Search Fire Weather, PMS 425-1

Text (indexed):
  1. Forecast Confidence
  2. National Weather Service Products
  3. Forecast Models
  4. Special Wildland Fire Guidance Tools
  5. Long Range Forecast Drivers 

Forecast Confidence

The typical Confidence Horizon for an application requiring forecast information with "Very High" confidence/accuracy is about three days.  What is critical is that there are frequent shifts in this relationship that both expand and contract the amount of time that "Very High" skill is available, thus changing the Confidence Horizon.

Typical Forecast Confidence Horizon

This is especially helpful when choosing the appropriate analysis tool in WFDSS (Near-term, Short-term or FS Pro) or applying the weather forecast within them. The concept is also helpful when placing explanations in the analysis or incident notes section of WFDSS.

The atmosphere is chaotic but sometimes there is rhythm in the chaos. Climate outlook scientists study coupled oceanic and atmospheric forcing mechanisms like the El Nino Southern Oscillation (ENSO) cycle and Madden Julian Oscillation (MJO). These forcing mechanisms are tied to several teleconnection or long range-long term correlated weather patterns that determine meteorological impacts across North America.

Forecast skill typically goes up (i.e., rhythm in the chaos) in the mid and long term when certain forcing mechanisms and teleconnection patterns align, thus adjusting the normal Confidence Horizon. Under these circumstances, a monthly or seasonal outlook can have Medium to sometimes High confidence for certain weather patterns such as warmer and drier conditions and sometimes frequent wind events. This is a shift from Low to Very Low confidence under normal situations for longer-range forecasts.

Other teleconnection alignments can lead to mixed atmospheric forcing signals, thus leading to unusually low confidence periods (i.e., conflicting rhythm).

Best Practices for Determining Weather Confidence

Review text discussions routinely issued by NWS, Predictive Services (7 Day Significant Fire Potential), Climate Prediction Center (CPC) and Storm Prediction Center (SPC).

NWS Area Forecast Discussion - This NWS product is intended to provide a well-reasoned discussion of the meteorological thinking which went into the preparation of the gridded forecast. The forecaster will try to focus on the most particular challenges of the forecast. The text will be written in plain language or in proper contractions and confidence can often times be discerned by the verbiage used. At the end of the discussion, there will be a list of all advisories, non-convective watches, and non-convective warnings. The term non-convective refers to weather that is not caused by thunderstorms. An intermediate Area Forecast Discussion will be issued when either significant forecast updates are being made or if interesting weather is expected to occur.

PS 7 Day Significant Fire Potential: Expression of confidence will sometimes be written in the weather discussion portion of the product.

SPC - CONUS Discussions are provided twice daily for the Day 1 and 2 outlooks during the early to late morning hours. The Day 3-8 outlook and discussion is updated once per day during the afternoon.

CPC 6-10 Day, 8-14 Day, and 3-4 Week Discussions:  6-10 and 8-14 day discussions are updated Mon to Fri but not updated by a forecaster during the weekend. 3-4 week discussions are updated on Fri. Confidence is oftentimes mentioned or alluded to in these discussions.

When the weather information gets fuzzy and you are not sure where it lies on the Confidence Horizon it is best to directly consult Predictive Service or NWS forecasters and Incident Meteorologists (IMETs). Don’t shy away from talking to all three sources so you hopefully can gain a clearer picture of the Confidence Horizon.

There are several types of questions you should consider asking.

  1. Does your office have access to a high-resolution model and use it for grid editing?
  2. How often do you update your discussions, is there a routine fire weather discussion during the fire season?
  3. Do you have a long-range forecast expert in the office?
  4. Does your office send out special email notices or produce webinar or webcasts routinely during the fire season or during significant events?
  5. Inquire about the spread or consistency in recent modeling?
  6. Are there any localized critical fire weather growth patterns for the area?

National Weather Service Products

Comprehensive Displays

NWS Fire Weather and Enhanced Data Display - National Weather Service’s (NWS) Experimental Enhanced Data Display (EDD) fills a void that currently exists in the NWS. It provides our partners and customers a single interface to access all things GIS related in the NWS. EDD is an extremely powerful and flexible GIS web application. Before the development of EDD, users had to navigate to countless web pages to get at the information they desired. EDD puts this information in one place making it very easy to display and manipulate this data. EDD is hosted on the National Internet Dissemination System (NIDS) and was developed by the Weather Ready Nation Pilot Project in Charleston, WV.

Short-Term Forecast Products (1-7 Days)

NWS Routine Fire Weather Forecasts - Generated twice daily during the area’s main fire season and updated when conditions warrant, these narrative forecasts include a discussion of expected weather events, general weather parameters for the forecast zone over the next 48 hours, and an outlook summary for days 3-5.

NWS Watches and Warnings - General site provides access point to different products with map emphasizing different watches and warnings. Issuance of a warning or watch implies stronger confidence levels in growth conditions between 12-96 hours ahead of an event.

NWS Spot Weather Forecasts - This interface is intended to be used solely for the relay of forecast information to the National Weather Service. Submissions sent through this online form are intended for internal agency use.

NWS Weather Prediction Center (WPC) - The WPC provides forecast products including deterministic and probabilistic quantitative precipitation forecasts and discussions, short-term and medium-range forecasts,  and surface analysis.

National Digital Forecast Database (NDFD) and Wildand Fire Assessment System NDFD Point Forecasts (CONUS Only) - The NWS's NDFD graphic products are derived from a prescribed set of data contained within the NDFD. These graphics are representations of the official NWS digital forecast. Forecast information for the Canadian portion of the Great Lakes is for informational purposes only and does not constitute an official forecast. In CONUS only, WFAS provides a tool that allows NDFD forecasts to be queried for individual latitude-longitude locations.

NWS Storm Prediction Center - This Center provides convective and fire weather outlooks out to 8 days across the CONUS. They also provide special fire, convective and precipitation weather interrogation tools such as the High Resolution Ensemble Forecast (HREF) and Short Range Ensemble Forecast (SREF) viewers.

Predictive Services 7 Day Significant Fire Potential – Product that highlights the likelihood that a wildland fire event will require mobilization of additional resources from outside the area in which the fire situation originates. Weather, fuels, resource availability and probabilities of ignition are assessed each day to create the probability levels out 7 days. Forecasts of Energy Release Component, Burning Index, 10-100 and 1000 hr dead fuel moistures can also be reviewed using the main webpage.

  • High Risk = Days in this category represent a probability of 20% or higher for a significant fire. 

Extended Forecast Products (1 Week to Several Months)

NWS Climate Prediction Center Extended Outlooks - The Climate Prediction Center (CPC) is responsible for issuing seasonal climate outlook maps for 1-13 months in the future. In addition, the CPC issues extended range outlook maps for 6-10 and 8-14 days as well as several special outlooks, such as degree day, drought and soil moisture, and a forecast for daily ultraviolet (UV) radiation index. Many of the outlook maps have an accompanying technical discussion.

Predictive Services Seasonal Outlooks – At the beginning of each month, seasonal outlooks are posted. These outlooks serve as assessments of the current and projected fuels, weather and fire potential out four months.

NWS Climate Prediction Center Expert Assessments - Includes Hazards Assessment, ENSO update, and others.  Climate Prediction Center (CPC) meteorologists and oceanographers review climate and weather observations and data along with model results and assess their meaning, significance, current status, and likely future climate impacts. Their findings are issued as assessments, advisories, special outlook discussions, and bulletins.

Drought Outlooks and Seasonal Climate Forecasts - These forecasts show predicted trends for areas experiencing drought depicted in the U.S. Drought Monitor, as well as indicating areas where new droughts may develop.

Forecast Models

Meteorologists produce weather forecasts based largely on interpreting and validating weather models. Several models are available with varying update cycles, output time intervals, temporal range and spatial resolution. Models are semi-routinely adjusted based on new research, new observing techniques and increased computer processing power.

Deterministic and Ensemble models have different classifications such as global, regional and convective allowing (CAMS). High resolution models (≤ 5 km) are generally convective allowing and have 15 min to 1-hour time-steps. They can resolve terrain induced and altered wind regimes, small scale boundary passages and banded and cellular precipitation features. Due to the differing scales, physics and initial conditions CAMs models can produce widely differing solutions when compared to each other thus making it tricky for forecasters to choose the right solution.

Deterministic, or operational, models use the best estimate of the current state of the weather (initial conditions) to provide a singular solution out in time. Outputs generally contain higher spatial resolution compared to ensemble outputs.

Deterministic ModelsUpdates per dayOutput Timestep (hrs)Range (hrs)Resolution
Global Forecast Model (GFS)4638413 km
European Computer Forecast Model (ECMWF)2122409 km
North American Mesoscale Model (NAM)41 to 360 to 843, 12, and 22 km
Global Environmental Multi-scale Model Canada (GDPS/GEM/CMC)2 to 41 to 654 to 240varies
Unified Model United Kingdom (UKMET)4614410 km
Navy Global Environmental Model (NAVGEM)43 to 6144 to 18013 to 31 km
High Resolution Rapid Refresh (HRRR)2415 min to 1 hr18 to 363 km
Weather Research & Forecasting (WRF/different variants)varies1varies but generally not beyond 72 hrs1.33 to 5 km

Probabilistic or ensembles are a collection of numerical model outputs that show slightly different possible outcomes. The outcomes are slightly different because each member of the ensemble has been perturbed or initialized with slightly different starting atmospheric conditions. Forecast skill can increase the first 1-2 weeks of a forecast period using these ensemble modeling systems.

Probabilistic ModelsUpdates per dayOutput Timestep (hrs)Range (hrs)ResolutionMembers & Control
Global Ensemble Forecast System (GFES/GFS ensemble variant)4638433 km21
Ensemble Prediction System (EPS/ECMWF ensemble variant)22436018 km52
Global Ensemble Prediction System (GEPS/GEM ensemble variant)2638466 km21
North American Ensemble Forecast System (NAEFS/blend of GEPS & GFES)26336111 km42
Navy Global Environmental Model Ensemble (NAVGEM)26384111 km16
High Resolution Ensemble Forecast (HREFv2)4148~3 km8
Short Range Ensemble Forecast (SREF)41 to 38716 to 40 km22 to 26
North American Multi-Model Ensemble (NMME)16 to 246 months111 km7

The amount of spread in an ensemble model should directly be related to the uncertainty of the forecast because the actual observed weather solution should fall somewhere in between the individual members solutions. Tighter the spread, more confidence in the forecast. Wider the spread, less confidence.

Graphic describing parts of an ensemble forecast. Shows the multiple members of the forecast family and highlights the range of beginning, or current, weather as well as the future forecasted state.

Ensemble Terms to be familiar withDefinition and Uses
MembersIndividual model run in an ensemble suite perturbed by slightly different initial conditions. Forecasters look at spread of the members.
MeanAverage value of the individual ensemble model members. Smooths out “chaos.”
ControlMimics the operational model run because it uses the same initial conditions but with a courser spatial (vertical and horizontal) resolution. Forecasters compare it to the operational run, if output different then differing spatial resolution has effect on the output. 
SpreadUsually represented by standard deviation. Larger the deviation, more uncertainty in the forecast.
Normalized SpreadPuts standard deviation in context with the general ensemble model behavior. For example, how does the current day 10 forecast standard deviation value compare to the past 30 days of day10 model forecasts? Helps determine proper confidence level.

There are several types of useful outputs that can result from ensemble weather modeling. For example, NAEFS provides outputs based on reviewing a 3-week period centered on the valid day using a 30 year climate record.

  • Standard anomaly: How different is forecast from climatological mean?
  • Percentile: Where would the forecast fall with respect to climatology? Max and Min values indicate the forecast falls out of the 30 year climate record thus a potentially significant event.
  • Return interval: How often do these forecasts show up in the climatology?
  • Probabilities: How many of the ensemble members are producing extreme values?

Special Wildland Fire Guidance Tools

These tools will help identify unusual or important fire weather and danger time periods and give higher confidence to a critical fire growth or slowing pattern. Publications explaining the tools or indexes are provided in the Weather References section of this guide.


Global Wildfire Information System (GWIS) which provides 8 km ECMWF based forecasts of FWI out 10 days across the Globe.


Hot Dry Windy (HDW): Designed to help identify days which are more likely to have adverse weather conditions. Represents the multiplication of maximum wind speed and maximum vapor pressure deficit (VPD).


Severe Fire Danger Index (SFDI): 5 separate classifications (Low-Moderate-High-Very High and Severe) represent the normalized percentile values of combining ERC and BI. Between 2003 to 2016, 75% of all MODIS active large fire pixels and 81% of all fire radiative power occurred when the index was Very High or Severe. NWS NDFD weather forecasts feed this index thus forecasted wind speeds may not adequately represent a locally significant terrain altered wind event especially beyond 3 days.

Fire Potential Index (FPI): Is a linearly scaled from 0 to 100 with 0 occurring when vegetation is near or fully green and 100 hr dead fuels are too moist to burn. FPI is 100 when vegetation is fully cured and 10 hr dead fuel moisture is 2%.

Fosberg Fire Weather Index (FFWI)

Regional Tools

Southern California Fire Buster: Routine 5 km forecasts updated twice per day out 72 hours for southwest portions of CONUS including CA and NV. 1-km forecasts can be requested. FFWI and Large Fire Potential are one of many outputs found in Fire Buster.

Western CONUS Monthly to Seasonal NFDRS Forecasts

Alaska Fire & Fuels (AKFF): CFFDRS Fire Weather Index (FWI) forecasts

Great Lakes Fire & Fuels (GLFF): CFFDRS Fire Weather Index (FWI) forecasts

Southeast US Fire Weather Intelligence Portal

Southern California Santa Anna Wildfire Threat Index

Long Range Forecast Drivers

It’s the meteorologist’s job to understand coupled atmospheric-oceanic teleconnections but the analyst should be aware of these teleconnections because they are generally referred to in longer range forecast discussions. The analyst will be introduced to a few important teleconnections and/or long-range outlook terms in the following table. It is important to point out that some teleconnection patterns can work together or work against each other. This is called constructive and destructive interference. Research continues in this arena and how climate change impacts traditional teleconnection impacts.

Teleconnections and Climate Forcing Mechanisms

Coupled oceanic- atmospheric forcing mechanismsUsefulness and DefinitionConfidence Impact
Spring Predictability BarrierRefers to the period of time when the statistical and dynamic climate models have less skill to predict ENSO trends. April-May-June represents this period for the northern hemisphere.Lower confidence in long range climate outputs when the models are initialized during the spring period.
El Nino Southern Oscillation (ENSO)Irregular periodic variation in winds and sea surface temperature over tropical eastern Pacific. Warming phase is El Nino and cooling phase is La Nina. There is also an ENSO neutral condition. Deep thunderstorm development over the eastern equatorial Pacific will help alter the jet stream and make more moisture available for Pacific storm systems that impact the USA.Warm or cool phases combined with other climate drivers such as certain phases of the PDO can lead to higher confidence long term outlooks.
Pacific Decadal Oscillation (PDO)A longer lived northern Pacific climate variability that has a negative and positive phase. The jet stream will tend to dip further south over the western United States under a positive phase and move further north under a negative phase.Positive or negative phases to the PDO combined with other climate drivers such as ENSO conditions can lead to higher confidence long term outlooks.
Pacific Meridional Model (PMM)Describes the interaction between ENSO and PDO teleconnections and has a negative and positive phase.Determining positive or negative phases of the PMM may help resolve the Spring Barrier issue and ENSO prediction. This should help lead to higher confidence outlooks originating during months of April through June.
ModokiAlternation in normal La Nina and El Nino SST patterns across the tropical Pacific thus disrupting typical teleconnection patterns. “This isn’t your grandfather’s El Nino”.Confidence becomes varied and can be less depending on other coupled ocean-atmosphere phenomena.
Madden Julian Oscillation (MJO)MJO is a tropical disturbance that propagates eastward around the global tropics with a cycle on the order of 30 to 60 days. They typically are most active during late fall, winter and early spring period. MJO can influence ENSO tendencies.Active MJO’s can increase forecast confidence for certain weather anomalies across USA.
Aleutian LowStrength of the Aleutian low combined with PMM modes can accentuate or dampen MJO impacts on the jet stream position and storm track across western USA.Confidence of an active storm track across western US increases when the Aleutian low is stronger than average and combines with a positive PMM and a MJO is present.
Arctic Oscillation (AO)Represent a pattern of differences in air pressure between the Arctic and mid-latitudes. AO’s influence winter weather in the northern hemisphere. Positive phase AO’s are representative of strong pressure systems where low pressure is found over the Arctic and high pressure over mid-latitudes. Negative phase AO’s represent a weaker pressure gradient due to less low pressure across Arctic and less high pressure in the mid-latitudes. AO phases can change in a matter of weeks.During negative phase AO’s there is higher confidence for cooler air, generally locked up in the Arctic, to eventually spill southward into CONUS while warmer air moves to the north.
North Atlantic Oscillation (NAO)Represents pressure difference between Iceland and the Azores. Azores typically have high pressure and Iceland low pressure. The magnitude of change dictates whether the NAO is in a positive phase or negative phase. Positive phases represent a large change in pressure, while negative phases are a small change. NAOs influence northern hemispheric weather by influencing the jet stream, especially during the winter months.During positive phase, jet stream generally less undulating with muted, more progressive troughs and ridges. During negative phase, jet stream is represented by high amplitude blocking troughs and ridges with a trough more over eastern portion of CONUS.
Atlantic Multi-Decadal Oscillation (AMO)Represents a coherent mode of natural variability occurring in the North Atlantic. Measurement is based upon average SST anomalies (0 to 80N). Cooler SST’s represent a negative phase. Warmer SST’s represent a positive phase.Has been used to correlate temperature and precipitation anomalies across northern hemisphere. Positive AMO’s have been linked to long-sustained droughts in Midwest and Southwest with increased Hurricane activity in N. Atlantic.


Text (indexed):

Fire weather notes for slash burning, Alberta Forest Service, 1985.

Andrews, Patricia L, Modeling Wind Adjustment Factor and Midflame Wind Speed for Rothermel’s Surface Fire Spread ModelGeneral Technical Report RMRS-GTR-266, USDA Forest Service. Rocky Mountain Research Station, 2012.

Bishop, Jim, Technical Background of the FireLine Assessment Method (FLAME), RMRS-P-46CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. CD-ROM. pages 27-74.

Lawson, B.D., Armitage, O.B., Weather Guide for the Canadian Forest Fire Danger Rating System, Edmonton, AB.

Haines, D.A., A Lower Atmospheric Severity Index for Wildland Fire, National Weather Digest. Vol 13. No. 2:23-27, 1988.

Latham, Don J. and Rothermel, Richard C., Probability of Fire-Stopping Precipitation Events, USDA Forest Service, Research Note INT-410; page 8, 1993.

Interagency Wildland Fire Weather Station Standards & Guidelines, PMS 426-3, National Wildfire Coordinating Group, 2014.

Schroeder, Mark J. and Buck, Charles C., Fire Weather: A Guide For Application of Meteorological Information to Forest Fire Control Operations, USDA Forest Service Agricultural Handbook 360, pages 85-126, 1970.

Seager, R., A. Hooks, A. Williams, B. Cook, J. Nakamura, and N. Henderson,  Climatology, Variability, and Trends in the U.S. Vapor Pressure Deficit, an Important Fire-Related Meteorological Quantity2015.

Simard, A.J., Calibration of Surface Wind Speed Observations in Canada, Forest Fire Research Institute, Ontario, 1971.

Werth, Paul and Ochoa, Richard, The Haines Index and Idaho Wildfire Growth, Fire Management Notes, 1990.

Werth, John and Werth, Paul, Haines Index Climatology for the Western United States, NOAA National Weather Service Western Region Technical Attachment No. 97-17, 1997.

Werth, Paul A., Potter, Brian E., Clements, Craig B., Finney, Mark A., Goodrick, Scott L., Alexander, Martin E., Cruz, Miguel G., Forthofer, Jason A., McAllister, Sara S.,  Synthesis of Knowledge of Extreme Fire Behavior: Volume I for Fire Managers, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 2011.

Whiteman, C. David, Mountain Meteorology: Fundamentals and Applications, Oxford University Press, 2000.


PRINT FBFRG Weather References
Text (indexed):

Anderson, H. E., Aids to Determining Fuel Models for Estimating Fire Behavior, U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, 1982.

Andrews, Patricia L., BehavePlus Fire Modeling System, Version 5.0: Variables, Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2009.

Bradshaw, Larry S., Deeming, John E., Burgan, Robert E., Cohen, Jack D., The 1978 National Fire-Danger Rating System: Technical Documentation, U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, 1984.

Burgan, Robert E., Concepts and Interpreted Examples in Advanced Fuel Modeling, U.S. Department of Agriculture, Forest Service, Intermountain Research Station, 1987.

Keane, Robert E., Garner, Janice L., Schmidt, Kirsten M., Long, Donald G., Menakis, James P., Finney, Mark A., Development of Input Data Layers for the FARSITE Fire Growth Model for the Selway-Bitterroot Wilderness Complex, USA, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 1998.

Keane, R.E, Reinhardt, E.D., Scott, J., Gray, K., Reardon, J., Estimating Forest Canopy Bulk Density Using Six Indirect Methods, NRC Canada,  2005.

Keane, Robert E.; Mincemoyer, Scott A.; Schmidt, Kirsten M.; Long, Donald G.; Garner, Janice L., Mapping vegetation and fuels for fire management on the Gila National Forest Complex, New Mexico, CD-ROM, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2000.

Rothermel, R. C., A mathematical model for predicting fire spread in wildland fuels, U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, 1972.

Rothermel, R. C., How to predict the spread and intensity of forest and range fires. Gen. Tech. Rep. INT-143. Ogden, UT:  U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, 1983.

Scott, J.H. and Reinhardt, E.D., Estimating Canopy Fuels in Conifer Forests, Forest Management Today. 62(4), 2002.

Scott, Joe H.; Burgan, Robert E., Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2005.

Scott, Joe H., Nomographs for estimating surface fire behavior characteristics, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2007.

Stratton, Richard D., Guidebook on LANDFIRE fuels data acquisition, critique, modification, maintenance, and model calibration, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2009.


PRINT FBFRG Fuels References
Text (indexed):
  1. Primary Reference
  2. LCP Data Sources
  3. Other Data Sources
  4. LCP Fuel Themes
  5. Nomenclature for Spatial Data Layers
  6. LCP Critique
  7. Editing and Updating the Landscape (LCP) File

Primary Reference

Guidebook on LANDFIRE fuels data acquisition, critique, modification, maintenance, and model calibration at Stratton, Richard D. 2009. RMRS-GTR-220. Fort Collins, CO, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 54 p. 

LCP Data Sources

LANDFIRE Data Distribution Site

There are several versions of LANDFIRE data, including LCP files (2001, 2008, 2010, 2012, and 2014). You can evaluate what is available in each version with its Version Comparison Table.  There is no online tool for editing the files before download. Downloaded files may be requested in either the US Albers or the local UTM projection.

Wildland Fire Decision Support System (WFDSS)

Analysis tools in WFDSS (Basic, STFB, NTFB, and FSPro) include downloadable LCP files.  Users may edit the LCP files before download.  Downloaded files come with a custom Albers projection that may require some reprojection effort before combining with shapefiles in FARSITE and FLAMMAP analysis. LCP Critique reports are available alongside the LCP file.

Interagency Fuel Treatment Decision Support System (IFTDSS)

IFTDSS uses spatial analysis tools in support of Hazard Analysis, Prescribed Burn Planning, Risk Assessment, Fuels Treatment, and Fire Effects planning.  Primarily based on the FLAMMAP processor, analysis tools use LANDFIRE data, allowing the user to edit and download LCPs from their projects.

Other Data Sources

Wildland Fire/Treatment History

  • Burn severity layers
  • Fire progression layers
  • Fuel treatments
  • Prescribed fire perimeters
  • Wildfire perimeters

Ecological Considerations

  • Areas of critical environmental concern
  • Sensitive or critical wildlife habitat
  • Threatened, endangered, and sensitive (TES) flora and fauna habitat
  • Rivers and streams
  • Water bodies
  • Vegetation or cover-type classification

Socio-Economic Considerations

  • Ownership and jurisdiction layer
  • Historical and recreational sites
  • Primary and secondary residences
  • Remote automated weather stations (RAWS)
  • Roads and Trails
  • Urban development

Other Base Layers

  • Aerial photos
  • Digital orthophoto quad (DOQ) or quarter quad (DOQQ)
  • Digital raster graph (DRG)

LCP Fuel Themes

Surface Fuel Model

13 original Fuel Models

Anderson, H. E. 1982. Aids to determining fuelmodels for estimating fire behavior. Gen. Tech. Rep. INT-122. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 22 p. 

40 Standard Fuel Models

Scott, Joe H.;Burgan, Robert E. 2005. Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model. Gen. Tech. Rep. RMRS-GTR-153. Fort Collins, CO: U.S. Department of Agriculture, Forest Service,Rocky Mountain Research Station.72 p.

The following themes all relate to a forest canopy that affects mid-flame wind speed, spotting, and crown fire potential.

Scott, Joe H.; Reinhardt, Elizabeth D. 2005. Stereo photo guide for estimating canopy fuel characteristics in conifer stands. Gen. Tech. Rep. RMRS-GTR-145. Fort Collins, CO: U.S.Department of Agriculture, Forest Service, Rocky Mountain Research Station. 49p.

Canopy Cover (CC)

In percent, 0-100%, practical Maximum is 70% in most conifer fuel types.

Canopy Height (CH or SH)

Units in Meters*10, divide by 10 to get actual height in meters.

Canopy Base Height (CBH)

Units in Meters*10, divide by 10 to get actual height in meters.

Canopy Bulk Density

Units in Kilograms/meter3*100, divide by 100 to get actual density.

Nomenclature for Spatial Data Layers

Fuel TypeFuel Model BlocPre-DefinedReserved for Future
Pre-defined Models
Available for
Custom Fuel Models
NB90-9991-93, 98-9994, 9590, 96, 97
GR100-119101-109110-112100, 113-119
GS120-139121-124125-130120, 131-139
SH140-159141-149150-152140, 153-159
TU160-179161-165166-170160, 171-179
TL180-199181-189190-192180, 193-199
SB200-219201-204205-210200, 211-219

LCP Critique

The LCP Critique report is an essential element in the calibration process. It can be obtained from the same WFDSS analysis landscape tab that the LCP was obtained from. Or, if the LCP is downloaded, it can be loaded in FLAMMAP and a critique can be generated from there.  There is a stand-alone version LCPCritique at

On the first page

  • View the filename, latitude, cell resolution, and coordinate system in the header information to insure the file used is correct.
  • View the Theme units, ranges, and value distributions to make sure that the lcp is valid and that there is no corrupted data.
  • Determine the important surface fuel models in the LCP.

As an example, this histogram shows that fuel models 183, 165, 102, and 122 are the primary surface fuels.

Fuels distribution display in LCP Critique report showing a bar graph of the fuel model classification.

Is that what you expect? What are the critical inputs for each of these fuel models? Are any of them dynamic?

Image and Legend Pages for Each Theme

Some data problems can be identified visually here, such as vertical and horizontal lines in slope themes. The fuel model image can be reviewed by comparing mapped fuel models with areas that have had ground verification or high confidence classifications.

Theme Distributions for each Surface Fuel Models, in order of importance

  • Evaluate the terrain theme ranges and distributions for elevation, slope, and aspect. Are these appropriate for the fuel model? How would you revise or adjust them? Consider whether the fuel model needs to be changed for certain terrain value combinations.
  • Canopy characteristics should be evaluated carefully to ensure that canopy cover (wind adjustment, fuel shading), tree heights (wind adjustment, spotting distance), and canopy base height (crown fire initiation), distributions make sense for the specific fuel model.
  • Canopy bulk density (active crown fire propagation) values are not only related to the fuel model and canopy tree species, they also must be appropriately scaled for the crown fire propagation model used (surface fire control - Finney vs. crown fire control - Scott & Reinhardt; see Crown Fire Initiation and Propagation Section.

Editing and Updating the Landscape (LCP) File

Any errors or necessary adjustments identified here should be included in landscape edits performed before the first analyses are conducted.

There are several tools for editing LCP files:


PRINT FBFRG Landscape Acquisition, Critique, and Editing
Text (indexed):
  1. Measures of Stability
  2. Lower Atmospheric Stability (Haines) Index

Measures of Stability

IndexMajor FactorsPrimary UtilityApplication
Davis Stability IndexLapse rateBasic measure of stabilitySoutheast US
Ventilation IndexMixing height and transport windSmoke dispersionUnited States
Haines (Lower Atmospheric Stability) IndexLapse rate and relative humidityLarge fire growth potentialUnited States
Pasquill Stability IndexSolar radiation, cloud cover and surface wind speed (surface based stability)Smoke dispersionSASEM
Lavdas Atmospheric Dispersion IndexPasquill, mixing height, transport windSmoke dispersion and fire growth potential.Florida

Lower Atmospheric Stability (Haines) Index

The Lower Atmospheric Severity Index, commonly known as the Haines Index, was developed during the 1980s as a fire weather tool to estimate the effect of atmospheric dryness and stability on the growth potential of a wildfire. The goal was to identify typical combinations of humidity and stability and contrast them with combinations of stability and humidity prevalent during problem fire outbreaks. Always reference local Climatology, see below.

Haines Index Calculation Criteria

LOW ELEVATION Stability Term (A)LOW ELEVATION Moisture Term (B)
950 – 850 mb °C
A = 1 when 3°C or less
A = 2 when 4-7°C
A = 3 when 8°C or more
950 mb T° C – 950 DP° C
B = 1 when 5° C or less
B = 2 when 6-9° C
B = 3 when 10° C or more
MID ELEVATION Stability Term (A)MID ELEVATION Moisture Term (B)
850 – 700 mb °C
A = 1 when 5°C or less
A = 2 when 6-10°C
A = 3 when 11°C or more
850 mb T° C – 850 DP° C
B = 1 when 5° C or less
B = 2 when 6-12° C
B = 3 when 13° C or more
HIGH ELEVATION Stability Term (A)HIGH ELEVATION Moisture Term (B)
700 – 500 mb °C
A = 1 when 17°C or less
A = 2 when 18-21°C
A = 3 when 22°C or more
700 mb T° C – 700 DP° C
B = 1 when 14° C or less
B = 2 when 15-20° C
B = 3 when 21° C or more
Haines Index (A + B)Potential for Large Fire
2 or 3
Very Low

U.S. Haines Elevation Classification Map

The Haines, or Lower Atmospheric Stability Index, uses different inputs based on the general classification of terrain elevation. This map displays areas of High, Mid, and Low elevation areas.

Haines Index Climatology


Text (indexed):

Agee, James K, Wright, Clinton S.  Williamson, Nathan, and Huff, Mark H.; Foliar Moisture Content of Pacific Northwest Vegetation and its Relation to Wildland Fire Behavior; Forest Ecology and Management, 2002.

Burgan, R.E., Estimating live fuel moisture for the 1978 National Fire Danger Rating System—1978, USDA Forest Service. Research Paper, 1979.

Burgan, R.E.; Hartford, R.A., Monitoring vegetation greenness with satellite data, United States Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, 1993.

Burgan, Robert E.; Hartford, Roberta A.; Eidenshink, Jeffery C., Using NDVI to assess departure from average greenness and its relation to fire business, U.S. Department of Agriculture, Forest Service, Intermountain Research Station, 1996.

Fosberg, M. A., and J. E. Deeming,  Derivation of the 1- and 10-hour timelag fuel moisture calculations for fire-danger rating, USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, 1971.

Hirsch, Kelvin G., Canadian Forest Fire Behavior Prediction (FBP) System: User’s GuideCanadian Forest Service Special Report, 1996.

Jolly, William M., Nemani, R. and Running, S.W., A generalized, bioclimatic index to predict foliar phenology in response to climate, Global Change Biology 11(4), 2005.

Jolly, W. Matt; Hadlow, Ann M.; Huguet, Kathleen, De-coupling seasonal changes in water content and dry matter to predict live conifer foliar moisture content, International Journal of Wildland Fire, 2014.

Jolly, W. Matt, Hintz, J., Kropp, R., and Conrad, E.,  Physiological drivers of the live foliar moisture content ‘spring dip’ in Pinus resinosa and Pinus banksiana and their relationship to foliar flammability, International Conference on Forest Fire Research, 2014.

Jolly, W.M.,  Development of fine dead fuel moisture field references for the Southeastern United States: SimpleFFMC, USDA Forest Service RMRS Fire Sciences Laboratory, 2016.

Nelson R.M., Jr., Prediction of diurnal change in 10-h fuel stick moisture content, Canadian Journal of Forest Research, 2000.

Norum, Rodney A.; Miller, Melanie, Measuring fuel moisture content in Alaska: standard methods and procedures, U.S. Department of Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station, 1984.

Rothermel, Richard C., How to predict the spread and intensity of forest and range fires, U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, 1983.

Schlobohm, P. and Brain, J., Gaining an Understanding of the National Fire Danger Rating System, PMS 932/NFES 2665, National Wildfire Coordinating Group, 2002.

Schroeder, Mark J.,  Ignition probability, USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, 1969.


PRINT FBFRG Fuel Moisture References
Text (indexed):
  1. Definitions
  2. Estimating Surface (20 feet) Wind Speed in Mountain Terrain
  3. Worksheet for Estimating 20 feet Surface Winds
  4. WindNinja
  5. Adjusting Surface (20 feet) Wind to Midflame Wind Speed


This graphic of different winds shows generally the source elevation and duration of different general (synoptic), local (mesoscale), and gust (microscale) winds. 

Wind Scales and Types. The horizontal dimensions and lifetimes of atmospheric phenomena illustrate the broad range of atmospheric space and time scales.

Critical Winds

Critical winds dominate the fire environment and easily override local wind influences. Examples include frontal winds, Foehn winds, thunderstorm winds, whirlwinds, surfacing or low-level jets (reverse wind profiles), and glacier winds.

General (Synoptic Scale) Winds

Synoptic scale, gradient, free air, ridgetop are large-scale winds produced by broad scale pressure gradients between high- and low-pressure systems. They may be influenced and modified considerably in the lower atmosphere by terrain and vegetative structure.

Local (Mesoscale) Winds

Thermal, convective, drainage, and convective winds are all caused by local temperature differences generated over a comparatively small area by local terrain and weather. They differ from those which would be appropriate to the general pressure pattern in that they are limited to near surface and are controlled by the strength of the daily solar cycle.

  • Slope Winds are driven by heat exchange at the slope surface. They can react quickly to insolation on the slope, with upslope breezes starting within a few minutes. The strength of upslope winds is also influenced by the length and steepness of the slope as well as the exposure. Upslope winds generally range from 3-8mph. The transition from upslope to downslope wind begins soon after the first slopes go into afternoon shadow and cooling of the surface begins. In individual draws and on slopes going into shadow, the transition period consists of (1) dying of the upslope wind, (2) a period of relative calm, and (3) gentle laminar flow downslope. Downslope winds are very shallow and of a slower speed than upslope winds, generally 2-5mph. The cooled denser air is stable and the downslope flow, therefore, tends to be laminar.
  • Valley Winds are similar to and linked with slope winds. Their development each day generally lags 1-3 hours behind that of slope winds. Peak speeds can be as much as double those of slope winds, reaching 10-15mph at their peak.
  • Land and Sea Breeze Circulations  during the day, sea/lake breeze can reach 10-15mph at the peak of solar heating in the afternoon. The corresponding land breeze is lighter, perhaps 5-10mph.

Surface Winds

Measured near the earth’s surface, at an observing station, customarily at some height (usually 20 feet or 10 meters) above the average vegetative surface and a distance equal to at least 10 times the height of any obstruction to minimize the distorting effects of local obstacles and terrain.

General to Surface Wind Relationship. This image depicts the relationship of various winds. Large-scale synoptic winds combine with local thermally-driven winds to produce 20-Foot winds. 20 Foot winds are reduced by sheltering vegetation and terrain to become Mid-flame winds.

Wind Gust is a sudden, brief increase in speed of the wind. According to U.S. weather observing practice, gusts are reported when the peak wind speed reaches at least 16 knots and the variation in wind speed between the peaks and lulls is at least 9 knots. The duration of a gust is usually less than 20 seconds. 

Midflame Wind Speed is the estimated wind speed at a height above the surface fuel equivalent to the height at midflame. This is the wind input required for estimating fire spread using the Rothermel surface fire model. It is generally derived from the Surface (20 feet) Wind based on sheltering from an upper canopy or flame height based on fuel bed depth.

Eye-Level Winds are frequently used to represent midflame wind speeds, though that may represent an overestimate for shallow and sparse fuelbeds that have lower flame heights or an underestimate for shrub and crown fuels with deep fuelbeds.

Effective wind speed is the combined effect of Midflame Wind Speed and the slope equivalent wind speed in the direction of maximum spread (head fire). Effective Wind Speed is used in place of midflame wind speed when winds are blowing upslope and to determine size and shape (length-to-width ratio) for those fires. See Section for Effective wind speed.

Estimating Surface (20 feet) Wind Speed in Mountain Terrain

Slopes and Ridges of Mountains

  • Isolated peaks tend to divert general wind flow horizontally and vertically. Some acceleration of general winds is likely around the flanks and over the top of isolated mountains peaks with gently inclined slopes. On the lee side of the peak, a turbulent reversal or wind eddies of general wind flow is possible.

Image depicting winds moving around an isolated peak as described in the text.

  • Overall, mesas tend to decelerate general winds because energy must be expended to create local reversals of wind flow called “separation eddies” that form upwind and downwind of steep sided barriers near separation eddies and on top of the mesa, expect 20 feet winds to be decelerated below what might be expected for the general area. Be aware of the potential for frequent gusts and shifts in wind direction near the eddies.

Continuous Ridges when airmass is instable, general winds tend to ride over the ridge. Under stable conditions, weak winds are blocked and a stagnant zone formed below the ridges. In either case, the atmospheric stability, the strength of the general wind and its angle of incidence, and influence of diurnal winds (which may be opposing) must be considered on the downwind side of the ridge.

Gaps in Terrain can produce a venturi effect, where winds can be expected to accelerate downwind of the constriction, primarily in the exit region. These gap winds are part of the general wind, because they are based on general winds.

Gap Winds. An image of the Bernoulli Effect in constricted terrain as described in text above.

  • Low Level Gorges  frequently facilitate gap flow when upwind airmass is stable and discourages the wind from rising over terrain. These gap winds are fairly shallow, less than a few thousand feet.
  • Mountain Passes and Saddles form upper level winds that impact high terrain tend to flow through the lowest possible spots in a mountain chain rather than climb over it. Local slope and valley winds should be included here.

Valley Influences

When valleys or basins are not aligned with general winds, eddies and nighttime inversions can result in significant reductions and anomalies in wind direction.

The local drainage wind component transitions from upslope as the sun hits the upper slopes, then up-valley as the heating becomes widespread to downslope as the sun sets and down valley during the night.

The general wind influence on surface winds in these valleys depends on its strength, the angle of incidence to the valley axis, the depth of the valley, its aspect alignment, and the time of day.

Valley Winds: This image demonstrates the diurnal transition between slope and valley winds and the importance of alignment of valleys with general winds

During the day, general winds that are aligned with the up-valley wind will increase the surface winds. Opposing winds will result in decreased surface winds. And perpendicular general winds will contribute little to the local winds found there.

During the night, general winds are most likely to surface when they are strong and aligned parallel to the valley axis.

  • Enclosed or Isolated Basins have generally reduced surface wind low on the slopes and valley bottoms. Inversions may limit even the infrequent gusts.
  • Elongated Valley Winds
  • Forked or Bent River Drainages are even more dominated by local winds, though the relationships are even more complex. In the daytime, look for general winds to surface primarily in several exposed stretches, creating a mosaic of stronger and weaker surface winds, depending on alignment. At night, the situation is simplified with predominately local downslope and down valley breezes. Beware of strong general winds that are aligned with certain sections.
  • Inversions in valleys are very effective at preventing general winds from surfacing on the midslopes or valley floor. Light local slope and valley flow will likely be the dominant winds. Expect to adjust the 20 feet wind downward when an inversion is present. They generally form at night, but may persist through daylight hours if sunlight is diminished by smoke, fog, or cloud cover. Beware that strong general winds at night can dissipate and inversion through turbulent mixing.

Critical winds

Foehn winds, barrier jets, downslope windstorms, and cold air avalanches may interact locally with the terrain features discussed above and result in even stronger flows.

Worksheet for Estimating 20 feet Surface Winds

Surface Wind Estimation Process. Estimating Surface Windspeed: This process chart aids the user in estimating surface windspeed through integration general and local factors.


WindNinja is a computer program that computes spatially varying wind fields for wildland fire and other applications requiring high resolution wind prediction in complex terrain.

Wind Ninja: This image depicts output from software that combines general winds, terrain, and vegetative cover.

WindNinja can be run in three different modes depending on the application and available inputs.

  • The first mode is a forecast, where WindNinja uses coarser resolution mesoscale weather model data from the US National Weather Service to forecast wind at future times.
  • The second mode uses one or more surface wind measurements to build a wind field for the area.
  • The third mode uses a user-specified average surface wind speed and direction.

Outputs include:

  • Direct map display.
  • Google earth kmz.
  • ArcGIS shapefiles and asci rasters.

WindNinja available for download to install for:

Adjusting Surface Wind to Midflame Wind Speed

Once general winds are adapted to 20 feet surface winds based on terrain and other local factors, adjustment of 20 feet wind to midflame wind depends on canopy sheltering and surface fuel bed depth. Note how the effect of sheltering varies based on fires position in terrain.

Image depicting Wind Adjustment Factors based on canopy cover and position on slope.

  • All Canopy covers less than 20% and all Crown Ratios less than 0.2 are considered unsheltered. Wind Adjustment Factor (WAF) for unsheltered fuel is a function of fuel bed depth only.
  • WAF for sheltered fuels is based on a combination of Canopy Cover, Canopy Height, and Average Crown Ratio for the site. As combinations of these factors increase, WAF becomes partially sheltered, then fully sheltered.

Unsheltered Fuels

  • Openings on level ground.
  • On high ridges where trees offer little shelter from wind.
  • Leafless canopy.
  • Surface with average Crown Ratio less than 0.2 (crowns less than 20% of tree height) and Canopy Cover less than 20%.
Wind Adj. Factor (WAF)Fuel ModelsBed Depth
0.5Grass (gr7, gr8, gr9)
Shr (4, sh4, sh5, sh7, sh8, sh9)
Slash (13, sb4)
More than 2.7 feet
0.4Grass & Grass-Shrub
(1, 2, 3, gr2, gr3,gr4, gr5, gr6, gs1, gs2, gs3, gs4)
(5, 6, 7, sh1, sh2, sh3, sh6)
Tbr-Undrsty (10, tu2, tu3)
Slash (11, 12, sb1, sb2, sb3
0.9 to 2.7 feet
0.3All Timber Litter Fuels
(8, 9, tl1 thru tl9)
gr1, tu1, tu4, tu5
Less than 0.9 foot

Partially Sheltered Fuels

  • Patchy timber.
  • Beneath canopy at midslope or higher with wind blowing directly at the slope.
Wind Adj. Factor (WAF)Fuel ModelsBed Depth
0.3All Fuel ModelsAny

Fully Sheltered Fuels

  • Under standing timber on flat or gentle slope.
  • Under standing timber near base of mountain with steep slopes above.
Wind Adj. Factor (WAF)Fuel ModelsBed Depth
0.2Open CanopyAny
0.1Dense CanopyAny


PRINT FBFRG Estimating Winds for Fire Behavior


Text (indexed):
  1. Hot-Dry-Windy Index
  2. Summary
  3. Critical Wind Events
  4. Hot, Dry, and Unstable Events
  5. Fire Slowing or Stopping Patterns

Hot-Dry-Windy Index

The Hot-Dry-Windy Index (HDW) was designed to help users determine which days are more likely to have adverse atmospheric conditions that make it more difficult to manage a wildland fire. It combines weather data from the surface and low levels of the atmosphere into a first-look product. HDW was designed to be very simple – a multiplication of the maximum wind speed and maximum vapor pressure deficit (VPD) in the lowest 50 or so millibars in the atmosphere. Because HDW is affected by heat, moisture, and wind, seasonal and regional variability can be found when comparing HDW values from different locations and times.


The four critical weather elements that produce extreme fire behavior are low relative humidity, strong surface wind, unstable air, and drought. The critical fire weather patterns that support these conditions can be separated into two primary categories: those that produce strong surface winds, and those that produce atmospheric instability. In both cases, an unusually dry airmass for the region and season must also occur. In brush and timber fuels, drought becomes an important precursor by increasing fuel availability.

Most periods of critical fire weather occur in transition zones between high- and low-pressure systems, both at the surface and in the upper air. The surface pressure patterns of most concern are those associated with cold fronts and terrain-induced foehn winds. Cold front passages are important to firefighters because of strong, shifting winds, and unstable air that can enhance the smoke column or produce thunderstorms. Foehn winds occur on the lee side of mountain ranges and are typically very strong, often occurring suddenly with drastic warming and drying. The area between the upper ridge and upper trough has the most critical upper air pattern because of unstable air and strong winds aloft that descend to ground level.

East of the Rocky Mountains, most critical fire weather patterns are associated with the periphery of high-pressure areas, particularly in the pre-frontal and post-frontal areas.

In the northern plains, Great Lakes, and the northeastern US, pre-frontal high pressure from the Pacific, Northwestern Canada, and Hudson Bay all can produce very dry conditions. Cold fronts produce relatively short lived periods of high winds and instability that can produce extreme fire behavior.

In the southeastern US, drought is frequently associated with the La Niña state of the southern oscillation pattern or a blocking ridge aloft near the Atlantic coast. Often critical weather patterns follow the frontal passage that brings extremely dry air due to a strong westerly or northwesterly flow. Look for strong winds that accompany the flow. Beware of advancing tropical storms as well.

In the southwestern US, the breakdown of the upper ridge, before monsoons develop, is manifest at the surface with breezy, dry, unstable conditions that transition to potentially very windy conditions as it finally breaks down. During transition to the monsoon pattern, shallow monsoons can produce gusty wind, low RH, and lightning without much precipitation.

In the Rocky Mountain and Intermountain Regions, the most significant pattern is the upper ridge-surface thermal trough that produces a dry and windy surface cold front.

Typical Ridge Breakdown in western US. For Rocky Mountain and Intermountain regions, the Upper Ridge/Surface thermal trough produces dry windy conditions at the surface.

  • Along the eastern slopes of the Rocky Mountains, weather patterns producing Chinook winds bring strong downslope winds that are unusually dry and warm.
  • In the intermountain west, critical fire weather is associated with upper troughs and overhead jet streams, or surface dry cold front passages.

Along the Pacific Coast, from Washington to California, weather patterns producing offshore flow or foehn wind are the most important.

In the Pacific Northwest, the east wind produces strong winds and dry air west of the cascades. The upper ridge breakdown is similar to that described for the rocky mountain & interior west.

In California, the most important are the north and mono winds of north & central regions and the Santa Ana and sundowner winds of southern California. The subtropical high aloft bring heat waves.

In Alaska, the primary pattern is the breakdown of the upper ridge with a southeast flow. It can bring gusty winds and dry lightning to the interior of Alaska after a period of hot, dry weather.

These are key words and catch phrases meteorologists typically use to describe critical fire weather growing and slowing patterns. These terms will often be used to explain weather patterns but are not exclusively used. The terminology will often be found in National Weather Service Area Forecast Discussion (AFD) and fire weather planning forecast discussions as well as predictive service 7-day outlook assessments.

Critical Wind Events

Breakdown of the Upper Ridge and Cold Frontal Passage

Breakdown of the upper ridge involves three main stages:

  • First stage represents warmer-drier-breezy and unstable conditions.  
  • Second stage wind speeds will increase while conditions remain warm-dry and unstable.
  • Third stage is defined by a cold frontal passage.

Breakdown of the upper ridge critical weather pattern.

Significant fire growth across the west and Alaska can be tied to all three stages but occurs most frequently during the second stage. Significant fire growth across the east is primarily related to post-cold frontal conditions or the third stage, but can occur during the second stage.

Cold Front Passage and Fire Growth. This graphic displays the frequency of fire growth events and their position with respect to position of the associated cold front.

Analysis of locations for fire growth with respect to cold frontal passage and generally breakdown of high pressure ridge. CFA is after the cold front passage, CFB is before cold front passage, WSL is warm sector of Low, and WS is warm sector of departing High.

Foehn or Downslope Winds

Foehn or downslope wind events have many regional names. You might recall that foehn or downslope winds are caused by air-forced over mountain ranges and through mountain passes in association with stable conditions. Common examples are Santa Ana and Chinook winds.

Foehn Winds are produced when stable subsiding air pushes up and over blocking ridges into areas of low pressure.

Thunderstorm Dynamics, Outflows, and Downbursts

Thunderstorms in the vicinity of a fire have the potential to produce outflow gust fronts or downbursts, regardless of whether the updraft is fed by the fire, or not. Any evidence of precipitation means the storm has developed to the point where it can produce these types of winds, as well as lightning. Rain at the ground or virga is a potential warning sign. Outflow gust fronts are winds radiating outward but primarily in the direction of storm motion, from the base of the convection. They are present in all well-developed convection and last tens of minutes to an hour or more. They can travel tens to hundreds of kilometers. Downbursts are much less common, shorter lived, and affect a much smaller area. Either type of wind has the potential to abruptly change the speed and direction of fire spread.

Thunderstorms and other strong convective forces can produce outflow gust fronts or downbursts when the convective forces weaken.

Sea Breeze Fronts

Sea breeze or sea breeze fronts can bring gusty, shifting winds and changes in humidity and stability that can drive fire behavior along coastal regions. The few hours leading up to the onset of the sea breeze are the warmest and driest and coincide with increasing wind speeds and unstable conditions. Following the passage of the sea breeze front, conditions will become cooler as well as more humid and stable. Sea breezes are more critical than land breezes because they occur during daylight hours.

Tropical Systems

Tropical systems, including tropical storms and hurricanes, produce an area of relatively warm, dry, and windy conditions around their northern and western periphery as they move ashore.

Hot, Dry, and Unstable Events

Critical fire growth periods are also tied to hot, dry, and unstable weather patterns. These patterns are generally tied to an upper ridge and a strong mid-level dry intrusion. The upper ridge and dry intrusion are ingredients that oftentimes set up the breakdown of the upper ridge pattern. A strong heat bubble combined with unusual mixing will create above normal temperatures, sometimes a heat wave, and very low day and nighttime humidity values. The unusual mixing is caused by an unstable atmosphere related to the heat bubble.

Thermal lows can develop near the surface and help concentrate this instability. The hot, dry, and unstable weather pattern is typically related to the subtropical or Bermuda high. Subtropical highs typically impact the western half of the US and Bermuda highs the eastern half. On rare occasions the highs will coalesce and create a super high which can impact large portions of the country.

Fire Slowing or Fire-Stopping Patterns

There are three primary reasons why geographical areas experience fire slowing and/or fire stopping periods; they are related to partial or whole-scale change in the weather and fuel regime. Such change includes partial green-up or fuel moistening promoted by periods of precipitation. Such change also includes temporary changes such as a cool, moist, stable weather regime replacing hot, dry, and unstable conditions during a multi-day period. Understand that the fire slowing and/or fire stopping period represents a temporary change.

There are four main fire slowing or stopping patterns across the country:

  • Closed Low-Deep Trough-Frontal Passages
  • Monsoon Bursts
  • Tropical storms
  • Smoke events

The season-ending period is like the fire slowing period with the main differences being the degree of change in fuels and weather conditions and how long they persist. During the season-ending period, there is an overwhelming change to fuel conditions, such as long lasting green-up or a significant rise in larger sized fuel moisture values. For most geographical areas, there is not just one event that brings the season’s end. It is an accumulative effect of a few or several weather events. For example, the southwest monsoon develops during a span of several days to weeks and brings about a mosaic change to the live and dead fuels.


PRINT FBFRG Critical Fire Weather


Text (indexed):
  1. Drought Assessments
  2. Local Climatology and Current Season Trends
  3. Regional Fire Seasonality

Drought Assessments

Meteorological Indicators

A wide range of weather based indices are available, based on accumulated precipitation alone, as well as precipitation combined with modeled evaporation and/or transpiration rates. These include spatial representations of soil moisture, vegetative stress, agriculture, and water supply. Many can be found using the assessment resources listed below.

National Fire Danger Rating System (NFDRS) includes the 1000-hr time lag fuel moisture, Energy Release Component (ERC), Growing Season Index (GSI), and Keetch-Byram Drought Index (KBDI) among its outputs. See Fire Danger Section.

Canadian Forest Fire Danger Rating System (CFFDRS) includes the Duff Moisture Code (DMC), Drought Code (DC), and Buildup Index (BUI) among its codes and indices. See CFFDRS Section.

Evaporative Demand Drought Index (EDDI) is an experimental drought monitoring and early warning guidance tool. It examines how anomalous the atmospheric evaporative demand (E0; also known as "the thirst of the atmosphere") is for a given location and across a time period of interest.

Standardized Precipitation Evapotranspiration Index (SPEI)  can measure drought severity according to its intensity and duration, and can identify the onset and end of drought episodes and allows comparison of drought severity through time and space, since it can be calculated over a wide range of climates

Evaporative Stress Index (ESI) describes temporal anomalies in evapotranspiration (ET), highlighting areas with anomalously high or low rates of water use across the land surface.

Standardized Precipitation Index (SPI) is the number of standard deviations that the observed value would deviate from the long-term mean. Since precipitation is not normally distributed, a transformation is first applied so that the transformed precipitation values follow a normal distribution.

Quantitative Precipitation Estimate (QPE) show spatial distribution of precipitation are multi-model estimates. Using a multi-sensor approach, it is one of the best sources of timely, high resolution precipitation information available. 

Assessments Resources

The US Global Climate Change Research Program (USGCRP) is mandated by Congress in the Global Change Research Act (GCRA) of 1990 to assist the Nation and the world to understand, assess, predict, and respond to human-induced and natural processes of global change.

NOAA is a source of timely and authoritative scientific data and information about climate. It provides news items, maps and data, and teaching resources.

Western Water Assessment NOAA Integrated Sciences and Assessments

Drought Monitor National Drought Mitigation Center

National Integrated Drought Information System National Centers for Environmental Information

National Drought Mitigation Center University of Nebraska – Lincoln

River Forecast Centers NWS Advanced Hydrological Prediction Services provides depictions of river flows and flooding; rain and snow fall in graphic and digital formats

Local Climatology and Current Season Trends

Evaluate Fire Occurrence Patterns

FireFamily Plus depictions of fire occurrence patterns are good for evaluating ignition patterns, but may provide little insight to climatology and fire growth in regions where incidents commonly exhibit multiple growth events during extended periods of active fire behavior.

Firefamily Plus Fire Occurrence Summary

Identify Normal Seasonal Trends

Local Winds Climatology

Wind roses are available in FireFamily Plus, Western Regional Climate Center, and in other tools. Ensure it includes only relevant winds, (e.g., exclude other seasons, night-time winds, etc.)

Example Wind Rose that shows graphically the probability of different windspeed and wind direction combinations.

Fire Season Severity

Use Appropriate Fire Potential Indicators (ERC, BUI) and determine season start, peak season, shoulder seasons, and season end.

Example Fire Season Climatology Graph. Minimum, Maximum, and Average trend lines represent the historic range of values for the identified season variable. Trends can help identify and segregate significant portions of the fire season.

Current Trends and Historic Norms/Extremes

General Trends

Evaluate and depict current conditions spatially, using a combination of drought assessment resources appropriate for the area of interest.

General Current Season Trends. Image on the left shows an example of the Drought Monitor that is based on several drought indicators. The image on the right shows a climatology graph with individual season trends overlaid to evaluate departures from normal conditions.

Current Local Conditions

Graphical Time Series depictions can highlight seasonal departures from norms and exceptional events. This FireFamily Plus Climatology graphic includes historic range (average, max, min), current year, and analog year.

Consult with Local Managers and Experts.

Get their help evaluating the objective analysis and to identify any local anomalies that may not be apparent.

Evaluate historic trends for weather that slows or stops fire growth

Fire Stopping Events

Originally reported by Latham and Rothermel (1993) from opinions of persons familiar with fire and fire weather in the Northern Rockies, example criteria were suggested as 0.5 inches of rain accumulated in 5 days or less. However, other fire potential indicators, such as cloud cover and relative humidity, can help identify periods of continuous low- or no-spread days during a fire season in a locality. These discrete events may not signal the end of the fire or the season. As such, it may be just as important to identify the frequency with which they occur and the duration of their influence as it is to predict a waiting time for the next event.

Fire Season-Ending Date

It is possible to identify the date in a fire season when fire growth is no longer likely or possible. This is generally understood to be the season end. If a fire’s threat to values of concern is more imminent or it is early in the fire season, a prediction of the season end may be less important than suggesting if and when a weather event will put the fire out. In bimodal seasons, such as the spring seasons in the southwest and the lake states, weather criteria can suggest fire ending dates in the early “season”, even though fire potential is expected to rise again in subsequent periods. Anticipating this date may be critical to strategic decisions as the season end approaches.

Event Frequency and Duration

As suggested above and depicted here, it may be valuable to identify the frequency of fire slowing or stopping events, especially if they are more common, such as in the eastern U.S. FireFamily Plus Event Locator can be used to evaluate data from a local RAWS station.

Precipitation Event Frequency. For fire slowing and stopping potential, frequencies of significant events, such as precipitation, can be helpful in assessing the likelihood they may occur. This may be especially valuable in areas where repeated events are anticipated.

TERM Waiting Time Distribution

FireFamily Plus (version 4.1) includes a TERM tool, in the Weather menu, to produce a waiting time distribution of historic fire- or season-ending dates. For each year evaluated, a single date is selected as the ending date based on established criteria. These dates are recorded and the distribution plotted to estimate the probability that the fire or season will end by a specific date.

Fire/Season Stopping Ending Likelihood, displayed as a probability density function.

Regional Fire Seasonality

The basic climate/weather factors temperature (hot vs. cold), atmospheric moisture (dry vs. moist), and wind patterns affect the fuel conditions and the tendency for fire start and spread. Fire season characteristics are driven by seasonal and continental-scale weather patterns, their movement, and variation. Seasonal air mass and jet stream changes affect various regions at different times and in different ways.

Map of the continental US with Peak Regional Fire Seasons shown. NW Jun-Oct, North and South CA May-Oct, Great Basin Jun-Sep, Mountains Jun-Sep, Plains Spring and Fall, Great Lakes and NE Mar-May and Oct-Nov, SE Feb-May and Oct-Nov.

The following will be key words and catch phrases meteorologists typically use to describe critical fire weather growing and slowing patterns. These terms will often be used to explain weather patterns but not exclusively used. The terminology will often be found in National Weather Service Area Forecast (AFD) and fire weather planning forecast discussions as well as Predictive Service 7-day outlook assessments.



  • Winter – generally very cold and dry.
  • Spring – cold and dry early, then warming with increasing downslope wind event potential.
  • Summer – warm and dry with lightning in June, then gradually moistening. Occasional wind events.
  • Fall – moist initially, then back towards winter conditions.

Fire Activity

  • Peak fire activity late spring and summer coincident with warmest/driest conditions, and wind event and dry lightning potential
  • Great majority of activity in interior between Alaska and Brooks ranges
  • Season ramps up quickly after melt-off and strongly relates to length of day
  • Season ends quickly with late summer/early fall moisture increase

Alaska Seasonal Fire Occurrence and Area Burned distribution.

Critical Weather Events

  • Foehn and Downslope wind - Glacial Katabatic downstream from glaciers, e.g. Juneau fjords, Alaska Range Chinook in the western Tanana Valley, Hillside Katabatic Winds, e.g. Anchorage Bowl, and Yukon Chinook winds in the eastern interior and through the Brooks Range.
  • Breakdown of the Upper Ridge - Boreal interior area from Galena to Fort Yukon, warming-drying ahead of the low-pressure system originating from the Sea of Okhotsk with gusty W-SW winds, and Low Pressure moving inland and loses wetting characteristics but keeps enough moisture for drier storms.

Fire Slowing or Stopping Events

  • Closed low/occluded low is a low-pressure system that originate from the Sea of Okhotsk and Bering Sea moves inland and stays for a multi-day period or a persistent moist southwest flow impacting the coastal areas.
  • Marine Inversion: coastal areas of Alaska especially during night.

Fire Growth Potential Indicators

  • FFMC and BUI, ISI and FWI



  • Winter/Spring – cool and moist with frequent and abundant precipitation, especially western portion of area. Relatively dry east.
  • Summer – some windy and dry potential early, then becoming generally warm and dry with infrequent wind events due to dry cold fronts.
  • Fall – return of cooler, more moist conditions ushered in by a period of windy, dry conditions with cold frontal passages. Potential for dry offshore wind events behind storm systems.

Fire Activity

  • Fire activity peaks in summer due to increasingly warm and dry conditions and potential for wind and lightning with dry cold frontal passages.
  • Rapid decrease in activity in fall with Pacific moisture on the increase, though this the peak period for dry offshore wind events and a few dry cold front passages are still possible.
  • Little to no activity late fall through spring.

Northwest Seasonal Fire Occurrence and Area Burned distribution

Critical Weather Events

  • Thermal Low/Subtropical Ridge
  • Breakdown of the Upper Ridge and Passage of a dry cold front
  • Foehn or Downslope Wind (East Wind west slopes of Cascades and Chinook Wind east slopes of the Cascades)

Fire Slowing or Stopping Events

  • Closed Lows/Wet Cold Front
  • Marine Layer/Onshore flow
  • Smoke Events

Fire Growth Potential Indicators

  • Energy Release Component
  • 100-hr fuel moisture
  • AVHRR satellite NDVI DA and RG
  • NWS QPE (30-60 days)
  • Drought Monitor

Northern California


  • Winter/Early Spring – cool and moist with regular precipitation events, especially in the mountains.
  • Late Spring/Summer – some windy/dry potential early, then generally warm and dry with infrequent wind events due to dry cold front influences.
  • Fall – return of cooler, more moist conditions ushered in by a period of windy, dry conditions with cold frontal passages. Potential for dry, north through east wind events behind storm systems.

Fire Activity

  • Fire activity peaks in summer due to increasingly warm and dry conditions and potential for wind and lightning with infrequent dry cold frontal passages.
  • Rapid decrease in activity by late fall with Pacific moisture on the increase, though peak period for dry northeast wind events.
  • Little to no activity late fall through early spring.

Northern California seasonal Fire Occurrence and Area Burned distribution

Critical Weather Events

  • Foehn or Downslope Wind (Mono, North Winds)
  • Breakdown of the Upper Ridge in the Interior
  • Subtropical Ridge/Thermal low

Fire Slowing or Stopping Events

  • Closed Low/Pacific Trough
  • Marine Layer/Onshore flow
  • Smoke Events

Fire Growth Potential Indicators

  • Spread Component (SC)
  • Burning Index (BI)
  • Energy Release Component (ERC)
  • Live Fuel Index (LFI)/Growing Season Index (GSI)
  • AVHRR satellite NDVI DA and RG
  • NWS QPE (30-60 days)
  • Drought Monitor

Southern California


  • Winter – occasional storm systems with mainly mountain precipitation. Inland intrusions of cool, moist Pacific air. Relatively dry inland lower elevations.
  • Spring – less frequent precipitation events and substantial inland intrusions of marine air.
  • Summer - hot and dry inland and maritime influence along coast. Occasional influx of monsoon moisture from southeast.
  • Fall – end of any monsoon moisture influence and begin of gradual inland shift in marine air mass. Period of greatest potential for dry offshore wind events.

Fire Activity

  • Fire activity peaks late spring through fall, when influence of maritime air is diminished.
  • Greatest potential for offshore wind events in the fall, when fuels are often driest.
  • Little activity winter-early spring due to maritime influence.
  • Fires possible at any time with offshore wind events.

Southern California Seasonal Fire Occurrence and Area Burned distribution

Critical Weather Events

  • Foehn or Downslope wind (Santa Ana and Sundowners)
  • Breakdown of the Upper Ridge away from the coasts
  • Subtropical Ridge

Fire Slowing or Stopping Events

  • Marine Layer/Onshore Flow
  • Closed Low/Pacific Trough

Fire Growth Potential Indicators

  • Spread Component (SC)
  • Burning Index (BI)
  • Energy Release Component (ERC)
  • National Fuel Moisture Database
  • Live Fuel Index (LFI)/Growing Season Index (GSI)
  • AVHRR satellite NDVI DA and RG
  • NWS QPE (30-60 days)
  • Drought Monitor



  • Winter – cool to cold with occasional precipitation. Dry, downslope winds possible in lee of Rockies.
  • Spring – warming, windy and dry transitioning to hot and dry.
  • Summer – hot and dry gives way to warm and moist abruptly with monsoon.
  • Fall – turning much drier and mild. Potential for few wind events followed by dropping temperatures.

Fire Activity

  • Fire activity increases in spring as it transitions from windy and dry to hot and dry.
  • Peak from May – mid-July, with monsoon thereafter.
  • Rare secondary fall season as moisture exits and jet drops south and wind event potential returns.
  • Little activity late fall - early winter.

Southwest Seasonal Fire Occurrence and Area Burned distribution

Critical Weather Events

  • Breakdown of the Upper Ridge
  • Subtropical Ridge
  • Monsoon transition (Edge of a Monsoon Burst and Edge of Back Door Cold Front)
  • Foehn or Downslope wind
  • Low Level Jet on Rangeland of the Front Range
  • Surface Dryline Passage on Rangeland of the Front Range

Fire Slowing or Stopping Events

  • Closed Low-Cold Frontal Passage
  • Back Door Cold Front
  • Monsoon Burst

Fire Growth Potential Indicators

  • ERC and BI
  • NFMD
  • AVHRR satellite NDVI RG and DA
  • NASA SPoRT RSM (0 to 10 cm)
  • NWS QPE (30 day)
  • Drought Monitor

Great Basin


  • Winter – periodic precipitation, mainly over mountains.
  • Spring – becoming windy, dry, and warmer.
  • Summer – hot and dry. Periodic wind events north and moisture surges south.
  • Fall – period of windy and dry conditions often followed by period of fair and dry weather before cooler temperatures and increased precipitation potential.

Fire Activity

  • Generally fine fuel types, fire season dependent on cured fuels and windy/dry conditions.
  • These conditions occur almost exclusively in the summer.
  • Little to no activity outside of summer.

Great Basin seasonal Fire Occurrence and Area Burned distribution

Critical Weather Events

  • Breakdown of the Upper Ridge
  • Subtropical Ridge
  • Edge of a Monsoon Burst (Hybrid)
  • Foehn or Downslope Wind (Chinooks down east slopes of the Sierras and west slopes of the Wasatch Mountains)

Fire Slowing or Stopping Events

  • Closed Low/Pacific trough
  • Monsoon Burst-duration of 3 days or more

Fire Growth Potential Indicators

  • ERC and BI
  • National Fuel Moisture Database
  • AVHRR satellite NDVI DA and RG
  • NWS QPE (30-60 days)
  • NASA SPoRT RSM 0-10 cm/GVF
  • Drought Monitor

Northern/Central Rockies and Great Plains


  • Winter – regular storm systems and precipitation, especially over mountains. Cold overall with potential for artic air intrusions.
  • Spring – period of heaviest precipitation in the mountains, but greatest Chinook wind potential in lee of Rockies and adjacent plains.
  • Summer – warm and dry over most mountain areas with occasional wind events north. Increasingly moist across the plains and far south.
  • Fall – period of windy/dry potential, then fairly dry and mild until temperatures drop and moisture increases.

Fire Activity

  • Fire activity on the plains peaks in spring and fall when windy/dry periods are coincident with dormant or cured fine fuels.
  • Fire activity in the mountains peaks in the summer, when it’s warmest and driest and some dry cold frontal passages are possible.
  • Little to no activity late fall through early spring.

Rockies and Great Plains seasonal Fire Occurrence and Area Burned distribution

Critical Weather Events

  • Breakdown of the Upper Ridge (Dynamic dry slot and Dry Cold Front)
  • Subtropical Ridge (Mid-level dry intrusion)
  • Edge of a Monsoon Burst (Hybrid)
  • Foehn or Downslope Wind (Chinook)
  • Low Level Jet and Surface Dryline on the Great Plains

Fire Slowing or Stopping Events

  • Closed Low-Pacific Trough-Cold Frontal Passage
  • Monsoon Burst
  • Smoke Event

Fire Growth Potential Indicators

  • ERC and BI
  • National Fuel Moisture Database
  • Live Fuel Index (LFI)/Growing Season Index (GSI)
  • AVHRR satellite NDVI DA and RG
  • NWS QPE (30-60 days)
  • Drought Monitor

Great Lakes and Northeast


  • Winter – generally cold with dry periods between widespread periodic precipitation.
  • Spring – warmer, windier, and drier. Driest immediately behind storm systems.
  • Summer – generally warm and humid under Bermuda High influence. Occasional windy/dry events far north.
  • Fall – turning much drier, then generally mild and dry with potential for windy and dry periods before temperatures drop.

Fire Activity

  • Fire activity maxima in spring and fall, coincident with windy periods near jet stream
  • Building warmth and dormant fine fuels in spring, leaf-off in fall
  • Season can extend well into summer far north if jet remains active and brings windy/dry events that are preceded by dry conditions of two weeks or more
  • Little or no activity winter months

Great Lakes and Northeast seasonal Fire Occurrence and Area Burned distribution

Critical Weather Events

  • Post Cold Frontal
  • Pre-Cold Frontal Southwest Wind cases
  • Bermuda High

Fire Slowing or Stopping Events

  • Cold Frontal Passage
  • Stationary Front
  • Closed Low

Fire Growth Potential Indicators

Canadian Forest Fire Danger Rating System

  • Build-Up Index (BUI)
  • Fire Weather Index (FWI)
  • Initial Spread Index (ISI)

National Fire Danger Rating System

  • Ignition Component (IC)
  • Spread Component (SC)
  • Energy Release Component (ERC)



  • Winter – generally driest time of year with greatest wind event potential behind passing storms, though widespread precipitation can also occur.
  • Spring – windy/dry potential retreats north, and warm, moist conditions become increasingly dominant.
  • Summer – warm to hot and humid with light winds. Occasional dry spells. Tropical cyclone activity increases late in the season.
  • Fall – very moist initially, then gradual infiltration of dry air. Moist conditions often persist along Gulf Coast.

Fire Activity

  • Fire activity maxima in late winter / early spring and fall, coincident with greatest potential for windy/dry conditions behind passing storm systems.
  • Dormant fine fuels with low live fuel moisture in winter and spring, leaf-off in fall in northern portion of region.
  • Season can extend year-round anytime warm/moist air becomes suppressed south and east.
  • Usually little activity summer months, though significant fire activity has historically occurred during unusual dry spells.

Southeast seasonal Fire Occurrence and Area Burned distribution

Critical Weather Events

  • Post Cold Frontal
  • Westerly Downslope Wind in the Appalachians and Ozarks
  • Sea Breeze
  • Tropical Storms
  • Bermuda High

Fire Slowing or Stopping Events

  • Closed Low/cold frontal passage
  • Stationary Front
  • Tropical Storm
  • Sea Breeze

Fire Growth Potential Indicators

  • ERC
  • 100 hr Fuel Moisture
  • Keetch-Byram Drought Index (KBDI) is sometimes misused
  • Standardized Precipitation Index (SPI)
  • Crop Moisture Stress Index
  • NWS QPE (30 to 60 day)


PRINT FBFRG Fire Season Climatology


Text (indexed):
  1. Fire Weather Apps
  2. Fireline Observations
  3. Wind Observations and Estimations
  4. Temperature and Humidity Observation
  5. Sky Observations
  6. Automated Weather Stations

Weather is the Most Variable Element when Anticipating Fire Behavior

Take time to review weather forecasts and observe weather changes, fireline observations, and monitoring automated weather stations are helpful to supplement information from forecasts. Single Resource (crew, squad, and individual) are responsible for ensuring that they keep informed of fire weather conditions and forecasts so that they may base all actions on current and expected behavior of the fire. The procedures include obtaining and reviewing latest forecasts, taking observations to validate them through the assignment, reporting what is learned to those who need the information, and requesting forecast updates when appropriate.

Fire Weather Apps

Fireline Observations

Location and Timing of Fireline Weather Observations

Below are four instances during a 24-hour period that are valuable in assessing forecasts and evaluating thresholds associated with fire behavior transitions:

  1. An early morning observation that represents time and conditions when the minimum temperature and maximum humidity occur.
  2. A late afternoon observation that represents the time and conditions when the maximum temperature and minimum humidity occur.
  3. When active fire behavior seems to increase and diminish during the burn period.
  4. Hourly throughout the afternoon or when changes occur, may be called for by fireline supervisors or dictated by changing conditions to ensure situational awareness.

 The weather observer should strive to pick observation sites that most accurately reflect environmental conditions around the fire’s location.

  • Decide whether a ridge-top, mid-slope, or drainage bottom location is most representative.
  • If on a slope, the aspect and slope steepness is an important consideration.
  • Consider what is a representative fuelbed for the fire.
  • Attempt to find a safe site upwind or on the flank of the fire. Generally, ventilated areas in the shade are desirable locations for the observation.
  • Minimize the fire’s influence on your observation. Avoid taking observations in the black. Avoid observations affected by gusty indraft breezes and radiant heat from the fireline.

Note the Type of Instruments Used

Record whether the observations were made with an electronic weather sensor or traditional sling psychrometer. Electronic temperature and humidity sensors should be calibrated regularly against weather instruments of reliable accuracy. Check the batteries.

Communicate and Document the Weather Observation

Accurate weather observation is of little use unless it is properly communicated in a timely fashion to those who need it. Make sure that current observations are reported verbally over the radio to ensure situational awareness.

  • Follow instructions for periodic radio reports to fireline supervisors and/or incident communications unit.
  • Report measurements with trends, i.e., Temperature: 75°, up 5º degrees from last hour.

Provide written documentation of weather observations to the fireline supervisor, situation unit, incident meteorologist, or the local weather forecast office. Retain a copy for your records. Don’t assume that weather observations are automatically being received by the proper users. The weather observer may need to take the initiative to verify that the information is being passed up the line. Forms are available.

Wind Observations and Estimates

Obtain Forecast from Incident Meteorologist or Fire Weather Forecaster

Wind speed and direction is the most variable weather factor over the duration of an assignment, the observer will be concerned with adjusting and validating forecasted winds as much as measuring current wind Speed. It is difficult for a meteorologist to produce localized wind forecasts, especially if the wind is influenced by terrain features. Forecasted winds will frequently need adjustment because they are representing a wind other than mid-flame, such as ridgetop or surface winds. Consider wind categories and definitions. It will be important to communicate with the meteorologist the factors that influence the wind measurements that are provided.

Use Surface Wind Estimation Worksheet

Report observation by type and/or height. Identify sheltering and aspect/slope position for the wind observation and note whether local winds are influencing the observation.

Consider Possibility of Critical Wind: Estimate or Validate 20 feet Surface Wind Speed

If the weather forecast product provides wind speed as free air or ridgetop, or if winds in the fire area are influenced by local winds, it may be necessary to use the worksheet for estimating 20 feet surface winds.

  • Identify speed and direction of any forecast critical wind.
  • Determine speed and direction of any local winds.
  • Determine speed and direction of general winds and whether they will influence the 20 feet wind.
  • Combine factors above into an estimate of local surface (20 feet) wind speed.

Visual Surface (20 feet) Wind Estimate - Modified Beaufort Scale

ClassWind SpeedTerminologyExampleVisible Effect
0Less than 1mphCalmIcon of visible wind effects as described in column 5 of this tableCalm, smoke rises vertically.
11 to 3mphVery Light BreezeIcon of visible wind effects as described in column 5 of this tableLeaves of quaking aspen in constant motion, small branches sway, tall grasses and weeds sway and bend with wind, wind vane barely moves.
24 to 7mphLight BreezeIcon of visible wind effects as described in column 5 of this tableTrees of pole size in the open sway gently, wind felt distinctly on face, leaves rustle, loose scraps of paper move, wind flutters small flag.
38 to 12mphGentle BreezeIcon of visible wind effects as described in column 5 of this tableLeaves, small twigs in constant motion, tops of trees in dense stands sway, light flags extended.
413 to 18mphModerate BreezeIcon of visible wind effects as described in column 5 of this tableTrees of pole size in the open sway violently, whole trees in dense stands sway noticeably, dust is raised in the road.
519 to 24mphFresh BreezeIcon of visible wind effects as described in column 5 of this tableBranchlets are broken from trees, inconvenience is felt in walking against wind.
625 to 31mphStrong BreezeIcon of visible wind effects as described in column 5 of this tableTree damage increases with occasional breaking of exposed tops and branches, progress impeded when walking against wind.
732 to 38mphModerate GaleIcon of visible wind effects as described in column 5 of this tableSevere damage to tree tops, very difficult to walk into wind, significant structural damage occurs.
839 to 46mphFresh GaleIcon of visible wind effects as described in column 5 of this tableSurfaced strong Santa Ana, intense stress on all exposed objects, vegetation, buildings, canopy offers virtually no protection.
947 to 54mphStrong GaleIcon of visible wind effects as described in column 5 of this tableSlight structural damage occurs, slate blown from roofs.
1055 to 63mphWhole GaleIcon of visible wind effects as described in column 5 of this tableSeldom experienced on land, trees broken, structural damage occurs.
1164 to 72mphStormIcon of visible wind effects as described in column 5 of this tableVery rarely experienced on land, usually with widespread damage.
1273mph or moreHurricane ForceIcon of visible wind effects as described in column 5 of this tableViolence and destruction.

Estimate or Validate Mid-flame Wind Speed

Eye-level wind speed is usually assumed to be the same as mid-flame wind speed. However, as suggested in the Fireline Assessment Method (FLAME) reference, it may be too low for flames in shrub fuels and too high for flames in forest litter. In any case, it may be necessary to adjust forecasted 20 feet winds or observed mid-flame wind speed to make comparisons and validate forecasts.

Observing Eye-Level Wind Speed in the Field

The observer should face directly into the wind and closely observe the wind speed indicator fluctuations. Exposure to sunlight is not a concern during the wind observation.

  • An eye-level wind speed measurement requires at least one full minute of sampling and preferably more.
  • Note time and rapidity of transitions in diurnal winds.
  • When using a Dwyer tube, mentally average the wind speed and note the peak gust during the sampling period.
  • Electronic sensors make wind averaging and gust measurement easy. They are more accurate and are preferred for eye level wind speed observations.
  • Remember - the wind direction is defined as the direction the wind is coming from.

Estimate Effective Wind Speed for Slope Influence

The influence of slope on fire spread is applied as a slope-equivalent wind speed.

Where slope is significant (generally 20% or more), all the fire behavior assessment tools in the Surface Fire Section, Surface Fire Behavior Worksheet, (FLAME, Lookup Tables, Nomograms & Nomographs, and BehavePlus) provide means for estimating effective wind speed.

Adjusted slope wind speed should be used in place of mid-flame wind speed estimate in fire behavior predictions.

Temperature and Relative Humidity Observation

Estimating temperature, relative humidity, and dew point can provide insight to critical fire behavior thresholds for ignition and crown fire potential.

Sling Psychrometer Use

The following are instructions for determining wet and dry bulb temperatures using the sling psychrometer. These instructions are based on those from page 259 of the S-290 Instructors Manual. Additional comments have been added.

  1. If your sling has been in your pack, you may need to hang it in a tree, in the shade, to let it adjust to the outside air temperature. This may be a good time to take the wind observation.
  2. Stand in a shaded, open area away from objects that might be struck during whirling. If in open country, use your body shade to shade the psychrometer. If possible, take weather observations over a fuelbed that is representative of the fuel that the fire is burning in. Stay away from heat sinks.
  3. Face the wind to avoid influence of body heat on the thermometers.
  4. Saturate the wick of the wet bulb with clean, mineral free water (distilled, if available) at air temperature.
  5. Ventilate thermometers by whirling at full arm’s length. Your arm should be parallel to the ground. Whirl for one minute.
  6. Note the wet bulb temperature. Whirl for another 40 or 50 times and read again. If the wet bulb is lower than the first reading, continue to whirl and read until it will go no lower. Read and record the lowest point. If the wet bulb is not read at the lowest point, the calculated relative RH will be too high. Calculate dew point each time. If it is changing significantly it may suggest a bad observation.
  7. Read the dry bulb immediately after the lowest wet bulb reading is obtained.
  8. Determine the RH from the tables.

Important Tips - sometimes beginners do not take accurate psychrometer readings because of the following common mistakes:

  • Changing psychrometers from one observation to the next, try to use the same throughout.
  • Not ventilating the psychrometer long enough to reach equilibrium.
  • Not getting the wick wet enough, or letting it dry out.
  • Holding it too close to the body or taking too long to read the thermometers.
  • Touching the bulb ends with the hands while reading.
  • Not facing into the breeze.

Estimating Relative Humidity and Dew Point from Psychometric Tables

Psychometric tables are included in the belt weather kit and provided on this site. The tables allow you to estimate RH and dew point from dry bulb and wet bulb temperatures.

  1. Find the correct table based on elevation at your observing location.
  2. Use your DB Temp and WB Temp to find the intersecting cell on the page.
  3. Read the resulting RH (below) and dew point (above) in that cell.

Example Table

Each Table is labeled with an Elevation Range, including an adjustment for Alaska.

Dry bulb Temperature is located on the left axis and the wet bulb temp is located at the top of each column. Cell at their intersection includes the resulting RH and dew point.

Temperature, Relative Humidity and Dew Point Tables are used to convert fireline measurement of dry bulb and wet bulb temperatures into estimates of Relative Humidity and Dew Point. Requires observation elevation, and the two temperature values.”

Adjusting Relative Humidity for Changes in Temperature and Elevation

Under certain circumstances, it may not be possible to estimate RH for a particular elevation. It may be necessary to make a field adjustment to forecasted RH for a time later in the burn period. In both cases, given that the air mass is unchanging and fairly neutral, it is possible to use current estimates of dew point and temperature and to make adjustments in both cases:

Case 1: Estimate RH for an elevation above or below the observation - assuming an average lapse rate of approximately 4° F, increase the temperature by 4° F for each 1000 feet drop in elevation or decrease it by 4° F for each 1000 feet increase in elevation. Using the new temperature and the estimated dew point, look up the new RH in the appropriate psychometric table.

Case 2: Validate a forecasted RH - using the estimated dew point and the forecasted temperature, look up the new RH in the appropriate psychometric table.

Vapor Pressure Deficit (VPD)

While RH refers to the amount of water vapor in the air as a percentage of saturation levels, Vapor Pressure Deficit represents an absolute measure of the difference between the moisture in the air and the amount it could hold when saturated.

VPD rises as the moisture deficit increases and may seem counter-intuitive for users comfortable using RH. It follows a seasonal trend of low levels in the winter and higher levels during the warm summer months, controlled by variation in temperature and atmospheric humidity.

VPD can provide important insight about the role of ambient temperature as well as atmospheric humidity. For example, at low temperatures a low RH will not be accompanied by significantly high VPD levels. But that same low RH under high temperatures will produce elevated VPD. The table below here provides an example interpretation.

Vapor Pressure Deficit, or VPD, is a measure of atmospheric humidity that emphasizes its effect on living vegetation. This table identifies a middle range, between 5 and 12, for best plant development. Above 12 produces moisture stress in plants. Below 5 may slow growth.

Long used in greenhouse and agricultural applications, it is a good indicator of the moisture stress experienced by green vegetation. The new Growing Season Index (GSI) uses it as a key criterion to green-up and curing phenology. GSI considers VPD of 9 mb optimum growing conditions.

The Crossover Concept (Alberta Forest Service 1985) refers to rising temperature (in °C) and falling RH reaching the point where they are equal (highlighted boxes in the table). Interpretations suggest the potential for extreme fire behavior.

Sky Observations

Airport Webcams are available at

Synoptic (Large-Scale) forecasts and representations of current conditions include reference to the relative stability of the atmosphere in the area. There are numerous indicators that can be reviewed and interpreted, several are referenced on the stability page.

A stable atmosphere generally tends to limit violent vertical motion. As a result, cloud build-ups during stable conditions tend to be wider and flatter, sometimes covering much of the sky. Note: strong general winds are possible during stable conditions depending upon the weather pattern. Unstable conditions tend to enhance vertical motion and increase ventilation of active fires.

General atmospheric conditions can be influenced by the terrain and other local factors to produce more localized effects. The weather observer can provide important information to meteorologists by reporting the visual cues and the timing of changes throughout the day. Visual cues are associated with a weather observation by recording them in the remarks column so that they get a time stamp. The firefighter should pay attention to the fire weather forecast and keep an eye on the sky for indicators of severe conditions that can influence the fire environment. Usually, if a visual cue is worth noting with the weather observation, photography can be very valuable supporting documentation. If a photo is taken, use a photo log or reference the photo number with the location date, time and other identifying comments.

Lightning and Wind

  • Lightning should be reported immediately to alert fireline supervisors to take appropriate precautions and to cue meteorologists to review their lightning detection tools.
  • Sudden wind shifts may be important indicators of breaking inversions or frontal passage.

Smoke, Dust, and Fire

  • Rising smoke column indicates neutral or instable conditions. Flattening column indicates inversion at that point.
  • Smoke column change direction as it rises indicates wind shear or local wind influence.
  • Smoke column developing a pyrocumulus cap cloud indicates strong instability and impending down drafts.
  • Haze and poor visibility are indicators of inversions. Is this localized (night-time inversion) or more general and persisting throughout the day? Note: if haze or poor visibility abates during the burn period, this is an indicator of increase in fire behavior.
  • Dust clouds radiating away from thunderstorms indicate potentially dangerous downdrafts.
  • Dust devils are important indicators of surface instability.
  • Firewhirls occur when convection from the fire combines with winds influencing the fire, adjacent terrain features that create eddies, instability from cold fronts, and/or multiple interacting fire plumes. Firewhirls are difficult to predict.

Note: Be aware of the potential for gusty erratic winds and firebrand transport when dust devils and firewhirls are observed.

Clouds, Fog, and Precipitation

Clouds occur when moisture in the atmosphere condenses into visible droplets or ice crystals. This usually occurs when moist air becomes cooled by lifting. The shape and texture of clouds reveals much about whether the lifting process has been gradual and gentle or rapid and potentially violent. Paying attention to the sky can help the firefighter stay aware of the current fire environment as well as anticipation of potential changes.

  • Cloud cover, in percent, is an important input for fuel moisture shading.
  • Building cumulus, towering cumulus, or thunderstorms are all indicators of significant instability that is probably already influencing surface winds.
  • Showers or virga may be indicators of instability.

The NWCG Fire Weather Cloud Chart, PMS 438, depicts sky signs of interest for wildland firefighters that are valuable tools in revealing the atmosphere’s current state as well as foretelling potential changes. Clouds are an important indicator of stability.

Clouds that reveal variations of instability in the atmosphere, as follows:

  • Cumulus (several varieties) - Weak instability. Normally not a concern for firefighters. However, when cumulus continues growing, firefighters are advised to keep an eye on the buildups due to the potential for sudden downdrafts and gusty winds.
  • Alto Cumulus (several varieties, e.g. castellanus) - Upper atmosphere instability and possible weather change. These indicate increasing moisture and instability with the potential for thunderstorms.
  • Cumulonimbus - Very unstable. Fully developed mature thunderstorms contain extreme vertical motion and the strong likelihood of gusty, erratic winds that can arise suddenly miles away from the cloud buildup. Localized wind gusts over 100 mph are possible with very strong thunderstorms along with lightning, virga, and hail. Very strong thunderstorms may also be accompanied by shelf clouds or tornados. Clearly, cumulonimbus clouds portend many hazards to the firefighter exposed on the fireline.
  • Pyrocumulus - Very unstable. Pyrocumulus clouds grow above ongoing wildfires drawing energy from the heat of combustion and condensation of moisture in the fire’s convection column. A white-capped pyrocumulus cloud is a concern for firefighters for the same reason as a thunderstorm - strong, gusty erratic winds can arise suddenly near a pyrocumulus. Virga, light raindrops, and even some lightning is possible with well-developed pyrocumulus clouds.

This image shows three cloud groups listed in descending order in the troposphere: 1. high clouds 16,000 to 50,000 ft 2. middle clouds 6,500 to 23,000 ft 3. low and vertically developed clouds up to 6,500 ft

Clouds that indicate a stable atmosphere, as follows:

  • Stratus (several varieties) - Stable and moist. Stratus clouds can cover much of the sky and blot out sunlight or even bring rain. Stratus clouds tend to mean higher humidity and decreased fire behavior. Normally not a concern for firefighters.
  • Cirrostratus (several varieties) - High level stratus clouds formed of ice crystals. Cirrostratus clouds are normally not a concern for firefighters. However, if these clouds increase from the west or northwest, a front may soon be approaching with strengthening general winds. Check the fire weather forecast.
  • Altostratus (several varieties) - Mid- to high-level stratus clouds that are a good indicator of an approaching front with strengthening general winds. Check the fire weather forecast.
  • Wave cloud or Lenticular cloud - Smooth, almond-shaped clouds that sometimes form over mountainous terrain in patterns similar to stacked dishes. These clouds tend to remain fixed over one peak and are a good indicator of strong general winds in the upper atmosphere that may descend to the surface. Wave clouds are sometimes seen during foehn wind events. Check the fire weather forecast.

Depiction of lenticular clouds. When they appear, anticipate increasing winds later in the afternoon.

Automated Weather Stations

A wide variety of weather observing networks are available, including:

Networks of Interest

  • Remote Automated Weather System (RAWS) are sited to assist land management agencies with monitoring air quality, fire weather, and support of research applications. There are a variety of standards, though the fire weather stations adhere to a different standard called for by the National Fire Danger Rating System (NFDRS).
  • Incident Remote Automatic Weather Stations (IRAWS) are intended for use on or near the fireline and can be rapidly relocated as desired by Fire Behavior Analysts (FBAs) or Incident Meteorologists (IMETs) to provide timely weather data. Fire Managers, FBAs and IMETs use IRAWS data to predict fire behavior, prescription burning times, fire weather forecasting, and canyon and ridge top winds. Generally, like RAWS equipment, mast heights may vary.
  • Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS) stations located generally near airports to serve aviation needs. ASOS stations also serve as a primary climatological observing network. They adhere to international standards for weather observations.
  • A wide variety of other station networks are available and may be appropriate for local and ad hoc uses.

Wind Observations from Automated Sensors

Generally, four factors govern the surface wind estimate produced by automated weather observing sensors.

  1. Local terrain influences on the general winds at any location due to exposure and differential surface heating related to slope, water and ice factors and channeling of general winds or air flow. Teh image below demonstrates the effect of terrain on wind measurements in different locations (Bishop, 2010).

Illustration showing when to use various wind adjustment factors in hills with vertical relief in the hundreds of feet. Use a factor of 1 for the upper parts of upwind slopes; a factor of .5 for the lower parts of upwind slopes; a factor of .75 for the upper parts of downwind slopes; and a factor of .25 for the lower parts of downwind slopes

  1. Sensor standards for timing and duration of observation - fire weather standard averages wind speed over 10 minutes while International standard averages wind speed over two minutes.
  2. Surface characteristics that produce differing friction factors - trees and buildings vs airports and agricultural regions. See figure.

Surface Wind Adjustment for Friction. This graphic illustrates the effect of surface roughness from trees and buildings. Typical RAWS (B) sense lower surface windspeeds due to surrounding forest cover.

Generally, gradient winds are reduced by friction from the earth’s surface. The surface friction in areas surrounded by large flat smooth surfaces (airports and agricultural areas) is less than that experienced in forest openings and in cities. (Lawson & Armitage, 2008)

  1. Sensor height above the prevailing cover. A “rough” surface represents forest clearings covered in low brush or slash whereas the “smooth” surface is used for clearings where the ground is smooth or covered in mowed grass or cropped brush. (Lawson & Armitage, 2008)
Mast Height (m)Rough Surface Adjustment FactorSmooth Surface Adjustment Factor


PRINT FBFRG Observing Fire Weather