J. L. McCreight

1.4k total citations
32 papers, 884 citations indexed

About

J. L. McCreight is a scholar working on Atmospheric Science, Water Science and Technology and Global and Planetary Change. According to data from OpenAlex, J. L. McCreight has authored 32 papers receiving a total of 884 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Atmospheric Science, 16 papers in Water Science and Technology and 14 papers in Global and Planetary Change. Recurrent topics in J. L. McCreight's work include Hydrology and Watershed Management Studies (14 papers), Cryospheric studies and observations (11 papers) and Climate change and permafrost (9 papers). J. L. McCreight is often cited by papers focused on Hydrology and Watershed Management Studies (14 papers), Cryospheric studies and observations (11 papers) and Climate change and permafrost (9 papers). J. L. McCreight collaborates with scholars based in United States, Germany and South Korea. J. L. McCreight's co-authors include Tingjun Zhang, Oliver W. Frauenfeld, Eric E. Small, Mark C. Serreze, Kristine M. Larson, A. Etringer, Roger G. Barry, D. Gilichinsky, Daqing Yang and Feng Ling and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Water Resources Research and Journal of Hydrology.

In The Last Decade

J. L. McCreight

31 papers receiving 858 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. L. McCreight United States 13 722 224 174 163 63 32 884
Matthias Bernhardt Austria 17 752 1.0× 407 1.8× 292 1.7× 135 0.8× 112 1.8× 33 969
Mohammed Ombadi United States 11 670 0.9× 654 2.9× 266 1.5× 215 1.3× 33 0.5× 20 1.0k
Eiichi NAKAKITA Japan 15 530 0.7× 559 2.5× 227 1.3× 161 1.0× 41 0.7× 135 799
Don Cline United States 11 725 1.0× 206 0.9× 244 1.4× 138 0.8× 118 1.9× 29 800
Wenjun Yu China 13 255 0.4× 355 1.6× 304 1.7× 154 0.9× 19 0.3× 33 621
Prabin Rokaya Canada 16 366 0.5× 142 0.6× 181 1.0× 91 0.6× 22 0.3× 26 557
Bernard Bilodeau Canada 16 804 1.1× 576 2.6× 140 0.8× 278 1.7× 32 0.5× 28 922
Thanh‐Nhan‐Duc Tran United States 16 240 0.3× 477 2.1× 456 2.6× 189 1.2× 22 0.3× 23 792
Craig D. Smith Canada 14 884 1.2× 546 2.4× 208 1.2× 117 0.7× 61 1.0× 27 1.0k
Naira Chaouch United States 11 433 0.6× 384 1.7× 95 0.5× 167 1.0× 21 0.3× 19 592

Countries citing papers authored by J. L. McCreight

Since Specialization
Citations

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

Fields of papers citing papers by J. L. McCreight

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. L. McCreight

This figure shows the co-authorship network connecting the top 25 collaborators of J. L. McCreight. A scholar is included among the top collaborators of J. L. McCreight 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. L. McCreight. J. L. McCreight 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.
Gharamti, Mohamad El, A. Rafieeinasab, & J. L. McCreight. (2024). Leveraging a novel hybrid ensemble and optimal interpolation approach for enhanced streamflow and flood prediction. Hydrology and earth system sciences. 28(14). 3133–3159. 2 indexed citations
2.
McCreight, J. L., et al.. (2024). Bayesian reduced-order deep learning surrogate model for dynamic systems described by partial differential equations. Computer Methods in Applied Mechanics and Engineering. 429. 117147–117147. 5 indexed citations
3.
Livneh, Ben, et al.. (2022). Evaluation of a new observationally based channel parameterization for the National Water Model. Hydrology and earth system sciences. 26(23). 6121–6136. 12 indexed citations
4.
5.
Towler, Erin & J. L. McCreight. (2021). A wavelet-based approach to streamflow event identification and modeled timing error evaluation. Hydrology and earth system sciences. 25(5). 2599–2615. 10 indexed citations
6.
Gharamti, Mohamad El, et al.. (2021). Ensemble streamflow data assimilation using WRF-Hydro and DART: novel localization and inflation techniques applied to Hurricane Florence flooding. Hydrology and earth system sciences. 25(9). 5315–5336. 19 indexed citations
7.
McAllister, Mary Louise, David Gochis, Michael Barlage, et al.. (2020). The Community WRF-Hydro Modeling System Version 5.2 Updates & New Community Focused Testbed. AGU Fall Meeting Abstracts. 2020. 1 indexed citations
8.
Cosgrove, B., A. L. Dugger, K. M. Sampson, et al.. (2018). Multi-variate evaluation of the NOAA National Water Model. AGU Fall Meeting Abstracts. 2018. 2 indexed citations
9.
McAllister, Mary Louise, David Gochis, Michael Barlage, et al.. (2018). The Community WRF-Hydro Modeling System Version 5 melding with the National Water Model: Enhancements and Education. AGU Fall Meeting Abstracts. 2018. 1 indexed citations
10.
Gochis, David, Michael Barlage, A. L. Dugger, et al.. (2018). WRF-Hydro Model Source Code Version 5. UCAR/NCAR. 16 indexed citations
11.
Dugger, A. L., A. Rafieeinasab, David Gochis, et al.. (2016). Evaluating CONUS-Scale Runoff Simulation across the National Water Model WRF-Hydro Implementation to Disentangle Regional Controls on Streamflow Generation and Model Error Contribution. AGU Fall Meeting Abstracts. 2016. 1 indexed citations
12.
Rafieeinasab, A., et al.. (2016). Evaluation of streamflow forecast for the National Water Model of U.S. National Weather Service. AGUFM. 2016. 1 indexed citations
13.
Gochis, David, Wei Yu, K. M. Sampson, et al.. (2015). Multi-scale model analysis and hindcast of the 2013 Colorado Flood. EGUGA. 7531. 1 indexed citations
14.
Gochis, David, Wei Yu, A. L. Dugger, et al.. (2014). Recent Developments and Applications of the WRF-Hydro Modeling System for Continental Scale Water Cycle Predictions. AGUFM. 2014. 1 indexed citations
15.
McCreight, J. L. & Eric E. Small. (2014). Modeling bulk density and snow water equivalent using daily snow depth observations. ˜The œcryosphere. 8(2). 521–536. 52 indexed citations
16.
McCreight, J. L., Eric E. Small, & Kristine M. Larson. (2014). Snow depth, density, and SWE estimates derived from GPS reflection data: Validation in the western U. S.. Water Resources Research. 50(8). 6892–6909. 83 indexed citations
17.
Larson, Kristine M., et al.. (2013). PBO H2O: Plate Boundary Observatory Studies of the Water Cycle. AGUFM. 2013. 1 indexed citations
18.
McCreight, J. L., A. G. Slater, Hans‐Peter Marshall, & Balaji Rajagopalan. (2012). Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size, random sampling, predictor quality, and validation procedures. Hydrological Processes. 28(3). 933–957. 17 indexed citations
19.
Strœve, Julienne, Allan Frei, J. L. McCreight, & Debjani Ghatak. (2008). Arctic sea-ice variability revisited. Annals of Glaciology. 48. 71–81. 30 indexed citations
20.
Frauenfeld, Oliver W., et al.. (2005). Response of Changes in Active Layer and Permafrost Conditions to Hydrological Cycle in the Russian Arctic. AGU Fall Meeting Abstracts. 2005. 5 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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