In this post I present a chart that tracks the daily Arctic Sea ice Extent (SIE) for 2007 and 2010. I chose 2007 as the comparison year because it had the record minimum and I wanted to be able to directly compare 2010 with the record minimum year to get a quick comparison of 2010 with the minimum year.
I will update this chart regularly on my Arctic Update page to help Arctic Sea Ice observers get a quick sense of the 2010 – 2007 comparison.
2010 – 2007 Comparison Chart
Here’s my R based 2010 – 2007 Arctic SIE extent chart. (Click image to enlarge)
I’ve added a number of features to this chart to help me quickly asses the situation:
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 examine the combined impacts of Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO) and El Nino – Southern Oscillation (ENSO) on the long-term GISS Land and Ocean Temperature Anomaly (LOTA) trend.
Professor Don Easterbrook of Western Washington University has stated …
“The PDO cool mode has replaced the warm mode in the Pacific Ocean, virtually assuring us of about 30 years of global cooling, perhaps much deeper than the global cooling from about 1945 to 1977.” source
Easterbrook’s PDO theory is repeated here and here. Clearly he believes that the shift in PDO phase from warm to cool will have a significant impact on global temperatures for the next 30 years.
In this post I take a closer look at PDO, AMO and ENSO indexes to see how they are related to the GISS anomaly trends.
This RClimate Script lets users retrieve and plot the monthly and moving average Pacific Decadal Oscillation (PDO) data from the University of Washington’s JISAO website. The script retrieves the PDO data from January, 1900 until latest month available at time script is run. The trend chart shows the JISAO PDO trend and user selected moving average period.
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.
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:
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 Trends – Keeling Curve
Here’s the Mauna Loa Observatory CO2 trend from 1958 to Dec., 2009.
Here are the data and RClimate Script links:
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.