Re: [asa] NASA - Climate Simulation Computer Becomes More Powerful

From: Rich Blinne <>
Date: Sun Aug 30 2009 - 09:41:37 EDT

On Aug 30, 2009, at 5:30 AM, Dave Wallace wrote:

> I would also hope that the climate community is spending a larger
> amount of their funding on basic climate science and improving data
> accuracy than on modeling and modelers. Glenn's review shows that
> the accuracy of ground stations leaves something to be desired and
> makes one wonder if the whole effort is as shoddy as the ground
> station data.
> Glenn's analysis can be seen at: http://
> If Glenn's data analysis can be shown
> to be wrong I would be most interested. Comments can be added to
> Glenn's blog entries.

Glenn's analysis has been shown wrong many times now and I am so tired
of the personal abuse that I will only debate him here. He can
continue to live in his bubble and will receive no comments from me on
his blog.

If you only include the high quality stations you get the same answer
when you do include them. Furthermore, nearby rural stations are used
to normalize the urban ones. You may recall a big stink in the
denialist community around 2007 because January 9, 2007 was when the
normalization occurred. Global average temperatures changed by less
than one thousandths of a degree after the adjustments.

Note Peterson 2006.

> The results clearly support the theory that homogeneity adjustments
> can account for changes in siting of stations, even changes to poor
> siting conditions, and serve as counter-example to the hypothesis
> that poor current siting causes a warm bias or even any bias in the
> homogeneity adjusted U.S. temperature record.

Note this from NOAA to improve local temperatures. As shown above
global temperatures are not really affected.

> National Temperature Trends: The Science Behind the Calculations
> On January 9, 2007 NOAA provided a press release stating that
> preliminary temperatures for the United States indicated 2006 was
> the warmest year on record. Included in the press release was
> reference to a new method for correcting biases in observations
> (Version 2) that had a preliminary rank for 2006 as the 2nd warmest
> year on record. After receipt of additional observations for 2006,
> temperature statistics were updated on May 1, 2007. The late data
> changed the rank for 2006 to the 3rd warmest year on record for the
> old method (Version 1) and the rank remained as 2nd warmest for the
> new data correction method (Version 2).
> Why such changes occur is rooted both in the way the observations
> are processed for quality and the delay in receipt of data on paper
> records from many stations. The observations come from the U.S.
> Historical Climatology Network (USHCN), a network of 1221 climate
> observing stations in the continental United States. These data are
> extensively quality controlled for errors and for small biases that
> may have occurred through time due to artificial changes at each
> observing station. These artificial changes include station
> relocations, different instrumentation, and changes in the landscape
> surrounding the station (e.g. urbanization, removal or planting of
> vegetation, etc.). Some of these changes may result in "random"
> changes to the data. For example, even small station relocations can
> result in temperature readings that are either slightly cooler or
> slightly warmer than what would have occurred at the former site.
> Other changes, such changes in urbanization in the vicinity of the
> station or changes in observing times, can systematically affect
> temperatures, e.g., add an urban warming bias to the temperature
> trends. Research has shown that the data from these kinds of changes
> can be corrected to a large degree based on physical and statistical
> methods (e.g., see Peterson 2006).
> Methods that have been used to correct temperature data are
> described in more than a dozen peer-reviewed scientific papers by
> NOAA's National Climatic Data Center (NCDC). A series of data
> corrections was developed to specifically address potential problems
> in trend estimation of the rates of warming or cooling in the USHCN.
> They include:
> Station moves and instrumentation changes (Karl and Williams
> 1987, Quayle et al. 1991),
> changes in observing practices, such as observing time changes
> (Karl et al. 1986), and
> urbanization (Karl et al. 1988).
> These data correction schemes have been applied to the USHCN to
> determine temperature trends across the United States up until the
> end of 2006. Beginning in 2007 improved correction schemes for items
> 1 and 3 above have been applied to the USHCN observations (Menne and
> Williams 2005, Menne and Williams 2007). They have been shown to
> improve our ability to monitor climate change and variations.
> Because different algorithms were used in making corrections to the
> station data in 2007 there are small differences in annual average
> temperatures between the older corrections (Version 1) and newer
> Version 2 corrections. These small differences in average
> temperatures result in minor differences in annual rankings for some
> years. The new correction scheme has virtually no impact on the long-
> term temperature trend as annual temperature trends in Version 1
> from 1895-2006 were 0.112F/decade and in Version 2 the trends were
> 0.110F/decade.
> NOAA continues to work to improve the quality and representativeness
> of climate data provided to the public and scientific communities.
> In addition to advanced quality control procedures, these efforts
> include modernization of the USHCN by installing new, more accurate
> instrumentation, and ensuring proper station siting in the process.
> In addition, by the end of next year NOAA should have in place a
> U.S. Climate Reference Network, a set of 114 very high quality
> stations optimized for monitoring climate. The operation of the US
> Climate Reference Network will virtually eliminate the need for the
> types of corrections that have to be applied to data available
> today. The modernization of the US Historical Climatology Network
> will enable trends of regional temperature to be estimated with far
> fewer data corrections.
> References
> Karl, T.R., H.F. Diaz, and G. Kukla, 1988: Urbanization: its
> detection and effect in the United States climate record, J.
> Climate, 1, 1099-1123.
> Karl, T.R., C.N. Williams, Jr., P.J. Young, and W.M. Wendland,
> 1986: A model to estimate the time of observation bias associated
> with monthly mean maximum, minimum, and mean temperature for the
> United States, J. Climate Appl. Meteor., 25, 145-160.
> Karl, T.R., and C.N. Williams Jr., 1987: An approach to adjusting
> climatological time series for discontinuous inhomogeneities. J.
> Climate Appl. Meteor., 26, 1744-1763.
> Menne, M.J., and C.N. Williams, Jr., 2005: Detection of
> undocumented changepoints using multiple test statistics and
> composite reference series. J. Climate, 18, 4271-4286.
> Menne, M.J., and C.N. Williams, Jr., 2007: Homogenization of
> temperature series via pairwise comparisons. J. Climate, in review
> Peterson, T.C., 2006: Examination of potential biases in air
> temperature caused by poor station locations, Bull. Amer. Meteor.
> Soc., 87, 1073-1080, DOI:10.1175/BAMS-87-8-1073
> Quayle, R.G., D.R. Easterling, T.R. Karl, and P.Y. Hughes, 1991:
> Effects of recent thermometer changes in the cooperative station
> network, Bull. Amer. Meteor. Soc.,72, 1718-1724.

Note this from the EPA on Urban Heat Island effect:

> Heat islands may skew long-term temperature records as urbanization
> encroaches on weather stations located near the outskirts of town.
> Consequently, researchers must remove heat island effects from
> temperature records to accurately estimate climate change.
> The data may be corrected in a variety of ways. In some cases,
> researchers statistically adjust urban weather station data to match
> trends seen in nearby rural stations; in other analyses urban data
> are simply excluded from the record.
> The Intergovernmental Panel on Climate Change (IPCC) has concluded
> that the impact of urban heat islands on temperature records is
> "real but local," [Note: this is what the data on Glenn's blog
> shows. He shows how some local stations show real differences
> between them. What he failed to show is how this causes any
> difference when looking at global climate. Since the current focus
> is now on the accuracy of the local climate the climate network is
> being modernized. See the following on the U.S. Climate reference
> network:] and has only a negligible
> effect on regional or global trends.2 The IPCC also noted that urban
> heat island effects on local climate appear to include changes in
> precipitation, clouds, and daily temperature range.
> Some of the methods used to remove urban biases from the temperature
> record are discussed in the National Climatic Data Center's
> background article on National Temperature Trends: The Science
> Behind the Calculations.

Rich Blinne
Member ASA

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Received on Sun Aug 30 09:42:47 2009

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