Luis Pineda

757 total citations
11 papers, 395 citations indexed

About

Luis Pineda is a scholar working on Global and Planetary Change, Atmospheric Science and Water Science and Technology. According to data from OpenAlex, Luis Pineda has authored 11 papers receiving a total of 395 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Global and Planetary Change, 8 papers in Atmospheric Science and 3 papers in Water Science and Technology. Recurrent topics in Luis Pineda's work include Climate variability and models (7 papers), Cryospheric studies and observations (4 papers) and Meteorological Phenomena and Simulations (4 papers). Luis Pineda is often cited by papers focused on Climate variability and models (7 papers), Cryospheric studies and observations (4 papers) and Meteorological Phenomena and Simulations (4 papers). Luis Pineda collaborates with scholars based in Ecuador, Belgium and Sweden. Luis Pineda's co-authors include Patrick Willems, Louise Crochemore, Rafael Pimentel, Berit Arheimer, Kristina Isberg, Abdulghani Hasan, Patricio Crespo, Jafet Andersson, Juanjo Nieto and Marcos Villacís and has published in prestigious journals such as Journal of Hydrology, Hydrology and earth system sciences and Journal of Hydrometeorology.

In The Last Decade

Luis Pineda

10 papers receiving 390 citations

Peers

Luis Pineda

GPC

AS

WST

EE

ECOLO

Feifei Yuan China

Suwash Chandra Acharya Australia

Weidong Xuan China

Chong-Yu Xu China

S. Jang United States

Guendalina Bruni Netherlands

Guo Xiao-ying China

Kirsti Hakala Australia

Sun‐Kwon Yoon South Korea

Duncan Faulkner United Kingdom

Feifei Yuan China

Luis Pineda

335 ×1.1

GPC

217 ×1.0

AS

154 ×0.8

WST

128 ×1.6

EE

25 ×1.0

ECOLO

Citations per year, relative to Luis Pineda Luis Pineda (= 1×) peers Feifei Yuan

Countries citing papers authored by Luis Pineda

Since Specialization

Citations

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

Fields of papers citing papers by Luis Pineda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luis Pineda

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

All Works

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11 of 11 papers shown

1.

Pineda, Luis, et al.. (2023). Early onset of heavy rainfall on the northern coast of Ecuador in the aftermath of El Niño 2015/2016. Frontiers in Earth Science. 11. 5 indexed citations

2.

Pineda, Luis, et al.. (2021). Heavy rainfall in the northern coast of Ecuador in the aftermath of El Niño 2015/2016 and its predictability .

3.

Arheimer, Berit, Rafael Pimentel, Kristina Isberg, et al.. (2020). Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation. Hydrology and earth system sciences. 24(2). 535–559. 100 indexed citations

4.

Condom, Thomas, et al.. (2020). Climatological and Hydrological Observations for the South American Andes: In situ Stations, Satellite, and Reanalysis Data Sets. Frontiers in Earth Science. 8. 57 indexed citations

5.

Arheimer, Berit, Rafael Pimentel, Kristina Isberg, et al.. (2019). Global catchment modelling using World-Wide HYPE (WWH), open data and stepwise parameter estimation. Lund University Publications (Lund University). 16 indexed citations

6.

Crochemore, Louise, Kristina Isberg, Rafael Pimentel, et al.. (2019). Lessons learnt from checking the quality of openly accessible river flow data worldwide. Hydrological Sciences Journal. 65(5). 699–711. 64 indexed citations

7.

Pineda, Luis & Patrick Willems. (2018). Rainfall extremes, weather and climate drivers in complex terrain: A data-driven approach based on signal enhancement methods and EV modeling. Journal of Hydrology. 563. 283–302. 15 indexed citations

8.

Pineda, Luis, et al.. (2015). Revisiting Multi-Objective MDPs with Relaxed Lexicographic Preferences.. National Conference on Artificial Intelligence. 63–68. 3 indexed citations

9.

Pineda, Luis & Patrick Willems. (2015). Multisite Downscaling of Seasonal Predictions to Daily Rainfall Characteristics over Pacific–Andean River Basins in Ecuador and Peru Using a Nonhomogeneous Hidden Markov Model. Journal of Hydrometeorology. 17(2). 481–498. 14 indexed citations

10.

Pineda, Luis, et al.. (2014). Evaluation of TRMM 3B42 precipitation estimates and WRF retrospective precipitation simulation over the Pacific–Andean region of Ecuador and Peru. Hydrology and earth system sciences. 18(8). 3179–3193. 103 indexed citations

11.

Pineda, Luis, Victor Ntegeka, & Patrick Willems. (2013). Rainfall variability related to sea surface temperature anomalies in a Pacific–Andean basin into Ecuador and Peru. Advances in geosciences. 33. 53–62. 18 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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