Daniel Vila

2.5k total citations
44 papers, 1.6k citations indexed

About

Daniel Vila is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Daniel Vila has authored 44 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Atmospheric Science, 30 papers in Global and Planetary Change and 10 papers in Environmental Engineering. Recurrent topics in Daniel Vila's work include Precipitation Measurement and Analysis (35 papers), Meteorological Phenomena and Simulations (31 papers) and Climate variability and models (19 papers). Daniel Vila is often cited by papers focused on Precipitation Measurement and Analysis (35 papers), Meteorological Phenomena and Simulations (31 papers) and Climate variability and models (19 papers). Daniel Vila collaborates with scholars based in Brazil, United States and Argentina. Daniel Vila's co-authors include José Roberto Rozante, L. Goncalves, Luiz A. T. Machado, Paola Salio, Yanina García Skabar, Demerval Soares Moreira, D. L. Toll, H. Laurent, Viviana Maggioni and Dirceu Luís Herdies and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Journal of Hydrology and Atmospheric chemistry and physics.

In The Last Decade

Daniel Vila

44 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Vila Brazil 20 1.4k 1.2k 323 275 69 44 1.6k
Brice Boudevillain France 25 1.1k 0.8× 958 0.8× 418 1.3× 315 1.1× 78 1.1× 50 1.5k
Youcun Qi China 21 1.7k 1.2× 1.0k 0.9× 353 1.1× 571 2.1× 54 0.8× 56 2.0k
Jean‐Martial Cohard France 19 633 0.5× 804 0.7× 166 0.5× 230 0.8× 59 0.9× 42 1.0k
Victor Venema Germany 11 1.0k 0.8× 1.4k 1.2× 441 1.4× 153 0.6× 30 0.4× 24 1.6k
Giorgia Fosser Italy 16 1.7k 1.3× 1.9k 1.7× 267 0.8× 125 0.5× 51 0.7× 29 2.1k
Tomeu Rigo Spain 25 1.1k 0.8× 1.2k 1.0× 130 0.4× 147 0.5× 72 1.0× 82 1.6k
Paola Salio Argentina 18 1.6k 1.2× 1.5k 1.3× 207 0.6× 227 0.8× 67 1.0× 45 1.9k
Lijuan Cao China 18 814 0.6× 1.1k 0.9× 137 0.4× 340 1.2× 53 0.8× 39 1.3k
B. Imam United States 16 1.8k 1.3× 1.6k 1.3× 641 2.0× 620 2.3× 56 0.8× 25 2.3k
Erwan Brisson Germany 14 1.3k 1.0× 1.4k 1.2× 183 0.6× 185 0.7× 41 0.6× 33 1.7k

Countries citing papers authored by Daniel Vila

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Vila

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Vila

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Vila. A scholar is included among the top collaborators of Daniel Vila 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 Daniel Vila. Daniel Vila 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.
Vila, Daniel, et al.. (2022). Analysis of Extreme Rainfall and Natural Disasters Events Using Satellite Precipitation Products in Different Regions of Brazil. Atmosphere. 13(10). 1680–1680. 16 indexed citations
2.
Eriksson, Patrick, et al.. (2022). An improved near-real-time precipitation retrieval for Brazil. Atmospheric measurement techniques. 15(23). 6907–6933. 3 indexed citations
3.
Vila, Daniel, et al.. (2020). Assessment of the Extreme Precipitation by Satellite Estimates over South America. Remote Sensing. 12(13). 2085–2085. 45 indexed citations
4.
Rozante, José Roberto, et al.. (2020). Performance of precipitation products obtained from combinations of satellite and surface observations. International Journal of Remote Sensing. 41(19). 7585–7604. 27 indexed citations
5.
Vila, Daniel, et al.. (2019). Can disaster events reporting be used to drive remote sensing applications? A Latin America weather index insurance case study. Meteorological Applications. 26(4). 632–641. 9 indexed citations
6.
Vila, Daniel, Damien Arvor, Thomas Corpetti, et al.. (2018). Performance of TRMM TMPA 3B42 V7 in Replicating Daily Rainfall and Regional Rainfall Regimes in the Amazon Basin (1998–2013). Remote Sensing. 10(12). 1879–1879. 30 indexed citations
7.
Barbieri, S., Daniel Vila, Silvia Puca, et al.. (2018). Assessment of Ground-Reference Data and Validation of the H-SAF Precipitation Products in Brazil. Remote Sensing. 10(11). 1743–1743. 4 indexed citations
8.
Braga, Ramon Campos, Daniel Rosenfeld, Ralf Weigel, et al.. (2017). Aerosol concentrations determine the height of warm rain and ice initiation in convective clouds over the Amazon basin. 4 indexed citations
9.
Braga, Ramon Campos, Daniel Rosenfeld, Ralf Weigel, et al.. (2017). Comparing parameterized versus measured microphysical properties of tropical convective cloud bases during the ACRIDICON–CHUVA campaign. Atmospheric chemistry and physics. 17(12). 7365–7386. 20 indexed citations
10.
Salio, Paola, et al.. (2017). Assessment of satellite precipitation estimates over the slopes of the subtropical Andes. Atmospheric Research. 190. 43–54. 78 indexed citations
11.
Braga, Ramon Campos, Daniel Rosenfeld, Ralf Weigel, et al.. (2017). Further evidence for CCN aerosol concentrations determining the height of warm rain and ice initiation in convective clouds over the Amazon basin. Atmospheric chemistry and physics. 17(23). 14433–14456. 57 indexed citations
12.
Ferreira, Nelson J., Timothy J. Schmit, Juan Carlos Ceballos, et al.. (2017). A Successful Practical Experience with Dedicated Geostationary Operational Environmental Satellites GOES-10 and -12 Supporting Brazil. Bulletin of the American Meteorological Society. 99(1). 33–47. 7 indexed citations
13.
14.
Skabar, Yanina García, et al.. (2016). Validación de la estimación de precipitación por satélite aplicando la técnica hidroestimador. Conicet. 42(1). 19–37. 3 indexed citations
15.
Kirstetter, Pierre‐Emmanuel, et al.. (2015). A consistent gauge database for daily rainfall analysis over the Legal Brazilian Amazon. Journal of Hydrology. 527. 292–304. 26 indexed citations
16.
Salio, Paola, et al.. (2014). Evaluation of high-resolution satellite precipitation estimates over southern South America using a dense rain gauge network. Atmospheric Research. 163. 146–161. 149 indexed citations
17.
Braga, Ramon Campos, et al.. (2014). Evaluation of GPROF-SSMI/S rainfall estimates over land during the Brazilian CHUVA-VALE campaign. Atmospheric Research. 163. 102–116. 7 indexed citations
18.
Fiolleau, Thomas, Rémy Roca, Daniel Vila, Luiz A. T. Machado, & C. F. Angelis. (2012). A new methodology for the detection and tracking of mesoscale convective systems in the tropics using geostationary infrared data. EGUGA. 11283. 1 indexed citations
19.
Inoue, Toshiro, Daniel Vila, Kavirajan Rajendran, et al.. (2009). Life Cycle of Deep Convective Systems over the Eastern Tropical Pacific Observed by TRMM and GOES-W. Journal of the Meteorological Society of Japan Ser II. 87A. 381–391. 20 indexed citations
20.
Vila, Daniel, et al.. (2009). Improved Global Rainfall Retrieval Using the Special Sensor Microwave Imager (SSM/I). Journal of Applied Meteorology and Climatology. 49(5). 1032–1043. 11 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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