Wildfires are favored by hot, dry, windy, rainless conditions-this knowledge about fire weather informs both short-term forecast and long-term prediction of wildfire activity. Yet, wildfires rely on the availability of ignition and fuel, which are underrepresented in fire forecast and prediction practices. By analyzing satellite measurements and atmospheric reanalysis, here we show that near-surface weather only partially captures wildfire occurrence and intensity across the daily to seasonal timescales. Beyond near-surface weather, convection and fuel abundance play a complementary role in regulating burning processes. Specifically, enhanced atmospheric convection is identified for over 40% of the low-human-impact regions and 61% of global burnable areas during wildfire ignition and spreading periods. Meanwhile, 56% of shrublands and 54% of grasslands see higher fuel load with actual occurrence of fire. Our results highlight the role of convection and fuel in wildfire forecast, prompting a revisit of wildfire prediction under intertwined atmospheric and terrestrial changes.
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http://dx.doi.org/10.1126/sciadv.adp7765 | DOI Listing |
Sci Rep
March 2025
Royal Society for the Protection of Birds, Sandy, UK.
ENSO (El Niño Southern Oscillation) events are becoming more frequent and more intense as climate change continues. Although ENSO effects are known to propagate into the southwest Atlantic, knowledge of how these anomalies result in ecological impacts is yet to be documented. A 3600 km transect in the southwest Atlantic from the Falkland Islands (Malvinas) to Tristan da Cunha during La Niña (March 2018) found a more abundant and speciose seabird assemblage, with more filter-feeding seabird and cetacean species, and a shallower and more concentrated pelagic biomass, than a near identical transect during El Niño (March 2019).
View Article and Find Full Text PDFNat Commun
March 2025
Frontiers Science Center for Deep Ocean Multispheres and Earth System and Key Laboratory of Ocean dynamics/Academy of Future Ocean, Ocean University of China, Qingdao, China.
Mesoscale eddies with horizontal scales from tens to hundreds of kilometers are ubiquitous in the upper ocean, dominating the ocean variability from daily to weekly time scales. Their turbulent nature causes great scientific challenges and computational burdens in accurately forecasting the short-term evolution of the ocean states based on conventional physics-driven numerical models. Recently, artificial intelligence (AI)-based methods have achieved competitive forecast performance and greatly increased computational efficiency in weather forecasts, compared to numerical models.
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February 2025
State Key Laboratory of Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing, 100190, China.
The atmospheric electric field (AEF) is an important electrical phenomenon that occurs between the Earth's surface and the ionosphere. It is primarily formed by negative charges on the surface and positive charges in the ionosphere, and is regulated by multiple factors, such as solar activity, meteorological conditions, and air pollution. On the basis of AEF's observational data from fair weather days in the Chenggong district of Yunnan, this study analyzes its daily variation trends, focusing on its correlations with the air quality indicator concentrations of PM2.
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February 2025
Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
Wildfires are favored by hot, dry, windy, rainless conditions-this knowledge about fire weather informs both short-term forecast and long-term prediction of wildfire activity. Yet, wildfires rely on the availability of ignition and fuel, which are underrepresented in fire forecast and prediction practices. By analyzing satellite measurements and atmospheric reanalysis, here we show that near-surface weather only partially captures wildfire occurrence and intensity across the daily to seasonal timescales.
View Article and Find Full Text PDFData Brief
April 2025
Net Zero and Resilient Farming, Rothamsted Research, North Wyke, Okehampton, Devon EX20 2SB, UK.
Weather conditions, hydrological responses and the dynamics of key nitrogen species in field runoff were continuously monitored at 15-min resolution on the intensively instrumented North Wyke Farm Platform (NWFP), a UK National Bioscience Research Infrastructure (NBRI), to support research on sustainable and resilient agriculture in the UK. Released data spanning 2013 to 2024 for 6 selected field catchments were aggregated to daily timestep, with reference to data quality flags, to produce continuous weather data, including maximum and minimum air temperature, daily total rainfall, wind speed and quality assured daily average soil moisture content, soil temperature at 15 cm depth, runoff rates, as well as nitrate, nitrite and ammonium concentrations. External data sources were sourced to infill some gaps for the weather data and summary statistics on data coverage were generated for the other data on an annual and seasonal basis where appropriate.
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