Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Julie Bessac"'
Autor:
Brandi L. Gamelin, Jeremy Feinstein, Jiali Wang, Julie Bessac, Eugene Yan, Veerabhadra R. Kotamarthi
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-15 (2022)
Abstract Global warming is expected to enhance drought extremes in the United States throughout the twenty-first century. Projecting these changes can be complex in regions with large variability in atmospheric and soil moisture on small spatial scal
Externí odkaz:
https://doaj.org/article/f49654f097ab4fcebcf047af7e8c0463
Publikováno v:
IEEE Open Access Journal of Power and Energy, Vol 9, Pp 66-75 (2022)
Disturbances in power systems, such as a generator trip, affect the frequency and voltage of the power grid. A framework that enables anticipating potentially dangerous frequency excursions (as signs of the disturbance start to reach sensors) is cruc
Externí odkaz:
https://doaj.org/article/d3474fe96e964c08820c46591b1b5090
Publikováno v:
Weather and Climate Extremes, Vol 36, Iss , Pp 100438- (2022)
In traditional extreme value analysis, the bulk of the data is ignored, and only the tails of the distribution are used for inference. Extreme observations are specified as values that exceed a threshold or as maximum values over distinct blocks of t
Externí odkaz:
https://doaj.org/article/7703a4e1882843b6b481fe1806172f9d
Publikováno v:
Journal of Advances in Modeling Earth Systems, Vol 13, Iss 4, Pp n/a-n/a (2021)
Abstract Stochastic representation of the influence of the subgrid‐scales on the resolved scales in weather and climate models has been shown to improve ensemble spread and resolved variability. We propose a statistical scale‐aware space‐time m
Externí odkaz:
https://doaj.org/article/4bb6a8e9262446ca9d79f6fe70c4ef95
Publikováno v:
Journal of Agricultural, Biological and Environmental Statistics. 28:358-364
We thank the authors for this interesting paper that highlights important ideas and concepts for the future of climate model ensembles and their storage, as well as future uses of stochastic emulators. Stochastic emulators are particularly relevant b
Publikováno v:
Advances in Statistical Climatology, Meteorology and Oceanography. 8:205-224
This study develops a statistical conditional approach to evaluate climate model performance in wind speed and direction and to project their future changes under the Representative Concentration Pathway (RCP) 8.5 scenario over inland and offshore lo
Understanding large-scale drought patterns and the mechanisms producing extreme drought events is vital to understanding future drought risks. Here we investigate the influence of teleconnections originating in the Pacific and Atlantic Oceans on regi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6486f461109ae41c4a461a107ec5398c
https://doi.org/10.5194/egusphere-egu23-2904
https://doi.org/10.5194/egusphere-egu23-2904
Publikováno v:
Computational Statistics & Data Analysis. 185:107762
We propose to use deep learning to estimate parameters in statistical models when standard likelihood estimation methods are computationally infeasible. We show how to estimate parameters from max-stable processes, where inference is exceptionally ch
Publikováno v:
2022 IEEE/ACM 8th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD).
Publikováno v:
Statistical Analysis and Data Mining: The ASA Data Science Journal. 14:662-675