Wind generation in the UK during the summer of 2018

By Daniel Drew

The record breaking summer of 2018 has featured in a number of recent blog posts (link1 and link 2), but one area not discussed is the impact of the prevailing hot, sunny and calm conditions on the electricity system in the UK- particularly the level of wind power generation. I was able to experience this first hand as in the spring of 2018 I started a 1-year placement in the energy forecasting team at National Grid (as part of the UKRI Industrial Innovation Fellowships ).

Figure 1: The daily mean wind power output for Great Britain during the summer of 2018. Based on data from  www.gridwatch.templar.co.uk

The proportion of the UK’s electricity provided by wind power has been growing rapidly over the last 10 years from only 1.5% in 2008 to 17% in 2017 (more than double the amount provided by coal). Wind generation is typically lower in the summer months, in 2017 wind provided 12.9% of the UK’s electricity needs from June to August. Several media reports have speculated this figure will be a lot lower for 2018, however we have to wait for the official energy figures to be published by the Department for Business, Energy and Industrial Strategy to confirm this.

Initial data provided by GridwatchUK, suggests that between June and August this year the level of wind generation was generally low. Expressed in terms of capacity factor (energy production as a proportion of the theoretical maximum), the level of wind generation in the UK was approximately 19.0%. Additionally, there were several periods where generation was persistently low for a number of days. For example, from the 11th – 14th July the capacity factor of wind generation was below 10% for 74 consecutive hours.

Given the relatively short period of time the wind farms have been operating, it is difficult to place events like this into context using measured power output data. Fortunately, work carried out by University of Reading and National Grid  developed a method for creating a synthetic long term hourly time series of wind generation (1980-present) based on the current distribution of wind capacity. Using the data produced in this study, shows that while the summer 2018 wind generation is lower than 38-year summer mean of 21.0%, it is far from the lowest value in the dataset (16.6% based on the meteorological conditions experienced in 1983). Additionally, the period of persistently low generation experienced in July (74 hours below 10%) occurs on average twice per year across the 38-year period. In summary, based on the figures currently available, the level of wind generation during the summer of 2018 was lower than average but within the limits of a 38-year climatology.

Posted in Climate, Climate change, Historical climatology, Renewable energy, University of Reading | Leave a comment

Clouds, climate and the Roaring 40s

By Richard Allan

In our new research we have traced large and long-standing biases in computer simulations of climate, affecting the tempestuous Southern Ocean, to errors in cloud that emerge rapidly within the atmospheric models. Biases evolve over time through knock on effects that shift the location of the battering winds known as the Roaring 40s. Our new method combines detailed computer simulations with observations of energy exchanged between the oceans and atmosphere that allowed us to better understand how deficiencies in climate models emerge in this key region for climate. This offers a route to improve the complex simulations necessary to make reliable climate change projections of the future.

The Southern Ocean is a pivotal component of the global climate system yet it is poorly represented in climate simulations, with significant biases in upper-ocean temperatures, clouds and winds. It plays an important role in the uptake of excess heat and carbon dioxide generated through human activities. However most coupled atmosphere-ocean climate models have substantial warm biases in Southern Ocean Sea Surface Temperature (SST) (see Figure 1) that have been linked to a lack of reflective super-cooled liquid water clouds in simulations. Our work has helped to elucidate the link back from the SST biases to cloud-related errors in absorbed sunlight and we identified a slower response of the region of intense winds affecting the Southern Ocean that further modify the biases.

 

Figure 1: Warm biases in simulated sea surface temperatures cover the Southern Ocean (large orange region near the bottom of the map) (IPCC AR5 Chapter 9, Figure 9.2(b)).

In our study we find that coupled climate simulations with warm biases in the Southern Ocean also receive too much heat flux at the surface in simulations using just the atmospheric part of the model (Figure 1). This suggests deficiencies that develop rapidly in the atmosphere are strongly linked with the long-term climatological bias in the simulations. Further analysis identified that too much sunlight due to unrealistic cloud is primarily to blame, consistent with previous research.

Figure 2: Link between sea surface temperature (SST) biases in coupled CMIP5 simulations and surface energy flux bias in the atmospheric component of the simulations (AMIP5) from Hyder et al. (2018)

To interpret the results a detailed framework was developed that resulted in a candidate for longest methods section of the year award! We attempted to summarise the main points in a schematic where we assume SST biases are linked to the energy budget of the upper mixed layer of the ocean as similarly applied in studies understanding ocean temperature variability. A further finding is that although initial deficiencies in cloud develop rapidly in simulations, the overall biases also relate to a response in the location of the “Roaring 40s” or more specifically the latitude of maximum westerly wind. As can be seen in Figure 3 below, positional errors in this “zonal wind maxiumum latitude” (ZWML) are also correlated with errors in the surface energy fluxes in the atmospheric simulations.

Figure 3: Errors in coupled model “zonal wind maxiumum latitude” (ZWML) correlate with errors in the surface energy fluxes in atmospheric simulations from Hyder et al. (2018)

Importantly, further detailed analysis demonstrates that our interpretive framework can be applied in targeting improvements to climate simulations that avoid “pasting over cracks” where one bias compensates for another. This offers a route to further improve the climate model simulations that are vital in providing realistic projections of how climate will change over the coming decades. The work was led by colleagues at the Met Office, involved a collaboration of many scientists and was conduced as part of the NERC DEEP-C and SMURPHS projects. The detailed research is available as an open access research paper in Nature Communications.

 

Posted in Climate, Climate change, Climate modelling, Clouds, earth observation, Energy budget, Numerical modelling, Oceans, Solar radiation | Leave a comment

Why was the sky Orange?

By William Davies

I was sitting in my house one morning in October 2017, engrossed in what I was doing. Gradually I noticed that an eerie darkness was smothering the natural light in the room. I stopped and looked outside. The sky was a dark orange! What was going on and where could I go for answers?

Earth observation satellites! These are good for this sort of event. From my experience using remote sensing instruments to study the atmosphere I know the value of this resource. This link: https://earthdata.nasa.gov/earth-observation-data/imagery provides access to a range of data useful for seeing what is going on with our planet. To see what ‘Worldview’ could tell us about 16th October 2017 look at Figure 1.

Figure 1. Worldview satellite image from 16th October 2017

The first thing Figure 1 tells us is that ex-hurricane Ophelia was playing a part – that’s the swirl of cloud to the west of the UK. There is a saying – ‘Red sky in the morning, shepherd’s warning’. That’s because our weather systems usually come from the west and the low morning sun to the east colours them red, as explained further below. But there is more – compare the dirty air over the UK with the whiteness of the storm’s centre. This air was coming from the south west – from the dusty Sahara and from Portugal and Spain where there were reports of wildfires.

These dusty, smoky particles are referred to by scientists as ‘aerosols’ along with other particles such as salt from the sea and nitrates and sulphates from pollution. Aerosols have a direct and indirect effect on the Earth’s climate. Their indirect effect comes about by playing the part of condensation nuclei that cause clouds to form (Davies et al., 2010). An increase in condensation nuclei means an increase in cloud formation with a reduction in water droplet size. This leads to an increase in cloud reflectance of sunlight – a cooling effect. The increase in reflectance happens because the total surface area of the water is greater when spread over more droplets (Twomey, 1974). The direct effect is that sunlight is absorbed and scattered by these aerosols (Davies and North, 2015). When aerosols absorb sunlight, this increases the atmospheric temperature – a warming effect. Some of the scattered sunlight is reflected back into space and this will also have a cooling effect. Understanding ‘aerosol – cloud’ interactions and the way that aerosols absorb and scatter sunlight is crucial in our understanding of the climate.

The red sky is caused by the way that light is scattered. Blue light has a shorter wavelength than red light and is scattered more easily by the molecules in the air (this is why a clear sky appears blue). Red light has a longer wavelength than blue light and is not scattered as easily. The orange sky was caused by the contribution the aerosols were making to the way the light was being scattered.

Here at University of Reading I am working on two projects that study the effect of aerosols. The CLoud-Aerosol-Radiation Interactions and Forcing Year 2017 (CLARIFY) field campaign flew from Ascension Island in the south eastern Atlantic. This has delivered airborne, surface-based and satellite measurements which will improve representation of aerosols and clouds and reduce uncertainty in their radiative effects in climate models. The Copernicus Atmosphere Monitoring Service (CAMS) provides analyses and forecasts that address environmental concerns relating to the composition of the atmosphere. At University of Reading we are producing climate forcing estimates for CAMS but there are many other CAMS teams across Europe covering a range of service themes.

Figure 2.  A recent CAMS dust aerosol forecast

Figure 2 displays a recent forecast for dust aerosol where it can be seen that dust off the north west coast of Africa was being blown over Spain and France towards the UK. By clicking on the icon at the top right of the global map one can choose a different type of aerosol to view.

Figure 3. A recent CAMS biomass burning aerosol forecast

In Figure 3 we can see the smoky aerosols that are the focus of the CLARIFY project. These biomass burning aerosols from Africa are emitted in August and September by agricultural waste burning and forest clearing. We can also see smoke from the wild fires in Northern California.

When I looked at these aerosol forecasts on 16th October 2017 the presence of dust and biomass burning aerosol over the UK was confirmed.

This orange sky was due to a combination of Ophelia, Saharan dust and wildfires over Portugal and Spain and was an unusual event which generated a lot of interest in the media (see https://www.bbc.co.uk/news/uk-england-41635906 ). It serves to remind us of the importance of aerosol research and the effect that varying aerosol optical properties can have on sunlight and on our climate.

References

Davies, W. H., North, P. R. J., Grey, W. M. F., and Barnsley, M. J.,2010. Improvements in aerosol optical depth estimation using multiangle CHRIS/PROBA images. IEEE T. Geosci. Remote, 48, 18–24. https://doi.org/10.1109/TGRS.2009.2027024

Davies, W. H., and North, P. R. J., 2015. Synergistic angular and spectral estimation of aerosol properties using CHRIS/PROBA-1 and simulated Sentinel-3 data. Atmos. Meas. Tech., 8, 1719–1731. https://doi.org/10.5194/amt-8-1719-2015

TWOMEY, S. A. ,1974. Pollution and the Planetary Albedo. Atmospheric Environment, 8, 1251–56. https://doi.org/10.1016/0004-6981(74)90004-3

Posted in Aerosols, Atmospheric chemistry, Atmospheric optics, Climate, Climate modelling, earth observation, Environmental hazards, Numerical modelling, Remote sensing, University of Reading | Leave a comment

Climate change art and politicisation

By Max Leighton

Figure 1 “Ice Watch” by Olafur Eliasson at the Place du Panthéon. The blocks of glacial ice taken from Greenland melted away from 3rd to 12th December 2015, during the Paris COP21 international climate negotiations.

Artists have contributed to the understanding of many of our greatest challenges; from the wrath of conflict and the spread of disease, to explorations into what it means to be human. From the early 2000s, artists all over the world have begun to engage more directly with the poster-child of humanity’s 21st century issues: climate change. Grown out of the soils of environmental activism, climate change art has become an established genre in its own right, with the age of the Anthropocene now an inspiration for art practitioners, curators, and educators alike (Nurmis 2016). Collaborations between artists and climate scientists have radical potential to open and diversify how, we as a society, learn to live with climate change. These collaborations are creating “spaces of possibilities” (Kagan 2015) for open-ended conversations between artists, scientists and society.

The mountain of evidence under the disciplinary rubric of Global Environmental Change (GEC), raises considerable, urgent and uncertain questions for our societies to answer; from the political (e.g. Tschakert 2012), economic (e.g. Heal 2017) and cultural (Adger et al. 2015), down to the deep eternal human dilemmas typically wrestled with through philosophy, religion and mythology (e.g. Hulme 2014). Despite the important progress made on key challenges within climate science, persistent barriers remain around transitioning from awareness and concern to action, communicating within deeply polarized environments, and dealing with the growing sense of overwhelm and hopelessness (Moser 2016). Both artists and many climate scientists now share a joint concern for how the public engages with their work (Kagan 2015), and as Smith and Howe (2015: 201) caricature, with due respect to the scientific enterprise: “artists can scream, scientists can’t.”

There is increasing interest around narrative, visual and performing arts (Galafassi et al. 2018); for instance, a project I am currently involved with uses storytelling techniques to make sense out of the rich, but messy knowledge gained from an ongoing workshop series interrogating complex water-related issues with local government, the private sector, academics and civil society. Dozens of noteworthy exhibitions, such as Boulder (2007), London and Copenhagen (2009), Paris (2012), New York (2013), Boston (2014), and Melbourne (2015), have placed visual art specifically themed around climate change on the map. A number of performance art projects led by Arts House Melbourne, for example, have used role-play to simulate disaster scenarios with the public, such as a flood event, turning the exhibition building into an Emergency Relief Centre for 24-hours. This project foregrounded the role of artists as an alternative experimental lens, rather than adding them in as mere communicators, or at worst, propogandists (Kagan 2015); not limiting artists to ‘science communication,’ is fresh, even radical, and proving curiously promising (Robin 2018).

Whilst this blog fully endorses art engaging with climate change, practitioners must navigate a politically and culturally polarised environment. Artistic disciplines, and academia in general, are typically practiced by individuals who are politically liberal or left-wing. Around 50% of the general public supports right-wing or conservative parties, compared to less than 12% of academics (Carl 2017). This ideological homogeneity is likely, in part, a consequence of people who have a strong desire to regularly seek out new ideas and experiences (scored as trait openness on the Big 5 personality test) also tend to hold left-liberal beliefs. These individuals are often more attracted to careers in the creative industries and academia, which carries a risk of bias. Within the social sciences, for example, a noteworthy group of social psychology scholars have warned against a lack of political diversity in their field steering researchers away from important but controversial topics and embedding left-liberal values in research methods (Duarte et al. 2015). These potential risks are unlikely to be resolved quantitively or instrumentally, however, the purpose of this blog is to suggest that artists and climate scientists may do well to engage with other perspectives and political persuasions. In light of the current political situation in the UK with the EU Referendum and the currents of populism around the globe, even projects with no political motivation must still tread carefully (Nurmis 2016). We make great efforts to achieve diversity with respect to gender, class and race; going forward, we may well be wise to give attention to political diversity, particularly in the context of climate change.

 References

Adger, W. N., Barnett, J., Brown, K., Marshall, N., & O’brien, K. 2013. Cultural dimensions of climate change impacts and adaptation. Nature Climate Change3(2), 112.

Kagan, S. 2015. Artistic research and climate science: transdisciplinary learning and spaces of possibilities. Journal of Science Communication14(1), C07.

Galafassi, D., Kagan, S., Milkoreit, M., Heras, M., Bilodeau, C., Bourke, S. J., … & Tàbara, J. D. 2018. ‘Raising the temperature’: the arts in a warming planet. Current Opinion in Environmental Sustainability, 31, 71-79.

Heal, G. 2017. The economics of the climate. Journal of Economic Literature55(3), 1046-63.

Hulme, M. 2014. Climate change and virtue: an apologetic. Humanities3(3), 299-312.

Moser, S. C. 2016. Reflections on climate change communication research and practice in the second decade of the 21st century: what more is there to say? Wiley Interdisciplinary Reviews: Climate Change, 7(3), 345-369.

Nurmis, J. 2016. Visual climate change art 2005–2015: discourse and practice. Wiley Interdisciplinary Reviews: Climate Change7(4), 501-516.

Robin, L. 2018. Environmental humanities and climate change: understanding humans geologically and other life forms ethically. Wiley Interdisciplinary Reviews: Climate Change9(1), e499.

Tschakert, P. 2012. From impacts to embodied experiences: tracing political ecology in climate change research. Geografisk Tidsskrift-Danish Journal of Geography112(2), 144-158

Posted in Academia, Climate, Climate change | Leave a comment

Characteristics of cumulus population and microphysical properties observed over Southeast Atlantic

By Yann Blanchard

Figure 1. Cumulus in the vicinity of Ascension Island, in a 100 x 100km image (which is close to global climate model spatial resolution) from MODIS onboard AQUA (22 July 2016)

Shallow cumulus cover large areas in the trade-wind marine regions and are considered to play an important role in the ocean–atmosphere exchanges and in the Earth radiative energy budget. Their small size (typically few hundreds of meters, Figure 1) and the heterogeneity of cumulus fields make it very challenging for global climate models which have relatively coarse spatial resolution (from tens to hundred of kilometres). Therefore, sub-grid physical processes (such as mass flux transport and entrainment) need to be parametrised into the models. Recent intercomparison studies between several climate models suggest that cumulus parametrisation is a source of a large discrepancy amongst models, causing uncertainty on climate sensitivity. To improve the representation of cumulus in models, more observations, especially at high-resolution, are needed.

In this work, we are focusing on cumulus occurring at Ascension Island (8°S, 14°W, see Figure 1) in the Southeast Atlantic Ocean. This region is doubly interesting as regards cumulus study. First, the occurrence of cumulus is relatively high (between 40 and 60%) from January to August, as the island is located in the southeasterly trade-wind region. Secondly, a large amount of biomass burning aerosols is transported from Southern Africa over the island, which makes it also interesting to study the interaction between clouds, aerosols and radiation.

Figure 2. 3-D cumulus reconstructed field from Ka-band scanning radar on 17 July 2017 and its 2-D projection. The size of the domain is 7 x 4km.

Capitalizing on a method developed at University of Reading (Fielding et al., 2014), we used reflectivity scans measured by a Ka-band (35 GHz) scanning radar to reconstruct 300 non-precipitating cumulus cloud fields (see an example in Figure 2). Those fields allow us to address macrophysical (cloud size distribution, thickness and cloud cover) and microphysical properties at a 50-m resolution. One of the key findings of this work is that, for the first time, the cloud size distribution of observed 3-D cumulus fields is described and shows that cumulus population follows a simple relationship (power-law), in agreement with satellite previous observations in 2-D. We also found that liquid droplet size is slightly smaller than what was observed in other Atlantic and Pacific regions. This is consistent with the presence of biomass burning aerosols that interact with clouds. We expect this unique dataset to help to improve our understanding of cumulus physical processes and to aid the low-cloud parametrisation efforts.

Reference

Fielding, M. D., J. C. Chiu, R. J. Hogan, and G. Feingold, 2014. A novel ensemble method for retrieving properties of warm cloud in 3‐D using ground‐based scanning radar and zenith radiances. J. Geophys. Res. Atmos., 119, 10,912–10,930, doi: 10.1002/2014JD021742.

Posted in Aerosols, Atlantic, Atmospheric chemistry, Climate modelling, earth observation, Numerical modelling, Oceans, Remote sensing, Solar radiation, University of Reading | Leave a comment

Sting jets in winter storms : how do the winds get so strong?

By Ambrogio Volonté

Figure 1: Windstorm Tini (12 Feb 2014) passes over the British Isles bringing extreme winds. A sting jet has been identified in the storm. Image courtesy of NASA Earth Observatory

The arrival of a winter storm battering the British Isles with strong gales and widespread rain might well seem an unfamiliar sight after the long spell of warm and settled weather that we have just experienced this summer. However, I am sure none of us has forgotten that these storms are common weather features here in the UK where winter seasons can get rather stormy, as 2013-2014 reminded us (see link here).

Among the most damaging phenomena that can be associated with winter storms  there is one, a strong descending air stream called sting jet , that in recent years has started to receive a lot of attention in the research community and in the media. A sting jet was firstly formally identified in the Great Storm of 16 October 1987 and in several other storms since then and, as discussed in a previous blog entry ,there are indications that their frequency, along with the associated wind risk, will increase in a warmer climate.

The Department of Meteorology has historically been and still is at the forefront of this research topic, whose current state of knowledge is reviewed in Clark and Gray (2018). In particular, in the last decade observational, modelling and climatological studies confirmed that sting jets can occur in intense extratropical cyclones in which a gap opens between the cold front and the back-bending warm front. It is in this frontal fracture region that the sting jet descends and accelerates, causing near-surface strong winds that are neither caused by the cold nor by the warm conveyor belt.

Figure 2:  3D (lon-lat-pressure) animated view in an earth-relative reference frame of sting-jet (green) and cold-conveyor-belt (blue) airstreams and wind speed at 850 hPa (shading, ms−1) from model simulations of windstorm Tini. (Volonté et al., 2018)

The main area of debate concerns now the dynamics of sting jets: how do they form, descend and accelerate? Our work (Volonté et al., 2018) addresses these questions using numerical weather prediction simulations of a sting-jet‐containing storm (windstorm Tini, see Figure 1). Through the use of Lagrangian trajectories (Figure 2), vorticity budgets and frontogenesis diagnostics we assess the relative importance of the release of mesoscale instabilities and synoptic‐scale cyclone dynamics. These simulations highlight the presence of a sting jet, whose descent and acceleration are initially influenced by sublimation and then largely driven by the release of mesoscale instabilities on the airstream. Figure 3 shows the mechanism playing a major role in the onset of these instabilities, with frontal circulations in the cloud head associated with combined tilting and stretching of vorticity on the sting jet. Vorticity and frontogenesis fields form a narrow slantwise banded structure in the cloud head, different from the widespread frontolysis expected from the large‐scale dynamics alone in the frontal‐fracture region.

This mechanism enhances the strong winds already generated in the area by the synoptic-scale cyclone dynamics and does not develop in simulations with insufficient model resolution, as our study shows. In fact, while the sting jet undergoes a process of destabilisation that strengthens its descent and acceleration in the higher‐resolution simulation, this process does not occur in the sting jet produced by a coarser‐resolution simulation, resulting in weaker winds and no instability generation or slantwise banded structures.

Figure 3: Schematic showing the mechanism leading to the onset of mesoscale instabilities on the sting jet. Horizontal vorticity is generated in the frontal zone and subsequent tilted onto negative vertical vorticity (associated with  mesoscale instabilities) along the sting-jet trajectory. (Volonté et al., 2018)

This analysis reveals the synergy between the paradigms of sting jet occurrence through the release of mesoscale instabilities and synoptic‐scale cyclone dynamics. Although this is a substantial step in understanding the mechanisms driving the formation and evolution of sting jets, further work is still necessary. These results have been obtained via the analysis of a case study, albeit a very clear one, and so their robustness needs to be assessed in a more general framework. For this reason, idealised simulations of sting-jet containing cyclones are currently being analysed. By this investigation we aim to shed light on the importance of the aforementioned enhancement mechanism in sting-jet storms with different properties, along with assessing the dependence of sting-jet occurrence and strength in different environmental conditions.

References:

Volonté, A. , Clark, P. and Gray, S.,2018. The Role of Mesoscale Instabilities in the Sting‐Jet dynamics of Windstorm Tini. Q.J.R. Meteorol. Soc.. Accepted Author Manuscript. doi:10.1002/qj.3264

Clark, P. and Gray, S.,2018. Sting Jets in extratropical cyclones: a review. Q.J.R. Meteorol. Soc.. Accepted Author Manuscript.  doi:10.1002/qj.3267

Posted in Climate, Climate change, extratropical cyclones, Monsoons, Numerical modelling, sting jet, University of Reading, Weather, Weather forecasting | Leave a comment

Summer temperatures 2018 – the ‘new normal’?

By Professor Sir Brian Hoskins (Grantham Institute, Imperial College London and Emeritus Professor at the University of Reading department of Meteorology) and Stephen Belcher (Met Office Chief Scientist and Visiting Professor at the University of Reading department of Meteorology)

Figure 1. Hyde Park, London, in a heatwave

There can be no doubt that the summer of 2018 has been remarkable both in the UK and across the world. Following an appearance on BBC Newsnight, in which the presenter Emily Maitlis asked if current temperatures can be considered the ‘new normal’, Professor Sir Brian Hoskins  and  Professor Stephen Belcher give their perspective of the heatwave and its connections to climate change.

In the UK the hot weather has been with us on and off since April. Some parts of East Anglia and southeast England have had virtually no rain in more than 55 days, and we may see our all time highest temperature record of 38.5°C fall by the end of this week.

The Arctic Circle has seen temperatures top 30°C, including at Badufoss and Makkaur in Norway, and in Finland temperatures have hit 33.4°C.

Meanwhile in Japan on Monday, the city of Kumagaya reported a new record temperature for the country, 41.1°C, and temperatures have exceeded 40°C in central Tokyo for the first time ever and there have been reports of many people being taken sick with heat stroke.

Naturally people are asking whether this is a result of climate change – is this the ‘new normal’. So what can we say?

Well, the atmospheric patterns leading to the UK heatwave do occur in the natural cycles in the weather, but they have been unusually persistent. The jet stream has weakened and got stuck to the north of the UK, with high pressure settled over the UK and Europe. In the summer such a pattern leads to dry soils, which means that if the sunny weather continues the energy of the sun is not used up in evaporating water and the temperatures rise even more.

In addition, we’ve seen a background of global warming due mostly to increased atmospheric greenhouse gases, with global mean temperatures rising more than 1°C above pre-industrial levels, and even more so over the northern continents. The natural cycles of weather mean that we shouldn’t expect heatwaves like this to happen every year but, when we do experience them, the warmer world means that there is an increased risk of even higher temperatures.

In 2003 Europe also experienced a pronounced heatwave. Research led at the Met Office showed that greenhouse gas concentrations in the atmosphere doubled the chance of the temperatures recorded in 2003 compared to what we’d expect in a pre-industrial world. This research also concluded that by the 2040’s the temperatures we saw in Europe in 2003 could be fairly normal in summer. We have updated this prediction with more recent data, and found that this prediction is still on track: the extreme temperatures we saw in the summer of 2003 can be expected to occur more regularly in Europe by the 2040s.

Figure 2. Summer mean temperatures anomalies over Europe (area in enclosed box) from CRUTEM4 observations (black), climate model simulations from CMIP5 (following RCP8.5) which include all forcings including greenhouse gases (red) and with only natural forcings (green). If greenhouse gas emissions are reduced to zero by 2050 the growth in temperature would cease.

At the Met Office, in collaboration with the universities, scientists are carrying out a detailed analysis of this particular heatwave and its expression in a warming world. Scientists are aiming to understand why the weather pattern this summer was so persistent, and to what extent this persistence may be influenced by human-induced climate change, as well as the role of global warming by greenhouse gases in raising the temperatures experienced in the heatwave. Findings will be published later in the year.

The temperatures we are currently experiencing may not yet be the ‘new normal’, but within a few decades they could be.

[Image credit: Stephen Craven]

 

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Exploring the impact of Gulf Stream temperature biases on the global atmospheric circulation

By Robert Lee

The climate state in numerical models often have differences when compared to a climatology from observations. These differences are often termed ‘biases’ and can be considered as a kind of error or deficiency in the model. These biases are often caused by poor representation of various physical processes in the models. This poor representation in turn can be caused by a number of factors, including: poor resolution (the number of gridpoints in the model), poor parameterizations (often derived empirically to fit often limited observational data), or poor knowledge of the process itself.

Atmospheric climate model biases have been shown to be sensitive to large-scale sea surface temperature (SST) biases, for example in the North Atlantic–European region (e.g. Keeley et al. 2012; Scaife et al. 2011). The more recent generations of climate models have reduced many of these large-scale SST biases, for example in this same mid-North Atlantic region in the UK Met Office Global Coupled 2 (GC2) model (Williams et al. 2015). However, despite improvements on the largescale, spatially smaller regions of SST biases remain and when they are located in regions of deep atmosphere–ocean interactions, there is potential for a knock-on chain-reaction of biases.

The GC2 model is a popular and well regarded model and can be configured for different Met Office applications including the seasonal forecast system (GloSea5), decadal prediction system (DePreSys3) and climate projection system (HadGEM3). It also has multiple spatial resolution configurations options, with one of the most popular being around 60km grid spacing. This version has a warm bias of up to almost 7°C in the Gulf Stream SSTs in the winter season (Figure 1b) just north of where the Gulf Stream leaves the US East Coast at Cape Hatteras heading northeast towards Europe (Figure 1a). This bias is originating within the ocean part of the model but is not seen in a higher resolution version. Hewitt et al. (2016) suggested it may be at least in part due to insufficient resolution in the ocean.

Figure 1. (a) Sea surface temperatures in the ERA-Interim reanalysis, with values very similar to observations, showing the Gulf Stream with the tightest SST gradients extending east-northeast from Cape Hatteras. (b) The GC2 coupled model bias relative to ERA-Interim, showing the largest SST bias just north of the Gulf Stream by the US Eastern Seaboard. (c & d) Two of the three experimental boundary boxes with their SST differences added onto the background SST in the experiments.

This region of SST biases is associated with enhanced surface heat flux biases as extra heat is transferred from the sea surface into the atmosphere in the model. In a new study by Lee et al. (2018) we explore the role of this SST bias, focusing on the atmospheric response by performing three experiments. These experiments are known as ‘sensitivity experiments’, where the SST biases are imposed on an atmosphere-only configuration of the model over a small (Figure 1c) and medium (Figure 1d) section of the Gulf Stream, and also the wider North Atlantic.

We found that the atmospheric dynamical response to this extra Gulf Stream heating (and associated shifting and changing SST gradients) is to enhance vertical motion (Figure 2), particularly during the periods when storms pass over. We found this dominated over other mechanisms for dissipating the extra heating over other possibilities including a linear local meridional wind response (as suggested by more theoretical studies e.g. Hoskins and Karoly 1981, Hendon and Hartmann 1982, and Hall et al. 2001) or via a change in the storm track activity transporting heat polewards (e.g. Hoskins and Valdes 1990).

Figure 2. A north-south vertical cross section through the atmosphere over the Gulf Stream showing vertical motion (colour shading) and eastward wind jet stream (line contours, m/s): (a) in ERA-Interim, showing a narrow section of ascent directly above the observed Gulf Stream; (b) in the GC2 coupled model showing a broader and stronger region of ascent, particularly over the region of large SST bias; (c) the additional vertical ascent resulting from the ‘medium’ sized box SST bias added in to the atmospheric model.

We found the response to this extra heating affects the atmosphere not only locally over the Gulf Stream but also in remote regions of the Northern Hemisphere, thereby partially reproducing some of the biases present in the full atmosphere-ocean coupled configuration. This chain of impacts spreading from the Gulf Stream region is able to travel around the hemisphere via an atmospheric wave train, known as a Rossby wave, with a wavenumber 5.

Figure 3. (a & b) Geopotential height at 500hPa in the mid-troposphere (nearly 5km above sea level) as a proxy for large-scale circulation differences, shown as (a) the GC2 coupled model bias and (b) the ‘small’ sized box SST bias experiment, partially reproducing the negative bias over the central North Pacific and Scandinavian regions. (c) The anomalous Rossby wave train produced in the ‘medium’ sized box SST bias experiment.

The enhanced ascent (often in the storms), and wave response pathways may have implications for the ability of models to respond correctly to variability or changes in the Gulf Stream. Despite representing only a small fraction of the total wave activity, these wave-5 Rossby waves have been shown to respond sensitively to changes in forcing (Simpson et al. 2016), with important implications for regional climate. Better global prediction requires particular attention to be paid to reducing any large western boundary current SST biases in such highly coupled and sensitive regions, such as the Gulf Stream. Therefore, a focus on reducing the origins of the ocean and SST biases in these regions of high ocean–atmosphere interaction may also reduce some of the global atmospheric biases in coupled global climate models, serving to highlight and direct future development and improvement priorities.

References

Hall NMJ, Lin H, Derome J, 2001. The extratropical signal generated by a midlatitude SST anomaly. Part II: Influence on seasonal forecasts. Journal of Climate, 14(12), 2696–2709. https://doi.org/10.1175/1520-0442(2001)014<2696:TESGBA>2.0.CO;2

Hendon HH, Hartmann DL ,1982. Stationary waves on a sphere: sensitivity to thermal feedback. Journal of Atmospheric Science, 39(9), 1906–1920. https://doi.org/10.1175/1520-0469(1982)039<1906:SWOASS>2.0.CO;2

Hewitt HT, Roberts MJ, Hyder P, Graham T, Rae J, Belcher SE, Bourdallé-Badie R, Copsey D, Coward A, Guiavarch C, Harris C, Hill R, Hirschi JJM, Madec G, Mizielinski MS, Neininger E, New AL, Rioual JC, Sinha B, Storkey D, Shelly A, Thorpe L, Wood RA, 2016. The impact of resolving the Rossby radius at mid-latitudes in the ocean: results from a high-resolution version of the Met Office GC2 coupled model. Geoscientific Model Development, 9(10), 3655–3670. https://doi.org/10.5194/gmd-9-3655-2016

Hoskins BJ, Karoly DJ ,1981.  The steady linear response of a spherical atmosphere to thermal and orographic forcing. Journal of Atmospheric Science, 38(6), 1179–1196. https://doi.org/10.1175/1520-0469(1981)038<1179:TSLROA>2.0.CO;2

Hoskins BJ, Valdes PJ, 1990. On the existence of storm-tracks. Journal of Atmospheric Science, 47(15), 1854–1864. https://doi.org/10.1175/1520-0469(1990)047<1854:OTEOST>2.0.CO;2

Keeley SPE, Sutton RT, Shaffrey LC ,2012. The impact of North Atlantic sea surface temperature errors on the simulation of North Atlantic European region climate. Quarterly Journal of the Royal Meteorological Society, 138(668), 1774–1783. https://doi.org/10.1002/qj.1912

Lee RW, Woollings TJ, Hoskins BJ, Williams KD, O’Reilly CH, Masato G , 2018. Impact of Gulf Stream SST biases on the global atmospheric Circulation. Climate Dynamics. In press. https://doi.org/10.1007/s00382-018-4083-9

Scaife AA, Copsey D, Gordon C, Harris C, Hinton T, Keeley S, O’Neill A, Roberts M, Williams K ,2011. Improved Atlantic winter blocking in a climate model. Geophysical Research Letters. https://doi.org/10.1029/2011GL049573

Simpson IR, Seager R, Ting M, Shaw TA, 2016. Causes of change in Northern Hemisphere winter meridional winds and regional hydroclimate. Nature Climate Change, 6(January), 65–70. https://doi.org/10.1038/nclimate2783

Williams KD, Harris CM, Bodas-Salcedo A, Camp J, Comer RE, Copsey D, Fereday D, Graham T, Hill R, Hinton T, Hyder P, Ineson S, Masato G, Milton SF, Roberts MJ, Rowell DP, Sanchez C, Shelly A, Sinha B, Walters DN, West A, Woollings T, Xavier PK ,2015.  The Met Office Global Coupled model 2.0 (GC2) configuration. Geoscientific Model Development, 8(5), 1509–1524. https://doi.org/10.5194/gmd-8-1509-2015

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What a summer!

By Ben Cosh

What a summer it has been so far. The data is brilliant when it is like this. Stephen Burt keeps an eye on it and has filled me in on the (nearly) record-breaking numbers we’re seeing.

It’s been hot.

The last three weeks average daily maximum temperature is more than 5 degrees hotter than normal. On the hottest day of the summer so far (1st July) we reached 30.8C and we’ve nudged above 30C a few of times.

But we’re a little way off really big records. Even last year we reached 32.5C on 21st June and the hottest maximum in our records is 36.4C from 3rd August 1990. In 1976 we got to 30C for 14 consecutive days, and in 2003 we did so for 6 consecutive days. I remember that week in 2003 because my mother-in-law was visiting from her home in Atlanta. Although 30C is commonplace where she lives, our lack of ubiquitous air conditioning made London almost unbearable!

It’s also been sunny and dry.

We had the second sunniest May since our records began in 1956, with 265 hours of sunshine. June had a third more sunshine-hours than normal with 253 hours. And in the last three weeks (the 21 days to Wednesday 11th July) we’ve had 261 hours of sunshine. That’s 12.44 hours a day. Only 1976 has a sunnier three-week period on record.

As I write this on 13th July, we’ve had no rain at all since 17th June. That’s 25 days and counting. This is our longest dry-spell for 21 years, since a 31-day period with no rain in 1997. I wonder if we’ll make it to the record of 37 days from… you’ve guessed it… 1976.

I am privileged to be the Head of the University of Reading School which includes our world-leading, globally-important department of Meteorology. But I watch the weather like most people do and post ad hoc forecasts (drawn from the main services) to our village Facebook group. There has been little point for the last six weeks though. There are only so many ways you can say: It’s going to be hot and sunny and dry again.

The Met Office and Meteogroup suggest this trend is going to continue for the next couple of weeks or so.

Perhaps a shower or two will creep in.

At the moment, that would be a big story round our way!

 

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A newcomer’s reflections on the fourth Lusaka Learning Lab

By Max Leighton (Social Research Assistant for Professor Ted Shepherd)

Figure 1: Lusaka participants recording a video message for the Maputo Learning Lab team.

The fourth Lusaka Learning Lab took place on the 17-18th April 2018, which is where I joined the Future Resilience for African Cities and Lands (FRACTAL) party. Albeit a little late at number four, a fresh pair of eyes can be useful to point out ‘the wood from the trees’ – so this will be my aim here. The first morning started with a diverse thirty-strong group bustling around a circle; water and energy technocrats, officials from Lusaka City Council, a host of community representatives, academics and a spirited facilitator.

We introduced ourselves with various members of the group giving updates on their work inviting others to get involved with future projects. There seemed to be a real sense of togetherness and enthusiastic Q&A sessions followed each update. The atmosphere was relaxed and informal, but purposeful.

It was hard to tell, however, if the trade-off between consensus building within the group, and allowing tensions to surface, was well struck. That said, two energetic debates arose from the two keynote presentations. The first was in response to the 19th statutory instrument of 2018 (SI 19) which enacts groundwater regulation into Zambian national law for the first time; the smallest plots of land issued by Lusaka City Council are smaller than the new minimum distance between boreholes and pit toilets specified in SI 19. The second between a Community-Based Organisation representative and an official from Lusaka City Council escalated into a lively debate involving a number of participants. All debaters seemed decidedly frank, suggesting there was genuine space for disagreement at the learning lab, despite the commitment to consensus.

As part of the lab outputs, there are four co-produced policy briefs – (1) flooding, (2) groundwater pollution, (3) groundwater levels and (4) water supply – which are in the final stages of completion. Time is never enough, so the briefs on groundwater levels and water supply were selected to be the meat for the two days.

Each participant brought their respective knowledge and experience to interrogate the two policy issues, as well as using the information from the Climate Risk Narratives (shown in Figure 2) as a ‘conversation starter’. The narratives distil what is known from climate model simulations (CMIP5) to inform three plausible narratives of the future climate – a little like the design fiction series Black Mirror which imagines plausible dystopian futures based on current trends and is also met with intense discussions about the way the world will be.

Figure 2: Climate Risk Narratives representing three possible future scenarios derived from CMIP5 over the next few decades for the Lusaka region.

Each narrative starts from the possible changes to the natural system and is then contextualised with the human-oriented knowledge to describe the likely societal impacts and responses required. The participants were receptive to the narratives and many applied their own knowledge intuitively. These discussions co-produced streams of knowledge around the two issues (groundwater levels and water supply) and they could have gone on for a great deal longer – we were finally asked to vacate the conference room.

After being welcomed into the messy process of coproduction, it has been particularly interesting to read through Alice McClure’s previous post on the very first learning lab back in September 2016 – also in Lusaka. Two phrases stand out; that participants called for “freedom of speech, creativity, honesty and trust” and, secondly, about the necessity of having “trust [in] the process.”

The group not only seemed to have trust in the learning labs, but many appeared to be emotionally invested. Phrases like; “progress is slow” and “it’s a messy art” have almost become tropes for co-production projects, however, the principles participants originally called for are now in full swing. Achieving this productive environment, by all accounts, isn’t the work of a moment, but capitalising on it and maintaining momentum beyond a 4-year project cycle appears to be a no-brainer. The point I’ll end on is that whilst the learning labs have been aimed at decision-makers, attempting to further integrate community voices seems like a sensible next step.

Posted in Africa, Climate, Climate change, Hydrology | Leave a comment