Fire weather indices are commonly used by fire weather forecasters to predict when weather conditions will make a wildland fire difficult to manage. Complex interactions at multiple scales between fire, fuels, topography, and weather make these predictions extremely difficult. We define a new fire weather index called the Hot-Dry-Windy Index (HDW). HDW uses the basic science of how the atmosphere can affect a fire to define the meteorological variables that can be predicted at synoptic-and meso-alpha-scales that govern the potential for the atmosphere to affect a fire. The new index is formulated to account for meteorological conditions both at the Earth’s surface and in a 500-m layer just above the surface. HDW is defined and then compared with the Haines Index (HI) for four historical fires. The Climate Forecast System Reanalysis (CFSR) is used to provide the meteorological data for calculating the indices. Our results indicate that HDW can identify days on which synoptic-and meso-alpha-scale weather processes can contribute to especially dangerous fire behavior. HDW is shown to perform better than the HI for each of the four historical fires. Additionally, since HDW is based on the meteorological variables that govern the potential for the atmosphere to affect a fire, it is possible to speculate on why HDW would be more or less effective based on the conditions that prevail in a given fire case. The HI, in contrast, does not have a physical basis, which makes speculation on why it works or does not work difficult because the mechanisms are not clear.

In this paper, we describe and analyze a climatology of the Hot-Dry-Windy Index (HDW), with the goal of providing fire-weather forecasters with information about the daily and seasonal variability of the index. The 30-year climatology (1981–2010) was produced using the Climate Forecast System Reanalysis (CFSR) for the contiguous United States, using percentiles to show seasonal and geographical variations of HDW contained within the climatology. The method for producing this climatology is documented and the application of the climatology to historical fire events is discussed. We show that the HDW climatology provides insight into near-surface climatic conditions that can be used to identify temperature and humidity trends that correspond to climate classification systems. Furthermore, when used in conjunction with daily traces of HDW values, users can follow trends in HDW and compare those trends with historical values at a given location. More usefully, this climatology adds value to HDW forecasts; by combining the CFSR climatology and a Global Ensemble Forecast System (GEFS) ensemble history and forecast, we can produce a single product that provides seasonal, climatological, and short-term context to help determine the appropriate fire-management response to a given HDW value.

A warm-season (May through October) Haines Index climatology is derived using 32-km regional reanalysis temperature and humidity data from 1980 to 2007. We compute lapse rates, dewpoint depressions, Haines Index factors A and B, and values for each of the low-, mid- and high-elevation variants of the Haines Index. Statistical techniques are used to investigate the spatial and temporal variability of the index across North America. The new climatology is compared with a previous climatology derived from 2.5° (~280 km) global reanalysis data. Maps from the two climatologies are found to be very similar for most of North America. The largest differences appear along the eastern coastline and in regions of large elevation gradients, where the orography in the 32-km climatology is better resolved than that of the 2.5° climatology. In coastal areas of eastern North America and where there is steeply sloping terrain, the new climatology can augment the information from the 2.5° climatology to help analyse the performance and interpret the results of the Haines Index in these regions. A linear trend analysis of the total number of high-Haines Index days occurring in each warm season reveals no significant linear trends over the 28-year data period.

On the morning of 2 June 2002, an abandoned campfire grew into a wildfire in the Double Trouble State Park in east-central New Jersey, USA. The wildfire burned 526 ha (1300 acres) and forced the closure of the Garden State Parkway for several hours due to dense smoke. In addition to the presence of dead and dry fuels due to a late spring frost prior to the wildfire, the meteorological conditions at the time of the wildfire were conducive to erratic fire behaviour and rapid fire growth. Observations indicate the occurrence of a substantial drop in relative humidity at the surface accompanied by an increase in wind speed in the vicinity of the wildfire during the late morning and early afternoon of 2 June. The surface drying and increase in wind speed are hypothesised to result from the downward transport of dry, high-momentum air from the middle troposphere occurring in conjunction with a deepening mixed layer. This hypothesis is addressed using a high-resolution mesoscale model simulation to document the structure and evolution of the planetary boundary layer and lower-tropospheric features associated with the arrival of dry, high-momentum air at the surface coincident with the sudden and dramatic growth of the wildfire.

Lower-tropospheric wind maxima, known as low-level jets (LLJs), play a vital role in weather and climate around the world. In this study, two 10-year (2006–2015) regional climate simulations using current (2011) and future (2100) land-use/land-cover (LULC) patterns over the continental United States (CONUS) are used to assess the sensitivity of LLJ properties, including jet occurrence, maximum speed, and the elevation of the maximum, to changes in LULC. The three simulated LLJ properties exhibit greater sensitivity in summer than in winter. Summertime jets are projected to increase in frequency in the central CONUS, where cropland replaces grassland, and decrease in parts of the Ohio-River Valley and the Southeast, particularly Florida, where urban expansion occurs. Little change is projected for wintertime jet frequency. Larger modifications to jet speed and elevations are projected in parts of the Ohio River Valley, the upper Southeast, and the Intermountain West. While there is some evidence of weaker, more elevated jets with urban expansion, the connection between changes in jet speed and elevation and changes in LULC patterns at a given location is weak. This result suggests that LULC will primarily affect the large-scale atmospheric conditions that contribute to the formation of LLJs, particularly in winter.