Research

Lightning-caused fires are an essential part of the fire regimes in numerous remote and mountain areas around the world, such as Siberia, boreal and western North America, the European Alps, Siberia, Australia, etc. Lightning fires are expected to increase because climate change is favoring the conditions for fire ignition and spread, independently of the additional projected increase in lightning activity. In this new global context, lightning fires will probably become an important part of the future fire crises.

Lightning fires show distinctive features compared with human-started fires. For example, some lightning fires present a prolonged initial latent period, known as “survival phase”, characterized by smouldering (i.e., burning slowly with smoke but no flame) of the soil organic matter, before turning to flaming combustion of surface vegetation. These holdover fires are generally difficult to detect during the first stage of development. Progress on the project appear below.

Holdover time database

Holdover fires are usually associated with lightning-ignited wildfires (LIWs), which can experience a smoldering phase or go undetected for several hours, days or even weeks before being reported. Since the existence and duration of the smoldering combustion in LIWs is usually unknown, holdover time is conventionally defined as the time between the lightning event that ignited the fire and the time the fire is detected. Therefore, all LIWs have an associated holdover time, which may range from a few minutes to several days. However, we lack a comprehensive understanding of holdover times.

Here, we introduce a global database on holdover times of LIWs. We have collected holdover time data from 29 different studies across the world through a literature review and datasets assembled by authors of the original studies. The database is composed of three data files (censored data, non-censored data, ancillary data) and three metadata files (description of database variables, list of references, reproducible examples). Censored data are the core of the database and consist of different frequency distributions reporting the number or relative frequency of LIWs per interval of holdover time. In addition, ancillary data provide further information to understand the methods and contexts in which the data were generated in the original studies. The first version of the database contains 42 frequency distributions of holdover time built with data on more than 152 375 LIWs from 13 countries in five continents covering a time span from 1921 to 2020. This database is the first freely available, harmonized and ready-to-use global source of holdover time data, which may be used in different ways to investigate LIWs and model the holdover phenomenon. The complete database can be downloaded at https://doi.org/10.5281/zenodo.7352172 (Moris et al., 2022).

Survival functions of holdover time

Lightning-ignited wildfires (LIWs) can go unreported for hours, days or even weeks before being reported. This is due to the fact that some LIWs present an intermediate phase between ignition and detection characterized by a smoldering combustion. Holdover time is generally defined as the time between lightning-induced ignition and fire detection. This study aims at obtaining survival functions to estimate the probability of a LIW reaching a certain holdover time.

To this end, we fitted nine different probability distributions (exponential, chi-squared, log-normal, log-logistic, F, gamma, Weibull, Pareto, and Gompertz) to data from a database gathering 42 frequency distributions of holdover time obtained from more than 152,375 LIWs in 13 countries from 1921 to 2020. Gamma distributions provide the best fits to the observed holdover times. Accordingly, we estimated several survival functions derived from gamma distributions fitted to holdover time data. The survival functions are monotonically decreasing functions characterized by high probabilities for short holdover times and low probabilities for long holdover times. These survival functions can be used for holdover times of LIWs occurring globally as well as in boreal, Mediterranean and temperate coniferous forest biomes. Survival functions are intended to provide a more reliable way to assess holdover time-based probabilities of lightning causing wildfires.