Tag Archives: Climate Agencies

Tracking Climate Trends with RClimate Scripts and Links

Some of my visitors may have noticed that I have added a new Climate Images page and have been adding climate data images to my right side panel. So far, I have 6 trend charts, 4 map images, 1 photo image and 1  data value  showing the CO2 concentrations, recent total solar irradiance (TSI) , temperature anomalies and  Arctic sea ice extent trends and map images of global and SST anomalies and  Arctic sea ice extent.

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RClimate Script: Arctic Sea Ice Extent Trend By Month

This RClimate Script lets users retrieve and plot the latest data on Arctic Sea Ice Extent  trends by month from 1979 to latest completed month. The trend chart shows National Snow and Ice Data Center’s (NSIDC)  monthly Arctic Sea Ice extent data.

Arctic Sea Ice Trend by Month

I’ve discussed the Arctic sea ice extent trends in this earlier post.

Here’s NSIDC’s Arctic  sea ice extent trend by month chart  since 1979.

This chart shows the 12 monthly sea ice extent trends, with the latest completed month highlighted in red.

Here are the data and RClimate Script links:

RClimate Script: Sea Surface Temperature (SST) Anomaly Trends

This RClimate Script lets users retrieve and plot the National Climatic Data Center’s monthly Sea Surface Temperature (SST) Anomaly dat series .  Links to the NCDC data file and my RClimate script are included. Users can run my script with a simple R source() statement.

NCDC  SST Anomaly

I’ve discussed the Hadley SST anomaly trends in this earlier post.

Here’s NCDC’s global SST anomaly data series trend since 1880.

This chart shows the decadal means and highlights the latest monthly SST anomaly.

Here are the data and RClimate Script links:

RClimate Script: Polar Amplification – 2000 to 2009

This RClimate Script lets users retrieve and plot the NASA GISS temperature anomaly data for 2000 to 2009 by latitude zone during the past decade. A link is provided to the NASA GISS data generation query page as well as links to my saved file of the GISS data and my RClimate script that users can run with a simple R source() statement.

Introduction

I’ve discussed polar amplification in this previous post.

NASA has reported that 2009 was the 2nd warmest year on record and that 2000 to 2009 was the warmest decade on record, based on global mean anomaly values. The increased anomalies over the decade were not uniform, as shown in this NASA image of 2000 – 2009 anomalies  compared to the 1951-1980 baseline period. (Click image to enlarge it)


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RClimate Script: CO2 Trends

This RClimate Script lets users retrieve the latest data file on monthly Mauna Loa  CO2 levels and generate a trend chart with the latest reading highlighted.

CO2 TrendsKeeling Curve

Here’s the Mauna Loa Observatory CO2 trend from 1958 to Dec., 2009.

Here are the data and RClimate Script links:

RClimate Script Introduction

Would you like to be able to generate a GISS temperature anomaly trend chart on your PC with just 1 line of R script? What about downloading the R script to your PC so that you can edit the script to fit your needs?

In this post I present my first RClimate Script so that users with just a little R experience who have R and 2 R libraries up and running on their PC  can  retrieve the latest NASA file on monthly GISS temperature anomalies, generate a trend chart and calculate the anomaly trend rate in 1-2 minutes.

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Understanding the Science of CO2’s Role in Climate Change: 3 – How Green House Gases Trap Heat

This post, the 3rd (1st here, 2nd  here) in the series on Understanding the Science of CO2’s Role in Climate Change, discusses how water vapor, CO2, CH4, O3 and N2O  absorb and emit the Earth’s longwave radiation, changing the Earth’s energy balance.

I’ve made a 5 panel chart that shows spectra data for 5  greenhouse gases (GHG). Molecules of these gases in the atmosphere absorb and emit the Earth’s infrared radiation at specific frequencies, trapping some of the Earth’s  radiation, warming the planet.

I’ve included a link to my R script so that readers can access the online spectra data and generate your own GHG spectra.

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Understanding the Science of CO2’s Role in Climate Change: 1 – Introduction

Moving Beyond Trend Charts

I have made many trend charts and regressions over the past 4 years as I try to learn as much as I can about climate change and CO2’s role in global warming. Here are links to some of my previous Climate Charts & Graphs work:

While these trend charts and regressions help to show the relationships between climate factors, I keep asking myself the fundamental question “how does atmospheric CO2 actually affect the earth’s temperature”. To answer this, I need to delve more deeply into the physics of CO2 in the atmosphere to really understand the CO2 – climate change relationship. As I read climate science papers and visit climate change websites, I get a sense for the physics of CO2 and climate change, but not a real solid understanding.

David Archer’s “Global Warming, Understanding the Forecast book and accompanying videos of his Chicago University lectures and Dennis Hartmann’s “Global Physical Climatology have helped my understand the role that solar radiation, hartmann_book_coverelectromagnetic spectrum, blackbody radiation,  Stefan-Boltzmann Equation, Planck’s Law,  atmospheric absorption bands and greenhouse gases play in the global energy balance and climate change.

To really understand CO2’s role, I need to work with the numbers and formulas myself so that I can see the cause and effect relationships. I have developed a series of Excel tools to help me understand the physics behind global warming and to be able to reproduce several of the critical charts necessary to understanding climate change.

This series of posts will outline and graphically display the key topics and present the Excel tools that I found helpful to me to understand basic climate change science.  Where possible, I present downloadable Excel workbooks to let readers work with the fundamental equations and check out the basic mathematical relationships for themselves.

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Worth Reading: Global Warming – Understanding the Forecast

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.

Global_warm_book_cover

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.

Solar Trends: Total Solar Irradiance Since 1611 – Update

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.

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