Pedro Miranda

5.7k total citations
121 papers, 3.5k citations indexed

About

Pedro Miranda is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Pedro Miranda has authored 121 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Atmospheric Science, 48 papers in Global and Planetary Change and 46 papers in Oceanography. Recurrent topics in Pedro Miranda's work include Climate variability and models (44 papers), Meteorological Phenomena and Simulations (40 papers) and Tropical and Extratropical Cyclones Research (22 papers). Pedro Miranda is often cited by papers focused on Climate variability and models (44 papers), Meteorological Phenomena and Simulations (40 papers) and Tropical and Extratropical Cyclones Research (22 papers). Pedro Miranda collaborates with scholars based in Portugal, United Kingdom and Italy. Pedro Miranda's co-authors include Pedro M. M. Soares, Rita M. Cardoso, João Catalão, António Tomé, Pedro Viterbo, Miguel A. C. Teixeira, Emanuel Dutra, Pedro Benevides, Margarida Belo‐Pereira and Giovanni Nico and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Geophysical Research Letters and Annals of the New York Academy of Sciences.

In The Last Decade

Pedro Miranda

110 papers receiving 3.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pedro Miranda Portugal 31 2.1k 1.7k 966 512 472 121 3.5k
Anny Cazenave France 30 905 0.4× 1.2k 0.7× 1.9k 2.0× 430 0.8× 215 0.5× 63 3.2k
M. G. Bosilovich United States 7 2.0k 0.9× 2.5k 1.5× 1.5k 1.6× 608 1.2× 1.2k 2.4× 10 4.7k
Prakash Chauhan India 25 734 0.3× 1.2k 0.7× 735 0.8× 210 0.4× 571 1.2× 265 2.9k
J. Radakovich United States 4 1.7k 0.8× 2.2k 1.3× 1.5k 1.5× 598 1.2× 1.2k 2.4× 5 4.3k
U. Jambor United States 3 1.8k 0.8× 2.2k 1.3× 1.5k 1.5× 598 1.2× 1.2k 2.6× 5 4.4k
Mark Iredell United States 11 2.4k 1.2× 2.2k 1.3× 976 1.0× 103 0.2× 254 0.5× 18 3.3k
Jean‐François Crétaux France 32 667 0.3× 1.6k 1.0× 1.3k 1.3× 439 0.9× 545 1.2× 76 3.1k
Johnny A. Johannessen Norway 39 2.3k 1.1× 1.1k 0.7× 4.0k 4.1× 502 1.0× 269 0.6× 171 5.2k
Jérôme Benveniste Italy 30 1.0k 0.5× 900 0.5× 1.9k 2.0× 370 0.7× 379 0.8× 132 2.9k
Christopher Watson Australia 30 677 0.3× 682 0.4× 1.6k 1.6× 1.3k 2.5× 1.3k 2.9× 83 4.0k

Countries citing papers authored by Pedro Miranda

Since Specialization
Citations

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

Fields of papers citing papers by Pedro Miranda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pedro Miranda

This figure shows the co-authorship network connecting the top 25 collaborators of Pedro Miranda. A scholar is included among the top collaborators of Pedro Miranda 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 Pedro Miranda. Pedro Miranda 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.
Miranda, Pedro, et al.. (2025). Robust tests for log-logistic models based on minimum density power divergence estimators. Communications in Statistics - Simulation and Computation. 1–34.
2.
Miranda, Pedro, et al.. (2025). Ensino de ciências por investigação: o uso da horta escolar na promoção da alfabetização científica. DELOS Desarrollo Local Sostenible. 18(64). e4041–e4041.
3.
Mateus, Pedro, João Catalão, Rui Fernandes, & Pedro Miranda. (2024). Atmospheric Water Vapor Variability over Houston: Continuous GNSS Tomography in the Year of Hurricane Harvey (2017). Remote Sensing. 16(17). 3205–3205.
4.
Miranda, Pedro, David K. Adams, Ricardo Tomé, Rui Fernandes, & Pedro Mateus. (2023). Optimizing Boundary Conditions in GNSS Tomography: A Continuous 7‐Month Case Study in the Amazon. Geophysical Research Letters. 50(22). 3 indexed citations
5.
Matheou, Georgios, et al.. (2022). Large‐eddy simulation of very stable boundary layers. Part I: Modeling methodology. Quarterly Journal of the Royal Meteorological Society. 148(745). 1805–1823. 8 indexed citations
6.
Matheou, Georgios, et al.. (2022). Large‐eddy simulation of very stable boundary layers. Part II: Length scales and anisotropy in stratified atmospheric turbulence. Quarterly Journal of the Royal Meteorological Society. 148(745). 1824–1839. 5 indexed citations
7.
Miranda, Pedro, et al.. (2022). Breast Implant-Associated Anaplastic Large Cell Lymphoma: Two Distinct Clinical Presentations. Acta Médica Portuguesa. 35(11). 835–839. 1 indexed citations
8.
Richardson, Mark, et al.. (2021). Global mean frequency increases of daily and sub-daily heavy precipitation in ERA5. Environmental Research Letters. 16(7). 74035–74035. 35 indexed citations
9.
Stevens, David King, Pedro Miranda, René Orth, et al.. (2020). Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data. Atmosphere. 11(12). 1362–1362. 11 indexed citations
10.
Miranda, Pedro, et al.. (2020). Speed‐up of the Madeira tip jets in the ERA5 climate highlights the decadal variability of the Atlantic subtropics. Quarterly Journal of the Royal Meteorological Society. 147(734). 679–690. 12 indexed citations
11.
Miranda, Pedro, Pedro Mateus, Giovanni Nico, et al.. (2019). InSAR Meteorology: High‐Resolution Geodetic Data Can Increase Atmospheric Predictability. Geophysical Research Letters. 46(5). 2949–2955. 25 indexed citations
12.
Cardoso, Rita M., et al.. (2017). Climate change signal in the Portuguese precipitation: high-resolution projections using WRF model and EURO-CORDEX multi-model ensembles. EGU General Assembly Conference Abstracts. 16092. 1 indexed citations
13.
Nogueira, Miguel, et al.. (2016). The Portuguese Climate Portal. EGUGA. 2 indexed citations
14.
Boutov, Dmitri, Álvaro Peliz, Pedro Miranda, et al.. (2014). Inter-annual variability and long term predictability of exchanges through the Strait of Gibraltar. Global and Planetary Change. 114. 23–37. 19 indexed citations
15.
Mateus, Pedro, Giovanni Nico, Ricardo Tomé, João Catalão, & Pedro Miranda. (2012). On The Mitigation Of Atmospheric Phase Delay Artefacts In Interferometric SAR Time Series. ESASP. 697. 67. 1 indexed citations
16.
Mateus, Pedro, Giovanni Nico, Ricardo Tomé, João Catalão, & Pedro Miranda. (2010). Approaches to Mitigate Atmosphere Artefacts in SAR Interferograms: GPS vs. WRF Model. ESASP. 677. 12. 2 indexed citations
17.
Miranda, Pedro, et al.. (2010). The 20 February 2010 Madeira flash flood. 1 indexed citations
18.
Nico, Giovanni, Ricardo Tomé, Pedro Benevides, João Catalão, & Pedro Miranda. (2009). Interferometric SAR analysis of atmospheric water vapor properties. EGU General Assembly Conference Abstracts. 7904. 2 indexed citations
19.
Soares, Pedro M. M., Pedro Miranda, A. Pier Siebesma, & J. Teixeira. (2002). An Advection-diffusion Turbulence Parameterisation Scheme Based On The Tke Equation. EGSGA. 5982. 1 indexed citations
20.
Ricaldi, Edgar, et al.. (1996). Observaciones geomagnéticas en el observatorio de Patacamaya. 2(2). 106–115. 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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