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.
Changes in Arctic melt season and implications for sea ice loss
2014562 citationsJulienne Strœve, T. Markus et al.Geophysical Research Lettersprofile →
Recent changes in Arctic sea ice melt onset, freezeup, and melt season length
2009529 citationsT. Markus, Julienne Strœve et al.Journal of Geophysical Research Atmospheresprofile →
Pervasive ice sheet mass loss reflects competing ocean and atmosphere processes
2020343 citationsKelly M. Brunt, B. M. Csathó et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of T. Markus'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 T. Markus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Markus more than expected).
This network shows the impact of papers produced by T. Markus. 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 T. Markus. The network helps show where T. Markus may publish in the future.
Co-authorship network of co-authors of T. Markus
This figure shows the co-authorship network connecting the top 25 collaborators of T. Markus.
A scholar is included among the top collaborators of T. Markus 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 T. Markus. T. Markus is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Comiso, J. C., Walter N. Meier, & T. Markus. (2018). Annomalies and Trends in the Sea Ice Cover from 40 years of Passive Microwave Data. AGU Fall Meeting Abstracts. 2018.2 indexed citations
Kurtz, N. T., et al.. (2017). Estimating Surface Elevation Bias Due to Subsurface Scattered Photons from Visible Wavelength Laser Altimeters. AGUFM. 2017.3 indexed citations
Neumann, T., T. Markus, Kelly M. Brunt, et al.. (2012). Airborne ICESat-2 simulator (MABEL) results from Greenland. AGUFM. 2012.1 indexed citations
13.
Wolken, G. J., Martin Sharp, Chris Derksen, et al.. (2011). Integrated Pan-Arctic Melt Onset Detection From Satellite Active/Passive Microwave Measurements, 2000-2009. AGU Fall Meeting Abstracts. 2011.3 indexed citations
14.
Brunt, Kelly M., T. Neumann, T. Markus, et al.. (2011). MABEL photon-counting altimetry data for ICESat-2 simulations. AGU Fall Meeting Abstracts. 2011.2 indexed citations
15.
Markus, T., Julienne Strœve, & Jeffrey Miller. (2009). Recent changes in Arctic sea ice melt onset, freezeup, and melt season length. Journal of Geophysical Research Atmospheres. 114(C12).529 indexed citations breakdown →
Massom, Robert A., A. P. Worby, Victoria I. Lytle, et al.. (2007). Early Springtime Snowcover on East Antarctic Sea Ice, ARISE 2003: Variability and Satellite Validation.. AGU Fall Meeting Abstracts. 2007.1 indexed citations
18.
Cavalieri, D. J., T. Markus, Albin J. Gasiewski, et al.. (2004). EOS Aqua AMSR-E Arctic Sea Ice Validation Program. UCL Discovery (University College London).1 indexed citations
19.
Nghiem, S. V., David G. Barber, G. Robert Brakenridge, et al.. (2003). Surface Water Applications of Satellite Scatterometry. AGU Fall Meeting Abstracts. 2003.1 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.