2012 NHC Proving Ground Products Hurricane Intensity Estimate (HIE) Chris Velden and Tim Olander 1.

Slides:



Advertisements
Similar presentations
Recent Advances in the Processing, Targeting and Data Assimilation Applications of Satellite-Derived Atmospheric Motion Vectors (AMVs) Howard Berger 1,
Advertisements

1 GOES-R Hurricane Intensity Estimation (HIE) Validation Tool Development Winds Application Team Tim Olander (CIMSS) Jaime Daniels (STAR)
Improvements to Statistical Intensity Forecasts John A. Knaff, NOAA/NESDIS/STAR, Fort Collins, Colorado, Mark DeMaria, NOAA/NESDIS/STAR, Fort Collins,
SPoRT Activities in Support of the GOES-R and JPSS Proving Grounds Andrew L. Molthan, Kevin K. Fuell, and Geoffrey T. Stano NASA Short-term Prediction.
A Blended, Multi-Platform Tropical Cyclone Rapid Intensification Index
Acknowledgments: ONR NOPP program HFIP program ONR Marine Meteorology Program Elizabeth A. Ritchie Miguel F. Piñeros J. Scott Tyo Scott Galvin Gen Valliere-Kelley.
ASII-NG: Developments and outlook NWCSAF 2015 Users Workshop.
Transitioning unique NASA data and research technologies to operations GOES-R Proving Ground Activities at the NASA Short-term Prediction Research and.
Convective Initiation Studies at UW-CIMSS K. Bedka (SSAI/NASA LaRC), W. Feltz (UW-CIMSS), J. Sieglaff (UW-CIMSS), L. Cronce (UW-CIMSS) Objectives Develop.
Using McIDAS-V for Satellite-Based Thunderstorm Research and Product Development Kristopher Bedka UW-Madison, SSEC/CIMSS In Collaboration With: Tom Rink,
UW-CIMSS/UAH MSG SEVIRI Convection Diagnostic and Nowcasting Products Wayne F. Feltz 1, Kristopher M. Bedka 1, and John R. Mecikalski 2 1 Cooperative Institute.
Geostationary Lightning Mapper (GLM) 1 Near uniform spatial resolution of approximately 10 km. Coverage up to 52 deg latitude % flash detection day.
GOES-R Proving Ground NOAA’s Hazardous Weather Testbed Chris Siewert GOES-R Proving Ground Liaison OU-CIMMS / Storm Prediction Center.
CORP Symposium Fort Collins, CO August 16, 2006 Session 3: NPOESS AND GOES-R Applications Tropical Cyclone Applications Ray Zehr, NESDIS / RAMM.
Joe Sienkiewicz 1, Michael Folmer 2 and Hugh Cobb 3 1 NOAA/NWS/NCEP/OPC 2 University of Maryland/ESSIC/CICS 3 NOAA/NWS/NCEP/NHC/ Tropical Analysis and.
Evidence of Strong Updrafts in Tropical Cyclones using Combined Satellite, Lightning, and High-Altitude Aircraft Observations Christopher S. Velden*, Sarah.
Development of a Probabilistic Tropical Cyclone Genesis Prediction Scheme Jason Dunion1, John Kaplan2, Andrea Schumacher3, Joshua Cossuth4, & Mark DeMaria5.
Improvements in Deterministic and Probabilistic Tropical Cyclone Wind Predictions: A Joint Hurricane Testbed Project Update Mark DeMaria and Ray Zehr NOAA/NESDIS/ORA,
Current State of Proving Ground User Readiness at the National Hurricane Center Andrea Schumacher, CSU/CIRA Mark DeMaria, NOAA/NCEP/NHC.
Overshooting Convective Cloud Top Detection A GOES-R Future Capability Product GOES-East (-8/-12/-13) OT Detections at Full Spatial and Temporal.
Training in NOAA Satellite Proving Ground Anthony Mostek and LeRoy Spayd NOAA/NWS/Training Division With Jim Gurka and Tim Schmit NOAA/Satellite & Information.
April nd IBTrACS Workshop 1 Operational Procedures How can we build consistent, homogeneous, well- documented climate quality data?
CIMSS TC Intensity Satellite Consensus (SATCON) Derrick Herndon and Chris Velden Meteorological Satellite (METSAT) Conference Ford Island Conference Center.
GOES-R Risk Reduction New Initiative: Storm Severity Index Wayne M. MacKenzie John R. Mecikalski John R. Walker University of Alabama in Huntsville.
1 CIMSS Participation in the Development of a GOES-R Proving Ground Timothy J. Schmit NOAA/NESDIS/Satellite Applications and Research Advanced Satellite.
Possible impacts of improved GOES-R temporal resolution on tropical cyclone intensity estimates INTRODUCTION The Advanced Baseline imager (ABI) on GOES-R.
1 CIMSS Participation GOES-R Proving Ground Status January 2011 UW-Madison Contributors to this presentation: Tim Schmit, Wayne Feltz, Jordan Gerth, Scott.
Update on 2011 National Hurricane Center Proving Ground Mark DeMaria, NESDIS/STAR PG All Hands Conference Call July 22,
1 GOES-R Proving Ground CIRA / RAMMB Progress Report 10 January 2011 National Center Interactions WFO Interactions ORI Case Study Conferences and Meetings.
Long-Term High-Temporal and Spatial Resolution Overshooting Storm Climatologies Using Geostationary Imagery INTRODUCTION AND BACKGROUND VALIDATION PROBABILISTIC.
Andrea Schumacher, CIRA/CSU Mark DeMaria, NOAA/NWS/NHC.
Improvements to the SHIPS Rapid Intensification Index: A Year-2 JHT Project Update This NOAA JHT project is being funded by the USWRP in NOAA/OAR’s Office.
 Rapidly developing convection is a known source of CIT  Satellite derived cloud top infrared (IR) cooling rate, overshooting tops (OT)/enhanced-V and.
The ARCHER automated TC center-fixing algorithm: Updates on real-time operations, accuracy and capabilities Anthony Wimmers and Christopher Velden Cooperative.
USING THE ROSSBY RADIUS OF DEFORMATION AS A FORECASTING TOOL FOR TROPICAL CYCLOGENESIS USING THE ROSSBY RADIUS OF DEFORMATION AS A FORECASTING TOOL FOR.
John Kaplan (NOAA/HRD), J. Cione (NOAA/HRD), M. DeMaria (NOAA/NESDIS), J. Knaff (NOAA/NESDIS), J. Dunion (U. of Miami/HRD), J. Solbrig (NRL), J. Hawkins(NRL),
A. FY12-13 GIMPAP Project Proposal Title Page Title: Improvements to the Advanced Dvorak Technique Status: New – but continuing work from GIMPAP FY07-09.
Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis SATELLITE LIAISON: MICHAEL J. FOLMER, PHD.
The Impact of Lightning Density Input on Tropical Cyclone Rapid Intensity Change Forecasts Mark DeMaria, John Knaff and Debra Molenar, NOAA/NESDIS, Fort.
1 2 nd GOES-R AWG Validation Workshop Winds Application Team Topic: Hurricane Intensity Estimation (HIE) Algorithm Chris Velden (CIMSS) Tim Olander (CIMSS)
Atlantic Simplified Track Model Verification 4-year Sample ( ) OFCL shown for comparison Forecast Skill Mean Absolute Error.
Upgrades to the Rapid intensification index (RII ) John Kaplan (NOAA/HRD), Christopher Rozoff (CIMSS), Charles Sampson (NRL), James Kossin (NOAA/NCDC),
Improvements to Statistical Forecast Models and the Satellite Proving Ground for 2013 Mark DeMaria, John Knaff, NOAA/NESDIS/STAR John Kaplan, Jason Dunion,
The 2013 Satellite Proving Ground at the National Hurricane Center Mark DeMaria, NCEP/NHC J. Beven 1, M. Brennan 1, H. Cobb 1, J. Knaff 2, A. Schumacher.
1 Developing Assimilation Techniques For Atmospheric Motion Vectors Derived via a New Nested Tracking Algorithm Derived for the GOES-R Advanced Baseline.
Theory West African dust outbreaks and the relationship with North Atlantic hurricanes Amato T. Evan, Christopher S. Velden, Andrew K. Heidinger & Jason.
Tropical Cyclone Rapid Intensity Change Forecasting Using Lightning Data during the 2010 GOES-R Proving Ground at the National Hurricane Center Mark DeMaria.
1 1. FY09 GIMPAP Project Proposal Title Page Revised: June 17, 2008  Title: Tropical Cyclone Forecast Product Improvement with GOES  Project Type: Product.
Operational Uses for an Objective Overshooting Top Algorithm Sarah A. Monette* #, Wayne Feltz*, Chris Velden*, and Kristopher Bedka^ Cooperative Institute.
THE NESDIS TROPICAL CYCLONE FORMATION PROBABILITY PRODUCT: PAST PERFORMANCE AND FUTURE PLANS Andrea B. Schumacher, CIRA Mark DeMaria, NESDIS/StAR John.
John Kaplan (NOAA/HRD), J. Cione (NOAA/HRD), M. DeMaria (NOAA/NESDIS), J. Knaff (NOAA/NESDIS), J. Dunion (U. of Miami/HRD), J. Solbrig (NRL), J. Hawkins(NRL),
Development of a Rapid Intensification Index for the Eastern Pacific Basin John Kaplan NOAA/AOML Hurricane Research Division Miami, FL and Mark DeMaria.
Developers: John Walker, Chris Jewett, John Mecikalski, Lori Schultz Convective Initiation (CI) GOES-R Proxy Algorithm University of Alabama in Huntsville.
Enhancement of SHIPS RI Index Using Satellite 37 GHz Microwave Ring Pattern: A Year-2 Update 67 th IHC/Tropical Cyclone Research Forum March 5-7, 2013.
GOES-R Hurricane Intensity Estimation (HIE) Winds-HIE Application Team Chris Velden & Tim Olander (CIMSS) Jaime Daniels (STAR)
Meeting the challenge of obtaining and interpreting observations of deep convection in tropical disturbances and hurricanes by Ed Zipser, Jon Zawislak,
The National Hurricane Center GOES-R Proving Ground Mark DeMaria NOAA/NESDIS, Fort Collins, CO GLM Science Meeting, Huntsville, AL September 26,
Performance of an Objective Model for Identifying Secondary Eyewall Formation in Hurricanes Matthew Sitkowski CIMSS – University of Wisconsin Jim Kossin.
New Tropical Cyclone Intensity Forecast Tools for the Western North Pacific Mark DeMaria and John Knaff NOAA/NESDIS/RAMMB Andrea Schumacher, CIRA/CSU.
4 th Workshop on Hyperspectral Science of UW-Madison MURI, GIFTS, and GOES-R Hyperspectral Applications for Aviation Advanced Satellite Aviation-weather.
1 Current and planned research with data collected during the IFEX/RAINEX missions Robert Rogers NOAA/AOML/Hurricane Research Division.
Andrea Schumacher, CIRA/CSU and Mark DeMaria, NWS/NCEP/NHC 1.
CIMSS Board of Directors Meeting 12 December 2003 Personnel: John Mecikalski (Principal Investigator) and Kristopher Bedka Objective: Develop methods to.
Tropical Cyclone Forecasting and Monitoring
Training Session: Satellite Applications on Tropical Cyclones
Mark DeMaria and John A. Knaff - NOAA/NESDIS/RAMMB, Fort Collins, CO
GOES-R Risk Reduction Research on Satellite-Derived Overshooting Tops
TC Intensity Estimation: SATellite CONsensus (SATCON)
Objective Overshooting Top and Cold V Detection
Advanced Dvorak Technique
Presentation transcript:

2012 NHC Proving Ground Products Hurricane Intensity Estimate (HIE) Chris Velden and Tim Olander 1

2 Hurricane Intensity Estimates (HIE) {Basically, the ADT} Real-time evaluation of GOES-R HIE during 2012 Atlantic hurricane season: – Will utilize MSG SEVERI imagery on systems east of 60W, and GOES- E CONUS imagery west of 60W – Automatically initiated upon official NHC declaration of tropical cyclone event (depression or greater strength) – Utilizes current ADT version (v8.1.3 w/MW) to ‘simulate’ HIE, with estimates derived every 15 minutes – Further training to be provided at NHC by HIE developers this week – Real-time (and season’s archived cases) HIE estimates available via dedicated webpage at UW-CIMSS:

2012 NHC Proving Ground Products Objective Tropical Overshooting Top (TOT) Detection Algorithm Chris Velden and Sarah Monette 3

Objective Tropical Overshooting Top (TOT) Detection Algorithm Goal: Adapt the existing CIMSS OT algorithm (Bedka et al.) to tropical applications, and demonstrate for GOES-R readiness Developers: Sarah Monette and Chris Velden (CIMSS) Collaborators: Wayne Feltz, Kris Bedka, Chris Rozoff Motivation: Precise location and timing of tropical cyclone (TC) genesis (TCG) and rapid intensification (RI) are two problematic areas for NHC forecasters. Concept: The TOTs are associated with vigorous tropical convection, and may be employed as a proxy for identifying “vortical hot towers”, hypothesized to be important for TCG and intensity change. Potential Applications: 1) Trends in TOTs can be related to favorable environmental factors for TCG or RI. 2) Marine and Trans-Atlantic aviation convective analyses. 4

Example: Hurricane Ivan (2004) TOT locations (yellow dots) are obtained for an MSG satellite scan (proxy for GOES-R demo). TOT trends can be monitored: Note the spike in the TOTs prior to the RI of Ivan. Image courtesy of Kristopher Bedka TOT algorithm technique synopsis: Find relative minima in the GOES 4-km 11 μm BT field colder than 215K. Compute the mean BT of the surrounding anvil cloud. Cloud pixel minima 9K colder than the surrounding anvil are flagged/identified as overshooting tops. Objective Tropical Overshooting Top (TOT) Detection Algorithm 5

Ongoing TOT research>applications: Another potential application of TOTs: oceanic aviation and hazard avoidance. Example: TOTs were used to help guide aircraft during PREDICT. On the right, the G-V plane track (red line) deviates to avoid a TOT in the vicinity (purple square, circled). Analysis of TOT trends with respect to TCG began in 2009, and continued in 2010 using data and cases from the Atlantic PREDICT/GRIP experiments. Preliminary findings are promising, however more data are needed to refine results. TOT trends have also been shown to be a promising predictor of RI. Initial testing using an objective logistic regression scheme for RI prediction has shown a modest increase in forecast skill (paper in JAMC accepted). Forecaster feedback and further tuning is needed. Objective Tropical Overshooting Top (TOT) Detection Algorithm 6

Additional training given to TAFB during AMS TC Conf., and during an NHC visit this week. Web pages with further details have been developed and made known to NHC/TAFB. Real-time evaluation of GOES-R TOT products during the 2012 Atlantic and EPAC hurricane season: - Utilizes MSG SEVERI IR imagery on systems east of 55W, and GOES IR imagery west of 55W - Will run continuously, with products derived every 15 minutes - Tropical disturbances will be followed and nearby TOTs plotted and graphed over time to produce TOT trend analyses for evaluation - Real-time TOT information will be sent via text files to NHC for N- AWIPS display. Also available via dedicated webpage at UW-CIMSS: 7