Doctored Data, Not U.S. Temperatures, Set a Record This Year

Published June 13, 2012

“Americans just lived through the hottest 12 months ever recorded, the National Oceanic and Atmospheric Administration reported Tuesday,” according to the May 15 Los Angeles Times.

Which begs the question, what does “recorded” mean?

To most people, the hottest temperatures ever “recorded” would imply that quality controlled thermometers registered higher readings during the past year than had ever occurred before. If you believe that this is what the National Oceanic and Atmospheric Administration (NOAA) means by hottest temperatures ever “recorded,” then you are wrong.

Raw temperature data show that U.S. temperatures were significantly warmer during the 1930s than they are today. In fact, raw temperature data show an 80-year cooling trend. NOAA is only able to claim that we are experiencing the hottest temperatures on record by doctoring the raw temperature data.

Doctoring real-world temperature data is as much a part of the alarmist playbook as is calling skeptical scientists at Harvard, Princeton,Columbia, MIT, NASA, NOAA, etc., “anti-science.” Faced with the embarrassing fact that real-world temperature readings don’t show any U.S. warming during the past 80 years, the alarmists who oversee the collection and reporting of the data simply erase the actual readings and substitute their own desired readings in their place. If this shocks you, you are not alone.

The bureaucracy at NOAA and NASA who report the U.S. temperature data undertake what they term “correcting” the raw data. These corrections are not just one-time affairs, either. As time goes by, older temperature readings are systematically and repeatedly made cooler, and then cooler still, and then cooler still, while more recent temperature readings are made warmer, and then warmer still, and then warmer still.

Science blogger Steven Goddard at Real Science has posted temperature comparison charts (available here, and here) showing just how dramatically the NOAA and NASA bureaucrats have doctored the U.S. temperature data during the past several decades. As the before-and-after temperature charts show, government bureaucrats with power and funding at stake have turned a striking long-term temperature decline (as revealed by the real-world data), into a striking long-term temperature increase.

It is, of course, possible that certain factors can influence the real-world temperature readings such that a correction in real-world temperature data may be justified. The most important such influence is the growth of towns and cities around temperature stations. Forty years ago, for example, Chicago‘s O’Hare airport was located in a largely rural area with surrounding agriculture and relatively sparse population. Forty years later, the city has expanded and consumed the entirety of the O’Hare region.

This begs the question, what is the localized temperature impact of our growing cities? As cities sprout up and grow, the expanding human population with its industrial machinery and urban land patterns create what is known as the urban heat island effect. Temperature readings in large cities, and even in modest-sized towns, are consistently and significantly warmer than the surrounding region. So as towns or cities grow in the vicinity of temperature stations, the more recent temperature readings show a warming trend that is entirely local and directly tied to local land-use decisions. It makes sense, therefore, to adjust more recent temperature readings downward to compensate for the artificial heat signal provided by the localized urban heat island effect.

Ironically, the government overseers of raw temperature data are doing just the opposite. As Goddard shows here, they are doctoring older temperature readings (when urban heat island effects were minimal) in a manner that makes the older temperature readings seem colder than was reported in the real-world data. At the same time, they are doctoring more recent temperature readings (when urban heat islands are more pronounced) in a manner that makes the more recent temperature readings seem warmer than the real-world data report.