Re: [asa] Data doesn't support global warming

From: Rich Blinne <>
Date: Mon Dec 21 2009 - 11:29:53 EST

Since I got slapped by the moderator yesterday for too many posts, I'm combining posts.

Bill check out this study. The study you cited only accounts for up to 50% of the warming. This study accounts for all of it once AGW is added to the solar forcing.

On Dec 21, 2009, at 7:05 AM, John Walley wrote:

> Rich,
> Thanks for acknowledging the "Human Sacrifices for Gaia" concern is valid and worth tracking. Your comment that it didn't get the level of attention that the "crazies" wanted is also valid and somewhat reassuring. It doesn't remove the threat however and there are still voices on the sideline advocating for it. And I think it would be obvious that if dark and evil forces really did intend to do something like this they wouldn't be letting on to it before they had the control they needed which isn't the case yet, so this may be just a false negative.

China's problem is not its population but its use of coal-fired power plants. It's also vitally important to find a way to get China to be more transparent on lowering emissions from these plants. One internal motivation is the correlation between their horrid electrical generation strategy and urban pollution. We had several families from China, Taiwan, and South Korea over for Thanksgiving. We asked them what their most favorite thing and least favorite thing was in the U.S. Everyone said the same thing. Their most favorite thing was our clean air and their least favorite thing was our health care system. Developing and exporting clean electrical generation technology to China would have two very positive benefits. Number one it would help the global warming situation and number two would also provide employment opportunities that wouldn't get outsourced. How that is done is of great debate and might get heated so I will skip the discussion here. But, at least I believe all sides can agree that that is a worthy goal even if we might disagree how that goal might get achieved.

For this next anecdote I will be deliberately vague (why should soon be obvious). Another Chinese couple we know found that they were pregnant with their second child. Members of an organization I am affiliated with encouraged them to keep the child. Little Jonathan is now nine months old. Even of those who are somewhat positive towards the one child policy it's viewed more as a necessary evil. Furthermore, they look at it as a specifically Chinese problem and are not advocating it for others. So, China isn't really pushing it abroad and they certainly haven't affected India. The Western neo-Malthusians from what I can tell are viewed as nuts by the nuts. One of the positive things that having Christians being involved with environmentalism is to provide some balance and moderation to the movement. Call me naive but I believe we have affected environmentalism more than the other way around. But, as I said before it's always good to be on guard and I viewed Chuck Colson's comments as a cautionary tale.

> Also I appreciate the averaging insight but there has to be some established mathematical approach like higher highs, lower lows, etc that can be agreed on up front that would be an accurate indicator of overall trends for this debate to be meaningful. As I said I am happy to accept however the trends come out and I am continuing to listen in on the debate with much interest. I think Glenn's point is valid though about the siting of the thermometers. If 69% is really the true number of sites violating their own guidelines then that is damning in my opinion.

> Also as someone else mentioned, I don't think anyone ever realized that something as mundane and trivial as daily temps in some backwoods place would ever be used in such an important decision is accurate. We have to take this data even from the 31% properly sited stations with a grain of salt and I am not convinced it is accurate enough to discern anything very accurately.

I'd take that 69% number with a grain of salt. For example, when I checked the Fort Morgan CO station in the GHCN Google Maps showed its location was in the middle of a farm field. The people who are cataloging the bad stations can help everybody out if they give the WMO station number which would show whether they are in the GHCN list or not. If they found something really egregious then these stations could be given special attention or dropped. Of the U.S. stations used to compute climate change16% of the stations are in areas with more than 30,000 people and many of the urban stations are in parks. Here is a comparison on what the warming looks like when comparing all the stations against the rural stations:

Here's the extended discussion in AR4 concerning the larger issue of UHI:

Many local studies have demonstrated that the microclimate within cities is on average warmer, with a smaller DTR, than if the city were not there. However, the key issue from a climate change standpoint is whether urban-affected temperature records have significantly biased large-scale temporal trends. Studies that have looked at hemispheric and global scales conclude that any urban-related trend is an order of magnitude smaller than decadal and longer time-scale trends evident in the series (e.g., Jones et al., 1990; Peterson et al., 1999). This result could partly be attributed to the omission from the gridded data set of a small number of sites (<1%) with clear urban-related warming trends. [RDB Note: just because you have a picture you then need to see if it's in the gridded data set.] In a worldwide set of about 270 stations, Parker (2004, 2006) noted that warming trends in night minimum temperatures over the period 1950 to 2000 were not enhanced on calm nights, which would be the time most likely to be affected by urban warming. Thus, the global land warming trend discussed is very unlikely to be influenced significantly by increasing urbanisation (Parker, 2006). Over the conterminous USA, after adjustment for time-of-observation bias and other changes, rural station trends were almost indistinguishable from series including urban sites (Peterson, 2003; Figure 3.3, and similar considerations apply to China from 1951 to 2001 (Li et al., 2004). One possible reason for the patchiness of UHIs is the location of observing stations in parks where urban influences are reduced (Peterson, 2003). In summary, although some individual sites may be affected, including some small rural locations, the UHI effect is not pervasive, as all global-scale studies indicate it is a very small component of large-scale averages. Accordingly, this assessment adds the same level of urban warming uncertainty as in the TAR: 0.006C per decade since 1900 for land, and 0.002C per decade since 1900 for blended land with ocean, as ocean UHI is zero. These uncertainties are added to the cool side of the estimated temperatures and trends, as explained by Brohan et al. (2006), so that the error bars in Section, Figures 3.6 and 3.7 and FAQ 3.1, Figure 1 are slightly asymmetric. The statistical significances of the trends in Table 3.2 and Section, Table 3.3 take account of this asymmetry.

The bigger problem from an error perspective when it was studied by Folland et al was sea surface temperatures in the SH before the 1940s. These were the differences in the temperature record that caused Glenn to have a cow. The reason for the problem was the spatial gaps of the measurements. If you are concerned about the accuracy of the temperature measurements it's far more important to have many not-so-good stations than fewer more perfect ones. Homogenization works well when that happens. When you have a limited number of high quality stations like at Darwin Airport it sometimes doesn't work so well. The Darwin situation was particularly problematic was that there was no overlap when the station moved in 1941 forcing extrapolation. As you well know extrapolation is far more error-prone than interpolation. It's like the NT record where there are many small variations. The fact that we have many highly imperfect copies allows us to reconstruct the original text. In the same way, the imperfect stations we have in aggregate are sufficient to have an accurate record for global climate change even if they cause the microclimate specialists fits. The siting requirements are to accommodate both micro and global climate so merely failing that requirement doesn't necessarily imply a problem for studying climate above the micro level. Still, as the science advances we need to understand the local effects and not dismiss it as "not global". Because of this NOAA is building brand networks that don't have the problems discussed. See here for more details: And since Glenn wants to post pictures I can too. :-)

> Also Glenn's repeated point that the overall reported warming trend being less than the error bars is also a very valid observation and one that is seeming to be inored.

Just because Glenn repeats it doesn't make it true. It's nowhere near valid. Here's the table of trends along with the error bars from AR4. Note also that the timescale is varied because AGW is accelerating particularly after 1980. The statistically significant trends are in bold. See Table 3-2

Temperature Trend (oC per decade)
Dataset 18502005 19012005 19792005
Land: Northern Hemisphere
CRU (Brohan et al., 2006) 0.063 0.015 0.089 0.025 0.328 0.087
NCDC (Smith and Reynolds, 2005) 0.072 0.026 0.344 0.096
GISS (Hansen et al., 2001) 0.083 0.025 0.294 0.074
Lugina et al. (2006) 0.079 0.029 0.301 0.075
Land: Southern Hemisphere
CRU (Brohan et al., 2006) 0.036 0.024 0.077 0.029 0.134 0.070
NCDC (Smith and Reynolds, 2005) 0.057 0.017 0.220 0.093
GISS (Hansen et al., 2001) 0.056 0.012 0.085 0.055
Lugina et al. (2005) 0.058 0.011 0.091 0.048
Land: Globe
CRU (Brohan et al., 2006) 0.054 0.016 0.084 0.021 0.268 0.069
NCDC (Smith and Reynolds, 2005) 0.068 0.024 0.315 0.088
GISS (Hansen et al., 2001) 0.069 0.017 0.188 0.069
Lugina et al. (2005) 0.069 0.020 0.203 0.058
Ocean: Northern Hemisphere
UKMO HadSST2 (Rayner et al., 2006) 0.042 0.016 0.071 0.029 0.190 0.134
UKMO HadMAT1 (Rayner et al., 2003) from 1861 0.038 0.011 0.065 0.020 0.186 0.060
Ocean: Southern Hemisphere
UKMO HadSST2 (Rayner et al., 2006) 0.036 0.013 0.068 0.015 0.089 0.041
UKMO HadMAT1 (Rayner et al., 2003) from 1861 0.040 0.012 0.069 0.011 0.092 0.050
Ocean: Globe
UKMO HadSST2 (Rayner et al., 2006) 0.038 0.011 0.067 0.015 0.133 0.047
UKMO HadMAT1 (Rayner et al., 2003) from 1861 0.039 0.010 0.067 0.013 0.135 0.044

Rich Blinne
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Received on Mon Dec 21 11:30:29 2009

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