Hot-Dry-Windy Index

Satellite image of fires (Grand Prix Fire, Old Fire and Piru Fire) being driven by Santa Ana winds.

Hot-Dry-Windy Index (HDWI, sometimes HDW) is a fire weather index used by wildfire forecasters and fire managers in the United States to identify days when atmospheric conditions are likely to make a wildland fire more difficult to control. The index combines three variables long recognized by fire behavior analysts as critical to fire spread — heat, dryness, and wind — into a single numerical value.

HDWI was introduced in a 2018 paper in the journal Atmosphere by a team of meteorologists from St. Cloud State University and the U.S. Forest Service. It was developed as a physically based alternative to the older Haines Index, which had been used operationally from 1988 until its discontinuation by the National Weather Service in 2025, and which did not account for wind and was never rigorously tested against historical fire behavior before its original adoption.

History

Fire meteorologists have long used the Haines Index (also called the Lower Atmospheric Severity Index) to anticipate days when weather would exacerbate wildfire behavior. Although the Haines Index gained wide operational use, its own creator, Forest Service meteorologist Donald Haines, acknowledged that it needed further refinement, and it lacked a wind component despite wind being one of the most important drivers of fire spread.

To address this gap, a team consisting of Alan F. Srock (St. Cloud State University) along with Joseph J. Charney, Brian E. Potter, and Scott L. Goodrick (U.S. Forest Service Research Stations) developed the Hot-Dry-Windy Index and published its formal definition in 2018. Following favorable results from field testing, the National Weather Service recommended that fire weather forecasters evaluate HDWI as an operational tool.

The original team's assessment of the Haines Index's shortcomings was later reinforced by an interagency review: in 2024, the National Wildfire Coordinating Group's Fire Weather Subcommittee concluded that the Haines Index (along with the unrelated Lightning Activity Level metric) should no longer be part of National Weather Service forecasts or NWCG training, on the grounds that peer-reviewed research did not support its ability to forecast major fire growth. The change took effect starting with the 2025 fire season, with Mixing Height—rather than HDWI—identified as the primary replacement metric for the Haines Index.

Calculation

HDWI is calculated as the product of the maximum wind speed and the maximum vapor pressure deficit (VPD) found within roughly the lowest 500 meters (about 50 hPa) of the atmosphere above a given location:

$\mathrm{H}\mathrm{D}\mathrm{W}=U\times \mathrm{V}\mathrm{P}\mathrm{D}(T,q)$

where HDW is the resulting index value, U is wind speed (in m/s) and VPD is the vapor pressure deficit, a function of temperature (T) and moisture content (q), expressed in hectopascals. VPD itself is defined as the difference between the air's saturation vapor pressure and its actual vapor pressure:

$\mathrm{V}\mathrm{P}\mathrm{D}(T,q)=e_s(T)-e(q)$

where $e_s(T)$ is the saturation vapor pressure at temperature T and $e(q)$ is the actual vapor pressure given the moisture content q. A larger VPD means the atmosphere can absorb more moisture, and thus pulls moisture out of vegetation more quickly. The index's developers chose VPD over the more common relative humidity because relative humidity can mask meaningful differences in evaporative demand at different temperatures.

Because HDWI folds together heat, moisture, and wind into a single continuous value with no artificial thresholds or sign changes, it is designed to be simple to compute at any location using standard meteorological observations or forecast model output. HDWI values are highly dependent on local and seasonal climatology, so forecasters typically interpret a given HDWI value relative to historical percentiles for that location and time of year rather than against a fixed universal scale.

Evaluation against historical fires

In the original 2018 study, HDWI was compared to the Haines Index using reanalysis weather data for four historical U.S. wildfires: the Pagami Creek Fire (Minnesota, 2011), the Bastrop County Complex (Texas, 2011), the Double Trouble Fire (New Jersey, 2002), and the Cedar Fire (California, 2003). For each fire, HDWI showed a clear peak on the date of most active fire behavior, while the Haines Index did not consistently distinguish that date from surrounding days — largely because the Haines Index does not incorporate wind.

A subsequent, broader evaluation—a 2019 master's thesis at Michigan State University—tested the index against twenty-three historical wildland fire events using five different meteorological datasets, finding that the original HDWI formulation identified each fire's day of largest spread in roughly 57 to 78 percent of cases, depending on the dataset used. A separate 2020 master's thesis at the University of Arizona examined modifying HDWI's calculation using higher-resolution regional weather model data, finding that the added resolution reduced artificially low HDWI values that the coarser global model tended to produce near coastlines.

A 2021 study by Brian E. Potter and Daniel McEvoy compared HDWI and other wind–moisture fire-weather indices for twenty "fires of unusual size" (exceeding 36,400 hectares) against a set of smaller large fires (10,100–30,300 hectares). Growth was similar between the two groups when weather conditions fell in the 40th-to-60th percentile range, but for weather in the 80th-to-100th percentile range, the fires of unusual size grew observably more than the smaller fires. The study also found that antecedent atmospheric dryness, measured using the Evaporative Demand Drought Index (EDDI), tended to be greater ahead of the fires of unusual size than ahead of the smaller fires.

Adoption and use

Animated loop of daily Max GEFS HDWI forecast percentile maps for the contiguous United States, July 20–29, 2026 (USDA Forest Service Hot-Dry-Windy Index tool; July 28 not included).

The U.S. Forest Service operates a public real-time HDWI forecasting tool that displays analyses and multi-day forecasts derived from the Global Ensemble Forecast System (GEFS), along with a 30-year climatology for comparison, covering the continental United States and Alaska. National Weather Service forecasters have access to this tool for operational use, and as early as 2018 meteorologists in Washington, Oregon, and Idaho had begun incorporating HDWI into their routine fire weather briefings. The animated forecast maps at right show HDWI values reaching the 90th-to-100th percentile of the 1981–2010 climatology across large portions of Oregon on July 24 and 25, 2026, during the state's 2026 wildfire season. This time frame coincides with the ignition of two large fires in Harney County, the Second Flat Fire and the Coleman Creek Fire, both of which started on July 25, 2026, and grew to over 100,000 acres each within days.

HDWI is documented in the National Wildfire Coordinating Group's Fire Behavior Field Reference Guide (PMS 437) as a "first-look" indicator of days with elevated potential for adverse fire behavior. California's Wildfire Forecast & Threat Intelligence Integration Center lists HDWI alongside other tools such as the Keetch-Byram Drought Index and the Evaporative Demand Drought Index as resources used to assess wildfire potential.

As wildfire seasons have lengthened, the index has also drawn broader public attention, with mainstream weather outlets framing it as a modern tool that addresses a limitation of older indices that did not factor in wind.

See also

• Canadian Forest Fire Weather Index System
• Fire weather
• Fosberg Fire Weather Index
• Haines Index
• National Fire Danger Rating System
• Vapor pressure deficit
• Wildfire

External links

• Hot-Dry-Windy Index (HDWI) real-time forecast maps and analyses – U.S. Forest Service