIP ENSEMBLE TEAM UPDATE Carolyn Reynolds (NRL) carolyn.reynolds@nrlmry.navy.mil Zoltan Toth (ESRL) zoltan.toth@noaa.gov Sim Aberson (HRD) Sim.Aberson@noaa.gov Tom Hamill (ESRL) tom.hamill@noaa.gov Jeff
A new mesoscale NWP system for Australia
A new mesoscale NWP system for Australia www.cawcr.gov.au Peter Steinle on behalf of : Earth System Modelling (ESM) and Weather&Environmental Prediction (WEP) Research Programs, CAWCR Data Assimilation
University of Oklahoma, Norman, Oklahoma 73072, USA. Accepted by Meteorological Applications. February, 2017
A comparison of the limited-area 3DVAR and ETKF-En3DVAR data assimilation using radar observations at convective-scale for the Prediction of Typhoon Saomai (2006) Feifei Shen 1,2* Ming Xue 1,2 and Jinzhong
Transitioning Physics Advancements into the Operational Hurricane WRF Model
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
Assimilation of cloud/precipitation data at regional scales
Assimilation of cloud/precipitation data at regional scales Thomas Auligné National Center for Atmospheric Research auligne@ucar.edu Acknowledgments to: Steven Cavallo, David Dowell, Aimé Fournier, Hans
Implementation and Evaluation of WSR-88D Radial Velocity Data Assimilation for WRF-NMM via GSI
Implementation and Evaluation of WSR-88D Radial Velocity Data Assimilation for WRF-NMM via GSI Shun Liu 1, Ming Xue 1,2 1 Center for Analysis and Prediction of Storms and 2 School of Meteorology University
Current Issues and Challenges in Ensemble Forecasting
Current Issues and Challenges in Ensemble Forecasting Junichi Ishida (JMA) and Carolyn Reynolds (NRL) With contributions from WGNE members 31 th WGNE Pretoria, South Africa, 26 29 April 2016 Recent trends
HFIP Annual Review Meeting November 5-7, 2018 Embassy Suites by Hilton Miami International Airport 3974 NW S River Dr, Miami, FL 33142
HFIP Annual Review Meeting November 5-7, 2018 Embassy Suites by Hilton Miami International Airport 3974 NW S River Dr, Miami, FL 33142 Overall Objectives The new HFIP Strategic Plan detailing the specific
Estimating Observation Impact in a Hybrid Data Assimilation System: Experiments with a Simple Model
Estimating Observation Impact in a Hybrid Data Assimilation System: Experiments with a Simple Model Rahul Mahajan NOAA / NCEP / EMC - IMSG College Park, MD 20740, USA Acknowledgements: Ron Gelaro, Ricardo
Nanjing University, Nanjing , China. Oklahoma, Norman, Oklahoma, USA, October, Submitted to Journal of Geophysical Research
Implementation of a Dynamic Equation Constraint based on the Steady State Momentum Equations within the WRF Hybrid Ensemble-3DVar Data Assimilation System and Test with Radar T-TREC Wind Assimilation for
Radiance Data Assimilation with an EnKF
Radiance Data Assimilation with an EnKF Zhiquan Liu, Craig Schwartz, Xiangyu Huang (NCAR/MMM) Yongsheng Chen (York University) 4/7/2010 4th EnKF Workshop 1 Outline Radiance Assimilation Methodology Apply
Advancements in Operations and Research on Hurricane Modeling and Ensemble Prediction System at EMC/NOAA
Advancements in Operations and Research on Hurricane Modeling and Ensemble Prediction System at EMC/NOAA Zhan Zhang and Vijay Tallapragada EMC/NCEP/NOAA/DOC Acknowledgements: HWRF Team Members at EMC,
Ensemble Prediction Systems
Ensemble Prediction Systems Eric Blake National Hurricane Center 7 March 2017 Acknowledgements to Michael Brennan 1 Question 1 What are some current advantages of using single-model ensembles? A. Estimates
Transitions. Newsletter Spring-Summer By stimulating the use of operational codes by the research community, composed of
Developmental Testbed Center DTC Transitions Newsletter Spring-Summer 2015 ISSUE 8 Courtesy of Paula McCaslin INSIDE THIS ISSUE DIRECTOR S CORNER 1,2 NITE ARTICLE 1,2 BRIDGES TO OPERATIONS 3 WHO S WHO
Plans for NOAA s regional ensemble systems: NARRE, HRRRE, and a regional hybrid assimilation
NOAA Earth System Research Laboratory Plans for NOAA s regional ensemble systems: NARRE, HRRRE, and a regional hybrid assimilation Tom Hamill (substituting for Stan Benjamin and team) NOAA Earth System
The Properties of Convective Clouds Over the Western Pacific and Their Relationship to the Environment of Tropical Cyclones
The Properties of Convective Clouds Over the Western Pacific and Their Relationship to the Environment of Tropical Cyclones Principal Investigator: Dr. Zhaoxia Pu Department of Meteorology, University
The EMC Mission.. In response to operational requirements:
The EMC Mission.. In response to operational requirements: Maintain operational model suite The scientific correctness and integrity of operational forecast modeling systems Modify current operational
Ensemble Kalman Filter Assimilation of Radar Data for a Convective Storm using a Two-moment Microphysics Scheme 04/09/10
Ensemble Kalman Filter Assimilation of Radar Data for a Convective Storm using a Two-moment Microphysics Scheme 04/09/10 Youngsun Jung 1, Ming Xue 1,2, and Mingjing Tong 3 CAPS 1 and School of Meteorology
Variational data assimilation of lightning with WRFDA system using nonlinear observation operators
Variational data assimilation of lightning with WRFDA system using nonlinear observation operators Virginia Tech, Blacksburg, Virginia Florida State University, Tallahassee, Florida rstefane@vt.edu, inavon@fsu.edu
University of Oklahoma, Norman, Oklahoma. June 6, 2012 Submitted to Weather and Forecasting Revised November 3, 2012
Track and Intensity Forecasting of Hurricanes: Impact of Convection-Permitting Resolution and Global Ensemble Kalman Filter Analysis on 2010 Atlantic Season Forecasts Ming Xue 1,2 *, Jordan Schleif 1,2,
Advancements to the Operational HWRF Modeling System at EMC
Advancements to the Operational HWRF Modeling System at EMC Vijay Tallapragada Hurricane Team Lead Environmental Modeling Center, NCEP/NOAA/NWS Camp Springs, MD 20746. WRF for Hurricanes Tutorial, Science
PUBLICATIONS. Journal of Geophysical Research: Atmospheres
PUBLICATIONS Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE Key Points: T-TREC-retrieved wind and radial velocity data are assimilated using an ensemble Kalman filter The relative impacts