Wood Romances

This is part one of a two part series on Marcott 2013. You can read the second part here . In 2013, Shaun Marcott and his collaborators published a global temperature reconstruction covering basically the entire Holocene - the last 11,300 years.[1] It was a significant achievement, and so it seems it must be vehemently attacked. The paper is nearly 10 years old at this point, and it's been both replicated and improved upon by later studies.[2][3] Perhaps therefore it's not really necessary for me to defend a paper that has both already been successfully defended[4][5][6][7] and has been replicated by further studies which use both more extensive proxies[2] and reanalyses.[3] However, the aspects of climate science that I find most fascinating are paleoclimate studies, and I would like this blog to develop a more or less "complete" treatment of the major paleoclimate studies that impact our understanding of climate science today. Seasonal Biases Long before Marcott...

I found csv file of the CMIP5 ensemble means for RCP4.5 and 8.5 on the Climate Reanalyzer website, so I downloaded both so I can do my own comparisons. I plotted multiple GMST datasets including 2 reanalyses with both RCP ensemble means from CMIP5. RCP4.5 over the last 15 years has been trending slightly warmer than observations. I don't have the 95% uncertainty envelopes, but observations here are clearly going to be well within the envelope.   But I decided to plot 30-year trends for these datasets with the expected 30 year trends in the two model ensemble means. It shows that while the models have expected a higher trends in warming over the last 15 years or so, RCP4.5 expects a steep drop off in warming rates right about now. This suggests to me that these scenarios are expecting a deceleration of our emissions in pretty substantially in ways that simply isn't happening. If current trends continue, we're likely to surpass RCP4.5 over the next decade or two, while RCP8.5...

95% CI Envelope for HadCRUT4 in McKitrick's Paper In a recent post , I shared why making conclusions from short-term trends is misleading. It's the kind of mistake that people make on social media, but I didn't think that I would find it in the scientific literature.  But in 2014, Ross McKitrick published a paper attempting to develop a statistical method for determining the length of the so-called "pause" in global warming through 2014. To do this, McKitrick calculated trends with 95% CIs through 2014 in 3 datasets - HadCRUT4, RSS and UAH. The lower bound CI overlapped 0 C/decade in 1995 for HadCRUT4, 1998 for UAH and 1988 for RSS. McKitrick then says these dates can give us the length of the "pause" in global warming. His words: I propose a robust definition for the length of the pause in the warming trend over the closing subsample of surface and lower tropospheric data sets. The length term J MAX is defined as the maximum duration J for which a vali...

In a recent post by Willis Eschenbach[1] at the Watts Up With That blog, we are again being told that there has been a recent decline in global temperatures. The argument was that a breakpoint analysis of multiple datasets reveals a break around 2015, and trends following that breakpoint are either flat or cooling. Yet it's completely unsurprising that such a breakpoint was found in 2015, since that was the beginning of a very large El Nino, and we haven't had a significant El Nino since. Instead, La Nina conditions have prevailed. Yet, the following is indisputable from the GMST data we have: 1. El Nino years are warming at about the same rate as La Nina years (both are warming at 0.2 C/decade since 1980). 2. El Nino years average almost 0.2 C warmer than La Nina years (the difference in the Y direction between the red and blue lines above). 3. The AGW warming signal is about 0.2 C/decade since 1980. 4. ENSO cycles between El Nino and La Nina inside of decadal time scales. Tha...

  A study was published last year that used two independent methods to estimate the rate at which the Earth's Energy Imbalance is increasing between mid-2005 and mid-2019. The first method used in situ measurements to calculate the planetary heat uptake. This method found the trend for 0–2,000 m ocean heat content anomaly to be 0.43 ± 0.40 W/m^2/decade. The second method used satellite measurements to calculate a CERES TOA energy flux of 0.50 ± 0.47 W/m^2/decade. These two trends were statistically identical to each other - the difference between them was 0.068 ± 0.29 W/m^2/decade.  The average value for EEI for the entire study period was 0.77 ± 0.06 W/m^2. In a previous post , I used three different estimates for EEI, this paper, one from Hansen (2005-2010) and one from von Schuckmann (2011-2018). I plotted all three of these values in the center year for the estimate in yellow as "studies."  In the above graph, I plotted the values for CERES and in situ measurements as...

In a previous post , I calculated ECS (accounting for increases in GHGs and aerosols) to be about 3.3 C.  The calculation was based on CO2 causing 2.11 W/m^2 increase in radiative forcing with a total increase, after accounting for GHGs other than CO2 and aerosols, of 2.17 W/m^2 (aerosols cancel out most of the effects of GHGs outside of CO2). One weakness of that approach is that it used a value for EEI that was an average for 2011-2018 with forcings that were current through 2020. I've been thinking about a way to improve this, and here's what I came up with. Transient Climate Response (TCR) Since the relationship between CO2 and temperature is logarithmic, I decided to plot the relationship between temperature and ln(rCO2) to see what that might be able to tell us about sensitivity from empirical data. So in the above graph, on the y-axis I plotted GMST from HadCRUT5 using a 1850-1900 baseline to match the IPCC's approximation of preindustrial levels. On the x-axis, I pl...

The IPCC (and others) have observed that there has been a near linear increase in GMST with cumulative anthropogenic carbon emissions. "In the literature, units of °C per 1000 PgC (petagrams of carbon) are used, and the AR6 reports the TCRE likely range as 1.0°C to 2.3°C per 1000 PgC in the underlying report, with a best estimate of 1.65°C."[1] To be clear, 1000 PgC = 1000 GtC = 1 TtC.  I decided to see if that has been observed in the empirical data. I took values from the 2021 global carbon budget [2] and HadCRUT5 set to a 1850-1900 baseline and plotted the relationship. The R^2 was 0.88, and the slope of the best fit line was 1.847 ± 0.104°C/TtC (2σ). So the 95% likely range is between 1.74 to 1.95 C/TtC from 1850-2021. If I start after we reach 200 GtC in 1951, the best fit line is 2.153 ± 0.176°C/TtC (2σ) and the R^2 increases to 0.90, but I think it's best to be conservative here. What this suggests to me is that the IPCC may again be a bit conservative their best e...