Is it climate variability or climate change? The adaptation dilemma
Climate change is a hot topic, being explored and observed in depth by researchers, fiercely debated by politicians and recently named the ‘defining issue of our time’ by the United Nations (UN).
A report released by the UN on 27 November 2018 stated that global carbon dioxide emissions increased in 2017 after a three-year period of stabilisation, and that without drastic action from Governments, we will likely see a climate increase of 3 degrees before the end of the century. With this in mind, it is important to consider how we will adapt to these changes and what sort of engineering infrastructure needs to be in place to ensure the human, environmental and economic health into the future.
While climate change is defined as changes in the characteristics of the climate system that persist over a period of time, concurrently we are experiencing climate variability, which is the deviation in the average state and other climatic statistics when compared to long-term statistics. So how do we know exactly when we are observing climate variability or climate change?
We have been systematically underestimating the increase in temperature.
Professor Taha Ouarda, National Institute for Scientific Research
Among the scientists studying these phenomena is Professor Taha Ouarda, an expert in the field of statistical hydro-climatology and risk analysis at the National Institute for Scientific Research (INRS-ETE) in Canada. Prof Ouarda delivered the University of New South Wales Global Water Institute (UNSW-GWI) seminar on Wednesday 21 November, where he demonstrated that the separating the two is not always easy.
Dr. Ouarda holds a PhD in Civil Engineering from Colorado State University, and has developed several approaches to estimate extreme hydro-meteorological events on local and regional scales, to model hydro-meteorological variables under changing environments, and to deal with a range of problems in the fields of hydrometeorology and environmental engineering through new computer software.
During his presentation, Prof Ouarda drew on his research and experiences to explain strategies to differentiate between climate change and climate variability in order to assist with adaptation decision-making for the future.
When describing climate change, Prof Ouarda explained the huge impact that greenhouse gases have on the average temperature of all planets in our solar system. While the average temperature on earth is currently 14 degrees celsius, without any greenhouses gases it would be -18 degrees Celsius. And while Earth has gone through many temperature fluctuations with periods of warming and ice ages in the past, the industrial revolution occurred when the cycle had already peaked, meaning that more greenhouse gases started entering our atmosphere and warming the planet when, according to past data, it should have been starting to cool.
Professor Ouarda said that we are now observing a movement from a low energy atmosphere to a high energy atmosphere, with events such as drought and flood becoming more intense. It is important then that engineers can adequately identify short and long-term trends and prepare for these events to mitigate the impacts as much as possible.
Professor Ouarda said that no matter what model you use, whether you look at all indicators separately or all together, all clearly signal a global increase in temperature. However, there are many examples of adaptation decisions being made based on projections that have been estimated incorrectly.
“We have been systematically underestimating the increase in temperature. But, at least with the temperature we know how it is evolving—it is increasing little by little,” said Prof Ouarda.
“What we don’t know is how this is going to impact the other variables. We are still guessing how this will influence things like precipitation.”
Prof Ouarda said that even if we stop emitting carbon dioxide altogether today, the earth’s temperature will take several centuries to stabilise, the sea level rise due to thermal expansion may take thousands of years to stabilise, and the sea level rise due to ice-melt will take several millenia to stabilise.
So if that describes climate change and its massive effect on our planet, what exactly is climate variability, and what is causing it?
According to Prof Ouarda, if we look at what drives our climate variability, it is our oceans’ currents. Ocean currents transport energy around the earth’s surface along with atmospheric circulation patterns. Shifts in these circulation patterns over multiple year periods drive corresponding shifts in climate, particularly influencing locations that receive more or less rainfall. By measuring the difference in pressures between two locations or patterns in sea surface temperatures, climate indices are derived that reflect these circulation patterns. These indices become excellent predictors of what type of climate we will experience, especially seasonally.
If we understand what causes climate change and what causes climate variability, theoretically it should then be easy to separate the two when studying data and making predictions for specific geographies and planning accordingly. However, this is not always the case.
Prof Ouarda cited examples of projects undertaken on the Niger River in Africa and the United Arab Emirates (UAE) to help make this point.
Separating climate variability and climate change is not always obvious, and we need to be able to do it because the implications are extremely important
Prof Taha Ouarda, National Institute for Scientific Research
When looking at data on the Niger River from around 1950 to 1990, there was a clear decrease in the average stream flow in the Niger River was over those 40 years, so naturally people started thinking it was climate change. However, the stream flow then started rising again in the early 1990s, raising questions about whether it was in fact climate variability that was being observed.
“If we have a climate variability signal that lasts for 40 years, how long should we wait before we can call it climate change?” asked Prof Ouarda.
“Separating the two is not always obvious, and we need to be able to do it because the implications are extremely important.”
Meanwhile, in the UAE, all signals indicate that long term rainfall is decreasing—whether looking at the total annual and monthly rainfall, the daily maximum rainfall during one year or month, and/or the number of rainy days per year and month. However, after studying the data in a different way, Prof Ouarda noticed that in the months of November and December, rainfall is actually increasing. This prompted him to look at the data seasonally, and he then detected significant changepoints in 1999, since when rainfall has actually been increasing. It was then identified that climate oscillation indices in the gulf region began a phase of change in 1999—indicating that rainfall in the UAE is being influenced by climate variability.
Furthermore, an extreme event is not always a result of climate change. Professor Ouarda pointed out that the longer you are sampling data, the more you will be likely to observe larger or more extreme events.
“The number of times I hear people say, ‘I’ve been living here for sixty years and I’ve never seen the river this high, it is obviously climate change’. Well, no it’s not. The longer you live, the more you are going to be observing events you have never seen before. Observing large or more extreme events every once in a while is a natural result of sampling.”
In order to get a clear picture of the climate phenomenon occurring, Professor Ouarda emphasises the importance of using models which integrate multiple parameters, including climate oscillation indices, and ensuring that an entire sequence of data is analysed. This means looking both the long and short-term trends, while working to gain an understanding of what is driving these trends—taking into account the fact that the drivers themselves may also be subject to climate change.
The types of models that integrate information about variability and trend are proving to be a popular tool to help make decisions that may impact ecosystems, communities and economies at many scales
Prof Taha Ouarda, National Institute for Scientific Research
“The types of models that integrate information about variability and trend are proving to be a popular tool to help make decisions that may impact ecosystems, communities and economies at many scales.”
Prof Ouarda also commented that statistics alone should not be used to make decisions, but simply to give a warning or an indication.
“Statistics give an indication of what the problem may be, but then you need to go and understand the phenomenon. You need to work with others to understand what you are observing and how to integrate it into engineering models.”
“We can develop good predictions for engineering infrastructure with a design life of 40-60 years if we can not only accurately identify and predict trends, but if also if we can determine what is driving these trends.”