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Downscaling for Fire Weather Forecasting in Complex Topography

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Title: Downscaling for Fire Weather Forecasting in Complex Topography


1
Downscaling for Fire Weather Forecasting in
Complex Topography
Heath HockenberryNational Weather Service Fire
Weather Program Manager
2
Fire Weather How are forecasts made?
  • Like everything else, start with the broad model
    output.
  • Unlike everything else, apply basic conceptual
    knowledge of terrain and fuels.

So how do we get from this.
To this ?
3
Fire Weather Old School Meteorology
  • Operational Fire weather is far from a complex,
    fine scale model with fire feedbacks and
    parameterizations.
  • Conceptual models are still the basis of
    forecasting in complex terrain.

Essential reading
Essential Training
4
S-190 Introduction to Wildland Fire Behavior
  • Basic Concepts and Terminology of Wildland Fire

5
Introduction to Fire Behavior TermsThis
exampleSpotting
  • Fire producing sparks or embers that are carried
    by the wind or convection that start new fires
    beyond the main fire

6
S-290 Introduction to Wildland Fire Behavior
  • The heart of fire weather is taught in this
    course

Stability
Winds
7
S-290 Techniques
Adjustment to Temperature using Average Lapse Rate
Known Elevations and the temperature at the
lowest elevation
Elevation Change 2000 feet Average Lapse Rate
-3.5F/1000 feet
Simple calculations like this are done all the
time in fire weather, for temperature adjustments.
8
S-290 Techniques
The thermal belt
Inversion Depth
9
S-390 and S-490 Advanced Wildland Fire Behavior
Wind Downscaling
  • General Winds
  • Local Winds

10
Examples of Local Wind circulationsslope winds
and sea breezes
11
20 FT WINDS RELATIONSHIP 20 ft winds General
Winds Local WindsWhich dominates?General?
Local? Both?
12
Terrain Forced Flows
  • The effects of terrain on General Winds
  • Dissipation of wind by terrain features
  • Acceleration of wind by terrain features
  • Diversion of wind around terrain features

Due to the complexity of terrain and atmospheric
interaction these are DIFFICULT TO PREDICT!
13
Terrain Correction Factors
  • Suggested General Wind correction factors
  • Assuming
  • Gently sloped terrain.
  • Neutral or unstable (or above inversion).
  • Windward slope exposed to general winds.
  • Upper 1/3 of slope 0.4 to 0.6 of General Wind
  • Middle 1/3 of slope 0.3 to 0.4 of General Wind
  • Lower 1/3 of slope 0.2 to 0.3 of General Wind
  • Sheltered Areas near zero

14
Terrain Correction Factors Example
6 mph
6 mph
6 mph
0-1 mph
Local slope winds
15
Terrain Correction Factors Example
20 mph
10 mph
7 mph
5 mph
0-1 mph
General Winds
16
Terrain Correction Factors Example
20 mph
16 mph
13 mph
11 mph
2 mph
20 ft WindsGeneral Winds Local Winds
17
Terrain Correction Factors Example
20 mph
16 mph
2 mph
2 mph
0 mph
20 ft WindsGeneral Winds Local Winds
18
High Elevation Gaps
Strong pass winds can also result from
upper winds combined with a low level pressure
gradient.
19
Advanced Incident Meteorology Forecasting
Forecasting on an Incident Management Team
20
Satellite Dish allows ingest and dissemination
of forecast products
21
IMET Forecasting
  • Why Pibals?
  • Diurnal Wind Patterns.
  • Complex Terrain.
  • Smoke/Public Health Concerns
  • Model problems!!!!

22
Incident Management Team Worried about the
forecasted Gap wind Event
? East
East Flank of Fire Left Alone ?
South ?
? West
July 7th 2003 Brent Wachter
23
Protect Taos Pueblo and Taos to the West
? Air Tanker Drop
24
IMET Forecasting
25
Sanford Fire
Data Rick Stratton, SEM, Missoula Fire Lab
26
Sanford Fire Fuel
27
WTR Weather Stream File for FARSITE
ENGLISH 8 12 0 600 1700 54 87 50 20 7500 8 13 0
600 1700 52 88 50 20 7500 8 14 0 600 1700 52 88
50 25 7500 8 15 0 600 1700 57 87 50 27 7500 8 16
0 600 1700 56 81 50 23 7500 8 17 0 600 1700 57 81
50 20 7500 8 18 0 600 1700 53 81 50 21 7500
28
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29
IMET Forecasting
30
Regression Equations Techniques
  • National Fire Danger Rating Forecasts from local
    NWS Offices.
  • Fire-business driven fuel dryness prediction,
    tailoring broad scale models to predict fuels
    receptiveness to fire.

31
DGEX vs. GFS (Model Downscaling)http//wwwt.emc.n
cep.noaa.gov/mmb/mmbpll/dgexhome.ops/
500 mb ht/Vort
850 mb wind
32
Acknowledgements
  • NWS Mets and IMETs Chuck Redman, Coleen Decker,
    Chris Gibson, Brent Wachter, Jim Prange, Bob
    Servick, Julia Rutherford, Bernard Meier, Larry
    VanBussum, and Chuck Baker.
  • Predictive Services GACC Mets Terry Marsha, John
    Saltenberger and Tim Mathewson.
  • NCEPs Geoff DiMego.
  • The National Interagency Fire Center Training
    Branch.
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