16th June 2014.
Methane in the earth system – what can we measure, understand and do about recent trends?
By Michelle Cain.
The topic of the latest Cambridge Centre for Climate Science (CCfCS) symposium was “Methane in the Earth System”, held on 5 June 2014, and supported by MethaneNet. The aim of the symposium was to bring a diverse range of speakers together to generate discussion on this broad theme. Not only did we hear from scientists about this topic, but also an engineer from the government Department for Energy and Climate Change (DECC), who was able to enlighten us on how DECC thinks about methane in terms of the UK policy environment.
Professor Euan Nisbet kicked off the afternoon with a whistle-stop tour of methane through the ages and across the globe: from methanogenesis 4 Gya (4×109 years ago) through to the present day. Entitled “Is methane the canary in the mine?”, the talk referred to the idea that methane may be like a lever that kick-starts periods of global warming. Is an increase in atmospheric methane a sign that the temperature is going to follow a similar trend? Or perhaps it’s the other way around, and increased temperature is responsible for the increasing atmospheric methane concentrations?
Observing and understanding the recent trends in atmospheric methane was the main focus of Professor Nisbet’s talk. The trends stabilised around the turn of this century, but have been rising since about 2007. The puzzle of why this has happened is yet to be solved. Measurements of isotopes of carbon in methane show that the global average isotopic ratio is getting “lighter”, meaning the sources are becoming more characteristic of wetland, and less like combustion. However anthropogenic emissions inventories show increases in recent years. If both of these trends are true, presumably the wetland source must be increasing at a greater rate than the anthropogenic source. This could be due to weather events like floods and the position of the inter-tropical convergence zone. The big question that follows on from this is whether this is a short- or a long-term trend. Professor Nisbet showed many examples of measurements, both short- and long-term, spanning the tropics to the poles, which will go some way to resolving this question in the fullness of time.
Dr Nic Gedney followed with a talk about one of the key aspects of understanding the methane trends – the modelling of methane emissions from wetlands. Both temperature and precipitation are critical for modelling wetland location and therefore methane emissions and potential feedbacks. For example, the Wetland and Wetland CH4 Inter-comparison of Models Project (Melton et al 2013) found that methane emissions increased when there was increased precipitation, and that global wetland area decreased when temperature increased. The model results revealed disagreements in both spatial and temporal extent of wetland areas and therefore methane emissions.
Dr Gedney also showed recent developments to the Joint UK Land Environment Simulator (JULES), a “process-based model of carbon, energy and water exchange between atmosphere and land surface.” The model uses drainage and topography to calculate inundation. Updating the model with a representation of organic soil and with new topography has improved the model compared to observations.
To make further improvements to the complex task of modelling methane emissions from wetlands, it will be essential to improve on observations of wetland extent. There are currently striking differences between inundation products derived from satellite observations and wetland models. However, wetlands are not always detectable until you “step into one and end up knee deep in water”, and so it’s clear that detection from space will have its limitations. Nonetheless, improvements to current measurement techniques will be a valuable step towards better understanding wetland areas.
This theme was continued in Professor John Burrows’ talk about measuring the anthropocene (in particular methane) from space, which he described as “very much work in progress”. The anthropocene is a new epoch, in which humans are changing the earth system dramatically. Examples of this include: burning fossil fuels, releasing other pollutants, causing the ozone hole and changing land use. Without measurements, it’s impossible to understand or manage how we are altering the earth system and climate.
Given that ground-based measurements will always be sparse, we need space-based techniques to get good global coverage. Ideally, a combination of low earth orbit (which has good global coverage) and geostationary orbit (high resolution, but less wide coverage) would provide the best information. Unfortunately, the current processes for getting a new satellite built are very slow, and it’s possible that the space-based measurements of methane will take a step backwards if new instruments are not developed quickly enough. CarbonSat is the next big project being considered for deployment by the European Space Agency. This would measure methane at a 2km by 2km resolution, however if successful, it won’t be launched until 2022.
Professor Burrows showed many different applications of satellite data in understanding recent methane trends. Data from the SCIAMACHY satellite have added to the quantification and identification of the recent increasing methane trend, which is mainly found in the tropics and northern mid-latitudes. These data have then been put into inverse methods to work out emissions. An inversion is a technique for calculating a best estimate of emissions by reconciling observations and a model using a cost function. Bergamaschi et al (2013) suggest that anthropogenic sources are causing the trend, and that wetlands and biomass burning dominate interannual variability. Another inversion study by Houweling et al (2014) was unable to discriminate between Asian anthropogenic and wetland sources. There are many other recent studies contributing to this debate, and this issue is far from resolved.
We heard more about inverse methods in Dr Matt Rigby’s talk, in which he explained why we should take some inverse modelling – including some of his own – with “a pinch of salt”. The key factor is how uncertainties are estimated. There are uncertainties in both the prior information and in the transport model used. Bayes’ theorem requires that these should be independent, but this is not always the case in inversions that use this assumption. Defining the size of an uncertainty may be simply an estimate, and may be “tuned” in concert with other uncertainties. Dr Rigby demonstrated an alternative approach to eliminate this particular problem: the use of a hierarchical Bayesian estimation, which estimates the uncertainties in the uncertainties. An example of this from Ganesan et al (2014), showed that a hierarchical approach tended to have a larger uncertainty, but one that is arguably closer to the true uncertainty.
Another approach for tackling the issue of uncertainty is to test a model’s sensitivity to its parameters. This can reveal large and sometimes non-linear sources of error, which are often simply untested and therefore ignored. Dr Rigby suggested that statistical emulators might be a good way to test for such systematic errors.
The concentration of atmospheric OH (the main sink for methane) is another uncertainty that affects our understanding of methane. Dr Rigby showed a time series of derived global OH concentrations based on methyl chloroform observations. This showed a low variability (<5%) in the past decade, although this is poorly constrained.
Although there is room for improvement in terms of reducing uncertainties, inverse methods are a key component to understanding methane emissions. The UK uses such techniques to verify bottom-up national emissions inventories, and is a world-leader in this kind of approach. The UK measurement network is also relatively dense, with recent projects like GAUGE adding to this.
We had a shift in perspective for the final talk of the day when we heard from Dr Philip Sargent, an engineer from DECC. Dr Sargent gave us a flavour of the concerns DECC has when it comes to methane. One aspect of DECC’s role is to weigh up which policy options emit the least greenhouse gases. For example, how does UK fracked gas compare to imports of liquid natural gas or via a pipeline? The UK must reduce carbon emissions if it is to meet the Committee on Climate Change’s 4th carbon budget in 2025.
The heart of the matter is that DECC must balance policies and spending related to methane with those related to carbon dioxide. Therefore metrics that allow comparisons to be made are essential. Dr Sargent posed an open question regarding what time horizon should be used for global warming potential (GWP). The Intergovernmental Panel on Climate Change (IPCC) says that using 100 years is an arbitrary choice. Alternatively, perhaps it is better to specify a cut-off date, and use that as the time horizon. Evidence, including uncertainties, to support the use of a particular metric and time horizon is one particular point that DECC is interested in, as it can be used for economists to base their models on. However, Dr Sargent also noted that it is preferable to continue using GWP (likely with more useful time horizons), as this term is well understood among policy makers – vital for international negotiations.
Formal proceedings ended with a discussion about the kinds of evidence the science community can usefully provide to government, which continued in more depth over the poster reception. A take home point from this final session was the importance of finding opportunities for policy makers to communicate with scientists. Sometimes talking to someone is the most effective route to providing them with the information that they require, but having that chance to talk can often be the limiting factor.
Bergamaschi, P., et al. (2013), Atmospheric CH4 in the first decade of the 21st century: Inverse modeling analysis using SCIAMACHY satellite retrievals and NOAA surface measurements, J. Geophys. Res. Atmos., 118, 7350–7369, doi:10.1002/jgrd.50480.
Ganesan, A. L., Rigby, M., Zammit-Mangion, A., Manning, A. J., Prinn, R. G., Fraser, P. J., Harth, C. M., Kim, K.-R., Krummel, P. B., Li, S., Mühle, J., O’Doherty, S. J., Park, S., Salameh, P. K., Steele, L. P., and Weiss, R. F.: Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods, Atmos. Chem. Phys., 14, 3855-3864, doi:10.5194/acp-14-3855-2014, 2014.
Houweling, S., Krol, M., Bergamaschi, P., Frankenberg, C., Dlugokencky, E. J., Morino, I., Notholt, J., Sherlock, V., Wunch, D., Beck, V., Gerbig, C., Chen, H., Kort, E. A., Röckmann, T., and Aben, I.: A multi-year methane inversion using SCIAMACHY, accounting for systematic errors using TCCON measurements, Atmos. Chem. Phys., 14, 3991-4012, doi:10.5194/acp-14-3991-2014, 2014.
Melton, J. R., Wania, R., Hodson, E. L., Poulter, B., Ringeval, B., Spahni, R., Bohn, T., Avis, C. A., Beerling, D. J., Chen, G., Eliseev, A. V., Denisov, S. N., Hopcroft, P. O., Lettenmaier, D. P., Riley, W. J., Singarayer, J. S., Subin, Z. M., Tian, H., Zürcher, S., Brovkin, V., van Bodegom, P. M., Kleinen, T., Yu, Z. C., and Kaplan, J. O.: Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP), Biogeosciences, 10, 753-788, doi:10.5194/bg-10-753-2013, 2013.