Andrew Schepen

1.9k total citations
41 papers, 1.3k citations indexed

About

Andrew Schepen is a scholar working on Global and Planetary Change, Atmospheric Science and Water Science and Technology. According to data from OpenAlex, Andrew Schepen has authored 41 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Global and Planetary Change, 22 papers in Atmospheric Science and 15 papers in Water Science and Technology. Recurrent topics in Andrew Schepen's work include Climate variability and models (33 papers), Hydrology and Drought Analysis (24 papers) and Meteorological Phenomena and Simulations (22 papers). Andrew Schepen is often cited by papers focused on Climate variability and models (33 papers), Hydrology and Drought Analysis (24 papers) and Meteorological Phenomena and Simulations (22 papers). Andrew Schepen collaborates with scholars based in Australia, China and United Kingdom. Andrew Schepen's co-authors include Quan J. Wang, David Robertson, Tongtiegang Zhao, James Bennett, Ming Li, Yvette Everingham, Andrew W. Wood, Maria‐Helena Ramos, Dongryeol Ryu and Florian Pappenberger and has published in prestigious journals such as Nature Communications, Journal of Geophysical Research Atmospheres and Journal of Climate.

In The Last Decade

Andrew Schepen

40 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrew Schepen Australia	21	1.1k	638	514	303	71	41	1.3k
Munir Ahmad Nayak India	12	685 0.6×	292 0.5×	198 0.4×	95 0.3×	38 0.5×	24	824
Kabir Rasouli Canada	14	361 0.3×	317 0.5×	426 0.8×	263 0.9×	27 0.4×	29	771
Mingwei Ma China	17	732 0.7×	314 0.5×	482 0.9×	133 0.4×	33 0.5×	33	1.0k
Zafar Iqbal Malaysia	13	548 0.5×	311 0.5×	194 0.4×	128 0.4×	43 0.6×	17	702
Kirien Whan Netherlands	16	793 0.7×	644 1.0×	126 0.2×	171 0.6×	59 0.8×	34	1.0k
Nachiketa Acharya United States	17	652 0.6×	489 0.8×	99 0.2×	209 0.7×	35 0.5×	46	815
T. Brandsma Netherlands	15	685 0.6×	437 0.7×	162 0.3×	278 0.9×	22 0.3×	25	913
Javad Bazrafshan Iran	16	636 0.6×	145 0.2×	280 0.5×	119 0.4×	25 0.4×	47	802
Ansoumana Bodian Senegal	18	777 0.7×	157 0.2×	499 1.0×	250 0.8×	12 0.2×	55	1.0k
Irfan Ullah China	13	539 0.5×	200 0.3×	146 0.3×	111 0.4×	38 0.5×	29	735

Countries citing papers authored by Andrew Schepen

Since Specialization

Citations

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

Fields of papers citing papers by Andrew Schepen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Schepen

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wang, Quan J., et al.. (2025). Considering ensemble spread improves rainfall forecast post‐processing. Quarterly Journal of the Royal Meteorological Society. 151(767). 2 indexed citations

Slater, Louise, Anne J. Hoek van Dijke, Feini Huang, et al.. (2025). Challenges and opportunities of ML and explainable AI in large-sample hydrology. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 383(2302). 20240287–20240287. 6 indexed citations

Schepen, Andrew, John Carter, Donald S. Gaydon, et al.. (2025). Forecasting agricultural drought: the Australian Agricultural Drought Indicators. Natural hazards and earth system sciences. 25(10). 4053–4070.

Schepen, Andrew, James Bennett, David Robertson, et al.. (2025). A Distributional Regression Network With Data Transformation for Calibrating Rainfall Forecasts. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2(2). 1 indexed citations

Schepen, Andrew, Justin Sexton, Bronson Philippa, et al.. (2024). Downscaled numerical weather predictions can improve forecasts of sugarcane irrigation indices. Computers and Electronics in Agriculture. 221. 109009–109009. 3 indexed citations

Wang, Quan J., et al.. (2021). Introducing long‐term trends into subseasonal temperature forecasts through trend‐aware postprocessing. International Journal of Climatology. 42(9). 4972–4988. 8 indexed citations

Risbey, James S., Dougal T. Squire, Amanda S. Black, et al.. (2021). Standard assessments of climate forecast skill can be misleading. Nature Communications. 12(1). 4346–4346. 43 indexed citations

Wang, Quan J., et al.. (2020). Embedding trend into seasonal temperature forecasts through statistical calibration of GCM outputs. International Journal of Climatology. 41(S1). 11 indexed citations

Schepen, Andrew, Yvette Everingham, & Quan J. Wang. (2020). An improved workflow for calibration and downscaling of GCM climate forecasts for agricultural applications – A case study on prediction of sugarcane yield in Australia. Agricultural and Forest Meteorology. 291. 107991–107991. 11 indexed citations

10.

Schepen, Andrew, Yvette Everingham, & Quan J. Wang. (2019). On the Joint Calibration of Multivariate Seasonal Climate Forecasts from GCMs. Monthly Weather Review. 148(1). 437–456. 15 indexed citations

11.

Schepen, Andrew, Yvette Everingham, & Quan J. Wang. (2019). Coupling forecast calibration and data‐driven downscaling for generating reliable, high‐resolution, multivariate seasonal climate forecast ensembles at multiple sites. International Journal of Climatology. 40(4). 2479–2496. 7 indexed citations

12.

Zhao, Tongtiegang, Quan J. Wang, & Andrew Schepen. (2019). A Bayesian modelling approach to forecasting short-term reference crop evapotranspiration from GCM outputs. Agricultural and Forest Meteorology. 269-270. 88–101. 22 indexed citations

13.

Zhao, Tongtiegang, Quan J. Wang, Andrew Schepen, & Morwenna Griffiths. (2018). Ensemble forecasting of monthly and seasonal reference crop evapotranspiration based on global climate model outputs. Agricultural and Forest Meteorology. 264. 114–124. 42 indexed citations

14.

Schepen, Andrew, Tongtiegang Zhao, Quan J. Wang, & David Robertson. (2018). A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments. Hydrology and earth system sciences. 22(2). 1615–1628. 49 indexed citations

15.

Charles, Stephen P., Quan J. Wang, Mobin‐ud‐Din Ahmad, et al.. (2018). Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods. Hydrology and earth system sciences. 22(6). 3533–3549. 24 indexed citations

16.

Schepen, Andrew, Tongtiegang Zhao, Quan J. Wang, & David Robertson. (2017). A new method for post-processing daily sub-seasonal to seasonal rainfall forecasts from GCMs and evaluation for 12 Australian catchments. 4 indexed citations

17.

Bennett, James, Quan J. Wang, David Robertson, et al.. (2017). Assessment of an ensemble seasonal streamflow forecasting system for Australia. Hydrology and earth system sciences. 21(12). 6007–6030. 55 indexed citations

18.

Schepen, Andrew, Tongtiegang Zhao, Quan J. Wang, Senlin Zhou, & Paul Feikema. (2016). Optimising seasonal streamflow forecast lead time for operational decision making in Australia. Hydrology and earth system sciences. 20(10). 4117–4128. 17 indexed citations

19.

Shin, Daehyok, et al.. (2011). WAFARi: A new modelling system for Seasonal Streamflow Forecasting service of the Bureau of Meteorology, Australia. Chan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation.. 1 indexed citations

20.

Plummer, Neil, Narendra Tuteja, Quan J. Wang, et al.. (2009). A seasonal water availability prediction service: opportunities and challenges. Congress on Modelling and Simulation. 14 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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