Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Julia Wagemann"'
Publikováno v:
International Journal of Digital Earth, Vol 14, Iss 12, Pp 1758-1774 (2021)
Cloud-based services introduce a paradigm shift in how users access, process and analyse Big Earth data. A key challenge is to align the current state of how users access, process and analyse the data with trends and roadmaps large data organisations
Externí odkaz:
https://doaj.org/article/9cc5e66840bb4834969651a1a9adb0e4
Autor:
Julia Wagemann, Federico Fierli, Simone Mantovani, Stephan Siemen, Bernhard Seeger, Jörg Bendix
Publikováno v:
Remote Sensing, Vol 14, Iss 14, p 3359 (2022)
There is a growing demand to train Earth Observation (EO) data users in how to access and use existing and upcoming data. A promising tool for data-related training is computational notebooks, which are interactive web applications that combine text,
Externí odkaz:
https://doaj.org/article/ee4f80603d5347a9b906390cb573dc62
Publikováno v:
International Journal of Digital Earth, Vol 11, Iss 1, Pp 7-25 (2018)
Big Earth Data has experienced a considerable increase in volume in recent years due to improved sensing technologies and improvement of numerical-weather prediction models. The traditional geospatial data analysis workflow hinders the use of large v
Externí odkaz:
https://doaj.org/article/f1cebfe8cc2b49d0ac006975eb168bf0
Publikováno v:
International Journal of Digital Earth. 14:1758-1774
Cloud-based services introduce a paradigm shift in how users access, process and analyse Big Earth data. A key challenge is to align the current state of how users access, process and analyse the d...
Publikováno v:
Journal of Open Source Education. 6:172
Autor:
Timo Kelder, Tim Marjoribanks, Louise Slater, Christel Prudhomme, Rob Wilby, Julia Wagemann, Nick Dunstone
Ensemble members from weather and climate predictions can be used to generate large samples of simulated weather events, allowing the estimation of extreme (hitherto unseen) events. Here, we provide a protocol and open workflow for applying the ‘UN
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c6f6103803086c8478ef1b7552972d25
https://doi.org/10.31223/x5t04c
https://doi.org/10.31223/x5t04c
Publikováno v:
IGARSS
Women, trans gender and nonbinary people continue to be underrepresented in scientific and technological fields, the geospatial and earth observation domain notwithstanding. A lack of same-gender role models, challenges caused by implicit bias and a
The European Centre for Medium-Range Weather Forecasts (ECMWF) is moving gradually towards an open data licence , aiming to make real-time forecast data available under a full, free and open data license by 2025. The introduction of open data policie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::67fa23d4f55a4be6e9009529eab548a9
https://doi.org/10.5194/ems2021-468
https://doi.org/10.5194/ems2021-468
Seasonal predictions as a high-resolution large ensemble to study extreme events over recent decades
Autor:
Julia Wagemann, Robert L. Wilby, Timothy I. Marjoribanks, Louise J. Slater, Timo Kelder, Christel Prudhomme
Large ensembles of climate model simulations may be used to assess the likelihood of extreme events, which only have a limited chance of occurring in observed records. In this talk, we discuss how the ECMWF seasonal prediction system SEAS5 can be use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d80c7b937c1e3c18c0057f9814ea8cf
https://doi.org/10.5194/egusphere-egu21-12136
https://doi.org/10.5194/egusphere-egu21-12136