Staff Profile:Dr Liz Stephens

Name:

Dr Liz Stephens

Job Title:

Associate Professor

Responsibilities:

• PI FATHUM Project
• Co-Director of Water@Reading with Professor Hannah Cloke
• Member of Consortium Coordination Team for Science for Humanitarian Emergencies and
• Resilience (SHEAR) Programme (NERC / DfID)
• Member of SHEAR Studentship Cohort Steering Group
• Environmental Science Research Division Impact Lead
  

Areas of Interest:

• Early warning systems and impact-based forecasting for hydrometeorological hazards
• Forecast-based Financing / Forecast-based Action, especially in humanitarian contexts
• Usability and understanding of probabilistic forecasts, decision-making under uncertainty
• Development and evaluation of the Global Flood Awareness System (GloFAS)
• Ensemble hydrometeorological forecasting and forecast evaluation

Research groups / Centres:

Environmental Sciences Research Division
Water@Reading

Key Facts:

Liz is currently seconded part time to the Red Cross Red Crescent Climate Centre as their Science Lead for Forecast-based Financing.

Liz is an interdisciplinary geographer with expertise in the assessment and forecasting of natural hazards. She works in collaboration with humanitarian organisations such as the Red Cross Red Crescent Climate Centre to improve decision-making from forecasts within developing country contexts, as part of the Forecast-based Financing community.

Liz is currently Principal Investigator of the Forecasts for AnTicipatory HUManitarian Action (FATHUM) project, funded by NERC / DfID's Science for Humanitarian Emergencies and Resilience (SHEAR) programme. The FATHUM project undertakes interdisciplinary research to strengthen forecast-based humanitarian action internationally.

From 2013 to 2016 Liz held a Leverhulme Early Career Fellowship working with the Joint Research Centre in Ispra, Italy and ECMWF on the Global Flood Awareness System (GloFAS), developing decision-relevant flood forecasting systems. Prior to joining the University of Reading in October 2013 Liz worked as a post-doctoral research assistant at Oxford University on a project addressing the usability of probabilistic forecasts.

Liz completed her PhD in Geography at the University of Bristol on the quantification and attribution of uncertainties in the modelling and mapping of flood risk. Additionally, as part of her roles in the KULTURrisk and UK Met Office Weather Game projects, Liz's research has addressed the challenges of communicating and utilising complex ensemble model output.

Projects:

• Principle Investigator: Forecasts for Anticipatory Humanitarian Action (FATHUM)
• Co-I Predicting Impacts of Cyclones in South-East Africa (PICSEA)
• Co-I National-Scale Impact-based Forecasting of Flood Risk in Uganda (NIMFRU)
• Co-I Improving the Role of Information Systems in Anticipatory Disaster Risk Reduction (IRIS)
• Co-I Improving Predictions of Drought for User Decision-Making (IMPETUS)

Current Postdoctoral Researchers:

• Dr Andrea Ficchi (FATHUM) - Hydrometeorology
• Dr Linda Speight (FATHUM) - Applied Flood Forecasting
• Dr Tobias Pforr (FATHUM) - Political Economy
• Dr Sara de Wit (FATHUM, Oxford University) - Social Anthropology

Postgraduate (PhD) Supervision:

Please feel free to contact me if you are interested in PhD research under any of my areas of interest. I am particularly keen to support potential students from groups not well represented in academia. The main route for funded studentships for UK / EU students is through the NERC SCENARIO DTP.

Lead Supervisor:

Sazzad Hossain. Extended range hydrometeorological forecasting for improved flood early warning to support earlier flood preparedness. Funded by NERC SHEAR Programme.

Faith Mitheu. A model for impact-based flood early warning in Uganda. Funded by NERC SHEAR Programme.

Jamie Towner. Climate variability and extended-range flood forecasting for the Peruvian Amazon. With Red Cross Climate Centre. Funded by NERC SCENARIO.

Second Supervisor:

Siobhan Dolan. Early warning of flash flood and landslide risk in S Asia. Funded by NERC SHEAR Programme. With ECMWF and British Geological Survey.

Fatima Pillosu. Statistical analysis of ECMWF Ensemble to improve rainfall inputs in real-time flood forecasting systems. Forecast Department, ECMWF

Helen Titley. Global flood predictability, early warning and the communication of probabilistic forecasts. Funded by the Met Office

Maureen Anyango Wanzala. Seamless seasonal to sub-seasonal forecasts of flood risk in River Nzoia Basin. Funded by a Commonwealth Scholarship

Ervin Zsoter. Understanding global flood hazard climatology for improved early flood warning. Funded by a Wilkie Calvert Studentship at ECMWF

Former PhD Students:

Dr Louise Arnal. Seasonal hydrological forecasting over Europe: prospects and applications. With ECMWF. Funded by a Faculty of Science Award and IMPREX (EC Horizon 2020 project)

Dr Rebecca Emerton. Extending the predictability of flood hazard at the global scale. Funded by NERC SCENARIO.

Publications:

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Jump to: 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012

Number of items: 28.

2020

• Zsoter, E. ORCID: https://orcid.org/0000-0002-7998-0130, Prudhomme, C. ORCID: https://orcid.org/0000-0003-1722-2497, Stephens, E. ORCID: https://orcid.org/0000-0002-5439-7563, Pappenberger, F. ORCID: https://orcid.org/0000-0003-1766-2898 and Cloke, H. ORCID: https://orcid.org/0000-0002-1472-868X (2020) Using ensemble reforecasts to generate flood thresholds for improved global flood forecasting. Journal of Flood Risk Management, 13 (4). e12658. ISSN 1753-318X doi: https://doi.org/10.1111/jfr3.12658
• Emerton, R., Cloke, H., Ficchi, A., Hawker, L., de Wit, S., Speight, L., Prudhomme, C., Rundell, P., West, R., Neal, J., Cuna, J., Harrigan, S., Titley, H., Magnusson, L., Pappenberger, F., Klingaman, N. and Stephens, L. (2020) Emergency flood bulletins for Cyclones Idai and Kenneth: a critical evaluation of the use of global flood forecasts for international humanitarian preparedness and response. International Journal of Disaster Risk Reduction, 50. 101811. ISSN 2212-4209 doi: https://doi.org/10.1016/j.ijdrr.2020.101811
• Zsótér, E., Cloke, H. L., Prudhomme, C., Harrigan, S., de Rosnay, P., Munoz-Sabater, J. and Stephens, E., (2020) Trends in the GloFAS-ERA5 river discharge reanalysis. ECMWF Technical Memoranda. 871. Technical Report. ECMWF doi: https://doi.org/10.21957/p9jrh0xp
• Arnal, L., Anspoks, L., Manson, S., Neumann, J. ORCID: https://orcid.org/0000-0003-3244-2578, Norton, T., Stephens, E. ORCID: https://orcid.org/0000-0002-5439-7563, Wolfenden, L. and Cloke, H. L. ORCID: https://orcid.org/0000-0002-1472-868X (2020) “Are we talking just a bit of water out of bank? Or is it Armageddon?” Front line perspectives on transitioning to probabilistic fluvial flood forecasts in England. Geoscience Communications, 3. pp. 203-232. ISSN 2569-7110 doi: https://doi.org/10.5194/gc-3-203-2020
• Towner, J., Cloke, H. L., Lavado, W., Santini, W., Bazo, J., Coughlan de Perez, E. and Stephens, E. M. (2020) Attribution of Amazon floods to modes of climate variability: a review. Meteorological Applications, 27 (5). e1949. ISSN 1469-8080 doi: https://doi.org/10.1002/met.1949

2019

• FicchÌ, A. and Stephens, L. (2019) Climate variability alters flood timing across Africa. Geophysical Research Letters, 46 (15). pp. 8809-8819. ISSN 0094-8276 doi: https://doi.org/10.1029/2019GL081988
• Emerton, R. E., Stephens, E. M. and Cloke, H. L. (2019) What is the most useful approach for forecasting hydrological extremes during El Niño? Environmental Research Communications, 1 (3). ISSN 2515-7620 doi: https://doi.org/10.1088/2515-7620/ab114e
• Towner, J., Cloke, H. L., Zsoter, E., Flamig, Z., Hoch, J. M., Bazo, J., Coughlan de Perez, E. and Stephens, E. M. (2019) Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin. Hydrology and Earth System Sciences, 23 (7). pp. 3057-3080. ISSN 1027-5606 doi: https://doi.org/10.5194/hess-23-3057-2019
• Zsoter, E., Cloke, H., Stephens, E., De Rosnay, P., Muñoz-Sabater, J., Prudhomme, C. and Pappenberger, F. (2019) How well do operational Numerical Weather Prediction configurations represent hydrology? Journal of Hydrometeorology, 20 (8). pp. 1533-1552. ISSN 1525-7541 doi: https://doi.org/10.1175/JHM-D-18-0086.1
• Stephens, E. M., Spiegelhalter, D. J., Mylne, K. and Harrison, M. (2019) The Met Office weather game: investigating how different methods for presenting probabilistic weather forecasts influence decision-making. Geoscience Communications, 2. pp. 101-116. ISSN 2569-7110 doi: https://doi.org/10.5194/gc-2-101-2019

2018

• Emerton, R., Zsoter, E., Arnal, L., Cloke, H. L., Muraro, D., Prudhomme, C., Stephens, E. M., Salamon, P. and Pappenberger, F. (2018) Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0. Geoscientific Model Development, 11. pp. 3327-3346. ISSN 1991-9603 doi: https://doi.org/10.5194/gmd-2018-118
• Hirpa, F. A., Pappenberger, F., Arnal, L., Baugh, C. A., Cloke, H. L., Dutra, E., Emerton, R. E., Revilla-Romero, B., Salamon, P., Smith, P. J., Stephens, E., Wetterhall, F., Zsoter, E. and Thielen-del Pozo, J. (2018) Global flood forecasting for averting disasters worldwide. In: Schumann, G. J.-P., Bates, P. D., Apel, H. and Aronica, G. T. (eds.) Global Flood Hazard: Applications in Modeling, Mapping, and Forecasting. Geophysical Monograph Series (233). Wiley, pp. 205-228. ISBN 9781119217862 doi: https://doi.org/10.1002/9781119217886.ch12
• Coughlan de Perez, E., Van Aalst, M., Bischiniotis, K., Mason, S., Nissan, H., Pappenberger, F., Stephens, E. and van den Hurk, B. (2018) Global predictability of temperature extremes. Environmental Research Letters, 13 (5). 054017. ISSN 1748-9326 doi: https://doi.org/10.1088/1748-9326/aab94a
• Arnal, L., Cloke, H. L., Stephens, E., Wetterhall, F., Prudhomme, C., Neumann, J., Krzeminski, B. and Pappenberger, F. (2018) Skilful seasonal forecasts of streamflow over Europe? Hydrology and Earth System Sciences, 22 (4). pp. 2057-2072. ISSN 1027-5606 doi: https://doi.org/10.5194/hess-22-2057-2018

2017

• Arnal, L., Wood, A. W., Stephens, E., Cloke, H. L. and Pappenberger, F. (2017) An efficient approach for estimating streamflow forecast skill elasticity. Journal of Hydrometeorology, 18 (6). pp. 1715-1729. ISSN 1525-7541 doi: https://doi.org/10.1175/JHM-D-16-0259.1
• Emerton, R., Cloke, H. L., Stephens, E. M., Zsoter, E., Woolnough, S. J. and Pappenberger, F. (2017) Complex picture for likelihood of ENSO-driven flood hazard. Nature Communications, 8. 14796. ISSN 2041-1723 doi: https://doi.org/10.1038/ncomms14796
• Coughlan de Perez, E., Stephens, E., Bischiniotis, K., van Aalst, M., van den Hurk, B., Mason, S., Nissan, H. and Pappenberger, F. (2017) Should seasonal rainfall forecasts be used for flood preparedness? Hydrology and Earth System Sciences, 21 (9). pp. 4517-4524. ISSN 1027-5606 doi: https://doi.org/10.5194/hess-21-4517-2017

2016

• Coughlan de Perez, E., van den Hurk, B., van Aalst, M. K., Amuron, I., Bamanya, D., Hauser, T., Jongman, B., Lopez, A., Mason, S., Mendler de Suarez, J., Pappenberger, F., Rueth, A., Stephens, E., Suarez, P., Wagemaker, J. and Zsoter, E. (2016) Action-based flood forecasting for triggering humanitarian action. Hydrology and Earth System Sciences, 20 (9). pp. 3549-3560. ISSN 1027-5606 doi: https://doi.org/10.5194/hess-2016-163
• Arnal, L., Ramos, M.-H., Coughlan de Perez, E., Cloke, H., Stephens, E., Wetterhall, F., van Andel, S.-J. and Pappenberger, F. (2016) Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game. Hydrology and Earth System Sciences, 20 (8). pp. 3109-3128. ISSN 1027-5606 doi: https://doi.org/10.5194/hess-20-3109-2016
• Emerton, R. E., Stephens, E. M., Pappenberger, F., Pagano, T. C., Weerts, A. H., Wood, A. W., Salamon, P., Brown, J. D., Hjerdt, N., Donnelly, C., Baugh, C. and Cloke, H. L. (2016) Continental and global scale flood forecasting systems. Wiley Interdisciplinary Reviews: Water, 3 (3). pp. 391-418. ISSN 2049-1948 doi: https://doi.org/10.1002/wat2.1137

2015

• Stephens, E., Day, J. J., Pappenberger, F. and Cloke, H. (2015) Precipitation and floodiness. Geophysical Research Letters, 42 (23). pp. 10316-10323. ISSN 0094-8276 doi: https://doi.org/10.1002/2015GL066779
• Stephens, E. and Bates, P. (2015) Assessing the reliability of probabilistic flood inundation model predictions. Hydrological Processes, 29 (19). pp. 4264-4283. ISSN 08856087 doi: https://doi.org/10.1002/hyp.10451

2014

• Stephens, E. and Cloke, H. (2014) Improving flood forecasts for better flood preparedness in the UK (and beyond). Geographical Journal, 180 (4). pp. 310-316. ISSN 1475-4959 doi: https://doi.org/10.1111/geoj.12103
• Wong, J. S., Freer, J. E., Bates, P. D. and Stephens, E. M. (2014) Sensitivity of a hydraulic model to changes in channel erosion during extreme flooding. Hydrological Processes, 29 (2). pp. 261-279. ISSN 0885-6087 doi: https://doi.org/10.1002/hyp.10148

2013

• Pappenberger, F., Stephens, E. M., Thielen, J., Salamon, P., Demeritt, D., Van Andel, S. J., Wetterhall, F. and Alfieri, L. (2013) Visualizing probabilistic flood forecast information: expert preferences and perceptions of best practice in uncertainty communication. Hydrological Processes, 27 (1). pp. 132-146. ISSN 0885-6087 doi: https://doi.org/10.1002/hyp.9253
• Stephens, E., Schumann, G. and Bates, P. (2013) Problems with binary pattern measures for flood model evaluation. Hydrological Processes, 28 (18). pp. 4928-4937. ISSN 0885-6087 doi: https://doi.org/10.1002/hyp.9979

2012

• Stephens, E. M., Edwards, T. L. and Demeritt, D. (2012) Communicating probabilistic information from climate model ensembles—lessons from numerical weather prediction. Wiley Interdisciplinary Reviews: Climate Change, 3 (5). pp. 409-426. ISSN 1757-7799 doi: https://doi.org/10.1002/wcc.187
• Stephens, E. M., Bates, P. D., Freer, J. and Mason, D. (2012) The impact of uncertainty in satellite data on the assessment of flood inundation models. Journal of Hydrology, 414-41. pp. 162-173. ISSN 0022-1694 doi: https://doi.org/10.1016/j.jhydrol.2011.10.040 (414-415, 162-173)

This list was generated on Sat Jan 23 20:47:59 2021 UTC.