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Senior Member
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Join Date: Mar 2011
Location: BC, CANADA
Posts: 1,557
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Senior Member
Join Date: Mar 2011
Location: BC, CANADA
Posts: 1,557
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1engineer, here is an interesting read on how satellite data, and in particular much of the data you cited (UAH, HADcrut4) has been interpolated and what most scientist think are the problems with how they extrapolated that data.
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Conclusion
The existence of bias in recent global mean temperature estimates has been confirmed by multiple means. This bias leads to an underestimation of recent temperature trends. The evidence is as follows.
(1)
Microwave sounding data from satellites, reanalysis data from weather models and observations from isolated weather stations all confirm that the unobserved regions of the planet and in particular the Arctic have been warming faster than the globe as a whole since the late 1990s.
(2)
Extrapolation by kriging and a hybrid method guided by the satellite data have been examined. Both provide good temperature reconstructions at short ranges. Over longer ranges the hybrid method performs well over land and kriging performs well for SSTs.
(3)
Extrapolation over land/ocean boundaries is problematic; however, observations and reanalyses confirm that air temperatures over ice are better reconstructed from land-based air temperature readings. Since the highest latitude observations are land-based, reconstruction from the blended land/ocean data is realistic.
(4)
The application of either kriging or the hybrid method to coverage-reduced reanalysis data produces global temperature estimates with substantially reduced uncertainties in comparison with simply omitting the unobserved regions.
The main benefit of the hybrid method is to bring observational data to bear on the question of coverage bias. However, the method is dependent on the satellite data and so only applicable from 1979. Given that the hybrid results are not very different from the kriging results, simple extrapolation appears to be justified for current levels of global coverage. In practice, the choice of extrapolation method makes little difference once the Antarctic stations are available: kriging, the GISTEMP kernel-smoothing method, inverse distance weighting and even basic nearest-neighbour give very similar results, especially when used in combination with a 1200 km cut-off as employed by GISTEMP (see supporting information). For periods prior to the establishment of the Antarctic stations, coverage is less complete and coverage bias remains an issue.
Around the poles, the NCDC temperature series has similar coverage issues to the HadCRUT4 data, although coverage at low latitudes is better. The mean coverage above 60°N since 1979 is 63% for the NCDC data, compared with 65% for HadCRUT4. Since most of the bias comes from higher latitudes, recent trends in the NCDC data are expected to be impacted in similar fashion to the HadCRUT4 trends.
The Arctic has experienced a very rapid temperature change over recent years, through a combination of polar amplification of greenhouse warming, albedo change due to both black carbon and snow/ice loss and possibly a contribution from multidecadal variability (Semenov et al. 2010; AMAP 2011). The pace of this change means that Arctic coverage has dominated bias in the global temperature estimates, despite the unobserved region being rather smaller than in the Antarctic. On this basis, the problem of coverage bias may exist whenever the Arctic has experienced rapid warming (or cooling) in the past. However, given the magnitude of recent Arctic warming and polar amplification relative to global trends, it is expected that those previous periods of warming (or cooling) in the Arctic are unlikely to bias the record to a greater extent than the bias recorded in recent decades by this study.
The Arctic is likewise the primary source of uncertainty in this work. Further work is needed to address the differing behaviour of the land and ocean domains. The need for a continuous climatology for cells that transform from ice to open ocean presents a significant impediment; however, it may be possible to place bounds on results by assuming constant high and low ice coverage. The Antarctic is the only region in which the kriging and hybrid temperature estimates are noticeably different. Further investigation into the origins of the difference is required.
It is hoped that the preliminary global temperature reconstructions presented here, by highlighting the potential scale of the bias in the short-term temperature trends, will provide an impetus for other groups to look at the problem using more sophisticated tools, including climate and reanalysis models.
Data and methods for this article are available at http://www-users.york.ac.uk/~kdc3/papers/coverage2013.
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Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends - Cowtan - 2014 - Quarterly Journal of the Royal Meteorological Society - Wiley Online Library
We are never going to get anywhere with this debate when we can't agree on the basic facts.
I find it funny that some of you guys think that things like sun spots, El Nino or the Milankovitch Cycles are things that real climate scientists haven't considered yet. I also find it extremely suspicious that most of the leading 'skeptic' scientists always seem to have strong ties to right wing american politics. From what I've read your often cited Dr Roy Spencer is also a creationist?
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Originally Posted by bofa
Ever notice how most models supporting climate change, yes even NASA's, show a period of 60 years or so? No reasonable scientist would accept as fact an assessment using a 0.0000013% sample size.
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^Well I certainly notice it in the information coming from the skeptics.
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The interactive web site, Woodfortrees.org, is an excellent tool for testing out claims about global temperature trends. As described on the home page, “This site hosts some C++ software tools for analysis and graphing of time series data, and an interactive graph generator where you can play with different ways of analyzing data.”
And when you play with the data on the site, it becomes evident that it is quite easy to show, as Paul Clark, Woodfortrees’ creator puts it, that the global average temperature is falling, or static, or rising, or “rising really fast!” All you have to do is pick your cherries — meaning your starting and ending dates — appropriately.
Here’s a chart he created that demonstrates this quite clearly. The y-axis is a measure of how temperatures (measured in C) have departed from the long-term average.
The chart uses satellite data on the temperature of the lower portion of the atmosphere compiled by researchers at the University of Alabama, Hunstville. Of the four global temperature series that are typically used to keep track of how the climate is changing, this one tends to return the lowest temperature anomalies. That makes it a favorite of climate change skeptics. And what does it show?
From 1978 (when this satellite record began) to the present, warming is unequivocally evident (the green trend line). But if you choose other starting and ending points, you can make a case for different trends. In other words, if you do some cherry picking, you can pretty much show whatever you want.
And that’s precisely what those skeptical headlines represent: cherry picking.
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Last edited by -JD-; 03-06-2014 at 09:23 PM.
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