Aircraft-based Observations: Impact on weather forecast model performance
|
|
- Chastity Campbell
- 6 years ago
- Views:
Transcription
1 Aircraft-based Observations: Impact on weather forecast model performance Stephen S. Weygandt Eric James, Stan Benjamin, Bill Moninger, Brian Jamison, Geoff Manikin* NOAA Earth System Research Laboratory *NOAA National Centers for Environmental Prediction Friends and Partners of Aviation Weather NBAA Convention, Oct 10-11, 2017
2 ABO impact HRRR (and on HRRR weather RAP) Milestones Future models: Milestones Key points #1: Aircraft data most important observation type over North America for 3-12h (situational awareness) forecast accuracy (winds, temperature, Rel. Hum.) #2: Increased aircraft data has improved US (and global) forecast skill ( ) #3: Geographical and temporal gaps in aircraft data provide opportunity for improved forecast accuracy through improved aircraft participation Ascent / descent 0-15 kft
3 Rapid Refresh and HRRR NOAA hourly updated models 13-km Rapid Refresh (RAP) 3-km High Resolution Rapid Refresh (HRRR) RAP Version 3 NCEP implement Aug 2016 Version 4 GSD (including HRRR-AK) NCEP Spring 2018 Hourly updating maximize use of ALL observations
4 Rapid Refresh HRRR (and hourly HRRR RAP) cycling Milestones Future Milestones improves guidance Use latest observations EACH HOUR to obtain freshest, most accurate snapshot of atmospheric state 1-hr fcst Background Fields 3DVAR Obs 1-hr fcst Analysis Fields 3DVAR Obs 1-hr fcst Get more accurate short-range weather forecasts for decision making WIND forecast errors 1h 3h 6h 12h Wind forecast improvement from hourly updating for 1-h vs. 6-h forecast Time (UTC) 1 Jan 10 Oct 2017 vector wind RMS error for CONUS rawinsondes for different forecast lengths
5 Observations HRRR (and HRRR assimilated: RAP) Milestones Future Milestones RAP and HRRR Hourly Observation Type Variables Observed Observation Count Rawinsonde Temperature, Humidity, Wind, Pressure 120 / 12h Aircraft Wind, Temperature 2,000-15,000 / hr Aircraft WVSS, Tamdar (3 Aug ) Humidity / hr Surface/METAR Temperature, Moisture, Wind, Pressure, Clouds, Visibility, Weather Surface/Mesonet Temperature, Moisture, Wind ~5K-12K Buoys/ships Wind, Pressure Profiler 915 MHz Wind, Virtual Temperature Radar VAD Wind 125 Radar Radial Velocity 125 radars Radar reflectivity CONUS 3-d refl Rain, Snow, Graupel 1,500,000 Lightning (proxy reflectivity) NLDN GOES AMVs Wind Polar Orbiter Satellite Radiances very large Geostationary Satellite Radiances large GOES cloud-top press/temp Cloud Top Height 100,000 GPS Precipitable water Humidity 260 WindSat Scatterometer Winds 2,000 10,000
6 Variables measured by each observation type Observation Types Temperature Wind Rel. Hum. Pres. / Height cloud/ saturation/ Hydrometeor Radiance Extent Raob Y Y Y Y D, 2x/day Surface Y Y Y Y Y --- 2D Aircraft Y Y Y Radar Reflectivity Radar Vr, VAD (~15%) (icing pireps not used) --- 3D Y --- 3D (in precip) --- Y D, Column GPS-met Y Column GOES (cloud, AMV) Satellite Radiance IN SITU OBS RADAR OBS Y --- Y --- 3D Y* 3D SATELLITE OBS *Satellite radiance: a complex function of temperature and humidity profiles Radar radial velocity: single wind component; AMV winds: height assignment issues
7 Regional Observation Impact studies with RAP - GSD Observation gaps are major source in limiting forecast accuracy, even over US RAP observation impact study 3 seasons, 8 (9) observation types Rawinsonde Aircraft obs Radar reflectivity VAD winds Surface obs GPS-Met AMV (winds) GOES clouds (Satellite Radiance) Aircraft observations most important observation type -- Ascent/descent and en route obs both important -- Water vapor observations (about 1/7 total) improve RH forecast accuracy Radar Coverage Sample aircraft obs coverage Raob Coverage
8 Aircraft observations -- most important data source for weather prediction skill Rawinsonde Aircraft Impact on WIND in hpa layer AC <350 mb AC >350 mb AC Temp+RH Reflectivity VAD Surface GPS AMV GOES 3/6/9/12 hr impact for each obs type Forecast degradation for withholding each obs type Raob Withhold: A ALL Rawinsonde B ALL Aircraft C Aircraft above 350 hpa D Aircraft below 350 hpa E Aircraft temp/humidity F ALL Profiler G ALL Radar Reflectivity H ALL VAD winds I ALL surface obs J ALL GPS-Met PW K ALL AMVs winds L GOES (winds/clouds) Aircraft obs most important for wind accuracy at all forecast lengths Significant impact also from rawinsonde, surface observations, GOES observations (likely from clearing of spurious convection)
9 Most Observation HRRR (and HRRR RAP) impact: Milestones Future Aircraft, Milestones raobs, GOES Rawinsonde Aircraft Radar reflect. VADs GPS 25% Error reduction (6-h) GOES Sat. radiance Surface AMVs Rawinsonde Aircraft Radar reflect. VADs GPS GOES Sat. radiance 25% Error reduction (6-h) Surface AMVs Relative humidity impact (%) ( mb) Rawinsonde Aircraft Profiler Radar Reflectivity VAD winds GPS-Met PW GOES RARS data Radiance data Surface obs AMVs Rawinsonde Wind impact (m/s) Spring retrospective Aircraft Radar reflect. VADs GPS 25% Error reduction (6-h) GOES ( mb) Sat. radiance Surface AMVs Temperature impact (k) ( mb)
10 Aircraft observation also important for global model forecast skill (satellite data dominates) Aircraft Raob/balloon Aircraft Cloud-drift vecs Surface obs Surface obs Global model obs impact: John Eyre UK Met Office - Impact on 24h global forecast error (FSOI) Contributions to the total observation impact on a moist 24-hour forecast-error energynorm, surface-150 hpa. Sat obs
11 Global aircraft observation importance will increase as global models start hourly cycling Global aircraft observation density
12 RUC skill HRRR improved (and HRRR RAP) Milestones from Future more Milestones aircraft obs RUC model frozen, skill improvement solely from more aircraft obs Monthly aircraft obs counts RUC RAP 6-h upper-level Wind RMS error Slide Date
13 FAA aircraft obs study (GSD, AvMet) GOALS: Quantify gaps in airborne observations (spatial, temporal, parameter, etc,) Identify most cost effective ways to obtain airborne data AMDAR obs density CONUS (obs/km**2) per 24h period 2017 MWR article by James and Benjamin Study sponsored by FAA Tammy Farrar project sponsor
14 AMDAR obs densitry -- time of day -- CONUS Morning 12z 18z Evening 00z 06z Afternoon 18z 00z Overnight 06z 12z
15 AMDAR obs by elevation full day CONUS All levels kft kft Ascent / descent 0-15 kft
16 Regional Observation Impact studies with RAP - GSD Significant gap to achieve profiles every 300 km/3h -- achieving frequent aircraft profiles out of regional airports estimated to significantly improve forecast accuracy Airborne observation study sponsored by FAA (GSD, AvMet) 2017 article by James and Benjamin, MWR What are the coverage expansion priorities For improved model skill? Slide kft Ascent / descent Data for an entire day
17 Improved mesoscale fields will lead better small-scale forecasts Previous results: Increased RAP skill leads to improved HRRR skill for thunderstorms and other weather hazards Improvements will be extended by ongoing storm-scale ensemble data assimilation for HRRR and future stormscale ensemble forecast system Improved short-term skill from HRRR ensemble HRRR ensemble skill HRRR current skill Slide 17 Wiring chart for HRRR Ensemble
18 ABO impact HRRR (and on HRRR weather RAP) Milestones Future models: Milestones Key points #1: Aircraft data most important observation type over North America for 3-12h (situational awareness) forecast accuracy (winds, temperature, Rel. Hum.) #2: Increased aircraft data has improved US (and global) forecast skill ( ) #3: Geographical and temporal gaps in aircraft data provide opportunity for improved forecast accuracy through improved aircraft participation Ascent / descent 0-15 kft
Weather Hazard Modeling Research and development: Recent Advances and Plans
Weather Hazard Modeling Research and development: Recent Advances and Plans Stephen S. Weygandt Curtis Alexander, Stan Benjamin, Geoff Manikin*, Tanya Smirnova, Ming Hu NOAA Earth System Research Laboratory
More informationApplications in situational awareness high-resolution NWP -- Ideas for the Blueprint DA discussion
Applications in situational awareness high-resolution NWP -- Ideas for the Blueprint DA discussion 8 March 2016 Stan Benjamin, David Dowell, Curtis Alexander NOAA/ESRL/GLOBAL SYSTEMS DIVISION Situational
More informationEnhancing short term wind energy forecasting for improved utility operations: The Wind Forecast Improvement Project (WFIP)
Enhancing short term wind energy forecasting for improved utility operations: The Wind Forecast Improvement Project (WFIP) Jim Wilczak NOAA S. Benjamin, I. Djalalova, L. Bianco, S. Calvert, J. Freedman,
More informationThe WMO Observation Impact Workshop. lessons for SRNWP. Roger Randriamampianina
The WMO Observation Impact Workshop - developments outside Europe and lessons for SRNWP Roger Randriamampianina Hungarian Meteorological Service (OMSZ) Outline Short introduction of the workshop Developments
More information2012 and changes to the Rapid Refresh and HRRR weather forecast models
2012 and 2013-15 changes to the Rapid Refresh and HRRR weather forecast models 31 October 2012 Stan Benjamin Steve Weygandt Curtis Alexander NOAA Earth System Research Laboratory Boulder, CO FPAW - 2012
More informationPlans 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
More informationCanadian Meteorological and Oceanographic Society and American Meteorological Society 21 st Conference on Numerical Weather Prediction 31 May 2012
Canadian Meteorological and Oceanographic Society and American Meteorological Society 21 st Conference on Numerical Weather Prediction 31 May 2012 The High Resolution Rapid Refresh (): An hourly updating
More information22 nd Conference on Weather Analysis and Forecasting / 18 th Conference on Numerical Weather Prediction June 2007, Park City, UT, Amer. Meteor. Soc.
22 nd Conference on Weather Analysis and Forecasting / 18 th Conference on Numerical Weather Prediction June 2007, Park City, UT, Amer. Meteor. Soc. 4A.2 TAMDAR AND ITS IMPACT ON RAPID UPDATE CYCLE (RUC)
More informationASSIMILATION OF METAR CLOUD AND VISIBILITY OBSERVATIONS IN THE RUC
9.13 ASSIMILATION OF METAR CLOUD AND VISIBILITY OBSERVATIONS IN THE RUC Stanley G. Benjamin, Stephen S. Weygandt, John M. Brown, Tracy Lorraine Smith 1, Tanya Smirnova 2, William R. Moninger, Barry Schwartz,
More informationThe 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
More informationAMDAR Global Status, Benefits and Development Plans*
AMDAR Global Status, Benefits and Development Plans* WMO CBS ET Aircraft Based Observations Bryce Ford * Adapted from Presentation at WMO Congress XVII, June 2015 by WMO CBS President, reviewed by WMO
More informationFAA Weather Research Plans
FAA Weather Research Plans Presented to: Friends /Partners in Aviation Weather Vision Forum By: Ray Moy FAA Aviation Weather Office Date: Aviation Weather Research Program (AWRP) Purpose: Applied Research
More informationAMDAR Forecast Applications. Richard Mamrosh NWS Green Bay, Wisconsin, USA
AMDAR Forecast Applications Richard Mamrosh NWS Green Bay, Wisconsin, USA AMDAR has many applications Aviation Low level wind shear Ceilings and visibilities Icing and turbulence Winter Storms Precipitation
More informationIntroduction to NCEP's time lagged North American Rapid Refresh Ensemble Forecast System (NARRE-TL)
Introduction to NCEP's time lagged North American Rapid Refresh Ensemble Forecast System (NARRE-TL) Binbin Zhou 1,2, Jun Du 2, Geoff Manikin 2 & Geoff DiMego 2 1. I.M. System Group 2. EMC/NCEP/NWS/NOAA
More informationA 21st century HRRR-based approach to estimating probable maximum precipitation to enhance dam safety and community resilience
30 May 2017 FIRO Science Task Group Workshop A 21st century HRRR-based approach to estimating probable maximum precipitation to enhance dam safety and community resilience Courtesy Bill McCormick, Chief,
More informationweather forecast Improving NOAA models for energy Stan Benjamin, Boulder, CO USA Joseph Olson, Curtis Alexander, Eric James,
Lamont, OK X Obs radar 5h HRRR Forecast Improving NOAA weather forecast models for energy Stan Benjamin, Joseph Olson, Curtis Alexander, Eric James, Dave Turner, Melinda Marquis NOAA Earth System Research
More information3.1 TAMDAR JET FLEETS AND THEIR IMPACT ON RAPID UPDATE CYCLE (RUC) FORECASTS
3.1 TAMDAR JET FLEETS AND THEIR IMPACT ON RAPID UPDATE CYCLE (RUC) FORECASTS William R. Moninger*, S. G. Benjamin, B. D. Jamison 1, T. W. Schlatter 2, T. L. Smith 1, and E. J. Szoke 1 NOAA Earth System
More informationAssimilation of Mesoscale Observations for use in Numerical Weather Prediction
Assimilation of Mesoscale Observations for use in Numerical Weather Prediction Steve Koch Thermodynamic Profiling Technologies Workshop Boulder 12 14 April 2011 Important Questions (from 2003 USWRP Mesoscale
More informationScatterometer Wind Assimilation at the Met Office
Scatterometer Wind Assimilation at the Met Office James Cotton International Ocean Vector Winds Science Team (IOVWST) meeting, Brest, June 2014 Outline Assimilation status Global updates: Metop-B and spatial
More informationUpdate on CoSPA Storm Forecasts
Update on CoSPA Storm Forecasts Haig August 2, 2011 This work was sponsored by the Federal Aviation Administration under Air Force Contract No. FA8721-05-C-0002. Opinions, interpretations, conclusions,
More informationNOAA s Severe Weather Forecasting System: HRRR to WoF to FACETS
NOAA s Severe Weather Forecasting System: HRRR to WoF to FACETS David D NOAA / Earth System Research Laboratory / Global Systems Division Nowcasting and Mesoscale Research Working Group Meeting World Meteorological
More informationFigure 1. Observations assimilated into RUC as of 2008 after upgrade, new observations in bold and with leading arrows.
6.2 IMPLEMENTATION OF THE RADAR-ENHANCED RUC Stan Benjamin, Stephen S. Weygandt, John M. Brown, Tanya Smirnova 2, Dezso Devenyi 2, Kevin Brundage 3, Georg Grell 2, Steven Peckham 2, William R. Moninger,
More informationWMO AMDAR Programme Overview
WMO AMDAR Programme Overview Bryce Ford - presenting on behalf of WMO and NOAA FPAW Nov 1, 2012 The WMO AMDAR Program AMDAR Programme Current Status WMO World Meteorological Organization (http://www.wmo.int)
More informationRecent Data Assimilation Activities at Environment Canada
Recent Data Assimilation Activities at Environment Canada Major upgrade to global and regional deterministic prediction systems (now in parallel run) Sea ice data assimilation Mark Buehner Data Assimilation
More informationAVIATION APPLICATIONS OF A NEW GENERATION OF MESOSCALE NUMERICAL WEATHER PREDICTION SYSTEM OF THE HONG KONG OBSERVATORY
P452 AVIATION APPLICATIONS OF A NEW GENERATION OF MESOSCALE NUMERICAL WEATHER PREDICTION SYSTEM OF THE HONG KONG OBSERVATORY Wai-Kin WONG *1, P.W. Chan 1 and Ivan C.K. Ng 2 1 Hong Kong Observatory, Hong
More informationRUC development on ceiling/visibility forecasts
RUC development on ceiling/visibility forecasts Stan Benjamin John M. Brown NOAA / FSL Stan.Benjamin@noaa.gov john.m.brown@noaa.gov 303-497-6387 303-497-6867 http://ruc.fsl.noaa.gov Bill Moninger Ed Szoke
More informationEmerging Aviation Weather Research at MIT Lincoln Laboratory*
Emerging Aviation Weather Research at MIT Lincoln Laboratory* Haig 19 November 2015 *This work was sponsored by the Federal Aviation Administration under Air Force Contract No. FA8721-05-C-0002. Opinions,
More informationDeterministic and Ensemble Storm scale Lightning Data Assimilation
LI Mission Advisory Group & GOES-R Science Team Workshop 27-29 May 2015 Deterministic and Ensemble Storm scale Lightning Data Assimilation Don MacGorman, Ted Mansell (NOAA/National Severe Storms Lab) Alex
More informationData Short description Parameters to be used for analysis SYNOP. Surface observations by ships, oil rigs and moored buoys
3.2 Observational Data 3.2.1 Data used in the analysis Data Short description Parameters to be used for analysis SYNOP Surface observations at fixed stations over land P,, T, Rh SHIP BUOY TEMP PILOT Aircraft
More informationObserving System Impact Studies in ACCESS
Observing System Impact Studies in ACCESS www.cawcr.gov.au Chris Tingwell, Peter Steinle, John le Marshall, Elaine Miles, Yi Xiao, Rolf Seecamp, Jin Lee, Susan Rennie, Xingbao Wang, Justin Peter, Alan
More informationConsolidated Storm Prediction for Aviation (CoSPA) Overview
Consolidated Storm Prediction for Aviation (CoSPA) Overview Ray Moy (FAA), Bill Dupree (MIT LL Lead), and Matthias Steiner (NCAR Lead) 27 September 2007 NBAA User Panel Review - 1 Consolidated Storm Prediction
More informationUtilization of Forecast Models in High Temporal GOES Sounding Retrievals
Utilization of Forecast Models in High Temporal GOES Sounding Retrievals Zhenglong Li, Jun Li, W. Paul Menzel, Steve Ackerman CIMSS/UW The CoRP Symposium Aug 12-13, 2008 Corvallis, OR Introduction: GOES
More informationReport 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
More informationRTMA Flowchart (CONUS)
22 nd Conf. Wea. Analysis Forecasting / 18 th Conf. Num Wea. Pred., June 2007, Park City, UT, Amer. Meteor. Soc. 4A.6 THE RTMA BACKGROUND HOURLY DOWNSCALING OF RUC DATA TO 5-KM DETAIL Stan Benjamin, John
More information8.2 EVALUATING THE BENEFITS OF TAMDAR DATA IN CONVECTIVE FORECASTING. Cyrena-Marie Druse 1 AirDat LLC. Evergreen, CO
8.2 EVALUATING THE BENEFITS OF TAMDAR DATA IN CONVECTIVE FORECASTING Cyrena-Marie Druse 1 AirDat LLC. Evergreen, CO 1. INTRODUCTION 1 The TAMDAR (Tropospheric Airborne Meteorological Data Reporting) Sensor
More informationSynthetic Weather Radar: Offshore Precipitation Capability
Synthetic Weather Radar: Offshore Precipitation Capability Mark S. Veillette 5 December 2017 Sponsors: Randy Bass, FAA ANG-C6 and Rogan Flowers, FAA AJM-33 DISTRIBUTION STATEMENT A: Approved for public
More informationMulti Radar Multi Sensor NextGen Weather Program. Presentation materials sourced from: Ken Howard HydroMet Research Group NSSL Warning R&D Division
Multi Radar Multi Sensor NextGen Weather Program Presentation materials sourced from: Ken Howard HydroMet Research Group NSSL Warning R&D Division What is Multiple Radar Multi Sensor System () is the world
More information11.1 CONVECTION FORECASTS FROM THE HOURLY UPDATED, 3-KM HIGH RESOLUTION RAPID REFRESH (HRRR) MODEL
Preprints, 24 th Conference on Severe Local Storms, October 2008, Savannah, GA, Amer. Meteor. Soc. 11.1 CONVECTION FORECASTS FROM THE HOURLY UPDATED, 3-KM HIGH RESOLUTION RAPID REFRESH (HRRR) MODEL Tracy
More informationJ3.4 FROM THE RADAR-ENHANCED RUC TO THE WRF-BASED RAPID REFRESH. NOAA Earth System Research Laboratory, Boulder, CO
22 nd Conf. Wea. Analysis Forecasting / 18 th Conf. Num Wea. Pred., June 2007, Park City, UT, Amer. Meteor. Soc. J3.4 FROM THE RADAR-ENHANCED RUC TO THE WRF-BASED RAPID REFRESH Stan Benjamin, Stephen S.
More informationConvective-scale NWP for Singapore
Convective-scale NWP for Singapore Hans Huang and the weather modelling and prediction section MSS, Singapore Dale Barker and the SINGV team Met Office, Exeter, UK ECMWF Symposium on Dynamical Meteorology
More informationMeasuring In-cloud Turbulence: The NEXRAD Turbulence Detection Algorithm
Measuring In-cloud Turbulence: The NEXRAD Turbulence Detection Algorithm John K. Williams,, Greg Meymaris,, Jason Craig, Gary Blackburn, Wiebke Deierling,, and Frank McDonough AMS 15 th Conference on Aviation,
More informationUncertainty in Operational Atmospheric Analyses. Rolf Langland Naval Research Laboratory Monterey, CA
Uncertainty in Operational Atmospheric Analyses 1 Rolf Langland Naval Research Laboratory Monterey, CA Objectives 2 1. Quantify the uncertainty (differences) in current operational analyses of the atmosphere
More information9.5 EVALUATING THE BENEFITS OF TAMDAR DATA IN AVIATION FORECASTING. Cyrena-Marie Druse 1 and Neil Jacobs AirDat LLC. Evergreen, CO
9.5 EVALUATING THE BENEFITS OF TAMDAR DATA IN AVIATION FORECASTING Cyrena-Marie Druse 1 and Neil Jacobs AirDat LLC. Evergreen, CO 1. INTRODUCTION 1 The TAMDAR (Tropospheric Airborne Meteorological Data
More informationDevelopment of High-Resolution Rapid Refresh (HRRR) Ensemble Data Assimilation, Forecasts and Post Processing
7 th Ensemble Users Workshop Ensemble Development I Development of High-Resolution Rapid Refresh (HRRR) Ensemble Data Assimilation, Forecasts and Post Processing 14 June 2016 Curtis Alexander, David Dowell,
More informationConvective-scale data assimilation at the UK Met Office
Convective-scale data assimilation at the UK Met Office DAOS meeting, Exeter 25 April 2016 Rick Rawlins Hd(DAE) Acknowledgments: Bruce Macpherson and team Contents This presentation covers the following
More informationCorridor Integrated Weather System (CIWS) MIT Lincoln Laboratory. CIWS D. Meyer 10/21/05
Corridor Integrated Weather System () Outline Example of Weather Impacting Air traffic Impacts on worst delay day Ways to reduce delay Improve forecasts Aid traffic flow management Aviation Delay Problem
More informationDoppler radial wind spatially correlated observation error: operational implementation and initial results
Doppler radial wind spatially correlated observation error: operational implementation and initial results D. Simonin, J. Waller, G. Kelly, S. Ballard,, S. Dance, N. Nichols (Met Office, University of
More informationAMVs in the ECMWF system:
AMVs in the ECMWF system: Highlights of the operational and research activities Kirsti Salonen and Niels Bormann Slide 1 Number of used AMVs Look back: how the use of AMVs has evolved NOAA-15,-16,-18,-19
More informationThe 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
More informationWVSS-II MOISTURE OBSERVATIONS: A low-cost tool for validating and monitoring asynoptic satellite data
WVSS-II MOISTURE OBSERVATIONS: A low-cost tool for validating and monitoring asynoptic satellite data Ralph Petersen 1, Sarah Bedka 1, Wayne Feltz 1, Erik Olson 1 and David Helms 2 1 Cooperative Institute
More informationCombining Polar Hyper-spectral and Geostationary Multi-spectral Sounding Data A Method to Optimize Sounding Spatial and Temporal Resolution
Combining Polar Hyper-spectral and Geostationary Multi-spectral Sounding Data A Method to Optimize Sounding Spatial and Temporal Resolution W. L. Smith 1,2, E. Weisz 1, and J. McNabb 2 1 University of
More informationFPAW October Pat Murphy & David Bright NWS Aviation Weather Center
FPAW October 2014 Pat Murphy & David Bright NWS Aviation Weather Center Overview Ensemble & Probabilistic Forecasts What AWC Is Doing Now Ensemble Processor What s In Development (NOAA Aviation Weather
More informationREVISION OF THE STATEMENT OF GUIDANCE FOR GLOBAL NUMERICAL WEATHER PREDICTION. (Submitted by Dr. J. Eyre)
WORLD METEOROLOGICAL ORGANIZATION Distr.: RESTRICTED CBS/OPAG-IOS (ODRRGOS-5)/Doc.5, Add.5 (11.VI.2002) COMMISSION FOR BASIC SYSTEMS OPEN PROGRAMME AREA GROUP ON INTEGRATED OBSERVING SYSTEMS ITEM: 4 EXPERT
More information1. Introduction 8.4. * Corresponding author address: Steve Weygandt, NOAA/GSD, R/E/GSD, 325 Broadway, Boulder, CO
Preprints, 12 th Conf. on IOAS-AOLS. January 2008, New Orleans, LA, Amer. Meteor. Soc. 8.4 Assimilation of radar reflectivity data using a diabatic digital filter within the Rapid Update Cycle Stephen
More informationThunderstorm-Scale EnKF Analyses Verified with Dual-Polarization, Dual-Doppler Radar Data
Thunderstorm-Scale EnKF Analyses Verified with Dual-Polarization, Dual-Doppler Radar Data David Dowell and Wiebke Deierling National Center for Atmospheric Research, Boulder, CO Ensemble Data Assimilation
More informationA 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
More informationDevelopment of an Hourly- Updated NAM Forecast System
Development of an Hourly- Updated NAM Forecast System Jacob Carley ab, Eric Rogers b, Shun Liu ab, Brad Ferrier ab, Eric Aligo ab, Matthew Pyle b, and Geoff DiMego b a IMSG, b NOAA/NWS/NCEP/EMC jacob.carley@noaa.gov
More informationWeather Evaluation Team (WET)
Weather Evaluation Team (WET) Presented to: Friends and Partners in Aviation Weather Kevin Johnston ATCSCC Tom Fahey Delta Air Lines 1 WET Membership FAA Denver ARTCC Atlanta ARTCC ATCSCC Minneapolis TRACON
More informationAmy Harless. Jason Levit, David Bright, Clinton Wallace, Bob Maxson. Aviation Weather Center Kansas City, MO
Amy Harless Jason Levit, David Bright, Clinton Wallace, Bob Maxson Aviation Weather Center Kansas City, MO AWC Mission Decision Support for Traffic Flow Management Ensemble Applications at AWC Testbed
More informationProgress in Aviation Weather Forecasting for ATM Decision Making FPAW 2010
Progress in Aviation Weather Forecasting for ATM Decision Making FPAW 2010 Jim Evans Marilyn Wolfson 21 October 2010-1 Overview (1) Integration with storm avoidance models and ATC route usage models (2)
More informationP5.11 TACKLING THE CHALLENGE OF NOWCASTING ELEVATED CONVECTION
P5.11 TACKLING THE CHALLENGE OF NOWCASTING ELEVATED CONVECTION Huaqing Cai*, Rita Roberts, Dan Megenhardt, Eric Nelson and Matthias Steiner National Center for Atmospheric Research, Boulder, CO, 80307,
More informationLocalized Aviation Model Output Statistics Program (LAMP): Improvements to convective forecasts in response to user feedback
Localized Aviation Model Output Statistics Program (LAMP): Improvements to convective forecasts in response to user feedback Judy E. Ghirardelli National Weather Service Meteorological Development Laboratory
More informationTransitioning NCAR s Aviation Algorithms into NCEP s Operations
Transitioning NCAR s Aviation Algorithms into NCEP s Operations Hui-Ya Chuang 1, Yali Mao 1,2, and Binbin Zhou 1,2 1. EMC/NCEP/NOAA, College Park MD 2. I.M. System Group, Inc. AMS 18th Conference on Aviation,
More informationAdvances in weather and climate science
Advances in weather and climate science Second ICAO Global Air Navigation Industry Symposium (GANIS/2) 11 to 13 December 2017, Montreal, Canada GREG BROCK Scientific Officer Aeronautical Meteorology Division
More informationNOAA Research and Development Supporting NextGen. Darien Davis NOAA Office of Oceanic and Atmospheric Research June 22, 2009
NOAA Research and Development Supporting NextGen Darien Davis Darien.l.davis@noaa.gov NOAA Office of Oceanic and Atmospheric Research June 22, 2009 FAA/NOAA Coordination Developing an integrated science
More informationP2.5. Preprint, 18 th Conference on Numerical Weather Prediction American Meteorological Society, Park City, UT
Preprint, 18 th Conference on Numerical Weather Prediction American Meteorological Society, Park City, UT P2.5 Development and Testing of a New Cloud Analysis Package using Radar, Satellite, and Surface
More informationAssimilation of Satellite Infrared Brightness Temperatures and Doppler Radar Observations in a High-Resolution OSSE
Assimilation of Satellite Infrared Brightness Temperatures and Doppler Radar Observations in a High-Resolution OSSE Jason Otkin and Becky Cintineo University of Wisconsin-Madison, Cooperative Institute
More informationSatellite-Derived Winds in the U.S. Navy s Global NWP System: Usage and Data Impacts in the Tropics
Satellite-Derived Winds in the U.S. Navy s Global NWP System: Usage and Data Impacts in the Tropics Patricia Pauley 1, Rolf Langland 1, Rebecca Stone 2, and Nancy Baker 1 1 Naval Research Laboratory, Monterey,
More informationUtilising Radar and Satellite Based Nowcasting Tools for Aviation Purposes in South Africa. Erik Becker
Utilising Radar and Satellite Based Nowcasting Tools for Aviation Purposes in South Africa Erik Becker Morné Gijben, Mary-Jane Bopape, Stephanie Landman South African Weather Service: Nowcasting and Very
More informationSATELLITE SIGNATURES ASSOCIATED WITH SIGNIFICANT CONVECTIVELY-INDUCED TURBULENCE EVENTS
SATELLITE SIGNATURES ASSOCIATED WITH SIGNIFICANT CONVECTIVELY-INDUCED TURBULENCE EVENTS Kristopher Bedka 1, Wayne Feltz 1, John Mecikalski 2, Robert Sharman 3, Annelise Lenz 1, and Jordan Gerth 1 1 Cooperative
More informationOSSE to infer the impact of Arctic AMVs extracted from highly elliptical orbit imagery
OSSE to infer the impact of Arctic AMVs extracted from highly elliptical orbit imagery L. Garand 1 Y. Rochon 1, S. Heilliette 1, J. Feng 1, A.P. Trishchenko 2 1 Environment Canada, 2 Canada Center for
More informationToward improved initial conditions for NCAR s real-time convection-allowing ensemble. Ryan Sobash, Glen Romine, Craig Schwartz, and Kate Fossell
Toward improved initial conditions for NCAR s real-time convection-allowing ensemble Ryan Sobash, Glen Romine, Craig Schwartz, and Kate Fossell Storm-scale ensemble design Can an EnKF be used to initialize
More informationAutomated Aircra- Observa2ons: Their Importance to Future Avia2on Transporta2on Opera2ons
Automated Aircra- Observa2ons: Their Importance to Future Avia2on Transporta2on Opera2ons Ralph Petersen 1, Bre0 Hoover 1, Anne-Sophie Daloz 1, Lee Cronce 1, Tim Wagner 1, Skyler Williams 1, Richard Mamrosh
More informationImpact of METOP ASCAT Ocean Surface Winds in the NCEP GDAS/GFS and NRL NAVDAS
Impact of METOP ASCAT Ocean Surface Winds in the NCEP GDAS/GFS and NRL NAVDAS COAMPS @ Li Bi 1,2 James Jung 3,4 Michael Morgan 5 John F. Le Marshall 6 Nancy Baker 2 Dave Santek 3 1 University Corporation
More informationChengsi 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
More informationNinth Workshop on Meteorological Operational Systems. Timeliness and Impact of Observations in the CMC Global NWP system
Ninth Workshop on Meteorological Operational Systems ECMWF, Reading, United Kingdom 10 14 November 2003 Timeliness and Impact of Observations in the CMC Global NWP system Réal Sarrazin, Yulia Zaitseva
More informationJidong 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,
More informationWG1 Overview. PP KENDA for km-scale EPS: LETKF. current DA method: nudging. radar reflectivity (precip): latent heat nudging 1DVar (comparison)
WG1 Overview Deutscher Wetterdienst, D-63067 Offenbach, Germany current DA method: nudging PP KENDA for km-scale EPS: LETKF radar reflectivity (precip): latent heat nudging 1DVar (comparison) radar radial
More informationThe 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
More information0-6 hour Weather Forecast Guidance at The Weather Company. Steven Honey, Joseph Koval, Cathryn Meyer, Peter Neilley The Weather Company
1 0-6 hour Weather Forecast Guidance at The Weather Company Steven Honey, Joseph Koval, Cathryn Meyer, Peter Neilley The Weather Company TWC Forecasts: Widespread Adoption 2 0-6 Hour Forecast Details 3
More informationCalculates CAT and MWT diagnostics. Paired down choice of diagnostics (reduce diagnostic redundancy) Statically weighted for all forecast hours
1 Major Upgrades All diagnostics mapped to Eddy Dissipation Rate ADDS now displays EDR values CAT diagnostic extended down to 1000 feet MSL & forecast hours 15 and 18 New Mountain Wave diagnostic CAT diagnostics
More informationStrategic Radar Enhancement Project (SREP) Forecast Demonstration Project (FDP) The future is here and now
Strategic Radar Enhancement Project (SREP) Forecast Demonstration Project (FDP) The future is here and now Michael Berechree National Manager Aviation Weather Services Australian Bureau of Meteorology
More informationMichael F. Stringfellow
Michael F. Stringfellow Thermals Columns or bubbles of warm air that rise from the ground when it is heated by the sun Soaring Sustained engineless flight using natural sources of lift Boundary or mixing
More informationEvaluation of Ensemble Icing Probability Forecasts in NCEP s SREF, VSREF and NARRE-TL Systems
Evaluation of Ensemble Icing Probability Forecasts in NCEP s, V and Systems Binbin Zhou 1,2, Jun Du 2, Geoff DeMigo 2 and Robert Sallee 3 1. I.M. System Group 2. Environmental Modeling Center of NCEP 3.
More informationMADIS Airlines for America Briefing
MADIS Airlines for America Briefing Meteorological Assimilated Data Ingest System (MADIS) FPAW Briefing Steve Pritchett NWS Aircraft Based Observations Program Manager MADIS Defined MADIS is a meteorological
More informationWeather vs. Climate. Tucson NWS homepage:
Weather vs. Climate Tucson NWS homepage: www.nws.noaa.gov/twc/ A Weather Forecaster? Betty claims to know exactly when it s going to rain because her knee starts to hurt. Ms. Betty Martin of Newburgh,
More informationTropical 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
More informationApplications of future GEO advanced IR sounder for high impact weather forecasting demonstration with regional OSSE
Applications of future GEO advanced IR sounder for high impact weather forecasting demonstration with regional OSSE Jun Li @, Tim Schmit &, Zhenglong Li @, Feng Zhu @*, Pei Wang @*, Agnes Lim @, and Robert
More informationP3.1 Development of MOS Thunderstorm and Severe Thunderstorm Forecast Equations with Multiple Data Sources
P3.1 Development of MOS Thunderstorm and Severe Thunderstorm Forecast Equations with Multiple Data Sources Kathryn K. Hughes * Meteorological Development Laboratory Office of Science and Technology National
More informationAdvances in weather modelling
Advances in weather modelling www.cawcr.gov.au Robert Fawcett - speaking on behalf of CAWCR Earth-System Modelling and CAWCR Weather and Environmental Prediction May 2013 The Centre for Australian Weather
More informationRegional Hazardous Weather Advisory Centres (RHWACs)
Regional Hazardous Weather Advisory Centres (RHWACs) The following outlines the criteria for the selection of RHWACs based on operational and functional requirements 1. Basic Principles The RHWAC must:
More informationReport from the Sixth WMO Workshop on the Impact of Various Observing System on NWP Lars Peter Riishojgaard, WMO
Report from the Sixth WMO Workshop on the Impact of Various Observing System on NWP Lars Peter Riishojgaard, WMO Scientific Organizing Committee: Erik Andersson, Co-Chair, ECMWF; Yoshiaki Sato, Co-Chair,
More informationNCEP Short Range Ensemble Forecast (SREF) System: what we have and what we need? Jun Du. NOAA/NWS/NCEP Environmental Modeling Center
N C E P NCEP Short Range Ensemble Forecast (SREF) System: what we have and what we need? Jun Du NOAA/NWS/NCEP Environmental Modeling Center (for NSF EarthCube Workshop, NCAR, Dec. 17-18, 2012) 1 An evolving
More informationHyperlocal Marine Weather: What s Happening?
Hyperlocal Marine Weather: What s Happening? André van der Westhuysen 1,2 and Jeff McQueen 1 1 NOAA / National Weather Service National Centers for Environmental Prediction 2 I.M Systems Group, Rockville
More informationThe 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
More informationProject Summary 2015 DTC Task MM5: Test of an Expanded WRF-ARW Domain
1. Introduction Project Summary 2015 DTC Task MM5: Test of an Expanded WRF-ARW Domain Trevor Alcott Ligia Bernardet Isidora Jankov The High-Resolution Rapid Refresh (HRRR) model represents a major step
More informationReview of GFS Forecast Skills in 2012
Review of GFS Forecast Skills in 2012 Fanglin Yang IMSG - Environmental Modeling Center National Centers for Environmental Prediction Acknowledgments: All NCEP EMC Global Climate and Weather Modeling Branch
More information2.2 APPLICATIONS OF AIRCRAFT SOUNDING DATA IN SHORT-TERM CONVECTIVE FORECASTING
2.2 APPLICATIONS OF AIRCRAFT SOUNDING DATA IN SHORT-TERM CONVECTIVE FORECASTING Phillip G. Kurimski* and Eugene S. Brusky Jr. NOAA/National Weather Service, Green Bay, WI 1. INTRODUCTION Automated real-time
More informationSatellite Cloud & Icing Products at NASA Langley Research Center
Satellite Cloud & Icing Products at NASA Langley Research Center Patrick Minnis NASA Langley Research Center Hampton, VA patrick.minnis-1@nasa.gov Friends/Partner in Aviation Weather Forum NBAA Convention,
More informationForecast for 6/28-7/31. Forecaster: Matthew Brewer Forecast made at: 12z 6/27/2017
Forecast for 6/28-7/31 Forecaster: Matthew Brewer Forecast made at: 12z 6/27/2017 Whiteface lodge Mesonet Meteogram for the past 24 hours http://www.nysmesonet.org/data/meteogram#?stid=wfmb Whiteface Summit
More information