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.

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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.

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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.

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

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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).

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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

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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.

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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).

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

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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.

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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.

References:

  • 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

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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.

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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

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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Get your geek on: handling data for ensemble forecasting

Contributed by James Bennett, David Robertson, Andrew Schepen, Jean-Michel Perraud and Robert Bridgart, members of the CSIRO Columnist Team

There’s something about discussions of data handling that’s particularly soporific – but don’t nod off yet!

Most hydrologists are trained to work on individual catchments and we often opt for simple conceptual models. In the pre-ensemble era, we were often quite happy to use unsophisticated ways of crunching numbers: many of us can remember (perhaps quite recently!) using desktop computers to tune and run models, storing data in text files, and so on.

Maybe it’s because it’s obvious, but it’s little remarked that switching from deterministic forecasts to ensembles means handling much more data. Here at CSIRO we tend to use 1000-member ensembles, and our partners at the Bureau of Meteorology use a method that generates 6000 (!) ensemble members for each forecast. If you’re running cross-validation experiments across multiple catchments this can lead to migraine-like data headaches.

In a recent experiment for 22 catchments we generated over 2TB of rainfall and streamflow hindcasts. Of course generating the hindcasts is only one step in the process –verifying them with a bunch of different tests and generating a load of plots can be even more time consuming. It’s simply not feasible to run experiments like this without getting your geek on [1], putting on your “big data” cap (backwards of course) and taking advantage of the awesome power of computer science.

Computer power and data storage

We first began developing a national seasonal forecasting service about 8 years ago. While seasonal forecasting is far less computationally intensive than, say, daily forecasting, we still hit the limits of what could be achieved with desktop computers. So we farmed out jobs to HTCondor, a system that scavenges unused processing power from the many desktop computers at CSIRO. More recently, we have been writing software for applications in short-medium term forecasting that takes advantage of parallelisation in CSIRO’s high-performance supercomputers.

Data storage is another crucial issue. A few years ago we got sick of storing and exchanging thousands of voluminous text files of differing formats and unknown provenance and repute, and followed the climate community on the path to data righteousness: netCDF.

netCDF is a self-describing binary file format that is purpose designed for multi-dimensional data. It’s traditionally been used by ocean and climate modellers, and has a very well described, yet adaptable, set of conventions. The cherry-on-top is that netCDF allows serious data compression, so that corpulent ensemble hindcast data can be squished into slender binary files for storage. We developed our own netCDF specification, including a lead time dimension (see fig below), that allows us to store many ensemble hindcasts/forecasts at different locations in each file, leading to massive speed-ups in forecast verification.

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Schematic of how we use the lead-time dimension to store multiple forecasts in a single netCDF file. The lead-time dimension is defined in relation to the time dimension, and means we can store many hindcasts in a single file. The files also handle large ensembles, multiple locations and multiple variables.

A huge benefit of using a standardised, well supported and self-describing binary file format is that it makes sharing data incredibly easy. At first, we found this beneficial within our small research group: even though there are only about 10 of us, we each manage to (strongly!) prefer different scripting languages – R, Matlab, Python. All these scripting languages have strong support for netCDF files so it’s very easy to load and manipulate data. The meta-data stored inside the netCDF files makes reviewing old experiments much easier – we find we don’t have to retrace our steps as much or (gulp!) regenerate hindcasts.

We have since had very good experiences with sharing our netCDF files with collaborators outside our group, and the Bureau of Meteorology has adopted our netCDF specification for operational forecasting. On the downside, binary data formats can be restrictive: netCDF is not readable with simple text editors, and this can occlude data from forecast users or collaborators who don’t have the time or inclination to learn scripting languages or other new software.

Of course, there are many other aspects to the issue of data in ensemble forecasting that we can’t cover in a short blog – we haven’t even touched on algorithm efficiency – and so we’d like to hear your data stories:

  • Have you faced similar problems with verifying ensemble forecasts?
  • Do you prefer other ways of storing data, like HDF5 or databases?
  • Do you have different or better ways of crunching and storing your data?

Tell us in the comments!

[1] Who are we kidding – we were geeks already. Shout out to those who saw the tribute to Missy ‘Misdemeanor’ Elliott in the phrase ‘get your geek on’: there’s a fair chance that you may be even geekier than us. (If not, then go on and treat yourself.)

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“Ex tempore”- El Niño Ready Nations (ENRN)

Contributed by Bapon Fakhruddin

Seasonal forecasting techniques today are far more advanced than they were 40 years ago, enabling ensembles of seasonal forecast simulations with state-of-the-art climate models that produce a probability distribution of possible outcomes at various lead times for slightly different initial conditions.

This is thanks to the development of complex coupled ocean–atmosphere–land numerical models, modern statistical forecasting tools, sophisticated data assimilation systems and global observing systems that provide real-time data for forecast initialization. The forecast ensembles nowadays are able to detect the predictable signal from ocean initial conditions as well as the unpredictable, chaotic elements of the climate system.

The advances in seasonal forecasting over the past 40 years have improved the prediction of ENSO events. However, the incorporation of these forecasts into the decision making to take appropriate response by the society still poses a challenge.

Figure: Predictive Ocean Atmosphere Model for Australia (POAMA) by Bureau of Meteorology. POAMA outlooks provide forecasts out to nine months ahead. The model ensemble distributions shown here provide a range of possible developments in sea surface temperature (SST) in the equatorial Pacific Ocean (NINO regions) and for the Indian Ocean

Predictive Ocean Atmosphere Model for Australia (POAMA) by Bureau of Meteorology. POAMA outlooks provide forecasts out to nine months ahead. The model ensemble distributions shown here provide a range of possible developments in sea surface temperature (SST) in the equatorial Pacific Ocean (NINO regions) and for the Indian Ocean.

El Niño Ready Nations (ENRN), as a concept, was inspired by 2 things: NOAA’s existing Weather Ready Nation program and the emergence of a forecast of an El Niño event of extraordinary magnitude in the tropical Pacific, a magnitude rivalling that of the 1997-98 “El Niño of the Century.” (NB: the 1982-83 El Niño was the first on to be called “The El Niño of the Century.”)

The forecast of a major El Niño was supported by researchers and was amplified through the media worldwide. The ENRN idea was included in the USAID Portal Project: a focused initiative to enhance national Disaster Risk Reduction (DRR), in parts, as part of a Portal Project for Lessons Learned about DRR in a Changing Climate, lead by Prof. Mickey Glanz.

The workshop held during the Networkshop in Bangkok, March 22-24, 2016, with support from USAID, was designed as an internal project mid-course correction activity. It brought together the country case-study leaders to report on their progress and to agree to a common core framework for inputs to their country reports.

The networking aspect of the Networkshop was also an explicitly desired output. The meeting brought together young and established professionals, from different disciplines and organizations, from national meteorological services, and from different countries, each with a demonstrated interested in hydro-meteorological DRR. This ability to bring people from diverse background together to discuss common problems was a key, unanticipated outcome of the Antalya Conference in mid-February 2015 and has been referred to as the “spirit of Antalya”.

ENRN’s activity is a contribution to the proposed Portal Project on “Lessons learned about DRR in a changing climate.” The portal project is a direct outcome of the Antalya (Turkey) DRR Conference of mid-February 2015. It was given the highest priority of the Antalya Conference’s “Six Calls to Action,” prepared for the UNISDR’s World Conference on Disaster Risk Reduction (WCDRR) in Sendai, Japan.

Professor Mickey Glanz is leader of the ENRN program

Professor Mickey Glanz is the leader of the ENRN program

This mix of experience, expertise and interests led to interesting discussions, not often heard in other meetings. For example, participants discussed the different meanings attributed to important words or DRR concepts in English. Participants from different cultures identified how, for example, “readiness” might be interpreted in their countries under the perspective of El Niño events.

The recent tropical cyclone (TC) Winston in Fiji was an example of a serious El Niño event. TC Winston reminded us how vulnerable the South Pacific is. Scientific information alone cannot make Fiji and other Pacific Island nations resilient. However, integrated multi-hazard risk management systems and strategies can be adopted to achieve sustainability and reduce vulnerability to natural disaster.

It is easier to write history knowing what has happened than it is to chart the future in a highly dynamic system. Global warming is altering the mean climate of Earth with potential impacts on the ENSO cycle that we are only beginning to fathom. More surprises may await us when learning more about ENSO in the future.

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Tracing The Origins of ESP

HEPEX Historical Hydrology Series, Edition 1

Contribution by Andy Wood, Tom Pagano, and Maury Roos, with special thanks to Mike Anderson

Every day in the western US and elsewhere in the world, reservoir release decisions are made based in part on seasonal reservoir inflow forecasts created using a operational technique called Ensemble Streamflow Prediction (ESP, which originally stood for Extended Streamflow Prediction).

ESP has become a key component of operational long lead prediction in a number of agencies (in the US, Russia, Czechoslovakia, Germany, Sweden, to name a few countries) in the last few decades. The earliest common references for ESP are a US Western Snow Conference presentation (Twedt et al., 1977) and Day et al. (1985) journal article.

But where did ESP really begin?

We have to go back a little over 40 years, when the State of California was about to grapple with a series of long lead ‘water supply forecast’ (WSF) busts in one of the worst droughts to hit parts of the western US in the 20th Century – the two year drought of 1976-77.

In the fall of 1977, California water resources were dire condition, leading to intense interest in predictions for the coming winter and 1978 water supply (i.e., snowmelt runoff) outcomes. California’s winter rain and snowfall typically provide the bulk of the water used by the state throughout the year.

The 1970s were an exciting period of experimentation with seasonal, regional climate forecasting. California was working with private consultants on a program called Project Hydrospect, the goal of which was to use long-range weather forecasts to help with water supply management.

Researchers at Scripps (including Jerry Namais, who in the 1960s had developed monthly and seasonal forecasts at the U.S. Weather Bureau ) were making innovative forecasts, leveraging new computer capabilities in linear algebra (eg, inverting matrices!) that opened doors to objective analysis techniques such as relating EOFs of Pacific Ocean SSTs to California climate. ENSO indices had not yet been defined … but that’s another interesting story, perhaps one for another blog.

The very first ESP river forecasts were simultaneously being developed in the mid-1970s by a joint federal-state operations center that housed personnel from the State of California Department of Water Resources (CADWR) and the California-Nevada River Forecast Center (CNRFC) of the National Weather Service (NWS).

Flood forecasting was a federal responsibility, and in theory, longer-range forecasts were a joint activity. The two parts of longer range forecasts were:

  1. a continuous soil moisture accounting model (the Sacramento model, developed by NWS; Burnash et al, 1973) and
  2. the concept of combining estimated initial hydrologic conditions (IHCs) with future meteorological forecasts based on historical sequences or seasonal climate predictions to drive hydrologic simulations extending out to seasonal lead times.

A depiction of a seasonal ensemble forecasts from one of the first publications in which it was called ESP is below.

An ESP illustrated by JC Schaake in 1978, from “Extended streamflow prediction techniques: description and applications during 1977”, Proc. of the Climate Diagnostics Workshop. John Schaake is a co-founder of HEPEX.

There are a lot of ‘Fathers of ‘ This and That in science and engineering. Here, perhaps, we can recognize CADWR’s Joyce Peters as the ‘Mother of ESP Forecasting’.  That’s quite a legacy.

The ideation of ESP and initialization date of the first ESP forecast in the US is unclear, but the likely first operational ESP forecaster was a woman named Helen Joyce Peters.

Ms. Peters headed the State side of the joint flood forecasting program at the time, and was running the long-lead forecasts as well. Anecdotal reports suggest that her forecasts predated those from the NWS side of the center (made by Bob Burnash) by several weeks to months.

Ms. Peters was a groundbreaker in more than one way: she was the California DWR’s first female engineer as well as an internationally-renowned groundwater specialist. Others involved in the effort included consultants Jack Hannaford, Joe Burns, Bob Zettlemoyer from the State, and John Schaake, who joined the NWS Hydrology Laboratory (HL) in 1974. In the same year, Dave Smith of NWS coined the term Extended Streamflow Prediction, and the NWS HL soon after began developing an NWS version of ESP for use in other RFCs.

The two first major applications of ESP were both drought related – predictions made during the California drought and also for a smaller but intense drought in Virginia, affecting the Occoquan Reservoir, which formed part of the water supply for the Washington DC area. Based on the ESPs and other analysis techniques, probabilistic predictions for reservoir target level failures could be compiled (figure below). Today, we take such approaches for granted, but at the time they were quite innovative applications of stochastic methods in hydrology.

ESP-based failure probabilities for reservoir levels over a future 6 month period, given a specific reservoir release of 40 million gallons per day (from Hirsch et al., 1977).

It’s interesting that the first ESP forecasts were made just an hour up the road from the source of so much modern-day innovation at companies such as Google and Apple.  Is there something special in the water there?

In any case, ESPs — born in Sacramento, and focusing on the water supply drainages of the California Sierras — were due in no small measure to Joyce Peters, a little-known original forecaster and program lead. Ms. Peters passed away in 2002 after a remarkable career with DWR lasting 37 years.

NB: This reconstruction of the ESP origin is based on notes from interviews Tom Pagano (AU BOM) conducted with John Schaake, former Chief Scientist of the NWS Office of Hydrology, and on correspondence between Andy Wood (NCAR), Eric Rosenberg (Hazen and Sawyer), and Tom Pagano with Maury Roos, the former Director of the California Department of Water Resources. California’s State Climatologist, Mike Anderson, was also extremely helpful in providing digitized copies of Hydrospect Project reports from the mid to late 1970s, which are a fascinating read. Like any history based on long-ago memories and incomplete documentation, it is likely to be just one possible version of the actual events, and may contain inaccuracies. It is also possible that ESP evolved independently in other countries. Please send comments if you know more details of this history, or a related forecasting history that would be of interest to HEPEX readers. 

References

  • Burnash, R.J.C., Ferral, R.L., and McGuire, R.A. (1973). “A Generalized Streamflow Simulation System – Conceptual Modeling for Digital Computers,” U.S. Department of Commerce, National Weather Service and State of California, Department of Water Resources.
  • Day, G. (1985). “Extended Streamflow Forecasting Using NWSRFS.” J. Wat. Res. Plan. Mgmt., 10.1061/(ASCE)0733-9496(1985)111:2(157), 157-170.
  • Hirsch, R, J Schaake and D Sheer (1977). Assessment of Current Occoquan Water Supply Situation. Pub: # ICPRB-M-4, Interstate Commission on the Potomac River Basin.
  • Twedt, T. M., J. C. Schaake, Jr., and E. L. Peck (1977). National Weather Service extended streamflow prediction. Proc., Western Snow Conference, 52 – 57.
Posted in ensemble techniques, historical, seasonal prediction | 2 Comments

Searching for allies in the meteorological community: Trieste, 12-16 Sep., 2016

Contributed by Louise Crochemore and Massimiliano Zappa

As you all know, the reign of MEPEX has begun… The belligerent fools.

Prospective work already carried out in the HEPEX community since 2004 has proven that we may find allies in the meteorological community that may support our cause and future collaborations. To quote Martin Best, who has more pacifist views than the McFools clan:

« Firstly, we need to have a better understanding of the motivations and requirements within each community. We need to recognize that we all have strengths and weaknesses »

The greater good may also be in our favour :

« Society needs us to develop a complete end to end modelling system […] to give us accurate information on the global and […] terrestrial water cycle. »

For several years now, a delegation has regularly been sent to the headquarters of “MEPEX” to negotiate and defend the cause of hydrology.

  • “Headquarters?” — you may ask. But the EMS Annual meeting, of course!
  • And “Where is this?” — you may now ask. Well, this year, it will be in Trieste Italy, from September 12th to 16th.

A meeting will be organized during the week to discuss ways forward: ASI10 Interfacing hydrological and meteorological models in forecasting system

To quote again Martin Best: « by coming together we can be more than the sum of the parts. »

Volunteers may submit their proposal for collaboration (or their abstract, as the community often call it) by the latest 21 April 2016. Note! The deadline has been extended to 29 April 2016.


Major questions that the meeting aims to raise:

  1. What is the optimal coupling strategy of meteorological forecasting or climate models and hydrological models?
  2. How can additional information (e.g., remotely sensed data) be used in coupled systems?
  3. How can these systems be evaluated and the output post-processed?
  4. How should the forecasts be presented and what type of risk analysis can be used in supporting decision makers?
  5. Can hydrological extreme events be forecasted satisfactorily by coupled systems today?
  6. How does the scale affect the coupling strategy and the skill of the coupled systems?

And, who knows, maybe we can hope to create a “HMEPEX” in some future days, under the auspices of peace and collaboration!

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