Wednesday 29 February 2012

Sea Ice and Snow

The Georgia Institute of Technology has recently released details of a study of the relationship between Arctic Sea Ice and Northern Hemisphere Snow Cover.  The press release summarises it as “The researchers analyzed observational data collected between 1979 and 2010 and found that a decrease in autumn Arctic sea ice of 1 million square kilometers -- the size of the surface area of Egypt -- corresponded to significantly above-normal winter snow cover in large parts of the northern United States, northwestern and central Europe, and northern and central China.”

This goes some way to explaining the fact that whereas Arctic Sea Ice has been tending to decrease (at 53,000 km2/year) snow coverage has declined more slowly (at 22,000 km2/year).  The importance of snow and ice is their role in the albedo feed-back mechanism. Snow reflects almost all the incoming energy, water and land (at least the northern boreal forests where most snow falls) reflect about 10%. So, other things being equal, the influence of snow and ice are equivalent. But, and it’s a big but, other things are not equal. Both sea ice and snow cover vary seasonally. The following chart shows average monthly values for the period 1978 to 2011. This shows that in winter snow covers a much larger area than sea ice.

 

However the albedo effect is only applicable when the sun is above the horizon. The next chart shows the areas adjusted for solar angle. In this case we have assumed a latitude of 80 °N for sea ice and 70 °N for snow and multiplied areas in the first chart by the sine of the sun angle at midday on the 15th of each month. (Calculated using the tool at http://aa.usno.navy.mil/data/docs/AltAz.php). This presents a very different picture and suggests that the influence of snow and ice are equivalent – with snow being perhaps more predominant.


This calculation is subject to a large number of caveats. The sea ice area is based on NSIDC ‘sea ice extent’ which owever thse figureshows “the total area of ocean covered with at least 15 percent ice”. This is reasonable as a metric since sea ice is almost 90% below water but of course such ice is not reflecting radiation. The use of 70 °N and 80 °N respectively and mid-day sun angle are also only approximate. Ideally it would be necessary to track areas of ice and snow at different times of the year, at different latitudes and the energy reflected at different times of day. 

The final chart shows the solar-angle adjusted ice and snow area. This was calculated as for the previous chart. It shows that despite the snow area being larger and reducing less than the albedo adjusted ice area has shown a steady decline.


Minor editorial changes on 2 March 2012.

Sunday 26 February 2012

Twenty-three climate model comparison


The realclimate.org blog has a thread posted by Barry Bickmore related to an article which appeared in the Wall Street Journal (WSJ). The original article was written by a group of eminent scientists with little specific expertise in the science of climate change. To summarise in over-simplistic terms they said that they could accept Anthropogenic Global Warming (AGW) but not Catastrophic Anthropogenic Global Warming (CAGW).  The WSJ published a response by a group of equally eminent climate scientists who supported CAGW.

The posting of Barry Bickmore looks at some of the claims in more detail than would be possible in a newspaper column. One point the first group of scientists had made was that climate models had not captured the recent stasis in temperatures. Bickmore’s response was that “individual models actually predict that the temperature will go up and down for a few years at a time, but the long-term slope (30 years or more) will be about what those straight lines say.” Below we show the annual temperatures expressed as degrees Celsius for 23 models (downloaded from the ClimateExplorer site) the maximum, minimum and average for these 23 models and the temperature from the HadCRU3 data series. As the HadCRU3 series only gives temperature anomalies we have adjusted it to give the same mean as the models for the period of overlap.


First of all it can be seen the chart supports Bickmore’s point. The average of the models follows the general trend of temperature from 1900 to the present and many of the individual models have periods with little or no increase even after the effect of CO2 kicked in from the mid-1970s onward. The current period may have some similarities to the period 1910 to 1970 when a strong Atlantic Multidecadal Oscillation led to an enhanced temperature increase for the first half of that period and to period of stasis for the second half. As the period of stasis, but with wide variations, lasted for about a quarter of a century we may have another decade or so of level temperatures with it still being possible to defend the models. In that period it is likely that models will improve and that the models themselves will be better able to represent such periods.

What is surprising is the difference between the models. The average temperature of the ‘hottest’ model is 15.4 °C and of the ‘coolest’ is 12.4 °C. This is, if my maths is correct, equivalent to a difference of 15.92 W/m², an order of magnitude larger than typical anthropogenic forcing estimates.

Although Bickmore doesn’t mention temperature we have produced a similar chart for precipitation.


This also shows a large difference between the models but, unlike temperature simulation, little evidence that the underlying trend has been captured. In this case the ‘wettest’ model has an average precipitation of 1184 mm/year and the ‘driest’ a precipitation of 918 mm/year. This is equivalent to 19.0 W/m², again large compared to anthropogenic forcing.