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
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. ..”
This RClimate Script lets users read a NetCDF file and plot the latest satellite altimetry based global mean sea level data from 1993 to the latest completed month. The trend chart shows NOAA’s Laboratory for Satellite Altimetry altimeter global mean sea level with the seasonal signal removed and inverted barometer.
I will add this chart to my Climate Trend update sidebar and update it each month as NOAA releases updated mean sea level data.
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.
This post shows how to retrieve on-line Arctic Sea Ice Extent data from the National Snow and Ice Data Center (NSIDC), consolidate the data files, generate a csv file, summarize and plot the data and post it as a Google Docs so that interested readers can download and analyze this data series themselves.
Links to the NSIDC source data files, R script and my Google Docs csv file are provided.
Sea Ice Extent Data and Definition
The Japan Aerospace Exploration Agency (JAXA) provides daily updates to the Arctic Sea Ice Extent and maintains a downloadable csv file of daily values from June, 2002 at this link.
JAXA and other climate science data sites define sea ice extent as the area of the ocean where sea-ice concentration is 15% of more.
NSIDC maintains a series of 12 ASCII files (one for each month) that include the monthly average sea ice extent values for the period 1979 to present. I am using the NSIDC data set because it covers a longer period (31 years) than the JAXA data series.
Here’s the 1979 – 2009 trend chart of monthly Arctic sea ice extent measurement data based on NSIDC files. (Click image to enlarge)
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.