Zobrazeno 1 - 10
of 318
pro vyhledávání: '"F. Di Giuseppe"'
Autor:
M. W. Jones, D. I. Kelley, C. A. Burton, F. Di Giuseppe, M. L. F. Barbosa, E. Brambleby, A. J. Hartley, A. Lombardi, G. Mataveli, J. R. McNorton, F. R. Spuler, J. B. Wessel, J. T. Abatzoglou, L. O. Anderson, N. Andela, S. Archibald, D. Armenteras, E. Burke, R. Carmenta, E. Chuvieco, H. Clarke, S. H. Doerr, P. M. Fernandes, L. Giglio, D. S. Hamilton, S. Hantson, S. Harris, P. Jain, C. A. Kolden, T. Kurvits, S. Lampe, S. Meier, S. New, M. Parrington, M. M. G. Perron, Y. Qu, N. S. Ribeiro, B. H. Saharjo, J. San-Miguel-Ayanz, J. K. Shuman, V. Tanpipat, G. R. van der Werf, S. Veraverbeke, G. Xanthopoulos
Publikováno v:
Earth System Science Data, Vol 16, Pp 3601-3685 (2024)
Climate change contributes to the increased frequency and intensity of wildfires globally, with significant impacts on society and the environment. However, our understanding of the global distribution of extreme fires remains skewed, primarily influ
Externí odkaz:
https://doaj.org/article/1290857b3acd4f2cb069464e1272169b
Publikováno v:
Geophysical Research Letters, Vol 51, Iss 12, Pp n/a-n/a (2024)
Abstract Accurate wildfire forecasting can inform regional management and mitigation strategies in advance of fire occurrence. Existing systems typically use fire danger indices to predict landscape flammability, based on meteorological forecasts alo
Externí odkaz:
https://doaj.org/article/f41723659fe4485ca6abf59515b66459
Autor:
J. R. McNorton, F. Di Giuseppe
Publikováno v:
Biogeosciences, Vol 21, Pp 279-300 (2024)
Effective wildfire management and prevention strategies depend on accurate forecasts of fire occurrence and propagation. Fuel load and fuel moisture content are essential variables for forecasting fire occurrence, and whilst existing operational syst
Externí odkaz:
https://doaj.org/article/d2e72b257d4a481a8ec9cb0860c5f0f9
Autor:
F. Di Giuseppe
Publikováno v:
Geophysical Research Letters, Vol 49, Iss 17, Pp n/a-n/a (2022)
Abstract In 2021, the availability of a physical model for lightning density prediction at ECMWF led to the development of data driven models to identify episodes conducive of fires. The machine‐learning classifiers worked remarkably well reaching
Externí odkaz:
https://doaj.org/article/e04a251dce8f49819ea64d352f8e005c
Publikováno v:
Natural Hazards and Earth System Sciences, Vol 20, Pp 2365-2378 (2020)
In the framework of the EU Copernicus programme, the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the Joint Research Centre (JRC) is forecasting daily fire weather indices using its medium-range ensemble prediction system.
Externí odkaz:
https://doaj.org/article/bae2477232a943aca3d15c42263a5c57
Publikováno v:
Atmospheric Chemistry and Physics, Vol 19, Pp 987-998 (2019)
Asian dust is a seasonal meteorological phenomenon which affects east Asia, and has severe consequences on the air quality of China, North and South Korea and Japan. Despite the continental extent, the prediction of severe episodes and the anticipati
Externí odkaz:
https://doaj.org/article/d71f4483eee84b12a74a5d73adeacef1
Autor:
A. Benedetti, J. S. Reid, P. Knippertz, J. H. Marsham, F. Di Giuseppe, S. Rémy, S. Basart, O. Boucher, I. M. Brooks, L. Menut, L. Mona, P. Laj, G. Pappalardo, A. Wiedensohler, A. Baklanov, M. Brooks, P. R. Colarco, E. Cuevas, A. da Silva, J. Escribano, J. Flemming, N. Huneeus, O. Jorba, S. Kazadzis, S. Kinne, T. Popp, P. K. Quinn, T. T. Sekiyama, T. Tanaka, E. Terradellas
Publikováno v:
Atmospheric Chemistry and Physics, Vol 18, Pp 10615-10643 (2018)
Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory b
Externí odkaz:
https://doaj.org/article/e38b6ad0fefe411b96ba5bf86272b358
Autor:
F. Wetterhall, F. Di Giuseppe
Publikováno v:
Hydrology and Earth System Sciences, Vol 22, Pp 3409-3420 (2018)
Two different systems provide long-range forecasts at ECMWF. On the sub-seasonal timescale, ECMWF issues an extended-range ensemble prediction system (ENS-ER) which runs a 46-day forecast integration issued twice weekly. On longer timescales, the
Externí odkaz:
https://doaj.org/article/35beab6114754d27bf4d0e0982f981fe
Publikováno v:
Atmospheric Chemistry and Physics, Vol 18, Pp 5359-5370 (2018)
The atmospheric composition analysis and forecast for the European Copernicus Atmosphere Monitoring Services (CAMS) relies on biomass-burning fire emission estimates from the Global Fire Assimilation System (GFAS). The GFAS is a global system and
Externí odkaz:
https://doaj.org/article/ad4e479eaee8411d8a98affc818ad6d0
Autor:
E. Dutra, W. Pozzi, F. Wetterhall, F. Di Giuseppe, L. Magnusson, G. Naumann, P. Barbosa, J. Vogt, F. Pappenberger
Publikováno v:
Hydrology and Earth System Sciences, Vol 18, Iss 7, Pp 2669-2678 (2014)
Global seasonal forecasts of meteorological drought using the standardized precipitation index (SPI) are produced using two data sets as initial conditions: the Global Precipitation Climatology Centre (GPCC) and the European Centre for Medium-Range W
Externí odkaz:
https://doaj.org/article/051e7312c80a4a8db6b421adba76e8a0