R. Meneghini

7.3k total citations · 2 hit papers
148 papers, 5.4k citations indexed

About

R. Meneghini is a scholar working on Atmospheric Science, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, R. Meneghini has authored 148 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 137 papers in Atmospheric Science, 83 papers in Environmental Engineering and 28 papers in Global and Planetary Change. Recurrent topics in R. Meneghini's work include Precipitation Measurement and Analysis (134 papers), Meteorological Phenomena and Simulations (99 papers) and Soil Moisture and Remote Sensing (82 papers). R. Meneghini is often cited by papers focused on Precipitation Measurement and Analysis (134 papers), Meteorological Phenomena and Simulations (99 papers) and Soil Moisture and Remote Sensing (82 papers). R. Meneghini collaborates with scholars based in United States, Japan and Italy. R. Meneghini's co-authors include Toshio Iguchi, Toshiaki Kozu, Liang Liao, Jun Awaka, Ken‐ichi Okamoto, John Kwiatkowski, Jeffrey A. Jones, William S. Olson, D. M. Levine and David Atlas and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Remote Sensing of Environment and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

R. Meneghini

141 papers receiving 5.2k citations

Hit Papers

Rain-Profiling Algorithm for the TRMM Precipitation Radar 2000 2026 2008 2017 2000 2016 250 500 750

Peers

R. Meneghini
Jothiram Vivekanandan United States
Alexander V. Ryzhkov United States
T. T. Wilheit United States
Carlton W. Ulbrich United States
Alexander Ryzhkov United States
Peter T. May Australia
Edward A. Brandes United States
Tammy M. Weckwerth United States
Jothiram Vivekanandan United States
R. Meneghini
Citations per year, relative to R. Meneghini R. Meneghini (= 1×) peers Jothiram Vivekanandan

Countries citing papers authored by R. Meneghini

Since Specialization
Citations

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

Fields of papers citing papers by R. Meneghini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of R. Meneghini

This figure shows the co-authorship network connecting the top 25 collaborators of R. Meneghini. A scholar is included among the top collaborators of R. Meneghini 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 R. Meneghini. R. Meneghini 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.
Li, Zhi, Yixin Wen, Liang Liao, et al.. (2023). Joint Collaboration on Comparing NOAA’s Ground-Based Weather Radar and NASA–JAXA’s Spaceborne Radar. Bulletin of the American Meteorological Society. 104(8). E1435–E1451. 9 indexed citations
2.
Meneghini, R., Hyo-Kyung Kim, Liang Liao, John Kwiatkowski, & Toshio Iguchi. (2020). Path Attenuation Estimates for the GPM Dual-frequency Precipitation Radar (DPR). Journal of the Meteorological Society of Japan Ser II. 99(1). 181–200. 14 indexed citations
3.
Seto, Shinta, Toshio Iguchi, R. Meneghini, et al.. (2020). The Precipitation Rate Retrieval Algorithms for the GPM Dual-frequency Precipitation Radar. Journal of the Meteorological Society of Japan Ser II. 99(2). 205–237. 68 indexed citations
4.
Liao, Liang, R. Meneghini, Ali Tokay, & Hyo-Kyung Kim. (2020). Assessment of Ku- and Ka-band Dual-frequency Radar for Snow Retrieval. Journal of the Meteorological Society of Japan Ser II. 98(6). 1129–1146. 9 indexed citations
5.
D’Adderio, Leo Pio, Gianfranco Vulpiani, Federico Porcù, Ali Tokay, & R. Meneghini. (2018). Comparison of GPM-CO and Ground-Based Radar Retrieval of Mass-Weighted Mean Rain Drop Diameter at Mid-Latitude. EGU General Assembly Conference Abstracts. 15907. 1 indexed citations
6.
Iguchi, Toshio, Shinta Seto, Jun Awaka, et al.. (2016). Performance of the Dual-frequency Precipitation Radar on the GPM core satellite. EGUGA. 1 indexed citations
7.
Meneghini, R.. (2015). Path Attenuation Estimates from the GPM Dual-Frequency Precipitation Radar. 1 indexed citations
8.
Munchak, S. Joseph, R. Meneghini, Mircea Grecu, & William S. Olson. (2015). A Consistent Treatment of Microwave Emissivity and Radar Backscatter for Retrieval of Precipitation over Water Surfaces. Journal of Atmospheric and Oceanic Technology. 33(2). 215–229. 7 indexed citations
9.
Williams, Christopher R., V. N. Bringi, Lawrence D. Carey, et al.. (2014). Describing the Shape of Raindrop Size Distributions Using Uncorrelated Raindrop Mass Spectrum Parameters. Journal of Applied Meteorology and Climatology. 53(5). 1282–1296. 81 indexed citations
10.
Meneghini, R.. (2011). Investigation of a dual-frequency surface reference technique for estimates of path-integrated attenuation.
11.
Iguchi, Toshio, Toshiaki Kozu, John Kwiatkowski, et al.. (2009). Uncertainties in the Rain Profiling Algorithm for the TRMM Precipitation Radar(1. Precipitation Radar (PR), Precipitation Measurements from Space). Journal of the Meteorological Society of Japan Ser II. 87. 1–30. 1 indexed citations
12.
Iguchi, Toshio, Toshiaki Kozu, John Kwiatkowski, et al.. (2009). Uncertainties in the Rain Profiling Algorithm for the TRMM Precipitation Radar. Journal of the Meteorological Society of Japan Ser II. 87A. 1–30. 253 indexed citations
13.
Liao, Liang & R. Meneghini. (2009). Changes in the TRMM Version-5 and Version-6 Precipitation Radar Products Due to Orbit Boost. Journal of the Meteorological Society of Japan Ser II. 87A. 93–107. 31 indexed citations
14.
Meneghini, R., Liang Liao, & Linwei Tian. (2006). The Potential of Water Vapor & Precipitation Estimation with a Differential-frequency Radar. 1 indexed citations
15.
Amitai, Eyal, et al.. (2005). Accuracy verification of spaceborne radar estimates of rain rate. Atmospheric Science Letters. 6(1). 2–6. 15 indexed citations
16.
Olson, William S., Péter Bauer, Nicolas Viltard, et al.. (2001). A Melting-Layer Model for Passive/Active Microwave Remote Sensing Applications. Part I: Model Formulation and Comparison with Observations. Journal of Applied Meteorology. 40(7). 1145–1163. 65 indexed citations
17.
Meneghini, R., S.W. Bidwell, Liang Liao, et al.. (2001). Doppler and reflectivity measurements at two closely-spaced frequencies. 1 indexed citations
18.
Prabhakara, C., R. Meneghini, David Short, et al.. (1998). A TRMM Microwave Radiometer Rain Retrieval Method Based on Fractional Rain Area. Journal of the Meteorological Society of Japan Ser II. 76(5). 765–781. 3 indexed citations
19.
Levine, D. M., R. Meneghini, Roger H. Lang, & Ş.S. Şeker. (1982). High Frequency Scattering from Arbitrarily Oriented Dielectric Disks. NASA STI/Recon Technical Report N. 83. 12306. 2 indexed citations
20.
Levine, D. M. & R. Meneghini. (1976). Radiation from a current filament driven by a traveling wave. NASA STI Repository (National Aeronautics and Space Administration). 77. 11294. 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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