42 citations as recorded by crossref.

1. Statistical calibration of probabilistic medium-range Fire Weather Index forecasts in Europe S. Bohlmann & M. Laine 10.5194/nhess-24-4225-2024
2. Climate change induced declines in fuel moisture may turn currently fire-free Pyrenean mountain forests into fire-prone ecosystems V. Resco de Dios et al. 10.1016/j.scitotenv.2021.149104
3. Some Challenges for Forest Fire Risk Predictions in the 21st Century V. Resco de Dios & R. Nolan 10.3390/f12040469
4. The compound event that triggered the destructive fires of October 2017 in Portugal A. Ramos et al. 10.1016/j.isci.2023.106141
5. A Global Bottom‐Up Approach to Estimate Fuel Consumed by Fires Using Above Ground Biomass Observations F. Di Giuseppe et al. 10.1029/2021GL095452
6. Forecast Zoning of Forest Fire Occurrence: A Case Study in Southern China X. Jing et al. 10.3390/f15020265
7. Prediction of Forest Fire Occurrence in Southwestern China X. Jing et al. 10.3390/f14091797
8. Brief communication: Key papers of 20 years in Natural Hazards and Earth System Sciences A. Gain et al. 10.5194/nhess-22-985-2022
9. Simulation-based high-resolution fire danger mapping using deep learning F. Allaire et al. 10.1071/WF21143
10. Historical spatiotemporal changes in fire danger potential across biomes J. Baijnath-Rodino et al. 10.1016/j.scitotenv.2023.161954
11. Utilizing Deep Learning and Spatial Analysis for Accurate Forest Fire Occurrence Forecasting in the Central Region of China Y. Guo et al. 10.3390/f15081380
12. Consideration of compound drivers and impacts in the disaster risk reduction cycle B. van den Hurk et al. 10.1016/j.isci.2023.106030
13. How well do multi-fire danger rating indices represent China forest fire variations across multi-time scales? Y. Pan et al. 10.1088/1748-9326/ad2d3d
14. Mapping the Most Susceptible Regions to Fire in Portugal T. Ermitão et al. 10.3390/fire6070254
15. Using hydrological modelling to improve the Fire Weather Index system over tropical peatlands of peninsular Malaysia, Sumatra and Borneo J. Mortelmans et al. 10.1071/WF24057
16. Creating resilient communities with medium-range hazard warning systems B. Fakhruddin et al. 10.1016/j.pdisas.2021.100203
17. Global data-driven prediction of fire activity F. Di Giuseppe et al. 10.1038/s41467-025-58097-7
18. Global warming is shifting the relationships between fire weather and realized fire-induced CO2 emissions in Europe J. Carnicer et al. 10.1038/s41598-022-14480-8
19. Contribution to the Study of Forest Fires in Semi-Arid Regions with the Use of Canadian Fire Weather Index Application in Greece N. Ntinopoulos et al. 10.3390/cli10100143
20. Multiscale Interactions between Local Short- and Long-Term Spatio-Temporal Mechanisms and Their Impact on California Wildfire Dynamics S. Afolayan et al. 10.3390/fire7070247
21. Impact of meteorological uncertainties on PM2.5 forecast: An ensemble air quality forecast study during 2022 Beijing Winter Olympics W. Wen et al. 10.1016/j.atmosenv.2025.121027
22. Sentinel-1 Response to Canopy Moisture in Mediterranean Forests before and after Fire Events F. Pirotti et al. 10.3390/rs15030823
23. Convergence in critical fuel moisture and fire weather thresholds associated with fire activity in the pyroregions of Mediterranean Europe V. Resco de Dios et al. 10.1016/j.scitotenv.2021.151462
24. Global seasonal prediction of fire danger F. Di Giuseppe et al. 10.1038/s41597-024-02948-3
25. State of Wildfires 2023–2024 M. Jones et al. 10.5194/essd-16-3601-2024
26. Combining precipitation forecasts and vegetation health to predict fire risk at subseasonal timescale in the Amazon K. Fernandes et al. 10.1088/1748-9326/ac76d8
27. Drought triggers and sustains overnight fires in North America K. Luo et al. 10.1038/s41586-024-07028-5
28. On the potential of using smartphone sensors for wildfire hazard estimation through citizen science H. Shachaf et al. 10.5194/nhess-24-3035-2024
29. Equations to Predict Carbon Monoxide Emissions from Amazon Rainforest Fires S. Gallup et al. 10.3390/fire7120477
30. Downscaled subseasonal fire danger forecast skill across the contiguous United States J. Abatzoglou et al. 10.1002/asl.1165
31. Google Earth Engine Framework for Satellite Data-Driven Wildfire Monitoring in Ukraine B. Yailymov et al. 10.3390/fire6110411
32. Accounting for fuel in fire danger forecasts: the fire occurrence probability index (FOPI) F. Di Giuseppe 10.1088/1748-9326/acd2ee
33. Vegetation optical depth as a key predictor for fire risk escalation D. Kankanige et al. 10.1016/j.ecoinf.2025.103050
34. Developing novel machine-learning-based fire weather indices A. Shmuel & E. Heifetz 10.1088/2632-2153/acc008
35. Europe faces up to tenfold increase in extreme fires in a warming climate S. El Garroussi et al. 10.1038/s41612-024-00575-8
36. The Performance of ECMWF Ensemble Prediction System for European Extreme Fires: Portugal/Monchique in 2018 R. Durão et al. 10.3390/atmos13081239
37. Probabilistic fire-danger forecasting: A framework for week-two forecasts using statistical post-processing techniques and the Global ECMWF Fire Forecast System (GEFF) R. Worsnop et al. 10.1175/WAF-D-21-0075.1
38. Exploring Forest Fire Dynamics: Fire Danger Mapping in Antalya Region, Türkiye H. Atalay et al. 10.3390/ijgi13030074
39. Multi-Indices Diagnosis of the Conditions That Led to the Two 2017 Major Wildfires in Portugal C. Andrade & L. Bugalho 10.3390/fire6020056
40. Improving the fire weather index system for peatlands using peat-specific hydrological input data J. Mortelmans et al. 10.5194/nhess-24-445-2024
41. Skillful seasonal prediction of key carbon cycle components: NPP and fire risk P. Bett et al. 10.1088/2515-7620/ab8b29
42. High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model A. Mandal et al. 10.1071/WF21106