Global Temperature update

The latest HadSST4 data release allows me to calculate global temperatures up to March 2022 based on spherical triangulation. HadSST4 results in higher temperatures compared to HadSST3 relative to the baseline of 1961-1990. I combine this with GHCN-V4C station data. The results for the monthly temperatures are shown below. There is still evidence of a weak La Nina and cool spots in Eastern Europe and central Siberia.

Temperature anomaly distribution of the Earth’s surface calculated by 3D spherical triangulation of all land and sea measurements. All points of the earth are covered using this method.

Upgrading from HadSST3 to HadSST4 has led to a slight increase in average temperature anomalies due to instrumentation corrections. The average temperature anomaly in March was 0.96C up from 0.78C in February.  The first three months of 2022 show a small temperature  increase on the annual 2021 average temperature from 0.79C to  0.86C

The monthly data show the effects of La Nina and El Nino cycles.

Monthly average temperatures calculated by the spherical triangulation method

The temperature data can be downloaded.

monthly anomalies

annual anomalies


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Wind Lulls

The installed capacity of  UK Wind farms is currently 25GW.  The business secretary Kwasi Kwarteng proposes to at least double that number, but there is a basic problem which seemingly everyone overlooks – Wind Lulls. Sometimes high pressure sits over northern Europe for many days on end bringing still air with no wind.  All UK, German and French wind turbines are becalmed producing little if any power. Life and essential services has to continue so old coal stations are fired up and CC Gas  stations run at maximum output to meet peak demand.

Here are two recent examples:

  1. The 7 day lull from 16-22 December 2021

Comparison of Gas and Wind output during the 7 day Wind Lull last December.

We also see below how coal is still needed to balance power on the grid.

2.The recent  10 day wind lull lasting 10 days. At least this time there was a bit of sunshine yet notice again how the remaining 2 coal power stations were also needed . The whole of March saw only two brief spells of good wind output.

10 day wind lull March 20 – March 30

Most of March saw light winds. Output reached a maximum of 15GW briefly or a maximum  load capacity of  60% . Note that I am also correcting the metered wind output to include embedded  small wind farms as well.

Gas output compared to wind output – almost perfect anti-correlation.

Don’t worry though we are told. We just need “energy storage”, but no-one ever calculates just how much energy we would need store in order to see us through a wind drought like we have just experienced or the one last December.

In December there was additionally no solar power generated. In fact solar energy is perversely anti-correlated to demand. Annual peak demand is around 6pm on winter evenings when solar energy output is zero. So let’s estimate how much energy would need to be stored to cover the December lull.

We need 7 days of continuous power delivery at an average load of  30GW. So we need to store:

7 x 24 x 30 = 5040 GWh  or  1.8 x 10**16 joules

This is a huge amount of energy which is approximately equivalent to

  • 1200 Hiroshima size bombs
  • 373 million fully charged Tesla Powerwalls
  • 67.2 million long range Tesla 3 car battery charges

So it is unlikely that any future fleet of electric cars can back up the grid, assuming their owners would agree to walk rather than drive during a wind lull.

The largest energy store in the UK is the Dinorwig pumped storage Power Station in Snowdonia. It took 10 years to construct but actually paid for itself within 2 years by balancing peak time loads.  It can store up to 9.1 GWh of energy which is a useful power source over short periods.  However it is still  500 times too small to balance a wind dominated energy grid for a week. Nor do we have enough mountains to dramatically increase such pumped storage systems.

The largest Tesla grid size battery storage is in Hornsdale Southern Australia. It can store 193 MWh which is useful to cover short outages but still way too small for a wind lull.

As David MacKay used to say “We need an Energy Policy which adds up”.


Posted in Energy, renewables, wind farms | 77 Comments

Homogenisation of temperature data

How accurate is the pair-wise homogenisation algorithm applied to GHCN land temperature measurements and the instrumentation corrections made to sea surface temperatures?

Long term station measurements are affected  by a station’s physical relocation, by environmental changes (urban development)  and by instrumentation changes. Station relocations are usually recorded in metadata but not in a consistent way. Therefore an automated algorithm called the pairwise homogenisation has been developed which compares nearby stations to then identify “break-points” for a given station relative to its neighbours. A statistically significant and persistent violation of relative homogeneity is presumed to be artificial. The GHCN data is updated daily and the full pairwise algorithm is then also run daily.

Sea Surface temperatures have been measured since 1850 using different methods from bucket temperature, engine inlet temperatures, through to buoys and satellite data. Methods to correct instrumentation changes have been developed. The latest HadSST4 data incorporating satellite corrections to recent buoy data.

The overall result of both these updates has been to increase the apparent recent warming. This can be seen by comparing the uncorrected global temperature data with the corrected data each calculated in exactly the same way by spherical triangulation.

Global temperatures calculated both on the raw and corrected temperature data

We see that the net effect is to increase the apparent warming since ~2000 by about 0.15C.  How sure are we that these automated algorithmic corrections are correct? A recent paper has looked in detail at the effects of the pairwise algorithm on GHCN-V4 and the results are surprising. They downloaded all daily versions of GHCN-V4  over a period of  10 years providing a consistency check over time of the corrections as applied. They studied European stations and found that an average of 100 different pairwise corrections were applied during that time while only 3% of these  actually corresponded to documented  metadata events e.g. station relocations.

This implies that the algorithm is far too sensitive. You can see below how consistent these adjustments were by seeing how many times each was repeated. This results in a consistency rate of just 16%. The rest are most likely wrong.

Just 19% of the adjustments made in V4 correspond to documented events in the associated metadata. There could be station moves or instrumentation changes that are not documented but if so then we would expect consistency after some particular date. This is not observed and most changes occur very inconsistently or intermittently.

Proximity of PHA adjustments to a documented event in the station’s metadata.


Another consideration is that a comparison of the temperature of one station with its near neighbours should occasionally identify those reading too hot and reduce the recorded temperature accordingly. Yet the trend  always seems to be towards a warmer trend than  that in the raw measurement data.

Here is one example. Click on image to see animation.


Posted in AGW, Hadley, NOAA, Uncategorized | Tagged | 19 Comments