chubbs

The bulk of the post-war Coatesville cooling occurred in 1946 and 1947 which is consistent with a 1946 move. The cooling relative to West Chester and ABE also matches the timing and roughly 2F magnitude of the NCEI and Berkeley Earth bias adjustments that you posted above.

Very interesting. More evidence supporting bias adjustment in Chester County. The detailed documentation describes many more station changes than the NCDC documented. Indicates that the move from the City of Coatesville to Doe Run Road occurred in 1946. Per NCDC documentation Doe Run road site wasn't used until 1949.

Most of the Arctic Ice caps are having a record or near record melt year. The exceptions are Greenland which has above average losses and Ellsmere Island the which has below average losses. The loss distribution is consistent with the average temperature map since May 1. The Atlantic side of the arctic has been warm, while the Pacific side has been cool. Other than Ellesmere, the arctic ice caps are on the Atlantic side. https://www.climato.uliege.be/cms/c_5855702/fr/climato-arctic

Nope. Your station selection and AI's method are both faulty. The key period for evaluating the Coatesville post-war moves is 1945-1950, the period immediately after the war when the moves occurred. I didn't include Sadsbury, Kennett Square, and the other Chesco stations you listed, because they didn't operate in that period. After reading the AI analysis more closely, I see that AI used regression analysis to make its determination. As I said above, that is a poor choice because the station moves are focused in time not spread out over a long period of time. AI based its conclusion largely on regression results from Devault and Morgantown both of which didn't start operating until 1951. AI is drawing a conclusion from two stations that don't provide any information on the Coatesville post-war moves; because, they weren't operating at the time. A clear indication of a faulty analysis approach. With 2 of the 3 Chesco stations, Caotesville and Phoenixville, both experiencing spurious cooling between 1945 and 1950, It is important to include non-Chesco stations in the analysis. That's why my analysis included 10 non-Chesco stations. The non-Chesco stations and West Chester agreed completely with West Chester in identifying the common weather signal between 1945 and 1955. Having the common weather signal makes identification of the Coatesville and Phoenixville moves easy; and, with plenty of stations is highly significant statistically. A faulty analysis does not disprove a good one. To disprove my analysis, you need show that the significant difference between the move and non-move stations in the 1945-55 period changes when more data is added. Good luck with that, the P value is 0.0001.

Extended the stat analysis to the 1970s to include the West Chester move. Two comparisons were made: individual years using 1972 minus 1945 as a metric, and a 5-year average using 1971-75 minus 1941-45 as a metric. The results are the same for both metrics: the Chester County COOPs are significantly different statistically from the non-Chesco stations. As was the case for the 1950s there is no overlap between the move and non-move stations. The Chester County COOPs have spurious cooling of over 2F. This analysis and the one above provide strong evidence that the larger NCEI bias adjustments are very robust statistically. This analysis also shows the problems with AI. As Don stated above AI is handy for an initial screening; but, AI is unlikely to give a complete and accurate answer to a complex problem.

Here's a closer look at the statistics of the Coatesville and Phoenixville post war moves. Differences between stations was removed by setting 1945 to zero to facilitate comparison between stations. Coatesville and Phoenixville behaved differently than the other stations, cooling relative to the other stations at the time of the moves; and, remaining cooler after the moves.. Using the temperature difference between 1945 and 1952 as a metric, Coatesville and Phoenixville are significantly different from 11 stations without station changes. The P value is 0.0001 which means that there is virtually no chance that Phoenixville and Coatesville are the same as the other 11 stations. Furthermore Phoenixville and Coatesville are significantly different from the other stations in every year after the moves in this period. Finally note also the good agreement among the 11 stations without changes. Chester County shares the same weather with a much larger region. Many stations can provide useful information on the Chester County COOP stations; which makes the identification of Chester County station changes very robust.

A good first step in using the raw data to identify station changes, with several station changes identified. What's missing are most of the station changes in Chester County. A couple of issues cause station changes to be missed: 1) It appears that only station moves and TOB changes described in NCDC documentation were investigated. There are two problems: NCDC documentation is incomplete and there are many other causes of station changes besides moves and TOB. 2) The common weather signal across stations is not identified. Having this signal facilitates the identification of station changes. and 3) Stations outside of Chester County are not used. Comments 2 and 3 work together. It easier to identify the common weather signal with more stations. The fact that many station changes are missed causes station comparison to break down. In summary the analysis is much less thorough than NCEI's A couple of comments on write-up itself. First like most AI its very wordy and wishy-washy. Too long to review carefully in detail. More importantly, there are no charts or quantification of any kind. Impossible to verify or compare to other results without hard numbers.

That's the $64 question for this year. Will we see the same type of "gobsmaking" global warming we saw in 2023 or will this year behave more like a typical strong/super el nino. So far I'd put this year in the typical camp, with global air temperatures lagging the rise in ENSO and global SST. One aspect that has held back global temperatures in the past 2 months has been very cold temperatures in Antarctica associated with a strong AAO+ regime. In 2023 AAO was strongly positive in January (see AAO table below), reversing by March, and staying negative through September. So the AAO boosted global temperatures in the first half of 2023 but are holding them back this year. One of the many factors that contributes to a different outcome in 2026 vs 2023. If the AAO reverses in August there will be an added boost in global temperatures on top of ENSO. We will see. 2023 2.304 0.554 -0.258 -0.921 1.452 -0.438 -0.818 -0.038 -1.050 0.535 0.097 1.510 2024 0.922 1.043 -0.058 1.005 -0.073 0.210 -0.597 -2.150 0.098 -0.567 1.020 -0.826 2025 -0.080 -0.271 0.733 1.138 0.509 0.209 0.753 0.357 -0.709 -1.236 -1.324 -1.136 2026 0.848 0.489 0.492 -0.125 0.544 2.506

OK lets see what the raw data says. After all bias adjustments are based solely on raw data. If the the steel mill impacted the Coatesville station it would be reflected in the raw data and in the NCEI bias adjustment. Below is a plot of Coatesville 1SW minus West Chester and the Coatesville bias adjustment (right axis). A station change at either Coatesville or West Chester causes a sudden change in relative temperature of Coatesville and West Chester. While a growing steel mill or an urban heat island in one of the towns would cause a gradual change in the difference between the two stations. There are many large sharp changes in Coatesville's temperature relative to West Chester. These are all station changes. There is no indication of a gradual long-term trend so a large change in the steel mill impact can be ruled out. Station changes are the primary cause of Coatesville's (and West Chester's) cooling. The Coatesville bias adjustment (right axis) tracks the raw temperature data at Coatesville and West Chester closely, capturing the each wide swing due to station changes. The only exception to the close tracking is when West Chester had station changes: 1915, the 1920s, the 1960s and with the West Chester move in 1970. Both stations start out at about the same temperature in the 1890s. Between 1894 and the 1960s, most of the chart movement is due to Coatesville station changes as West Chester experienced relatively minor station changes. After 1920 Coatesville cools relative to West Chester. The change is anything but gradual with several large swings due to station changes. From the late 1940s to the late 1950s Coatesville is 2F cooler than West Chester. The rural Doe Run Road site is the coolest Coatesville station location. Coatesville warms by roughly 0.5F around 1960. After 1960 the main station changes are at West Chester, ending in the 1970 move which cools West Chester to down Coatesville's level. Note that station changes can be warming or cooling, but on balance both stations cooled significantly over the period due to station changes. This exercise is another feather in NCEI's cap. The Coatesville and West Chester raw data shows that bias adjustments are needed and accurate in Chester County. No surprise if you have been reading the thread.

You left in all the other station changes. Your current station population is much cooler, more rural, and higher elevation compared to the older COOPs. All the COOPs were in towns before the Coatesville post-war move. The more I look at the Chesco COOP data the more problems I find. Per NCDC the Coatesville 1SW shelter was made of window blinds before 1902. The "window blinds" apparently produced a big spike in 100F days in 1900, which wasn't observed in West Chester or Philadelphia. After the "window blind" spike, the Coatesville 1SW data is similar to Philadelphia and West Chester with no indication of the pronounced downtrend you are showing. Once again the local raw data doesn't agree with the climate trend you are reporting.

Yes TOB is not an issue at Coatesville. The big issue is station moves and other changes. The NCDC chart below shows all the locations of the Coatesville COOP station. The station numbers increase as you go back in time: Site 1 is the newest and site 6 is the original site. The most consequential move was the last one from site 2 in the City of Coatesville to to a rural site on Doe Run Road. The pictures illustrate the change. As documented in the Chester County thread roughly 2F spurious cooling with this move. photos

July to-date satellite OiSST has reached the peak anomaly from the 2023-24 nino.

We have a good example in Chester County PA. Here are high temperatures for July 1934 and 1936 for 4 local stations. Phoenixville ran much warmer than the other stations probably due to poor shelter placement. Phoenixville also carried over hot temperatures to the next day when the other stations cooled. This shows that the Phoenixville max/min thermometer was flipped near the time of peak temperature while the other stations were not. Phoenixville completely dominates the # of 95 and 100F days in Chester County in the 1930-40s, but the data is spurious. This is why I don't trust plots of historic max temperatures in the US, unless the data has been scrutinized for bad data. Only takes one or two bad apple stations to create a spurious result.

Nope no dust bowl in Chester County, just Phoenixville with a bad shelter location. Philadelphia and West Chester don't agree at all with your plot. Not surprising since once again you are confounding station changes and weather. East Nantmeal and West Grove are a little different than the City of Coatesville or West Chester don't you think?

Clear that you do not understand the science behind bias adjustments. Bias adjustments are not made in an ad hoc manner or to raise or lower the temperature of a station. Bias adjustments are only made to correct station changes. If the station observation time doesn't change, then no adjustment is needed. Adjustments are based solely on raw data. A station has to change with time in a manner that is different from all other stations that experience the same weather. The goal is to include weather and exclude station changes when calculating long-term climate trends. The only way to evaluate bias adjustments is to inspect raw station data at the time of the station change. Here's an example using the West Chester 1970 move. The old West Chester COOP shut down in December of 1969 and re-opened in May of 1970 at a new location. Subtracting Coatesville from West Chester isolates the relative temperature changes at the two stations at the time of the move. The raw data shows that the new West Chester site cooled by significantly relative to Coatesville after the move. That's all the proof needed to identify a major station change at either Coatesville or West Chester. We know from raw data from Phoenixville that West Chester is the guilty party. The Chesco raw data clearly shows that West Chester cooled significantly after its 1970 move. The NOAA bias adjustment is in complete agreement with the raw data from Coatesville and West Chester. That shouldn't be surprising. NCEI is using all the raw data that experiences the same weather as West Chester, hundreds of stations potentially. I've looked at multiple large station changes at the Chesco COOPs and NCEI nails every one. Note that NCEI is asking a similar question as your AI analysis. Does West Chester respond to local May 1970 weather in the same as the other regional stations? However the NCEI procedure is much more targeted than AI, is using more data, and it is using the right conceptual model. The temperatures at West Chester do not vary independently of the temperatures at Coatesville or other stations. This gives the NCEI analysis much more power. It can correctly flag the West Chester move as a major station change. While your AI analysis can not. The raw data is the final arbiter and in this case NCEI is clearly superior to AI.