Assessing Global Wildfire Dynamics and Climate Resilience: A Focus on European Regions Using the Fire Weather Index ^†

Abstract

Wildfires pose significant threats to ecosystems, human safety, and socio-economic stability, necessitating a deep understanding of fire-prone landscapes for effective management. This study assesses the temporal and spatial patterns of the Fire Weather Index (FWI), a crucial indicator of landscape flammability, with a particular focus on European regions. Historical FWI data from the European Forest Fire Information System (EFFIS) under the Copernicus Emergency Management Service (CEMS) are analyzed using tools such as the Climate Data Store (CDS) API. The results reveal spatial patterns, highlighting regions with heightened wildfire risk and those with reduced fire danger. Southern and Southeastern Europe face elevated danger, driven by factors like high temperatures, low humidity, and reduced precipitation, while Northwestern and Northeastern Europe exhibit lower risk due to milder conditions. The study further delves into the implications of these patterns on agrivoltaic systems, the distinct climatic and environmental factors influencing elevated FWI levels across various regions, and how the findings of this research can guide tailored wildfire management strategies for European areas. The findings inform resilient strategies for policymakers, land managers, and communities, contributing valuable insights for proactive and sustainable wildfire mitigation.

1. Introduction

Wildfires represent a global challenge, affecting ecosystems, livelihoods, and human safety [1,2]. As climate change intensifies (on temperature and precipitation [3,4], agriculture [5] and water resources [6], and our energy consumption and production [7,8]), understanding and assessing the Fire Weather Index (FWI) become crucial for anticipating and managing the increasing risks associated with wildfires [9,10]. This study focuses on providing a comprehensive evaluation of FWI worldwide, with a specific emphasis on European regions, where the diverse climate and landscape necessitate region-specific insights. The primary motivation is rooted in the urgent need to enhance our understanding of FWI dynamics globally and, more critically, in Europe.

The primary objective of this study is to analyze the spatial and temporal patterns of the FWI, emphasizing European regions. By doing so, the study aims to contribute valuable insights into the factors influencing fire danger, providing a foundation for effective wildfire management strategies. The specific focus on Europe recognizes the region’s vulnerability to climate change-induced wildfire risks and the necessity for tailored approaches to address these challenges.

While existing research has established the correlation between FWI and wildfire activity [11,12], there is a notable gap in region-specific assessments, particularly for Europe. The current understanding of FWI dynamics is often generalized and lacks nuanced insights into the diverse climates and ecosystems present on the continent. This study seeks to bridge this gap by conducting a detailed analysis that considers the intricate interactions between climate, topography, and vegetation in European regions.

This study’s originality lies in its focus on providing a nuanced analysis of FWI in European regions, contributing region-specific knowledge crucial for wildfire management. The research questions guiding this study include:

• How do spatial and temporal patterns of FWI vary across the world, with a particular focus on European regions? How do they affect agrivoltaic systems? (Section 4; Section 5.1)
• What are the specific climatic and environmental factors contributing to heightened FWI in different areas? (Section 5.2)
• How can the insights gained from this study inform targeted wildfire management strategies for European regions? (Section 5.3)

The study uses historical FWI data obtained from the European Forest Fire Information System (Section 3). The analysis involves the generation of spatial plots, anomaly comparisons, and weekly time series plots to capture the dynamic nature of FWI. Specific attention is given to region-specific variations, and the analysis integrates both climatic and environmental factors to provide a comprehensive understanding of FWI patterns in Europe.

This paper follows a structured format to comprehensively address the research objectives. After this introduction (Section 1), which provides an overview of the research importance and motivation, Section 2 delves into the literature review, highlighting the existing research, knowledge gaps, and the originality of this study. Section 3 details the data and methodology employed in the research, outlining the approach used to analyze the spatial and temporal patterns of the Fire Weather Index (FWI). In Section 4, the focus shifts to the presentation and analysis of results, particularly examining the spatial and temporal dynamics of FWI in European regions. Section 5 consolidates the findings and insights gleaned from the study, emphasizing its contribution to understanding FWI impacts on agrivoltaic systems, the factors influencing fire danger, and effective wildfire management strategies tailored to European contexts. Finally, Section 6 provides a summary of the study, highlighting practical implications and limitations, offering a comprehensive conclusion to the research endeavor.

2. Literature Review and Knowledge Gaps

Understanding the spatial and temporal patterns of the Fire Weather Index (FWI) [13] and its implications for agrivoltaic systems, fire danger factors, and wildfire management strategies in European regions is crucial for effective landscape management and risk mitigation.

The literature on this subject provides valuable insights into various aspects of FWI dynamics and its associated impacts.

Existing research has demonstrated the correlation between FWI and wildfire activity, highlighting the importance of FWI as a predictor of fire danger. Maggioros et al. [14] explore the application of Convolutional Neural Networks (CNNs) in analyzing geospatial data to identify wildfire-affected areas. Using transfer learning techniques and integrating the Canadian Fire Weather Index (FWI) to assess moisture conditions, the study establishes a methodology for computing wildfire risk levels. The CNN model achieves an impressive accuracy of 95% in identifying burnt areas. This research highlights the effectiveness of CNNs and transfer learning in predicting and mitigating wildfires, providing a robust approach for assessing burnt areas and enabling timely interventions and preventative measures against wildfires. Salehi et al. [15] propose a data-driven approach, termed the Context-Based Fire Risk (CBFR) model, to predict wildfire risk using weather data. Addressing the challenge of temporal dynamicity in weather data, the model employs context-based anomaly detection techniques. It maintains multiple historical models for different temporal variations and utilizes ensemble learning techniques to predict wildfire risk accurately. The CBFR model is unsupervised, flexible, and scalable, making it applicable to any region of interest. Experimental results conducted in the Blue Mountains, Australia, demonstrate the model’s substantially higher accuracy compared to existing wildfire rating systems, indicating its effectiveness as a supplement to operational wildfire management systems. Deng et al. [16] investigate the impact of climate change on forest fires in Yunnan Province, focusing on fire dynamics. Utilizing the RegCM regional climate model and the Canadian Fire Weather Index (FWI), the study simulates and analyzes forest fire dynamics from 2019 to 2033 under three climate scenarios (Representative Concentration Pathways): RCP2.6, RCP4.5, and RCP8.5. Results indicate that climate change will increase temperatures, alter humidity and wind speed, and reduce precipitation in Yunnan, extending the fire danger period, particularly under RCP8.5 scenarios. FWI values are projected to rise across Yunnan, especially in the west under RCP2.6 and RCP8.5. The study concludes that future carbon emissions will exacerbate these changes, leading to more frequent, longer, and severe forest fires. This research provides valuable insights for managing and preventing forest fires in Yunnan, a region prone to such disasters. However, while the relationship between FWI and wildfire activity has been well established, there remains a notable gap in region-specific assessments, particularly for European regions. Many studies have focused on FWI dynamics in specific geographic locations but fewer have provided detailed analyses of FWI patterns in European contexts.

Moreover, the impact of FWI on agrivoltaic systems, which integrate agricultural practices with solar energy production [17,18], has received limited attention in the literature. Agrivoltaic systems are susceptible to fire risks, and understanding how FWI variations influence these systems is essential for sustainable land use planning and energy production.

Furthermore, while some studies have identified the primary climatic and environmental factors influencing FWI dynamics, such as temperature, humidity, and precipitation patterns, there is still a need for region-specific assessments that consider the unique climate and landscape characteristics of European regions. El Garroussi et al. [19] assess how changes in temperature and precipitation would impact the intensity and duration of extreme fires across Europe. Using a 30-year ERA5 reanalysis, the analysis examines the effects of various climate change projections on fire events compared to a baseline of fire danger. The findings indicate that Southern Europe may see a tenfold increase in the likelihood of catastrophic fires under a moderate CMIP6 scenario. Additionally, if global temperatures rise to the +2 °C threshold, Central and Northern Europe could also become more vulnerable to wildfires during droughts. The heightened probability of fire extremes, coupled with an average one-week extension of the fire season across most countries, would pose additional challenges to Europe’s ability to cope with wildfires in the coming decades. Semenova et al. [20] investigate the spatiotemporal distribution of fire weather conditions in the mixed forest areas of Belarus and Ukraine during the fire seasons from 1990 to 2020. Monthly mean Fire Weather Index (FWI) values, averaged for each administrative area, were used for analysis. The study found that the lowest FWI values were observed in the northern and northwestern regions of Belarus, while the highest values were in the southeast. In Ukraine, FWI values increased toward the eastern regions. Seasonally, FWI values increased from March to May, peaking in the middle of summer across all regions. Analysis of FWI dynamics over five-year periods revealed varying frequencies of danger fire weather conditions, ranging from “very low” to “moderate” levels for most of the study period. However, in the last pentad (2015–2020), a “high” fire danger level began to appear in the south of Belarus and the northern part of Ukraine. Additionally, some regions of Ukraine experienced a decrease in the frequency of FWI values, indicating “low” danger levels, while observing an increase at higher levels, possibly linked to observed climate change in the region.

In light of these knowledge gaps, this study aims to fill a critical research void by providing a comprehensive evaluation of FWI patterns in European regions. By analyzing historical FWI data and integrating insights from agrivoltaic systems, fire danger factors, and wildfire management strategies, this research seeks to contribute valuable knowledge to the field and inform targeted interventions for wildfire risk mitigation in European contexts.

3. Data and Methodology

In this study, we employ the Fire Weather Index (FWI) as a key metric to assess fire danger and potential wildfire occurrences in the European State of the Climate (ESOTC) assessment. Wildfires are known to develop in areas with combustible vegetation and an ignition source, such as lightning strikes or human activities [1]. Factors like vegetation type, structure, moisture content, topography, and wind influence the duration, intensity, direction, and speed of fire spread.

To analyze how the flammability of specific areas changes in response to weather conditions, we use fire danger indices, particularly the FWI. These indices, calculated from daily temperature, relative humidity, wind speed, and precipitation, provide a measure of landscape flammability. While they do not directly account for ignition, FWI has demonstrated correlation with fire activity in terms of burnt area.

The data used in this study were provided by the European Forest Fire Information System (EFFIS) (https://effis.jrc.ec.europa.eu/, accessed on 12 February 2024), a part of the Copernicus Emergency Management Service (CEMS), and has been made available through the Climate Data Store (CDS) (https://cds.climate.copernicus.eu/cdsapp#!/dataset/cems-fire-historical?tab=form, accessed on 12 February 2024) by the European Commission Joint Research Centre.

The data cover the period from 1991 to 2022, allowing for a comprehensive analysis of fire danger trends. The analysis focuses on the summer months (May to September) to capture the peak fire danger period.

The anomaly analysis for the year 2022 is conducted by comparing the number of days with FWI exceeding a threshold of 50 to the mean number observed between 1991 and 2020. The results are visualized to highlight regions of interests by masking areas where the anomaly is between −1 and 1 (Figure 1 and Figure 2).

Furthermore, weekly time series plots are generated to compare the FWI anomalies in 2022 with the reference period mean. These plots (Figure 3) provide insights into the temporal patterns of the fire danger, showcasing regions with excess fire danger compared to the reference period mean.

Overall, the methodology employed in this study facilitates a comprehensive understanding of FWI anomalies and their implications for fire danger assessment in the European context. The results shed light on areas exhibiting heightened fire risk, contributing valuable information for the ESOTC assessment.

4. Results

The anomaly analysis for the year 2022 provides crucial insights into the variation of Fire Weather Index (FWI) values compared to the reference period mean (1991–2020). This analysis involves a comparison of the number of days with FWI exceeding a threshold of 50 during 2022 against the number observed in the reference period. The visual representation of these results is depicted in Figure 1.

The x-axis of the plot represents geographic regions, while the y-axis indicates the magnitude of the FWI anomaly. Positive values on the y-axis signify an excess number of days with high FWI in 2022 compared to the reference period, represented in red. Conversely, negative values indicate a reduction in the number of days, with high FWI illustrated in blue. The shaded grey region, corresponding to FWI anomalies between −1 and 1, serves to pinpoint areas where the observed variation is within a relatively moderate range. This masking approach helps in focusing attention on regions where the FWI anomaly is more pronounced, either exceeding or falling below the expected values based on the reference period mean.

4.1. Global Assessment of FWI Anomalies in 2022: Identifying Fire Risk and Resilience

The global analysis of the FWI anomaly for the year 2022 (Figure 1) reveals distinct patterns across geographic regions, with regions with increased wildfire risk (highlighted in red) and those indicating a relative reduction in fire danger (highlighted in blue).

Noteworthy red regions are observed across various continents, indicating an elevated number of days with FWI exceeding the threshold of 50 in 2022 compared to the reference period mean. These areas, spanning parts of North America, South America, Africa, and Asia, might experience increased wildfire risk due to factors such as prolonged periods of high temperatures, reduced humidity, and limited precipitation during the analyzed period (Figure 1).

Regions with dense, combustible vegetation and ecosystems prone to rapid drying are susceptible to heightened fire risk. Arid and semi-arid regions, such as certain parts of Australia, the Mediterranean, and the Amazon rainforest, may exhibit increased vulnerability to wildfires as indicated by the red shading in Figure 1.

Noticeable blue regions, suggesting a reduction in the number of days with high FWI in 2022, are observed in temperate zones and areas with consistent precipitation. These areas include parts of Northern Europe, Canada, and the coastal regions of South America (Figure 1). Higher moisture content, milder temperatures, and adequate rainfall contribute to a lower risk of wildfires during the analyzed period.

Regions with resilient ecosystems, characterized by sufficient soil moisture and vegetation moisture content, tend to exhibit a relative reduction in fire danger. This resilience is often associated with temperate climates and regular precipitation, acting as protective factors against rapid vegetation drying and ignition.

In summary, the global analysis highlights diverse patterns of fire danger across continents (Figure 1). The identified regions in red and blue provide a comprehensive understanding of the complex interplay between climatic factors and wildfire risk on a global scale. This information underscores the importance of region-specific wildfire management strategies and global collaboration to address the multifaceted challenges associated with wildfire prevention and mitigation.

4.2. Assessment of FWI Anomalies over Europe in 2022: Unveiling Regional Fire Risk Dynamics

The analysis of the FWI anomaly over Europe (Figure 2) for the year 2022 reveals distinct patterns across geographic regions, with areas highlighted in red indicating potential heightened wildfire risk and those in blue suggesting a relative reduction in fire danger.

Notable red regions appear in Southern and Southeastern Europe, suggesting an elevated number of days with FWI exceeding the threshold of 50 in 2022 compared to the reference period mean. This heightened fire danger can be attributed to several factors. Warmer temperatures, lower relative humidity, and decreased precipitation during the summer months might have collectively contributed to increased vegetation dryness, rendering these areas more susceptible to ignition and rapid fire spread (top-left and top-right panels of Figure 2).

Regions with complex topography, such as a mountainous terrain, may experience increased fire danger due to the potential for enhanced wind channels and reduced moisture retention. These areas often exhibit heightened sensitivity to weather variations, amplifying the impact of unfavorable conditions on fire risk.

Notable blue regions in Northwestern and Northeastern Europe indicate a reduction in the number of days with FWI exceeding the threshold in 2022 compared to the reference period mean. This reduction could be linked to more moderate temperatures, higher relative humidity, or increased precipitation during the analyzed period. These factors contribute to the overall dampening of fire danger, making ignition and fire spread less likely (bottom-left and bottom-right panels of Figure 2).

Regions with ample vegetation moisture content and climate resilience, particularly those with a history of consistent precipitation, may experience a reduction in fire danger. Adequate soil moisture and higher humidity levels provide a protective buffer against rapid vegetation drying and ignition, mitigating the risk of wildfires.

In summary, the identified regions in red and blue provide valuable insights into the localized factors influencing fire danger. The observed patterns align with climate and geographical considerations, emphasizing the need for region-specific wildfire management strategies. This nuanced analysis supports targeted interventions, such as enhanced monitoring, early warning systems, and resource allocation, tailored to the distinct fire risk profiles of different European regions.

These visualized results enable a targeted identification of regions experiencing notable deviations in fire danger during the analyzed period. The regions highlighted in red indicate potential areas of increased wildfire risk, whereas those in blue suggest a relative reduction in fire danger. This nuanced understanding of FWI anomalies is essential for refining strategies in wildfire management, aiding in the allocation of resources and the implementation of preventive measures in regions prone to heightened fire risk.

4.3. Temporal Analysis of FWI Anomalies in 2022: Weekly Insights for European Regions

To delve deeper into the temporal patterns of fire danger, we generated weekly time series plots comparing the Fire Weather Index (FWI) anomalies in 2022 with the reference period mean for specific European regions. These plots, illustrated in Figure 3, offer valuable insights into the fluctuations and deviations in FWI values over the course of the year.

Figure 3 presents the weekly time series plots for ESOTC regions, namely, Europe, Southwestern Europe, Northwestern Europe, Southeastern Europe, and Northeastern Europe. The x-axis represents weeks, with data points showcasing the mean FWI values for each week. The shaded regions in Figures indicate the range of FWI values during the reference period, emphasizing the variability in fire danger.

The reference period mean is depicted by a solid line, providing a baseline for comparison. Additionally, the shaded areas above and below this line represent the 10th to 90th percentile range and the minimum to maximum range, respectively, during the reference period. Regions where the 2022 FWI values surpass the reference period mean are highlighted in red, while those falling below are depicted in blue.

These plots reveal distinct temporal patterns in fire danger across different European regions. Areas exhibiting excess fire danger in 2022 compared to the reference period are visually identified, providing a nuanced understanding of the region’s most susceptible to heightened fire risk during specific weeks of the year.

In summary, the weekly time series plots contribute a dynamic perspective to the ESOTC assessment, enhancing our ability to pinpoint regions with notable FWI anomalies. This information is pivotal for proactive measures in mitigating potential wildfire risks and underscores the significance of integrating detailed temporal analyses into climate assessments.

5. Discussion

5.1. Impact of Wildfires on Agrivoltaics

Wildfires pose significant challenges to agrivoltaic systems, which integrate solar energy production with agricultural practices [17]. The interaction between wildfires and agrivoltaics is multifaceted, influencing both the energy production and agricultural components of these systems. Wildfires can directly impact the energy production capacity of solar panels in agrivoltaic setups. The intense heat and flames from wildfires may damage or destroy solar panels, leading to a temporary or permanent reduction in energy generation. Additionally, smoke and debris from wildfires can accumulate on the surface of solar panels, reducing their efficiency and further hindering energy production [21,22].

Agrivoltaic systems are designed to support crop growth beneath solar panels, offering benefits such as shade and reduced evaporation (ma réf). However, wildfires can result in the destruction of crops due to direct exposure to flames or heat. The heat generated during a wildfire may also compromise soil health, affecting the nutrient composition and microbial activity crucial for plant growth. The combined impact of fire and heat stress can lead to significant agricultural losses within agrivoltaic systems [23,24].

Understanding the impact of wildfires on agrivoltaics is vital for developing resilient systems. Incorporating fire-resistant materials in the construction of solar panels, implementing vegetation management strategies, and designing firebreaks around agrivoltaic installations are potential measures to enhance resilience. Additionally, selecting fire-resistant and drought-tolerant crops can contribute to the overall adaptability of agrivoltaic systems in wildfire-prone regions [25].

The economic implications of wildfires on agrivoltaics extend beyond immediate damages. Reconstruction and replacement costs for damaged solar panels, loss of agricultural yields, and potential disruptions to energy supply contracts can result in financial setbacks for stakeholders. Evaluating the economic viability of agrivoltaic systems in wildfire-prone areas requires a comprehensive understanding of both short-term losses and long-term resilience strategies [26].

Effective wildfire management policies and emergency response plans are crucial for mitigating the impact on agrivoltaic systems. Collaborative efforts between energy and agriculture sectors, local authorities, and researchers are essential to develop guidelines for designing resilient agrivoltaic installations and implementing proactive measures to minimize the risk of wildfire-related damage.

In conclusion, the impact of wildfires on agrivoltaics necessitates a holistic approach that considers both energy production and agricultural aspects. Recognizing the vulnerabilities and implementing resilient strategies will be key to enhancing the sustainability and long-term viability of agrivoltaic systems in regions prone to wildfires.

5.2. Factors Contributing to Heightened FWI

Understanding the specific climatic and environmental factors that contribute to heightened Fire Weather Index (FWI) in different areas is essential for developing targeted wildfire management strategies. This section delves into the intricate interactions between various factors, shedding light on their role in influencing FWI dynamics.

• Temperature Extremes: Elevated temperatures are a primary driver of heightened FWI. Warmer conditions contribute to increased evaporation rates, drying out vegetation and fuels, thereby raising the overall flammability of the landscape. Regions experiencing prolonged periods of high temperatures, especially during critical months, are susceptible to heightened FWI. An analysis of temperature anomalies can highlight areas with increased fire danger [27,28].
• Relative Humidity: Low relative humidity exacerbates fire danger by accelerating the drying of vegetation. Regions with consistently low humidity levels, particularly during fire-prone seasons, may exhibit heightened FWI. An examination of humidity anomalies provides insights into areas where dry conditions contribute significantly to elevated FWI [29,30].
• Precipitation Patterns: Inadequate precipitation can lead to decreased moisture content in vegetation, increasing its susceptibility to ignition. Extended periods of drought, characterized by below-average precipitation, contribute to heightened FWI. An analysis of precipitation anomalies helps identify regions where insufficient rainfall is a contributing factor to increased fire danger [30,31].
• Vegetation Type and Structure: The type and structure of vegetation play a crucial role in FWI dynamics. Highly combustible vegetation, such as dry grasslands or dense forests with accumulated dead biomass, can significantly contribute to heightened fire danger. Examination of land cover and vegetation characteristics provides valuable insights into the potential for increased FWI in areas with specific vegetation types [32].
• Topography: Topographical features influence wind patterns and moisture retention, impacting fire spread. Mountainous terrain, for example, can channelize winds and contribute to the rapid spread of wildfires. Analyzing topographic factors, such as slope and aspect, helps identify areas where the landscape may amplify the effects of adverse weather conditions on FWI [33].
• Wind Speed and Direction: Wind can accelerate the spread of wildfires by carrying embers over longer distances. Regions experiencing consistently high wind speeds during fire-prone periods may face heightened FWI. A comprehensive assessment of wind speed and direction anomalies offers insights into areas where wind is a significant contributing factor to increased fire danger [34].

By examining these climatic and environmental factors in detail, this study aims to unravel the complexities underlying heightened FWI, providing a nuanced understanding of the diverse influences shaping fire danger in different regions. This knowledge is fundamental for developing effective and targeted wildfire prevention and management strategies.

5.3. Wildfire Management Strategies for European Regions

The insights gained from this study provide valuable information for informing targeted wildfire management strategies in European regions. By understanding the spatial and temporal patterns of FWI across Europe, authorities can identify areas at higher risk of wildfires and allocate resources more effectively. For regions experiencing heightened FWI, proactive measures such as increased monitoring, early warning systems, and enhanced firefighting capabilities can be implemented to mitigate the risk of wildfires. Additionally, knowledge of FWI variations can inform land-use planning and forest management practices to reduce the likelihood of ignition and limit the spread of wildfires. Furthermore, incorporating agrivoltaic systems into wildfire management strategies can offer additional benefits. Agrivoltaics, which combine agricultural production with solar energy generation, can help mitigate wildfire risk by reducing the availability of combustible vegetation through grazing or crop cultivation. Moreover, the shading provided by solar panels can create microclimatic conditions that decrease evaporation and increase soil moisture, potentially reducing the flammability of surrounding vegetation. By integrating insights from this study into wildfire management planning, European regions can enhance their resilience to wildfires and protect both human communities and ecosystems.

6. Conclusions and Policy Implications

This study presented a comprehensive analysis of the Fire Weather Index (FWI) for the European State of the Climate (ESOTC) assessment, aiming to visualize and understand the flammability of different European regions. The motivation for this research lies in the critical role that FWI plays in assessing fire danger, providing insights into potential wildfire risk based on weather conditions. The methodology involved retrieving historical FWI data from the European Forest Fire Information System (EFFIS), a part of the Copernicus Emergency Management Service (CEMS), and using various tools, including the Climate Data Store (CDS) API.

Results were obtained by calculating the anomaly of the number of days with FWI exceeding a threshold of 50 for the year 2022, compared to the reference period mean from 1991 to 2020. The anomaly analysis revealed distinct spatial patterns, highlighting regions with increased wildfire risk (in red) and those indicating a relative reduction in fire danger (in blue). Southern and Southeastern Europe exhibited heightened fire danger, attributed to factors like warmer temperatures, lower humidity, and decreased precipitation. Conversely, Northwestern and Northeastern Europe showed reduced fire danger, linked to more moderate temperatures, higher humidity, or increased precipitation.

The implications of these findings underscore the importance of region-specific wildfire management strategies. Regions with increased risk may benefit from enhanced monitoring, early warning systems, and resource allocation, while areas with reduced risk can focus on maintaining climate resilience and vegetation moisture content. The analysis contributes nuanced insights into the localized factors influencing fire danger, emphasizing the need for tailored interventions aligned with the distinct fire risk profiles of different European regions.

However, this study has its limitations. The analysis is based on FWI data and does not consider actual fire occurrences or ignition sources. Future areas for improvement could involve incorporating additional variables, such as lightning strike data or land cover characteristics, to enhance the predictive capability of the analysis. Additionally, exploring the impact of wildfires on real agrivoltaic systems could provide valuable insights into the intersection of fire risk, climate, and agriculture. Overall, this research contributes to the ongoing efforts to understand and address wildfire challenges in the world, with a particular focus on Europe, paving the way for informed decision-making and proactive wildfire management strategies.