Seppo Pulkkinen

724 total citations
29 papers, 411 citations indexed

About

Seppo Pulkkinen is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Seppo Pulkkinen has authored 29 papers receiving a total of 411 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Atmospheric Science, 10 papers in Global and Planetary Change and 6 papers in Environmental Engineering. Recurrent topics in Seppo Pulkkinen's work include Meteorological Phenomena and Simulations (16 papers), Precipitation Measurement and Analysis (15 papers) and Soil Moisture and Remote Sensing (5 papers). Seppo Pulkkinen is often cited by papers focused on Meteorological Phenomena and Simulations (16 papers), Precipitation Measurement and Analysis (15 papers) and Soil Moisture and Remote Sensing (5 papers). Seppo Pulkkinen collaborates with scholars based in Finland, United States and Switzerland. Seppo Pulkkinen's co-authors include Daniele Nerini, Loris Foresti, Carlos Velasco‐Forero, Alan Seed, Urs Germann, V. Chandrasekar, Ari‐Matti Harri, Tero Niemi, Teemu Kokkonen and Annakaisa von Lerber and has published in prestigious journals such as Applied Energy, IEEE Transactions on Geoscience and Remote Sensing and Journal of Hydrology.

In The Last Decade

Seppo Pulkkinen

28 papers receiving 399 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seppo Pulkkinen Finland 10 304 250 84 57 23 29 411
Gregory West Canada 13 382 1.3× 347 1.4× 79 0.9× 30 0.5× 19 0.8× 26 499
Jorge Baño‐Medina Spain 9 345 1.1× 359 1.4× 70 0.8× 72 1.3× 16 0.7× 18 479
Daniele Nerini Switzerland 10 531 1.7× 400 1.6× 118 1.4× 62 1.1× 30 1.3× 24 636
Jiali Wang United States 10 155 0.5× 157 0.6× 77 0.9× 20 0.4× 17 0.7× 18 286
Leiming Ma China 11 321 1.1× 200 0.8× 114 1.4× 17 0.3× 29 1.3× 36 419
Piers Buchanan United Kingdom 6 268 0.9× 245 1.0× 70 0.8× 21 0.4× 6 0.3× 8 308
Valentine Anantharaj United States 11 233 0.8× 214 0.9× 68 0.8× 42 0.7× 13 0.6× 41 340
Roberto Bentivoglio Netherlands 7 106 0.3× 240 1.0× 135 1.6× 138 2.4× 34 1.5× 9 305
Erik T. Smith United States 10 199 0.7× 220 0.9× 41 0.5× 17 0.3× 5 0.2× 20 357

Countries citing papers authored by Seppo Pulkkinen

Since Specialization
Citations

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

Fields of papers citing papers by Seppo Pulkkinen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seppo Pulkkinen

This figure shows the co-authorship network connecting the top 25 collaborators of Seppo Pulkkinen. A scholar is included among the top collaborators of Seppo Pulkkinen 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 Seppo Pulkkinen. Seppo Pulkkinen 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.
2.
Pulkkinen, Seppo, et al.. (2025). Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall. Geoscientific model development. 18(5). 1851–1878. 1 indexed citations
3.
Pulkkinen, Seppo, et al.. (2025). Benchmarking K DP in rainfall: a quantitative assessment of estimation algorithms using C-band weather radar observations. Atmospheric measurement techniques. 18(3). 793–816. 1 indexed citations
4.
Pulkkinen, Seppo, et al.. (2024). DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties. Geoscientific model development. 17(9). 3839–3866. 3 indexed citations
5.
Mäkinen, T., et al.. (2023). Advection-Free Convolutional Neural Network for Convective Rainfall Nowcasting. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 1654–1667. 16 indexed citations
6.
Folini, Doris, et al.. (2023). Intraday probabilistic forecasts of surface solar radiation with cloud scale-dependent autoregressive advection. Applied Energy. 351. 121775–121775. 14 indexed citations
7.
Mäkinen, T., et al.. (2022). Bayesian Classification of Nonmeteorological Targets in Polarimetric Doppler Radar Measurements. Journal of Atmospheric and Oceanic Technology. 39(10). 1561–1578. 6 indexed citations
8.
Zhang, Zhe, T.I. Laakso, Seppo Pulkkinen, et al.. (2020). Comparative Study of AI-Based Methods—Application of Analyzing Inflow and Infiltration in Sanitary Sewer Subcatchments. Sustainability. 12(15). 6254–6254. 14 indexed citations
9.
Schleiss, Marc, Jonas Olsson, Peter Berg, et al.. (2020). The accuracy of weather radar in heavy rain: a comparative study for Denmark, the Netherlands, Finland and Sweden. Hydrology and earth system sciences. 24(6). 3157–3188. 59 indexed citations
10.
Pulkkinen, Seppo, V. Chandrasekar, Annakaisa von Lerber, & Ari‐Matti Harri. (2020). Nowcasting of Convective Rainfall Using Volumetric Radar Observations. IEEE Transactions on Geoscience and Remote Sensing. 58(11). 7845–7859. 27 indexed citations
11.
Koistinen, Jarmo, Annakaisa von Lerber, Seppo Pulkkinen, et al.. (2019). Seamless probabilistic MUlti-source Forecasting of heavy rainfall hazards for European Flood awareness - SMUFF project. EGU General Assembly Conference Abstracts. 14302. 1 indexed citations
12.
Pulkkinen, Seppo, Daniele Nerini, Carlos Velasco‐Forero, et al.. (2019). Pysteps: an open-source Python library for probabilistic precipitation nowcasting (v1.0). Geoscientific model development. 12(10). 4185–4219. 161 indexed citations
13.
Pulkkinen, Seppo, Daniele Nerini, Carlos Velasco‐Forero, et al.. (2019). pysteps - a Community-Driven Open-Source Library for Precipitation Nowcasting. Arcimis (State Meteorological Agency). 2 indexed citations
14.
Pulkkinen, Seppo, V. Chandrasekar, & Ari‐Matti Harri. (2019). Stochastic Spectral Method for Radar-Based Probabilistic Precipitation Nowcasting. Journal of Atmospheric and Oceanic Technology. 36(6). 971–985. 9 indexed citations
15.
Pulkkinen, Seppo, V. Chandrasekar, & Ari‐Matti Harri. (2018). Nowcasting of Precipitation in the High-Resolution Dallas–Fort Worth (DFW) Urban Radar Remote Sensing Network. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(8). 2773–2787. 11 indexed citations
16.
Kyröläinen, Heikki, et al.. (2017). Effects of eight weeks of physical training on physical performance and heart rate variability in children. Biomedical Human Kinetics. 9(1). 175–180. 1 indexed citations
17.
Niemi, Tero, Lassi Warsta, Maija Taka, et al.. (2017). Applicability of open rainfall data to event-scale urban rainfall-runoff modelling. Journal of Hydrology. 547. 143–155. 23 indexed citations
18.
Pulkkinen, Seppo, et al.. (2016). Probabilistic radar-gauge merging by multivariate spatiotemporal techniques. Journal of Hydrology. 542. 662–678. 9 indexed citations
19.
Pulkkinen, Seppo. (2014). Nonlinear kernel density principal component analysis with application to climate data. Statistics and Computing. 26(1-2). 471–492. 4 indexed citations
20.
Pulkkinen, Seppo, Marko M. Mäkelä, & Napsu Karmitsa. (2011). A continuation approach to mode-finding of multivariate Gaussian mixtures and kernel density estimates. Journal of Global Optimization. 56(2). 459–487. 7 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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