David L. Randel

1.1k total citations
19 papers, 798 citations indexed

About

David L. Randel is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, David L. Randel has authored 19 papers receiving a total of 798 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Atmospheric Science, 6 papers in Global and Planetary Change and 4 papers in Environmental Engineering. Recurrent topics in David L. Randel's work include Meteorological Phenomena and Simulations (14 papers), Precipitation Measurement and Analysis (11 papers) and Soil Moisture and Remote Sensing (4 papers). David L. Randel is often cited by papers focused on Meteorological Phenomena and Simulations (14 papers), Precipitation Measurement and Analysis (11 papers) and Soil Moisture and Remote Sensing (4 papers). David L. Randel collaborates with scholars based in United States, China and Japan. David L. Randel's co-authors include Christian D. Kummerow, Thomas H. Vonder Haar, Thomas J. Greenwald, Cynthia L. Combs, Graeme L. Stephens, Veljko Petković, Mark S. Kulie, Naiyu Wang, S. Joseph Munchak and Ralph Ferraro and has published in prestigious journals such as Journal of Climate, Geophysical Research Letters and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

David L. Randel

17 papers receiving 759 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David L. Randel United States 8 732 466 163 85 31 19 798
Philippe Chambon France 14 909 1.2× 748 1.6× 98 0.6× 68 0.8× 26 0.8× 33 958
Masahiro Kazumori Japan 13 820 1.1× 668 1.4× 84 0.5× 101 1.2× 36 1.2× 24 871
Soyoung Ha United States 12 668 0.9× 600 1.3× 118 0.7× 77 0.9× 41 1.3× 23 729
Josée Morneau Canada 8 530 0.7× 502 1.1× 105 0.6× 53 0.6× 16 0.5× 8 579
Leo Pio D’Adderio Italy 18 536 0.7× 299 0.6× 164 1.0× 54 0.6× 20 0.6× 38 605
Cristina Lupu United Kingdom 8 580 0.8× 509 1.1× 58 0.4× 67 0.8× 47 1.5× 12 642
James A. Jung United States 14 660 0.9× 580 1.2× 54 0.3× 88 1.0× 59 1.9× 31 705
Christoph Schraff Germany 9 616 0.8× 566 1.2× 78 0.5× 54 0.6× 30 1.0× 10 667
Hélène Brogniez France 16 652 0.9× 612 1.3× 28 0.2× 62 0.7× 28 0.9× 40 701
B. Katz United States 4 527 0.7× 490 1.1× 44 0.3× 142 1.7× 16 0.5× 6 588

Countries citing papers authored by David L. Randel

Since Specialization
Citations

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

Fields of papers citing papers by David L. Randel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David L. Randel

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

All Works

19 of 19 papers shown
1.
Petković, Veljko, et al.. (2023). Can We Estimate the Uncertainty Level of Satellite Long-Term Precipitation Records?. Journal of Applied Meteorology and Climatology. 62(8). 1069–1082. 4 indexed citations
2.
You, Yalei, Naiyu Wang, Takuji Kubota, et al.. (2020). Comparison of TRMM Microwave Imager Rainfall Datasets from NASA and JAXA. Journal of Hydrometeorology. 21(3). 377–397. 6 indexed citations
3.
Stocker, Erich Franz, et al.. (2019). A Comparison of the GPROF Algorithm Results in the 2A-CLIM and 2A Data Products. The EGU General Assembly. 7079.
4.
Kummerow, Christian D., et al.. (2019). Tropical Cyclone Rain Retrievals from FY-3B MWRI Brightness Temperatures Using the Goddard Profiling Algorithm (GPROF). Journal of Atmospheric and Oceanic Technology. 36(5). 849–864. 2 indexed citations
5.
Ringerud, Sarah, Mark S. Kulie, David L. Randel, Gail Skofronick‐Jackson, & Christian D. Kummerow. (2019). Effects of Ice Particle Representation on Passive Microwave Precipitation Retrieval in a Bayesian Scheme. IEEE Transactions on Geoscience and Remote Sensing. 57(6). 3619–3632. 15 indexed citations
6.
Petković, Veljko, Christian D. Kummerow, David L. Randel, Jeffrey R. Pierce, & John K. Kodros. (2017). Improving the Quality of Heavy Precipitation Estimates from Satellite Passive Microwave Rainfall Retrievals. Journal of Hydrometeorology. 19(1). 69–85. 16 indexed citations
7.
Brown, P., Christian D. Kummerow, & David L. Randel. (2016). Hurricane GPROF: An Optimized Ocean Microwave Rainfall Retrieval for Tropical Cyclones. Journal of Atmospheric and Oceanic Technology. 33(7). 1539–1556. 11 indexed citations
8.
Kummerow, Christian D., David L. Randel, Mark S. Kulie, et al.. (2015). The Evolution of the Goddard Profiling Algorithm to a Fully Parametric Scheme. Journal of Atmospheric and Oceanic Technology. 32(12). 2265–2280. 263 indexed citations
9.
Kummerow, Christian D., et al.. (2010). An Observationally Generated A Priori Database for Microwave Rainfall Retrievals. Journal of Atmospheric and Oceanic Technology. 28(2). 113–130. 134 indexed citations
10.
Randel, David L.. (2007). Space-time variations in the earth radiation budget. Digital Collections of Colorado (Colorado State University).
11.
Haar, Thomas H. Vonder, Richard Engelen, J. M. Forsythe, et al.. (2001). Continuation of the NVAP Global Water Vapor Data Sets for Pathfinder Science Analysis. NASA Technical Reports Server (NASA). 7 indexed citations
12.
Greenwald, Thomas J., Cynthia L. Combs, Andrew S. Jones, David L. Randel, & Thomas H. Vonder Haar. (1999). Error estimates of spaceborne passive microwave retrievals of cloud liquid water over land. IEEE Transactions on Geoscience and Remote Sensing. 37(2). 796–804. 3 indexed citations
13.
Combs, Cynthia L., Thomas J. Greenwald, Andrew S. Jones, David L. Randel, & Thomas H. Vonder Haar. (1998). Satellite detection of cloud liquid water over land using polarization differences at 85.5 GHz. Geophysical Research Letters. 25(1). 75–78. 4 indexed citations
14.
Greenwald, Thomas J., Cynthia L. Combs, Andrew S. Jones, David L. Randel, & Thomas H. Vonder Haar. (1997). Further Developments in Estimating Cloud Liquid Water over Land Using Microwave and Infrared Satellite Measurements. Journal of Applied Meteorology. 36(4). 389–405. 31 indexed citations
15.
Randel, David L., et al.. (1996). A New Global Water Vapor Dataset. Bulletin of the American Meteorological Society. 77(6). 1233–1246. 287 indexed citations
16.
Randel, David L. & Thomas H. Vonder Haar. (1990). On the Interannual Variation of the Earth Radiation Balance. Journal of Climate. 3(10). 1168–1173. 8 indexed citations
17.
Haar, Thomas H. Vonder, et al.. (1987). The Prototype Digital Weather Laboratory at Colorado State University. Bulletin of the American Meteorological Society. 68(3). 230–236. 1 indexed citations
18.
Randel, David L., et al.. (1984). Analysis of Nimbus Earth Radiation Budget measurements for climate study. NASA Technical Reports Server (NASA). 45(3). 200–5. 2 indexed citations
19.
Martin, Donald C., et al.. (1964). PROLONGED FUNCTIONAL SURVIVAL OF DOG RENAL GRAFTS WITH LOCAL RADIATION.. PubMed. 15. 156–8. 4 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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