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

First recording of surface flooding in London using CCTV cameras

On Friday 2nd of June 2017 Met Office issued a yellow warning of heavy rain with possible hail and lightning over London. Also Environmental Agency issued a number of flood alerts for London for the same period of time. This allowed us to test our newly setup system for recording open data CCTV images from London Transport Cameras (aka JamCams).

Following the flood alerts we setup to record all Transport for London (TFL) cameras which where within the main flood alert areas, these were 4 areas in London.

Figure 1. Areas selected for recording TFL CCTV camera images on 2nd of June 2017 corresponding to flood alerts from Environmental Agency.

This resulted in downloading images from just over 110 CCTV cameras accross from  the marked areas in Figure 1. Dowload started on many cameras at 2:30pm on 2nd of June 2017 and continued for 24h with an image downloaded every 5min.

Many of these images showed heavy rain as it passed over London on the afternoon of the 2nd June 2017; some cameras even captured images of lightning which was seen over North London but we didn’t capture any images of flooding in the four coloured areas in Figure 1.

Figure 2. Image of heavy rain on A23 Brixton Rd/Vassell Rd as seen by one of the CCTV cameras in London on 2nd July 2017 at 5:19pm

Figure 3. Image of lightning on captured on London CCTV camera at A12 East Cross Route on 2nd of June 2017 at 4:17pm

However, following the flooding allert on London for Transport site allowed us to capture surface flooding that happened on the North Circular road between 4-7pm resulting in traffic jams in the area.

Figure 4. Map of the surface flooding on the North Circular on 2nd of June 2017

The surface flooding was very localised and only one camera captured it, the one just below the blue circle in the Figure 4. We recorded both still and video images from this camera. In the video below you can see the surface flooding affecting the slip road going North.

We are currently setting up similar systems to download live traffic CCTV images from Leeds, Bristol, Exeter, Newcastle, Glasgow, and Tewkesbury.

Sewer network challenge at MathsForesees study group 2017

by Sanita Vetra-Carvalho

The second Maths Foresees study group was held on 3rd-6th April 2017, hosted by the Turing Gateway to Mathematics at the Isaac Newton Institute, Cambridge. The Maths Foresees network was established in May 2015 under the EPSRC Living with Environmental Change (LWEC) umbrella to forge strong links between researchers in the applied mathematics and environmental science communities and end-users of environmental research. The Maths Foresees events take a collaborative approach to industry problem solving where over the course of four days, mathematical and environmental scientists explored real challenges posed by companies operating in the environmental sector.

In this second event, there were five industry challenges presented to the participants (around 50 in total) from three companies: JBA, Sweco and Environmental Agency. All of the challenges this year were linked to flooding issues:

I joined the group interested solving sewer modelling challenge proposed by Sweco and presented by James Franklin. The urban flood model InfoWorks ICM (Integrated Catchment Modeling) by Innovyze that is used by Sweco, comprises a subsurface sewer network and a street-level road surface model. The two are coupled via manholes but smaller drains/gullies are not included since the exact locations of gullies and drains are not known (it would be very costly in manpower to locate them) and more importantly it would be computationally unfeasible to directly model gullies in InfoWorks model. As a consequence, the model does not represent floodwater drainage correctly. In a typical simulation, floodwater stays on the road surface and does not drain away as it should. This results in an inaccurate flood extents, particularly in urban environments (see an image below of a typical simulation of a storm).

A typical simulation using InfoWorks ICM: floodwater stays on the road surface and pools indefinitely rather than charging the network during the recession of a storm.

The challenge for the group was to see how we could improve the model representation of the collection network; that is how to represent gullies in the model to simulate a more realistic exchange (sinks and sources) of surface water between the sewer network and surface model.

Our group had two and half days to propose a solution. Our initial idea to couple a 2D surface shallow water model to a 1D sewer network model (also shallow water model) to model realistic fluid exchange between the two models turned out to be too difficult to accomplish in the limited time period. Hence, we concentrated our efforts on the main problem at hand, how to represent realistic sinks in the model without directly resolving gullies in the model. To this end, our group produced two 2D surface models: 2D shallow water model and 2D diffusive wave model. The second model was developed in parallel as in a future it would be easier to couple to a 1D drainage network. Our group run both models on an idealised road setting: 100m straight road with 3 manholes every 30m and 20 gullies every 10m, where directly resolved (see image below).

Representation of an idealised 100m road with gullies and manholes

We compared runs where we resolved gullies directly on the mesh every 10m on both sides of the road (the case which is computationally unfeasible for Sweco to run but is the most realistic) to line sink runs where we averaged the effect of the number gullies on the road and removed the surface liquid from the model at each gridpoint that is adjacent to the pavement. Both of our 2D surface models showed that the line sink representation of the gullies removed approximately the same volume of surface water in the model as directly resolving each gully in the model thus making line sink solution a realistic and computationally affordable to represent the effect of gullies in the model. While our solution lacked the two-way flow exchange between the surface model and sewer network we proposed that if implemented in the InfoWorks model the volume of water sunk through line sinks would become a source in the sewer network through the nearest manhole in the model. Our findings and the proposed solution to the Sweco challenge was positively received by James Franklin. A full report of our solution will be published on Turing Gateway to Mathematics site over next two months.

I very much enjoyed being part of the Maths Foresees study group 2017 and am very thankful to all the organisers at MathsForesees network and Turing Gateway of Mathematics for organising this event as well as Isaac Newton Institute for hosting it. It was very refreshing to be ‘locked’ into the Isaac Newton Institute alongside other participants to solve these challenges in a mentally very rich and inspiring environment. The event naturally offered a very fruitful ground for networking too. I would encourage any mathematician interested in solving environmental problems to take a part in any future MathsForesees events!

Our boards of brainstorming @MathsForesees event

Mathematics of Planet Earth Jamboree

 by Jemima Tabeart

On 20th-22nd March the Mathematics of Planet Earth Centre for Doctoral Training (MPE CDT) held its third annual Jamboree event. This is a celebration of the work of the staff and students of the CDT and includes seminars from industrial and academic speakers, as well as the opportunity for students to present their research. For the first time this year, the first two days of the Jamboree were used to host an Industrial study group. Representatives from EDF Energy and AIR Worldwide (catastrophe modelling for the insurance and re-insurance industry) posed real-world problems to cross-cohort groups of students, who then attempted to provide some new mathematical insight into possible solutions.

 

Our group was given a task by EDF Energy to investigate the interaction of extreme wind and rain events in the UK. EDF Energy’s assets in the UK include nuclear and other types of power plants, so understanding of extreme events is important in order to they can take appropriate safety measures. Currently extreme rain and wind events are considered separately, and we were asked to consider ways of determining how to define and deal with extreme wind-rain events. We were given hourly reanalysis data from the last 40 years, on a coarse 1 degree grid over the UK. The group split into two parts: one looking at more conceptual ideas about how extreme events can be caused by an interaction of factors, and the other considering the data provided.

 

Our part of the group identified some known extreme weather events, and focused on the data for these time periods. We looked at which events had both extreme wind and extreme rain, and mapped these to geographical locations to see where extreme wind-rain occurs most frequently. We also tried to see if there was a time lag between rain and wind events in the same location. Initial plots indicated that the most likely lag time was 0 hours, although this might be due to the relatively coarse resolutions. Other members of the group also suggested a method for combining the threshold values for extreme wind and rain to create a combined parameter. As well as a presentation of the main ideas that took place on the day to industry representatives, written reports will be sent to the respective companies so that they can take the suggestions further.

 

The study group was a great opportunity for cross-cohort work that brought together students with contrasting research interests. The challenge of producing something in a short amount of time is very different to what we normally expect as PhD students, and the ideas of getting stuck in straight away and not spending hours agonising over every decision is something that will be useful going forward. I really enjoyed working with real-world data and on problems outside my usual subject area – applying techniques I’ve learned during my PhD to other applications is very satisfying, and gives me the confidence that I am developing my transferable skills through my research!