Arctic Sea Ice Extent (SIE) follows an annual cycle, with maximum levels usually in March and minimum values in September. Many analysts use day-of-year charts to compare the SIE cycle by years so that they can assess the current years trend with previous years. In this post, I present an alternative to the day-of-year chart which shows the daily values a calendar month previous years and the current year.
Arctic Sea Ice Extent (SIE)
I have discussed Arctic Sea Ice Extent (SIE) here and here. Both of those posts used the NSDIC monthly Arctic SIE data. In this post, I use the Japan Aerospace Exploration Agency (JAXA) daily data series, available at this link.
Here’s the JAXA day-of-year chart . Click image to enlarge.
In this post I present combined long term and recent trend charts of UAH Channel 5 temperature anomalies using R’s figure inside figure capability. This approach provides a better picture of global temperature trends than UAH’s day-of-year plots.
The University of Alabama Huntsville (UAH) provides a daily update to their Channel 5 global average temperature at 14,000 feet. I have previously posted about this data set here. The source data file link is here.
Reader GH sent me an e-mail asking about a previous Arctic sea ice extent trend post (click). GH asked ….
“Why is there such a difference between this type of representation and the chart at link ? What you’ve written above seems to imply that the definitions of extent are the same. Just looking at 2002 – present, I’m not clear why the JAXA chart doesn’t appear to demonstrate the same clear trend. ..”
Non Issue Is Over
It’s been an interesting 24 hours in the chart blog world. I am happy to announce that the Chart Doctor name issue is completely resolved on my part and I apologize for generating what turned out to be an unnecessary controversy because Akismet flagged my comment to Chandoo’s post as spam. Continue reading
Chart Doctor Started 9/30/06
I started my Chart Doctor feature at ProcessTrends.Com way back on 9/30/06: Continue reading
In this post I show 4 charts of the same data to demonstrate what Excel chart users are missing by not having a more powerful charting tool. This post, building on my previous discussion of using factors for conditional formatting, shows the potential advantages of plotting summary values and bounding area polygons . These analytical displays are not readily available to even advanced Excel users. Continue reading
In reading a recent Excel charting post, I got that Yogi Berra feeling, “..this is deja vu all over again”. I could have sworn that I had made or seen a similar chart several years ago. This post looks into the deja vu mystery and reports on my findings. You’ll have to read this post to see if Yogi’s quote applies to Excel charts.
Is there a single “best” way to display temperature anomaly data? The answer is obvious – NO! The best display depends on what we are trying to show. Statistical charts compare one variable with one or more other variables.
Since our display option affects how we interpret the data, it is important to be clear on what we are comparing. In this post I want to show 3 ways to display temperature anomaly data and the implications that the display method has on our interpretation of the data. I’ll use a map, a trend chart and a dot plot. Continue reading
In this post, I show how to add change points to a trend chart with R. Readers can compare my R and Excel – VBA solutions for the same chart to compare R and Excel VBA charting programming. Continue reading
In this post, I define a Tukey boxplot, review the history of boxplots in Excel and walk through an R script for making a proper Tukey boxplot. A link to the source data and R script files is provided. Continue reading