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  <title> ProcessTrends</title>
  <link> http://processtrends.com</link>
  <description>Global Warming Trend Analysis with R and Excel</description>

<item>
<title>Consolidated Global Land and Ocean Temperature Anomaly Series Since 1979</title>
<description> 
Trend chart shows monthly temperature anomaly data for 5 major temperature Land - Ocean anomaly
series: GISS, NOAA, Hadley, RSS and UAH. First 3 use station data, the last 2 use satellite based observations.
The CSV data file is updated monthly from source agency data files. All source agency data is downloaded monthly 
so that any changes in source data will be reflected in the consolidated file.
</description>
<link>http://processtrends.com/RClimate.htm#consoldiated_5_series</link>
<pubDate>Wed, 24 Feb 2010 11:30:00 EST</pubDate>
</item>



<item>
<title>RClimate Script: Arctic Sea ice Extent Trends by Month</title>
<description> 
This R script allows users to retrieve monthly Arctic Sea Ice Extent data file and generate a trend chart 
showing monthly traces for each month. Users can source() the script to generate an up-to-date chart without having to 
download either the data file or script.
</description>
<link>http://processtrends.com/RClimate.htm#Arctic_Sea_Ice_Extent_by_Month</link>
<pubDate>Wed, 10 Feb 2010 11:30:00 EST</pubDate>
</item>


<item>
<title>R Climate Script: RSS Temperature Anomaly Trends </title>
<description>
This R script continues my effort to provide a family of R scripts that allow users to access online climate agency 
without having to download and store the source data or copy/paste scripts. Users can simply source() the scripts 
to get a plot of the latest climate data. 

This R script retrieves RSS's monthly temperature anomaly data file, calculates the annual means and generates a plot that 
highlights the latest monthly reading. Users can run this script and reproduce the chart on their PC without having to 
download either the script or data file. Simply source() the R script in an R session on your PC and you'll have the chart 
ready to print on your PC.  
</description>
<link>http://processtrends.com/RClimate.htm#RSS</link>
<pubDate>Fri, 05 Feb 2010 12:50:00 EST</pubDate>
</item>




<item>
<title>R Climate Script: SST Anomaly Trends </title>
<description>
This R script retrieves NOAA's NCDC SST anomaly trend file, calculates the decadal means and generates a plot that 
highlights the latest monthly reading. Users can run this script and reproduce the chart on their PC without having to 
download either the script or data file. Simply source() the R script in an R session on your PC and you'll have the chart 
ready to print on your PC.  
</description>
<link>http://processtrends.com/RClimate.htm#SST_Anomaly</link>
<pubDate>Mon, 01 Feb 2010 10:30:00 EST</pubDate>
</item>

<item>
<title>Process Trends</title>
<description>Enhanced Data Visualization Charts in Excel and R  </description>
<link>http://www.processtrends.com/index.htm</link>
<pubDate>Mon, 01 Feb 2010 10:30:00 EST</pubDate>
</item>

<item>
<title>R Climate Scripts</title>
<description>
I have started a new page to present a series of R scripts that retrieve on-line climate
data from international climate agencies, process data and generate trends charts. The 
R script files are set up so that users can source() the file with 1 command and execute 
the R script from ProcessTrends.com without having to download either the data or R script.  
</description>
<link>http://processtrends.com/RClimate.htm</link>
<pubDate>Wed, 20 Jan 2010 08:30:00 EST</pubDate>
</item>


<item>
<title> CO2 and Temperature Trends</title>
<description> 
In a previous post I discussed problems with an Excel based CO2 and temperature
trend chart that used 2 Y axes. Double axis charts can be misleading because 
they may distort the Y axis for one of the series.

In this post I show another example of am ineffective double Y axis CO2 and 
temperature trend chart and present 2 alternative ways to show the same data 
more effectively. Links to my  R scripts and Google spreadsheet based data file 
are included.
</description>
<link>http://chartsgraphs.wordpress.com/2009/08/31/co2-and-temperature-trends//</link>
<pubDate>Fri, 25 Sep 2009 10:10:00 EDT</pubDate>
</item>





<item>
<title>Decadal Trend Rate in Long Term Trend Chart </title>
<description> 
This post presents an R based chart of global GISS land and sea temperature anomaly 
data for the 1880-2009 period with both the long term trend and the individual decadal
trends. Links to the source data file and the R script are provided so that readers 
can reproduce/ improve on this analysis.
</description>
<link>http://chartsgraphs.wordpress.com/2009/07/02/decadal-trend-rates-in-global-temperature/</link>
<pubDate>Thu, 02 Jul 2009 17:10:00 EDT</pubDate>
</item>




	
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