This post is part of Blog Action Day. Since I write about climate charts and graphs regularly, I struggled to find a topic that would fit Blog Action Day beyond what I usually write.
I am currently reading David Archer’s Global Warming – Understanding the Forecast and realized that telling my readers about this excellent book, accompanying lecture videos and on-line models would make a great post.
This book is a must read for anyone who wants to understand the science behind global warming, how sunlight warms the earth, how the earth emits infrared radiation (earth light), how greenhouse gases affect the earth’s climate, and how climate models work. David Archer, a professor in the Geophysical Sciences Department at the University of Chicago, wrote this book for his class on global warming for non-science majors.
The book is accompanied with video lectures from his Fall, 2009 class and access to 8 on-line state of the art interactive models used by climate scientists.
David Archer’s book is the best climate science book that I have found.
This post continues my analysis of solar trends, this time comparing reconstructed total solar irradiance (TSI) and temperature anomaly (GISS) trends for the 1880 – 2009 period. I use 11 year moving averages to smooth both series so that we can see the longer term trends. Links to a download-able copy of my R script is provided for those readers who wish to prepare their own charts.
This is the 2nd in a series of posts I will be doing on solar trends. In this post, I show how to retrieve online daily satellite and reconstructed TSI data, plot the daily data as well as annual and 11 year moving average smooths for the data series. Links to the original data sources and my R script Google document are provided. Updated 10/1/09.
This is the 1st in a series of posts I will be doing on solar trends. In this post, I show how to retrieve online monthly sunspot data back to 1749, calculate average annual sunspot numbers (SSN), plot the monthly and annual average SSN as well as a lowess smooth, add the Solar Cycle number to the plot and generate a csv file that will be used in future posts. Links to the original data source, my annual SSN and cycle date Google spreadsheet files, and my R script Google document file are provided.