Mark Iredell

39.6k total citations · 1 hit paper
18 papers, 3.3k citations indexed

About

Mark Iredell is a scholar working on Atmospheric Science, Global and Planetary Change and Astronomy and Astrophysics. According to data from OpenAlex, Mark Iredell has authored 18 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Atmospheric Science, 7 papers in Global and Planetary Change and 6 papers in Astronomy and Astrophysics. Recurrent topics in Mark Iredell's work include Meteorological Phenomena and Simulations (7 papers), Ionosphere and magnetosphere dynamics (6 papers) and Solar and Space Plasma Dynamics (5 papers). Mark Iredell is often cited by papers focused on Meteorological Phenomena and Simulations (7 papers), Ionosphere and magnetosphere dynamics (6 papers) and Solar and Space Plasma Dynamics (5 papers). Mark Iredell collaborates with scholars based in United States. Mark Iredell's co-authors include Shrinivas Moorthi, Jesse Meng, David Behringer, Malaquías Peña, Sudhir Nadiga, Mingyue Chen, Jiande Wang, Qin Zhang, Michael Ek and Rongqian Yang and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Journal of Climate and Geophysical Research Letters.

In The Last Decade

Mark Iredell

17 papers receiving 3.2k citations

Hit Papers

The NCEP Climate Forecast System Version 2 2013 2026 2017 2021 2013 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Iredell United States 11 2.4k 2.2k 976 412 254 18 3.3k
Shrinivas Moorthi United States 19 4.5k 1.8× 4.5k 2.0× 1.7k 1.8× 214 0.5× 353 1.4× 38 5.5k
T. J. Hoar United States 22 1.6k 0.7× 1.8k 0.8× 765 0.8× 202 0.5× 298 1.2× 52 2.5k
Paul Berrisford United Kingdom 23 3.4k 1.4× 3.5k 1.6× 1.0k 1.1× 134 0.3× 190 0.7× 41 4.1k
Véronique Ducrocq France 32 3.1k 1.3× 3.2k 1.4× 615 0.6× 284 0.7× 464 1.8× 109 4.1k
Robert G. Fovell United States 33 2.6k 1.1× 2.3k 1.0× 468 0.5× 238 0.6× 425 1.7× 75 3.2k
Eric J. Fetzer United States 38 3.9k 1.6× 3.9k 1.7× 568 0.6× 330 0.8× 163 0.6× 152 4.6k
Kiyotoshi Takahashi Japan 10 5.1k 2.1× 5.4k 2.4× 1.8k 1.9× 182 0.4× 226 0.9× 14 6.2k
Michael J. Reeder Australia 33 2.9k 1.2× 2.6k 1.2× 806 0.8× 555 1.3× 192 0.8× 135 3.5k
P. Kållberg United Kingdom 23 2.9k 1.2× 2.7k 1.2× 591 0.6× 133 0.3× 180 0.7× 33 3.6k
Arthur Y. Hou United States 30 4.6k 1.9× 3.6k 1.6× 629 0.6× 264 0.6× 791 3.1× 64 5.2k

Countries citing papers authored by Mark Iredell

Since Specialization
Citations

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

Fields of papers citing papers by Mark Iredell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Iredell

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

All Works

18 of 18 papers shown
1.
Lu, Cheng‐Hsuan, Arlindo da Silva, Jun Wang, et al.. (2016). The implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP. Geoscientific model development. 9(5). 1905–1919. 26 indexed citations
2.
Wang, Houjun, R. A. Akmaev, Tzu‐Wei Fang, et al.. (2014). First forecast of a sudden stratospheric warming with a coupled whole‐atmosphere/ionosphere model IDEA. Journal of Geophysical Research Space Physics. 119(3). 2079–2089. 45 indexed citations
3.
Saha, Suranjana, Shrinivas Moorthi, Xingren Wu, et al.. (2013). The NCEP Climate Forecast System Version 2. Journal of Climate. 27(6). 2185–2208. 2599 indexed citations breakdown →
4.
Lu, Cheng‐Hsuan, Arlindo da Silva, Mian Chin, et al.. (2013). The NEMS GFS aerosol component; NCEP's global aerosol forecast system. 6 indexed citations
5.
Wang, Houjun, et al.. (2012). Correction to “First simulations with a whole atmosphere data assimilation and forecast system: The January 2009 major sudden stratospheric warming”. Journal of Geophysical Research Atmospheres. 117(A3). 3 indexed citations
6.
Fuller‐Rowell, T. J., Houjun Wang, R. A. Akmaev, et al.. (2011). Forecasting the dynamic and electrodynamic response to the January 2009 sudden stratospheric warming. Geophysical Research Letters. 38(13). n/a–n/a. 84 indexed citations
7.
Wang, Houjun, T. J. Fuller‐Rowell, R. A. Akmaev, et al.. (2011). First simulations with a whole atmosphere data assimilation and forecast system: The January 2009 major sudden stratospheric warming. Journal of Geophysical Research Atmospheres. 116(A12). n/a–n/a. 80 indexed citations
8.
Lu, Cheng‐Hsuan, Haiyan Huang, Yanping Hou, et al.. (2010). Development of global aerosol forecasting system at NCEP. AGU Fall Meeting Abstracts. 2010. 1 indexed citations
9.
Akmaev, R. A., Fei Wu, T. J. Fuller‐Rowell, Houjun Wang, & Mark Iredell. (2010). Midnight density and temperature maxima, and thermospheric dynamics in Whole Atmosphere Model simulations. Journal of Geophysical Research Atmospheres. 115(A8). 49 indexed citations
10.
Fuller‐Rowell, T. J., R. A. Akmaev, Fei Wu, et al.. (2008). Impact of terrestrial weather on the upper atmosphere. Geophysical Research Letters. 35(9). 65 indexed citations
11.
Akmaev, R. A., T. J. Fuller‐Rowell, Fei Wu, et al.. (2008). Tidal variability in the lower thermosphere: Comparison of Whole Atmosphere Model (WAM) simulations with observations from TIMED. Geophysical Research Letters. 35(3). 82 indexed citations
12.
Dickinson, R. E., Stephen E. Zebiak, J. G. Anderson, et al.. (2002). How Can We Advance Our Weather and Climate Models as a Community?. Bulletin of the American Meteorological Society. 83(3). 431–434. 20 indexed citations
13.
Iredell, Mark, et al.. (1997). Global Data Assimilation and Forecast Experiments Using SSM/I Wind Speed Data Derived from a Neural Network Algorithm. Weather and Forecasting. 12(4). 859–865. 10 indexed citations
14.
Iredell, Mark, et al.. (1993). Dynamic coupling between the NMC global atmosphere and spectral wave models. 1 indexed citations
15.
Kanamitsu, Masao, Jordan C. Alpert, Kenneth A. Campana, et al.. (1991). Recent Changes Implemented into the Global Forecast System at NMC. Weather and Forecasting. 6(3). 425–435. 243 indexed citations
16.
Iredell, Mark. (1988). The Effect of Orographic Forcing on the Mean Flow of the Stratosphere.. 1 indexed citations
17.
Takacs, Lawrence L., et al.. (1981). On the effect of high latitude filtering in global grid point models. NASA Technical Reports Server (NASA). 83(2). 96–104. 1 indexed citations
18.
Baker, W. E., et al.. (1981). Objective analysis of observational data from the FGGE observing systems. 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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