Image (top) shows fire at Estreito da Calheta, Madeira, Portugal, in August, 2016
Is it possible to predict where a wildfire is likely to start? Or to say how ferociously it will burn before it has even ignited?
Can satellite observations help?
In a year of unprecedented fires in the Northern Hemisphere, from California in the US to the Arctic Circle in Sweden, scientists in Portugal have made exciting progress in doing just that – with implications for responding better to this recurring threat.
In early August, a wildfire in the Monchique region of southern Portugal injured 45 people, caused more than €10 million in damage to property, forced the evacuation of about 2,000 residents and required the efforts of 1,450 firefighters to contain.
Three months earlier, in May, Professor Carlos DaCamara of the Faculty of Sciences at the University of Lisbon was part of a team led by Professor José M. C. Pereira of the university’s Institute of Agronomy which released a map of Portuguese municipalities illustrating their risk of a major blaze during this year’s fire season.
(A newspaper article, in Portuguese, showing the list of Portuguese municipalities with risk of major fire, can be seen here.)
However, according to a statistical model developed by Professor DaCamara’s research group, a severe fire season was not expected to occur, given the mild temperatures and rainfall observed during spring and early summer.
(An interview with Professor DaCamara, in Portuguese, can be seen here.)
Although the project found the chance of experiencing fires in Portugal on the same scale as the deadly blazes of last year was lower, it identified the areas at risk.
The region of highest probability of a major fire? Monchique.
Here’s the back story.
These maps of the fire risk throughout Portugal show (left) the day before the Monchique blaze ignited (2 August), when the probability was rated as “exceptional” for that region, and (right) the day the fire started (3 August).
Among the fire-related products developed by the EUMETSAT LSA SAF is the Fire Radiative Power product, which provides information about the radiant heat emitted by fires. Scans of Europe produced every 15 minutes by EUMETSAT’s Meteosat Second Generation (MSG) geostationary spacecraft provide this data.
“Back in the 1970s, Canada produced a set of indices based on meteorological parameters – temperature, wind speed, air humidity and precipitation – related to the easiness of a fire building up in intensity or spreading,” Professor DaCamara, who was a member of the LSA SAF, said.
“The LSA SAF calibrated these indices against the database of fire radiative power first measured by MSG.
Professor DaCamara said his team found that probability distribution of fire radiative energy follows a predictable pattern.
“What we are producing is a statistical model of probability that once a fire attains a certain level of energy, that it will then attain another level of energy that makes it difficult, or impossible, to contain,” he said.
The model has shown promising results during this fire season. Professor DaCamara is confident that the fire season in Portugal this year will not be as severe as last year and said the Monchique blaze was expectable.
The genesis of the tragic events of the 2017 fire season in Portugal are illustrated in this animation, which covers the period from 13 July to 29 August 2017. The level of risk and the outbreak of fires is clearly shown.
Preconditions for a fire
How can a serious wildfire be expected if, as has happened in a number of cases around the world, it starts as a result of human activities?
Professor DaCamara outlined the three ingredients needed for a major fire:
“The first is meteorological conditions. This can be predicted and can be used to then predict the fire radiative power released by the fires,” he said.
“Secondly, you need vegetation that is stressed by lack of water and heights of temperature. You can have an idea of the status of vegetation at the beginning of the fire season.
“The third is ignition. In Mediterranean countries, especially Portugal, 97 percent of ignitions are man-made, they are not natural, like in Canada. Of those, a huge proportion, 80 percent, are a result of malpractice.”
Those man-made fires include arson but cover other sources of ignition. For example, fire is used in agricultural practices, exactly when the conditions for large fires are prevalent.
The determination that the sources of ignition exist, whether man-made or natural, negligence or arson, are taken into account in the models of probability of having large fires.
Professor DaCamara’s group has developed a website, called CeaseFire, with daily maps showing the fire risk throughout Portugal. The website uses LSA SAF products, derived from EUMETSAT’s satellite observations, and is sponsored by the Portuguese pulp and paper company, Navigator.
“We have focused on Portugal as we are based here and because of the severity of wildfires we have,” Professor DaCamara said. “We have calibrated this model specifically for Portugal.
“We also received a tender from the World Bank and now produce daily forecasts of the fire danger in the Zambezia Province of Mozambique.”
Professor DaCamara said daily forecasts for the Zambezia region have been produced since June and the results so far are promising.
Professor DaCamara’s team now produces daily forecasts of the fire danger in the Zambezia region of Mozambique in a project funded by the World Bank.
Other countries, among them Greece and Armenia, have expressed interest in the model and there is scope to extend the forecasts to other regions. However, the particular characteristics of those countries or regions would need to be factored into the modelling.
The fire risk in parts of Greece is clear from the image on top, of the day a deadly wildfire began (23 July). The fire risk visibly decreased over the next two days.
“The product would have to be adapted to the different type of climate and different type of landscape in non-Mediterranean countries,” Professor da Camara said.
“The product will work in other places and can help local authorities in better management and planning, for example, for the distribution of fire-fighting equipment and resources during the fire season.