J
Jeanine Jones
Researcher at California Department of Water Resources
Publications - 5
Citations - 234
Jeanine Jones is an academic researcher from California Department of Water Resources. The author has contributed to research in topics: Storm & Precipitation. The author has an hindex of 3, co-authored 5 publications receiving 117 citations.
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Journal ArticleDOI
Windows of opportunity for skillful forecasts subseasonal to seasonal and beyond
Annarita Mariotti,Cory Baggett,Elizabeth A. Barnes,Emily Becker,Amy H. Butler,Dan C. Collins,Paul A. Dirmeyer,Laura Ferranti,Nathaniel C. Johnson,Jeanine Jones,Ben P. Kirtman,Andrea L. Lang,Andrea Molod,Matthew Newman,Andrew W. Robertson,Siegfried D. Schubert,Duane E. Waliser,John R. Albers +17 more
TL;DR: There is high demand and a growing expectation for predictions of environmental conditions that go beyond 0-14-day weather forecasts with outlooks extending to one or more seasons and beyon... as discussed by the authors.
Journal ArticleDOI
A Vision for Future Observations for Western U.S. Extreme Precipitation and Flooding
F. M. Ralph,Michael D. Dettinger,Allen B. White,David W. Reynolds,Daniel R. Cayan,Timothy Schneider,Robert Cifelli,K. T. Redmond,Michael L. Anderson,F. Gherke,Jeanine Jones,Kelly Mahoney,L.E. Johnson,Seth I. Gutman,V. Chandrasekar,Jessica D. Lundquist,Noah P. Molotch,Levi D. Brekke,Roger S. Pulwarty,John D. Horel,Lawrence J. Schick,A. Edman,Philip W. Mote,John T. Abatzoglou,R. B. Pierce,Gary A. Wick +25 more
TL;DR: In this paper, the authors present a vision for mitigating impacts of such weather and water extremes that is tailored to the unique meteorological conditions and user needs of the Western U.S. in the 21st Century.
Journal ArticleDOI
Seasonal cultivated and fallow cropland mapping using MODIS-based automated cropland classification algorithm
Zhuoting Wu,Zhuoting Wu,Prasad S. Thenkabail,Rick Mueller,Audra Zakzeski,Forrest Melton,Forrest Melton,Lee F. Johnson,Lee F. Johnson,Carolyn Rosevelt,John L. Dwyer,Jeanine Jones,James P. Verdin +12 more
TL;DR: In this article, the authors developed and tested automated cropland classification algorithm (ACCA) that provide accurate, consistent, and repeatable information on seasonal cultivated as well as seasonal fallow croplands extents and areas based on the Moderate Resolution Imaging Spectroradiometer remote sensing data.