Dr. Phillip Bothwell Storm Prediction Center October 1, 2007NOAA SAB - Fire Weather Research Working Group Experimental Probabilistic Forecasts of Lightning and Dry Thunderstorms

SPC Fire Weather Program and Activities Day 1, 2, and Day Fire Weather Outlooks SPC recognized as a center of expertise in convection The initial problem-(1997)…forecast dry thunderstorms (0.10 inch precipitation or less)

SPC Fire Weather Outlooks – Began June 1998 (nearly 10 years forecasting experience)! June 2007 now through day 8!

SPC Fire Weather Outlook Categories  Critical Fire Weather Areas  Extremely Critical Fire Weather Areas Areas are for anonymously high wind/low humidity events with dry vegetation  Dry Thunderstorm Areas For thunderstorms with 0.10 inch or less

Wildfires continue to increase in number. The costs are staggering! Fire suppression costs for the USDA Forest Service and the Department of Interior have exceeded $1 billion every year since In two of those years, costs exceeded $2 billion. In 2007, the Forest Service will spend 45% of its budget on wildland fire suppression compared to 13% in Source: National Association of State Foresters Issue Paper (April 2007)

Importance of Lightning Forecasts Wildfires are either lightning or human caused!  Those started by lightning account for more than 50 percent of all total acreage burned each year  The Goal: Fight wildfires in the earliest stages Fire growth can be mitigated and smoke management/air quality can be improved by more accurate lightning forecasts - leading to better advance placement of resources (men and machinery)

12 The effect of storms that produce only one flash is different from those that have large numbers of flashes! (i.e., severe lightning storms*). At the SPC in 2006, probabilities were produced for 1 or more and 100 or more CG flashes for the Western U.S. WFOs and U.S. Forest Service New for 2007 : Guidance is provided to Raleigh NC WFO for both 1 and 100 or more CG for their summer experiment for predicting significant lightning in their Hazardous Weather Outlook product *Currently there is no definition of “severe lightning storm”

Lightning caused fires* - NOT just problem for the West! *

* Source: National Interagency Coordination Center (lightning and human caused fires and acres began in 2001) Nation-wide: 2001 to 2006 average Lightning started wildfires are responsible for around 17% of all wildfires (from 12.5 to 20%) Yet, lightning started wildfires responsible for 64% of total acres burned (from 51 to 86%). Lightning started wildfires in Alaska 2004 were responsible for 80% of total acres burned. Florida-3% of the fires are lightning starts (on avg). In 2001, lightning started fires burned 10 times more acres than human started fires

Geographic Area Coordination Centers and Regions Lightning Started Wildfires are NOT just limited to the West!

Alaska

2004 lightning flashes Alaska (Understanding the nature/size of the Problem) SPC to begin testing Alaska PPF Lightning Forecasts summer 2008 Yellow-CG flashes Interior of Alaska

“Lightning can spark a wildfire-anywhere in the U.S. Differences in West vs East” “A Dry Thunderstorm ( or less) occurs: 1)where the rainfall is the lightest, 2)falling through the driest air, 3) from the highest cloud bases…and… 4) for the shortest period of time”

Similarities and Differences (wet vs. dry) 1)where the rainfall is the lightest, 2) for the shortest period of time 3)Lightning outside the main rain shaft/heavy precipitation 4)On-going drought, dry and/or dead vegetation 5)Different fuel types from those in the West Fuels burn even when green! 6) Often more lightning CG flashes in eastern U.S. Storms “Lightning can spark a wildfire-anywhere in the U.S. Differences in West vs East”

Project Objectives (starting in 1997):  Forecast lightning across the United States.  Better understanding of dry thunderstorms.  Better understanding of storms that produce large numbers of CG flashes.

Lightning Prediction Method:  Perfect Prog(nosis) Forecast (PPF) Technique  Use LTG Climatology as predictors  Principal Component Analysis  Logistic regression  40 km grid resolution at 3 hour forecast intervals

Lightning Prediction Method (Continued): Results – Forecasts across U.S. (to 87 hours) for:  Probability of 1 or more CG flashes using NAM (NCEP North American Meso model) as input  Probability of 100 (or any number) or more CG flashes (Prediction of significant LTG)

LTG CLIMO: Probability of 1 or more CG flashes / 40x40 km grid box / 3 hrs. Centered on July UTC (early morning)15-18UTC UTC (mid day)21-00UTC

LTG CLIMO: Probability of 100 or more CG flashes / 40x40 km grid box / 3 hrs. Centered on July 12 (2100 to 0000 UTC) Probability of 100 or more is lower (11% or less) For Western US-primarily SW monsoon related! Forecasts need to be compared to “climatology” of the event! Intense areas of CG lightning can often be associated with strong to severe storms (and/or flooding). 14

Perfect Prog Forecast (PPF) Grid Points Each point is 40 x 40 km

Now, let’s briefly look at some characteristics of Dry Thunderstorms (OU-SPC Joint Research Project - from Lengyel 2003)….

The Project used a combination of: 1)cloud base height (MLCH) 2) sub-cloud humidity (ASRH), and a “new term” 3) precipitation duration (P24D) A new parameter* was defined as FTPI (Fuquay dry Thunderstorm Potential Index). * Similar to finding by Fuquay (1962). Known NOT well known-in advance

2003 Pilot Project- A Dry Thunderstorm Potential Index-FTPI (following Fuquay’s initial work – NOT on a scale from 0 to 100) Approximately 75% dry storms above dashed line and nearly 75 % wet storms below dashed line “DRY”“Transition”“WET >”

Simplifying, since we don’t know the hours of precipitation in advance (P24D), we have the modified index or Dry Thunderstorm Potential Index (DTPI). “*2006- Dry Thunderstorm Potential Index ( DTPI )” – Designed to range from 0 -> 100 (wet-> dry) Example: (Cloud Base of 10,000 ft AGL * (100-30% sub cloud humidity) )/10,000 = DTPI of 70

First – Let’s take a look at an example from 2006

Mike Vescio (MIC PDT) “Your guidance is pegging our area for a big event on Monday. Let’s see how it verifies.” 24 hr Day 3 fcst 12 to 12 UTC Aug 21-22, 2006 Now, an example of a Day 3 Forecast for Aug. 21, Ltg climo < 5% and forecast of around 10 % DTPI at 100

Columbia Complex (Washington state) wildfire  On 8/21/06, lightning caused fire began in Columbia County WA.  7 residences and 8 other buildings destroyed, 31 buildings damaged  Final total was 109,422 acres and a reported cost of $35,400,000 for this lightning started wildfire complex.

Now – Let’s take a look at 2007

Sunday, June 3, 2007 (Forecast and verification) Day 4 forecast 12 to 03 UTC * (DTPI Hatched at 50,75,100) Day 1 forecast 15 * to 12 UTC and #CG lightning per 40 km grid box Approximately 10 lightning “starts” reported in this area. *12 UTC NAM (input data) goes through 03 UTC (partial Day 4) and Day 1 NAM cycle starts at 15 UTC

Observed Dry Thunderstorm Potential Index (DTPI) and 24 hour lightning plus reported precipitation UTC 6/3-6/4/07

South Florida “BICY Fire complex” ignited by lightning May 4, 2007 – 64,000 acres A special look at the lightning ignited wildfires across Florida and Georgia in early May 2007 (sector was not routinely available)

Forecast of significant lightning (100 or more CG flashes) and 40 km boxes reporting 100 or more CG for May BICY Fire complex- ignited by lightning May Ltg Climatology is < 3%

Milford Flats July 6, 2007 Largest wildfire in Utah history (50 x 20miles) Forecasts and CG lightning flashes (per 40 km grid)

Southern California Sept (forecast and lightning) Small wildfire start-(Butler fire)

In 2007-The SPC provided on the Web site (*.gov domains) SPC provided Day 1, 2, 3 and (partial) Day 4 NAM based automated probabilistic lightning forecast guidance at 40 km resolution The guidance was updated with each NAM model run every 6 hours included probabilities of  1 or more and  100 or more CG lightning flashes  Dry Thunderstorm Potential Index  Lightning verification plots available the next day  The web displays had three domains: NW US, SW US and EC US (E ast Central US- Raleigh NC Sig. lightning experiment )

2007 Lightning Forecasts Forecasts for 3 regions (two for Dry thunderstorms…one for excessive Lightning events). Available to Forest Service/NWS offices and Incident Meteorologists through Sept Data Archive (daily including verification)

The Future - Predicting Lightning Risk Nationwide-including Alaska A Fully Funded multi-year Joint Fire Sciences Proposal June 2007-Dec Miriam Rorig, Brian E. Potter, Robert Solomon USDA Forest Service, Pacific Wildland Fire Sciences Lab Phillip Bothwell NOAA, NOAA/NWS Storm Prediction Center

Joint Fire Sciences Program Proposal. Lightning Climatology for Alaska development of improved dry lightning algorithms to expand their coverage, and improve accuracy and usability of such predictions in fire management. dry thunderstorm predictions at high spatial resolutions (including Alaska) applying the newly developed algorithms to the latest operational weather forecast model

Two new sources of data 32 km North American Regional Reanalysis (NARR) data covering Alaska – to develop equations (3 hourly data from present back as far as 1979) In 2009, we will also have a Rapid Refresh model at high resolution covering Alaska available to use with Perfect Prog equations.

North American Regional Reanalysis (NARR) Proposed Alaska Domain

Current RUC CONUS domain RUC Rapid Refresh (2009) Continental situational awareness model Hourly NWP Update for: - CONUS - AK/Can - Pac/Atl - Caribbean Planned approx Rapid Refresh domain

Success with display ingesting and display Lightning over Alaska on SPC workstations. Contours of CG flashes on new 45 km grid for Alaska-21 to 00 UTC July 2007 (Contours-1-red, 3-green, 10-blue, 30-gold, 100-cyan, 300 (or more)-magenta)

Research -> Operations: Automated Lightning Forecasts through Day 4 on Web Forecasts produced for 1 or more CG flashes and 100 or more CG flashes for each NAM cycle Forecast Cloud base and sub-cloud humidity combined in a single (conditional) parameter Dry Thunderstorm Potential Index (DTPI) to highlight areas of potential dry thunderstorms. 40 km lightning verification (qualitative verification on line) Forecasters able to provide feedback from the Web page. Web page contained on line tutorials about the products and their development

Co-location of the Storm Prediction Center with University of Oklahoma, National Severe Storms Laboratory and other research/operational agencies at the National Weather Center offers unique research opportunities in Fire Weather. We can quickly transfer research to operations Summary

Joint Fire Sciences Program is a program that works and brings together different Federal agencies sharing common problems and goals.

SPC Fire Weather Outlooks available on the Web: Past PPF lightning forecasts with verification data available at:

Automated guidance for Dry Thunderstorms using the NCEP NAM model data as input...limited to *.gov domains Developer - Dr. Phillip Bothwell, Storm Prediction Center. Please send your comments to The Dry Thunderstorm Potential Index (DTPI) (for Day 1,2,and 3) is NOT A PERCENTAGE IT IS AN INDEX from 0 to 100 (dashed contours above 50 show areas where the cloud bases will be the highest and/or the sub-cloud humidity the lowest-leading to more evaporation) Example: 10,000 ft agl (Most Unstable Parcel Cloud Base) / 10,000 * ( (sub-cloud RH of 30%)) = 70 DTPI (cloud base is normalized (divided) by 10000)) DAY 1 forecasts are 3 hourly, DAY 2 are 6 hourly and DAY 3 is 24 hours - Start time in lower left of figures (Note: 6 and 24 hourly forecasts computed from maximum probability in any 3 hourly period) INPUT DATA - 12 UTC NAM; Probabilities-Solid contours (1,5,10,20,30,40,50,60,70,80,90%); DTPI (NOT a probability)-Dashed Contours(50,60,70,80,90,100) Reference papers (*.doc) and PowerPoint Presentation at bottom of this Web page NW US Day 1 Probability of 1 or more CG flashes and Dry Thunderstorm Potential Index (DTPI) click here for forecast NW US Day 1 Probability of 100 or more CG flashes and Dry Thunderstorm Potential Index (DTPI) click here for forecast NW US Day 2 Probability of 1 or more CG flashes and DTPI click here for forecast NW US Day 2 Probability of 100 or more CG flashes and DTPI click here for forecast NW US Day 3 Probability of 1 or more CG flashes and DTPI click here for forecast NW US Day 3 Probability of 100 or more CG flashes and DTPI click here for forecast SW US Day 1 Probability of 1 or more CG flashes and Dry Thunderstorm Potential Index (DTPI) click here for forecast SW US Day 1 Probability of 100 or more CG flashes and Dry Thunderstorm Potential Index (DTPI) click here for forecast SW US Day 2 Probability of 1 or more CG flashes and DTPI click here for forecast SW US Day 2 Probability of 100 or more CG flashes and DTPI click here for forecast SW US Day 3 Probability of 1 or more CG flashes and DTPI click here for forecast SW US Day 3 Probability of 100 or more CG flashes and DTPI click here for forecast Reference Materials click here for LTG REF Paper 1 click here for LTG REF Paper 2 Reference Materials click here for LTG PowerPoint Presentation1 click here for forecast click here for LTG REF Paper 1click here for LTG REF Paper 2 click here for LTG PowerPoint Presentation Experimental SPC Perfect Prog(nosis) Lightning Forecasts

Visible satellite for 00 UTC July 8, 2005 with both 0 to 3 hour lightning forecast (short term) for one or more CG flashes and lightning contours over the 3 hour interval. Probability contours are 1 and 2 % light blue, 5, 10, 15, and 25% orange to tan and 40% cyan. White contour is 1 or more CG flashes, red is 3 or more, green is 10 or more, blue is 30 or more, yellow is 100 or more. Questions?