Ellicott City security cameras could offer useful and real time flood information

Ellicott City security cameras could offer useful and real time flood information

by Sanita Vetra-Carvalho

We have come across an illustrating source of a network of security cameras capturing a flash flood in Ellicott City, Maryland, US on Sunday 27th of May 2018. The video is a collage of 12 cameras all located on or near the Main Street in Ellicott City. The information from these videos would have been useful at the time of the flooding.

The videos clearly show how the Patapsco River and two out of its four tributaries (Tiber River and Hudson River) rapidly swell and overflow. We see how this results in the Main Street also becoming a fast flowing river with water washing away cars, destroying buildings, and accumulating debris. The flood lasted only four hours but caused catastrophic damage to local infrastructure, residents property, and claimed a life of a National Guardsman [1,4].

Figure 1. The map showing Ellicott City, Maryland and adjacent rivers. Image credit USA Today.

 

The cameras were installed by a local property owner, Ron Peters and can be seen in this YouTube video:

 

The flooding event

A storm released nearly two months of rain, over 9 inches (24cm) in just two hours (3 to 5pm local time), which swept away several roads, cars and brought more than 10 feet (3.0 m) of rapidly moving water down Main Street in the Old Ellicott City [1]. The old city is a very urban area set in a valley next to Patapsco River and its four tributaries. Due to the urban landscape the rainfall has nowhere to go except for running down the valley to the main river.

This was the second 1-in-1000 flood event within two years in Ellicott City. Both 2016 and 2018 events claimed lives and caused millions of dollars in damage [1,4]. However, flooding is nothing new to this city.  The city officials are looking into introducing green areas in the city to allow the rain water to be absorbed into the ground reducing the surface runoff.

 

New flood alert system

Associate Professor Nirmalya Roy and his group from University of Maryland Baltimore County (UMBC) are working on using a network of temperature and liquid sensors and have produced a new flood warning system for Ellicott City [2,4]. They are also working on using the local flood related information from social media such as Twitter into the flood alter algorithm which warns public through loudspeakers in the city [3,4].

It is clear that the videos captured from these security cameras provide a rich source of water information of the rivers and the Main Street. Information such as water levels and surface velocities can be extracted from these videos [5] and used as part of an existing flood warning system or an independent one. Further, videos also capture additional information on floods and damage caused that is valuable to rescue teams, insurance companies etc.

[1] https://www.wypr.org/post/ellicott-city-flood-nothing-new
[2] mpsc.umbc.edu/wp-content/uploads/2018/12/BipendrBasnyat_Thesis.pdf
[3] https://userpages.umbc.edu/~nroy/UMBC%20prof%20from%20Ellicott%20City%20developing%20flood-warning%20system.pdf
[4] https://wtop.com/howard-county/2019/02/emergency-sirens-will-inform-residents-in-historic-ellicott-city-md-flood-zone/
[5] https://flood-obs.com/non-contact-monitoring/

Highlights of the EUMETNET Crowd Sourcing Workshop 2019

Highlights of the EUMETNET Crowd Sourcing Workshop 2019

EUMETNET, is a grouping of 31 European National Meteorological Services which is provides a framework for collaboration between its members in the meteorological and hydrological fields. You can find out more about EUMETNET and its missions here.

ON 12-13th of March 2019 EUMETNET held a Crowd Sourcing Workshop at the Met Office in Exeter, UK, which a number of us from DARE attended remotely. The workshop was attended by a large number of the EUMETNET members both in person and remotely.  The topics covered included:

  • description of the Met Office observation network (WOW) and their move to a cloud based data system;
  • the existing crowd sourcing platforms across the Europe (see the list below);
  • summaries of other recent crowd sourcing meetings/workshops;
  • data related issues such as data format, quality control, storage, data sources and legal issues.

From the various talks it was clear that there is a great opportunity for crowdsourced data to contribute to meteorological forecast accuracy, in particular to nowcasting and more timely warnings since observations had higher spatial resolution in the established crowd sourcing platforms. However, the collected data types and their quality control varied greatly between the various crowdsourcing platforms discussed. For example, e.g. AEMET, concentrate on collecting singular atmospheric observations which are characterised by being local, rare, of significant intensity and with the capacity to cause high social impact. While, the Met Office Weather Observation Website (WOW) system accepts all types of observations from various types of sources.

Three necessary condition for success with novel observations. Slide from Malcolm Kitchen (Met Office) talk at the EUMETNET Crowd Sourcing Workshop from 12-13th March 2019 at the Met Office, UK.

 

Distinction between crowd sourced and opportunity data, such as smartphone pressure measurements, car temperature data, aircraft data was also made. Leading to an important discussion on collection of such data which often requires collaboration with industry e.g. car manufacture, mobile network provider etc. Should companies release such opportunity data for the mutual benefit through improved forecasts and warning systems? A number of companies already release their data, however, these are exceptions rather than the norm currently. There is no coherent agreement on how this would be uniformly achieved in practice which remains an open question for the debate.

List of various crowd sourcing platforms discussed at the workshop:

From Germany to Brazil: on climate risk communication

by Javier García-Pintado

Last week, on 22-23 October 2018, around 230 scientists from the three ocean and climate related clusters of excellence in northern Germany met in Berlin in the joint conference on Ocean – Climate – Sustainability Research Frontiers. The participants brought in lively discussions within the context of scientific and societal action towards ocean and climate research. Apart from the discussions more oriented toward the basic climate science and technical aspects, from a personal standpoint (perhaps because of its distance from my own work), I found a number of presentations from “The Future Ocean” cluster in Kiel, which include scholars from politics, social science, philosophy and international law most interesting. Some of these presentations offered a window on the connection between climate change and global and local politics in countries (e.g.; as tropical islands in the Indian ocean, who generally rely on external aid) most affected by increasing sea levels and coastal erosion. In common, this class of talks indicated a need for improving the communication of climate and natural risk science to society. Actually, a huge component of the unpredictability in future climate projections comes from the societal component.

However, as analyzed in one talk in the conference, it seems that, ultimately, public opinion is mostly driven by what is shown on TV, and TV, public offer is in turn mostly driven by the economic powers. Thus, as described the writer Jose Luis Sampedro more than 6 years ago, “public opinion” (defined in Wikipedia as consisting of the “desires, wants, and thinking of the majority of the people”), is in reality the “opinion of the media” or the “opinion of the economic powers”. This clearly connects to the results of Brazil elections just yesterday and the new presidency, and so to the derived very uncertain future of the Amazon management. Apart from the risks to biodiversity, a further deforestation of the Amazon rainforest would make it impossible to cut carbon pollution and the aspirational target of no more than 1.5ºC global warming above pre-industrial temperatures set in the Paris climate agreement. Brazilian people (and they are not alone) seem either oblivious to the problem or convinced that they are not affected by it (even, as from a friend’s personal communication last week, it appears that some people in Brazil sadly believe climate change is an European hoax to take control over their rainforest). Generally rising sea levels and increased storm surge risks, as well as the extra energy accumulated in the Earth system in general (and ocean in particular, boosting atmospheric convection and associated flood risks), will surely lead to a further demand of online, continuously updated, risk information to face emergency situations in the future city. One can wish the best for Brazil and the Amazon, which is the best for the world. In any case, let’s hope that Copacabana is not swallowed in the sea before Rio is transformed into a resilient city.

Machine learning and data assimilation

Machine learning and data assimilation

by Rossella Arcucci

Imagine a world where it is possible to accurately predict the weather, climate, storms, tsunami and other computational intensive problems in real time from your laptop or even mobile phone – if one has access to a supercomputer then to be able to predict at unprecedented scales/detail. This is the long term aim of our work on Data Assimilation with Machine Learning at the Data Science Institute (Imperial College London, UK) and as such, we believe, it will be a key component of future Numerical Forecasting systems.

We proved that the integration of machine learning with Data assimilation can increase the reliability of prediction, reducing errors by including information with an actual physical meaning from observed data. The resulting cohesion of machine learning and data assimilation is then blended in a future generation of fast and more accurate predictive models. This integration is based on the idea of using machine learning to learn the past experiences of an  assimilation process. This follows the principle of Bayesian approach.

Edward Norton Lorenz stated “small causes can have larger effects”, the so called butterfly effect. Imagine a world where it is possible to catch “small causes” in real time and predict effects in real time as well. To know to act! A world where science works with continuously learning from observation.

Figure 1. Comparison of the Lorenz system trajectories obtained by the use of Data Assimilation (DA) and by the integration of machine learning with Data assimilation (DA+NN)

DARE first field trip to Tewkesbury

DARE first field trip to Tewkesbury

The Dare team went on a field trip last month! It was a well planned and executed trip – as you would expect from a group of mathematicians. It was also a very interesting trip for us since most of us have only ever used data (e.g. for improving forecasts) not collected it. Even better Tewkesbury area has become a sort of benchmark for testing new data assimilation methods, ideas, tools, observations, etc, and so many of us have worked with LisFlood numerical model (developed by a team led by Prof. Paul Bates at the University of Bristol) over the Tewkesbury domain. We have seen the river runs in the model outputs, watched the rivers Avon and Severn go out of banks in our plots, and investigated various SAR images of the area but we have never been to the area. We generally do not need to visit the area when working with the models, however, now that there was a chance to do so, it was no surprise that many of us were keen to go. And we did go like ‘d’ A-team:

Figure 1. ‘d’A-team have arrived!

 

However we had a more important reason for visiting too – we were going to the Tewkesbury area to collect metadata from a number of river cameras located near Tewkesbury town. These river cameras are high definition webcams owned and serviced by Farson Digital Ltd in various location over the UK. We had recently discovered that six of such cameras are within the LisFlood model domain and have captured the November 2012 floods in the area. With the permission from the Farson Digital Ltd, we have obtained hourly daylight images of the floods from 21st November 2012 to 5th of December 2012. Hence, the aim our trip was to obtain accurate (with errors of no more than few centimeters) positional information (i.e. latitude, longitude, height) of the cameras themselves as well as the positional information of a number of markers in the images for each of the cameras. We need this information to extract as accurately as possible water extents and water depth from these images using image processing tools (which we are currently working on).

Figure 2. Rivers Avon and Severn domain map in the LisFlood model with the six river cameras located where the red/white circles are positioned.

 

To take these measurements we had borrowed some tools from the Department of Geography at the University of Reading. We used a differential GPS tool (GNSS) to very accurately (on order of few centimeters) measured the position of a given point in 3D space, that is its latitude, longitude, and height above the sea level, however, it had to be used on the ground (e.g. could not measure remote or high points such as building corners where some cameras were mounted) and not be too close to buildings or large trees. To measure remote and high points we used Total Station, which allowed us to shoot a laser beam to the desired point to measure its 3D position in space.

Figure 3. Steve Edgar from the Environmental Agency showing masterclass with TotalStation.

 

We had planned to visit all six cameras within the space of the two days 16th and17th of April, however, despite our best plans and fantastic organisation skills we were too ambitious with our time and we had to drop the camera furthest from our base – the Bewdley camera (see map with camera positions in figure 2). Thus, on our first day, we took measurements from Wyre Piddle, Evesham, and Digglis Lock cameras, spotting ourselves live on the Farson Digital Ltd site.

Figure 4. Dare team spotted at the Evesham site live on Farson Digital Ltd river cameras on 16th of April.

 

We returned to our base – the Tewkesbury Park Hotel, to be joined by the Ensemble team from the Lancaster University. Ensemble Project is lead by Prof. Gordon Blair, and as Dare is funded by the EPSRC Senior Fellowship in Digital Technology for Living with Environmental Change. It was very interesting to meet the Ensemble project team and learn more in-depth about their work, future interests, and scope for the collaboration.

Figure 5. Prof. Gordon Blair (University of Lancaster) giving an overview of the Ensemble project and introducing his team.

 

On our second day, the Dare team visited the Tewkesbury camera while the Ensemble team learned more about the purpouse of the data collection and the Novermber 2012 floods in the area. Then we all jointly measured a large number of points at the Strensham Lock. In 2012 we all would have been totally sumberged in water in this picture since the flood waters completely swallowed the island on which the house is standing flooding the building along with it.

Figure 6. Dare and Ensemble project teams at the Strensham Lock.

 

Our grand finale was the meeting with the director of the Farson Digital Ltd Glyn Howells as well as a number of stakeholders who have commissioned the cameras we visited. It was very interesting for us to learn how the network of the river cameras was born from the need to know and understand the current state of the river for a variety of river users – fishermen, campers, boaters, etc. Also, how these cameras have become invaluable assets to many stakeholders for various reasons – greatly reducing the number of river condition related phone enquiries, monitoring river bank and bridge conditions, and so on.

Now a month later we have downloaded and processed the data we collected from these stations. In figure 7 we have plotted the data points we took at the Tewkesbury site, owned both by the Environmental Agency and Tewkesbury Marina (both of which we greatly thank for their support and assistance before and during our trip, especially to Steve Edgar from EA and Simon Amos and Bruno from Tewkesbury Marina). In the figure, the red dots are the camera positions – pre-2016 and current camera positions, and the black dots are all the other measurements we took using both the TotalStation and GNSS tools, which are plotted against the Environmental Agency lidar data with 1m horizontal resolution.

Figure 7. Locations of the point measurements from both Total Station and GNSS we took at the Tewkesbury town. Red dots are camera locations (pre-2016 and current positions), black dots are measurements of various reference points that can be seen from the camera. To make this image we used the Environmental Agency 1m horizontal resolution lidar data and LandSerf open source GIS software.

 

We are currently working on extracting the water extent from these images which we then will use to produce water depth observations. Our final aim is to see how much forecast improvement such rich source of observations offer, in particular, before the rising limb of the flood.

We are very thankful to Glyn Howells and the various stakeholders for permitting us to use of the images, allowing us to take the necessary measurements, assisting us on the sites, and joining at the workshop!

Our first DARE workshop

Our first DARE workshop

by Sarah Dance

Workshop participants

The DARE team organised a workshop on data science for high impact weather and flood prediction, held by the river at the lovely University of Reading Greenlands Campus in Henley-on-Thames, 20-22 Nov 2017. The workshop objectives were to enable discussion and exchange of expertise at the boundary between digital technology, data science and environmental hazard modelling, including

  • Data assimilation and data science for flood forecasting and risk planning
  • Data assimilation and data science for high impact weather forecasting
  • Smart decision making using environmental data

The meeting was attended by over 30 participants from  5 different countries. We had some great presentations ( to be made available on this webpage) and discussion. We came up with some recommendations to help promote and deliver research and business applications in the digital technology-environmental hazard area. We plan to write a meeting report detailing these recommendations that we hope will be published in a peer-reviewed international journal.  Watch this space!

 

Serving society with better weather and climate information.

Serving society with better weather and climate information.

by Sarah Dance

I have just come back from the European Meteorological Society 2017 conference in Dublin, where I was co-convenor for a session on Data Assimilation. It’s theme was Serving Society with better Weather and Climate Information. A key challenge for the meteorological communities is how best to harness the wealth of data now available – both observational and modelled – to generate and communicate effectively relevant, tailored and timely information ensuring the highest quality support to users’ decision-making.  The conference produced some highlight videos that sum up the activities better than I could!

Wetropolis flood demonstrator

Wetropolis flood demonstrator

By Onno Bokhove, School of Mathematics, University of Leeds, Leeds.

  1. What is Wetropolis?

The Wetropolis flood demonstrator is a conceptual, life installation showcasing what an extreme rainfall event is and how such an event can lead to extreme flooding of a city, see below in Fig. 1. A Wetropolis day is chosen to be 10s and it rains on average every 5.5min for 90% of the time during a Wetropolis day, i.e., 9s in two locations both in an upstream reservoir and in a porous moor in the middle of the catchment. This is extreme rainfall and it causes extreme flooding in the city. It can rain either 10%, 20%, 40% or 90% in a day; and, either nowhere, only in the reservoir, only on the porous moor or in both locations. Rainfall amount and rainfall location are randomly drawn via two skew-symmetric Galton boards, each with four outcomes, see Fig. 2. Each Wetropolis day, so every 10s, a steel ball falls down the Galton board and determines the outcome, which outcome we can follow visually: at the first split there is a 50% chance of the ball going to the left and of 50% to the right, and the next two splits one route can only go right with a 100% chance and the other one splits even with 50%-50% again; subsequent splits are even again. An extreme event occurs with probability 7/256, so about 3% of the time. In 100 wd’s, or 1000s, this amounts to about every 5.5min on average. When a steel ball rolls through one of the four channels of the Galton board it optically triggers a switch and via Arduino electronics each Galton board steers pump actions of (1,2,4,9)s causing it to rain in the reservoir and/or the porous moor.

Fig. 1. Overview of the Wetropolis flood demonstrator with its winding river channel of circa 5.2m and the slanted flood plains on one side, a reservoir, the porous moor, the (constant) upstream inflow of water, the canal with weirs, the higher city plain, and the outflow in the water tank/bucket with its three pumps. Two of these pumps switch on randomly for (1,2,4,9)s of the 10s `Wetropolis Day’ (SI-unit: wd). Photo compilation: Luke Barber.

 

Wetropolis’ construction is based on my mathematical design with a simplified one-dimensional kinematic model representing the winding river, a one-dimensional nonlinear advection diffusion equation for the rainfall dynamics in the porous moor, and simple time-dependent box models for the canal sections and the reservoir, all coupled together with weir relations. The resulting numerical calculations were approximate but led to the design by providing estimates of the strength of the pumps (1-2l in total for the three aquarium pumps), the length and hence the size of the design with the river water residence time typically being 15-20s, and the size of the porous moor. The moor visually shows the dynamics of the ground water level during no or weak rainfall as well as strong rainfall, and how it can delay the through flow when the conditions are dry prior to the rainfall by circa 2-3wd (20-30s). When the rainfall is strong, e.g., for two consecutive days of extreme Boxing Day rainfall (see movie in [2]), the moor displays surface water overflow and thus drains nearly instantly in the river channel.

Fig. 2 Asymmetric Galton board. Every Wetropolis day, 10s, a steel ball is released at the top (mechanism not shown here). The 4×4 possible outcomes in two of such boards, registered in each by 4 electronic eyes (not shown here either), determine the rainfall and location in Wetropolis, repectively. Photo: Wout Zweers.

Wetropolis’ development and design was funded as an outreach project in the Maths Foresees’ EPSRC Living with Environmental Change network [1].

  1. What are its purposes?

Wetropolis was first designed to be a flood demonstrator in outreach purposes for the general public. It can fit in the back half of a car and can be transported. Comments from everyone, including the public, are positive. Remarks from scientists and flood practitioners such as people from the Environment Agency, however, made us realise that Wetropolis can also be used and extended to test models and explore concepts in the science of flooding.

 

  1. Where has Wetropolis been showcased hitherto?

The mathematical design and modelling was done and presented early June 2016 at a seminar for the Imperial College/University of Reading Mathematics of Planet Earth Doctoral Training Centre. Designer Wout Zweers and I started Wetropolis’ construction a week later. One attempt failed (see June 2016 posts in [2]) because I made an error in using the Manning coefficient in the calculations, necessitating an increase of the channel length to 5m to have sufficient residence time of water in the 1:100 sloped river channel. Over the summer progress was made with a strong finish late August 2016 so we could showcase it at the Maths Foresees’ General Assembly in Edinburgh [1]. It was subsequently shown at the Leeds Armley Museum public Boxing Day exhibit December 8th, 2016 and also in March 2017. I gave a presentation for 140 flood victims for the Churchtown Flood Action Group Workshop, late January 2017 in Churchtown, on the science of flood including Wetropolis. We showcased it further at: Be Curious public science festival, University of Leeds; the Studygroup Maths Foresees (see Fig. 3), at the Turing Gateway to Mathematics, Cambridge; and, a workshop of the River and Canal Trust in Liverpool.


Fig. 3. Wetropolis at the Turing Gateway to Mathematics. Photo TGM. Duncan Livesey and Robert Long (Fluid Dynamics’ CDT, Leeds) are explaining matters.

  1. What are its strengths and weaknesses?

The strength of Wetropolis is that it is a life visualisation of probability for rainfall and flooding in extreme events combined, river hydraulics, groundwater flow, and flow control, since the reservoir has valves such that we can store and release water interactively). It is a conceptual model of flooding rather than a literal scale model. This is both a weakness and a strength because one needs to explain the translation of a 1:200 return period extreme flooding and rainfall event to one with a 1:5.5min return period, explain that the moor and reservoir are conceptual valleys where all the rain falls, since rain cannot fall everywhere. This scaling and translation is part of the conceptualisation, which the audience, whether public or scientific, needs to grasp. The visualisations of flooding in the city and the ground water level changes will be improved.

  1. Where does Wetropolis go from here?

Wetropolis’ revisited is under design to illustrate aspects of Natural Flood Management such as slowing-the-flow by inserting or taking our roughness features, leaky dams and the great number of such dams needed to create significant storage volume of flood waters, as well as the risk of their failure. Wetropolis will (likely) be shown alongside my presentation in the DARE international workshop on high impact weather and flood prediction in Reading, November 20-22, 2017. Finally, analysis of river levels gauges combined with the peak discharge of the Boxing Day 2015 floods of the Aire River leading to the extreme massive flooding in Kirkstall, Leeds reveals that the estimated flood excess volume is about a 1 mile by 1 mile by 1.8m deep (see [3] and Fig. 4). Storing of all this excess flood volume in 4 to 5 artificially induced and actively controlled flood plains upstream of Leeds seems possible. Moreover, it could possibly have prevented the floods. Active control of flood plains via moveable weirs is now considered, also in a research project with Wetropolis featuring as conceptual yet real test environment. (PhD and/or DARE postdoc posts are available soon.)

Fig. 4. Leeds’ flood levels at Armley Mills Museum: 1866: bottom, 2015: top, 5.21m. Photo O.B. with Craig Duguid (Fluid Dynamics’ CDT, Leeds) showcasing Wetropolis.

 References and links

[1] Maths Forsees UK EPSRC LWEC network [2] Resurging Flows, public page with movies of experiments, river flows and Boxing Day 2015 floods in Leeds and Bradford, photos and comments on fluid dynamics. Two movies on 31-08-2016 show Wetropolis in action. In one case two consecutive extreme rainfall events led to a Boxing Day 2105 type of flood. (What is the chance of this happening in Wetropolis?) Recall that record rainfall over 48hrs in Bingley and Bradford, Yorkshire, contributed for a large part to the Boxing Day floods in 2015. [3] ‘Inconvenient Truths’ about flooding . My introduction at the 2017 Study Group.

Coupled atmosphere-ocean data assimilation re-interpreted

Coupled atmosphere-ocean data assimilation re-interpreted

by Polly Smith

So my original plan for this blog was to write something about my research on coupled atmosphere-ocean data assimilation but then my PI Amos Lawless beat me to it with his recent post. I was pondering on how I might put a new spin on things when I remembered someone telling me about the Up-Goer Five challenge. The idea is to try to describe a complicated subject using only the thousand most common English words. A quick google search shows that as usual I am rather late to the party – plenty of people have already had a go and there are some brilliant descriptions out there.

This is what I came up with …

People want to know if it will be hot or cold, dry or raining today, tomorrow, next month, next year and further. People who work with large pretend worlds on big computers want to get better at telling everyone what might happen to help them plan ahead; to do this we need to look at what both the near-sky and big blue water are doing now and what they might do in time to come. To get the best guess going forward we have to start from the right point. My work is trying to help the big computer people move forward with this problem. This is hard because there are lots of things we do not know about how the real world near-sky and big blue water work and about the conversations they have together; they are joined to each other but not in an easy way. Seeing what the near-sky is doing can help us understand the big blue water and seeing what the big blue water is doing can help us understand the near-sky, but we can’t see everything all the time. Our approach is to use the things we already understand about how the near-sky and big blue water work together to make a small pretend world on a computer, and then add some numbers seen from the real world about what the near-sky and big blue water are doing close to now and what they were doing in the near past. We also give the computer a starting guess and tell it how good we think this first guess is and how good we think the seen world is – this is hard to know for sure but we are working on different ways to do this as best we can. The computer takes our directions and puts all this stuff together in an amazing way to give us an even better starting point from which we can build a picture of how things may look going forward. Things can change very quickly in the real world so finding exactly the right answer is not possible, but we can make a very good guess and we expect to get even better as we continue to work hard to learn more about the world.

This was far from easy, but a really useful exercise in describing science in a non-technical way; a great idea if you want to try and communicate your science to a wider audience. Why not give it a go?

“Weather” by Randall Munroe (https://xkcd.com/1324/)

 

 

Can observations of the ocean help predict the weather?

Can observations of the ocean help predict the weather?

by Dr Amos Lawless

It has long been recognized that there are strong interactions between the atmosphere and the ocean. For example, the sea surface temperature affects what happens in the lower boundary of the atmosphere, while heat, momentum and moisture fluxes from the atmosphere help determine the ocean state. Such two-way interactions are made use of in forecasting on seasonal or climate time scales, with computational simulations of the coupled atmosphere-ocean system being routinely used. More recently operational forecasting centres have started to move towards representing the coupled system on shorter time scales, with the idea that even for a weather forecast of a few hours or days ahead, knowledge of the ocean can provide useful information.

A big challenge in performing coupled atmosphere-ocean simulations on short time scales is to determine the current state of both the atmosphere and ocean from which to make a forecast. In standard atmospheric or oceanic prediction the current state is determined by combining observations (for example, from satellites) with computational simulations, using techniques known as data assimilation. Data assimilation aims to produce the optimal combination of the available information, taking into account the statistics of the errors in the data and the physics of the problem. This is a well-established science in forecasting for the atmosphere or ocean separately, but determining the coupled atmospheric and oceanic states together is more difficult. In particular, the atmosphere and ocean evolve on very different space and time scales, which is not very well handled by current methods of data assimilation. Furthermore, it is important that the estimated atmospheric and oceanic states are consistent with each other, otherwise unrealistic features may appear in the forecast at the air-sea boundary (a phenomenon known as initialization shock).

However, testing new methods of data assimilation on simulations of the full atmosphere-ocean system is non-trivial, since each simulation uses a lot of computational resources. In recent projects sponsored by the European Space Agency and the Natural Environment Research Council we have developed an idealised system on which to develop new ideas. Our system consists of just one single column of the atmosphere (based on the system used at the European Centre for Medium-range Weather Forecasts, ECMWF) coupled to a single column of the ocean, as illustrated in Figure 1.  Using this system we have been able to compare current data assimilation methods with new, intermediate methods currently being developed at ECMWF and the Met Office, as well as with more advanced methods that are not yet technically possible to implement in the operational systems. Results indicate that even with the intermediate methods it is possible to gain useful information about the atmospheric state from observations of the ocean. However, there is potentially more benefit to be gained in moving towards advanced data assimilation methods over the coming years. We can certainly expect that in years to come observations of the ocean will provide valuable information for our daily weather forecasts.

Figure 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

References

Smith, P.J., Fowler, A.M. and Lawless, A.S. (2015), Exploring strategies for coupled 4D-Var data assimilation using an idealised atmosphere-ocean model. Tellus A, 67, 27025, http://dx.doi.org/10.3402/tellusa.v67.27025.

Fowler, A.M. and Lawless, A.S. (2016), An idealized study of coupled atmosphere-ocean 4D-Var in the presence of model error. Monthly Weather Review, 144, 4007-4030, https://doi.org/10.1175/MWR-D-15-0420.1