Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Andrew Schepen"'
Autor:
James S. Risbey, Dougal T. Squire, Amanda S. Black, Timothy DelSole, Chiara Lepore, Richard J. Matear, Didier P. Monselesan, Thomas S. Moore, Doug Richardson, Andrew Schepen, Michael K. Tippett, Carly R. Tozer
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-14 (2021)
Many different methods have been developed to forecast climate phenomena like the El Nino-Southern Oscillation (ENSO) which makes a fair comparison of their capabilities crucial. In this perspective, the authors discuss how choices in the evaluation
Externí odkaz:
https://doaj.org/article/9d7dd92951164f0cb18c3354bbbe7c83
For streamflow forecasting, calibration of ensemble numerical weather prediction (NWP) models has long been considered a necessary evil. Necessary, because NWP forecasts are usually too biased to force calibrated hydrological models, they often produ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7afc9c1fd7ca06c3349c0dae130677f3
https://doi.org/10.5194/egusphere-egu23-4846
https://doi.org/10.5194/egusphere-egu23-4846
The continuing improvement of seasonal rainfall outlooks means they are now skillful enough to predict inflows to hydropower schemes and help to anticipate operational decisions. Hydro Tasmania, Australia’s largest generator of hydropower, is worki
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f45e3ee31ba61317464ff6cf5231bd9
https://doi.org/10.5194/egusphere-egu23-5859
https://doi.org/10.5194/egusphere-egu23-5859
Publikováno v:
International Journal of Climatology. 42:4972-4988
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c6875ab66096701de61bab5925f439c
https://doi.org/10.1002/joc.7515
https://doi.org/10.1002/joc.7515
Publikováno v:
Journal of Hydrometeorology. 23:25-37
Climate trends have been observed over the recent decades in many parts of the world, but current global climate models (GCMs) for seasonal climate forecasting often fail to capture these trends. As a result, model forecasts may be biased above or be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba46f020cb4c126316459ae0b0668c94
https://doi.org/10.1175/jhm-d-21-0099.1
https://doi.org/10.1175/jhm-d-21-0099.1
Publikováno v:
Monthly Weather Review. 149:2513-2522
For managing climate variability and adapting to climate change, seasonal forecasts are widely produced to inform decision-making. However, seasonal forecasts from global climate models are found to poorly reproduce temperature trends in observations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24398d343c3ef7ee99b03c620708372a
https://doi.org/10.1175/mwr-d-20-0318.1
https://doi.org/10.1175/mwr-d-20-0318.1
Autor:
Andrew Schepen, Doug Richardson, Didier Monselesan, Amanda S. Black, Dougal T. Squire, Carly R. Tozer, James S. Risbey, Thomas S. Moore
Publikováno v:
Journal of Hydrometeorology. 22:371-385
Subseasonal forecast skill is not homogeneous in time, and prior assessment of the likely forecast skill would be valuable for end-users. We propose a method for identifying periods of high forecast confidence using atmospheric circulation patterns,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fffbb20fe6e05fe2c44a58792cfe478c
https://doi.org/10.1175/jhm-d-20-0054.1
https://doi.org/10.1175/jhm-d-20-0054.1
Publikováno v:
Monthly Weather Review. 148:437-456
Multivariate seasonal climate forecasts are increasingly required for quantitative modeling in support of natural resources management and agriculture. GCM forecasts typically require postprocessing to reduce biases and improve reliability; however,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b36993e3602b355d5c2d91c7b690e698
https://doi.org/10.1175/mwr-d-19-0046.1
https://doi.org/10.1175/mwr-d-19-0046.1
Publikováno v:
Agricultural and Forest Meteorology. 324:109116
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3053f917bfe3af72cefe238a2832df4
https://doi.org/10.1016/j.agrformet.2022.109116
https://doi.org/10.1016/j.agrformet.2022.109116
Autor:
Andrew Schepen, Doug Richardson, Dougal T. Squire, Amanda S. Black, Didier Monselesan, Michael K. Tippett, Carly R. Tozer, James S. Risbey, Thomas S. Moore, Chiara Lepore, Richard J. Matear, Timothy DelSole
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-14 (2021)
Nature Communications
Nature Communications
Assessments of climate forecast skill depend on choices made by the assessor. In this perspective, we use forecasts of the El Niño-Southern-Oscillation to outline the impact of bias-correction on skill. Many assessments of skill from hindcasts (past
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::111233c5222292301bfda32c8fa86a98
https://doi.org/10.1038/s41467-021-23771-z
https://doi.org/10.1038/s41467-021-23771-z