Measurement. Climate4you. Analysis of Temperature Change using World Class Stations. Guest essay by Ron Clutz This is a study to see what the world’s best stations (a subset of all stations I selected as “world class” by criteria) are telling us about climate change over the long term.
There are three principle findings. To be included, a station needed at least 200 years of continuous records up to the present. Geographical location was not a criterion for selection, only the quality and length of the histories. 247 years is the average length of service in this dataset extracted from CRUTEM4. The 25 stations that qualified are located in Russia, Norway, Denmark, Sweden, Netherlands, Germany, Austria, Italy, England, Poland, Hungary, Lithuania, Switzerland, France and Czech Republic. A look at temperature anomalies for all 4 global metrics: Part 1. NOTE: Please note that part 2 is now online, please see it here.
I recently plotted all four global temperature metrics (GISS, HadCRUT, UAH, RSS) to illustrate the magnitude of the global temperature drop we’ve seen in the last 12 months. At the end of that post, I mentioned that I’d like to get all 4 metrics plotted side-by-side for comparison, rather than individually. Of course I have more ideas than time these days to collate such things, but sympathetic reader Earle Williams voluntarily came to my rescue by collating them and providing a nice data set for me in an Excel spreadsheet last night.
The biggest problem of course is what to do with 4 different data sets that have different time spans. The simplest answer, at least for a side by side comparison is to set their time scales to be the same. Here is the first graph, the raw anomaly data as it was published this month by all the above listed sources: March 2005 to January 2008, magnified view – click for larger image. Comparing the Four Global Temperature Data Sets. Reposted from Jennifer Marohasy’s website.
THERE are four official global temperature data sets and there has been much debate and discussion as to which best represents change in global temperature. Tom Quirk has analysed variations within and between these data sets and concludes there is 1. Substantial general agreement between the data sets, 2. Substantial short-term variation in global temperature in all data sets and 3. No data set shows a significant measurable rise in global temperature over the twelve year period since 1997. Global Temperature Revisited Article by Tom Quirk One of the most vexing things about climate change is the endless debate about temperatures. Temperature Misunderstandings. Clive Best provides this animation of recent monthly temperature anomalies which demonstrates how most variability in anomalies occur over northern continents.
Beyond the issues with the measurements and the questionable adjustments, there is a more fundamental misconception about air temperatures in relation to “climate change.” Clive Best does a fine job explaining why Global Mean Temperature anomalies do not mean what people think. Below is my synopsis of his recent essay entitled Do Global Temperatures make sense? (link) Background: Earth’s Heat Imbalance. What We Know About CO2, Global Atmospheric Temperatures. Despite large uncertainties and many unknowns in Earth Science, scientists have a reasonable understanding of the answers to these questions.
Atmospheric CO2 is a “greenhouse gas,” and therefore, an increase of its concentration in the atmosphere will tend to warm the air. But the latest scientific research by William Happer of Princeton University has shown that the belief that a doubling of atmospheric CO2 will cause directly a 1°C warming of the globe may be incorrect. Indeed, the more likely answer is that a doubling of CO2 will cause only a 0.6°C warming, or about 40% less than previously thought. This makes it even more important to take with caution the excessive impact of CO2 on global air temperatures. Complicating our understanding is that many processes involving the atmosphere, the ocean, and the land surface which affect the warming effect of CO2 are highly complex and largely incompletely understood. A recent paper published in Earth Science Reviews (by W. An interesting and unique graph that ties ENSO, global temperature and other climate variables together. Yesterday, WUWT covered the sharp drop in global temperatures that followed the peak of the 2015/16 El Niño.
That caught the interest of John B from Toronto, and he writes in with a graph he has rendered that illustrates correlation of many climate metrics. While it is true that “correlation is not causation” it can also be said that correlation is well worth investigating further. He writes: Thought you might be interested in this plot I made. I’m not a climate scientist, but I have more than 15 years experience in signal analysis.Coding is done by me using .NET with GDI graphics.PS. Click for a much larger image at 1920×1080 pixels. Note that the intensity of the red and green colors used to depict ENSO events (El Niño in red and La Niña in green) varies with the strength of the event. Wood for Trees: Interactive Graphs.
The Reference Frame: GISS: 1998-2016 comparison suggests a trend of 2 °C per century. Thursday update: British HadCRUT4 have completed their 2016 data, too.
The last column contains the annual averages. The difference from GISS is significant. 2016 was only 0.013 °C (GISS: 0.13 °C!) Warmer than 2015. Using R and JAMSTEC NetCDF Files to Examine Ocean Temperatures. By Andy May It doesn’t matter if you think fossil fuel CO2 emissions are going to end the world or lead us to a greener and more beautiful one.
Either way, to be a true climate change geek you need access to climate data! On Cowtan and Way (2013) “Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends”