NOVEMBER 2012 D O W D Y A N D M I L L S 2025 Atmospheric and Fuel Moisture Characteristics Associated with Lightning-Attributed Fires ANDREW J. DOWDY AND GRAHAM A. MILLS Centre for Australian Weather and Climate Research, Docklands, Melbourne, and Bushfire Cooperative Research Centre, East Melbourne, Victoria, Australia (Manuscript received 12 October 2011, in final form 16 May 2012) ABSTRACT A systematic examination is presented of the relationship between lightning occurrence and fires attributed to lightning ignitions. Lightning occurrence data are matched to a database of fires attributed to lightning ignition over southeastern Australia and are compared with atmospheric and fuel characteristics at the time of the lightning occurrence. Factors influencing the chance of fire per lightning stroke are examined, including the influence of fuel moisture and weather parameters, as well as seasonal and diurnal variations. The fuel moisture parameters of the Canadian Fire Weather Index System are found to be useful in indicating whether a fire will occur, given the occurrence of lightning. The occurrence of ‘‘dry lightning’’ (i.e., lightning that occurs without significant rainfall) is found to have a large influence on the chance of fire per lightning stroke. Through comparison of the results presented here with the results of studies from other parts of the world, a considerable degree of universality is shown to exist in the characteristics of lightning fires and the atmo- spheric conditions associated with them, suggesting the potential for these results to be applied more widely than just in the area of the study. 1. Introduction lightning occurs outside of the rain shaft of a thunder- storm (commonly known as a bolt from the blue). Lightning is the ignition source of many wildfires Rorig and Ferguson (1999, hereinafter RF99) showed throughout the world. A greater understanding of the that the occurrence of dry lightning, defined as lightning processes through which lightning-ignited fires occur that occurs with rainfall less than 0.1 in. (2.54 mm), in can therefore be expected to produce benefits such as the U.S. Pacific Northwest was related to high values of reductions in the response time to these fires and thus lower-tropospheric instability (represented by a large a reduction in the damage that they cause, as well as temperature difference between 850 and 500 hPa) com- a better understanding of natural fire regimes and their bined with low atmospheric moisture levels (represented range of ignition parameters and conditions. by high dewpoint depression at 850 hPa). RF99 found This paper investigates atmospheric states that could that the number of lightning-caused fires corresponded potentially influence the chance that lightning will cause more closely to these two parameters than to the total a fire, including the occurrence of ‘‘dry lightning’’— number of lightning flashes that occurred. Their method lightning that occurs without significant rainfall. A lightning correctly classified between 56% and 80% of days on strike on the ground with little accompanying precipi- which thunderstorms occurred as either ‘‘dry’’ or ‘‘wet,’’ tation (dry lightning) can occur in a number of ways: if using their rainfall threshold. a thunderstorm is high based with relatively dry air at Fires attributed to lightning ignitions (hereafter re- lower levels such that rain evaporates before reaching ferred to as lightning fires) have been the subject of a the ground (i.e., virga), if a thunderstorm is fast moving number of recent Northern Hemisphere studies [exam- such that the rainfall is spread thinly on the ground, or if ples of these include Lutz et al. (2009), Reineking et al. (2010), Drobyshev et al. (2010), Kilpela¨inen et al. (2010), and Garcia-Ortega et al. (2011)]. In contrast, a relatively Corresponding author address: Andrew J. Dowdy, Bureau of Meteorology, 700 Collins St., Docklands, Melbourne, VIC 3008, limited number of such studies have been undertaken Australia. for Southern Hemisphere locations. This imbalance is E-mail: [email protected] not ideal as there are some characteristics of lightning DOI: 10.1175/JAMC-D-11-0219.1 Ó 2012 American Meteorological Society Unauthenticated | Downloaded 09/28/21 09:13 PM UTC 2026 JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY VOLUME 51 lightning data, rainfall data, atmospheric profile data obtained from NWP models, and modeled fuel moisture data. The Department of Sustainability and Environment in Victoria maintains a fire database that includes an attribution of ignition source to each fire, and those fires attributed to lightning ignition provide the dataset for this study. The data also include information such as the location of the fire ignition and the time that the fire was first observed. The dataset includes fires that were ig- nited on public land (i.e., land managed by the state government of Victoria), as well as a small number of FIG. 1. Geographic boundary of the state of Victoria in southeast fires that were ignited on private land and spread onto Australia. Latitude, longitude, and topography are also shown. public land. In this study fires ignited on private land have not been used, as to do so would produce significant inconsistencies in the data between different locations. fires for which considerable variation occurs, even be- This subset of the fire dataset, consisting of lightning- tween geographic regions that are relatively close to each attributed fires that were ignited on public land, com- other. For example, Wierzchowski et al. (2002) report poses our lightning-fire dataset. that the average probability of fire from a single light- The lightning fires are most commonly first observed ning flash for adjacent provinces in Canada is 0.07% for during the afternoon [between about 1300 and 1900 local Alberta and 2% for British Columbia. time (LT)]. The fires are observed primarily from their The probability of fuel ignition by lightning has been smoke seen during daylight hours, which is likely to shown to be relatively independent of fuel moisture, with account for the jump in the number of fires observed some fuels igniting even though they may be very wet after 0600 LT. About 96% of the lightning fires occur (e.g., Latham et al. 1997). In contrast, the probability that between November and March, with January being the an ignition is sustained is highly dependent on fuel mois- most common month for their occurrence. Considerable ture (e.g., Rothermel 1972; Wotton and Martell 2005). interannual variability is apparent in the number of light- The high dependency of ignition survival on fuel moisture ning fires, ranging from about 60 during the year 2000 up is the reason why the concept of dry lightning is of im- to about 380 during the year 2007. portance. The influence of the preexisting fuel moisture is Lightning data were obtained from the commercial investigated in this study using the three fuel moisture provider Global Position and Tracking Systems Pty., components of the Canadian Forest Fire Weather Index Ltd., (GPATS) Australia. The GPATS data are based (FWI) System (Van Wagner 1987; Dowdy et al. 2009). on the time of arrival of the lightning discharge at a net- This study is the first systematic examination under- work of three or more radio receivers (e.g., Cummins and taken in Australia of the relationship between lightning Murphy 2009). This technique can detect the multiple occurrence and lightning fires. Nine years of lightning- return strokes that can be contained within a single light- fire occurrence data for fires occurring on public lands in ning flash, as well as distinguish between cloud-to-cloud the state of Victoria (Fig. 1) in Australia’s southeast are and cloud-to-ground lightning. This study uses a broad- used together with lightning occurrence data to examine scale approach for combining the lightning data with the the atmospheric conditions associated with lightning fires. fire data (i.e., only using a daily temporal resolution, as The occurrences of lightning, dry lightning, and lightning well as an effective spatial resolution of ;10 km as de- fires are compared with tropospheric atmospheric states tailed in the following section; see section 2b) and so (the RF99 phase space of instability and dryness) and imperfections in the lightning detection efficiency surface atmospheric and fuel characteristics that might (such as if they are not 100% efficient at distinguishing influence ignition survival using a combination of ob- between cloud-to-ground and cloud-to-cloud lightning) servational and gridded products. are not expected to significantly influence the results pre- sented in this study. 2. Data and methodology To classify whether a particular lightning stroke is wet or dry, rainfall data have been obtained from a gridded a. Data sources analysis of rainfall observations (Jones et al. 2009). The In this study, data from a variety of sources are com- rainfall data represent the total rainfall for the 24-h pe- pared, including fire occurrence and characteristics data, riod up to 0900 LT. This is 11 h ahead of UTC when Unauthenticated | Downloaded 09/28/21 09:13 PM UTC NOVEMBER 2012 D O W D Y A N D M I L L S 2027 daylight saving time is in effect. The grid spacing of the b. Determining fire ignition time data is 0.058 in both latitude and longitude—approximately The lightning-fire data contain the time that a fire was 5km3 5 km—throughout Victoria. first observed, not the time that a fire was ignited. The NWP forecasts from a mesoscale version of the Aus- lightning-fire data can be combined with the lightning tralian Bureau of Meteorology’s operational Limited data to estimate the ignition time of each lightning fire. Area Prediction System (MESOLAPS; Puri et al. 1998) The lightning stroke closest in time prior to the first have been used to provide the horizontal, vertical, and observation of a lightning fire is used as the most likely temporal resolutions of parameters describing the atmo- fire ignition time, provided that the lightning stroke oc- spheric state.