Developing and running an ensemble prediction system – Interview with Jutta Thielen-del Pozo

Posted by Maria-Helena Ramos (IRSTEA)

I met Jutta Thielen-del Pozo in 2005, when I went to the JRC in Ispra, Italy, to take a post-doctoral position. I had been doing research in hydrology for some time, but I didn’t know anything about ensemble predictions when I joined her team. They were developing the European Flood Awareness System (EFAS) and the first tests using weather ensemble predictions to issue EFAS warnings were just starting. I was fortunate enough to count with Jutta’s patience and amiability to get involved in the research being done within EFAS and introduced to the HEPEX community.

Jutta is now Head of the Scientific Development Unit at the European Commission since July 2016, a challenging position as the units aims at stimulating novel and trans-displinary research within the JRC through a Centre of Advanced Studies, Exploratory Research, and novel instruments such as Science and Art and Collaborative Doctoral  Partnerships between JRC and higher education institutions.

Her new position has in no way reduced her historic enthusiasm for HEPEX and its community. She acted as a HEPEX co-chair from 2007 to 2012, and much of what this initiative is today is thanks to her pushing things forward, and adding people and ideas to the group.

At the JRC, Jutta was the EFAS project leader for 10 years, from 2003-2012. She acquired a broad experience in designing and running an ensemble prediction system. Since many of us are also dealing with these issues, I have asked her some questions. Here are her answers.

MHR: In your opinion, what are the crucial choices one has to make when starting the design of an ensemble flood prediction system?

JT: First of all, I think it is crucial to understand what the system is supposed to deliver and what the expectations are. Is it a small watershed with typically flash floods where decision makers have little time to act or is it a larger river with a comparatively slower response time? Is it an urban watershed? Is the watershed entirely within one’s own administrative boundaries or are others involved? Is the decision making pathway, from information to action in case of floods, long or short? How are the vulnerability and the coping capacity of society in case of flooding?

Depending on these answers, the required lead times and acceptable accuracies of the forecasts can be determined, which, in return, will determine which input data are required and what type of models and forecasting system is most suitable. For example, for flash flood prone regions, radar data blended with nowcasting and short term forecasts will be essential, whereas for riverine flood prone areas it is rather medium-range to monthly forecasts that will be more useful.

However, I would say that although input data and process modelling are key elements for a successful ensemble flood forecasting system, equally important is a communication and training strategy, so that the results are properly communicated and understood at any point in the forecasting chain. Only then users will understand that uncertainties exist; that they are acceptable at longer lead times if at the same time they provide longer time to act; and that uncertainties can and will be reduce as the events draw nearer and more data becomes available. This is particularly true today with the plethora of data sources available, including satellite and social media.

Generally, the HEPEX community has shown that whatever type of flood, ensemble prediction systems (EPS) tend to provide longer warning times for the decision making and yield more robust results. EPS give forecasters and decision makers more time to take different preparedness actions, play through different scenarios and therefore allow both preparedness and response teams to act more decisively during the crisis.

MHR: And what are the main difficulties someone should expect when running an ensemble flood prediction system in real-time?

JT: Real time operational forecasting always puts enormous pressure on not having the process chain interrupted – and there can be manifold reasons for this. There are the technical issues on site to ensure a 24/24 business continuity (power supply, redundancy of the systems in case one or more systems fails, sufficient storage at any time of the processing chain, availability of nodes for processing…) I remember an incident of the early EFAS days when a process got into an endless loop because a simple line of code was accidently deleted, which then started filling the hard disk. That was a nightmare at the time!

Then there are software issues, e.g. in case of necessary updates not having been sufficiently tested and resulting in hiccups or termination of processes. One particular aspect of ensemble prediction systems is that it involves a lot of input and output data and, for different reasons, not all files or all ensemble members may be available.  Therefore the process chain must be able to cope with time delays, partial availability of data and files, without flawing the analysis and visualisation of files.

I think another important aspect is that, during a crisis, forecasters are often asked additional questions which then need to be answered under enormous time pressure. Therefore the system should be designed in a way that additional information and in depth analysis can be extracted at any time in an easy way without slowing down the actual forecasting capacity.

MHR: How do you see the future of HEPEX? Any topics we should focus on or new directions to consider?

JT: I think HEPEX has already taken a good direction by involving end users and different stakeholders from the beginning. Yet much of the HEPEX activity remains directed towards scientists, forecasters and civil protection. I think social media now opens up new doors to keep involving the public more directly in flood forecasting. Posting pictures while flooding is going on is an obvious way and already taking place, but possibly this could be even more integrated. There is always the prejudice that “the public don’t understand probabilities”, but perhaps it is time to put this to the test and use the outcome to the advantage of the ensemble prediction systems?

Although HEPEX is open to everybody it is not yet a full global community and mostly restricted to those scientists and end users that have the technical power to run large and complex models and data sets. Yet, flooding takes the biggest toll in those regions where such capabilities are not available. And we know that flooding disproportionally affects the poorer communities. I would therefore like to see HEPEX trying to involve also end-users and scientists from those regions where computing power is limited, and finding solutions to introduce the value of ensemble prediction there too in order to have a fairer distribution of warning information globally.

MHR: And a last question: what are your working challenges now as Head of the Scientific Development Unit at the JRC?

JT: Since my new unit targets Scientific Development in the JRC in general, it is not focused on a particular topic. Its aim is rather to become the incubator for new research not yet part of the JRC’s portfolio, to stimulate exploratory research and to use Art and Science to connect JRC scientists across the JRC and with society. Such programmes are really important – in fact, if you remember, EFAS and the ensemble prediction system benefited in 2005 from the exploratory research programme at the time.

This is exciting and challenging at the same time. In order to address the changes in sciences and changes in society, my unit fosters collaboration between natural science and technology with the social sciences and humanities. We will be involving experts at the science-policy interface. This is opening up new ways of thinking and challenges us to think across disciplines. In this sense, I hope that with my work I can continue to contribute to HEPEX and stimulate new research questions.

 Thank you, Jutta, for your time and contribution!