Written by Joseph DÂ’Aleo
July 28, 2008
By Joseph D'Aleo, CCM' AMS Fellow
Exerpt from full report
The University of Alabama, Huntsville MSU satellite based global assessment reported on the other hand this June was the 9th coldest in the 30 years of record keeping. In fact, their global mean was actually below the average (base period 1979-1998) with a value of -0.11C (-0.19F). The other NASA satellite source, RSS had June as the 13th coldest out of the last 30 years.
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Recall the CO2 was negatively correlated for almost 4 decades from the 1940s through the 1970s. It was positively correlated from 1900 to 1930s and again 1979 to 1998. This on-again, off-again relationship suggests CO2 is not driving the climate bus but maybe a passenger in the back.
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The Data Base Issues
But why the discrepancy of satellite and surface based data bases? A statement is frequently made that the current warming is unprecedented and that using the global data bases something like “the 12 warmest years have occurred in the last 13 years.” This is nonsense.
Though there has clearly been some cyclical warming in recent decades, the global surface station based data is seriously compromised by urbanization and other local factors (land-use /land-cover, improper siting, station dropout, instrument changes unaccounted for and missing data) and thus the data bases overestimate the warming. Numerous peer-reviewed papers (referenced at end) in the last several years have shown this overestimation may be the order of 30 to 50%. I believe the recent warming is comparable or less than the warming in the 1930s and is now over.
Station drop-out has occurred-- from a peak of 6,000 stations in 1970 to 2,000 today. The biggest dropoff occurred around 1990. Many of the stations that were dropped were rural. A larger percentage of the stations remaining were urban.
Dr. Thomas Oke (the winner of the American Meteorological Society Helmut Landsberg award in 2007 for his pioneer work in urbanization), in 1973 showed how even cities with 1000 population could have a significant warming relative to urban areas (2 degrees Celsius). The global data bases do not consider an area a city and adjust for urbanization until the population exceeded 100,000. This introduces a warm bias into the data bases.
Zhou et al (2005) have shown global data bases (for China) not properly adjusted for urbanization. Block (2004) showed the same problem exists in central Europe. Hinkel et al (2003) showed even the village of Barrow, Alaska with a population of 4600 has shown a warming of 3.4F in winter over surrounding rural areas.
More and more of the world is urbanized (population increased from 1.5 B to 6.5 B today). Cities grow around airports where we measure temperatures. See this detailed review of this Urban Heat Island (UHI) issue. NOAA, Hadley and NASA have argued urban contamination is not an issue mainly using the flawed discredited papers by Jones, Parker and Peterson. NASA’s adjustments have been shown by Steve McIntyre to be erratic with the majority actually warming urban areas instead of adjusting temperatures down.
Another issue that has been an issue over the entire history of observations is the erratic nature of station histories and the missing data that must be somehow accounted for.
Try this to see for yourself how bad the global station data is. Go to this site (GISS - virtually the same as NOAA’s GHCN though the adjustments made differ), scroll down to the map and click on any region. You will see stations listed - notice the highly variable reporting periods. Start clicking on stations. You will get plots. But before you move to other stations go to the bottom and click on “Download monthly data as text”. You will see for many/most stations numerous “999.9"s meaning missing data. How do you come up with annual averages when one to multiple months are missing? I was told that in most cases the data is available (Environment Canada tells us they have their data we show as missing) but that NOAA and NASA is making no efforts to go out and get it.
Instrumentation Changes Unadjusted For
Stephen McIntyre has shown in The HO-83 Hygro-thermometer that the change to the HO-83 went unadjusted for even though Karl 1995 noted a discontinuity of about 0.5CF before and after switchover.
Pielke and Davey (2005) found a majority of stations including climate stations in eastern Colorado did not meet WMO requirements for proper siting. He has extensively documented poor siting and land use change issues in numerous peer review papers, many summarized in the landmark paper Unresolved issues with the assessment of multi-decadal global land surface temperature trends (2007).
Anthony Watts started a volunteer effort to document siting issues with all 1221 stations in US. He and his team is now through over 554 stations. He and his team is now through over 554 stations. See the results on http://surfacestations.org and numerous examples highlighted on http://wattsupwiththat.wordpress.com. Most of these siting issues identified introduce a warm bias.
Using the government’s own rating system, Anthony has shown a majority of the stations are inadequately sited (87% are CRN 3-5).
Even with the issues, the US network because it does not suffer from the same extent of station dropout and missing data shows minimal warming since the last cyclical peak in 1930.
If the estimates if the warming are exaggerated by a 30-50%, the warming is waithin the margin of error for the instrumentation.
In fact the trend for only the stations rated CRN 1 show a lower second peak.
This is supported by the plot of All-time Record State Temperatures in which 37 of the 50 states set their new records in the decades prior to 1960.
Also the record daily highs in June and July in Des Moines
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