Fun things of a Friday.

The Onion, everyone's favourite satirical newspaper, hit the headlines this week when North Korean dictator Kim Jong Un was named the winner of their 'Sexiest Man Alive' award and Chinese news agency China People's Daily took them at face value, publishing a glowing 55 page online spread on the news.

The Onion has quite a history of its cutting satire being taken seriously but this gem from 2008 is probably a little too out there to be taken seriously by anyone.

http://www.theonion.com/articles/hurriphoonado-cuts-swath-of-destruction-across-eas,2629/

It is still hilarious though...

A new dawn for Oil?

One of the more frustrating parts of being an environmentalist ‘in the know’ so to speak is that sometimes you have to challenge perceived wisdom of the kind that you really wish was actually true. The notion of oil and gas as finite, fossil fuels is one that almost everyone is familiar with; the notion that oil is going to run out very soon is one that is almost as widely held. However if you ask a geologist when we’re going to run out of oil they will describe a much murkier picture. Indeed for a glimpse of how confused the situation is, here is an article I wrote earlier this year for Experimentation Online on the subject of oil resources. While estimates of when the black gold will dry up vary wildly it can probably be safely assumed that we have at least fifty years of oil left and, according to a new report by the IEA among other sources, we may have much longer.

To summaries the IEA report, the somewhat controversial exploitation of oil shales and tar sands is leading to a supply boom for oil and gas in the western world. In the US alone supply from these sources is expected to rise from 23% currently to 49% by 2035. Instead of the slow decline of supply as the points of ‘peak oil’ and ‘peak gas’  are reached new technologies and ever increasing demand (along with the ever increasing cost that every motorist is familiar with) are leading to an oil boom. In fact, as engines become more efficient and supply continues to increase the IEA quite optimistically predicts that the US is on track to becoming self-sufficient in terms of both oil and natural gas and may even become a major exporter in the future. 

This is all a bit different from what you thought you knew about oil isn’t it?

While it is the US and Canada that are benefiting the most right now, being rich in the geological formations that contain this unconventional oil and having the technology to extract it, the rest of the world may yet follow. On the heels of the IEA report The Diplomat published a very interesting article highlighting the potential for extraction of oil and gas from unconventional sources to spread to Asia. As ever China appears to be heading for a collision course with America having made recent moves to try to acquire the appropriate technology to extract fossil fuels from its own shale 

formations. Australia seems even better placed to compete on the global market with both a more suitable geological setting than China and a proximity to the burgeoning, oil hungry economies of South-East Asia that America cannot match. However it is not unrealistic to suggest that some of these developing economies will, given time, try to drain their own shales and tar sands rather than buying from their neighbours. The think tank EAI (not to be confused with IEA) which specialises in developing new energy policies for India suggests that the country, now the world’s fifth largest economy may have up to 15 billion tonnes of oil shale reserves alone in three main regions, the Assam Shelf, Naga Schuppen Belt and Assam-Arakkan Fold Belt. The idea that the Indian government and energy industry as a whole will ignore this potentially vast resource is naïve to say the least.

So it appears that the perceived wisdom that oil is running out needs a bit of a revision. Conventional oil bearing formations such as those being drained in the North Sea and Persian Gulf are edging towards their peak but there is still plenty in the tank for the world as a whole. The range of environmental and economic consequences of this are vast and could fill a number of pages (I again recommend the article in The Diplomat for a brief, Asia-centric summary of them). However, as long as there is money in extracting oil and gas and we, the public, feel no pinch at the pump there is never going to be the will to invest wholesale in the innovative green technologies needed if we are truly going to combat climate change. For once it would perhaps be best if that perceived wisdom was correct. If we really were staring down an empty oil barrel we might start sorting out the climate before it is too late.

Paper Review: ‘A review on the forecasting of wind speed and generated power’. Lei et al 2009.

Wind farms are a divisive issue both in this country and abroad. Their supporters will tell you that they are a clean and increasingly efficient way of harnessing a potentially limitless source of energy. Sceptics, the new environment secretary Owen Patterson among them, will argue that they are unsightly, noisy and ineffective. In arguments between these two sides the science of how we work out the efficiency of wind farms is often ignored. The simple fact is that wind energy can never be incorporated large scale into a county’s power supply unless there is a reliable method of forecasting the wind. Without this there is no way of working out how much power a set of wind turbines will generate, making it virtually impossible to plan for their use.

In this paper the fully range of wind speed prediction methods are reviewed.  It is highlighted that there are both Physical modelling methods, which use the physical characteristics of a given site to predict future wind speed and Statistical models that run almost entirely on previously observed data. The paper also goes on to review a number of new Artificial Intelligence based models.

Most physical models are mathematical NWPs or Numerical Weather Prediction models. They use a wide range of input data including the orographic characteristics of a site, the ‘roughness’ of terrain, average pressure and temperature and potential obstacles in the area. This data is used to help predict wind speeds at a particular site. More advanced physical models also include subsidiary programmes that can model the effect of obstacles in more detail (WAsP programs) or even take into account the effect of turbine shadowing (PARK programs). Obviously then physical models require a large amount of data of be gathered before they are run and often the data they generate needs to be analyses further. The paper recommends that for short term forecasting of wind speed accurate evaluation models are also needed in order to give reliable results.

There are a much wider range of statistical models, the majority of which are based upon the input of historical wind speed data and the identification of patterns and trends by computer programmes. These range from more simple Autroregressive models (AR) to more complex Autoregresssive moving average models (ARMA), each with their own limitations and advantages. For example the paper cites a study that has shown ARMA models to have 95% accuracy on both long and short scales of prediction but only when using 2-yearts of previous wind speed data. There are also spatial correlation models which aim to increase the accuracy of predictions by using data from nearby sites as well as the location of wind turbines. These models have been shown to be very effective on flat terrain but almost useless when trying to predict wind speed over complex topography.

The paper also mentions artificial intelligence based models that are a much more recent development in wind speed forecasting. A number of examples of such models are presented in the paper but there is little consensus on their effectiveness.

The overall trends seem to be that NWP based physical models perform well over large spatial scales and long time periods. Statistical models are often more effective over very short-term temporal scales and certain AI models only appear accurate when there is a very large amount of historical data to compute. There is however no ‘silver bullet’ model that can accurately predict wind speed regardless of location or time scale. As the paper rightly points out there is much more study in this area needed if wind power is ever to become a viable renewable energy source and it is most likely that a synthesis of a number of different models will prove the most effective in forecasting wind speed in the future.

(The full paper, ‘Ma Lei, Luan Shiyan, Jiang Chuanwen, Liu Hongling, Zhang Yan,

 A review on the forecasting of wind speed and generated power, 

Renewable and Sustainable Energy Reviews, 

Volume 13, Issue 4, May 2009, Pages 915-920’ is available here)

Fun things on a Friday

Now I can type again I thought I'd share this little gem. Not exactly 'fun' but more highly creative and informative. Show this to any of you're friends or family that aren't clued up on climate change or don't know why they should stop driving their Land Rover round central London...




I should acknowledge that I got this of my friend Katrina who blogs here

Oops.

Just to let you know I've recently broken/dislocated/badly sprained a finger. The upshot is that typing is very slow and will be for a week or so at the least. Expect less words from me.

Just a little thing...

Relating to the article a few weeks about the environmental costs of war...

http://thediplomat.com/2012/11/13/a-war-unending-the-vietnam-war-and-agent-orange/

Read and learn.

Climate changes = more hurricanes? Simple maths or false numbers?

In last week’s article on Hurricane Sandy I stated out and out that the storm’s strength and northerly track were mainly the effects of climate change. Scientifically such a black and white statement should probably have been supported with evidence and as such I have decided to review a recent paper from the journal Nature Geoscience on the links between climate change and tropical cyclones. Hopefully this will serve to support the stance I made in the previous article and inform readers who wish to explore some of the scientific evidence of a link between climate and the intensity of hurricanes. Is it a simple relationship or a more complex one?

The paper, titled ‘Topical Cyclones and Climate Change’ and authored by Knutson et al, analyses both the past correlation between climate change and tropical storm characteristics and uses data from modelling to project the effect of climate change on tropical cyclone intensity in the future. Sea surface temperature (SST) has been tracked and found to have increased by several tenths of a degree over the last few decades. The paper cites the IPCC fourth report and US Climate Change Science program report 3.3 that states that these changes are ‘very likely’ due to anthropogenic global warming.

When considering past data the picture painted by the study is confused. While the rise in SST is easy to follow how this has effected Tropical Cyclone strength is less certain due to both the suggestion of natural climatic variability in the Atlantic (relevant for Atlantic tropical cyclone frequency) and a number of biases in the data especially as data is more readily available and reliable for the Atlantic Ocean compared to the Pacific. The paper states that without adjustment for possible missing data hurricanes have increased in frequency from the late 1800s onwards but shows no significant trend from the 1850s to the present. In terms of intensity (measured via the power dissipation index or PDI) it is also difficult to find an overall trend. The paper compiles information from a number of studies as the graphs below show until very recently there has been no rise in PDI over a prolonged period but rather a number of short term peaks and troughs with no significant long term trend.

However when it comes to the projection of future intensity and frequency of tropical storms (and therefore hurricanes) the paper presents more defined conclusions. It is projected that frequency of tropical cyclones will either remain the same or reduce on a global scale as greenhouse warming continues. The decrease may be as much as -34% although in some individual basins there is an error factor of +/-50% on these projections. In terms of intensity the maximum wind speed is predicted to rise (on average) by +2 to 11% while rainfall is modelled to increase by +20% within a 100km radius of the cyclone centre. There is an error margin of +/-15% associated with some of the methods of modelling (usually for individual basins).

There is still a degree of uncertainty with these figures, especially the figures for cyclone frequency which the authors state they have ‘very low confidence in’. However the models have been calibrated against past observed data so at the very least the overall trends predicted by modelling can be relied upon.

This brief summary of the paper has attempted to highlight the relevant data and trends within the data. The conclusions that can be drawn from it are that it is likely that climate change will cause an increase in the intensity of tropical storms (and therefore hurricanes) but that it is not yet certain whether it will have the same effect on frequency. Despite this these conclusions provide a strong link between climate change and hurricanes.