While there are many online climate data resources, the source data files are in numerous data formats, presenting a challenge to climate citizen scientists who want to retrieve and analyze several climate indicators at the same time.
I have been working to develop a consolidated open access data file and RClimate scripts that users can use to retrieve climate data, conduct their own analysis and generate their own climate charts. My goal is to make it easier for climate citizen scientists to get their hands on the data in a simple, usable format (CSV). This post updates the status of my RClimate efforts.
The 5 global land-ocean temperature anomaly (LOTA) series use different baseline periods, making direct comparisons between the series more difficult than it would be if each series had the same baseline period.
This post shows how to convert the 5 major LOTA series to a common baseline. Links to on-line source data file and RClimate script are provided. Here is long term LOTA trends using a 133 month moving average and 1979-2008 baseline.
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This post presents an RClimate script to develop a temperature sounding profile and calculate the ambient lapse rate using University of Wyoming atmospheric sounding data. Understanding atmospheric structure and lapse rate is essential to a full understanding of the role of greenhouse gases in global warming.
In this post I present a trend chart which shows the September anomaly trends for the 5 major global temperature anomaly series and a table that shows how September 2010 ranks over the entire record for each series. The source data and RClimate script file links are provided.
Update 1: In a comment, ChristianP suggested the addition of a loess regression fit to the trend line chart. Thanks ChristianP.
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Do-it-yourself citizen scientists need to conduct proper data analysis to reach valid conclusions.
In this post I show how the blogger Inconvenient Skeptic misleads himself on the role of the Atlantic Multi-decadal Oscillation in global warming because he misinterprets his own trend charts and implies causation from correlation.