Future Projections of Fire Occurrence in Brazil Using EC-Earth Climate Model

Fire has a fundamental role in the Earth system as it influences global and local ecosystem patterns and processes, such as vegetation distribution and structure, the carbon cycle and climate. Since, in the global context, Brazil is one of the regions with higher fire activity, an assessment is here performed of the sensitivity of the wildfire regime in Brazilian savanna and shrubland areas to changes in regional climate during the 21st Century, for an intermediate scenario (RCP4.5) of climate change. The assessment is based on a spatial and temporal analysis of a meteorological fire danger index specifically developed for Brazilian biomes, which was evaluated based on regional climate simulations of temperature, relative humidity and precipitation using the Rossby Centre Regional Climate Model (RCA4) forced by the EC-Earth earth system model. Results show a systematic increase in the extreme levels of fire danger throughout the 21st Century that mainly results from the increase in maximum daily temperature, which rises by about 2 °C between 2005 and 2100. This study provides new insights about projected fire activity in Brazilian woody savannas associated to climate change and is expected to benefit the user community, from governmental policies to land management and climate researches

Near- and Middle-Infrared Monitoring of Burned Areas from Space

We describe a methodology to discriminate burned areas and date burning events that use a burn-sensitive (V, W) index system defined in near-/mid-infrared space. Discrimination of burned areas relies on a monthly composite of minimum of W and on the difference between this composite and that of the previous month. The rationale is to identify pixels with high confidence of having burned and aggregate new burned pixels on a contextual basis. Dating of burning events is based on the analysis of time series of W, and searching for the day before maximum temporal separability is achieved. The procedure is applied to the fire of Monchique, a large event that took place in the southwest of Portugal in August 2018. When the obtained pattern of burned pixels is compared against a reference map, the overall accuracy is larger than 99%; the commission and omission errors are lower than 5 and 10%, respectively; and the bias and the Dice coefficient are above 0.95 and 0.9, respectively. Differences between estimated dates of burning and reference dates derived from remote-sensed observations of active fires show a bias of 0.03 day and a root mean square difference of 0.24 day

Assessing the role played by meteorological conditions on the interannual variability of fire activity in four subregions of Iberia

The Iberian Peninsula is recurrently affected by severe wildfires resulting from an interplay of human activities, landscape features and atmospheric conditions. Aims. The role played by atmospheric conditions on wildfire activity in 2001–2020 is assessed in four pyror- egions of the Iberian Peninsula. Methods. Wildfire activity is characterised by Fire Radiative Power (FRP) and meteorological danger is rated by the Fire Weather Index (FWI). The distribution of log 10 FRP in each pyroregion consists of a truncated lognormal central body with Generalised Pareto distributions as tails, and the model is improved using FWI as covariate. Synthetic time series of total annual FRP are generated using the models with and without FWI as covariate, and compared against observed FRP. Key results. Pyroregions NW, N, SW and E present increases of 1, 5, 6 and 7% in interannual explained variance of FRP when progressing from the model without to that with FWI as covariate. Conclusions. The models developed characterise the role of meteorological conditions on fire activity in the Iberian Peninsula, and are especially valuable when comparing expected impacts for different scenarios of climate change. Implications. The largest effects of atmospheric conditions on fire activity are in regions of the IP where the strongest impact of climate change is expectedinfo:eu-repo/semantics/publishedVersio

Multistability, phase diagrams, and intransitivity in the Lorenz-84 low-order atmospheric circulation model

We report phase diagrams detailing the intransitivity observed in the climate scenarios supported by a prototype atmospheric general circulation model, namely, the Lorenz-84 low-order model. So far, this model was known to have a pair of coexisting climates described originally by Lorenz. Bifurcation analysis allows the identification of a remarkably wide parameter region where up to four climates coexist simultaneously. In this region the dynamical behavior depends crucially on subtle and minute tuning of the model parameters. This strong parameter sensitivity makes the Lorenz-84 model a promising candidate of testing ground to validate techniques of assessing the sensitivity of low-order models to perturbations of parameters

Impact of High Concentrations of Saharan Dust Aerosols on Infrared-Based Land Surface Temperature Products

An analysis of three operational satellite-based thermal-infrared land surface temperature (LST) products is presented for conditions of heavy dust aerosol loading. The LST products are compared against ERA5’s skin temperature (SKT) across the Sahara Desert and Sahel region, where high concentrations of dust aerosols are prevalent. Large anomalous differences are found between satellite LST and ERA5’s SKT during the periods of highest dust activity, and satellite–ERA5 differences are shown to be strongly related to dust aerosol optical depth (DuAOD) at 550 nm, indicating an underestimation of LST in conditions of heavy dust aerosol loading. In situ measurements from two ground stations in the Sahel region provide additional evidence of this underestimation, showing increased biases of satellite LST with DuAOD, and no significant dependence of ERA5’s SKT biases on dust aerosol concentrations. The impact of atmospheric water vapor content on LST and SKT is also examined, but dust aerosols are shown to be the primary driver of the inaccurate LSTs observed. Based on comparisons with in situ data, we estimate an aerosol-induced underestimation of LST of approximately 0.9 K for every 0.1 increase in DuAOD. Analysis of brightness temperatures (BTs) in the thermal infrared atmospheric window reveals that dust aerosols have the opposite effect on BT differences compared to water vapor, leading to an underestimation of atmospheric correction by the LST retrieval algorithms. This article highlights a shortcoming of current operational LST retrieval algorithms that must be addressed

The compound event that triggered the destructive fires of October 2017 in Portugal

Portugal is regularly affected by destructive wildfires that have severe social, economic, and ecological impacts. The total burnt area in 2017 (∼540,000 ha) marked the all-time record value since 1980 with a tragic toll of 114 fatalities that occurred in June and October events. The local insurance sector declared it was the costliest natural disaster in Portugal with payouts exceeding USD295 million. Here, the 2017 October event, responsible for more than 200,000 ha of burnt area and 50 fatalities is analyzed from a compound perspective. A prolonged drought led to preconditioned cumulative hydric stress of vegetation in October 2017. In addition, on 15 October 2017, two other major drivers played a critical role: 1) the passage of hurricane Ophelia off the Coast of Portugal, responsible for exceptional meteorological conditions and 2) the human agent, responsible for an extremely elevated number of negligent ignitions. This disastrous combination of natural and anthropogenic drivers led to the uncontrolled wildfires observed on 15 October

Assessing the role of compound drought and heatwave events on unprecedented 2020 wildfires in the Pantanal

The year 2020 had the most catastrophic fire season over the last two decades in the Pantanal, which led to outstanding environmental impacts. Indeed, much of the Pantanal has been affected by severe dry conditions since 2019, with evidence of the 2020's drought being the most extreme and widespread ever recorded in the last 70 years. Although it is unquestionable that this mega-drought contributed significantly to the increase of fire risk, so far, the 2020's fire season has been analyzed at the univariate level of a single climate event, not considering the co-occurrence of extreme and persistent temperatures with soil dryness conditions. Here, we show that similarly to other areas of the globe, the influence of land-atmosphere feedbacks contributed decisively to the simultaneous occurrence of dry and hot spells (HPs), exacerbating fire risk. The ideal synoptic conditions for strong atmospheric heating and large evaporation rates were present, in particular during the HPs, when the maximum temperature was, on average, 6 °C above the normal. The short span of the period during those compound drought-heatwave (CDHW) events accounted for 55% of the burned area of 2020. The vulnerability in the northern forested areas was higher than in the other areas, revealing a synergistic effect between fuel availability and weather-hydrological conditions. Accordingly, where fuel is not a limiting factor, fire activity tends to be more modelled by CDHW events. Our work advances beyond an isolated event-level basis towards a compound and cascading natural hazards approach, simultaneously estimating the contribution of drought and heatwaves to fuelling extreme fire outbreaks in the Pantanal such as those in 2020. Thus, these findings are relevant within a broader context, as the driving mechanisms apply across other ecosystems, implying higher flammability conditions and further efforts for monitoring and predicting such extreme events

Quantifying the Clear-Sky Bias of Satellite Land Surface Temperature Using Microwave-Based Estimates

International audienceMost available long-term databases of land surface temperature (LST)derived from space-borne sensors rely on infrared observations and aretherefore restricted to clear-sky conditions. Hence, studies based onsuch data sets may not be representative of all-weather conditions andmay be considered as "biased" toward clear sky. An assessment of theimpact of this restriction is made using 3 years of LST derived frompassive microwave observations that are not affected by most clouds. Asystematic analysis in space and time is performed of the "clear-skybias," defined as the difference between average clear-sky and averageall-weather LSTs. The amplitude of the bias is closely related to thefraction of clear-sky days, and therefore, arid regions are associatedto very low values of bias whereas midlatitudes present the highestvalues. During daytime, the input of solar radiation for clear-skysituations leads to higher LST values, and therefore, the bias isgenerally positive (e.g., 2-8 K over the midlatitudes) whereas, duringnighttime, the bias is generally negative although with lower amplitude(around -2 K), because of the increased radiative cooling for clear-skysituations. The clear-, cloudy-, and all-sky LSTs are also compared withnear-surface air temperature. Although LST is generally higher than airtemperature, the contrast between the two may be strongly influenced bylocal weather conditions. Both the clear-sky bias and differencesbetween LST and air temperature are also analyzed at the local scaletaking into account the predominant cloud regime