FcstVerChallenge: will you join the HEPEX team?

You may have read Florian’s recent post on the WMO’s “forecast verification challenge”. In short: the WMO’s World Weather Research Programme set a challenge to develop new user oriented verification scores, metrics, diagnostics or diagrams. Any entries have to be submitted by the end of October and the winning entry will be awarded with a “keynote” presentation at the 2017 WMO verification meeting in Geneva as well as free passage into that event.


Some HEPEX-ers got together last week and discussed a joint effort to develop a new metric. While in the past, brilliant verification metrics have been developed by individuals (Brier´s probability score) as well as by small groups (CRPS decomposition), we realized that we’re likely to do better if we made this a team effort. More ideas, more points of view, more -and more varied- experience and expertise should all contribute to a better idea. Or to multiple ideas even, maybe.

So, our question to you:


It’ll be a great way to meet new people. It’ll be good to further sustain the HEPEX community. It’ll be a fantastic story if we get a result. In any case, it’ll be fun.

To organise the team effort, we’ve set up a Slack team space that we can use for team communication. Slack is essentially a virtual space where the team can have a conversation. It’s searchable. It can be used in conjunction with tools like Skype video calling, Trello and file sharing tools like Google Drive and Microsoft OneDrive. It’s everything we need to work across space and time.

If you’re interested, drop either Florian, Julie or myself an email and we’ll set you up on Slack so you can start the ride!

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Ensemble forecasting experiments in a medium size tropical basin using MASTER rainfall forecasts

Contributed by Adalberto Meller and Fernando Fan, members of the LSH Research Group Guest Columnist Team

As we have seem in our first post, great advances occurred in Brazil in the last years concerning the development of flood alert systems, but still today there is a low number of operational systems in terms of territory coverage, especially those using a probabilistic approach.

One of the first researches in Brazil to evaluate ensemble flood forecasts in South America was presented by Meller (2012) and Meller et al. (2014), but only published in Portuguese. Today we are using HEPEX space to present it to the broader community.


Figure 1. Paraopeba basin location.

The research assessed the performance of a short term ensemble flood forecasting system in a medium size tropical basin, the Paraopeba River Basin (Figure 1), based on data and streamflow forecasting tools available in operational mode in Brazil. The methodology consisted in the use of the MGB-IPH hydrological model, coupled to an ensemble of rainfall forecasts generated by several models with different initial conditions and parameterizations.

The weather forecast database used in the study comprised 50 outputs of NWP (numerical weather prediction) models, which differs in the type of model (global or regional), spatial resolution, parameterization, initial and boundary conditions. The preparation of this database came from an initiative of the Meteorologia Aplicada a Sistemas de Tempo Regionais Laboratory (MASTER-IAG/USP Lab) – in cooperation with other centers aiming conducting an intercomparison and combination activity of NWP models (Silva Dias et al., 2006).

Weather forecasts were issued by the centers of many countries once or twice a day (00:00 UTC or 12:00 UTC), with lead times between 48 and 168 hours, generally accumulated every six hours. Upon receipt, weather forecasts are interpolated by the MASTER-IAG laboratory to points corresponding to the latitudes and longitudes of a wide network of surface monitoring gauges in South America (Figure 2).


Figure 2. Location of surface stations where weather forecasts are provided by the MASTER Lab.

Besides the ensemble, a single deterministic streamflow forecast is also given by MASTER Lab, based on a quantitative precipitation forecast derived from the optimal combination of several outputs of NWP models . It was used as the reference forecast to assess the performance of the streamflow ensemble forecasts at the Paraopeba basin.

The aim of the reduction technique applied by MASTER Lab is to get a deterministic forecast with better performance than the arithmetic mean of the whole or any of the ensemble members. The methodology used by MASTER Lab is to assign different weights to each of the ensemble members in the composition, according to their performance in a period of 15 days prior to the forecast.

Using MASTER Lab data, flood forecasts were performed for three rainy seasons (austral summer) between 2008 and 2011. Figure 3 shows the results of forecasts from December 2009. The results from the ensemble flood forecasts were assessed by deterministic and probabilistic performance metrics.


Figure 3. Ensemble forecasts from December 2009 at the Paraopeba river.

General deterministic assessments showed that the ensemble mean have similar performance to those obtained by the deterministic reference forecast (the best forecast according to MASTER Lab), although showing better performance over most of the ensemble members. Based on the probabilistic performance measures, however, results showed the existence of an ensemble overforecasting and underspread of the members in regard to observed values, especially during initial lead times.

Results for predictions of dichotomous events, which tested the exceedance or not of a flood warning thresholds, showed that the 9th decile of the ensemble over performed the deterministic forecast and even the ensemble mean. In most cases, it was observed an increase in the proportion of correctly forecasted events while keeping false alarm rates at low levels. This benefit was generally higher for higher flow thresholds and for longer lead times, which are particularly important situations for flood mitigation.

Figure 4 shows results of ROC diagrams for 12, 24, 48 and 72 hours lead time and for the flow threshold of 623 m³/s, which is an estimated situation of lower channel extravasation of the river Paraopeba.


Figure 4. ROC diagrams at 12, 24, 48 and 72h lead times and flow 623 m³/s (threshold). Squares represent the ensemble percentiles 1º, 5º and 9º. The Red dot is the deterministic reference and the black dot is the ensemble mean.


  • Meller, A. (2012). Short Term Ensemble Flood Forecasting (Previsão de Cheias por Conjunto em Curto Prazo). PhD Thesis.  Federal University of Rio Grande do Sul. Hydraulic Research Institute. 224p.
  • Meller, A., Collischonn, W., Fan, F. M., Buarque, D. C., Paiva, R. C. D., Dias, P., Moreira, D. Short Term Ensemble Flood Forecasting. Revista Brasileira de Recursos Hídricos, v. 19, p. 33-49, 2014.
  • Silva Dias, P.L., Moreira, D.S., Dolif Neto, G. (2006). The Master Super Model Ensemble System (MSMES). Proceedings of 8th ICSHMO, Foz do Iguaçu, Brazil, April 24-28, p.1751-1757.
Posted in case-studies, columnist, ensemble techniques, floods | 2 Comments

A user-oriented forecast verification metric competition

H:\Downloads\wwrp.jpg Forecast performance is one of the most central themes not only in day-to-day weather forecasting, but also in HEPEX.

It is so important that we have devoted an entire chapter in our science and implementation plan to it (see here). I am, in particular, often forwarding the link to these blog posts when I am explaining (or trying to explain) forecast properties to a forecast user.

Nevertheless, many of the scores remain abstract. Whilst a forecast bias may still be easy to communicate, trying to get across what a root mean squared error is, is already far more challenging – and I haven’t even started with probabilistic scores.

There is no question that we need these scores to optimize and develop our forecasting systems, however, they are a “communication nightmare”. In HEPEX, we have developed games in trying to easy this communication (remember the peak box game from the HEPEX meeting in Maryland and, recently, in Quebec?).

Therefore, it is great that this communication nightmare is now also recognized by the verification component of the World Weather Research Program. They issued the challenge to develop and demonstrate the best New User-Oriented Forecast Verification Metric.

The challenge is cross-cutting and cross-disciplinary. It considers all applications of meteorological and hydrological forecasts that are relevant to user sectors such as agriculture, energy, emergency management, transport, etc. The metrics can be quantitative scores or diagnostics (e.g., diagrams), but they must be new to be considered for the prize.

  • Do you have an idea to propose?
  • Do you already use a score which would be ideal to the WWRP challenge?
  • Do you have a very specific user who would benefit from a very specific score?

If so, then join in and submit your entry here. For more details on the challenge visit the webpage here.

Posted in announcements-events, forecast users, verification | 1 Comment

Forecasting over international borders: limitations and solutions for large-scale or continental forecasting systems

Contributed by Chantal Donnelly (SMHI), member of the SMHI Guest Columnist Team

Global and continental forecasting schemes already exist and are used to inform disaster management in countries without sufficient national forecast systems of their own, as inputs to operational oceanographic models and for the general interest of citizens. I have been lucky enough to have worked with two operational European forecasting systems (setting up of E-HYPE and the WET tool, as an operational EFAS forecaster and testing E-HYPE in EFAS). My colleagues have also just recently set up a forecast system for the Arctic basin, Arctic-HYPE. So, I thought I’d reflect on some of the challenges specific to international forecasting.

Unlike national or subnational forecast systems, which often have access to their own country or region’s collected hydrometeorological data and expertise, international forecasting systems have to do with inhomogenous collations of data from different countries. There can be huge differences in how neighbouring countries contribute to international databases!

Historical collations of daily precipitation and temperature observations are improving, for example the E-OBS product in Europe, but data coverage both in time and space tends to be fairly uneven. Similarly, the global runoff data centre (GRDC) provides a fantastic service in collating and disseminating river discharge data around the world, but again, not all discharge data is available for all periods in this data set either.

So, what are some of the limitations for international forecasting and how can these be solved? Here are just a few:

  • There is often no single forcing data set that is consistently better than others. For example, in Europe, variations in precipitation and temperature gauges used in different data sets mean that quality varies regionally (e.g. Fig 1)
Fig.1. Row 1: Percentage difference between the mean and coefficient of variation of precipitation between gridded observations (5 km) and WFDEI and, Row 2: for discharge simulated using the gridded 5 km observations and WFDEI for the period 1991 to 2010.

Fig.1. Row 1: Percentage difference between the mean and coefficient of variation of precipitation between gridded observations (5 km) and WFDEI and, Row 2: for discharge simulated using the gridded 5 km observations and WFDEI for the period 1991 to 2010.

  • The available historical forcing sets are often only available to a fixed period (e.g. 2013), so can’t be used for hydrological model spin-up and initialisation.
  • This leads to a mix of model based forcing (reanalysis/forecast) and observation based forcing (interpolated observations) to calibrate, spin-up/initialise and run forecasts. As a result, potentially 3 or more different forcing sets can be used to make a forecast, e.g. (i) calibration to best available historical forcing, (ii) spin up with reanalysis and/or saved forecasts (iii) forecasting with ensemble or deterministic forecast model.
  • Real-time discharge data is generally unavailable for assimilation into the forecast model, so initial states are only as good as the calibrated hydrological model and forcing data.

We have begun testing solutions to these issues in our operational international forecasting at SMHI.

To secure a continuous  forcing data set that can continue from an  historical reference period until near-real-time, we created GFD (or global forcing data). This in an operational product that can flexibly correct a gridded reanalysis or forecast grid to gridded observations. By flexible we mean that either the gridded model data or observations can be interchanged so that when an historical reanalysis such as ERA-INTERIM is not available (e.g. typically at t-3 months), this can be replaced by saved deterministic forecast data (DFD). GFD corrects both ERA-INTERIM and the saved forecasts to gridded monthly mean precipitation (e.g. GPCC), ensuring continuity of the forcing data set from calibration to model initialisation. We are also now testing to see if we could similarly exploit our knowledge of the biases between forecasts (saved) and best available historical forcing data to correct our meteorological forecasts (e.g. Fig. 2).

Fig 2. Percentage difference between gridded observations (5 km) and saved deterministic forecasts at the E-HYPE model subbasin scale for the period 2010-2014. Note the large positive biases in the forecast over northern Europe and local negative biases in extremes over most of continental Europe as well as strong local biases for more extreme precipitation events (P99).

Fig 2. Percentage difference between gridded observations (5 km) and saved deterministic forecasts at the E-HYPE model subbasin scale for the period 2010-2014. Note the large positive biases in the forecast over northern Europe and local negative biases in extremes over most of continental Europe as well as strong local biases for more extreme precipitation events (P99).

This could potentially be useful not only for homogenising input forcing data to international forecast systems, but possibly also for bias-correcting forecasts in all hydrological forecasting systems.

We are also investigating remote sensing solution for model initialisation including altimeter measurements of surface water bodies, and satellite derived snow extent and depths. Our ultimate goal is to make international forecasting more useful despite the limitations that international borders sometimes present!


  Calibration Spin-up Forecasts Comments
WET: Water in Europe Today WFDEI to 2013 Saved ECMWF deterministic forecasts ECMWF deterministic forecast http://riverinfo.eu/

Currently being updated to GFD

Arctic-HYPE GFD GFD-GPCC first guess + saved ECMWFW det. forecasts corrected to GPCC ECWF deterministic forecast http://hypeweb.smhi.se/arctichype/

The spin-up uses 3 different combinations of gridded reanalysis/forecast and gauge data as data becomes online/available

Read more here.

Posted in columnist, data systems, operational systems | 2 Comments

Reflections on the 2016 HEPEX workshop (6-8 June 2016)

Contributed by QJ Wang, Maria-Helena Ramos, Andy Wood, François Anctil, Antoine Thiboult, Dirk Schwanenberg and Rodolfo Alvarado Montero

What a fantastic workshop! And this was certainly thanks to all the participants that you can see in the group photo below.


Participants to the workshop

The workshop was attended by about 85 people from 16 countries, with about 60 oral and posters presentations. The programme and the presentations that were made available by the authors can be seen here.


François Anctil (Université Laval) welcome participants on the first day

Many of the workshop attendees were connected through WhatsApp, so they could easily meet outside the workshop hours. Some early morning participants, for instance, were ready to go running at 6am, although not everyone responded to these calls after late nights, plenty of relaxed conversations and some beers.

In the programme, there was, of course, the highly anticipated game, this year featuring the economic value of ensemble forecasts. It was presented by Micha Werner, and we are looking forward to hearing more about the results (note: he publicly promised to provide a blog post as soon as the game sheets collected are analysed!).

The game will also join the Hepex resources page soon, and thus be available for the community to play it during meetings and courses.


Micha Werner presenting “The game of making decisions under uncertainty: How sure must one be?”


Massimiliano Zappa in front of his poster

Talking about games, we also had the opportunity to play again the peak-box game, proposed by Massimiliano Zappa, which was played in a plenary session at the Hepex workshop in Maryland (USA) in 2014. This was a nice example of interactive poster, where 42 participants were able to try their chances (and test their wisdom) in forecasting the peak and timing of a real flood event. In this PPT you can follow the diversity of opinions and our winner (thanks, Massimiliano, for sharing it with us!).

It was also pleasing to hear the significant progress made, since the Norrköping workshop, in setting up a testbed for inter-comparisons of techniques, methods and systems for seasonal streamflow forecasting. The topic is progressing fast within HEPEX, with notably a Special issue being prepared in HESS (check here for open submissions). If you want to participate to the experiment, contact Andrew Schepen (CSIRO) or Andy Wood (NCAR).

Also about experiments and testbeds, this year the Hepex workshop was followed by a break-out session. About 15 people attended the side event called “Assimilate your basin”. It was organized by Dirk Schwanenberg, Albrecht Weerts, Rodolfo Alvarado Montero and Peter Krahe. The participants provided 8 case studies to a testbed for data assimilation in hydrological models, conducted hindcasting experiments and assessed the forecast performance. The group discussed the common interest in data assimilation and the possibility of setting up a related HEPEX inter-comparison experiment in the near future. Further news will come soon in the Hepex Portal (or contact the session organizers if you are interested to learn more about it).


Break-out-session “Assimilate your basin”

Science, operations and applications

Three themes emerged from the workshop:  science, operations, and applications.

  • The last theme, applications, featured very strongly compared with previous workshops. There were a number of presentations on the use of forecasts in decision-making, and how this resulted in actions and impacts. Methods for evaluating the value of ensemble forecasts were contrasted, and showed how social structure and communications play an important role in achieving impacts. Many case studies, including from hydropower corporations and flood emergency and water management agencies, demonstrated the benefits and complexities of using ensemble forecasts.
  • On forecasting operations, how forecasters interact with forecasting models drew much interest once again – If one was not “in the loop”, one could certainly be just as effective or even more so operating “over the loop”! Challenges and successes in forecasting operations and water management for trans-boundary water systems such as the Great Lakes were highlighted. Practical and yet significant issues were discussed on how to maintain consistency in streamflow forecasting services when weather and climate forecasting models were frequently updated. Attention was also drawn for consistency in forecasts and forecasting methods across regions for operating large energy grids, for which hydropower can play a significant role. What integration of sciences and technologies could achieve was ably demonstrated by success in developing highly sophisticated forecasting systems for complex urban regions.
  • On forecasting science, new methods and successes in real applications of data assimilation were presented. The possibility of doing streamflow forecasting within NWP models is getting real, especially when these NWP models could be calibrated by new solvers developed by hydrologists. Downscaling of weather and climate forecasts was always going to be an area of strong interests, but this year Shaake Shuffle became a ground for fertile research, with a number of variants proposed to make it working even better! Different ways to handle hydrological uncertainty, being through representing multiple initial conditions, multiple hydrological models, or total residues, were showing progress towards achieving reliable ensemble forecasts.

A perfect score


Quebec city on a sunny day

The workshop was a great success – with a perfect “energy score” of 100!

We thank all the key note speakers, speakers, poster presenters, and all attendees, for making the workshop such a success. In particular, we thank all those that participated to the workshop organization for running such a wonderful workshop – with perfect accuracy and little uncertainty!

We also thank the sponsors of the workshop for the excellent facilities and warm hospitality.

The charm of Quebec city will last in the memory of attendees for a long time.


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Evaluation of an operational high resolution HEPS to a southern Brazilian basin

Contributed by Vinicius Siqueira, member of the LSH Research Group Guest Columnist Team.

CPTEC is the Brazilian center for weather and Climate Studies (Centro de Previsão de Tempo e Estudos Climáticos). It has recently developed a high-resolution version of the Eta meteorological model (5 km), with five members combining different parameterization schemes and boundary conditions.

Currently, the ensemble forecasts are operationally issued at the Brazilian National Institute for Space Research (INPE) twice a day (00 UTC and 12 UTC), and are provided with temporal resolution and lead time of 1 hour and 72 hours, respectively.

In this context, the study presented here (Siqueira et al., 2016, in press) aimed to assess the quality of ensemble flood forecasts generated using this high resolution Eta model version at Taquari-Antas river basin, and its potential to provide additional information to a local Flood Alert System.

The basin is a steep basin located in a mountainous region in southern Brazil, and due to its geological characteristics and radial drainage pattern, streamflow is largely dominated by surface runoff with high peak flows and short duration times. Climate is sub-tropical and there is no seasonality, so floods can occur in any month of the year but mostly in austral winter and spring (June to October). Figure 1 shows the location of the Taquari-Antas basin.


Figure 1. Location of Taquari-Antas Basin and Encantado city (red dot) in Southern Brazil. Reaches marked in red are critical flood-prone areas.

The hydrological model MGB-IPH was coupled to the high-resolution meteorological EPS Eta model, as well as to the deterministic version of Eta regional model. On a single event evaluation, the peak discharge was reasonable well predicted by at least one ensemble member, in nearly all forecasts, with a good prediction of the flood timing for the considered lead times (Figures 2 and 3).


Figure 2. MGB-Eta Hydrological Ensemble Forecasts for a 1-2 year flood occurred in Encantado city (Taquari-Antas basin).


Figure 3. MGB-Eta Hydrological Ensemble Forecasts for a 40-year flood occurred in Encantado city (Taquari-Antas basin).

In a comparison with deterministic forecasts, the ensemble ones showed higher accuracy and higher probability of detection (POD) for the reference thresholds, preserving false alarm rates at reasonably low levels (Figure 4).

An overall tendency of underestimation was also identified, with most observations falling between the higher ranks of the ensemble. Furthermore, the combination of previous forecasts (t-12h) with the recent ones leads to a slight increase of ensemble spread and POD, despite the performance reduction in terms of accuracy and bias for the ensemble mean.


Figure 4. ROC curves of the forecasting systems. Symbols outlined in red, green and blue are related to watch, alert and flooding thresholds, respectively. The deterministic forecasts are shown by filled symbols, following the same coloring scheme for the reference thresholds.

Results suggest that there is a benefit in having hydrological ensemble forecasts obtained from the high resolution EPS Eta model, which is starting to be used as complementary information to a local Flood Alert System (Chagas et al. 2014), supporting pre-alert issues and Civil Defense internal planning actions.


  • CHAGAS, A.; CASTILHO, PEDROLLO, M.; GERMANO, A.; SOTERIO, P. The Warning Flood System in Taquari River Basin. In: 6th International Conference in Flood Management, Sao Paulo, Brazil. Proceedings… Sao Paulo: [s.n.] 2014.
  • CHOU, S. C.; BUSTAMANTE, J. F.; GOMES, J. L.  Evaluation of Eta Model seasonal precipitation forecasts over South America. Nonlinear Processes in Geophysics, v. 12, n. 4, p. 537–555, 2005.
  • SIQUEIRA, V. A.; COLLISCHONN, W. ; FAN, F. M.; CHOU, S. C. . Flood ensemble forecast from operational Eta model provisions in the basin of the Taquari-Antas / RS. Revista Brasileira de Recursos Hídricos, 2016 (in press).
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Live from the HEPEX 2016 Workshop in Quebec

During the HEPEX 2016 Workshop in Quebec, our dedicated team of HEPEX enthusiasts will give a live report of the meeting. All Tweets that include the #hepex hashtag will be displayed on this page. Feel free to contribute by Tweeting what you see and hear!

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Workshop on Data Assimilation in Terrestrial Systems, September 19-21 in Bonn, Germany

By Harrie-Jan Hendricks Franssen and Insa Neuweiler

The workshop on Data Assimilation in Terrestrial Systems will be held in Bonn, Germany

This workshop will provide a platform for scientific exchange among researchers working on data assimilation methods and applications in terrestrial systems. In particular, we hope to stimulate the interdisciplinary exchange among atmospheric researches, hydrologists, soil scientists, biogeochemists and engineers.

Topics to be discussed are the development, improvement and evaluation of methodologies both in synthetic and real-world studies, and operational applications of data assimilation including real-time forecasting, control and management.

This workshop wants to focus on operational applications and includes two invited talks which focus on operational data assimilation: the talk by Gabrielle de Lannoy (University of Leuven) addresses assimilation of remote sensing data from SMA, and the talk by Roland Potthast (German Meteorological Service) addresses operational data assimilation in the context of weather forecasts.

A further topic we especially want to focus on in this workshop is data assimilation for coupled models like atmosphere-land surface models or land surface-subsurface models. The invited talk by Henrik Madsen (Danish Hydraulic Institute) focuses on important aspects of data assimilation for such models. The invited talk by Ahmed ElSheik (Heriot-Watt University Edinburgh, UK) addresses data assimilation for subsurface systems.

We invite participants interested in data assimilation developments and applications for the subsurface, land surface, and the atmosphere with the goal to analyze and/or predict terrestrial water and heat energy cycles, rainfall-runoff processes, and biogeochemical cycles.

We would like to attract contributions addressing method evaluation with both synthetical studies and studies on real systems. Studies which involve operational applications and multiple compartments of the terrestrial system are particularly welcome.

Abstract submission is possible until May 31, but likely it will be extended (contact the organizers).

The conference website provides further information on abstract submission and registration.

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The GloFAS Community Workshop – Supporting the Integration of Global Flood Forecasts Locally

By Rebecca Emerton, Liz Stephens and Hannah Cloke

Global Flood conf 20161_128

Workshop participants from SENAMHI (Peru), the Red Cross/Red Crescent Climate Centre (U.S., Peru and London), the Mozambique Red Cross, the Belize Hydromet Service, the Xiamen Weather Service Centre, JRC, ECMWF and the University of Reading.

On the 4th of May, delegates from across the world gathered at the University of Reading for the first Global Flood Awareness System (GloFAS) community workshop, aimed at supporting the integration of GloFAS forecasts into existing national and local forecasting capabilities. The workshop, led by Professor Hannah Cloke and Dr. Liz Stephens, included seminars, practical activities and discussion sessions.

hannah liz

Liz and Hannah

Participants of the full three-day workshop attended from the Servicio Nacional de Meteorología e Hydrología del Perú (SENAMHI), the Red Cross/Red Crescent Climate Centre (U.S., Peru and London), the Mozambique Red Cross, the Belize Hydromet Service, the Xiamen Weather Service Centre, the European Commission Joint Research Centre (JRC), the European Centre for Medium-Range Weather Forecasts (ECMWF) and the University of Reading.

First-day open event attracted a large crowd

presentation 0

Sir David Bell, University of Reading

The event kicked off with an afternoon of seminars, attended by forecasters, academics, policy-makers and decision makers from far and wide. The introductory remarks were given by Professor Hannah Cloke, before handing over to Sir David Bell, the Vice Chancellor of the University of Reading, who warmly welcomed everyone to the beautiful University of Reading and introduced the connections with institutions such as ECMWF  and the Red Cross/Red Crescent Climate Centre, and the interdisciplinary research at the University that led to this event.

Global Flood conf 20161_21

Florence Rabier, ECMWF

Dr. Florence Rabier, the director of the ECMWF, gave the first keynote presentation, providing an insight into the role of the ECMWF and its forecasts, and how GloFAS came to be. The second keynote was given by Dr. Nicola Ranger from the UK’s Department for International Development (DFID), who discussed how DFID make use of forecasts, both directly and indirectly.

Global Flood conf 20161_33

Nicola Ranger, DFID

Further presentations were given by Erin Coughlan de Perez from the Red Cross / Red Crescent Climate Centre, Professor Ros Cornforth, the director of the Walker Institute, and Dr. Peter Salamon, the GloFAS project manager at the JRC. Erin’s presentation, entitled “Think globally, act locally?”, discussed how GloFAS, a global scale flood forecasting system, can be applied at the local scales at which the Red Cross / Red Crescent Societies often operate. An example was highlighted where Forecast-based Financing, an initiative which aims to distribute humanitarian funding ahead of a natural disaster, was successful ahead of floods in Uganda in late 2015 based on GloFAS forecasts.

presentation 3

Listening intently to talks

Ros went on to discuss “Making forecasts matter”; how science can be used to help by breaking down academic borders and working together with communities, policymakers and forecasting services. The AMMA Forecasters’ Handbook, a guide for operational forecasting in West Africa, was discussed as an example; a significant project developed through collaboration between researchers and forecasters, to include long-used local forecasting knowledge alongside new research and techniques.

Global Flood conf 20161_66

Peter Salamon, JRC

In the last talk of the afternoon, Peter provided insight into the technical aspects of GloFAS, and how the system can be used to support flood risk management globally. Peter began by stating that the principal objectives of GloFAS are to provide added, complementary value for national emergency response services and support international organisations and global actors.

posters 1

Discussion during the poster session

During the evening, participants had the chance to present posters, and both the seminars and posters provided a platform for many lively discussions and a brilliant end to the day.

Two days of GloFAS workshop

The following two days focused on the use and integration of GloFAS forecasts, beginning with presentations from each participant on forecasting practices in their country or region, and their own role and experiences. Training sessions were provided by Hannah Cloke on ensemble forecasting and hydrological modelling, and specifically on the GloFAS interface and forecasts by Peter Salamon.

workshop activity 2

Ervin Zsoter, ECMWF explaining GloFAS initialisation

The workshop also involved plenty of interactive sessions led by Liz Stephens, Ervin Zsoter (ECMWF), Hannah Cloke, and PhD students Louise Arnal and Rebecca Emerton. These sessions provided hands-on training for participants on how to access and interpret the output of GloFAS forecasts by plotting the data using various different visualisations; evaluating GloFAS forecasts, during which users were able to calculate and plot various different skill scores, for example, to evaluate GloFAS in several different regions and river basins; and post-processing of forecasts, led by Ervin Zsoter (with thanks also to Paul Smith [ECMWF]), which saw participants using bias correction techniques to analyse forecast uncertainty, and attempt to improve the forecasts.

workshop activity1

Examining GloFAS output

This workshop provided an excellent opportunity for forecasters, decision-makers, researchers and model developers to work and learn together. While the aim of the workshop was to support the integration of GloFAS forecasts into local capabilities, alongside the training given, the model developers and researchers gained a valuable insight into the needs of the forecast users, and everyone was able to learn something from working together with other members of the GloFAS community.

This workshop was funded by the GFDRR/DFID Challenge Fund and a research impact award made by NERC to Professor Hannah Cloke, with further support from the University of Reading and the Walker Institute.

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A never-ending struggle – Improving spring melt runoff forecast via snow information

Contributed by David Gustafsson (SMHI), member of the SMHI Guest Columnist Team

As long as we can remember, the Swedish hydropower hydrologists have tried to improve the spring melt runoff predictions by integrating snow measurements in their forecast models. Various measurements techniques have been used: traditional snow surveys with snow tube sampling; snowmobile and helicopter borne ground-penetrating radar and gamma-ray sensors; laser-scanning; and of course numerous attempts with satellite data (Photo 1). The usual conclusions have been, “yes we can reduce the forecast error with this new snow data but … improvements were not systematic between sites and years, and also very small compared to average errors in the HBV model. So why putting an effort on including snow data when it only increases the overall uncertainty?”.

Photo 1. Snow water equivalent measurement in Jämtland, Sweden. (photo by D. Gustafsson)

Photo 1. Snow water equivalent measurement in Jämtland, Sweden. (photo by D. Gustafsson)

Typically, the average forecast error is around 10-20% for the total spring melt runoff volume. In the latest attempt with assimilation of in-situ and satellite based snow information, we managed to show a reduction of volume errors from 20-30% to around 15-20%, corresponding to a relative improvement of some 20-30% (more details will be shown at the upcoming HEPEX workshop in Quebec!). Not so impressive maybe, but we raise the question “how does this compare to the actual economic value of the hydrological forecasts?

The 2015 spring melt season was very interesting in Sweden. The winter was a typical NAO+ with more precipitation and higher temperatures than usual, resulting in unusually little snow at low altitudes in most part of the country and much more snow than usual at higher altitudes in the middle and northern part of Sweden. On top of that, the spring was rather cold and the snow melt season was extended long into the summer months. The forecast models also indicated much more snow than usual in the large important hydropower basins; consequently the experienced reservoir managers decided to increase power production during spring to empty the reservoirs as much as possible. They do this to avoid spilling of meltwater that should be used for the next winter – but they did not empty the reservoirs as much as the forecasts suggested, partly due to bad experience from the previous year with a similar situation, and partly due to limits in the production capacity. Despite their best efforts and expert knowledge on hydro-climatic forecasts, there was a lot of water spilled at the end of summer, when the reservoirs were already full while snow melt was still ongoing. In addition, the impact of their decision was amplified by the unusual amount of rainfall in the early summer. Of course, the large amount of snow was there in the forecast models, but this year instead, the snow melt timing and the additional rainfall during the snow melt season affected the forecast skill.

In the case where regulation was perfect and no water was lost, rough estimates by our hydropower users indicate that the economic value of the lost power production could have been in the order of 10-60 million SEK (roughly about 1-6 million Euros); note that this is only in one of the major rivers in Sweden – the Ume River which happens to be one of the test cases in the IMPREX project. So despite the small improvements over the past, it seems like that the never-ending struggle to improve snow melt forecasts with snow data will continue and could be motivated also from economic perspectives. However, this story also tells us that identifying the drivers of predictability should be one of the key elements to improve the hydrological forecasts and their use.

Special thanks to Björn Norell (Vattenregleringsföretagen AB) for estimates of water loss and economic values of potential power production.

Posted in case-studies, columnist, data assimilation, economic value, forecast users, seasonal prediction, Unclassified | 1 Comment