Jaime Daniels

1.7k total citations · 1 hit paper
31 papers, 1.2k citations indexed

About

Jaime Daniels is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Jaime Daniels has authored 31 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Atmospheric Science, 17 papers in Global and Planetary Change and 7 papers in Oceanography. Recurrent topics in Jaime Daniels's work include Meteorological Phenomena and Simulations (22 papers), Climate variability and models (10 papers) and Atmospheric and Environmental Gas Dynamics (7 papers). Jaime Daniels is often cited by papers focused on Meteorological Phenomena and Simulations (22 papers), Climate variability and models (10 papers) and Atmospheric and Environmental Gas Dynamics (7 papers). Jaime Daniels collaborates with scholars based in United States, Germany and Finland. Jaime Daniels's co-authors include Timothy J. Schmit, Paul C. Griffith, Mathew M. Gunshor, Steven J. Goodman, Wayne Bresky, Christopher S. Velden, W. Paul Menzel, Steven Wanzong, David Santek and Steven J. Nieman and has published in prestigious journals such as Geophysical Research Letters, Monthly Weather Review and Bulletin of the American Meteorological Society.

In The Last Decade

Jaime Daniels

28 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Closer Look at the ABI on the GOES-R Series

2016 510 citations Timothy J. Schmit, Paul C. Griffith et al. Bulletin of the American Meteorological Society profile →

Peers

Jaime Daniels

AS

GPC

OCEAN

EE

AE

Pascal Brunel France

Mathew M. Gunshor United States

Kenneth Holmlund Germany

James J. Gurka United States

Lihang Zhou United States

Sergio Rota Germany

P. D. Watts Germany

Alain Ratier Germany

Paolo Pili Germany

Naimeng Lu China

Pascal Brunel France

Jaime Daniels

1.2k ×1.3

AS

1.0k ×1.2

GPC

126 ×0.7

OCEAN

169 ×1.5

EE

124 ×1.1

AE

Citations per year, relative to Jaime Daniels Jaime Daniels (= 1×) peers Pascal Brunel

Countries citing papers authored by Jaime Daniels

Since Specialization

Citations

This map shows the geographic impact of Jaime Daniels's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jaime Daniels with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaime Daniels more than expected).

Fields of papers citing papers by Jaime Daniels

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jaime Daniels. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jaime Daniels. The network helps show where Jaime Daniels may publish in the future.

Co-authorship network of co-authors of Jaime Daniels

This figure shows the co-authorship network connecting the top 25 collaborators of Jaime Daniels. A scholar is included among the top collaborators of Jaime Daniels based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jaime Daniels. Jaime Daniels is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Pinker, R. T., Yingtao Ma, Wen Chen, et al.. (2022). Top-of-the-atmosphere reflected shortwave radiative fluxes from GOES-R. Atmospheric measurement techniques. 15(17). 5077–5094. 4 indexed citations

2.

Günther, Tobias, Ákos Horváth, Wayne Bresky, Jaime Daniels, & Stefan A. Buehler. (2021). Lagrangian Coherent Structures and Vortex Formation in High Spatiotemporal‐Resolution Satellite Winds of an Atmospheric Kármán Vortex Street. Journal of Geophysical Research Atmospheres. 126(19). 4 indexed citations

3.

Horváth, Ákos, Wayne Bresky, Jaime Daniels, et al.. (2020). Evolution of an Atmospheric Kármán Vortex Street From High‐Resolution Satellite Winds: Guadalupe Island Case Study. Journal of Geophysical Research Atmospheres. 125(4). 15 indexed citations

4.

Yu, Yunyue, Peng Yu, & Jaime Daniels. (2019). Production, monitoring and evaluation of GOES-R series land surface temperature data (Conference Presentation). 50–50.

5.

Santek, David, Richard Dworak, Régis Borde, et al.. (2019). 2018 Atmospheric Motion Vector (AMV) Intercomparison Study. Remote Sensing. 11(19). 2240–2240. 20 indexed citations

6.

Daniels, Jaime. (2018). Introducing Atmospheric Motion Vectors Derived from the GOES-16 Advanced Baseline Imager (ABI). 1 indexed citations

7.

Kalluri, Satya, Jaime Daniels, Mathew M. Gunshor, et al.. (2018). The First Year of Advanced Baseline Imager. 7. 8601–8604. 1 indexed citations

8.

Daniels, Jaime. (2017). Use of GOES-R Advanced Baseline Imager (ABI) Proxy Data to Assess the Performance of the GOES-R Winds Algorithm. 1 indexed citations

9.

Schmit, Timothy J., et al.. (2016). A Closer Look at the ABI on the GOES-R Series. Bulletin of the American Meteorological Society. 98(4). 681–698. 510 indexed citations breakdown →

10.

Velden, Christopher S., et al.. (2016). Assimilation of High-Resolution Satellite-Derived Atmospheric Motion Vectors: Impact on HWRF Forecasts of Tropical Cyclone Track and Intensity. Monthly Weather Review. 145(3). 1107–1125. 64 indexed citations

11.

DeMaria, Mark, Ralph Ferraro, John L. Beven, et al.. (2015). Satellite tools to monitor and predict Hurricane Sandy (2012): Current and emerging products. Atmospheric Research. 166. 165–181. 5 indexed citations

12.

Daniels, Jaime, et al.. (2012). Atmospheric Motion Vectors Derived via a New Nested Tracking Algorithm Developed for the GOES-R Advanced Baseline Imager (ABI). AGU Fall Meeting Abstracts. 2012. 2 indexed citations

13.

Daniels, Jaime, et al.. (2009). GOES-R Algorithm Working Group (AWG). Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7456. 74560P–74560P.

14.

Li, Zhenglong, Jun Li, W. Paul Menzel, et al.. (2008). GOES sounding improvement and applications to severe storm nowcasting. Geophysical Research Letters. 35(3). 32 indexed citations

15.

Prins, E. M., Christopher S. Velden, Jeffrey D. Hawkins, et al.. (2006). 13th AMS Conference on Satellite Meteorology and Oceanography. Bulletin of the American Meteorological Society. 87(5). 633–638.

16.

Velden, Christopher S., Jaime Daniels, David Santek, et al.. (2005). Recent Innovations in Deriving Tropospheric Winds from Meteorological Satellites. Bulletin of the American Meteorological Society. 86(2). 205–224. 184 indexed citations

17.

Daniels, Jaime. (2004). Status of the NOAA/NESDIS Operational Satellite Wind Product System: Recent Improvements, New Products, Product Quality, and Future Plans. 4 indexed citations

18.

Hillger, Donald W., Timothy J. Schmit, & Jaime Daniels. (2003). Imager and sounder radiance and product validations for the GOES-12 science test. 10 indexed citations

19.

Ellrod, Gary P., et al.. (1998). An Assessment ofGOES-8Imager Data Quality. Bulletin of the American Meteorological Society. 79(11). 2509–2526. 24 indexed citations

20.

Nieman, Steven J., W. Paul Menzel, Christopher M. Hayden, et al.. (1997). Fully Automated Cloud-Drift Winds in NESDIS Operations. Bulletin of the American Meteorological Society. 78(6). 1121–1133. 139 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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