Wood Romances

The graph below from John Shewchuk is intended to show that models predict too much warming compared to satellite data. Shewchuk claims that the red line is the average of 102 IPCC CMIP5 model runs for the surface through 50K feet. In all likelihood, this is just lifted from graphs of model-observation comparisons that John Christy has plotted in the past. Shewchuk claims the blue line is UAH satellite observations for the total troposphere layer (TTT). The problems with this graph are numerous, and many of the problems are inherited from Christy's graph (problems with his comparison are well-documented ). The two time series are separated from each other even in 1980 to exaggerate the differences between the two (even if the trendlines do intersect at 1980). The 102 model runs are not shown, only the model mean, and the 95% confidence interval is also not shown, so we have no idea what the spread in the model runs might be. But Shewchuk has added his own dishonest twist to this g...

The December 2024 data from RSS was just made available, so I thought I'd put together some summary graphs for RSSv4 and UAHv6.1. The 2023-2024 warming spike was more pronounced in satellite data, which is intriguing. But RSS continues to show more warming than UAH.   Here are trends for the full dataset and the last 30 years: 1979 - 2024 Trends UAH: 0.153 ± 0.012°C/decade (2σ) RSS: 0.230 ± 0.012°C/decade (2σ) 1995-2024 Trends UAH: 0.162 ± 0.025°C/decade (2σ) RSS: 0.249 ± 0.024°C/decade (2σ) These trends seem pretty disparate from each other (RSS shows ~50% more rapid warming), and my uncertainty calculation doesn't account for all the sources of error in these datasets. Most importantly (as I share here ), difficulties with satellites beginning around 1998 were resolved in different ways between RSS and UAH. The decisions made by each explain a good portion of the disagreement between them (they can be seen between 1998 and 2004 below), and that is not factored in to the abov...

There's a graph circulating on X created by Javier Vinós that is being used to suggest that global warming rates are actually decreasing. The origin of this graph comes from a WUWT blogpost , and it superficially seems convincing. The relevant graph is labeled "Figure 2," and the caption claims, "Evolution of the warming rate for 15-year periods between 1979 and 2022 in °C/decade and its linear trend, from monthly UAH 6.0 satellite temperature data." Javier Vinós Thinks Global Warming Rates are Decreasing Javier Vinós was kind enough to explain how he made this graph: "To analyze the evolution of the warming rate, we subtract from each monthly data the previous one to calculate the monthly increase. We then deseasonalize the monthly increase by finding the 12-month moving average to remove a lot of the noise. Finally, we calculate the 15-year average warming rate in °C/decade by calculating the 180-month moving average and multiplying the resulting data by ...

CO2 Coalition 's " Fact #21 " claims that "IPCC models have overstated warming by up to three time too much." According to this claim to fact, John Christy's testimony on "February 2016 to the U.S. House Committee on Science, Space & Technology included remarkable charts that document just how much the models overestimate temperatures. The red line in the chart shows the average of 102 climate model runs completed by Christy and his team at the University of Alabama at Huntsville using the models on which the IPCC itself relies. Also shown on the chart are the actual, observed temperatures. The models exaggerate warming, on average, two and a half times the actual temperature (or three times over in the climate-crucial tropics). Here's the graph they use to support this claim. The above graph reports to show 32 models and 102 model runs within the CMIP5 model ensemble. They are limited to those runs in the KNMI Climate Explorer. The models are s...

Sea Level Rise Since 1900 Humans have been very concerned with sea levels for centuries, since understanding tides and sea levels has been important for maritime travel, fishing, and many other aspects of coastal living, including recreation. We have built tide gauges to monitor sea levels, giving us a long-term record of sea levels along our coasts that can now be used for measuring sea level rise (SLR) in response to climate change. As scientists have become more interested in paleo climates, they have also developed reliable means of estimating sea levels going back thousands of years. Both of these methods, proxies and tide gauges, are generally limited to estimating sea levels along our coastlines, but in early 1990s, scientists developed a means to use satellites to estimate sea levels, and this approach for the first time allowed scientists to estimate global mean sea level (GMSL) from most of the surface of the oceans, rather than just our coastlines. Each of these lines of evi...

RSSv.4.0 and UAHv.6.0 Satellite Temperatures In a previous post , I summarized the most important reasons why the instrumental record is more accurate than satellites, and I showed that there is far more disparity between satellite datasets than there are among GMST datasets. In this post, I'd like to examine the satellite datasets to see if we can say to what extent some are more accurate than others. There are several satellite datasets, but three (RSS, UW and NOAA) strongly agree with each other, while the dataset from UAH is the outlier of the four. Keep in mind that in general all four of these use the same satellites So for the sake of simplicity, I'm going to simply compare RSS and UAH.  University of Alabama Huntsville (UAH) The UAH dataset is maintained by John Christy and Roy Spencer. For better or for worse, these scientists have strong disagreements with many of the conclusions of mainstream climate scientists. And at least in the opinion of many, perhaps not coinci...