Outflow Flight Module Outflow Module Team Jim Doyle, Jon Moskaitis, Peter Black, Leslie Lait, Russ Elsberry, Chris Velden Overall Science Objectives I.Observe.

Slides:



Advertisements
Similar presentations
5-7 March, 2013 #S7-03 Black, Moskaitis, Doyle, Velden, Braun 67 th IHC/ TC Research Forum, NCWCP, College Park, MD A New TC Observing Strategy Peter G.
Advertisements

Robert DeMaria.  Motivation  Objective  Data  Center-Fixing Method  Evaluation Method  Results  Conclusion.
Hurricane center-fixing with the Automated Rotational Center Hurricane Eye Retrieval (ARCHER) method Tony Wimmers, Chris Velden University of Wisconsin.
Shear vector
Rappin et al. (2011) Paper Discussion Patrick Duran 1 of 22 Introduction Asymmetric Env.ConclusionsQuestionsSymmetric Env. The Impact of Outflow Environment.
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
Understanding and Predicting the Impact of Outflow on Tropical Cyclone Intensification and Structure (“TCI-14” & “TCI-15”) An FY14-18 ONR Departmental.
Unit 4 – Atmospheric Processes. Winds… Earth’s atmospheric circulation is an important transfer mechanism for both energy and mass The imbalance between.
Using ensemble data assimilation to investigate the initial condition sensitivity of Western Pacific extratropical transitions Ryan D. Torn University.
Examination of the Dominant Spatial Patterns of the Extratropical Transition of Tropical Cyclones from the 2004 Atlantic and Northwest Pacific Seasons.
USE OF HS3 DATA TO UNDERSTAND THE TROPICAL CYCLONE OUTFLOW LAYER John Molinari, Kristen Corbosiero, Stephanie Stevenson, and Patrick Duran University at.
The Relative Contribution of Atmospheric and Oceanic Uncertainty in TC Intensity Forecasts Ryan D. Torn University at Albany, SUNY World Weather Open Science.
Ryan Spackman (STC/ESRL), Marty Ralph (Scripps), Chris Fairall (ESRL), Allen White (ESRL), Janet Intrieri (ESRL) CalWater 2 Early Start G-IV Flights “AR.
Depression 2/M John R. Jaromahum. Depressions  or 'lows' play an important part in the weather  tending to bring rain and strong winds. Depressions.
WIND.
Sector Search Pattern HEY! I’M OVER HERE !!!. Characteristics: v Used in small search areas v There is a good starting point v Small search objects Sector.
Application of the Computer Vision Hough Transform for Automated Tropical Cyclone Center-Fixing from Satellite Data Mark DeMaria, NOAA/NCEP/NHC Robert.
Chris Birchfield Atmospheric Sciences, Spanish minor.
Tropical Meteorology I Weather Center Event #4 Tropical Meteorology What is Tropical Meteorology? – The study of cyclones that occur in the tropics.
Dr. Scott Braun Principal Investigator. Hurricane Intensity Is Difficult To Predict Intensity prediction is difficult because it depends on weather at.
Improvements in Deterministic and Probabilistic Tropical Cyclone Surface Wind Predictions Joint Hurricane Testbed Project Status Report Mark DeMaria NOAA/NESDIS/ORA,
Chris: From the P3, use AXBTs, take temp and humidities of the sonde profile and deduce SST. 190 sondes from G4 in Feb but no SSTs. For a couple of wind.
Evaluation and Development of Ensemble Prediction System for the Operational HWRF Model Zhan Zhang, V. Tallapragada, R. Tuleya, Q. Liu, Y. Kwon, S. Trahan,
NASA’s Hurricane and Severe Storm Sentinel (HS3): Results from the 2012 Deployment and Plans for 2013 Scott Braun Paul Newman (NASA/GSFC) 3/5/201367th.
A Comparison of Two Microwave Retrieval Schemes in the Vicinity of Tropical Storms Jack Dostalek Cooperative Institute for Research in the Atmosphere,
Benjamin A. Schenkel University at Albany, State University of New York, and Robert E. Hart, The Florida State University 6th Northeast.
Computing Deep-Tropospheric Vertical Wind Shear Analyses for TC Applications: Does the Methodology Matter? Christopher Velden and John Sears Univ. Wisconsin.
Pre-Genesis Monitoring of the 3-D Atmospheric and Oceanic Environment Via High Altitude Aircraft Observations Jeff Hawkins 1, Peter Black 2, Pat Harr 3,
SAL Flight Modules Scott BraunJason Dunion Peter Colarco.
Thoughts on OIB Science Team KCJ. Acquisition Strategies OIB developed 3, basic acquisition strategies February 2011 I. Establish once the bedrock topography.
Rapid Intensification of Hurricane Earl (2010): Vorticity and Mass Flux Budgets 1. Motivation: Various studies have emphasized the importance of different.
Three Lectures on Tropical Cyclones Kerry Emanuel Massachusetts Institute of Technology Spring School on Fluid Mechanics of Environmental Hazards.
Case of June , Dropsonde Jet Lear Jet: (model 35A?) Ceiling: ~ 43,000 Feet (roughly 30 min to 37,000 ft.) Duration: 6 hours; option to refuel.
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
Shuyi S. Chen Joseph Tenerelli Rosenstiel School of Marine and Atmospheric Science University of Miami Effects of Environmental Flow and Initial Vortex.
1 James D. Doyle 1, Hao Jin 2, Clark Amerault 1, and Carolyn Reynolds 1 1 Naval Research Laboratory, Monterey, CA 2 SAIC, Monterey, CA James D. Doyle 1,
SEAC4RS Hurricane Study Brief Description of SEAC4RS Science Objectives of SEAC4RS Hurricane Component How both experiments can benefit Sample flight plans.
HS3 Review and Planning Meeting Scott Braun. Goals of Meeting Review 2012 campaign – Initial science results – Lessons learned Prepare for 2013 campaign.
NASA Ames Research Center, Moffett Field, CA HS3 Science & Deployment Preparation Meeting, 7-9 May, 2013 A New TC Observing Strategy Peter G. Black 1,
1 Aircraft observations of the multiscale structure and evolution of rapidly intensifying tropical cyclones Robert Rogers 1, Paul Reasor 1, Jun Zhang 2,
AMS Annual Meeting - January NRL Global Model Adaptive Observing During TPARC/TCS-08 Carolyn Reynolds Naval Research Laboratory, Monterey, CA OUTLINE:
Adaptive Observation Techniques ENSEMBLE TRANSFORM KALMAN FILTER SINGULAR VECTORS Sensitive areas for adaptive sampling include both the hurricane core.
Spatial Verification Methods for Ensemble Forecasts of Low-Level Rotation in Supercells Patrick S. Skinner 1, Louis J. Wicker 1, Dustan M. Wheatley 1,2,
A Proposed New Strategy for Tropical Cyclone Reconnaissance Based on Western Pacific TCS08 Proof of Concept Peter G. Black (1), Jeffrey D. Hawkins (2)
Sensing Hazards with Operational Unmanned Technology: NOAA's multi-year plan to deploy the NASA Global Hawk aircraft for high impact weather Michael L.
2015 HS3 Science Team Meeting Ames Research Center, Moffett Field, CA.
Doppler Lidar Winds & Tropical Cyclones Frank D. Marks AOML/Hurricane Research Division 7 February 2007.
Ryan Spackman and Chris Fairall 5 November 2014 CalWater 2015 – NOAA P-3.
Science Questions What is role of hot towers in TC intensification and RI? Are they a cause of intensification or an effect? How does wind and temperature.
Benjamin A. Schenkel University at Albany, State University of New York, and Robert E. Hart, The Florida State University 4 th.
Dynamics and predictability of the rapid intensification of Hurricane Edouard (2014) Erin Munsell Summer 2015 Group Meeting August 17 th, 2015.
The Tropical Transition of Cyclones: Science Issues and Critical Observations or TC Genesis: A Global Problem Chris Davis (NCAR) Collaborators: Lance Bosart.
T-PARC/TCS-08 Quicklook 29 October Operations by the numbers… 9 participating nations –Canada, China, England, France, Germany, Japan, South Korea,
Satellite + Aircraft Tropical Cyclone Surface Wind Analysis Joint Hurricane Testbed.
An Analysis of the Tropical Cyclone Cirrus Canopy Using HS3 and TCI Observations Patrick Duran and John Molinari University at Albany, SUNY 32 nd Conference.
Shuyi S. Chen, Robert A. Houze Bradley Smull, David Nolan, Wen-Chau Lee Frank Marks, and Robert Rogers Observational and Modeling Study of Hurricane Rainbands.
Andrea Schumacher1, M. DeMaria2, and R. DeMaria1
Predictability and forecast evaluation of ensemble simulations of long-lived Hurricane Nadine (2012)
Evolution of Hurricane Isabel’s (2003) Vortex Structure and Intensity
Rosenstial School of Marine and Atmospheric Science
Derek Ortt1 and Shuyi S. Chen, RSMAS/University of Miami
Jianyu Liang (York U.) Yongsheng Chen (York U.) Zhiquan Liu (NCAR)
NOAA P-3 Status for BAMEX
More on tropical cyclones
An Analysis of Large Track Error North Atlantic Tropical Cyclones.
Line and Character Attributes 2-D Transformation
Tropical Cyclone Structure-2008 (TCS-08) ONR/NRL Funded Projects
Science Objectives contained in three categories
Status Report of T-PARC/TCS-08
(NRL Base-funded project)
Presentation transcript:

Outflow Flight Module Outflow Module Team Jim Doyle, Jon Moskaitis, Peter Black, Leslie Lait, Russ Elsberry, Chris Velden Overall Science Objectives I.Observe and document the tropical cyclone (TC) outflow layer structure (e.g., depth, lateral and vertical shear, stability etc.), evolution, and its interaction with inner core convection and the environment. II.Deploy dropsondes in sensitive regions (including the outflow jet) and assess the impact on TC prediction. Under what conditions would you fly the module?  Storms with outflow and that are accessible for the GH.  Generalized modules have been formulated for small and large storms, and for storms that are interacting with troughs. Under what conditions would you not fly? What are the guidelines?  Weak storms or storms in formation that have poorly defined outflow.  TCs that require long ferries and on-station time is thus limited

Outflow Flight Module How would you de-scope the plan if the system is at long range or some other factor(s) limits on-station time?  One module could be performed (instead of repeated module)  Partial lawnmower or linear segment could be performed Dropsonde plan  Higher frequency sondes across regions of interest such as jet cores or the outflow edge.  Deploy dropsondes every 1-2 degrees.  Deploy dropsondes near way points where possible  Deploy dropsondes in sensitive regions (including the outflow jet) as diagnosed from ensemble or adjoint targeting products. Modules designed to be repeated twice during a flight 1.Lawnmower -Double lawnmower pattern (for 2 outflow jets) with core transect -Polar coordinate pattern 2.Square Spiral 3.Linear Repeat (Time Evolution- Hovmöller) for fast-moving TC

Outflow Flight Module Design Strategy I.Three basic pattern types 1.Lawnmower 2.Square spiral 3.Linear Repeat (Time Evolution- Hovmöller) II.Four Basic Orientations 1.Fixed (square) 2.Stretched (rectangular) 3.Rotated (along-feature) 4.Distorted (trapezoidal) III.Three Outflow Regions 1.Poleward Outflow Jet (POJ) 2.Storm-Centric Outflow (SCO) 3.Equatorward Outflow Jet (EOJ) IV.Three Coordinate Reference Systems 1.Earth-Relative 2.Storm-Relative 3.Feature-Relative V.Three Flight Module Strategies (standard size) 1.Fly POJ, SCO and EOJ modules twice 2.Fly POJ and SCO once each 3.Fly SCO and EOJ once each

Outflow Dropsonde Deployment Strategy Flight Times  Center pattern on T 0 = 1200 GMT  Block-Out (T.O.-30 min) T1= 0000 GMT  Block-In (Landing+30 min) T2= 2400 GMT  Center pattern on T 0 = 0000 GMT  Block-Out (T.O.-30 min) T1= 1200 GMT, day 1  Block-In (Landing+30 min) T2= 1200 GMT, day 2 Sonde Spacing/ number of sondes/leg along and across track/ total sondes  Small: o lat (30-60 nm, km)/ e.g.  Standard o lat ( nm, km)/ e.g.6x5  Large o lat ( nm, km) Input Parameters  Storm initial location (lat, lon); forecast speed and direction of motion  Feature speed and direction of motion  Initial Point, IP (radius, azimuth from initial storm location)  Initial heading

Module 1: Lawnmower pattern: Maria (2011) example Flight legs 2º apart, and 30 drops in 2ºx2º grid in this example Repeat pattern and fly home or move on to another objective Black dot: Best-track position Blue line: Flight track Blue dots: Dropsondes

Module 1: Lawnmower pattern: Maria (2011) example Flight legs 2º apart, and 30 drops in 2ºx2º grid in this example Repeat pattern and fly home or move on to another objective Black dot: Best-track position Blue line: Flight track Blue dots: Dropsondes A Options: Rotate, Stretch/ Compress Fixed, storm or feature relative A- go home: 30 sondes B- Repeat: 60 sondes C- Fly another feature: 60 sondes

Module 1: Lawnmower pattern: Maria (2011) example Flight legs 2º apart, and 30 drops in 2ºx2º grid in this example Repeat pattern and fly home or move on to another objective Black dot: Best-track position Blue line: Flight track Blue dots: Dropsondes A B Options: Rotate, Stretch/ Compress Fixed, storm or feature relative A- go home: 30 sondes B- Repeat: 60 sondes (option: ferry to start pt. over outflow core) C- Fly another feature: 60 sondes

Module 1: Lawnmower pattern: Maria (2011) example Flight legs 2º apart, and 30 drops in 2ºx2º grid in this example Repeat pattern and fly home or move on to another objective Black dot: Best-track position Blue line: Flight track Blue dots: Dropsondes A B C Options: Rotate, Stretch/ Compress Fixed, storm or feature relative A- go home: 30 sondes B- Repeat: 60 sondes C- Fly another feature: 60 sondes

Module 1: Lawnmower variant – Polar Coordinate Transform: Earl (2010) Black dot: Best-track position Blue line: Flight track Blue dots: Dropsondes Radial legs are evenly spaced in azimuth and 30 drops in this example Re-center pattern and fly again before returning home Ferry flight segment over land is for illustrative purposes only. Not feasible during experiment.

Black dot: Best-track position Blue line: Flight track Blue dots: Dropsondes Module 1: Lawnmower Variant Igor (2010) example 75 drops in this example

Module 2: Square spiral pattern: Maria (2011) example Flight legs 2º apart, and 30 drops in 2ºx2º grid in this example Repeat pattern and fly home or move on to another objective

Module 2: Square spiral pattern: Maria (2011) example Flight legs 2º apart, and 30 drops in 2ºx2º grid in this example Repeat pattern and fly home or move on to another objective Black dot: Best-track position Blue line: Flight track Blue dots: Dropsondes Options: Rotate, Stretch/ Compress Fixed, storm or feature relative A- go home: 30 sondes B- Repeat: 60 sondes C- Fly another feature: 60 sondes A

Module 2: Square spiral pattern: Maria (2011) example Flight legs 2º apart, and 30 drops in 2ºx2º grid in this example Repeat pattern and fly home or move on to another objective Black dot: Best-track position Blue line: Flight track Blue dots: Dropsondes Options: Rotate, Stretch/ Compress Fixed, storm or feature relative A- go home: 30 sondes B- Repeat: 60 sondes C- Fly another feature: 60 sondes A B

Module 2: Square spiral pattern: Maria (2011) example Flight legs 2º apart, and 30 drops in 2ºx2º grid in this example Repeat pattern and fly home or move on to another objective Black dot: Best-track position Blue line: Flight track Blue dots: Dropsondes Options: Rotate, Stretch/ Compress Fixed, storm or feature relative A- go home: 30 sondes B- Repeat: 60 sondes C- Fly another feature: 60 sondes A B C

Black dot: Best-track position Blue line: Flight track Blue dots: Dropsondes Module 3: Linear Repeat: Danielle (2010) example Ferry to 35ºN and travel back and forth as many times as desired, while storm translates rapidly northeast Combine with extratropical transition objective Time Evolution- Hovmöller