The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where Robert Cifelli sits on this spectrum.
This scientist: 148 publications — 40th percentile
40% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 687 publications or more.
The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where Robert Cifelli sits on this spectrum.
This scientist: 40 D-Index — 19th percentile
19% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 125 D-Index or more.
Robert Cifelli is affiliated with the National Oceanic and Atmospheric Administration in the United States. Their research primarily focuses on earth and planetary sciences, with significant contributions to environmental science. Within these broad fields, their work spans multiple subfields, including atmospheric science, global and planetary change, water science and technology, environmental engineering, and earth-surface processes.
Their scientific investigations cover a range of topics relevant to meteorological and hydrological phenomena. The main topics addressed in their publications include:
Their work has been published extensively in several notable journals and publication venues, including:
Frequent collaborators with Robert Cifelli include Haonan Chen, Kelly Mahoney, Mimi Hughes, Francesca Viterbo, and David Gochis. These partnerships have contributed to a multidisciplinary approach toward understanding atmospheric and hydrological processes.
Among their recent papers, several stand out for their focus on operational forecasting, model evaluation, and machine learning applications in meteorology:
These publications reflect an engagement with both theoretical and applied dimensions of meteorological science, including the use of advanced computational methods such as deep learning for improving weather prediction and satellite data interpretation.
Stephen W. Nesbitt;Robert Cifelli;Steven A. Rutledge
R. Cifelli;V. Chandrasekar;S. Lim;P. C. Kennedy
Robert Cifelli;Walter A. Petersen;Lawrence D. Carey;Steven A. Rutledge
K. M. Lau;Yihui Ding;Jough-Tai Wang;Richard Johnson
S. Lang;W-K. Tao;J. Simpson;R. Cifelli
Walter A. Petersen;Stephen W. Nesbitt;Richard J. Blakeslee;Robert Cifelli
Edward J. Zipser;Cynthia H. Twohy;Si Chee Tsay;K. Lee Thornhill
Robert Cifelli;Nolan Doesken;Patrick Kennedy;Lawrence D. Carey
Jeffrey L. Stith;James E. Dye;Aaron Bansemer;Andrew J. Heymsfield
Kelly Mahoney;Darren L. Jackson;Paul Neiman;Mimi Hughes
Wayne Higgins;Dave Ahijevych;Jorge Amador;Ana Barros
David J. Raymond;Steven K. Esbensen;Clayton Paulson;Michael Gregg
Haonan Chen;V. Chandrasekar;Robert Cifelli;Pingping Xie
Timothy J. Lang;David A. Ahijevych;Stephen W. Nesbitt;Richard E. Carbone
Gwo-Jong Huang;V. N. Bringi;Robert Cifelli;David Hudak
J. J. Shi;J. J. Shi;W.-K. Tao;T. Matsui;T. Matsui;R. Cifelli
Robert Cifelli;V. Chandrasekar;Haonan Chen;Haonan Chen;Lynn E. Johnson;Lynn E. Johnson
Robert Cifelli;Christopher R. Williams;Deepak K. Rajopadhyaya;Susan K. Avery
Benjamin J. Moore;Kelly M. Mahoney;Ellen M. Sukovich;Robert Cifelli
Robert Cifelli;Steven A. Rutledge
Haonan Chen;Haonan Chen;V. Chandrasekar;Haiming Tan;Robert Cifelli
K. M. Lau;Yihui Ding;Jough-Tai Wang;Richard Johnson
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