T. E. LaRow

839 total citations
21 papers, 503 citations indexed

About

T. E. LaRow is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, T. E. LaRow has authored 21 papers receiving a total of 503 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Atmospheric Science, 18 papers in Global and Planetary Change and 5 papers in Oceanography. Recurrent topics in T. E. LaRow's work include Climate variability and models (18 papers), Tropical and Extratropical Cyclones Research (10 papers) and Meteorological Phenomena and Simulations (10 papers). T. E. LaRow is often cited by papers focused on Climate variability and models (18 papers), Tropical and Extratropical Cyclones Research (10 papers) and Meteorological Phenomena and Simulations (10 papers). T. E. LaRow collaborates with scholars based in United States, Australia and Italy. T. E. LaRow's co-authors include S. Cocke, D. W. Shin, James J. O’Brien, T. N. Krishnamurti, Eric P. Chassignet, Young‐Kwon Lim, J. T. Schoof, James B. Elsner, Sarah Strazzo and John G. Bellow and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Journal of Climate and Geophysical Research Letters.

In The Last Decade

T. E. LaRow

21 papers receiving 484 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
T. E. LaRow United States 13 447 408 108 76 35 21 503
P. Goswami India 11 261 0.6× 238 0.6× 42 0.4× 40 0.5× 54 1.5× 32 357
Emilia Paula Diaconescu Canada 10 517 1.2× 463 1.1× 39 0.4× 62 0.8× 24 0.7× 13 575
Vinay Kumar United States 13 656 1.5× 594 1.5× 145 1.3× 35 0.5× 28 0.8× 57 729
Venkatraman Prasanna South Korea 11 291 0.7× 215 0.5× 52 0.5× 69 0.9× 48 1.4× 23 369
C. H. Matarira Zimbabwe 8 282 0.6× 155 0.4× 64 0.6× 73 1.0× 16 0.5× 14 335
Alexis Donald Australia 4 449 1.0× 382 0.9× 144 1.3× 34 0.4× 12 0.3× 5 488
J. Brent Roberts United States 12 373 0.8× 279 0.7× 182 1.7× 41 0.5× 39 1.1× 24 456
J. Jacobeit Germany 7 259 0.6× 171 0.4× 33 0.3× 41 0.5× 20 0.6× 12 327
André Kamga France 7 366 0.8× 280 0.7× 22 0.2× 102 1.3× 16 0.5× 12 418
Uffe Andersen Denmark 6 249 0.6× 237 0.6× 41 0.4× 62 0.8× 23 0.7× 8 359

Countries citing papers authored by T. E. LaRow

Since Specialization
Citations

This map shows the geographic impact of T. E. LaRow'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. E. LaRow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. E. LaRow more than expected).

Fields of papers citing papers by T. E. LaRow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T. E. LaRow. 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. E. LaRow. The network helps show where T. E. LaRow may publish in the future.

Co-authorship network of co-authors of T. E. LaRow

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

All Works

20 of 20 papers shown
1.
Rose, L. Shea & T. E. LaRow. (2016). The Relationship Between Climate Oscillations and Regional Extremes. AGUFM. 2016. 1 indexed citations
2.
Strazzo, Sarah, James B. Elsner, T. E. LaRow, et al.. (2016). The influence of model resolution on the simulated sensitivity of North Atlantic tropical cyclone maximum intensity to sea surface temperature. Journal of Advances in Modeling Earth Systems. 8(3). 1037–1054. 14 indexed citations
3.
Strazzo, Sarah, James B. Elsner, & T. E. LaRow. (2015). Quantifying the sensitivity of maximum, limiting, and potential tropical cyclone intensity to SST: Observations versus the FSU/COAPS global climate model. Journal of Advances in Modeling Earth Systems. 7(2). 586–599. 11 indexed citations
4.
Daloz, Anne Sophie, Suzana J. Camargo, James P. Kossin, et al.. (2014). Cluster Analysis of Downscaled and Explicitly Simulated North Atlantic Tropical Cyclone Tracks. Journal of Climate. 28(4). 1333–1361. 48 indexed citations
5.
LaRow, T. E.. (2010). Seasonal Atlantic tropical cyclone hindcasting/forecasting using two sea surface temperature datasets. 1 indexed citations
6.
Shin, D. W., Guillermo A. Baigorria, S. Cocke, et al.. (2009). Assessing Maize and Peanut Yield Simulations with Various Seasonal Climate Data in the Southeastern United States. Journal of Applied Meteorology and Climatology. 49(4). 592–603. 31 indexed citations
7.
Schoof, J. T., D. W. Shin, S. Cocke, et al.. (2008). Dynamically and statistically downscaled seasonal temperature and precipitation hindcast ensembles for the southeastern USA. International Journal of Climatology. 29(2). 243–257. 29 indexed citations
8.
LaRow, T. E., et al.. (2008). Atlantic Basin Seasonal Hurricane Simulations. Journal of Climate. 21(13). 3191–3206. 64 indexed citations
9.
Shin, D. W., S. Cocke, & T. E. LaRow. (2007). Diurnal cycle of precipitation in a climate model. Journal of Geophysical Research Atmospheres. 112(D13). 18 indexed citations
10.
Lim, Young‐Kwon, D. W. Shin, S. Cocke, et al.. (2007). Dynamically and statistically downscaled seasonal simulations of maximum surface air temperature over the southeastern United States. Journal of Geophysical Research Atmospheres. 112(D24). 28 indexed citations
11.
Cocke, S., T. E. LaRow, & D. W. Shin. (2007). Seasonal rainfall predictions over the southeast United States using the Florida State University nested regional spectral model. Journal of Geophysical Research Atmospheres. 112(D4). 21 indexed citations
12.
Shin, D. W., John G. Bellow, T. E. LaRow, S. Cocke, & James J. O’Brien. (2006). The Role of an Advanced Land Model in Seasonal Dynamical Downscaling for Crop Model Application. Journal of Applied Meteorology and Climatology. 45(5). 686–701. 26 indexed citations
13.
14.
LaRow, T. E., S. Cocke, & D. W. Shin. (2005). Multiconvective Parameterizations as a Multimodel Proxy for Seasonal Climate Studies. Journal of Climate. 18(15). 2963–2978. 8 indexed citations
15.
Shin, D. W., S. Cocke, T. E. LaRow, & James J. O’Brien. (2005). Seasonal Surface Air Temperature and Precipitation in the FSU Climate Model Coupled to the CLM2. Journal of Climate. 18(16). 3217–3228. 15 indexed citations
16.
Shin, D. W., S. Cocke, & T. E. LaRow. (2003). Ensemble Configurations for Typhoon Precipitation Forecasts. Journal of the Meteorological Society of Japan Ser II. 81(4). 679–696. 5 indexed citations
17.
Shin, D. W., T. E. LaRow, & S. Cocke. (2003). Convective scheme and resolution impacts on seasonal precipitation forecasts. Geophysical Research Letters. 30(20). 9 indexed citations
18.
Roads, John O., S. Cocke, Leonard M. Druyan, et al.. (2003). International Research Institute/Applied Research Centers (IRI/ARCs) regional model intercomparison over South America. Journal of Geophysical Research Atmospheres. 108(D14). 40 indexed citations
19.
Cocke, S. & T. E. LaRow. (2000). Seasonal Predictions Using a Regional Spectral Model Embedded within a Coupled Ocean–Atmosphere Model. Monthly Weather Review. 128(3). 689–708. 87 indexed citations
20.
LaRow, T. E. & T. N. Krishnamurti. (1998). Initial conditions and ENSO prediction using a coupled ocean-atmosphere model. Tellus A Dynamic Meteorology and Oceanography. 50(1). 76–94. 9 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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