Storylines of regional climate change

By Giuseppe Zappa 

An outstanding question for climate science is quantifying how global warming will regionally affect the aspects of climate that are most directly relevant to society, such as precipitation, windiness and extremes. But achieving this task is proving not to be simple. The main available tool consists in computer simulations performed using ensembles of climate models. These models are used to run scenarios in which greenhouse gas concentrations increase with time, so that the climate response to warming can be evaluated. But, for the aspects of climate that are controlled by the atmospheric circulation, there still remains substantial spread across the model projections thus leading to uncertainties in how regional climate will respond to global warming.

Figure 1:Decadal evolution of cold season (November to April) Mediterranean precipitation as a function of global warming in the simulations from 36 climate models from the 5th phase of the Coupled Model Inter-comparison Project (CMIP5) for the RCP8.5 emissions scenario. Precipitation and temperature changes are evaluated relative to the 1960 to 1990 mean. The thick line shows the multi-model. For presentation purposes, the horizontal axis starts at 0.2 K. 

Let’s consider Mediterranean precipitation as an example. Figure 1 shows that while the average of 36 climate model projections, as well as most of the individual models, indicate a future decline in winter Mediterranean precipitation, the magnitude of the precipitation reduction, even for a given warming of the planet, remains highly uncertain. Notably, the projected drying at 2 degrees warming in some models can be larger than the drying at 4 degrees warming in other models. Taking the multi-model mean provides a simple, and often adopted, approach to summarise the ensemble and communicate the regional projections to stakeholders and decision makers. But substantial information on the uncertainty is lost by simply averaging the model responses. So is this fully justified?

In a recent paper, Zappa and Shepherd propose to use an alternative storyline approach to characterise the uncertainty in regional climate projections from ensembles of climate models. To think in terms of storylines, it is necessary to realise that regional atmospheric circulation can be driven by remote aspects of climate. This is true on seasonal timescales, for example in response to the development of El Nino or La Nina events in the tropical Pacific, but it is equally true for the long timescales associated with climate change. In particular, Zappa and Shepherd identify two remote drivers of atmospheric circulation whose response to climate change is both uncertain and capable of influencing the European and Mediterranean climate: the magnitude of the upper tropospheric warming in the tropics and the strength of the Northern Hemisphere stratospheric vortex.

Figure 2:Four different plausible storylines of cold season Mediterranean precipitation change per degree of global warming. The different  storylines depend on the magnitude of the tropical amplification of global warming and on the strength of the stratospheric vortex response as indicated above the figures. See Zappa and Shepherd 2017 for more details. 

By applying a statistical framework to the climate models output, four different plausible storylines of Mediterranean precipitation change are identified for different combinations in the two remote drivers responses (see Figure 2). The patterns of regional precipitation change per degree of global warming within each storyline are found to be rather diverse: depending on the storyline, the Mediterranean precipitation response can be larger (Figure 2b) or weaker (Figure 2c), or it can be more focused on the eastern (Figure 2d) or on the western (Figure 2a) Mediterranean. A worst case storyline of Mediterranean climate change is identified for a large tropical amplification of global warming and a strengthening of the stratospheric vortex (Figure 2b), in which case the Mediterranean drying per degree of global warming is expected to be particularly enhanced. 

Until there is sufficient physical understanding or observational evidence to discard one of the above combination of driver responses, these four storylines should be considered equally plausible future realisations of Mediterranean regional climate change. It is worth to highlight that, until discarded, the worst case storyline could still be realised. This should be kept in mind when evaluating the risks of climate change and developing local adaptation plans. 

Reference:

Zappa, G. and T.G. Shepherd, 2017: Storylines of atmospheric circulation change for European regional climate impact assessment. Journal of Climate,30, 6561-6577, https://doi.org/10.1175/JCLI-D-16-0807.1

Posted in Atmospheric circulation, Climate, Climate change, Climate modelling, Greenhouse gases, Numerical modelling, Stratosphere, Troposphere | Leave a comment

How the Hadley Cells work

By Gui-Ying Yang

The Hadley Cell, named after British meteorologist George Hadley who discovered this tropical atmospheric overturning circulation, is one of the basic concepts in weather and climate. Figure 1 shows the zonal mean overturning circulation in a latitude height plane for Boreal summer June-July-August (JJA), based on 30 years (1981-2010) of ECMWF data. It is seen that the JJA Hadley Cell is dominated by its ascent near 10°N and descent near 20°S, with motion towards the summer hemisphere near the surface and a return flow towards the winter hemisphere in the upper troposphere. This classic picture of the zonally averaged Hadley Cell gives a smooth impression of the cross-equatorial flow moving from one hemisphere to the other. The basic theories of the Hadley Cell are based on angular momentum conservation with the additional consideration of some mixing and friction near the surface. However, angular momentum conservation from zero velocity at the equator moving to another latitude, φ, gives a zonal wind u=aΩsin2 φ/cos φ (134 m s-1 at 30o latitude and 700 m s-1 at 60o latitude) that is many times larger than that observed as seen in Figure 1. It is clear from Figure 1 that the angular momentum is far from uniform and the motion crosses angular momentum contours. Consistent with this, the actual subtropical jet maximum of about 40 m s-1 at 30oS is very much smaller than the value suggested by the theory based on angular momentum conservation in the upper branch of the Hadley Cell. This implies that eddy angular momentum mixing processes are actually of order one importance. In this study, we will reveal some interesting features associated with the Hadley Cell.

Figure 1:  The JJA zonal mean overturning circulation in a latitude-height cross section, based on 30 years of ERA-Interim data.  Colours indicate absolute angular momentum and blue contours indicate zonal winds.

Firstly, to investigate the nature of the JJA momentum flux, Figure 2 shows the steady and transient momentum flux in JJA 2009. It is seen that in addition to the expected strong transient momentum flux in the midlatitude, whose importance for the Hadley Cell has often been stressed, both steady and transient fluxes show a maximum in the tropical upper troposphere, extending from the region of tropical convection in the summer hemisphere into the sub-tropics of the winter hemisphere. The dividing line between tropical positive values and sub-tropical negative values looks almost identical in the steady and the transient, suggestive that there is a motion with SW-NE tilts north of about 15oS and NW-SE south of that with an amplitude that fluctuates in time. The latitude-longitude pictures at 150 hPa show that this signature comes predominantly from the Indian Ocean (not shown). This can be seen in the case studies below (Figure 5).

The Boreal winter picture indicates a similar tropical upper-tropospheric flux maximum but with the sign reversed as expected (not shown).

This indicates that angular momentum flux in the tropical upper troposphere, which has been neglected, is very important for the existence of the Hadley Cell.

Figure 2: Northward momentum flux of westerly wind in JJA 2009.

Then to examine the zonal and temporal variation of winds and convection in the Hadley Cell region, Figure 3 shows the JJA mean motion at (a) 200 hPa and (b) 950 hPa and Outgoing Longwave Radiation (OLR).  It is clear that the zonal average motion described by the Hadley Cell occurs in longitudinally confined regions that can be associated with the tropical convective heating regions (Low OLR). The lower tropospheric meridional motion contains the flow from the S Indian Ocean into the S Asian and the W Pacific regions of convection. It also shows the flow from the S Hemisphere into the E Pacific and Atlantic Inter Tropical Convergence Zone (ITCZ) heating regions. In the upper troposphere there is a return flow in each of these regions.  

Figure 3: Climatology JJA motion.

To illustrate the transient behaviour, Hovmöller of 5°N-10°S v at 200hPa (used to show the upper-tropospheric cross-equatorial motion) and  0-20°N OLR for 2009 JJA season are presented in Figure 4. The motion is seen to be localised in longitude and time.  The cross equatorial motion in the upper troposphere is strongest in transient waves associated with convective events over the Indian and W Pacific region.

 Figure 4: Transient motion in JJA 2009.

Finally, individual synoptic events in different longitudinal sectors are analysed. As a case study, Figure 5 (a),( b) show the upper and lower tropospheric horizontal winds for early July 2009 with contours of Potential Vorticity (PV) and OLR, respectively. On 6 July when convection is predominately in Indian sector, the lower tropospheric inflow is seen to have its origin from 30-40oS near 60oE. Two days later (8 July), in the upper troposphere, return flow reaches 30oS where it interacts with the S Hemisphere winter subtropical jet and the eastward moving synoptic waves on it, with a horizontal tilt consistent with that suggested by the momentum flux shown in Figure 2.  A filament of N Hemisphere positive PV moves towards the anti-cyclonic side of the S Hemisphere jet.

On 11 July, when convection is predominately in the Philippine sector, similar features are seen in a region shifted to the east.

Figure 5: (a) 370K PV and 150-hPa winds and (b) OLR and 950-hPa winds in early July 2009, 5 days apart with OLR and lower level winds leading the upper level features by two days.

In summary, this study gives evidence that:

(1) The existence of the Hadley cell involves not only the expected strong transient momentum flux in the midlatitude, but also the strong momentum flux in the tropical upper troposphere.

(2) The upper branch of the Hadley Cell is concentrated in certain longitudinal sectors and intensified cross-equatorial flow is associated with flaring in organised convection in those regions.  The tropical upper tropospheric motions associated with convection are crucial to the existence of the Hadley Cell.

(3) Filaments of the upper tropospheric air move from the summer to the winter hemispheres or are mixed in; they can reach the anti-cyclonic side of the winter subtropical jet and interact with the weather systems on it.

These observed features/processes have important implications on weather, climate and climate change, therefore it is important to know how well they are represented in weather and climate models. Also knowing that the cross-equatorial transfer of trace chemicals in the atmosphere occurs in filaments may have significant implications for atmospheric chemistry models, with almost undiluted summer hemisphere air moving deep into the winter hemisphere.

Posted in Climate, Climate change, Climate modelling, earth observation, Equatorial waves, extratropical cyclones, Tropical convection, Troposphere, Waves, Weather, Wind | Leave a comment

Mechanisms of Climate Change in the Indian Summer Monsoon

By Jon Shonk

Over one billion people are reliant on the rainfall of the Indian Summer Monsoon. During the wet season, which usually spans June to September, some parts of India receive over 90% of their total annual rainfall. Deficits or excesses of rainfall can have devastating effects, such as drought, inundation, crop failure and health issues. Bouts of extreme weather, such as short periods of very intense rain, can also have detrimental effects via flash flooding and the triggering of landslides.

It is therefore important to get an idea of how monsoon rainfall might change in a warmer future climate. Climate prediction uses numerical models to advance an initial global “snapshot” of the atmosphere and ocean forward in time using a supercomputer, and then examines the statistics of the weather over some period in the future. Nowadays, many institutions around the world run their own climate models. While these are all based around the same physical principles, the formulation and structure of the models can be very different. This means that the behaviour of models, even if initialised from the same global snapshot, can be quite different after 100 years of simulation.

The five maps in Figure 1 show the projected change in rainfall (averaged from June to August) over India in a future world that is 1.5 °C warmer than pre-industrial conditions (about 0.8 °C warmer than today), for five different climate models. There is a clear disagreement in the pattern of change, with no obvious consensus on which parts of India are likely to become wetter or drier.

Figure 1. Projected changes in rainfall as a result of a 1.5 °C warming, according to five climate models. Rainfall is averaged over June, July and August. Data from the HAPPI project (see Mitchell et al, 2017 for details).

So can we infer anything about the future Indian Summer Monsoon from these models? An advantage of using multiple models is that we can build an “ensemble” of predictions – that is, a number of plausible future climate projections. But the challenge is then how to statistically combine the projected changes to produce a single, clear, robust message.

The simplest option is to take an average across the projections from the five models (Figure 2a). The result is a weak pattern of slightly wetter conditions over eastern India and Bangladesh. However, the averaging process leads to areas where an increase of rainfall in one model cancels out a decrease in another, and understanding the reasons why models project such differences could provide extra clues as to how the monsoon might change.

Figure 2. Projected changes in rainfall, shown as the average across the same five models used in Figure 1. The changes for a warming of (a) 1.5 °C and (b) 2.0 °C are shown. Data from the HAPPI project.

By examining the behaviour of the models individually we can build an idea of the mechanisms by which the rainfall distribution changes in a warmer climate. This has been the focus of my recent work. I have also been looking at the differences in rainfall change between a world that is 1.5 °C warmer and one that is 2 °C warmer (Figure 2b). A paper on this should be ready soon…

 

Posted in Climate, Climate change, Climate modelling, drought, Environmental hazards, Flooding, Monsoons, Numerical modelling, Oceans | Leave a comment

Image conscious atmospheric science

By Giles Harrison

A frequently-heard mantra in physics is “Like charges repel and unlike charges attract”. At face value this paraphrase of Coulomb’s Law seems useful for clouds too, as, quite apart from the obvious example of thunderclouds, water drops in clouds are almost always charged to some extent. However, as it turns out, there are further subtleties to explore in the case of cloud droplets. The simple summary of the 1785 experimental findings of the French engineer and physicist, Jean Auguste Coulomb, made using a sensitive torsion balance, only applies to point charges, which, small though they are, cloud droplets are not. In fact they are sufficiently large for the charge within them to move around, i.e. to use a technical description, water droplets are polarisable. This means that, should there be another charge nearby, the charges within a water drop will re-arrange themselves in response. If this second charge is carried by another droplet, the charge in one will be re-arranged in response to the charge in the other. This is electrostatic induction: overall, the total charge on each droplet does not change, but its distribution within the droplet alters.

This concept is visualised below in figure 1. In the left-hand picture, there are two drops, both carrying negative charges. If they were solely point charges, they would repel each other in accordance with Coulomb’s Law. In the right-hand picture, in which a smaller droplet has been moved closer to the larger drop, a positive charge – known as an image charge – is induced on the droplet’s side of the drop by the negative charge. If the drops were brought closer still, the induced image charge in one would induce a stronger opposite charge in the other, which, perhaps counter-intuitively for two negatively charged objects, leads to attraction. Consequently when charged drops are driven together by turbulent motions and collide, the strong electrostatic attraction which always occurs between the image charges is likely to make them coalesce, and discourage them bouncing off each other. Collision and coalescence occurs continuously in clouds, and allows drops to grow sufficiently that they can ultimately fall as rain. Our initial work indicates that this process is accelerated by droplet charging.

Figure 1. Electrical forces between a small water droplet and a larger water drop, each carrying an overall negative charge (left). As the droplet approaches the drop, a positive image charge is induced in the drop (right), leading to an attraction.

These and related matters were discussed at a recent workshop at Reading on Microphysics of electrified clouds. In work funded at Reading by the United Arab Emirates Rain Enhancement Programme, a team of scientists and engineers is investigating how droplet charging affects droplet collisions and the formation of rain, and whether this can be used practically to influence clouds. Our project is pursuing these questions using a combination of numerical modelling and experimental work. A novel aspect of the numerical work is inclusion of a full description of the turbulent flow usually present in clouds (figure 2).

 

Figure 2. A system of droplets subjected to a turbulent flow field. An animation of the simulation is available here.

A second strand of work concerns the electrical environment of clouds in the UAE. This has been little explored, so, to obtain new information, we have established an automatic measurement site that provides a combination of cloud and atmospheric electricity data (figure 3).  

Figure 3. Measuring equipment being installed in the UAE to provide continuous data on atmospheric properties. Data is obtained by remote interrogation from Reading.

Finally, we need an inexpensive and flexible means to actually get into clouds, to make further measurements and undertake experiments on the effects of introducing charge. As well as the established Reading techniques exploiting modified meteorological balloons, we are using Unmanned Aerial Vehicles (UAVs) for this, designed specially by our collaborators at the Engineering Department at the University of Bath (figure 4).

Figure 4. UAVs developed by the Engineering Department at the University of Bath. (a) launch system and (b) the airframe planned to carry the meteorological instrumentation for the field experiments. Test flights can be viewed here.

This combination of new technologies, surface monitoring equipment and numerical modelling is allowing direct exploration of charge effects in non-thunderstorm clouds. In this, we are conscious that the often neglected electrostatic image force between water droplets seems likely to play a central role.

Follow UK atmospheric electricity activities at ctrwiae.org and on twitter: @atmos_elect

Posted in Clouds, earth observation, Measurements and instrumentation, Microphysics, Numerical modelling, University of Reading, Weather | Leave a comment

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.

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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