In this post I introduce my RClimate functions which allow R users to easily download and plot monthly temperature anomaly data for the 5 major global temperature anomaly data series: GISS, HAD, NOAA, RSS, UAH.
Consolidated LOTA Data File
In this previous post I introduced my global Land Ocean Temperature Anomaly (LOTA) monthly csv file that Excel and R users can download to conduct climate trend analysis.
In this post, I introduce my RClimate.txt R scripts that users can source() to simplify access to the LOTA data. Please note that I have used the “.txt” descriptor for my file type to avoid download problems encountered when I use the standard R file descriptor.
This post discusses my updated and enhanced UAH Channel 5 daily trend chart. Updated 3/29/11
Update 1: 3/29/11
Since I have received a number of comments and questions about this post, I am updating it to address these comments and improve the chart.
I plot the Channel 5 data because it is available in rear real time so that readers can get a sense for how the monthly global temperature anomaly is shaping up. However, the comments tell me that there is some confusion about Channel 5 and how it compares to the UAH TLT data.
Lucia at The Blackboard has a detailed discussion of UAH TLT and Channel 5 here. Bob Illis has an interesting chart that shows the differences between UAH TLT and Channel 5 here.
Dr. Roy Spencer discussed tracking daily global temperature anomalies here.
I have revised my chart to show both the UAH TLT 5.4 and Channel 5 monthly trends as well as the daily Channel 5 data for the current month.
I’ve added this UAH Channel 5 trend chart to my sidebar: (Click to enlarge)
Phil Jones Statement (February , 2010)
Phil Jones of the Climate Research Unit (CRU) responded to a series of questions from the BBC in early February, 2010 (link). Question B dealt with global warming trends in the 1995 – 2009 period. Here’s the BBC question and Phil Jones answer:
BBC Question B: B – “Do you agree that from 1995 to the present there has been no statistically-significant global warming?”
Phil Jones Answer: “Yes, but only just. I also calculated the trend for the period 1995 to 2009. This trend (0.12C per decade) is positive, but not significant at the 95% significance level. The positive trend is quite close to the significance level. Achieving statistical significance in scientific terms is much more likely for longer periods, and much less likely for shorter periods.”
Phil Jones’ statement provided a time series regression learning moment for many of us citizen climate observers who quickly checked his statement with our Excel, R or other handy regression analysis tools. I sure did. Two readers, J and S, contacted me with questions – comments:
We are at the half way point in June, 2010 and the Arctic Sea Ice Extent is melting at a record-breaking pace. Please note I have adjusted my post based on JAXA’s 6/15/10 data update.
I have added a new page – Arctic Update where I will regularly have the latest JAXA day of year chart, my month to date data table and my month to date Sea Ice Extent chart. 6/17/10
Here’s the JAXA day-of-year chart which clearly shows how ASIE has dropped dramatically in May and so far in June. The mid June levels are the lowest in JAXA’s 2003-2010 period.
Here’s my JAXA data trend chart which shows the daily June values for each year. The blue dots reflect the daily values and the red dots reflect the ASIE values for the latest data date for each year. The green line is intended to assist reader in comparing the same values for the same data in each year.
Clearly the June 2010 ASIE is dropping rapidly, with the 6/15/2010 value significantly less than the values on this data in previous years.
This table provides additional information on the magnitude of the June ASIE decrease.
June, 2010 started at the lowest point in the 2003-2010 period, 32,000 km^2 less than the previous June 1 low in 2003. So far in the first half of June, 2010, ASIE has decreased 0.898 million km^2, beating the previous full June record of 0.797 million km^2. The mid June 2010 rate of decrease has been 60,000 million km^2 per day, considerably greater than the previous maximum mid June rate of 53,000 in 2008. (Corrected 7/7/10 based on Derek McCreadie comment)
Details on my RClimate script are available in this previous post.
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.
Lucia at The Blackboard has on on-going bet where readers submit predictions of the monthly UAH anomaly, the April bet post is here.
Lucia does some very interesting climate analysis, some of her charts, however, can give me a headache if I stare at them to long. Let’s look at her April UAH bet chart(Warning, may give you a headache if you look for too long)
What can we say about this chart? Well, um, ah, – – – let’s be positive:
- It was done in Excel. The ugly grey shading gives Excel away every time
- It’s colorful, yes, very colorful
- It has lots of data, yes, lots of data
- It is clearly labeled