J. Miller

1.0k total citations · 1 hit paper
9 papers, 730 citations indexed

About

J. Miller is a scholar working on Atmospheric Science, Astronomy and Astrophysics and Molecular Biology. According to data from OpenAlex, J. Miller has authored 9 papers receiving a total of 730 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Atmospheric Science, 2 papers in Astronomy and Astrophysics and 1 paper in Molecular Biology. Recurrent topics in J. Miller's work include Cryospheric studies and observations (6 papers), Climate change and permafrost (5 papers) and Arctic and Antarctic ice dynamics (5 papers). J. Miller is often cited by papers focused on Cryospheric studies and observations (6 papers), Climate change and permafrost (5 papers) and Arctic and Antarctic ice dynamics (5 papers). J. Miller collaborates with scholars based in United States, United Kingdom and Türkiye. J. Miller's co-authors include T. Markus, Julienne Strœve, A. P. Barrett, Linette Boisvert, N. T. Kurtz, Marco Tedesco, J. G. Sonntag, D. J. Cavalieri, W. B. Krabill and Robert D. Nevels and has published in prestigious journals such as Remote Sensing of Environment, Geophysical Research Letters and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

J. Miller

9 papers receiving 704 citations

Hit Papers

Changes in Arctic melt season and implications for sea ic... 2014 2026 2018 2022 2014 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
J. Miller United States 7 649 162 95 89 88 9 730
J. Scott Stewart United States 12 778 1.2× 229 1.4× 183 1.9× 97 1.1× 83 0.9× 21 891
Melinda Webster United States 21 1.3k 2.0× 295 1.8× 102 1.1× 108 1.2× 54 0.6× 54 1.3k
Polona Itkin Norway 17 814 1.3× 129 0.8× 107 1.1× 122 1.4× 53 0.6× 41 891
Frédéric Laliberté Canada 15 549 0.8× 340 2.1× 184 1.9× 37 0.4× 56 0.6× 23 676
Tom Carrières Canada 16 695 1.1× 166 1.0× 124 1.3× 69 0.8× 22 0.3× 37 733
Byongjun Hwang United Kingdom 16 643 1.0× 98 0.6× 183 1.9× 115 1.3× 40 0.5× 52 720
Richard A Allard United States 15 491 0.8× 203 1.3× 271 2.9× 36 0.4× 30 0.3× 56 620
David Munday United Kingdom 16 466 0.7× 439 2.7× 561 5.9× 59 0.7× 29 0.3× 42 783
Д. В. Моисеев Russia 10 142 0.2× 119 0.7× 196 2.1× 51 0.6× 83 0.9× 38 370
Ingrid H. Onarheim Norway 8 807 1.2× 391 2.4× 325 3.4× 171 1.9× 91 1.0× 8 930

Countries citing papers authored by J. Miller

Since Specialization
Citations

This map shows the geographic impact of J. Miller'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 J. Miller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Miller more than expected).

Fields of papers citing papers by J. Miller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. Miller. 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 J. Miller. The network helps show where J. Miller may publish in the future.

Co-authorship network of co-authors of J. Miller

This figure shows the co-authorship network connecting the top 25 collaborators of J. Miller. A scholar is included among the top collaborators of J. Miller 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 J. Miller. J. Miller is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Farrell, W. M., D. Lauben, J. Miller, et al.. (2022). Quasi‐Periodic Whistler Mode Emission in the Plasmasphere as Observed by the DSX Spacecraft. Journal of Geophysical Research Space Physics. 127(8). 2 indexed citations
2.
Petty, Alek, David Schröder, Julienne Strœve, et al.. (2017). Skillful spring forecasts of September Arctic sea ice extent using passive microwave sea ice observations. Earth s Future. 5(2). 254–263. 40 indexed citations
3.
Strœve, Julienne, T. Markus, Linette Boisvert, J. Miller, & A. P. Barrett. (2014). Changes in Arctic melt season and implications for sea ice loss. Geophysical Research Letters. 41(4). 1216–1225. 562 indexed citations breakdown →
4.
Cavalieri, Donald J., T. Markus, Alvaro Ivanoff, et al.. (2012). A Comparison of Snow Depth on Sea Ice Retrievals Using Airborne Altimeters and an AMSR-E Simulator. IEEE Transactions on Geoscience and Remote Sensing. 50(8). 3027–3040. 29 indexed citations
5.
Kurtz, N. T., T. Markus, D. J. Cavalieri, et al.. (2008). Comparison of ICESat Data With Airborne Laser Altimeter Measurements Over Arctic Sea Ice. IEEE Transactions on Geoscience and Remote Sensing. 46(7). 1913–1924. 58 indexed citations
6.
Tedesco, Marco & J. Miller. (2007). Observations and statistical analysis of combined active–passive microwave space-borne data and snow depth at large spatial scales. Remote Sensing of Environment. 111(2-3). 382–397. 18 indexed citations
7.
Tedesco, Marco & J. Miller. (2007). Northern Hemisphere Snow-Covered Area Mapping: Optical Versus Active and Passive Microwave Data. IEEE Geoscience and Remote Sensing Letters. 4(2). 221–225. 7 indexed citations
8.
Nevels, Robert D. & J. Miller. (2001). A simple equation for analysis of nonuniform transmission lines. IEEE Transactions on Microwave Theory and Techniques. 49(4). 721–724. 13 indexed citations
9.
Miller, J., et al.. (1985). Variable focal length radiometer for particle sizing. 115–122. 1 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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