Probabilistic Hurricane Storm Surge (P-Surge) Arthur Taylor MDL / OST December 4, 2006.

Slides:



Advertisements
Similar presentations
Probabilistic Guidance for Hurricane Storm Surge (P-surge) Arthur Taylor and Bob Glahn Meteorological Development Laboratory, National Weather Service.
Advertisements

Research Lead  The University of North Carolina at Chapel Hill CHC-R 5 th Annual Meeting January 31-February 1, 2013 Coastal Wave – Surge Modeling R.
1 End-User Evaluation of the NC-CERA Storm Surge Visualization Tool Jessica Losego Institute for the Environment University of North Carolina at Chapel.
Andrea Schumacher, CIRA/CSU Mark DeMaria, NOAA/NESDIS/StAR Dan Brown and Ed Rappaport, NHC.
National Weather Service SLOSH S ea, L ake, and L ake, and O verland O verland S urges from S urges from H urricanes H urricanes Part 1: W. Shaffer / MDL.
WRC HURRICANE DAMAGE POTENTIAL SCALE GULF OF MEXICO HURRICANES PAST – PRESENT – FUTURE MMS ITM January 6, 2009 Jill F. Hasling, President Certified Consulting.
The Storm Surge Toolkit Jamie Rhome Storm Surge Specialist/Team Lead National Hurricane Center Jamie Rhome Storm Surge Specialist/Team Lead National Hurricane.
Motivation The Carolinas has had a tremendous residential and commercial investment in coastal areas during the past 10 years. However rapid development.
CHAPTER 5: PREDICTING STORM SURGE LESSONS FROM HURRICANE IKE.
Applications of Ensemble Tropical Cyclone Products to National Hurricane Center Forecasts and Warnings Mark DeMaria, NOAA/NESDIS/STAR, Ft. Collins, CO.
Details for Today: DATE:3 rd February 2005 BY:Mark Cresswell FOLLOWED BY:Assignment 2 briefing Evaluation of Model Performance 69EG3137 – Impacts & Models.
NOAA’s National Weather Service: Probabilistic Storm Surge (P-Surge) Arthur Taylor, Nicole P. Kurkowski MDL / OST July 26, 2006.
Validation of the Ensemble Tropical Rainfall Potential (eTRaP) for Landfalling Tropical Cyclones Elizabeth E. Ebert Centre for Australian Weather and Climate.
Session 10: Hurricane Storm Surge Modeling and Analysis 1 Hurricane Storm Surge Modeling.
Storm Surge Products John Cole Warning Coordination Meteorologist NWS Morehead City/Newport NC Acknowledgements: Jamie Rhome and Rick Knabb (NHC), Mark.
HFIP Ensemble Products Subgroup Sept 2, 2011 Conference Call 1.
Chapter 12 - Forecasting Forecasting is important in the business decision-making process in which a current choice or decision has future implications:
T T18-05 Trend Adjusted Exponential Smoothing Forecast Purpose Allows the analyst to create and analyze the "Trend Adjusted Exponential Smoothing"
WHY IKE A CATEGORY 2 HURRICANE WAS SO DEVASTATING THE FREEMAN HURRICANE DAMAGE POTENTIAL SCALE 2011 Hurricane Outlook Jill F. Hasling, President Certified.
Research Lead  The University of North Carolina at Chapel Hill CHC-R 5 th Annual Meeting January 31-February 1, 2013 AdcircLite-NC: Rapid evaluation of.
Mesoscale & Microscale Meteorological Division / ESSL / NCAR WRF (near) Real-Time High-Resolution Forecast Using Bluesky Wei Wang May 19, 2005 CISL User.
Surge Height (NAWIPS) 5.4 feet Impact (Inundation) 4 feet TWL – (MHHW – MSL) 8 – (4-0)=4.
National Weather Service – Newport/Morehead City NC NHC/WFO Tropical Products…and What’s New for 2012 WFO Newport Hurricane Awareness Seminar July 17,
Chapter 9: Weather Forecasting
Advanced Applications of the Monte Carlo Wind Probability Model: A Year 2 Joint Hurricane Testbed Project Update Mark DeMaria 1, Robert DeMaria 2, Andrea.
A. Schumacher, CIRA/Colorado State University NHC Points of Contact: M. DeMaria, D. Brown, M. Brennan, R. Berg, C. Ogden, C. Mattocks, and C. Landsea Joint.
Using Partnerships to Meet NOAA’s Needs for its Next Generation Storm Surge System NOS/OCS/CSDL J. Feyen F. Aikman M. Erickson NWS/NCEP/EMC H. Tolman NWS/OST/MDL.
Deputy Assistant Administrator Mitigation Directorate Michael Buckley FEMA’s Utilization of Tropical Forecasts and Products.
Improved Statistical Intensity Forecast Models: A Joint Hurricane Testbed Project Update Mark DeMaria, NOAA/NESDIS, Fort Collins, CO John A. Knaff, CIRA/CSU,
Update on Storm Surge at NCEP Dr. Rick Knabb, Director, National Hurricane Center and representing numerous partners 21 January 2014.
Mark DeMaria, NOAA/NESDIS/StAR Andrea Schumacher, CIRA/CSU Dan Brown and Ed Rappaport, NHC HFIP Workshop, 4-8 May 2009.
Improvements in Deterministic and Probabilistic Tropical Cyclone Surface Wind Predictions Joint Hurricane Testbed Project Status Report Mark DeMaria NOAA/NESDIS/ORA,
Office of Coast Survey NOAA’s Storm Surge Modeling Capabilities Jesse C. Feyen Storm Surge Roadmap Portfolio Manager.
Guidance on Intensity Guidance Kieran Bhatia, David Nolan, Mark DeMaria, Andrea Schumacher IHC Presentation This project is supported by the.
Continued Development of Tropical Cyclone Wind Probability Products John A. Knaff – Presenting CIRA/Colorado State University and Mark DeMaria NOAA/NESDIS.
Pablo Santos WFO Miami, FL Mark DeMaria NOAA/NESDIS David Sharp WFO Melbourne, FL rd IHC St Petersburg, FL PS/DS “HURRICANE CONDITIONS EXPECTED.”
Large Ensemble Tropical Cyclone Forecasting K. Emanuel 1 and Ross N. Hoffman 2, S. Hopsch 2, D. Gombos 2, and T. Nehrkorn 2 1 Massachusetts Institute of.
NOAA’s National Weather Service: Probabilistic Storm Surge (P-Surge) Arthur Taylor, Bob Glahn, Wilson Shaffer MDL / OST November 30, 2005.
An Improved Wind Probability Program: A Year 2 Joint Hurricane Testbed Project Update Mark DeMaria and John Knaff, NOAA/NESDIS, Fort Collins, CO Stan Kidder,
An Improved Wind Probability Program: A Joint Hurricane Testbed Project Update Mark DeMaria and John Knaff, NOAA/NESDIS, Fort Collins, CO Stan Kidder,
Development of a Baseline Tropical Cyclone Model Using the Alopex Algorithm Robert DeMaria.
Storm Surge Modeling and Forecasting LTJG Jeffrey Pereira, NOAA Storm Surge Unit National Hurricane Center NOAA Storm Surge Workshop May 2011 LTJG Jeffrey.
NHC Activities, Plans, and Needs HFIP Diagnostics Workshop August 10, 2012 NHC Team: David Zelinsky, James Franklin, Wallace Hogsett, Ed Rappaport, Richard.
Caribbean Disaster Mitigation Project Caribbean Institute for Meteorology and Hydrology Tropical Cyclones Characteristics and Forecasting Horace H. P.
Page 1© Crown copyright 2006 Matt Huddleston With thanks to: Frederic Vitart (ECMWF), Ruth McDonald & Met Office Seasonal forecasting team 14 th March.
Hurricane Irene August 2011 Hurricane Irene August 2011 NOAA Service Assessment Frank Marks and Wes Browning (Co-team leads) November 27, 2012.
Probabilistic Hurricane Storm Surge (P-Surge) Arthur Taylor Meteorological Development Laboratory, National Weather Service January 20, 2008.
Development of Probabilistic Forecast Guidance at CIRA Andrea Schumacher (CIRA) Mark DeMaria and John Knaff (NOAA/NESDIS/ORA) Workshop on AWIPS Tools for.
Caribbean Disaster Mitigation Project Caribbean Institute for Meteorology and Hydrology Storm Surge Atlases Presentation, description, data Horace H. P.
Analysis of Cloud-to-Ground Lightning Within 16 Landfalling Hurricanes Danielle Nagele.
© 2006 Accurate Environmental Forecasting Climate Effects on Hurricane Frequency and Severity Dail Rowe, PhD Accurate Environmental Forecating.
NOAA/NWS Digital Services 1 NWS Forecast Evolution and Delivery in a Digital Era Glenn Austin Office of Climate, Water, and Weather Services David Ruth.
1 Vision for Marine and Coastal Services Digital Products Jamie Vavra Marine and Coastal Weather Services Branch Office of Climate, Water and Weather Services.
FREEMAN HURRICANE DAMAGE POTENTIAL SCALE GULF OF MEXICO HURRICANES PAST – PRESENT – FUTURE PUG 2009 February 2009 Jill F. Hasling, President Ben Maloney.
Improved Statistical Intensity Forecast Models: A Joint Hurricane Testbed Year 2 Project Update Mark DeMaria, NOAA/NESDIS, Fort Collins, CO John A. Knaff,
NOAA Data & Catastrophe Modeling Prepared by Steve Bowen of Impact Forecasting September 16, 2015.
Enrica Bellone, Jessica Turner, Alessandro Bonazzi 2 nd IBTrACS Workshop.
Andrea Schumacher, CIRA/CSU Mark DeMaria and John Knaff, NOAA/NESDIS/StAR.
Maritza De La Luz. Category One: Winds from 119 to 153 km (74 to 95 mi.) per hour. No damage to building structures. Some damage to construction signs.
Improving the Validation and Prediction of Tropical Cyclone Rainfall Robert Rogers NOAA/AOML/HRD Tim Marchok NOAA/GFDL Bob Tuleya NCEP/EMC/SAIC Funded.
Figures from “The ECMWF Ensemble Prediction System”
Extra-Tropical Storm Surge (ETSS 2.0) Pre-Implementation Briefing College Park, MD May 14, 2015 Arthur Taylor, Huiqing Liu and Ryan Schuster MDL/NWS/NOAA.
Cliquez pour modifier le style du titre Cliquez pour modifier le style des sous-titres du masque 1 Storm surge modeling at RSMC La Réunion 6th session.
Coastal Emergency Risks Assessment (CERA)
Storm Surge Forecasting Practices, Tools for Emergency Managers, A Probabilistic Storm Surge Model Based on Ensembles and Past Error Distributions.
2016 Hurricane Season National Weather Service
Discussion topics (examples):
Storm Surge Modeling and Forecasting
Storm Surge Definitions:
Verification of Tropical Cyclone Forecasts
Presentation transcript:

Probabilistic Hurricane Storm Surge (P-Surge) Arthur Taylor MDL / OST December 4, 2006

Probabilistic Storm Surge 2006 Introduction NHC begins operational SLOSH runs 24 hours before landfall. Provides a storm surge estimate for non-evacuation applications.Provides a storm surge estimate for non-evacuation applications. Problem: Surges are based on a single NHC forecast track and associated parameters. When provided accurate input, SLOSH results are within 20% of high water marks.When provided accurate input, SLOSH results are within 20% of high water marks. Track and intensity prediction errors are the largest cause of errors in SLOSH surge forecasts and can overwhelm the SLOSH results.Track and intensity prediction errors are the largest cause of errors in SLOSH surge forecasts and can overwhelm the SLOSH results.

Probabilistic Storm Surge 2006 Probabilistic Storm Surge Methodology Create an ensemble of SLOSH runs based on NHC’s official advisory and historic forecast errors. Creates a probability of storm surge for this one forecast of this particular threatening hurricane. Not to be confused with FEMA’s 100-year surge levels.Creates a probability of storm surge for this one forecast of this particular threatening hurricane. Not to be confused with FEMA’s 100-year surge levels. Which hurricane forecast errors most impact storm surge? Cross track error (impacts landfall location)Cross track error (impacts landfall location) Along track error (impacts the timing of the storm)Along track error (impacts the timing of the storm) Intensity errorsIntensity errors Structure of the storm errorsStructure of the storm errors

Probabilistic Storm Surge 2006 SLOSH’s Input Track Location Can get from NHC’s advisoryCan get from NHC’s advisory Forward Speed Can compute from NHC’s advisoryCan compute from NHC’s advisory Radius of Maximum Winds (Rmax) Not given in NHC’s advisory due to lack of skill in forecasting changes in RmaxNot given in NHC’s advisory due to lack of skill in forecasting changes in RmaxPressure Can only get the current value (no forecast values) from NHC’s advisoryCan only get the current value (no forecast values) from NHC’s advisory

Probabilistic Storm Surge 2006 SLOSH’s Rmax and Pressure Since NHC’s advisory does not provide Rmax, or forecast Pressure, we need to compute them. The SLOSH parametric wind model relates Rmax, Pressure, and Maximum Wind Speed (Vmax). Given any two, the third can be computed.The SLOSH parametric wind model relates Rmax, Pressure, and Maximum Wind Speed (Vmax). Given any two, the third can be computed. Vmax is provided in NHC’s advisory.Vmax is provided in NHC’s advisory. Since the current Pressure is provided, one can estimate the current Rmax.Since the current Pressure is provided, one can estimate the current Rmax. We assume that Rmax remains constant, then calculate the resulting Pressures.We assume that Rmax remains constant, then calculate the resulting Pressures.

Probabilistic Storm Surge 2006 Example: Katrina Advisory 23

Probabilistic Storm Surge 2006 Varying Katrina’s Tracks The NHC’s cone of error is 50% of possible cross track error. The NHC’s cone of error is 50% of possible cross track error. We include 90% of possible cross track error (roughly 3 times the size of the cone of error). We include 90% of possible cross track error (roughly 3 times the size of the cone of error). Spacing based on size of the storm Spacing based on size of the storm

Probabilistic Storm Surge 2006 Varying the Other Parameters: Size: Small (30%), Medium (40%), Large (30%) Forward Speed: Fast (30%), Medium (40%), Slow (30%) Intensity: Strong (30%), Medium (40%), Weak (30%)

Probabilistic Storm Surge 2006 Determine Which Basins to Run We try all SLOSH input tracks in all operational basins: For each basin, eliminate tracks which never forecast tropical storm force winds.For each basin, eliminate tracks which never forecast tropical storm force winds. Remove basins where all the tracks were eliminated.Remove basins where all the tracks were eliminated. Treat eliminated tracks as if they generated no surge in a basin.Treat eliminated tracks as if they generated no surge in a basin.

Probabilistic Storm Surge 2006 Calculate probability of exceeding X feet Look at each cell in each SLOSH run. If the surge exceeds X, add the weight associated with that SLOSH run to the total.If the surge exceeds X, add the weight associated with that SLOSH run to the total. The weight of a run is: cross track weight * along track weight * intensity weight * size weightThe weight of a run is: cross track weight * along track weight * intensity weight * size weight The total weight is the probability of exceeding X feet.The total weight is the probability of exceeding X feet.

Probabilistic Storm Surge 2006 Katrina Adv 23: Probability > 5 feet of storm surge

Probabilistic Storm Surge 2006 Calculate height exceeded by X percent of ensemble storms. Determine the exceedance surge height, for each cell, so that only X percent of the ensemble surges exceed it. For each cell, sort the heights of each ensemble SLOSH run.For each cell, sort the heights of each ensemble SLOSH run. Starting from the tallest height, sum the weights until the sum is equal to the given percentage, X.Starting from the tallest height, sum the weights until the sum is equal to the given percentage, X. The height associated with the last weight added is the exceedance height for that cell.The height associated with the last weight added is the exceedance height for that cell.

Probabilistic Storm Surge 2006 Katrina Adv 23: 10% of the ensemble storms exceed this height

Probabilistic Storm Surge 2006 Where can you access our product? When is it available? Beginning with the first NHC advisory forecasting landfall of a hurricane in 24 hours.Beginning with the first NHC advisory forecasting landfall of a hurricane in 24 hours. Available approx. 1-2 hours after the advisory release time.Available approx. 1-2 hours after the advisory release time.

Probabilistic Storm Surge 2006 Customer Feedback What is your affiliation? From: To: Total Number of Responses: 126

Probabilistic Storm Surge 2006 Customer Feedback Scores What is the perceived technical quality of the storm surge graphics? How easy are the storm surge graphics to interpret and use?

Probabilistic Storm Surge 2006 Customer Feedback Comments “ Excellent product should save lives. ” “ Nice product. Easy to read. ” “ Storm surge is the one area that local forecasters either rarely mention or speak in such generalities that the information is useless. This tool is greatly appreciated by those on us living in the coastal high hazard area. ” “ I need to know what my risk of storm surge is where I live - this graphical representation brings an important level of visual realization to this dangerous situation. ” “ Extend the product out to 48 hours prior to landfall instead of 24 hours. ” “ You only give two ranges of storm surge … 10% and > 5 feet. Add additional thresholds to the graphics. ” “ Needs ability to zoom in closer to effected areas. ” “ Hard to understand the 10 % exceedance graphic. ”

Probabilistic Storm Surge 2006 Is it statistically Reliable? If we forecast 20% chance of exceeding 5 feet, does it actually exceed 5 feet 20% of the time? Step 1: Create forecasts for various projections and thresholds for the following storms: Bonnie98, Bret99, Charley04, Claudette03, Dennis05, Earl98, Floyd99, Frances04, Georges98, Gaston04, Isabel03, Ivan04, Jeanne04, Katrina05, Lili02, Wilma05Step 1: Create forecasts for various projections and thresholds for the following storms: Bonnie98, Bret99, Charley04, Claudette03, Dennis05, Earl98, Floyd99, Frances04, Georges98, Gaston04, Isabel03, Ivan04, Jeanne04, Katrina05, Lili02, Wilma05 Step 2: Get a matching analysis of storm surge.Step 2: Get a matching analysis of storm surge. Step 3: In each grid cell when we forecast 15-25% probability of exceeding 5 feet, calculate the observed relative frequency. Repeat for other probability groups, threshold values, and forecast projections.Step 3: In each grid cell when we forecast 15-25% probability of exceeding 5 feet, calculate the observed relative frequency. Repeat for other probability groups, threshold values, and forecast projections.

>2 ft Forecasts 12hr 48hr36hr 24hr

>5 ft Forecasts 12hr 48hr36hr 24hr

>7 ft Forecasts 12hr 48hr36hr 24hr

Probabilistic Storm Surge 2006 Current Development We were “experimental” in 2006, and plan on becoming “operational” in 2007.We were “experimental” in 2006, and plan on becoming “operational” in We are investigating other methods of verifying the forecasts.We are investigating other methods of verifying the forecasts. We are working on adding the data to the NDGD (National Digital Guidance Database).We are working on adding the data to the NDGD (National Digital Guidance Database). We are working on delivering the data to AWIPS.We are working on delivering the data to AWIPS. We are developing more training material.We are developing more training material. Based on the feedback from 2006, we plan to add more “zoom” capability.Based on the feedback from 2006, we plan to add more “zoom” capability.

Probabilistic Storm Surge 2006 Future Development We would like to include probability over a time range, both incremental and cumulative.We would like to include probability over a time range, both incremental and cumulative. We would like to allow interaction with the data in a manner similar to the SLOSH Display program.We would like to allow interaction with the data in a manner similar to the SLOSH Display program. We would like to investigate its applicability to Tropical storms.We would like to investigate its applicability to Tropical storms.