Guest Post by Willis Eschenbach
I do my best to maintain my sense of awe regarding the things I study. I’ve had the good fortune in my life to be a commercial fisherman on the Bering Sea, and to voyage and fish on the edges of the Arctic ice. To me, sea ice, whether fixed to the shore or free-floating, is an awesome sight. As the poet said almost two hundred years ago,
And now there came both mist and snow,
And it grew wondrous cold:
And ice, mast-high, came floating by,
As green as emerald.
And through the drifts the snowy clifts
Did send a dismal sheen:
Nor shapes of men nor beasts we ken—
The ice was all between.
As I sift through the layers of dusty numbers and I work to understand the intricacies of the weather, I strive to maintain that sense of wonder at the scope and scale and beauty of what I am studying … but I digress.
As the song has it, I often “go to the corner, and I end up in Spain”. This time, I started out to examine what happens to the upwelling radiation when the ocean freezes over. To do this, I planned to use the Reynolds_v2_ice_cover dataset from KNMI (NetCDF is available at the bottom of the page). My idea was to compare the ice coverage data to the CERES satellite radiation dataset.
But when I had downloaded the ice cover data, here’s what I found out about the ice cover:
Figure 1. Sea ice coverage (total of northern and southern sea ice) as a percentage of total ocean area. Top panel shows the raw data. Middle panel shows the average seasonal cycle. The bottom panel shows the residual, which is the raw data minus the seasonal component.
This shows a curious evolution over time. Over the first decade plus of this record, the ice coverage gradually decreased by about half of a percent. Then from 2004 to 2010, the coverage rapidly increased by a full percent, and has stayed there for the last five years.
Now, I knew that the global sea ice has lately been on the increase. But I was unaware that the change was either that fast or that large. It increased by about one part in eight, about 12%, in a short six years. Among other things, this should be a cautionary tale about the unreliability of short ice datasets like this one …
Anyhow, I plan to follow this up by comparing the ice data to the CERES data. I just wanted to highlight this frozen oddity.
Regards to all,
w.
My Usual Request: If you disagree with me or anyone, please quote the exact words you disagree with. I can defend my own words. I cannot defend someone else’s interpretation of some unidentified words of mine.
My Other Request: If you think that e.g. I’m using the wrong method on the wrong dataset, please educate me and others by demonstrating the proper use of the right method on the right dataset. Simply claiming I’m wrong doesn’t advance the discussion.
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Looks like the analysis approach is to generate some sort of invariant seasonal component, subtract that and look at anomalies. I am not sure I agree with this.
First, are we so sure the seasonal component is identical every month, every year? I would think it is affected by a number of factors that are not identical each year.
Second, the peak and minimums can vary in time each year by a month or more. This leads to for example, a very high anomaly in 2010 that does not exist in the original data.
Third, it reduces the total information available, masking the differences between max value trends and min value trends. While the max value does appear to have declined slightly until 2003, the min value is more constant.
Is there some other way to look at this that might be more useful?
Willis
Any correlation/causation between that change in sea ice and the “pause” since 2000?
Increased ice – increased albedo – lower warming?
Or too many other parameters like ENSO.
Hi Willis,
Sorry to be off-topic, but I have tried some times to get this under your attention.
It’s about the correlation between Length of Day and Temperature: -LOD predicts dT 6 years ahead.
“Climate Change and Long-Term Fluctuations of Commercial Catches – The Possibility of Forecasting”
Source: http://www.fao.org/docrep/005/y2787e/y2787e00.htm
Would you maybe take a look at it? It’s very intriguing imho.
Best regards,
Scarface
2.1 SUMMARY
A phenomenon of close correlation between the main climatic index dT and geophysical index (-LOD) still remains an intricate puzzle of geophysics. Another challenging puzzle is the observable 6-year lag between the detrended run of dT and -LOD. Taking into account this lag, the LOD observations can be used as a predictor of the future climatic trends. Even without a mechanism for a causal relationship between the detrended climatic (dT) and geophysical (LOD) indices, the phenomenon of their close similarity for the last 140 years makes LOD a convenient tool to predict the global temperature anomaly (dT) for at least 6 years ahead.
world sea ice appears much lower this year.
The plot using the KNMI interface does not show your increasing sea ice to that extent. My guess is you aren’t area weighting the values. There’s been a drop in sea ice cover in the northern hemisphere and an increase in the southern which would skew your plot if you didn’t take area into account.
The CERES instruments fly at about 700 km and seem to scan and average energies over the entire LW spectrum. It is easy to see how they measure the TOA radiance, but they do so “where the TOA net flux has been energy balanced.” Hmmm…why not just give me the radiance? Spent maybe half an hour looking for an explanation of this balancing, their “fill” procedure, and exactly how they distinguish between surface and TOA radiance when their instrument must look down through the entire atmosphere.
No luck except for an algorithm reference that wanted to zoom me away…
Something funky definitely has been happening in and around Antarctica for the past several years.