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.

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

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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.

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

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.


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.)

Posted in columnist, data systems | 5 Comments

“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. 


  • 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 | 1 Comment

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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Hydrological forecasting at EGU 2016

Next Sunday, attendees from all over the world will start to arrive in Vienna and get prepared for the week-long annual event organized by the European Geosciences Union.

EGU2016 will take place from 17–22 April 2016 and, as in every year, there will be several scientific sessions of interest to the hydrological forecasting community. The program of the Hydrological Forecasting Sub-division of the Division on Hydrological Sciences is rich of about 200 contributions that will be presented as oral, poster and PICO presentations along 8 scientific sessions.

Here you find some guidance to help you find the sessions related to forecasting and see who is presenting what in Vienna:

MondayThere is a lot to see already on the first day of the conference:

  • 08:30–10:00 / Room 2.95: Flash floods and associated hydro-geomorphic processes – Flash flood monitoring, forecasting and warning is at the heart of this session, with presentations focusing, this year, on urban areas, ungauged sites and impact-damage analyses from recent events observed in 2015, such as the 2-3 November flood in Spain or the 15 October flood in France.

Just a short break for coffee and back to the same room for six more oral presentations before lunch:

At lunch time, we will have the Hydrological Forecasting Sub-Division Meeting:

12:15–13:15 / Room 2.17

It’s free and open to everybody interested in learning more about how the hydrological forecasting sessions are organized at EGU. In the agenda: feedback from the organization of the sessions in 2016, plans for next year, news from HEPEX, etc. If you are not coming to Vienna but want to leave a message to the group, just add a comment to this post or contact me.

In the afternoon, more oral presentations are planned and, for the 5th consecutive year, a game is proposed:

Another short break for coffee and back to the same room:

  • 15:30–17:00 / Room 2.95: Ensemble hydro-meteorological forecasting – Ensemble-based forecasting systems from all over the world and decision-making issues focusing several sectors are the main topics of the presentations here. If you think you are going to get tired of so many talks, well, I am sure this will not happen, but, just in case, you can find a nice way to relax while playing a game. Presented by Micha Werner, you are invited to make decisions under uncertainty: How sure must one be? That’s the question this year! Make sure to be in the room on time to play it.

If you played last year’s game (or also if you didn’t), you may be curious to learn more about the results that Louise Arnal will show in the poster A.189. You can also check the paper submitted to the HESS journal here. All games promoted by HEPEX can be freely downloaded from the Resources page.

On Monday, there is also a poster about HEPEX (A.194): a traditional “meeting point” for the forecasting community at EGU. Another tradition is the HEPEX social meeting @ EGU. This year, it will take place on Wednesday evening. Come to the poster and contact Hannah Cloke, Liz Stephens or myself for more details if you want to join us.

POSTER SESSION 17:30–19:00 / Hall A: poster presenters will be glad to talk to you. Come and enjoy relaxed discussions at the end of the day!

TuesdayOn the next day, two large forecasting sessions are scheduled:

  • 08:30–12:00 / Room 2.95: Drought and water scarcity – Starting with two talks to present the European 2015 drought from a climatological and a hydrological perspective, respectively, several works will follow on drought indicators, impact analyses, the economic value of drought information and the forecasting of droughts.

A break for lunch, and here we go with the PICO session of the Hydrological Forecasting sub-division:

  • 13:30–17:00/ PICO spot 1: Operational forecasting and warning systems for natural hazards – Here we will have 24 presentations of 2 min each on operational systems, followed by time to discuss in front of a screen and with the authors. If you ever dreamt about running your models and your forecasts operationally, this is the place to go on Tuesday afternoon. See how easy (or challenging!) operations can be.

POSTER SESSION 17:30–19:00 / Hall A: at the end of the day, posters from the Drought and water scarcity session will be displayed (check the list here).

WednesdayOne more day of sessions organized and co-organized by the Hydrological Forecasting sub-division:

A nice break for a well-deserved coffee and then back to attend sessions from other sub-divisions of the Hydrological Sciences (check here), before you head to the last co-organized session of the Hydrological Forecasting sub-division:

POSTER SESSION 17:30–19:00 / Hall A: poster presenters of the Wednesday sessions will be there. Come and join the group to meet new people and chat with old colleagues!

There’s much more of EGU on Thursday and Friday. Just check the Hydrological Sciences (HS) programme here.  Also, don’t forget the HS Division Meeting convened by Elena Toth on Thursday, 21 Apr, 12:15–13:15 / Room B.

See you very soon in Vienna!

Posted in activities, announcements-events, meetings | Leave a comment

Hydrological forecasting needs and practices in Brazil

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

Brazil is the largest country in South America, covering 8,515,767 km2, which corresponds to 47% of the continent. Two of the world’s major river basins are located in Brazil, namely the Amazon and La Plata, and much of its rivers and water resources are shared among Brazil and several South American neighborhood nations.


Figure 1. Brazilian municipalities, main hydropower dams and rivers (click on the image to enlarge)

Although part of the international attention on Brazilian water resources normally focuses on the Amazon basin, most of the country population is located in the South and South-east regions and along the coast, as can be seen by the distribution of municipalities in Fig. 1.

Important economical and societal impacts of flood hazards are frequent in Brazil. Some are related to flooding in the large Brazilian rivers and several others, to flooding in smaller rivers. Since the 70’s, more than 19 million Brazilians were affected by floods, according to the EM-DAT international disaster database.

Another important issue in Brazil is the use of water resources for energy production. A large amount of the large rivers are regulated by reservoir of hydropower dams (Fig. 1), and hydrological information is important not only for the optimization of energy generation but also for the operation that targets the mitigation of floods.

Role of flood forecast information

This brief description of Brazil highlights the important role that flood forecast information may have, but also some challenging features for the development of hydrological forecast systems. We can mention, at least, the following:

  • the continental scale of the region,
  • the transboundary nature of some basins,
  • the diversity of climates and hydrological characteristics,
  • the fact that flood hazards occur at multiple spatio-temporal scales and there is a need for forecast information at both, larger and smaller, rivers, and
  • the extensive river flow operation by hydropower plants.

Short and medium range flow forecasts are basically used in the Brazilian context for two purposes: (i) the scheduling of hydropower reservoirs operation and (ii) flood forecasting at vulnerable locations, with a greater emphasis on the first one.

Forecasts for hydropower generation

It is not possible to describe the Brazilian forecasting practices without talking about hydropower reservoirs and power generation, as some reservoirs operate to mitigate flood impacts on upstream and downstream cities (see, for instance, Fan et al., 2014; Araujo et al., 2014).

Under normal flow conditions, The National System Operator (Operador Nacional do Sistema, or ONS) uses forecasts of average daily inflow with lead times up to 14 days to schedule the hydropower generation in the system. These forecasts are generated by ONS or by the dam operation agents (responsible for the plants) themselves using rainfall-runoff models or, more commonly, PARMA models.

The system is managed through an interconnected national system, the “Sistema Interligado Nacional” (SIN). When the inflows to SIN reservoirs is not at normal conditions, but in a state of “attention”, “alert” or “emergency” (defined from the level of expected volumes and any violation of hydraulic constraints), the operation of the reservoirs is usually not controlled by ONS, but carried out by the agents of the local power generation plant.

For such cases, forecast information also has great value to support decision making, especially during floods when the anticipated knowledge about an event provides valuable lead time for reservoir operation. Some reservoirs such the ones from Três Marias HPP, Estreito HPP, Foz de Areia HPP, Segredo HPP, and even Itaipu HPP have operational restrictions to help reduce or avoid downstream and upstream floods, and ensure dam safety.

Flood forecasts at vulnerable locations

Another use of forecasts that is growing in Brazil relates to human, economic and sanitary impacts of floods. Flood inundation has caused large negative impacts in the last decades, and according to the Emergency Events Database EM-DAT (CRED, Université Catholique de Louvain, Brussels), Brazil is among the ten countries most affected by floods in the world.

Great advances are expected in the coming years concerning the development of flood alerts systems, especially after the federal government of Brazil established a Center for Natural Disaster Monitoring and Alert (CEMADEN), led by the Ministry of Science and Technology (MCT). CEMADEN aims at developing, testing and implementing monitoring and forecast systems for natural disasters in Brazil. However, since it is a recently created center, operational flood forecast systems are still not fully developed.

Most of the operational flood forecasting systems in Brazil are led by the Geological Survey of Brazil (CPRM). It operates forecasting systems at vulnerable areas in some rivers, as Doce (MG), Caí (RS), Taquari (RS), Parnaíba (Piauí), Muriaé (RJ e MG), Negro (AM), Acre (AC), and Branco (RR). The forecasts are available at the CPRM website in a system called “SACE – Sistema de Alerta Contra Enchentes.” These forecasts are performed using data-based models, and present generally good performance for short lead times, usually less than 3 days.

And what about ensemble forecasts?

Currently, there are several efforts to develop forecasting systems in Brazil, ranging from simple statistical models to state-of-the-art methods using distributed hydrological models coupled to ensemble meteorological forecasts.

Works such as Fan et al. (2014), Fan et al. (2015a, 2015b) and Schwanenberg et al. (2015) showed great possibilities and advantages for the use of ensemble forecasts, in comparison to the use of deterministic forecasts, as is currently done for flood anticipation and reservoirs operation (Figures 2 and 3). These works are however decentralized, as current hydrological forecasting systems are being developed for specific rivers at several different places (e.g., at universities, regional hydrologic centers and by the hydropower sector).


Figure 2. São Francisco, Tocantins, and Doce river basins, the test areas of Fan et al. (2015a)


Figure 3. Mean Continuous Ranked Probability Score (CRPS) results for the three tested locations by Fan et al. (2015a)  (click on the image to enlarge)

A lot more still to be done

Although there is know-how on state-of-the-art hydrological forecasts in Brazil, at this moment, it has not converted into a countrywide operational flood forecasting system.

There is not also a clear picture about the exchange of information between forecasting centers or, for example, between operational forecasts generated to be used by hydropower companies and forecasts generated to be used by local early flood warning systems for the same river basin – even though forecasting systems for hydropower reservoirs are, to some extent, intended to help flood warning and flood response.

Also, currently there is not a countrywide or continental forecasting system in Brazil, such as EFAS and AFFS, although proposals for the development of such systems have been discussed. We have also promoted discussions on the use of probabilistic forecasts for decision-making during national conferences, following the examples from the games developed under HEPEX (see a recent paper in Portuguese here).

We believe that the Brazilian scenario may change in next years, with the growth of regional and countrywide forecast systems through the development and transfer of technological knowledge and the growth of institutions as CEMADEN, which currently receives the information of the GLOFAS system.

Do you want to know more?

We strongly invite you to visit our poster at the Ensemble hydro-meteorological forecasting” session organized at EGU 2016. The poster is EGU2016-8608 and the display time will be Monday, 18 Apr 2016, 08:00-19:30 at board number A.192. We will not be there, but Maria-Helena Ramos will be glad to present more details to you!

Also, we would like to recommend the Chapter “Hydrological Forecasting Practices in Brazil” in the book “Flood Forecasting: A Global Perspective” by Thomas E Adams (Editor) and Thomas C. Pagano (Editor).

A list of references for this post can be downloaded here.

Posted in columnist, forecast users, operational systems | 5 Comments

Can the world of hydrology accept the truth? Let the reign of MEPEX begin!


Contributed by Dr. Meteo McFool and his meteorological accomplices


For too long, we have tolerated so called Hydrologists claiming to use their voodoo magic to make enhanced forecasts or claim they know anything about the water cycle. These so-called ‘scientists’, ‘engineers’ and ‘experts’ (seriously?) are dangerous as they talk to the public, decision makers and politicians, pretending to possess some esoteric knowledge about extreme events such as floods or droughts — without acknowledging that all their wisdom comes from the only true science:  meteorology.

Initiatives such as this pompous HEPEX have to be stopped, as only the pure scientific discipline of meteorology can be triumphant. It is time to give this deluded, doomed initiative a true focus and a real future … and rename it MEPEX!

Although the wisdom of MEPEX is obvious, here are 15 FACTS describing the necessity of the new regime:

  1. Hydrology IS NOT a science, just merely a ponderous extension of the Atmosphere. Actually, hydrology is really “the science of already solved problems”. Simple example: lot of rain == flooding; no rain == drought! How hard can it be??
  2. Hydrology is irrelevant! 0.04% of the global water is stored in the atmosphere and only meager 0.006% can be found in rivers. Meteorologists are also very good friends with the oceanographers, who take care of 97% of all the water on earth, so who are you?!
  3. Hydrological faux-scientists copy from superior meteorologists and then claim progress – no example necessary because we all know it after a glance at the scientific literature.  The hydrology journals basically just propagate the achievements of meteorologists but with some years of delay and loss of impact (factor).
  4. Even so, ‘hydrologists’ have somehow failed to learn from meteorologists about the need to apply the laws of physics – it is obvious that every river catchment can be easily modeled without all that frankly embarrassing empiricism and uncertainty.
  5. Hydrologist’s ‘knobology’ models resort to sketchy calibration and while numerical weather models are based on physics so (once parameterized and, ahem, just ever-so-slightly and carefully tuned and nudged to perfection) they just run and produce beautiful, physically harmonious output.
  6. Meteorology uses verification to check model output, which means we are actually seeking the absolute TRUTH. Hydrologists do not even bother to assess their forecasts, or at best just use slippery concepts like validation or benchmarking — just plain lazy!
  7. Meteorology uses BIGGER computers and has BIGGER office buildings, which is enough evidence for superiority.
  8. Meteorology is on the TV and radio every single day – Hydrology, rarely so.  If no journalist is taking it seriously, how can YOU?! Maybe it’s because the ‘water people’ can NEVER give a simple answer.  It’s always a tiresome ‘blah blah soil moisture blah blah rain-on-snow blah blah infiltration’ and never just ‘it flooded because it rained really damn hard for too long’! Again, it’s not brain surgery!  More like accounting.
  9. Meteorology is a true university subject taught at thousands of old and very prestigious universities. Hydrology is a hodge-podge pseudo-science that hides behind disciplines such as geography, civil engineering, forestry and many other derived-meteorology disciplines. Some insular anomalies on obscure campuses exist, but their universities don’t brag about them.
  10. Meteorology has been around since ancient Greece, whereas hydrology was invented by the ancient Egyptians who were clearly…clearly… erm… ok, you win that one. But still, they were merely engineers, not scientific geniuses like Aristotle!
  11. The British Queen acknowledges Meteorology (there is a Royal Meteorological Society!). Hydrologists in the UK have a British Hydrological Society which is not incorporated in the Royal Charter. Any monarchist can therefore only recognize the one true science.
  12. In Switzerland, a republic, the hydrological society is joint with the limnological society, while the meteorological society is acknowledged to be a science by itself.
  13. Hydrologists in many countries are so unimportant that they can only find work in agencies devoted to other scientific purposes, such as the ‘Geological Survey’ or the ‘Weather Service’, and they are so far down in the chain of command that most of their bosses have no idea what they actually do (and don’t care as long as they keep quiet).
  14. Even a lazy meteorologist can do a hydrologist’s job (e.g., to get out of the shift work), but hydrologists are not allowed anywhere near meteorology, as they have little hope of grasping and applying the elegant complexities of the superior science.
  15. In many countries hydrology and meteorology are managed by the same institute, and meteorology always comes first in the acronym SMHI, SENAMHI, NIMH, ….
    Well, ok, not always, but very often!

We can’t be even bothered to think of more reasons, it is common sense and plain obvious – simply ask the true meteorologist next to you.

Before citing this article we strongly suggest to check the author’s name and date of publication.

Posted in April fools! | 6 Comments