Why did the earth cool ~6C during the Pleistocene resulting in the current deep ~100 Ky glacial cycles? The most probable cause is plate tectonics – the opening of the Atlantic and continuing rise of the Himalayas after India collided with Asia. Less well known though is the increasing height of the Andes, Greenland and Western US as shown below. All this data are from the PaleoDEM project
Comparison of topgraphy 5My ago and Today.
an alternative view of the same data is though contour plots
Topographic contour plot. Coastlines drawn are the current ones
We can quantify the net change in land topography by calculating the surface area of the earth above a certain height. This shows that over the last 5 million years there has been an increase in land surfaces above 3000m altitude by about 5.4 million square km. That figure represents a net global increase of 56% in such high altitude land masses. This land movement is concentrated in the Himalayas, the Western coasts of America and especially Greenland. These last two areas extend into high latitudes where changes in albedo are important factors. So how might all this affect the global climate?
1. High altitudes are colder simply due to the fall in temperature with lapse rate. Above 3000m is something like 20C colder than at sea level. Moisture falls as snow and glaciers develop.
2. A 50% increase in glaciated areas increases global albedo thereby reducing net incoming solar radiation slightly, which I estimate at about 0.5% or up to 2W/M2. Perhaps just as important a result is that Milankovitch orbital forcing gets amplified as more land remains permanently glaciated at higher latitudes. This amplification effect is evident in the Ice Volume data.
5 Million year trends in Ice Volume and implied global temperatures
When did Antarctica become permanently ice covered? Prior to 2.5My ago the “West Antarctic Ice Sheet and Antarctic Peninsula Ice Sheets together grew successively larger, with periodic collapses during interglacials. During periods of West Antarctic Ice Sheet absence, the Antarctic Peninsula Ice Sheet remained as a series of island ice caps” (source). This might also explain why initially glacial cycles followed the obliquity cycle since NH insolation and SH insolation are out of phase. Changes in Ice volume partially cancel if Antarctica also contributes to sea levels due to land based melt-back. In this case the MPT (Mid Pleistocene Transition) may represent the end of this cancelation effect and the start of NH dominance.
Peak electricity demand in the UK occurs between 5-30pm to 6pm each weekday evening. I have been monitoring daily power generation on an hourly basis for several years. During 2018 extra wind capacity has been added to the grid and a new interconnection between Scotland and England has improved deployment. As a result the net average power contribution of wind has increased since last year’s result. Note that my figures also include an estimated increase in metered wind power to include smaller embedded onshore wind farms using the procedure described here.
Figure 1 shows the latest overall result.
Figure 1. Contribution of different fuels to UK daily peak demand
Figure 2 shows the yearly average contributions to daily maximum and minimum demand for different fuels. Note how at night (minimum power) the contribution of both wind and nuclear increase dramatically, although for different reasons. Nuclear is always on producing a fixed output while wind output depends only on weather conditions. The demand balance is always met with dispatchable fuels – gas, imports, coal in winter, or Bio (DRAX – wood burners). Solar output is minimal in winter.
UK electricity generation by fuel for red – peak demand blue – low demand at night.
Wind supplies an average 13% of peak demand and 18% of low demand at night. Our ageing nuclear stations still provide 19% of peak demand and 28% of low demand night-time energy.
We can see how crucial gas generation plays in smoothing out the erratic power generation from wind in the following plot.
Comparison of daily peak power supply from Gas and Wind. Gas is tuned to smooth out the surges and falls in power generation by UK’s fleet of wind turbines.
In 2019 roughly half the electricity supply was from low carbon sources and half from fossil fuels (gas and coal). Further expansion of wind capacity always needs an equivalent amount of gas capacity to offset days with no wind.
I wanted to check whether the choice of baseline can affect the calculation of global temperature anomalies from station data. Each temperature index (GISS, Berkeley, CRU) uses different normalisation periods for calculating weather station temperature anomalies. I was surprised to discover that this choice makes no difference whatsoever to the results.
I used the new GHCN V4 which contains 27315 weather stations, and calculated the global average temperature anomaly relative to 5 different 30-year baseline periods using Spherical triangulation. Selecting different baselines restricts the analysis to those stations with sufficient data falling within those periods. Here are the results.
Global Land temperature anomalies calculated relative to 5 different baselines. The numbers in brackets are the number of stations contributing for each baseline period.
All the trends are very similar despite a factor of up to 8 difference in the number of stations used. We can compare them all directly by offsetting each onto the same 1961-1990 baseline. To do this I simply scale each one by the offset difference between 1961-1990 (shown in ‘calc’ brackets).
All 5 baselines offset to the same 1961-1990 normalisation. The offsets are shown as Calc.
The results are surprisingly similar. This means that the choice of baseline period is essentially arbitrary and does not affect the end result.