Alan Seed

4.3k total citations
90 papers, 3.0k citations indexed

About

Alan Seed is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Alan Seed has authored 90 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Atmospheric Science, 67 papers in Global and Planetary Change and 19 papers in Environmental Engineering. Recurrent topics in Alan Seed's work include Precipitation Measurement and Analysis (58 papers), Meteorological Phenomena and Simulations (54 papers) and Hydrology and Drought Analysis (38 papers). Alan Seed is often cited by papers focused on Precipitation Measurement and Analysis (58 papers), Meteorological Phenomena and Simulations (54 papers) and Hydrology and Drought Analysis (38 papers). Alan Seed collaborates with scholars based in Australia, New Zealand and United Kingdom. Alan Seed's co-authors include Clive Pierce, G. L. Austin, Merab Menabde, Neill E. Bowler, Ashish Sharma, Daniel Harris, Siriluk Chumchean, Loris Foresti, Geoff Pegram and Urs Germann and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Water Resources Research and Journal of Hydrology.

In The Last Decade

Alan Seed

89 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alan Seed Australia 31 2.4k 2.2k 654 557 76 90 3.0k
Urs Germann Switzerland 35 3.3k 1.4× 2.6k 1.2× 793 1.2× 705 1.3× 13 0.2× 108 3.9k
Yuejian Zhu United States 24 2.3k 1.0× 2.4k 1.1× 493 0.8× 429 0.8× 37 0.5× 67 2.9k
Nikolina Ban Switzerland 22 3.1k 1.3× 3.5k 1.6× 294 0.4× 500 0.9× 13 0.2× 34 4.0k
Isztar Zawadzki Canada 41 4.9k 2.1× 3.3k 1.5× 1.4k 2.2× 310 0.6× 48 0.6× 130 5.4k
Luca Ferraris Italy 23 810 0.3× 1.2k 0.5× 235 0.4× 507 0.9× 14 0.2× 60 1.4k
Yudong Tian United States 30 3.1k 1.3× 2.4k 1.1× 1.0k 1.5× 850 1.5× 12 0.2× 52 3.8k
Juerg Schmidli Germany 20 2.3k 1.0× 2.4k 1.1× 387 0.6× 267 0.5× 12 0.2× 47 2.8k
C. Kidd United States 21 1.8k 0.7× 1.3k 0.6× 654 1.0× 361 0.6× 7 0.1× 60 2.2k
Ali Tokay United States 33 4.2k 1.7× 2.3k 1.0× 1.3k 2.0× 156 0.3× 10 0.1× 96 4.5k
Frédérique Cheruy France 22 1.8k 0.8× 2.1k 1.0× 539 0.8× 247 0.4× 8 0.1× 49 2.6k

Countries citing papers authored by Alan Seed

Since Specialization
Citations

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

Fields of papers citing papers by Alan Seed

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alan Seed

This figure shows the co-authorship network connecting the top 25 collaborators of Alan Seed. A scholar is included among the top collaborators of Alan Seed 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 Alan Seed. Alan Seed 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.
Guyot, Adrien, Alain Protat, R. Uijlenhoet, et al.. (2019). Effect of disdrometer type on rain drop size distribution characterisation: a new dataset for south-eastern Australia. Hydrology and earth system sciences. 23(11). 4737–4761. 33 indexed citations
2.
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
3.
Foresti, Loris, Maarten Reyniers, Alan Seed, & Laurent Delobbe. (2016). Development and verification of a real-time stochastic precipitation nowcasting system for urban hydrology in Belgium. Hydrology and earth system sciences. 20(1). 505–527. 68 indexed citations
4.
Seed, Alan, et al.. (2015). Seamless hourly rainfall ensemble forecasts. 1 indexed citations
5.
Bates, Bryson C., Daniel Argüeso, Jason P. Evans, et al.. (2015). Preliminary assessment of the impact of climate change on design rainfall IFD curves. University of Southern Queensland ePrints (University of Southern Queensland). 2 indexed citations
6.
Jakob, Dörte, et al.. (2015). Assessing the credibility of downscaled rainfall extremes for the Greater Sydney region - a novel approach using blended radar/gauge data. 80. 1 indexed citations
7.
Jordan, Phillip, Rory Nathan, & Alan Seed. (2015). Application of spatial and space-time patterns of design rainfall to design flood estimation. 88. 1 indexed citations
8.
Foresti, Loris & Alan Seed. (2014). The effect of flow and orography on the spatial distribution of the very short-term predictability of rainfall from composite radar images. Hydrology and earth system sciences. 18(11). 4671–4686. 19 indexed citations
9.
Seed, Alan, et al.. (2012). Application of a space-time stochastic model for downscaling future rainfall projections. 579–586. 5 indexed citations
10.
Walker, Jeffrey P., et al.. (2011). Comparison of weather radar, numerical weather prediction and gauge-based rainfall estimates. Chan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation.. 4 indexed citations
11.
Zappa, Massimiliano, Keith Beven, Michael Bruen, et al.. (2010). Propagation of uncertainty from observing systems and NWP into hydrological models: COST‐731 Working Group 2. Atmospheric Science Letters. 11(2). 83–91. 72 indexed citations
12.
Siriwardena, L, et al.. (2006). Which Theoretical Distribution Function Best Fits Measured within Day Rainfall Distributions across Australia. Minerva Access (University of Melbourne). 498. 2 indexed citations
13.
Austin, G. L. & Alan Seed. (2005). Special issue on the hydrological applications of weather radar—guest editors' preface. Atmospheric Science Letters. 6(1). 1–1. 3 indexed citations
14.
Yu, Bofu, et al.. (2005). Integration of weather radar data into a raster GIS framework for improved flood estimation. Atmospheric Science Letters. 6(1). 66–70. 5 indexed citations
15.
Gray, W. R., et al.. (2005). Nowcasting for New Zealand. Atmospheric Science Letters. 6(1). 35–39. 2 indexed citations
16.
Pierce, Chris, Elizabeth E. Ebert, Alan Seed, et al.. (2004). The Nowcasting of Precipitation during Sydney 2000: An Appraisal of the QPF Algorithms. Weather and Forecasting. 19(1). 7–21. 63 indexed citations
17.
Seed, Alan. (2004). Modelling and forecasting rainfall in space and time. IAHS-AISH publication. 137–152. 3 indexed citations
18.
Jordan, Phillip & Alan Seed. (2002). Are We Taking the Point Too Far?: A Problem with Design Temporal Patterns at Catchment Scale. 111. 2 indexed citations
19.
Pegram, Geoff, Alan Seed, & Scott Sinclair. (2002). Comparison of Methods of Short-term Rainfield Nowcasting. EGSGA. 4355. 1 indexed citations
20.
Seed, Alan. (2001). A dynamic and spatial scaling approach to advection forecasting. 2 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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