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.
Resolution Requirements for the Simulation of Deep Moist Convection
2003674 citationsGeorge H. Bryan, J. Michael Fritsch et al.Monthly Weather Reviewprofile →
A Benchmark Simulation for Moist Nonhydrostatic Numerical Models
2002556 citationsGeorge H. Bryan, J. Michael FritschMonthly Weather Reviewprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by George H. Bryan
Since
Specialization
Citations
This map shows the geographic impact of George H. Bryan'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 George H. Bryan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George H. Bryan more than expected).
This network shows the impact of papers produced by George H. Bryan. 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 George H. Bryan. The network helps show where George H. Bryan may publish in the future.
Co-authorship network of co-authors of George H. Bryan
This figure shows the co-authorship network connecting the top 25 collaborators of George H. Bryan.
A scholar is included among the top collaborators of George H. Bryan 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 George H. Bryan. George H. Bryan is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Stern, Daniel P., George H. Bryan, & Sim D. Aberson. (2015). Extreme Updrafts and Wind Speeds Measured by Dropsondes in Tropical Cyclones. 2015 AGU Fall Meeting. 2015.3 indexed citations
8.
Bryan, George H.. (2014). A framework for studying the inner core of tropical cyclones using large eddy simulation.3 indexed citations
Stern, Daniel P. & George H. Bryan. (2013). The Structure and Dynamics of Coherent Vortices in the Eyewall Boundary Layer of Tropical Cyclones. EGU General Assembly Conference Abstracts. 2014. 15852.2 indexed citations
Bryan, George H.. (2010). The effects of turbulence on hurricane intensity.12 indexed citations
13.
Bryan, George H.. (2008). Evaluation of the theoretical speed and depth of gravity currents using three-dimensional numerical simulations.1 indexed citations
Bryan, George H.. (2006). Mechanisms for the production of severe surface winds in a simulation of an elevated convective system.9 indexed citations
16.
Bryan, George H.. (2006). The relative importance of lower-level and upper-level shear on the intensity of squall lines.1 indexed citations
17.
Bryan, George H.. (2005). Statistical convergence in simulated moist absolutely unstable layers.9 indexed citations
18.
Bryan, George H.. (2004). Cellular structures in simulated squall lines with moist absolutely unstable layers. 11th Conference on Aviation, Range, and Aerospace and the 22nd Conference on Severe Local Storms.1 indexed citations
Bryan, George H.. (2003). An investigation of the convective region of numerically simulated squall lines. PhDT.21 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.