Tuesday, March 8, 2016

Steele saga - Repost 2/5 - Regarding the question of USHCN homogenization

This is a reposting of the second of five responses I made regarding various aspects of Jim Steele's 1/7/15 WattsUpWithThat 'essay' - in light of Steele's recent comment, I think it's only fair to bring it up again.

Here I share information about the temperature record, global, California and Yosemite, and finish with some links for more detailed information explaining the complexities and reasons for temperature adjustments and "homogenization."


Monday, January 26, 2015

Regarding the question of USHCN homogenization

Regarding Mr. Steele's January 7th, 2015 WUWT blog post, while I won't respond to the personal stuff beyond answering any question in the comments section - Mr. Steele's January 7th, 2015 WUWT blog post does make some interesting points regarding US Historical Climatology Network (USHCN) and data homogenization.  Now that stuff get's up into pure expert level and is quite frankly beyond the abilities of non-experts such as Mr. Steele and myself to realistically judge.  But, he does open up yet another avenue of investigation and I will be making inquires at the USHCN to see what they can teach me about their records and temperature data processing.

In relation to my dialogue with Mr. Steele, the irony is that he relies on his interpretation of USHCN data to make his point that California is not experiencing any warming, yet he broadcasts contempt for USHCN homogenization methods and their models.  What's up with that?  I also have to wonder why he didn't respond to my emails requesting more details and share this information with me.  In any event, I'll share the information I'm able to gather over the next days and weeks.

In the meantime, perhaps it would be good to bring all this back down to Earth and actual observations.

Mr. Steele's repeatedly claims it's the local that matters.  But in truth any appreciation of the "local" is impossible without understanding how it fits into the global pattern.  I hope the following video drives that message home (followed by 2014 NOAA, NASA videos and look at California temperatures):

NASA | A Year in the Life of Earth's CO2

Published on Nov 17, 2014 
An ultra-high-resolution NASA computer model has given scientists a stunning new look at how carbon dioxide in the atmosphere travels around the globe.
Plumes of carbon dioxide in the simulation swirl and shift as winds disperse the greenhouse gas away from its sources. The simulation also illustrates differences in carbon dioxide levels in the northern and southern hemispheres and distinct swings in global carbon dioxide concentrations as the growth cycle of plants and trees changes with the seasons. 
The carbon dioxide visualization was produced by a computer model called GEOS-5, created by scientists at NASA Goddard Space Flight Center’s Global Modeling and Assimilation Office. 
The visualization is a product of a simulation called a “Nature Run.” The Nature Run ingests real data on atmospheric conditions and the emission of greenhouse gases and both natural and man-made particulates. The model is then left to run on its own and simulate the natural behavior of the Earth’s atmosphere. This Nature Run simulates January 2006 through December 2006. 
While Goddard scientists worked with a “beta” version of the Nature Run internally for several years, they released this updated, improved version to the scientific community for the first time in the fall of 2014.
This video is public domain and can be downloaded at: http://svs.gsfc.nasa.gov/goto?11719
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Also there's the inconvenient fact for climate science bashers that it's the experts and the collective climatological consensus that keeps getting it right.

NASA | 2014 Warmest Year On Record

NASA | 2014 Warmest Year On Record

Published on Jan 16, 2015
The year 2014 now ranks as the warmest on record since 1880, according to an analysis by NASA scientists.

Nine of the 10 warmest years since modern records began have now occurred since 2000, according to a global temperature analysis by scientists at NASA’s Goddard Institute for Space Studies in New York.

2014’s record-breaking warmth continues a long-term trend of a warming climate. The global average temperature has increased about 1.4 degrees Fahrenheit (0.8 degrees Celsius) since 1880, with most of that warming occurring during the last three to four decades.

The warming trend is largely driven by the increasing concentrations of carbon dioxide and other heat-trapping greenhouse gases in the atmosphere, caused by human emissions.

This video is public domain and can be downloaded at: 

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NASA | Six Decades of a Warming Earth

Published on Jan 21, 2014

This visualization shows how global temperatures have risen from 1950 through the end of 2013.

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Global Analysis - Annual 2014

NOAA's National Climatic Data Center (NCDC)

Global Highlights
  • The year 2014 was the warmest year across global land and ocean surfaces since records began in 1880. The annually-averaged temperature was 0.69°C (1.24°F) above the 20th century average of 13.9°C (57.0°F), easily breaking the previous records of 2005 and 2010 by 0.04°C (0.07°F). This also marks the 38th consecutive year (since 1977) that the yearly global temperature was above average. Including 2014, 9 of the 10 warmest years in the 135-year period of record have occurred in the 21st century. 1998 currently ranks as the fourth warmest year on record.
  • The 2014 global average ocean temperature was also record high, at 0.57°C (1.03°F) above the 20th century average of 16.1°C (60.9°F), breaking the previous records of 1998 and 2003 by 0.05°C (0.09°F). Notably, ENSO-neutral conditions were present during all of 2014.
  • The 2014 global average land surface temperature was 1.00°C (1.80°F) above the 20th century average of 8.5°C (47.3°F), the fourth highest annual value on record.
  • Precipitation measured at land-based stations around the globe was near average on balance for 2014, at 0.52 mm below the long-term average. However, as is typical, precipitation varied greatly from region to region. This is the third consecutive year with near-average global precipitation at land-based stations.
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Research News
NASA, NOAA Find 2014 Warmest Year in Modern Record
Posted Jan. 16, 2015

The year 2014 ranks as Earth’s warmest since 1880, according to two separate analyses by NASA and National Oceanic and Atmospheric Administration (NOAA) scientists. …

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Oh and regarding Jim's claim that California hasn't 'really' been experiencing any warming - H/T to Mr. Steele for including this study in some footnotes. Why he ignores it is yet another question.

My conjecture is that creating confusion is exactly what his goal is.

From http://whatsupwiththatwatts.blogspot.com/2014/12/yosemite-np-mystery-temp-graph.html

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Jim Steele claimed: "even though most maximum temperatures in California had not risen significantly.[3]"

But, here's the tally:
California Tmax trend average broken into 11 regionals. 


Doesn't add up to Mr. Steele's claim, now does it?
And that's from 1918 to 2006
the scary part is 1970 to 2006 . . . and beyond.  
Check out the study:
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The identification of distinct patterns in California temperature trends
Eugene C. Cordero · Wittaya Kessomkiat · John Abatzoglou · Steven A. Mauget
Received: 28 August 2009 / Accepted: 4 November 2010 © Springer Science+Business Media B.V. 2011 

4.2 Comparison of annual trends: 1918–2006 with 1970–2006
It is understood that forcings (i.e., natural and anthropogenic) may interact in a nonlinear fashion, thus affecting temperatures across different time and spatial scales. To evaluate this, we compared annual trends across different regions for two different time periods, 1918–2006 and 1970–2006. 
The most prominent feature in this comparison (Fig. 5) was accelerated warming trends from 1970–2006. Statewide Tmax trends between 1970–2006 (+0.27C dec−1) were more than three times as large as the trend between 1918–2006 (+0.07C dec−1), while Tmin trends between 1970–2006 (+0.31C dec−1) were almost twice as large as trends between 1918– 2006 (+0.17C dec−1). (my highlights)
The finding that trends for Tmin were larger than Tmax for the entire period, while trends in Tmin were nearly the same as Tmax since 1970 is qualitatively similar to results observed for global temperature (Vose et al. 2005).
Although statewide trends in temperature for Tmin and Tmax were about the same since 1970, there were distinct regional differences. "

Department of Meteorology and Climate Science
San Jose State University, College of Science

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Victor Venema at Variable Variability 
put together a good reading list of articles that look into temperature adjustment: 
Climatologists have manipulated data to REDUCE global warming 
Variable Variability
Phil Plait at Bad Astronomy comment on the Telegraph piece: No, Adjusting Temperature Measurements Is Not a Scandal 
John Timmer at Ars Technica is also fed up with being served the same story about some upward adjusted stations every year: Temperature data is not “the biggest scientific scandal ever” Do we have to go through this every year? 
The astronomer behind And Then There's Physics writes why the removal of non-climatic effects makes sense. In the comments he talks about adjustments made to astronomical data. Probably every numerical observational discipline of science performs data processing to improve the accuracy of their analysis. 
Steven Mosher, a climate "sceptic" who has studied the temperature record in detail and is no longer sceptical about that reminds of all the adjustments demanded by the "sceptics". 
Nick Stokes, an Australian scientist, has a beautiful post that explains the small adjustments to the land surface temperature in more detail. 
My two most recent posts were about some reasons for temperature trend biases: Temperature bias from the village heat island and Changes in screen design leading to temperature trend biases 
You may also be interested in the posts on how homogenization methods work (Statistical homogenisation for dummies) and how they are validated (New article: Benchmarking homogenisation algorithms for monthly data)
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