Wood Romances

One of the most common studies cited in favor of a low equilibrium climate sensitivity (ECS) was published by Lewis and Curry in 2018 (LC18).[1] Their paper used the standard energy balance equation I've used in previous blogposts to estimate both ECS and TCR. They arrived at median estimates with 95% uncertainties of 1.66 C for ECS (1.15–2.7 C) and 1.33 C for TCR (1.0–1.9 C). These values are significantly below the range estimated by the more recent IPCC assessment reports. Since the publication of this paper, Sherwood et al 2020[2], published what may be the most comprehensive assessment of ECS and found a 95% range of 2.3–4.7 C. Argument of LC18 So I thought it might be interesting to do a back-of-the-envelope style update to LC18. I think there are several reasons why this can be valuable. Since the publication of this paper, a number of new insights have been published: The publication of HadCRUT5 had significant improvements over HadCRUT4, even the dataset with kriging to li...

  This is part 2 of a series on the Hockey Stick (updated 1/8/2025 to correct statements I made about the scale of a graph). Here's part 1 . When Mann and his colleagues were constructing their proxy reconstruction for NH temperatures for their MBH98 paper, there were two significant challenges that had to be addressed. The first was calibrating proxy model to the instrumental record. They can't expect that the proxy data would match the instrumental record with absolute precision, so if they over-calibrated the model, the proxy would fit the instrumental record but would not reconstruct earlier temperatures. Random noise in the proxy and instrumental data will make the proxy data less reliable in reconstructing the past. So the challenge was to fit the overall climate trends in the proxy data to the instrumental record while allowing for variability between the two datasets. The second challenge was to address the clustering of climate proxies so that one set of proxies doesn...

Berkeley Earth just released a new version of the GMST dataset, and it has 4 times the spatial resolution of the previous version of the data set at 0.25° x 0.25° (that's about 30 km at the equator). Visually, the difference is pretty striking when viewing temperature anomalies as a map. Here, for instance are 2022 global temperatures relative to a 1981-2010 mean. The time series has also slightly different from the previous version. Comparing the new high resolution dataset to the previous version, global temperatures in the base period appear to be slightly higher, lowering the amount of current warming above the 1980-1900 mean slightly. However, current warming rates appear to be slightly higher, at about 0.22 °C /decade instead of 0.21 °C /decade for the last 30 years. Here's how 30-year trends have changed across the dataset. To illustrate this, in a recent post , I calculated the warming above the 1850-1900 mean in the three datasets that go back to 1850, and the current ...

After Michael Mann and his colleagues (MBH) published their first "hockey stick" paper in 1998[1] and its follow up in 1999[2], scientists had compelling evidence that recent warming, especially warming following 1950 or so, was unique in recent centuries. Geological evidence revealed that recent increases global and NH temperatures were detectable at rates beyond the natural variability observed over the last several hundred years. The resulting "hockey stick" graph was used in the IPCC's third assessment report, and the contrast between this graph and the previous schematic in the 1990 report was visually evident. The 1990 schematic was not a true reconstruction of global or even hemispheric temperatures; it was indistinguishable from a reconstruction Central England temperatures published in Lamb 1965. The 1990 graph was only a schematic with no temperature scale, and it ended in ~1950. The MBH "hockey stick" reconstruction was the first time the IP...

Every year I try to think of a way to update my simple calculations for ECS and TCR. My methods don't really change that much; they reflect updated data and become a little more complex. Make no mistake, they are simple calculations based on estimates of forcings, temperature and EEI using the energy balance equation. It doesn't compete with peer-reviewed studies by Sherwood[1] or the assessments of the IPCC. My intent with this is to show that the central estimates of the IPCC (and most climate models) are very consistent with empirical data.   The first step in the calculating ECS and TCR values is assessing the earth's energy imbalance and collecting the relevant forcing data. Earth's Energy Imbalance There are several estimates for EEI to choose from, but I think the most conservative approach is to use an average value for the full time frame between 2005 and 2019, when observations become much  more reliable. One study, Loeb et al 2021[2] estimated EEI to be 0.77 ...

In previous posts in this series , I've tried summarize what I consider bad behavior among those debating climate change. So far I've discussing what I consider statistically unethical practices - using short-term trends, misusing scales, and using local instead of global data. Here I'd like to look how we make comparisons between types of data. In climate science, we need to deal with all sorts of different kinds of data. For global temperatures, I can think of at least 3 - proxies, the instrumental record (satellites, thermometers), and models (reanalysis, modeled projections, etc). It's perfectly fine to create graphs that include all of these kinds of data, but in doing so, we have to make sure that we are communicating honestly and making comparisons accurately. Proxy data has lower resolution and larger confidence intervals than the instrumental record, and modeled projections always depend in part on the assumed scenario, and confidence intervals for these projec...