Survey results: views and opinions about Hepex and hydrological forecasting

Contributed by Maria-Helena Ramos

At the beginning of the year, we launched a short online survey to gather some views and opinions about Hepex and start a discussion on the future of Hepex: how should the community continue its efforts? What should Hepex be in 10 years’ time?

During the 7th International Hepex Workshop in Melbourne we had an interactive poster that complemented this survey and collected some more views and opinions from the participants of the workshop.

Below you will find some interesting results from this survey, summarized from the 40 responses collected and the workshop poster.

Who we are

The online survey received answers from people working all over the world, as can be seen below:

The answers showed that respondents are:

  • more involved in science, operations, ensemble techniques, hydrological modelling and verification;
  • less involved in policy making, flood inundation mapping, evaluation of economic value and user-driven evaluation.

See the answers below for:

“How much are you involved in…”

  1. Forecasting science
  2. Operational forecasting
  3. Forecast-based decision making
  4. Policy making
  5. Ensemble techniques in meteorology
  6. Ensemble techniques in hydrology
  7. Hydrological modelling for forecasting systems
  8. Flood inundation mapping
  9. Data assimilation
  10. Statistical pre/post-processing, bias correction
  11. Verification of forecast quality
  12. Evaluation of the economic value of forecasts
  13. User-driven evaluation of forecast added value

HEPEX activities: 

A large majority (72.5%) visit the Hepex Blog Portal at least once a month (50%, at least twice a month). Additionally, 90% of the survey respondents say they are satisfied or very satisfied with Hepex.

  • The Hepex activities they like most are workshops, sessions or meetings at major conferences, special journal issues, the Blog portal, mailing list and interview posts.
  • There was no majority “disliking” a particular activity, but some people said they like “very little” Twitter, LinkedIn and Hepex Daily.
  • “No opinion” was more often voted for Hepex Daily, Twitter, LinkedIn and Experiments and testbeds.

How much do you like the following HEPEX activities?

  1. HEPEX Workshops
  2. HEPEX sessions or meetings at major conferences (EGU, AGU, IAHS)
  3. HEPEX experiments or testbeds
  4. Special HEPEX journal issue
  5. The Blog Portal (www.hepex.org)
  6. Webinars
  7. Notifications through the HEPEX Google mailing list
  8. Communication through HEPEX LinkedIn
  9. Communication through HEPEX Twitter
  10. The HEPEX Daily!
  11. Interview blog posts
  12. April fools! blog posts

Some respondents noted that, given limited and volunteer resources, Hepex is already doing plenty of activities. However, some suggested other possible additional activities that we could have in Hepex. The main suggestions are compiled below:

Young Hepex-ers, training and outreach:

  • A “young HEPEX” subgroup (PhD students and 2-3 years Postdoc) to initiate educational courses and lead tasks, and to guarantee dialogue among new contributors/friends.
  • Training sessions, summer school, winter course, MOOC, Education oriented sections (towards young hydrological scientists and more).
  • Advanced short courses in best community practice/state of the art hydrological forecasting for next generation of scientists (MSc, PhD, early career scientists).
  • More outreach to the public and decision makers to understand the need for probabilistic forecasting over deterministic forecasting.
Post-event analyses, testbeds, experiments:

  • More post-event analyses, operational points of view, and showcases in different areas.
  • More rigorous comparisons and frameworks, international testbeds, and more momentum in experiments/testbeds.
Funding & projects, regional activities, science advising:

  • Reflecting on how we might collectively begin applying for international research grant programs.
  • Funding for HEPEX testbeds.
  • Intermittent activity to write an occasional letter to funding programs or agencies advocating for investment in key science areas.
  • More regional activities in Asian Pacific.
  • HEPEX is in a very good position to influence other scientific communities. How about using this to propose novel common methods for doing and showcasing science? E.g. Should the concept of scientific papers be redesigned to be more concise, where information can be summarised in one diagram? Should we reconsider our approach for experiments design? Should an experiment be designed primarily to solve, explore a user or operational need?
Publications, website & tools:

  • More common experiments and papers.
  • We could identify a handful of barriers in ensemble prediction and application to work on jointly and aim to demonstrate how these are being tackled and what progress has been made in a few short joint papers.
  • Collaborative effort to write scientific articles/opinion paper.
  • Reviews of published work.
  • A web page with relevant publications classified by themes, test bed, applications, etc to facilitate research by the members/contributors. Each publication should have 3 highlights (120 characters each) so that this is more than a repository.
  • The web page would also allow reports because many operators will have reports that are precious information, publicly available, just not peer reviewed. That might facilitate in the future some review papers/summary as well.
  • A dynamic roadmap that explains the techniques used for each attribute/context and the different steps of the forecasting framework.
  • A shared code repository.

“Today, Hydrological Ensemble Prediction is…”

“For me, HEPEX is….”

  • a way of keeping in touch.
  • a community of researchers working on similar / related research topics to myself and my interests.
  • a platform to know what is currently ongoing in hydrological science.
  • a very useful network to discuss broad scientific and technical questions related to hydrometeorological ensemble forecasts.
  • greatly needed to promote ensemble hydrological forecasting.
  • a community of scientists with a common interest.
  • a great community.
  • very important! Keep me update!
  • the place to be.
  • my scientific family (a bit cheesy but true).
  • a friendly and open group of scientists who believe more progress can be made as a collective rather than only individuals.
  • mainly a science community.
  • an international scientific/user community, in which I can disseminate results from my investigations efficiently, whilst I can get constructive criticism. These are the benefits of being a member of a family.
  • a place to be inspired and challenged.
  • a very inclusive community of researchers and practitioners furthering the development and use of ensemble prediction methods for streamflow.
  • a family.
  • an informal community of people interested in hydrometeorological forecasting, trying to stay connected with the latest science and find collaborators.
  • a coalition of the willing.
  • a community of common ideas and purpose.
  • non funded excellence in science done by peers that are also friends.
  • a nice resource to keep updated with developments in ensemble forecasting.
  • a welcoming, competent and active community!
  • an initiative to coordinate world-wide work and advance flood prediction.
  • motivation and support.
  • a great community of ensemble forecast researchers, users and communicators.
  • a community where people exchange ideas and collaborate.
  • a collaborative scientific community dedicated to improving ensemble flow forecast and developing its operational implementation.
  • the reference community in probabilistic hydrologic forecasting.
  • interesting as an outsider.
  • the best scientific group I’ve ever met.
  • a way to stay connected with the ensemble forecasting community.
  • an outstanding example of international scientific community.
  • HEPEX is a window that I can view the world of ESP research.

“The future of HEPEX is….”

We could identify four main groups of responses:

IN GENERAL
  • assured
  • fantastic
  • very promising for the betterment of mankind
  • bright because many opportunities exist
SCIENCE AND OPERATIONS
  • going more operational, and more sub-seasonal.
  • as for TIGGE and S2S, have WMO supporting it to provide a range of operational products freely available to everyone.
  • a bridge between research and operations, with focus on automation of multi-model ensemble hydrological forecasting, efficient dissemination of information and optimal decision making.
COMMUNITY AND MEMBERSHIP
  • continuing to build its community
  • a growing community and enabler of exciting research
  • linked to people and surely facing ups and downs
  • involvement of more members
  • more involvement from the members in the daily work
  • more active
  • widespread
  • the early career scientists!
  • to become more interdisciplinary, especially by connecting more with humanities and social sciences.
  • resides in continuing in filling the gaps between the diverse communities interested in the many aspects of flood forecasting.
  • to promote hydrological ensemble prediction and facilitate exchanges and collaboration.
  • remaining HEPEX and keeping the promotion of collaboration both in experiments, ideas, and in training students.
  • bridging the gap between research community and operational/end-user community.
POSSIBLE PATHWAYS
  • to be clarified. Either it becomes a group in which everybody wants to have its name but few contribute, or it comes back to something more structured with identified key questions / test cases / methods…
  • unknown.
  • unclear. It can continue as it is with greater and more balanced investment of time by members to contribute interesting blogs and self-organize to create gatherings/meetings.  It can try to become more formal, perhaps with a certain funding to support dedicated effort toward website management.  Or it can fade away, having performed well for 10 years in drawing attention to the value of hydrologic ensemble forecasting

“The future of hydrological forecasting is….”

Three main aspects are highlighted in the responses:

TECHNIQUES
  • ensemble forecasting
  • ensemble-based across all space-time scales
  • seamless ensemble forecasts covering short to extended range lead times
  • offering ensemble forecasts that seamlessly integrate over space (from sub-catchments to continents) and through lead-times (hours to years)
  • an Earth System that provides seamless predictions and integrates decision-making processes
  • made of probabilities and data assimilation
  • the correction of forecasting bias and errors
  • probabilistic, impact-based
  • based on multi-model / multi-system forecasting, and impact-based forecasting
  • in using alternative data sources and using sophisticated pre- and post-processors to improving ensemble forecasting
  • in combining information from many different (sometimes competitive) sources
SCIENCE
  • lies with more basic scientific understanding
  • understanding more sophisticated interaction between the atmosphere, rivers and humans
  • to integrate meteorology/climatology, hydrology, forecasting services and water management
  • on the one hand proposing scientific innovations that make sense for operations (not unrealistic/disconnected from operational constraints) and gradually including hydrological forecasting in a much broader perspective, or system approach, of integrated water resources management
  • bright if we a.) integrate hydrology even better within meteorological forecasting systems, and b.) make progress towards better understanding what a ‘useful’ degree of skill means in practice… e.g. is a forecast with a CRPSS of 0.06 useful and to whom in what situation?
  • somewhat linked to progresses in meteorological forecasting and remote sensing
  • to find its role in the next generation of high-resolution process-resolving NWP models
  • to provide consistency and knowledge as new coupling techniques are developed
  • There is now less research on improving the representation of hydrological processes but rather representing the uncertainty in their representation.
  • New research is toward extending the application of the forecast into estuary models, inundation maps, hydropower, infrastructure safety, etc.
COMMUNICATION AND NEW SYNERGIES
  • more reliable, and user friendly / automation
  • communication and interaction with social media / communicate probabilities
  • challenging / promising / very important due to climate change in the world
  • to find synergistic value from both ensemble systems and high resolution deterministic systems so that the field is not split into two camps, those that pursue resolution and complexity and those that try to quantify uncertainty
  • a rosy one, provided there are sufficient links between research advances and operational services and applications to improve water management
  • clouded because there is no clear leadership for the direction needed. The science is there, but policy needs to be established.

In summary…

This survey is the first step into a discussion that will certainly help us moving forward with updated goals to better tackle the main challenges the community face today, almost fifteen years after the first meeting that launched HEPEX as a novel experiment in the international hydrological sciences community.

A big “thank you” to all those who took their time to answer and participate!

If you have any additional comments, post them in the comment box below.

Survey organizers: Maria-Helena Ramos, Fredrik Wetterhall, Andy Wood, QJ Wang, Florian Pappenberger, Jan Verkade, Hannah Cloke, Ilias Pechlivanidis, and François Anctil.

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Hydrological forecasting, ensembles and related topics at AGU 2018: Time to write your abstracts

Contributed by Andy Wood and Flavio Lehner, NCAR 

You can help to advance the science of hydrological prediction, forecasting systems, and our understanding of the value of ensembles through the presentation of your recent related scientific and practical developments, applications and approaches at the AGU Fall Meeting in 2018.  The meeting will be held on December 10-14, 2018.

Why should I go to AGU next year?

  1. For once, AGU will be held in Washington D.C. instead of San Francisco. This is much closer than usual if I do not hail from the western U.S. or Pacific Rim countries — and D.C. is a remarkable, iconic city.
  2. AGU’s sessions on hydrologic forecasting and ensembles are trending up in quality and number
  3. HEPEXers always go out to socialize, which is obviously a lot of fun
  4. Where else can I just go check out some talks on tectonophysics or volcanology if my brain needs a break from hydrology? AGU is, as they say, ‘yuge’ … with cutting edge science, workshops, and other attractions.
  5. I suffer from FOMO and don’t want to take a chance on not being where the action is.

Important: Abstract submission deadline is 1 August 2018 23:59 EDT/03:59 +1 GMT.

Sessions

Hydrologic prediction and related sessions (where does one draw the line?) may be offered under a variety of different AGU Sections, including Hydrology, Global Environmental Change, Earth and Space Science Informatics, Atmospheric Sciences, and Natural Hazards among others. AGU also tries to help attendees find sessions using the concept of SWIRL (Sessions With Interdisciplinary Research Linkages) themes to “curate your experience at Fall Meeting”. There are even Scientific Neighborhoods to hang out in this year.

Although we can’t highlight all of the sessions or talks that could be of interest to the HEPEX community (and invite you to search the online program), the tables below include a number of sessions that are related to forecasting, climate and weather extremes, ensembles in various contexts, and hazard management.

In Hydrology, closest to home, sessions having to do with forecasting, prediction, floods, droughts, and ensembles include the following.

Session Title Summary
H005 Advances in Ensemble Flood Forecasting, Flood Estimation, and Risk Analysis Continuation of a long-running AGU HEPEX-themed session, this year focusing on ensemble hydro-meteorological forecasting to support short-term flood mitigation and long-term flood risk management. HEPEX conveners — Andy Wood, Marie-Amelie Boucher, Paulin Coulibaly.
H007 Advances in Integrated Observations, Modeling and Predictions for Weather, Climate, and Impact Assessments Uses of observations and models in addressing extreme hydrometeorological events, and developments of observational and information systems, and the integration of observations from various sources are of high interest.
H049 Drought Process and Prediction: Vulnerability, Hazard, and Risk All aspects of drought monitoring, diagnosis, and prediction, including the physical mechanisms, S2S predictability, probabilistic and deterministic drought recovery modeling and forecasting, drought variability, and diagnosis and attribution of drought risk. HEPEX conveners Hamid Moradkhani among others.
H057 Extreme Rainfall and Flooding: Monitoring, Forecasting, Risk Assessment, and Socioeconomic Consequences Past and prospective changes in intense rainfall and floods under environmental changes; predicting these events over short- to long-term periods; quantifying uncertainty/error in intense rainfall and flood prediction; case studies and risk assessment.
H062 Global Floods: Forecasting, Monitoring, Risk Assessment, and Socioeconomic Response Supports Global Flood Partnership (GFP) — global flood forecasting, monitoring and impact assessment; modeling and remote sensing, socioeconomic sciences, hazard response, and preparedness fields and risks
H092 New Methods for Hydrologic Drought Characterization, Prediction and Assessment Studies exploring the characterization and quantification of hydrologic drought and low streamflow in support of water resources management
H073 Hydrometeorological simulation and forecasting of atmospheric rivers and their impacts: Processes, simulations, and observations Forecasting and observing the impacts of ARs: coupled atmospheric-hydrologic modeling for streamflow prediction during ARs; impacts on water resources; forecast skill and predictability near real-time data assimilation and parameter estimation techniques to improve forecasts, and other topics
H105 Remote Sensing Applications for Water Resources Management, Including Droughts, Floods and Associated Water Cycle Extremes Use of satellite, airborne and ground-based sensor networks to: estimate hydrologic resources in the U.S. and internationally to improve water resources management; and support risk-based decision making. Topics: floods and droughts, water supply monitoring and forecasting; water balance and more …
H106 Research, Development and Evaluation of the National Water Model and Facilitation of Community Involvement Continental-scale hydrologic prediction related topics including remote sensing, data assimilation, anthropogenic effects, big data, decision support, calibration, machine learning, model testing and evaluation – and community involvement.
H132 Water and Society: Using Hydroclimatic Forecasts to Enhance Water Resources Decision-making Improving the use of forecast information through: improving relevance to decision makers, quantifying forecast uncertainty; integrating forecasts with users’ institutional settings; improving delivery technologies; and using forecasts for the operation of water systems. HEPEX convener Paul Block among others.
H139 Weather/Climate Ensembles and Downscaling Methodologies for Hydrologic Prediction Systems: Methods, Process Understanding, Applications and Verification Ensemble methods and downscaling of multi-model climate and weather projections and their relevance in improving hydrologic modeling and prediction across spatial and temporal scales. HEPEX convener Firas Saleh.

In Global Environmental Change and Atmospheric Science, several interesting sessions that focus on ensembles in the climate projection context are being offered, as well as sessions on weather and climate forecasting – here’s a sample.

GC039 Ensemble Modeling Approaches to Studying the Earth System Response to Anthropogenic Forcing Large Ensemble (LE) climate simulations with Earth System Models (ESMs) are now possible. Focus on ESM LE-related science and studies, including the role of internal climate variability in future projections – but also seeking perspectives from other ensemble-application communities (eg, HEPEX). Convener: Flavio Lehner
A065 Large Ensemble Climate Model Simulations: Exploring Natural Variability, Climate Change Signal, Extremes and Compound Events at various Spatio-Temporal Scales Using Large Ensembles (LEs) with Earth System Models or Regional Climate Models to assess the role of internal variability for future climate projections, including extreme events.
A048 Extreme Weather Events: Forecast skill, Uncertainty Quantification and Impact Modeling On the importance of statistical and dynamical ensembles in forecasting extreme events and the influence of forecast uncertainty on managing severe weather.
A097 Sub-seasonal to seasonal prediction of weather and climate Seasonal, and more recently also sub-seasonal (weeks 3-4) predictions: science and applications, for example in the water resource sector.

In Natural Hazards, a number of sessions relate to drought and flood modeling and monitoring, and management of extremes and related risks.

NH002 Advances in Drought Risk Management: Forecasting, Monitoring, Assessment, and Response Applications for managing drought risk, from drought forecasting to new response methods. Goal is to formulate future research prospects for the drought risk community.
NH020 Integrated Flood Modeling Integrative and inter-disciplinary science to tackle the physical, socio-economic, and managerial processes that determine the severity of a flood event.
NH030 Remote Sensing: Monitoring, Prediction, and Hazard Mitigation of Hydroclimatic Extreme Events Applications of remotely-sensed data for characterization and modeling of hydroclimatic extreme events.
NH031 Research, Risk Analysis, Monitoring, Forecasting, and Mitigation of Natural Hazards in a Dynamic, Changing World Integrative and inter-disciplinary session on natural hazards, spanning topics from current event attribution to vulnerability assessments to understanding of hydroclimate drivers and strategic responses to natural hazards.

This list is just a sample — you can search for other sessions by AGU Section here or by various search terms here.

Abstracts can be submitted here.  Hope to see many of you there!

Other Deadlines and Tips

  • A number of travel grants may be available, especially for students, with the earliest deadlines closing 8 August 2018.
  • Book hotels and flights early to get good rates.  The AGU website offers guidance and more information on venues, hotels, and local transportation.

If you don’t see your session listed and want to promote it, please include a title and link in the comment response to this blog post.

 

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Drought Monitoring and Prediction in South Asia

Contributed by:  Vimal Mishra* and Saran Aadhar, Civil Engineering, Indian Institute of Technology (IIT) Gandhinagar, India

Drought is one of the most complex natural disasters. In South Asia — a region including India, Pakistan, Bangladesh, Sri Lanka, Nepal, and Bhutan — increasing population, dependence on agriculture, and frequent droughts have resulted in water scarcity and food scarcity. In India, for example, about 330 million people were affected by the 2014-15 droughts, which led to severe water shortages (Mishra et al., 2016). Some of the detrimental impacts of droughts can be mitigated by proactive planning, including the monitoring and prediction of drought conditions. Real-time monitoring of drought conditions involves assessing the conditions of precipitation, evapotranspiration, soil moisture, runoff, and vegetation health. Providing information on the intensity and spatial extent of drought, and identification and prediction of onset and development of droughts can assist in proactive planning and decision-making by administrators, water managers, and farmers.

We have recently developed an ensemble-based drought monitoring and prediction system for South Asia, extending a prior Experimental Drought Monitor (Shah & Mishra, 2015) that was developed for India. The South Asia Drought Monitoring and Prediction System (Aadhar & Mishra, 2017) provides daily short-term forecasts (out to 15 days lead time) of precipitation, soil moisture, and runoff conditions, as well as associated drought indices: the standardized precipitation index (SPI), standardized soil moisture index (SSI) and standardized runoff index (SRI) reflecting meteorological, hydrological, and agricultural drought, respectively. A website for the drought monitoring and prediction system in South Asia provides online, real-time information from the system (examples shown in Figure 1).

Figure 1 – Examples of real-time drought products depicting conditions on 20th May 2018 and 7 and 15 day lead drought prediction in South Asia. Lower panels highlight the associated outcomes in terms of regions of drought persistence and recovery. More information can be obtained online (see South Asia Drought Monitor link below).

Drought Monitoring and Prediction System Components

The South Asia Drought Monitor uses retrospective daily precipitation data at 0.25 degree spatial resolution for the period of 1951-2007 from APHRODITE (Yatagai et al, 2012), which was developed for the Asian monsoon region using observation stations from different countries. For daily real-time precipitation forcing, the Tropical Rainfall Measurement Mission (TRMM) 3B42RT v7 precipitation data were used. Retrospective daily maximum and minimum temperature were obtained, also at 0.25 degree, from the Princeton University meteorological global dataset (Sheffield et al, 2006). Observed temperature data are not available in near-real time; therefore, we used daily maximum and minimum temperatures from the Global Ensemble Forecast System (GEFS) from 2006 onwards.

Meteorology from both TRMM and GEFS data were bias-corrected and applied to drive VIC model simulations from 1951 to the present, and through the forecast period. Validation of the drought monitoring and forecast products has also been conducted. For example, we compare the VIC model simulated (SSI and SRI) drought results with the Drought Severity Index (DSI). The DSI is the remotely sensed drought extent which is based on vegetation health, calculated using MODIS ET/PET and NDVI data for the vegetated land surface at 8-day, monthly, and yearly intervals. Figure 2 shows the VIC model simulated areal extents of drought for the 2002 monsoon season case, which revealed similar drought extents to those obtained from DSI estimates.

DSI.gif

Figure 2 – Comparison of drought indices from the VIC model simulation (drought monitor) with the DSI for the monsoon season drought in the year 2002. The area under the drought was estimated using DSI (Left), SRI (Middle), and SSI (Right).

Real-time meteorological forecasts from the Global Ensemble Forecast System (GEFS) reforecast were used to drive the medium range (7 to 15 –days) drought and downscaled precipitation forecast in South Asia. The GEFS reforecast is available at the spatial resolution of 1 degree at every 3-hour temporal resolution for 0 to 72 hours and 6-hour temporal resolution for 72 to 384 hours. We regridded the 1-degree daily precipitation, maximum (Tmax) and minimum (Tmin) temperatures to 0.25 degree. The GEFS reforecasts of precipitation and air temperatures data were used to forecast the hydrological variables (soil moisture and runoff) using the VIC model simulation. Shah et al. (2016; 2017) describe the skill of the soil moisture and runoff drought indices over India based on the GEFS forecast data. Currently, the South Asia Drought Monitoring and Prediction System also provides information in a form that supports a drought early warning system (DEWS), which compares current drought conditions with past (1-week, 1-month, 3-month, and 1-year) drought conditions for every South Asian country (Figure 3).

Figure 3 – Drought early warning system (DEWS) products for 20th May 2018 for South Asia, including the area (%) under drought of different severity categories. More information can be obtained online (see links below).

Comments, questions and feedback on the effort are welcome!

Contact:  Vimal Mishra — email vmishra@iitgn.ac.in or Twitter @vmishraiit

References

Aadhar, S., & Mishra, V. (2017). High-resolution near real-time drought monitoring in South Asia. Scientific Data, 4, 170145. Retrieved from http://dx.doi.org/10.1038/sdata.2017.145

Mishra, V., Aadhar, S., Asoka, A., Pai, S., & Kumar, R. (2016). On the frequency of the 2015 monsoon season drought in the Indo-Gangetic Plain. Geophysical Research Letters, 43(23), 12,102-12,112. https://doi.org/10.1002/2016GL071407

Shah, R., Sahai, A. K., & Mishra, V. (2016). Short-to-medium range hydrologic forecast to manage water and agricultural resources in India. Hydrology and Earth System Sciences Discussions, (October), 1–23. https://doi.org/10.5194/hess-2016-504

Shah, R., Sahai, A. K., & Mishra, V. (2017). Short to sub-seasonal hydrologic forecast to manage water and agricultural resources in India. Hydrology and Earth System Sciences, 21(2), 707–720. https://doi.org/10.5194/hess-21-707-2017

Shah, R. D., & Mishra, V. (2015). Development of an Experimental Near-Real-Time Drought Monitor for India. Journal of Hydrometeorology, 16(1), 327–345. https://doi.org/10.1175/JHM-D-14-0041.1

Sheffield, J., G. Goteti, and E. F. Wood, Development of a 50-yr high-resolution global dataset of meteorological forcings for land surface modeling, J. Climate, 19 (13), 3088-3111.

Yatagai, A., K. Kamiguchi, O. Arakawa, A. Hamada, N. Yasutomi, and A. Kitoh, 2012: APHRODITE: Constructing a Long-Term Daily Gridded Precipitation Dataset for Asia Based on a Dense Network of Rain Gauges. Bull. Amer. Meteor. Soc., 93, 1401–1415, https://doi.org/10.1175/BAMS-D-11-00122.1

Links:

South Asia Drought Monitor

Drought Early Warning System

 

 

Posted in disaster risk reduction, droughts, monitoring, operational systems | Leave a comment

10 years of the Sub-Division on Hydrological Forecasting at EGU (2008 – 2018)

Contributed by Maria-Helena Ramos and Femke Davids

The field of Hydrological Forecasting has grown over the last ten years into an interesting and thought-provoking sub-division to the European Geosciences Union (EGU). Through this sub-division, at one of the largest Geoscience conferences in the world, we address many challenges that today’s hydrologists, and also users and decision-makers in the water sector, have to deal with. Below you will find an interesting read into the background and history of this field at EGU.

This week the call-for-sessions has opened for the program of EGU 2019. The procedure for bringing in new sessions is different. The organizers of EGU2019 want to create an opportunity for a more bottom-up approach of conference sessions. Anyone, not only existing conveners, can upload a session to the proposed program. The aim is to create a diverse program with unique sessions.Check here for guidelines.

The chairs of the sub-divisions and main division on Hydrological Sciences will coordinate and adjust the proposed sessions when necessary into an aligned program. In case of overlap of sessions proposed, conveners will be contacted and might have to make changes. We suggest contacting the chair of the Hydrological Forecasting sub-division (Femke Davids) about your idea for a new session and how it would fit under the existing structure of the sub-division, which currently is:

HS4 – Hydrological Forecasting

  • HS4.1 – Forecasting hydrological extremes: (flash) floods, droughts and water scarcity
  • HS4.2 – Improving and quantifying forecasting methodologies and uncertainties
  • HS4.3 – Operational and impact forecasting, preparedness and decision making

Note that when proposing and uploading a session the following rules apply:

  • You can only be main convener for one session at EGU
  • You can be involved as a convener (main and/or co-) for a maximum of 3 sessions in total
  • The number of conveners for a session is limited between 2 minimum and 5 maximum (incl. main convener)
  • (co-)conveners should not have a solicited presentation, or be a presenting author in their own sessions

The public call-for-sessions for EGU 2019 (here) is open from 25th June to 13th Sep 2018.

Are you curious to learn more about the sub-division? Check below its history.

History of the sub-division on Hydrological forecasting at EGU

Back to EGU 2006, there were no sessions directly related (or explicitly devoted) to hydrological forecasting in the Hydrological Sciences (HS) Division programme.

In the EGU 2007 programme, two sessions related to forecasting are co-listed in the HS programme. They were mainly organized by the Natural Hazards (NH) Division. Other forecasting-related sessions were organized in the NH Division, but not co-listed in HS. At this time, the HS Division is not yet structured in sub-divisions. The two sessions co-listed in the 2007 programme were focused on new science and operations related to flash floods. HEPEX appears as one specific session in the programme, convened by Gabor Balint (Vituki, Hungary) and Jutta Thielen (JRC, Italy):

  • NP5.05: Ensemble prediction in hydrology (HEPEX) (co-listed in HS & NH), Convener: Balint, G., Co-Convener: Thielen, J.
  • NH2.02: Operational tools for flash-flood forecasting (co-listed in HS), Convener: Aronica, G., Co-Convener: Borga, M., Moore, R., Mancini, M.

A year later, at EGU 2008, the HS Division starts to be structured in sub-divisions (SD). There were 10 thematic SDs, plus 2 general SDs listed. The SD on Hydrological Forecasting is HS3. Jan Szolgay is the chair of the sub-division, responsible for the organization of its programme during the period running from 2008 to 2011.

In 2008, the final programme included 3 main sessions, plus 1 co-organized. The topics are expanded to explicitly cover specific challenges such as data assimilation and uncertainty quantification. The Flash floods session is complemented with a session focusing on medium to long range forecasting for water management. Operational systems are included, with a session that calls attention to real-world case studies and covers the local, regional and national scales (at that time, we are not yet talking about continental or global scales in hydrological forecasting):

  • HS3.1: Predictive probability, uncertainty and data assimilation in hydrological forecasting, Convener: Moore, R., Co-Convener: Todini, E., Loukas, A., Madsen, H., Thielen-del Pozo, J.
  • HS3.3: Medium and long-term hydrological forecasting for water management and water allocation, Convener: Toth, E., Co-Convener: Aronica, G., Butts, M., Loukas, A.
  • HS3.4: Local, regional and national hydrological forecasting systems. Real-world case studies (Hydrological Forecasting Open Session), Convener: Balint, G., Co-Convener: Blöschl, G., Reggiani, P., Szolgay, J.
  • IS31 – NH2.5/AS4.02/HS3.5: Flash floods: observations and analysis of atmospheric and hydrological controls (co-organized by NH, AS & HS), Convener: Borga, M., Co-Convener: Price, C., Szolgay, J., Mugnai, A.

In EGU 2009, a major change appears in the way the programme is presented in the EGU website, reflecting how the community is growing fast. The HS Division lists 13 sub-divisions. Hydrological forecasting is sub-division HS10. It has grown now to include 5 main sessions. The Flash floods session is now mainly organized by the HS Division. Ensemble forecasting appears again as a separate session. The operational session is now focused on hydrological models and methods for forecasting systems:

  • HS10.1/AS4.3/NP5.4: Ensemble hydrological forecasting: from theory to practice (co-organized), Convener: Prof. Ranzi  | Co-Convener: F Pappenberger
  • HS10.2/NH2.5: Flash flood events: observations, processes and forecasting (co-organized), Convener: M. Borga  | Co-Conveners: G. T. Aronica, G. Blöschl, J. Szolgay, R. Weingartner
  • HS10.3: Uncertainty and data assimilation in hydrological forecasting, Convener: R. J. Moore  | Co-Convener: H. Madsen
  • HS10.4: Medium and long-term hydrological forecasting for water management and allocation, Convener: A. Loukas  | Co-Conveners: E. Toth, G. T. Aronica
  • HS10.5: Hydrological models and methods in operational forecasting systems, Co-Conveners: Butts, J. Danhelka, J. Szolgay, G. Blöschl

In the EGU 2010 programme, the sub-division on Hydrological forecasting is listed as HS11, with 5 sessions. They are now organized slightly different. Two novelties are the inclusion of decision-making and a focus on monitoring and forecasting water scarcity conditions. Additionally, the SD has the honour to host the “Outstanding Young Scientist Lecture”, by Jasper A. Vrugt:

  • HS11.1/AS4.4/NH1.13: Flash floods: Observations, modelling, forecasting and impacts (co-organized), Convener: Marco Borga  | Co-Conveners: Jan Szolgay, Rolf Weingartner, Giuseppe Tito Aronica, Günter Blöschl
  • HS11.2: Hydrological forecasting systems: Models and methods in operational application, Co-Conveners: Jan Szolgay, Günter Blöschl, Michael Butts, Jan Danhelka, Vadim Kuzmin
  • HS11.3: Uncertainty, data assimilation and decision-making in hydrological forecasting (including Outstanding Young Scientist Lecture; Jasper A. Vrugt), Convener: Robert Moore  | Co-Conveners: Henrik Madsen, Ezio Todini
  • HS11.4/AS1.22/NH1.12: Towards practical applications in ensemble hydro-meteorological forecasting (co-organized), Convener: Yi He  | Co-Conveners: Florian Pappenberger, Albrecht Weerts, Michael Bruen, Maria-Helena Ramos
  • HS11.5: Hydrological monitoring and forecasting of water scarcity conditions, Convener: Elena Toth  | Co-Conveners: Athanasios Loukas, Giuseppe Tito Aronica

For EGU 2011, the SD Hydrological forecasting is HS4. It has 4 sessions, with the session on hydrological models and operations joining the session on uncertainty, data assimilation and decision-making. For a consecutive year, it has the honour to host an awarded lecture, the “Arne Richter Award for Outstanding Young Scientists Lecture”, by Florian Pappenberger:

  • HS4.1/NH1.11: Flash floods: observations, modeling, forecasting and risk management (co-organized), Convener: Marco Borga  | Co-Conveners: Jan Szolgay, Giuseppe Tito Aronica, Günter Blöschl, Eric Gaume
  • HS4.2: Hydrological forecasting: application, uncertainty estimation, data assimilation and decision-making, Convener: Robert Moore  | Co-Conveners: Günter Blöschl, Vadim Kuzmin, Henrik Madsen, Jan Szolgay, Albrecht Weerts
  • HS4.3/AS4.13/NH1.12: Towards practical applications in ensemble hydro-meteorological forecasting (including Arne Richter Award for Outstanding Young Scientists Lecture; Florian Pappenberger) (co-organized), Convener: Maria-Helena Ramos  | Co-Conveners: Florian Pappenberger, Albrecht Weerts, Yi He
  • HS4.5: Drought and water scarcity: hydrological monitoring, modeling and forecasting, Convener: Elena Toth  | Co-Conveners: Athanasios Loukas , Giuseppe Tito Aronica

By EGU 2012, HS4 on Hydrological forecasting becomes a well-established sub-division, covering a wide range of topics.

The new SD chair, proposed during the SD meeting held in Vienna in 2011, is Elena Toth. She will be responsible for the organization of the sub-division programme during the next 4-year period, starting in 2012 and up to the 2015 programme. Later, she will be elected for the presidency of the HS Division, in the EGU autumn 2014 elections.

In 2012, HS4 has 5 sessions in its programme, including a new session on the value of forecasts for society, policy and decision-making:

  • HS4.1/GM7.8/NH1.7: Flash floods: processes, forecasting and risk management (co-organized), Convener: M. Borga  | Co-Conveners: G. T. Aronica, G. Blöschl, J. Szolgay, J. J. Gourley
  • HS4.2: Hydrological forecasting: challenges in uncertainty estimation, data assimilation, post-processing, real-time control and decision-making, Convener: R. J. Moore | Co-Conveners: A.H. Weerts, N. Voisin, H.-J. Hendricks Franssen, D. Schwanenberg
  • HS4.3/AS1.18/NH1.2: Ensemble hydro-meteorological forecasting for improved risk management: across scales and applications (co-organized), Convener: M.-H. Ramos  | Co-Conveners: F Pappenberger, J.D. Brown, S. J. van Andel, Y. He, G. Mascaro
  • HS4.4: Drought and water scarcity: hydrological monitoring, modeling and forecasting, Convener: E. Toth  | Co-Conveners: G. T. Aronica, J.V. Vogt, A. Loukas
  • HS4.6: Why predict? The value of prediction in hydrological sciences and policy, Convener: J.S. Verkade  | Co-Conveners: A. Iglesias, H. Winsemius

The sub-division programme for EGU 2013 is very much similar to the one in the previous year, with some modifications in the titles and scope of the sessions. The HS Division lists 12 sub-divisions, amongst which Hydrological forecasting (HS4) with 5 sessions:

  • HS4.1/AS1.21/GM7.6/NH1.7: Flash floods: from observations to risk governance (co-organized), Convener: Marco Borga  | Co-Conveners: Eric Gaume, Jan Szolgay, Giuseppe Tito Aronica, Jonathan Gourley, Günter Blöschl
  • HS4.2: Hydrological forecasting: challenges in uncertainty estimation, data assimilation, post-processing and decision-making, Convener: Robert Moore  | Co-Conveners: Albrecht Weerts, Henrik Madsen
  • HS4.3/AS4.20/NH1.13: Ensemble hydro-meteorological forecasting for improved risk management: across scales and applications (co-organized), Convener: Schalk Jan van Andel  | Co-Conveners: Florian Pappenberger, Yi He, Maria-Helena Ramos
  • HS4.4: Drought and water scarcity: hydrological monitoring, modelling and forecasting to improve water management, Convener: Jürgen Vogt  | Co-Conveners: Elena Toth, Micha Werner, Giuseppe Tito Aronica, Athanasios Loukas
  • HS4.5: Hydrology for decision-making: the value of forecasts, predictions, scenarios, outlooks and foresights, Convener: Jan Verkade  | Co-Conveners: Hessel Winsemius, Ana Iglesias

A similar situation is found at the EGU 2014 General Assembly (GA): the Hydrological forecasting sub-division (HS4) organizes 5 main sessions:

  • HS4.1/AS4.18/GM7.14/NH1.7: Flash floods and associated hazards: monitoring, forecasting, preparedness and coping strategies (co-organized), Convener: Marco Borga  | Co-Conveners: Eric Gaume, Jonathan Gourley, Giuseppe Tito Aronica, Emmanouil Anagnostou, Massimiliano Zappa
  • HS4.2: Hydrological forecasting: Untangling and reducing predictive uncertainty through improved model process description, data assimilation and post-processing, Convener: Robert Moore  | Co-Conveners: Henrik Madsen, Albrecht Weerts
  • HS4.3/AS1.17/NH1.10: Ensemble hydro-meteorological forecasting (co-organized), Convener: Schalk Jan van Andel  | Co-Conveners: Maria-Helena Ramos, Sara Liguori, Florian Pappenberger, Yi He, Ronald Hutjes
  • HS4.4: Drought and water scarcity: hydrological monitoring, modelling and forecasting to improve water management, Convener: Jürgen Vogt  | Co-Conveners: Athanasios Loukas, Elena Toth, Micha Werner, Brunella Bonaccorso
  • HS4.5: Hydrology for decision-making: the value of forecasts, predictions, scenarios, outlooks and foresights, Convener: Jan Verkade  | Co-Conveners: Hessel Winsemius, Ana Iglesias

At the EGU 2015 GA, the sub-division introduces the PICO sessions in its programme. PICOS were first introduced at the GA in 2013. The PICO format seems to be very suitable for demonstrating operational forecasting systems and case studies. This first time is already a success for the operational forecasting session, with 25 presentations scheduled.

In 2015, the Hydrological forecasting SD (HS4) proposes 5 main sessions, plus 1 co-listed with the Climate (CL) division (where the notion of impact models is explicitly addressed):

  • HS4.1/AS1.22/GM7.12/NH1.10: Flash floods, hydro-geomorphic response, forecasting and risk management (co-organized), Convener: Isabelle Braud  | Co-Conveners: Marco Borga, Marcel Hürlimann, Massimiliano Zappa, Francesc Gallart, Jonathan Gourley
  • HS4.2: Hydrological forecasting: Untangling and reducing predictive uncertainty through improved model process description, data assimilation and post-processing PICO Session; Convener: Robert Moore  | Co-Conveners: Henrik Madsen, Albrecht Weerts
  • HS4.3/AS1.3/NH1.3: Ensemble hydro-meteorological forecasting (co-organized), Conveners: Sara Liguori , Maria-Helena Ramos  | Co-Conveners: Florian Pappenberger, Schalk Jan van Andel, Giovanni Battista Chirico
  • HS4.4: Drought and water scarcity: hydrological monitoring, modelling and forecasting to improve water management, Convener: Jürgen Vogt  | Co-Conveners: Athanasios Loukas, Elena Toth, Micha Werner, Brunella Bonaccorso
  • HS4.6/NH1.2: Operational forecasting and warning systems for natural hazards: challenges and innovation (co-organized) PICO Session, Convener: Femke Davids  | Co-Conveners: Jan Verkade, Michael Cranston, Jan Szolgay
  • CL5.5/CR3.7/HS4.8/SSS12.14: Linkages between climate and impact models: methodological challenges to serve contextual demands (co-organized), Convener: Ole Rössler  | Co-Conveners: Andreas Fischer, Sven Kotlarski, Renate Wilcke, Annelie Holzkämper, Nadine Salzmann

In EGU 2016, the sub-division on Hydrological forecasting (HS4) has a new chair, Maria-Helena Ramos. She is appointed to be responsible for the sub-division programme from 2016 to 2019. Later, she will be elected president of the HS Division, in the EGU autumn 2017 elections, and step down from the SD HS4 chair after the EGU GA in April 2018.

In 2016, HS4 has 6 main sessions, plus 2 co-listed. New contributors keep joining the programme group as co-conveners, including several early career scientists:

  • HS4.1/AS4.30/GM9.12/NH1.7: Flash floods and associated hydro-geomorphic processes: observation, modelling and warning (co-organized), Convener: Isabelle Braud  | Co-Conveners: Marcel Hürlimann, Marco Borga, Jonathan Gourley, Jose Agustin Brena Naranjo, Massimiliano Zappa
  • HS4.2/NH1.18: Predictability and predictive uncertainty estimation in hydrologic forecasting (co-organized), Convener: Albrecht Weerts  | Co-Conveners: Henrik Madsen, Giovanni Battista Chirico, Rodolfo Alvarado Montero, Oldrich Rakovec, Joshua K. Roundy
  • HS4.3/AS4.31/NH1.9: Ensemble hydro-meteorological forecasting (co-organized), Convener: Fredrik Wetterhall  | Co-Conveners: Schalk Jan van Andel, Maria-Helena Ramos, Kolbjorn Engeland, Rodrigo Paiva, Jan Verkade
  • HS4.4: Drought and water scarcity: monitoring, modelling and forecasting to improve hydro-meteorological risk management, Convener: Jürgen Vogt  | Co-Conveners: Athanasios Loukas, Elena Toth, Micha Werner, Brunella Bonaccorso, Christel Prudhomme
  • HS4.5/NH1.10: Operational forecasting and warning systems for natural hazards: challenges and innovation (co-organized) PICO Session, Convener: Femke Davids  | Co-Conveners: Jan Szolgay, Michael Cranston, Ilias Pechlivanidis
  • HS4.8/CL3.10: Servicing Water Users by forecasting, outlooks and climate projections for water services (co-organized), Convener: Bart van den Hurk  | Co-Conveners: Johannes Hunink, Henning Rust, Tim aus der Beek, Florian Pappenberger, Christopher White, Andrew W. Robertson, Louise Crochemore
  • NH1.6/AS1.4/HS4.9: Coupled atmosphere-hydrological modeling for improved hydro-meteorological predictions (co-organized), Convener: Harald Kunstmann  | Co-Conveners: Alfonso Senatore, D. Gochis, Francesca Viterbo
  • NP5.2/AS1.2/HS4.10: Advances in statistical post-processing for deterministic and ensemble forecasts (co-organized), Convener: Stéphane Vannitsem  | Co-Conveners: Jakob W. Messner, Daniel S. Wilks

In EGU 2017, the programme of the SD is very similar to the previous year. The SD Hydrological forecasting (HS4) has 6 main sessions, plus 2 co-listed. The novelty this year is a Short course on Hydrological Forecasting, co-organized with the general sub-division of HS and the Early Career Scientists programme (SC52/HS12.5). It was convened by Shaun Harrigan, and co-convened by Marie-Amélie Boucher and Jan Verkade (lecturers) and Maria-Helena Ramos.

  • HS4.1/AS4.35/GM9.11/NH1.10: Flash floods and associated hydro-geomorphic processes: observation, modelling and warning (co-organized), Convener: Isabelle Braud  | Co-Conveners: Marcel Hürlimann, Marco Borga, Jonathan Gourley, Massimiliano Zappa, Jose Agustin Brena Naranjo
  • HS4.2/NH1.11: Predictability, predictive uncertainty estimation and decision-making in hydrologic forecasting (co-organized), Convener: Albrecht Weerts  | Co-Conveners: Henrik Madsen, Giovanni Battista Chirico, Oldrich Rakovec, Rodolfo Alvarado Montero, Joshua K. Roundy, Hamid Moradkhani, Jan Verkade
  • HS4.3/AS4.36/NH1.12: Ensemble hydro-meteorological forecasting (co-organized), Convener: Fredrik Wetterhall  | Co-Conveners: Schalk Jan van Andel, Maria-Helena Ramos, Jan Verkade, Kolbjorn Engeland, Rodrigo Paiva, Tomasz Niedzielski
  • HS4.4: Drought and water scarcity: monitoring, modelling and forecasting to improve hydro-meteorological risk management, Convener: Brunella Bonaccorso  | Co-Conveners: Athanasios Loukas, Christel Prudhomme, Micha Werner, Jürgen Vogt
  • HS4.5/NH1.13: Operational forecasting and warning systems for natural hazards: challenges and innovation (co-organized) PICO session, Convener: Femke Davids  | Co-Conveners: Jan Szolgay, Michael Cranston, Ilias Pechlivanidis
  • HS4.6/CL3.02: From sub-seasonal forecasting to climate projections: predicting hydrologic extremes and servicing water managers (co-organized), Convener: Louise Crochemore  | Co-Conveners: Henning Rust, Christopher White, Johannes Hunink, Tim aus der Beek, Bart van den Hurk, Christel Prudhomme
  • NP5.3/AS1.2/HS4.8: Advances in statistical post-processing for deterministic and ensemble forecasts (co-organized), Convener: Stéphane Vannitsem  | Co-Conveners: Jakob W. Messner, Daniel S. Wilks
  • NH1.6/AS1.4/HS4.9: Coupled atmosphere-hydrological modeling for improved hydro-meteorological predictions (co-organized), Convener: Harald Kunstmann  | Co-Conveners: Alfonso Senatore, D. Gochis , Francesca Viterbo

At the last GA, EGU 2018, the the final programme of the SD on Hydrological forecasting (HS4) has 5 main sessions, plus 1 co-listed, after a final merging of the predictive uncertainty and the ensemble prediction sessions:

  • HS4.1/AS4.27/GM8.7/NH1.11: Flash floods and associated hydro-geomorphic processes: observation, modelling and warning (co-organized), Convener: Isabelle Braud  | Co-Conveners: Marcel Hürlimann, Marco Borga, Jonathan Gourley, Massimiliano Zappa, Jose Agustin Brena Naranjo
  • HS4.3/AS1.10/NH1.13: Ensemble hydro-meteorological forecasting and predictive uncertainty estimation (co-organized), Convener: Fredrik Wetterhall  | Co-Conveners: Tomasz Niedzielski, Maria-Helena Ramos, Jan Verkade, Kolbjorn Engeland, Rebecca Emerton, Oldrich Rakovec, Joshua K. Roundy, Albrecht Weerts
  • HS4.4 Media: Drought and water scarcity: monitoring, modelling and forecasting to improve hydro-meteorological risk management, Convener: Brunella Bonaccorso  | Co-Conveners: Athanasios Loukas, Christel Prudhomme, Micha Werner, Carmelo Cammalleri
  • HS4.5/NH1.14: Operational forecasting and warning systems for natural hazards: challenges and innovation (co-organized)PICO session, Convener: Michael Cranston  | Co-Conveners: Ilias Pechlivanidis, Femke Davids, Gabriela Guimarães Nobre, Konstantinos Bischiniotis, Liz Stephens
  • HS4.6/CL3.13: From sub-seasonal forecasting to climate projections: predicting hydrologic extremes and servicing water managers (co-organized), Convener: Louise Crochemore  | Co-Conveners: Henning Rust, Bart van den Hurk, Christopher White, Johannes Hunink, Tim aus der Beek, Louise Arnal
  • NP5.3/AS1.5/HS4.8: Advances in statistical post-processing for deterministic and ensemble forecasts (co-organized), Convener: Stéphane Vannitsem  | Co-Conveners: Jakob W. Messner, Daniel S. Wilks

In April 2018, in consultation with the SD conveners, Femke Davids is appointed to become the new chair of the sub-division for the programmes covering the period from 2019 to 2022.

On average, 170 abstracts have been presented per year in the SD Hydrological Forecasting programme in the past years. We thank all the contributors that helped to shape and organize the Sub-Division on Hydrological Forecasting, including chairs, conveners and presenters of oral, poster and PICO presentations. We hope that this enthusiastic group will continue pushing forward the limits of science and operations in hydrological forecasting. We expect new ideas and collaborations to emerge in the next years.

If you want to contribute, keep an eye on the EGU 2019 website and join us in the phases of preparation of the next programme (the public call-for-session-proposals is now open) and submission of abstracts (which will be open from Oct 2018 until 10 Jan 2019).

And if we missed or misinterpreted any details on the history of the sub-division, please let us know using the comment box below.

Posted in announcements-events, historical | Leave a comment

Skilful seasonal forecasts of streamflow over Europe?

Contributed by Louise Arnal, University of Reading & ECMWF

Editor’s Note: Don’t miss the brilliant cartoon summary at the bottom of this post!

Over recent decades, seasonal streamflow forecasting methods have evolved and diversified, reflecting changes in our scientific understanding of streamflow predictability on seasonal timescales and our increasing computer power. The first operational model-based ensemble seasonal streamflow forecast, called the ESP1,2 (ensemble streamflow prediction), relies on the correct knowledge of the initial hydrological conditions (IHC; i.e. of snowpack, soil moisture, streamflow and reservoir levels, etc.) and a large land surface memory, and contains no information on the future climate (if you’d like to know more about the ESP, I recommend reading this very good HEPEX blog post about it!).

In basins where the meteorological forcings drive the streamflow predictability however, this last point is a limitation of the ESP. This motivates the use of seasonal climate forecasts to feed hydrological models and extend the predictability of hydrological variables on seasonal timescales3, which we refer to as climate-model-based seasonal streamflow forecasts (CM-SSF). While studies exploring the skill of CM-SSF are abundant outside of Europe, they are still relatively scarce in this part of the world, partly due to the limited quality of seasonal climate forecasts (particularly for the variables of interest to hydrology: precipitation and temperature) for the extra-tropics.

In our recent paper, published in the HESS special issue on Sub-seasonal to seasonal hydrological forecasting, we carried out a Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) CM-SSF (produced using the raw ECMWF System 4 seasonal climate forecast [Sys4] as an input to the Lisflood hydrological model), benchmarked against the ESP (produced using historical meteorological observations as an input to Lisflood; both forecasts go out to 7 months lead time). Below are the two main questions tackled in this paper.

C:\Users\sd869122\Documents\conferences&co\EGU 2018\photos\Louise A\IMG-20180409-WA0006.jpg

Louise presenting results from this paper at EGU 2018.

Does seasonal climate information improve the predictability of seasonal streamflow over Europe?

Overall, we found that Sys4 improves the predictability over historical meteorological information for pan-European seasonal streamflow forecasting for the first month of lead time only (in terms of accuracy, sharpness and overall performance). This shows the importance of the IHC and the land surface memory for seasonal streamflow forecasting in Europe. However, the predictability varies per season and we show that the CM-SSF is more skilful at predicting autumn and winter streamflows than for the spring and summer.

Our findings suggest that patterns in the CM-SSF skill are not mirrored in the Sys4 precipitation and temperature hindcasts, which calls for a more in depth look into the link between meteorological and hydrological variables on seasonal timescales over Europe.

What is the potential usefulness of the EFAS seasonal streamflow forecasts for flood preparedness?

As the quality of seasonal streamflow forecasts increases, their usability for decision-making has lagged behind. Translating forecast quality into added value for decision-making is not straightforward for short-range forecasting, let alone on seasonal timescales. While this has been explored for many water-related applications, such as navigation4, reservoir management5, water resource management6 and hydropower7, among others, seasonal streamflow forecasts have yet to be adopted by the flood preparedness community. In this paper, we additionally investigated the ability of the CM-SSF and the ESP to predict lower and higher than normal streamflow conditions up to 7 months ahead, which we term potential usefulness.

Here, we show results for higher than normal streamflows only (see the figure below); results for lower than normal streamflows can be found in the paper. Overall, we found that at least one of the two forecasting systems is capable of predicting higher than normal streamflows months in advance, with the ESP the most potentially useful system generally. However, our results suggest that the CM-SSF is more potentially useful than the ESP beyond 1 month of lead time for certain European regions and seasons, noticeably in winter for ~40 % of Europe.

Following the Red Cross Red Crescent Climate Centre Ready-Set-Go! approach8, seasonal streamflow forecasts could complement existing forecasts at shorter timescales and provide monitoring and early-warning information for flood preparedness.

Maps of the most potentially useful forecasting system (based on its ability to predict higher than normal streamflows, as measured with the ROC score) for all four seasons. The pie charts (also known as camembert plots in France!) display the ‘best’ system for each lead time (i.e. 1 to 7 months), as shown in the example pie chart. There are three possible cases: (1) neither the ESP nor the CM-SSF is potentially useful (red), (2) the ESP is potentially useful and better than the CM-SSF (yellow), or (3) the CM-SSF is potentially useful and better than the ESP (blue).

If you’d like to know more about this research, you can read the full paper here.

And if you’ve always wondered what a paper would be like if it was written as a cartoon with superheroes, check out the cartoon I made to summarise this paper!

C:\Users\sd869122\Documents\sciart projects\paper#3\comic_2.png

References:

1Twedt, T. M., Schaake, J. C., and Peck, E. L.: National Weather Service extended streamflow prediction, Proceedings Western Snow Conference, Albuquerque, New Mexico, 52–57, April 1977.

2Day, G. N.: Extended streamflow forecasting using NWSRFS, J. Water Res. Plan. Man., 111, 157–170, https://doi.org/10.1061/(ASCE)0733-9496(1985)111:2(157), 1985.

3Pagano, T. C. and Garen, D. C.: Integration of climate information and forecasts into western US water supply forecasts, Climate variations, climate change, and water resources engineering, edited by: Garbrecht, J. D. and Piechota, T. C., American Society of Civil Engineers location, Reston, Virginia, US, 86– 103, 2006.

4Meißner, D., Klein, B., and Ionita, M.: Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe, Hydrol. Earth Syst. Sci., 21, 6401–6423, https://doi.org/10.5194/hess-21-6401-2017, 2017.

5Turner, S. W. D., Bennett, J. C., Robertson, D. E., and Galelli, S.: Complex relationship between seasonal streamflow forecast skill and value in reservoir operations, Hydrol. Earth Syst. Sci., 21, 4841–4859, https://doi.org/10.5194/hess-21-4841-2017, 2017.

6Schepen, A., Zhao, T., Wang, Q. J., Zhou, S., and Feikema, P.: Optimising seasonal streamflow forecast lead time for operational decision making in Australia, Hydrol. Earth Syst. Sci., 20, 4117– 4128, https://doi.org/10.5194/hess-20-4117-2016, 2016.

7Hamlet, A. F., Huppert, D., and Lettenmaier, D. P.: Economic Value of Long-Lead Streamflow Forecasts for Columbia River Hydropower, J. Water Res. Plan. Man., 128, 91–101, https://doi.org/10.1061/(ASCE)0733-9496(2002)128:2(91), 2002.

8White, C. J. et al.: Potential applications of subseasonal-to-seasonal (S2S) predictions, Meteorol. Appl., 24, 315–325, https://doi.org/10.1002/met.1654, 2017.

 

Posted in decision making, ensemble techniques, forecast techniques, operational systems, seasonal prediction, verification | Leave a comment

Workshop Summary: Hydrological Services for Business

contributed by Shaun Harrigan, ECMWF

Over 60 participants ranging from consultancy companies, hydro-meteorological services, (re)insurance, and academia were welcomed at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, UK from the 8th to 9th of May 2018 to meet with the Global Flood Awareness System (GloFAS) development team. They were provided the opportunity to shape the future of GloFAS forecasting products and service provision. GloFAS is part of the Copernicus Emergency Management Service.

Participants at the ‘Hydrological Services for Business’ workshop at ECMWF in Reading 8th to 9th May 2018; Photo by ECMWF

The first session introduced GloFAS and the need for a global hydrological service. Peter Salamon from the European Commission Joint Research Centre (JRC) kicked off proceedings giving an overview of the Copernicus Emergency Management Service in providing hazard information for improved disaster management in Europe. David Green from NASA put forward the case that hydrological services are critical for global businesses by reducing risk and building resilience. Sazzard Hossain, Marcio Moraes, and Anshul Agarwal presented case study applications of GloFAS for flood forecasting in Bangladesh, Brazil, and Myanmar, respectively.

In the second session Catalina Jamie from the Red Cross Red Crescent Climate Centre showed the importance of hydrological services in the humanitarian sector for providing forecast-based financing allowing action before a disaster happens. John Bevington from JBA Consulting demonstrated that innovative products can be produced by combining raw GloFAS output with flood hazard maps via their Flood Foresight service.

Participants defining what makes a good global hydrological service and discussing the barriers of service uptake. Photo by ECMWF.

Plenty of lively discussion at the poster session. Photo by Hannah Cloke.

Participants got a chance to provide input during an interactive session on defining the most important criteria for a good global hydrological service. Common feedback included provision of information in regions lacking data and scientific capacity in order to aid local decision making; information on quality of forecasts (skill, accuracy, reliability) and associated documentation; service reliability; and availability of training material. Identified key barriers of service uptake included a perceived/actual lack of skill in the service in the region of interest; lack of access to discharge observations in many parts of the globe to allow model calibration and forecast evaluation; and managing the volume and complexity of forecast data.

The interactive participation continued with 3 minute ‘ignite’ talks ranging from Jan Verkade on the Deltares GLOSSIS system for storm surge forecasting, Matteo DallAmico on ‘mysnowmaps.com’, to Andy Wood highlighting hydrological prediction developments at NCAR. There were lively discussions and networking at the evening poster session.

Plenty of lively discussion at the poster session. Photo by Hannah Cloke.

 

Christel Prudhomme from ECMWF kicking off the interactive session on shaping the future of GloFAS. Photo by Hannah Cloke.

Day 2 turned towards how users can help shape future products and service provision of GloFAS. Arthur Essenfelder from the Euro-Mediterranean Centre on Climate Change (CMCC) talked on the importance of co-development between service providers and end users using climate services as an example. This provided fodder for the second interactive session where participants provided their input on improving current products (i.e. 30-day flood and seasonal forecasts) and shaping the development of future products (i.e. weekly forecast summary and rapid flood risk assessment).

 

The final session concentrated on how to improve service provision to end users. Carlo Buontempo from ECMWF showed how large complex datasets are made easily accessible to a variety of end users within the Copernicus Climate Change Service (C3S) Climate Data Store (CDS) together with an online interactive toolbox for retrieving, analysing and plotting data (will go live later in June). Jim Nelson from Brigham Young University (BYU) showed how tailor-made GloFAS forecasts at smaller spatial scales can be provided to the community and presented the infrastructure that enables a service to deliver local access to global forecast data. The session finished by asking users to describe their workflows in regards to obtaining forecast information through ‘user stories’. This feedback will be used to prioritise future GloFAS service developments with the aim to better accommodate user needs.

Peter Salamon closed the workshop and thanked the speakers and participants for their enthusiastic participation and valuable feedback during the interactive sessions that will help prioritise developments and shape the future of GloFAS. Workshop presentations are available online here.

An optional GloFAS training session took place after the workshop which included many hands-on exercises for participants to discover the different products and how they could be used for decision-making.

GloFAS training given by Ruth Coughlan, ECMWF. Photo by Louise Arnal.

About GloFAS

GloFAS went fully operational as a 24/7 supported service on the 23rd of April 2018. GloFAS is part of the Copernicus Emergency Management Service and provides forecasts of floods up to 30 days ahead as well as outlooks of high and low flows up to 4 month ahead in rivers across the world. GloFAS has currently over 1,600 registered users. Its forecasts are freely available to all users and can be accessed here.

 

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Risk Communication for Cyclone Early Warning – Do people get the message, and understand what it means for them?

Contributed by Bapon Fakhruddin, Senior DRR and Climate Resilience Specialist, Tonkin+Taylor & Co-chair of the Risk Interpretation and Application of IRDR/ICSU

Every year, New Zealand is impacted by ex-tropical cyclones (ETCs) – typically, one ETC makes landfall per year, between the months of November and April. As tropical cyclones approach New Zealand, they begin to lose their strength and undergo extratropical transition (ETT). Some of these weather systems are as large as New Zealand’s North Island when considering the full diameter of the storm, and ETCs can still induce heavy rainfall as well as strong mean winds and wind gusts, coupled with an increased forward motion, making them just as much of a hazard as tropical systems. ETCs have impacted New Zealand in the past (Cyclone Cook, Pam, Victor, Drena, Fergus, etc.) and have the potential to cause flooding and coastal infrastructure damage, generate primary and secondary wind damage to vegetation, and higher-than-normal wave heights and coastal storm surges. The recent Cyclone Cook impacted many regions and devastated peoples’ livelihoods and properties (e.g. heavy rain and high winds in Bay of Plenty, Gisborne and Hawke’s Bay caused flooding, landslips, fallen trees and widespread power outages).

Figure 1. Cyclone Cook approaching New Zealand. Image via NZ Herald.

Producing and Communicating Coastal Inundation Forecasts

Early warning is a key element of disaster risk reduction. It has long been recognized that if society could have advanced information on weather, the adverse effects associated with it could be minimized. Coastal inundation associated with tropical and extra tropical cyclones has a long history of causing death and destruction along our coastlines—and the threat has never been greater. It is imperative that the ever-increasing coastal population understands cyclone risk, particularly related to coastal inundation and storm surge.

Advances in meteorological, hydrological and engineering sciences are fast generating a range of new methodologies for forecasting weather and flood events, including ensemble prediction systems (EPS) and new hydrological or hydrodynamic models. However, many of these advanced prediction systems have not yet been incorporated into operational forecast systems. Consequently, operational forecasts have not yet been integrated into decision making processes in order to reduce disaster risks. In the real world, it has been observed that people do not always notice warnings, or are unable to understand the meaning of probabilistic forecasts well enough to consider themselves at risk. This provides a call to action for our Met Service and Civil Defence research and operations program to develop and implement new coastal inundation mitigation strategies.

Communication of storm coastal inundation is closely tied to how such forecasts are generated and the accuracy of the scientific data they are based on. For example, tropical cyclone forecasts issued by the Met  Service have lots of uncertainty. To generate coastal inundation information requires the integration of a cyclone model, storm surge model, wave model and hydrodynamic or river model. It is obvious that when linking a number of models, the level of uncertainty will be very high. At the same time, cyclones change path very frequently and the model needs to have the capacity to generate information in short intervals so that forecast information can reach people living within a few kilometers of the coast. While cyclone track forecasting continues to improve, the mean position errors for tropical cyclones in the area near the South Pacific (160ᵒ East to 120ᵒ West, 25ᵒ South to 40ᵒ South – this area is covered by the Tropical Cyclone Warning Center (TCWC) Wellington, operating within the Meteorological Service of New Zealand Ltd, or MetService) during 2014/15 and 2015/16 cyclone season were 73 km and 93 km respectively, for 24 hours lead time. The longer the lead time, the larger the uncertainties in the track forecasts. Figure 2 shows the cyclone forecast track error (based on ECMWF forecasts 2010-2016) with lead time.

Figure 2: Tropical Cyclone track errors in the ECMWF forecasts (2010-2016). The bars at the top (bottom) of the lines signal the 95th (5th) percentile of track errors. The upper (lower) bounds of the quadrate boxes signal the 75th (25th) percentile of track errors. The bars inside the boxes are the median track errors.

Figure 3. Cyclone COOK Cone of Uncertainty forecast by MetService

A major conundrum in weather messaging is how to communicate forecast uncertainty. While opinions are mixed, there is consensus within the weather enterprise that the level of certainty should be communicated as part of forecasts. For example, the cone of uncertainty released by TCWC based on past track error is probably the most recognized uncertainty graphic, certainly in TC-prone areas (See Figure 3), but often, critiqued, actual testing of its interpretation and use by stakeholders is scarce.

Geographers at the University of Alabama have been testing alternative TC warning graphics with the public, and results indicate preference for a Color Probability Cone that is a revised version of one issued by the Australia Bureau of Meteorology (See Figure 4).

Figure 4. Example of color probability cone and inland hazards for community understanding. The inland hazards are outlined in color and expected times for experiencing those specific hazards are included in the colored zone (Radford, 2012, thesis document)

Significant research efforts have focused on understanding how people make evacuation decisions including the important effects of past experience. Research shows that before deciding to take a disruptive and often expensive action such as evacuation, people must understand the forecast, believe it applies to them and, most importantly, feel that they and/or their loved ones are at risk. However, common practice has been to prepare and release forecast messages without adequately understanding how they are received, understood, and interpreted.

For any new forecasts product (e.g. coastal inundation), there will at first be a lack of communication of the warning to the affected people, and interpretation or internalization of the information for decision-making and response. In order to make a good decision, the capacity to generate coastal inundation forecasts with sufficient lead-time and an acceptable degree of accuracy is essential based on end to end early warning framework.

Research and development (RD) advancements in tropical cyclone (TC) forecasts using ensemble methods have been widely used for operational TC track forecasting. Either simple, weighted, or selective ensemble mean TC track forecasts tend to have smaller position errors than single-model-based (deterministic) forecasts. It’s clear that early warning is not helpful unless it reaches the people who need to act, and provides information about impacts (Figure 5). To respond to the early warning, the information needs to be understood and internalized by the public. Thus an interpretation and translation of the scientific information is essential. The new system needs to incorporate users’ needs to enable people to visualize the possible scenarios with probabilities of risk to reduce their vulnerabilities.

Figure 5: End-to-end impact-based early warning system

 

Further Reading:

Lorrey, A. M., Griffiths, G., Fauchereau, N., Diamond, H. J., Chappell, P. R. and Renwick, J. (2014), An ex-tropical cyclone climatology for Auckland, New Zealand. Int. J. Climatol., 34: 1157–1168.

S.H.M. Fakhruddin, Akiyuki Kawasaki, Mukand S. Babel, Community responses to flood early warning system: Case study in Kaijuri Union, Bangladesh, International Journal of Disaster Risk Reduction, Volume 14, Part 4, December 2015, Pages 323-331, ISSN 2212-4209, https://doi.org/10.1016/j.ijdrr.2015.08.004.

TCC 16 report of TCWC Wellington. World Meteorological Organization, RA V meeting, Honiara, Solomon Island

Morrow, B. H., and Lazo, 2015: Effective tropical cyclone forecast and warning communication: Recent social science contributions. Tropical Cyclone Research and Review, 4, 38-48

Fakhruddin SHM (2015) Risk Communications for Coastal Inundation Forecasting to the Community. J Psychol Psychother 5:203. doi: 10.4172/2161-0487.1000203

Posted in decision making, disaster risk reduction, forecast communication | Leave a comment

Help build Ireland’s new Flood Forecast Centre!

Contributed by Sinéad Duffy, Met Éireann

Here at Met Éireann, the Irish national meteorological service, we are working on building an operational Flood Forecast Centre (FFC) for fluvial and coastal floods. After widespread flooding across Ireland in December 2015/January 2016, the Government of Ireland took the decision to establish a National Flood Forecast and Warning Service (NFFWS). Met Éireann are working with the Office of Public Works (OPW) to make this a reality. The NFFWS will incorporate the operational FFC in Met Éireann with guidance for standards and performance overseen by the OPW.

I’m writing this blog post as we have two invitations to make to the HEPEX community and beyond. The first: take a look at the Hydrometeorologist jobs we’ve advertised and apply if you’d like to work in the new FFC at our Dublin headquarters. The second: let us know if you have hydrological models and integrator systems suitable for real-time flood forecasting. We are doing a study to review, develop and trial models suitable for operational forecasting for five representative catchments around Ireland and integrator systems suitable for real-time flood forecasting.

Hydrometeorologists Wanted!

We recently recruited a Chief Hydrometeorologist and we are now recruiting hydrometeorologists to work in a position which will be a mix of operational flood forecasting, development of hydrological and coastal flood forecasting models, and managing dissemination of Met Éireann Flood Forecast Centre products. The jobs will be varied and interesting, and you will be involved in building a national flood forecasting system from the early stages.

We need people with:

  • Experience of the development, calibration and operation of flood forecasting models and services;
  • A qualification of at least Level 8 (B.Sc. Hons) on the National Framework of Qualifications in one or more of the following: Hydrology, Oceanography, Meteorology or where Hydrology was taken as a major component e.g. Civil Engineering, Earth and Environmental Sciences.

The job information booklet and link to the application system are available here. The closing date for applications is 7th June 2018. This is an established (permanent) post subject to successful completion of a probationary contract of one year from appointment date (further details in the information booklet). On completion of three years satisfactory service, the Hydrometeorologist will receive three additional salary increments if they take or have taken exams to show that they are capable of reading and understanding with ease technical publications in any two of the following languages: French, German and Russian.

Other departments in Met Éireann are looking for meteorologists to work in Numerical Weather Prediction, Regional Downscaling, Operational Forecasting and Digital Communications. If you or anybody that you know would like a permanent post in those fields, please have a look at the information booklet and link to the application system here. The closing date for meteorologist post applications is 31st May 2018.

Hydrological Models and Integrator Systems for Operational Fluvial Flood Forecasting in Ireland Wanted!

To help us equip the Flood Forecast Centre for its fluvial forecasting task, we have decided to undertake a study of a range of existing available hydrological models and integrator systems. They will be reviewed, developed and trialed for operational fluvial flood forecasting use in Ireland.

The study was awarded to IMDC, an engineering company experienced in hydrological modelling and forecasting systems. The study started April 2018 and will last until October 2019. The study contains following stages:

  • Comprehensive literature review of existing hydrological models
  • Comprehensive literature review of existing integrator systems. An integrator system combines a hydrological model with real-time observed and forecasted data, starts new simulations, facilitates the visualisation of model input and output, triggers alerts and disseminates information to relevant stakeholders
  • Model development for five representative catchments: Shannon, Barrow, Nore, Slaney and Moy & Killalla
  • Trialling of hydrological models for fluvial flood forecasting. Models are tested on five representative catchments
  • Trialling of integrator systems for fluvial flood forecasting, including a 2 month pre-operational test

Based on the literature review three hydrological models and three integrator systems will be selected for further development and trialling on the five representative catchments. Each model is first calibrated and validated, and then tested both with historic data and with real-time forecast data from a number of meteorological data-sets.

The target forecast accuracy is expressed in terms of advance warning time and flow magnitude. A model should predict the actual peak flow to within +/- 10% and 6 hours of the actual peak at the gauged forecast points, and with a lead time of greater than 24 hours.

More details can be found on the Met Éireann website.

Submissions from Providers

Providers of hydrological models and integrators systems suitable for real-time flood forecasting are kindly invited to get in contact with Met Éireann. Suitable models and integrator systems will then be included in the literature review. Your submission should reach us by 15th of June 2018.

Please contact:

Email: hydroreview@met.ie

C/O: Eoin Sherlock, Met Éireann, Glasnevin Hill, Dublin 9, D09 Y921, Ireland
Tel: +353-1-8064200

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Further reading

  1. Update on the development of a National flood forecasting and warning service for Irelandby Jim Casey and Oliver Nicholson, OPW in the EFAS Bulletin for Feb/Mar 2018.
  2. Hydrometeorologist job details and application. The closing date is 7th June 2018.
  3. Meteorologist job details and application. The closing date is 31st May 2018.
Posted in announcements-events, jobs | 1 Comment

Recent development of post-processing methods in short-term hydrometeorological ensemble forecasting

Contributed by Wentao Li and Qingyun Duan 

Due to various uncertainties in model inputs and outputs, initial and boundary conditions, model structures and parameters, raw forecasts from meteorological or hydrological models suffer from systematic bias and under/overdispersion errors and they need to be corrected before being used in applications. Various statistical post-processing methods have been developed to correct these errors and achieve “sharp” forecasts subject to “reliability”. As in the book “Statistical methods in the atmospheric sciences” by Wilks, statistical post-processing methods can be generally divided to two categories from the view of statistics, namely regression-based methods (e.g., ensemble MOS and logistic regression) and kernel density-based methods (e.g., BMA and ensemble dressing). An example of the flow of a regression-based statistical post-processing method is shown in Figure 1. As there is already a review of post-processing in a previous blog in 2013,  in this blog post we discuss several newly developed post-processing methods for short- to medium-term hydrometeorological forecasting.

Figure 1. An example of a regression-based statistical post-processing method for hydrometeorological ensemble forecasting, modified from Dr. John Schaake’s presentation of Ensemble Pre-Processor (EPP).

As described in several papers (e.g., Scheuerer et al., 2015), there are several difficulties in post-processing variables such as precipitation and streamflow/river stage: (1) these variables follow a mixed distribution of a positive probability at zero value and a skewed continuous distribution for non-zero amounts; (2) the heteroscedasticity problem, namely that the forecast uncertainty increases with the magnitude of forecast variables; and (3) the representation of spatio-temporal and inter-variable dependency, which is important for applications such as hydrological forecasting.

To model the hydrometeorological variables with skewed distribution and non-homogeneous variance, one common treatment is to apply transformations to normalize the variables and stabilize the variance. After the transformation, traditional statistical models under assumptions of Normal distribution and homogeneity can be applied. Examples of the transformations include the Box-Cox or power transformation in heteroscedastic censored logistic regression (HCLR) and the log-sinh transformation in Bayesian joint probability (BJP). Moreover, there are also post-processing models that directly use non-Gaussian distributions without any transformations, such as the censored, shifted Gamma (CSG) distribution-based EMOS by Scheuerer and Hamill (2015). To deal with the heteroscedasticity problem, EMOS model includes the ensemble spread of raw forecasts as predictor to adjust the non-homogenous forecast uncertainty. R packages such as “ensembleMOS” and “crch” have made it easy to apply these methods.

How to model spatio-temporal and inter-variable dependency of hydrometeorological variables has gained much attention in recent years. To solve this problem, several “shuffling techniques” have been developed, namely to “shuffle” the ensemble members generated from the post-processed probability distributions according to some “rank structures” which represent the spatio-temporal and inter-variable dependency. Among these methods, the Schaake shuffle are mostly applied, in which the ensemble members are reordered according to the “rank structures” obtained from historical observation archives. However, the drawback of Schaake shuffle is that the templates from past observations may not represent the current synoptic situation.

Recently, two types of Schaake shuffle variants have been developed. One type is the ensemble copula coupling (ECC) scheme developed by Schefzic et al. (2013). ECC reorders ensemble members according to the “rank structures” of raw ensemble forecasts, thus accounts for the multivariate rank structure information of the current synoptic situation. The other type of variants select the “rank structures” from a subset of historical observations under “similar” situations using synoptic analogs or other similarity criterions. This type of method includes the “SimSchaake” by Schefzic et al. (2016), the minimum divergence Schaake shuffle (MDSS) by Scheuerer et al. (2017) and the meteorological analogues-based Schaake shuffle by Bellier et al. (2017). Wu et al. conducted a comparison experiment of the three schemes of shuffling techniques, namely the original Schaake shuffle and its two types of variants.

Besides this progress, what challenges remain for post-processing? A 2013 blog post by Nathalie Voisin, Jan Verkade and Maria-Helena Ramos (here) included a list of challenges for post-processing, many of which still need to be worked on. We also recommend this chapter by Dr. Thomas M. Hamill, which also emphasizes several challenges in post-processing, such as developing post-processors suitable for limited training data, and sharing post-processing software and data together “to build a postprocessing community”.

What other challenges do you think exist in post-processing? We welcome your comments on your experiences and opinions of post-processing below.

You can find the full review on statistical postprocessing methods for hydrometeorological ensemble forecasting in the authors’ recently published review paper:

Li W, Duan Q, Miao C, et al (2017). A review on statistical postprocessing methods for hydrometeorological ensemble forecasting. WIREs Water, e1246.

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23 (+1) unsolved questions in hydrology

Contributed by Bettina Schaefli

Have you heard about the 23 unsolved problems” initiative of IAHS, in reference to the 23 unsolved problems of Hilbert? After the launch of this initiative in November 2017, the web-based discussion culminated in a round of brainstorming at EGU 2018 and in a voting process at the Vienna Catchment Science Symposium.

Personally, I did not contribute any question at the discussion stage. I simply could not think of a question that relates to observed phenomena, is universal and specific (the three original requirements to formulate the problems). Are all questions that I work on not related to a particular climate region or to modeling rather than observed phenomena?

The proposed questions and the brainstorming session clearly showed that most colleagues did not self-censor their ideas and simply proposed anything what hydrologists currently work on.

At this stage, I really asked myself how we could possibly bring the hundreds of questions and problems (around 260) down to a reasonable number. And what would the added value of such a process be? Asking this question around me during the brainstorming session, I got an interesting answer: at the very least, we can learn something about what our research community is concerned about.

Of course! Why did I not consider this aspect before? With renewed enthusiasm and with a complete perspective change, I went to the Vienna Catchment Science Symposium following EGU; not to decisively influence the final choice of “the unsolved problems” but to observe a scientific experiment of a new kind: put 40 scientists in a room, together with a moderator. Give them a list of 60+ questions and roughly 1.5 h to reformulate, rank or delete them. Of course the process starts slowly. People do not know each other, some hesitate to openly say what they think about questions that were obviously formulated by some of the most famous hydrologists. Should I really vote to delete the favorite question of the moderator?

The great thing about a direct-democratic process, with hand-voting, is that it creates its own dynamic. Everyone can see what you vote or that you don’t vote; and there is no time for deep thinking. Over the course of the exercise, it becomes more and more fun: the moderator announces a problem number, the audience yells “delete” or votes for gold, silver or bronze. Hands go up and down, and even the most intriguing problems are voted within a few seconds.

Incredibly enough, after three such rounds in three parallel rooms, the list was brought down to 16 gold questions and 29 silver questions. The final outcome is now in the hands of a paper drafting team and will be published in a paper with a giant author list in the Hydrological Sciences Journal. Once you read the questions/problems, you will no longer be able to decipher what complex processes have led to these specific questions. But every reader might find a few unexpected questions that trigger new thinking; and together, the selected problems nicely reflect what the hot topics are in hydrology at the moment. With some gaps however. The question of how to make hydrology more open and replicable is not reflected in the retained questions, for example.

And: the single most important problem has been completely forgotten: why is hydrology not more gender-balanced?

Posted in activities, meetings, projects, social participation | Tagged , , | 1 Comment