Jet Stream Wave Patterns Further Distort the Official Global Temperatures
Some know the inadequacies of the world temperature data. Few know the degree of manipulation and corruption of the data done to prove the 20th century temperature increase was unnatural. It completely undermines the scientific claims of the Intergovernmental Panel on Climate Change (IPCC). Lack of accurate data was the problem the father of modern climatology, Hubert Lamb, identified when he set up the Climatic Research Unit (CRU) because,
…it was clear that the first and greatest need was to establish the facts of the past record of the natural climate in times before any side effects of human activities could well be important.
The situation is worse now sadly, due to people at the CRU and government weather agencies.
Lamb would be mortified because people at the CRU and those closely associated, including government agencies, manipulated the data to achieve results. Major evidence humans caused warming were made in the 2001 IPCC by Phil Jones, one of Lamb’s successors as Director of the CRU. He said global temperatures increased 0.6°C since the end of the 19th century. This was claimed to be outside natural increases and only possible because of human addition of CO2. The difficulty is, everyone ignores the error range Jones included of ±0.2°C. A 33 percent error factor would preclude its use in any other circumstance. Besides, we will never know because Jones lost the original data thwarting the fundamental scientific test of reproducible results.
It was likely selected, adjusted, and manipulated because this happens to all temperature data. Joe D’Aleo and Anthony Watts demonstrate the extent with examples of what and how it was done. This article presents one more way in which the location of selected weather stations influences and biases results.
Data was always inadequate, especially on which to build computer models, but that was ignored. A variety of statistical devices, most illogical, were created to produce the desired political result. The data situation has deteriorated considerably since Lamb retired. There are far fewer stations now than then. Figure 1 shows the number of stations in 1970 compared to 1997.
The map is misleading because each station dot is proportionally about 200km across – but still the change is dramatic. Gaps are so great they make analysis meaningless, but the National Oceanic and Atmospheric Administration (NOAA) does it anyway. As D’Aleo and Watts explain,
To fill in these areas requires NOAA to reach out maybe 1250km or more (in other words using Atlanta to estimate a monthly or annual anomaly in Chicago).
As D’Aleo explained to me,
GISS says they use 1200km, which means they search an area that covers 1,745,799.52 square miles to find data to fill in holes. This is roughly halfway between the total area of India and Australia and roughly three times the size of Alaska.
D’Aleo and Watts itemize the adjustments to the records, and in every case it enhances the amount and rate of warming. Other changes, such as use of fewer stations, and a higher percentage of urban and land stations, all enhance the warming.
Another factor that enhances warming is the predominance of stations in the middle latitudes, but particularly in eastern North America and Western Europe. Middle latitude monthly temperature variation is greater than in polar or tropical regions. Large planetary waves (Rossby Waves) form along the boundary between cold polar air and warm tropical air. The Waves migrate from west to east, creating a general 4- to 6-week cycle of temperature. Figures 2 and 3 show two different conditions of the Wave pattern relative to North America and Western Europe.
In this discussion a cold Wave is when polar air on the poleward side of the Jet Stream covers eastern North America and Western Europe as in Figure 2. It’s a warm Wave when tropical air covers these regions as in Figure 3.
Because of the general length of the Waves from peak to peak the likelihood of both areas being warm or cold is quite high. As a result the predominance of stations can skew the average for a particular month. The argument that the pattern cancels itself out over a year doesn’t hold. The stations used are predominantly urban and affected by the urban heat island effect (UHIE), this means the temperatures from the two regions are higher in summer and winter.
Dominance of the number of stations in these regions and at this latitude is significant because they’re a high percentage of the global total. This is just one more problem with a totally inadequate system, deliberately corrupted to achieve results for a political agenda.