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Attempts at climate prediction

Climate predictions are difficult, and it is worth remembering that a century ago we had little idea of the driving forces and their consequences. The saying ‘Red sky at night, shepherd’s delight; red sky in the morning, shepherd’s warning’ was true, but at the limit of our predictive power for weather. We now have more data, better understanding, and highly sophisticated computer modelling that offers a fairly accurate forecast for maybe a week ahead. Stretching this modelling to really long-term changes is still challenging, even though broad patterns of climate warning are feasible and predictable (only the details are tentative). The very encouraging aspects are that as recently as 1987, when computer power was vastly less than today, the meteorology failed to successfully warn that a small hurricane would strike the UK in October. By contrast, in 2013 the UK weather gurus could not only predict that a major storm was developing in the Atlantic, but do so several days in advance of the event. Further, the modelling indicated correctly where, when, and how powerfully it would make landfall on the American coast. Supercomputers and refined modelling may continue to improve forecasts, but this is an expensive business. In 2014, a planned improvement of just a factor of 13 in computing power was budgeted to cost the UK ?97 million.

To most of us, changes in temperature of a few degrees do not seem very profound, as during the course of the year the average daily, and monthly, temperatures in, say, the UK are quite variable, both locally and across the country. Over the last half-century, values have averaged around a range 4—17°C (39—63°F) from January to July, with some years being a few degrees away from the longer-term average. This scale of variation is quite typical in many countries and, for an area as large as, say, the United States, different parts of the nation will have extremely different seasonal patterns and values.

So it is not surprising that there is a difficulty in recognizing longterm changes in the average values. In part, there is a reluctance to consider changes if there are financial implications (i.e. subconsciously reject the possibility of global warming). Slow changes are also difficult to recognize because within our lifespan they may be less than 1°C. In countries where the natural swing in temperature from winter to summer is much more, then the change in patterns are difficult to visualize and appreciate as a long-term trend. Perceived temperature is actually a poor indicator of long-term trends, which are best viewed graphically from detailed records. This requires the skill to understand what is being displayed on a graph.

Among the major reasons that discussions of global warming are so acrimonious is that the general public, and many politicians, have little scientific training (or indeed actively reject anything termed scientific—despite their use of all the modern technologies), so they gain no information (and definitely no insight) when presented with graphical or tabulated data.

A second problem is that for a complex problem, such as predicting the speed and magnitude of climatic changes, there are many variables, a range of views, and distortions from the egotistical scientists who will happily discredit their rivals. For all of us (with or without scientific training), the easy option is complacency—ignoring the entire problem. Alternatively, in most complex discussions we focus on results and views that support what we would prefer to hear. Further, the more affluent are cushioned from climatic changes both at work and in their private lives. They therefore are more likely to only focus on matters that might alter their wealth. Historically, in industrial terms, this has invariably meant more power and more pollution.

Instead of trying to guess if our own experience is clearly telling us there is climatic warming, over and above the normal fluctuations, we need to find a change that is more readily recognized by us without reference to detailed data. In fact, we are far more observant of changes in intensities of storm patterns and rainfall than of temperature. These are related to temperature, as seawater evaporation increases with temperature, and higher values give more energy to storms, and more rain.

So consider the consequences of starting from a modest mid-Atlantic surface water temperature of 21°C (70°F), and then ask what happens if it warms just 2°C (3.6°F), which is well within the effects seen in recent years. This very small temperature shift causes more water vapour, higher rainfall, and more energy transported into the atmosphere. Just a 2° shift can generate an increase of about 13 per cent in total rainfall. So an increase in storms and flooding will be far more obvious than the temperature change. If we are unlucky, and the more serious climate-warming scenarios turn out to be correct, in the Atlantic region, where the weather of both the UK and the US eastern seaboard originate, simple physics says that a temperature rise of 5°C (9°F) will generate around 35 per cent more rain! The extra energy will equally drive more storms, higher winds, and yet more hurricanes. On the western side of the Atlantic, the hurricane season would not just have more powerful examples, but it would extend over more months per year.

Predicting changes is complex, as the very same basic temperature variations influence the way the jet streams swing around in the upper atmosphere. Examples in recent years have shown very clearly that when they do, the USA can have heavy snowfalls and the UK highly varied and energetic weather conditions. Intense sudden flooding in parts of the UK have followed rates of daily and total rainfall that had never been recorded in the 270 or so years of UK meteorological records. The flooding of towns by rivers bursting their banks is partly a consequence of such towns developing alongside rivers, or at the junction of major waterways. Investing in umbrellas and boats may be a good long-term strategy.

Evidence of these changing weather patterns is obvious (at least on the scale of a few decades). For example, in parts of Virginia, the temperature at Christmastime 2015 reached 70°F (definitely not the weather for sleigh bells). However, by January 2016, Washington, DC, had several feet of snow and hurricane-force winds, which were claimed to be among the worst ever recorded in the region at that time of year. The fluctuations emphasize how tracking climate change by our individual experience is remarkably difficult—we need a more clinical overview of weather records.

 
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