Where Do All My Balloons Go?

By: Andrew K. Mirza

Turbulence! If you have ever travelled by aeroplane, then you may have experienced atmospheric turbulence during the flight: It is when the captain switches on the seat-belt sign; requests all passengers return to their seats and buckle up; the flight attendants pause their dispensing of refreshments and stow away their trollies.  Then the aeroplane encounters turbulence that may range from a slight judder to something more intense.  As quick as it is encountered it passes.  The seat belt sign is switched off, the flight attendants resume their duties, and you are free to roam the cabin; the event is reduced to a passing remark such as “… it was a bumpy ride …” But what you experienced, however briefly, may have important implications for climate change.  Not so much because of the flight you’ve taken but in a more subtle way of accounting for how much of the greenhouse gases in the atmosphere can be attributed to a particular country.

This requires not only the simulation of the atmosphere but also the subsequent dispersion of greenhouse gases emitted from various processes of nature and human activity.  The DARE-UK project aims to detect and measure regional greenhouse gas emissions and estimate the fraction of those measurements that can be attributed to the UK.  Thus sophisticated computer models have been developed that can model dispersion which, when coupled with weather forecast models, aim to estimate where, when and how much of the greenhouse gases have come from or come to the UK.

One such computer model is called the Numerical Atmospheric dispersion ModEl – NAME. This model was originally developed by the Met Office in response to the Chernobyl nuclear accident and has since been put to use in many other applications: air quality forecasts,  emergency response to accidental chemical releases, and it is routinely used to model the dispersion of volcanic ash, e.g., the eruption of the Icelandic volcano Eyjafjallajökull.  NAME models the dispersion by releasing virtual particles within a virtual atmosphere, such as a weather forecasting model.

If you imagine these virtual particles as being balloons; hundreds or thousands of them are released from your garden every day.  Each balloon carries a package representing a fraction of your daily contribution to the global emissions of greenhouse gases.  They ascend and travel wherever the weather forecast modelled wind takes them.  Some will only travel a short distance while others may travel a long way.  However, whether your balloons travel a short or long distance will depend on atmospheric turbulence.  In particular, whether turbulence pushes your balloon through the interface between the boundary layer and the free atmosphere or causes it to bounce back downwards.  The boundary layer is the lower part of the atmosphere that is subject to friction due to the earth’s surface whereas the free atmosphere is the upper part of the atmosphere where surface friction has a very small effect.  Therefore, how we represent turbulence in the dispersion model is important.

Currently in NAME turbulence in the free atmosphere is assumed to have a fixed intensity that does not vary in space or time.  But we know from our experience in an aircraft this is not the case, turbulence varies in where it happens when it happens and in its intensity.  So my contribution to the DARE-UK project is to investigate and evaluate how varying the representation of free atmosphere turbulence in space and time may impact atmospheric dispersion.

Figure 1: Shows two plots which are vertical slices from near the surface up to 3~km. Figure 1(a) shows the current scheme for representing turbulence in the free atmosphere (light blue regions) which uses a fixed value whereas figure 1(b) shows the new scheme (yellows and pale blues) which varies according to how the wind speed changes in space and time.  Both models use the same scheme for turbulence in the boundary layer (dark blues).

Figure 2: Shows a horizontal slice just above the surface.  It is clear from these two figures that the turbulence due to the new scheme varies in space and intensity (yellow is low, pale blue is moderate).

Figure 3: shows the averaged difference between the fixed and variable schemes during a day, showing how the turbulence using the new scheme not only varies in time but also how its intensity evolves (areas in red).  The intensity will determine whether your balloon remains within the boundary layer, and is likely to remain in the UK, or it passes into the free atmosphere and is likely to travel beyond the UK.

My work now is to identify what impact this space-time varying turbulence has on the dispersion of your balloons, i.e., what weather regimes enhance or diminish turbulence in the free atmosphere.  To do this a tracer gas, Radon, will be attached to the balloons and allowed to disperse within the model atmosphere.  At the end of the modelling period, we compare the amount of Radon that reaches the monitoring sites that measure actual Radon.  This comparison will help us understand whether our new variable turbulence scheme is an improvement over the fixed turbulence scheme. If not then we can investigate why there is no improvement.  Knowing this will help us understand where your contribution to greenhouse gases ends up, i.e., whether your balloons stay mostly in the UK or travel to Europe, and, of course, vice-versa.  So that bumpy ride in the aircraft may help us to understand more clearly where all your balloons go.

If you’d like more information about the DARE-UK Project why not visit their website.

References: 

Brown, A., S. Milton, M. Cullen, B. Golding, J. Mitchell and A. Shelly, 2012: Unified Modeling and Prediction of Weather and Climate: A 25-Year Journey. Bulletin of the American Meteorological Society 93, 12, 1865-1877, https://doi.org/10.1175/BAMS-D-12-00018.1.

Dacre, H. F., A. L. M. Grant, N. J. Harvey, D. J. Thomson, H. N. Webster and F. Marenco, 2015: Volcanic ash layer depth: Processes and mechanisms, Geophys. Res. Lett.42, 637–645, https://doi.org/10.1002/2014GL062454.

Jones, A., D. Thomson, M. Hort and B. Devenish, 2007: The U.K. Met Office’s Next-Generation Atmospheric Dispersion Model, NAME III. In Air Pollution Modeling and its Application XVII (Proceedings of the 27th NATO/CCMS International Technical Meeting on Air Pollution Modelling and its Application) (pp. 580–589). Springer. https://doi.org/10.1007/978-0-387-68854-1_62, (https://www.researchgate.net/publication/226303857_The_UK_Met_Office%27s_Next-Generation_Atmospheric_Dispersion_Model_NAME_III).

Manning, A. J., D. B. Ryall, R. G. Derwent, P. G. Simmonds and S. O’Doherty, 2003: Estimating European emissions of ozone-depleting and greenhouse gases using observations and a modeling back-attribution technique, J. Geophys. Res.108, 4405, D14, https://doi.org/10.1029/2002JD002312.

Thomson, D. J., W. L. Physick and R. H. Maryon, 1997: Treatment of Interfaces in Random Walk Dispersion Models. Journal of Applied Meteorology, 36, 9, 1284-1295, https://doi.org/10.1175/1520-0450(1997)036<1284:TOIIRW>2.0.CO;2.

Wada, A. and Coauthors, 2013: Quantification of emission estimates of CO2, CH4 and CO for East Asia derived from atmospheric radon-222 measurements over the western North Pacific, Tellus B: Chemical and Physical Meteorology65,1, https://doi.org/10.3402/tellusb.v65i0.18037.

White, E. D. and Co-authors, 2019: Quantifying the UK’s carbon dioxide flux: an atmospheric inverse modelling approach using a regional measurement network, Atmos. Chem. Phys.19, 4345–4365, https://doi.org/10.5194/acp-19-4345-2019.

This entry was posted in Atmospheric dispersion, Boundary layer, Greenhouse gases, Numerical modelling, Turbulence, Wind. Bookmark the permalink.

Leave a Reply

Your email address will not be published.