So who can answer Jerry Pournelle's questions about Global Warming?

[godix]

@Sam_Stone

I’ll offer again to participate in a thread on global warming solutions that starts from the premise that global warming is happening, that the IPCC report is roughly correct, and which proceeds from those assumptions.

I don’t entirely buy into the premise, while I accept global warming I have major concerns about the IPCC, but what the hell, I’m bored so I’ll play along.

Let me add one more premise to yours though. Regardless of what we do, the climate will change. I’m not spewing the common BS argument that it used to be hotter so everything is fine now. Rather I’m saying that even if we control our greenhouse gases emissions, the climate will eventually change due to factors entirely beyond humans control. The factors that caused changes before man would still exist after all. So it’s entirely possible we spend trillions fighting CO2 and then a volcano on the scale of Mount Tambora or Krakatoa changes everything for years anyway.

Since this is pretty much a certainty, I consider spending large amounts of money, resources, and political will to fighting AGW to be pointless. Even if we win that fight, we’ll lose the war against climate change. Now certainly green energy should be pursued, but rather for reasons of energy independence and that oil & coal are limited resources. Since they won’t run out for quite awhile though, there’s no real reason we must have it right this instant. So continue researching it, but delay the plans to push it into production today, even though a lot of it isn’t financially or technologically reasonable yet.

In the mean time, we should in invest in adaptation technologies. These would all provide benefits when the climate changes, regardless of what the reason for the change is. As an added bonus, most of them would provide other benefits currently as well. Here’s some of the techs I think we should be pouring money into instead of all the various carbon capture schemes.

• Desalinization. It’s technologically possible, but still very expensive. Once we have affordable desalinization, we could literally farm the deserts.

• Water management. Along with the desalinization, this needs controlled. Many parts of the world are seriously overtaxing the water table. If we could improve water management that would benefit when the climate changes, and also help head off problems with shrinking water tables which has nothing to do with AGW.

• Improved farming. There are a variety of methods to this, anything from the chemical heavy farming to genetic engineering crops to withstand harsher environments to just better farming methods. I’ve read several recent articles about methods that do not use harsh chemicals or GE modified crops but still yield increases that are roughly similar.

• Disaster management. Within just the last few years we saw an earthquake in china that killed or injured up to half a million, a tsunami that killed a quarter of a million over 14 nations, New Orleans turned into a hellhole for survivors, etc. Climate change is predicted to cause more natural disasters over time. We should be sinking money into preparation for these sorts of things and well developed emergency response to them. Even if AGW doesn’t cause more disasters, it’s not like there aren’t plenty of disasters that have nothing to do with climate change anyway

• Improved infrastructure. Should be self explanatory really. If we’re going to have to move people or goods around to deal with changes, we’ll need an infrastructure to move it around on. This mostly is an issue in the poorer areas of the world. The first world generally has a decent infrastructure, although not without it’s own problems.
  Those are just a few suggestions off the top of my head. As you can see, the common point of them is that none are dedicated to fighting AGW. If we can adjust and cope with it instead, that’s a solution as well. It is a solution that has far larger benefits that developing technology for carbon sinks or political treaties to reduce CO2 emissions.

[Whack-a-Mole]

@Magiver

You keep talking about fossil fuels and I’ve never mentioned it once.

Not explicitly no but you were complaining about the cost of solar tech. Well, “expensive” has to be in relation to something. A Cessna airplane is expensive in relation to a car but cheap in relation to a Lear Jet.

The “cheap” stuff today is the stuff that relies (mostly) on fossil fuels for power (add in nuclear and that rounds it out).

Most new technology tends to be expensive at first. Just the way of things. Over time those costs should drop.

[GIGObuster]

@godix

Let me add one more premise to yours though. Regardless of what we do, the climate will change. I’m not spewing the common BS argument that it used to be hotter so everything is fine now. Rather I’m saying that even if we control our greenhouse gases emissions, the climate will eventually change due to factors entirely beyond humans control. The factors that caused changes before man would still exist after all. So it’s entirely possible we spend trillions fighting CO2 and then a volcano on the scale of Mount Tambora or Krakatoa changes everything for years anyway.

The reality is that the effect of particulates from volcanoes is short lived, the role of science is not to sit down and marvel why changes happen, but why and what forces climate change?

The overwhelming reasons remain solar irradiation and carbon dioxide. And the solar output is not correlating with the current warming.

potholer54

[wevets]

Re: Systemic error in global temperature measurement

There are four major global surface temperature records, NASA’s GISS, the Hadley Centre’s HADCRU, Japan’s JMA, and NOAA’s NCDC. They all use different methods to generate averages and grid boxes from the global thermometer measurements, but they all do show general agreement (graphs showing the different datasets on the same axes can be found here and here,) which makes me wonder - if there is some sort of post-measurement bias, then why wouldn’t at least one of the four datasets not have it? Or wouldn’t the bias show up as favoring warming or cooling? (here is a graph showing the symmetry of adjustments made - there doesn’t appear to be systematic bias in favor of warming or cooling (and the adjustments in general are quite small, with a mean adjustment of 0.017°C decade[sup]-1[/sup].)

I’m sure no-one will be surprised that climate scientists have investigated the question of systematic error in temperature measurement. A paper, quoted below, exploring the possibility of spatial bias due to incomplete and uneven coverage of temperature stations around the globe found that the errors accounted for by spacing and timing are very small relative to the detected trends in temperature:

@Jones et al. 1997

Typical standard errors estimated for annual data on the interannual timescale since 1951 are 0.059°C, implying that individual years need to be at least 0.12°C apart before they can be classed as being significantly different from one another. The reduction in data availability prior to 1950 increases errors associated with annual estimates. For the second half of the ninteenth century the standard error is 0.091°C, making it harder for two years to be significantly different from one another. The standard errors reduce on the annual interdecadal timescale to 0.048°C (1951–95) and 0.078°C (1851–1900).

Source: Jones et al. 1997. Estimating sampling errors in large-scale temperature averages. Journal of Climate. Vol. 10, pgs. 2548-2568.
From time to time, new temperature analyses are compared to older ones, and so far the story has not been one of changing the basic picture of global temperature changes, instead the newer estimates tend to refine the picture and add specificity to the amount of uncertainty. This quote from a new surface temperature analysis by Smith et al. illustrates that:

@Smith et al.

A great deal of work has recently been done to improve the accuracy of NCDC’s surface temperature analyses. These comparisons show that the new analysis has essentially the same interannual to interdecadal variations in global averages. Where differences do occur they are primarily confined to the early years, when sampling is more sparse. An advantage to the new analysis is the availability of uncertainty estimates. The addition of more observational data could reduce these uncertainty estimates and make regional analyses more accurate, but these results suggest that more data would be unlikely to greatly change the average global temperatures over most of the analysis period.

Source: Smith et al. 2005. New surface temperature analyses for climate monitoring. Geophysical Research Letters Vol. 32, L14712
Even John Christy, much loved by climate change deniers everywhere because his satellite tropospheric temperature measurements tend to show less warming than surface or other satellite measurements, participated in this analysis that concludes the nonrandom errors are much smaller than detected trends:

@Karl et al.

Experiments have been conducted to quantify the potential magnitude of this error. The analysis includes errors introduced into the climate record because of both incomplete global coverage and inadequate sampling within those areas presumed to have adequate observations. In these experiments the uncertainty in calculating historical temperature trends is dependent upon the pattern of temperature change, the method of treating the effect of nonrandom spatial sampling, and the time and length over which the trend is calculated but is relatively insensitive to the random errors associated with estimating regional-scale (grid cell size) temperature anomalies. Results imply that errors associated with century-scale trends of temperature are probably an order of magnitude smaller than the observed global warming of nearly 0.5[degrees]C per 100 years since the late nineteenth century.

Source: Karl et al. 1994. Global and hemispheric temperature trends: Uncertainties related to inadequate spatial sampling. Journal of Climate Vol. 7:7

Re: The Urban Heat Island Effect. As Chronos had mentioned, since the UHI has been known for a long time, there’s plenty of research out there showing that the manner in which data is treated eliminates the UHI from the reported trends.

@David Parker

The main impact of any urban warming is expected to be on Tmin on calm nights (Johnson et al. 1991). However, for 1950–2000, the trends of global annual average Tmin for windy, calm, and all conditions were virtually identical at 0.20° ± 0.06°C decade[sup]-1[/sup] (Fig. 4a,b and Table 1). When the criterion for calm was changed to the lightest decile of wind strength, the global trend in Tmin remained 0.20° ± 0.06°C decade[sup]-1[/sup] (Fig. 4c). So the overall analysis appears not to show an urban warming signal and to be robust to the criterion for calm.

Source: Parker, DE. 2005. A demonstration that large-scale warming is not urban. Journal of Climate Vol. 19, quote from pg. 2886.

This isn’t isolated work either …

@Folland et al.

Since 1979, trends in worldwide LSAT derived from high-quality records at weather stations in the Northern Hemisphere, in regions where urbanisation is likely to have been strong, agree closely with satellite-derived temperature trends in the lower troposphere above the same regions. This suggests that urban heat-island biases have not significantly affected assessed surface temperature over the period.

Source: Folland et al. 2002. Observed climate variability and change. Weather Vol. 57, quote from pg. 276.
The UHI would be extremely easy to detect as a non-random bias, since all you have to do is compare urban to rural or compare windy days (when the heat coming off the concrete won’t have a large effect on air temp.) to non-windy days.

It is true that non-random error is a much more intelligent critique of the global temperature record than the one Pournelle posted on his site, but I have yet to see evidence that the non-random error is larger than the literature indicates.