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Messages - Bill Fothergill

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1
Arctic sea ice / Re: IJIS
« on: May 18, 2017, 04:27:45 PM »

Is this the largest drop for the day of the year?

From March 15 to 16, -112k
From April 04 to 05, -101k

However, the NSIDC daily went up 8k between the 14th & 15th May, so it will be interesting to see what happens (in about 4 hours time) when their daily figures get updated.

In case you meant drops for May 16 from any year, then the biggest drop was -105k from 2012.

Oops.  :-[

Re-reading the original question, I think my interpretation was incorrect.

I thought the questioner asked if the drop of 90,700 sq kms had been the largest to date for this year.

mea culpa   :-[


Yes, and we are now 4th lowest for the date. Might catch up with 2006 by the next few days. 2015 is a different task, might take over the second place by the first week in June when SIE stalled in 2015.

Yep, two days of -60K sq kms would put 2017 fractionally below 2006.

However, today's NSIDC daily only dropped by four thousand sq kms.

2
Arctic sea ice / Re: IJIS
« on: May 17, 2017, 10:00:07 AM »

Is this the largest drop for the day of the year?

From March 15 to 16, -112k
From April 04 to 05, -101k

However, the NSIDC daily went up 8k between the 14th & 15th May, so it will be interesting to see what happens (in about 4 hours time) when their daily figures get updated.

3
Consequences / Re: Global Surface Air Temperatures
« on: May 16, 2017, 12:20:06 AM »
... I don't think we should be surprised to see borderline El Niño conditions by late fall ...

As mentioned above, the April 2017 value was just 0.01o C below the equivalent value from 2010. However, the Nino3.4 Region values for the two years tell a completely different story.

Using NOAA's rolling 3-month threshold of +0.5o C, el Nino conditions held from JJA 2009 through to MAM 2010. On the other hand, after spending 8 months in negative territory (including a weak la Nina from JAS 2016 till NDJ) the 2017 FMA figure has just crept into positive territory.

http://www.cpc.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml


It doesn't bode well.

4
Arctic sea ice / Re: IJIS
« on: May 15, 2017, 09:54:26 PM »
As there is not a great deal of movement on the IJIS/JAXA/ADS daily numbers at the moment, I thought I would re-post an updated version of the rolling-365 day average SIE chart which was posted near the end of January.

Three features of the data are readily apparent in the chart...

1) there is an unambiguous overall downward trend in annual average sea ice extent;

2) there is the appearance of an approximately 5-year cycle superimposed on the longer downward trend, and;

3) the downward spiral has recently been halted, albeit for what could be a brief period. (N.B. Once the data for the 16th, or possibly 17th, of May is at hand, the rolling average will be at its highest level since the end of 2016.)


The reasons behind points (1) and (3) are pretty straightforward, and therefore will be addressed first.

To all bar the inhabitants of Flatland, point (1) is clearly the direct consequence of the planetary energy imbalance due to the ~ 100ppm(v) rise in atmospheric CO2 levels since Charles Keeling started tracking these values nearly 60 years ago.

The current slight rise in the curve - point (3) - can be characterised as noise, but it is nonetheless possible to explain this in part. When any rolling 365-day average value is plotted, the "instantaneous" gradient of the curve is determined by a very simple inequality. Except for the vanishingly remote chance of Day X in any year having exactly the same value as Day X of the previous year, the inequality can exist in either of two, mutually exclusive, forms...

Day X(Year N) > Day X(Year N-1),
OR
Day X(Year N) < Day X(Year N-1)

Whenever the Day X(Year N-1) value represents a genuine statistical outlier, then it is axiomatic that the Day X(Year N) value is generally likely to be less extreme, in other words, it is likely to demonstrate regression toward the mean.

That is exactly the situation we are seeing at present, and are going to be seeing for some time to come. When I did a snapshot on May 11th, this is what the rolling-365 day average would be seeing over the next 12 months...

181 days in which the Day X(Year N-1) value was the lowest on record
76 days in which the Day X(Year N-1) value was the 2nd lowest on record
72 days in which the Day X(Year N-1) value was the 3rd lowest on record

(NB Obviously the likelihood of regression to the mean taking place is affected by any developments in the shape of the overall trend.)

Graph 1 & 2 (below) are a matching pair which only differ in the Y-axis; the first shows the actual value of the rolling 365-day average extent, whilst its partner shows this as an anomaly from the Jan 2006 - December 2015 mean.

Graph 3 (bar chart) puts the above into a bit more context by also including overall means for the 1980's, 1990's, 2000's and 2010-2016. Column 5 shows the highest value for the rolling average attained over the last decade, and the remaining columns show the local minima recorded at the turning points in the first 2 graphs.


Moving onto point (2) - the putative approximately 5-year cycle superimposed upon the overall declining trend in sea ice extent. This is a topic that has been (and is being) discussed on the ASIB. My own view - for what little that is worth - was that the period under examination was far too short to determine if this was a genuine recurring pattern.

Given the current lack of activity in SIE numbers, I downloaded the .csv file from the ADS version 2 site - as this starts from 1979, rather than 2003 as per ADS version 1 - with the intention of extending the chart back by about 25 years. However, owing to the number of data drops during the early stages (and the fact that daily measurements  only began during 1987) it was easier to use the NSIDC monthly values as a reasonable proxy.

This is shown on graph 4, and, to my surprise, with the data stretched back to ~ 1980, there is still some semblance of a recurring pattern.

Given the approximately 5 year periodicity of this possibly cyclic phenomenon, it seemed like an idea to map - for starters - the Nino 3.4 anomalies. As with the SIE data, this was smoothed to give a rolling 12-month average, and was then lagged by 6, 12, 18, 24 and 30 month periods. This is shown as graph 5.

The Nino anomaly values are shown on a secondary Y-axis which has been inverted to display +ve anomalies as downward pointing excursions. It was hoped that by implementing this inversion, dips in the SIE might line up with el Nino events, but any such correlation escapes my Mk I eyeball. (Although, following the successful operation last year, I should perhaps call it a Mk II?)

Whilst graph 5 singularly fails to demonstrate any obvious correlation between el Nino/la Nina patterns and sea ice extent behaviour, it's been included in the hope that it may, nonetheless, give an idea to someone. Hopefully, at least two of the regular contributors to the ASIB might have some words offer, as we have differing views on the subject.

5
Arctic sea ice / Re: IJIS
« on: May 15, 2017, 05:12:40 PM »
Some decent drops the last two days but we are still 6th lowest and a whooping 800K behind 2016... Even 2004 had lower extent at this date of year.

2016 isn't a concern, if you ask me; given 2016's very low June decrease and the state of this year's ice, that 800k extent gap will disappear within the next 5-6 weeks. (Between May 31 and June 15, last year dropped by just 541k km2, while 2012 lost an amazing 1.347M--a "gap closing" of over 800k.)

My hunch is that 2017 will spend most of July and August in either first or second place.

Although 2017 might be currently "languishing" in 6th lowest position, when the data for May 14th gets factored in, the current SIE is only ~ 90k sq kms higher than the 3rd lowest for the date (2006), and ~ 180k sq kms higher than that recorded in 2015, which is the 2nd lowest for the date.

As at May 14, and just considering the period stretching from 2004 until now, 2012 has the 2nd highest SIE for the date in the IJIS/ADS database - and I think we all know what happened a bit later in that year.

6
Arctic sea ice / Re: IJIS
« on: May 11, 2017, 07:21:44 PM »
UPTICK in May?! :o How unusual is that?

There are a handful in the record. 2004 had a two day uptick of 19664 and 8586 on May 25 and 26.  There are a sprinkling of others but they are pretty rare.

As dnem said, May upticks are rare. I happen to have a spreadsheet based on the ADS Version 1 .csv (basically, this is from 2003 onwards) already set up to shown daily increments, and this reveals some even later upticks...

04 June 2016: +3,537
08 June 2015: +1,662
30 July  2013: +4,102

There are 4 more near the end of August, and then the colour scheme starts transitioning from red to black.

7
Arctic sea ice / Re: The 2017 melting season
« on: May 09, 2017, 12:47:01 PM »
...
I think I am going to move this to a separate thread
...
- The energy for raising 1.8 degrees 30 m of water is equivalent to that needed for bottom-melting approximately 0.75 m of ice!!!! (since raising 1C of a 80m-deep extent of water requires the same energy to melt 1m of the same extent of ice)
...

NB I will move my comment over to the appropriate thread once you have set it up.

I was going to mention that the density of ice is less than that of water, but you appear to have already included that in order to get to the 0.75 metre value.

(30/80) * 1.8 would just give 0.675 metres, but if the (relative) density was taken as ~ 0.9, that would give your figure of 0.75 metres.

I think your x80 multiplier would only be appropriate for fresh water. The SH of sea water varies somewhat with salinity, but is roughly 3.985 kJ.kg-1.K-1, as opposed to the 4.186 kJ.kg-1.K-1 value for pure water. {I am assuming you are using a value of around 333.5 kJ.kg-1 as the enthalpy of fusion?}

However, that only represents a difference of ~ 5%, so it doesn't really help much in answering the question you raised.


8
Consequences / Re: Global Surface Air Temperatures
« on: May 06, 2017, 01:37:58 AM »
HadCrut annual comes with an estimated 2017 value, with a confidence range.

Top three stuff, new record possible.

Interesting that the very provisional "predicted" year-end value for HadCRUT is currently showing as the 4th consecutive record year...

2014 +0.575o C
2015 +0.760o C
2016 +0.773o C
2017 +0.820o C

As each of the three monthly anomaly values so far this year (+0.740o C ; +0.847o C ; +0.876o C ) was considerably cooler than the equivalent value(s) from 2016 (+0.906o C ; +1.070o C ; +1.069o C ), for this "projection/prediction" to be realised, the remainder of the year could get interesting.

To equal the 2016 temperature anomaly, the remaining 9 months of the year would need to average about 0.065o C warmer than that clocked up for April - December 2016 (which was ~ +0.694o C).

To get to the "predicted" value, the April - December average for this year would need to be about 0.125o C warmer than the equivalent from last year.

I would expect that the teams from the Met Office and the CRU are looking at the ENSO figures with some interest. NOAA figures put the July - December 2016 average anomaly in the 3.4 region at -0.71o C, but the Mar-April average this year is +0.3o C, and there currently seems to be about a 50% chance that an el Nino could develop later this year. (Although one would certainly expect some lag in the relationship.)

9
Consequences / Re: Global Surface Air Temperatures
« on: May 04, 2017, 01:20:55 AM »
Amidst the above talk about April, the UK Met Office and the University of East Anglia have finally managed to publish the March HadCRUT numbers. Coming in at +0.876o C, this was the 2nd warmest March and the 6th warmest of any month in the dataset.

The top 20 are...

1998/02   0.761   0.638   0.880   13
2007/01   0.834   0.692   0.981   10
2015/05   0.707   0.548   0.866   20
2015/06   0.740   0.594   0.886   14
2015/08   0.738   0.511   0.965   16
2015/09   0.792   0.599   0.986   11
2015/10   0.837   0.703   0.976   8
2015/11   0.836   0.720   0.955   9
2015/12   1.024   0.893   1.151   3
2016/01   0.906   0.753   1.061   5
2016/02   1.070   0.938   1.200   1
2016/03   1.069   0.923   1.208   2
2016/04   0.915   0.771   1.059   4
2016/06   0.731   0.585   0.877   17
2016/07   0.728   0.542   0.919   18
2016/08   0.770   0.549   0.994   12
2016/09   0.711   0.516   0.906   19
2017/01   0.740   0.577   0.906   14
2017/02   0.847   0.716   0.977   7
2017/03   0.876   0.733   1.018   6

Col 1 = Date; Col 2 = Anomaly, Cols 3 & 4 = Lower and Upper 95% Conf Range; Col 5 = Rank

One does not need to be excessively eagle-eyed to notice that 18 of these are from within the most recent 24 months.



Rather worryingly, things continue to warm up in the Nino 3.4 Region. The latest NOAA numbers are..

2016  11   25.96   26.88   -0.93
2016  12   26.08   26.80   -0.72
2017  01   26.24   26.61   -0.37
2017  02   26.63   26.80   -0.17
2017  03   27.49   27.32    0.17
2017  04   28.29   27.86    0.43

Cols 1 & 2 = Date; Col 3 = Actual Temp; Col 4 = Climatology; Col 5 = Anomaly

That's shaping up for the >= +0.5o C threshold for el Nino conditions by the end of May, although it would need to reach at least +0.75o C for the more meaningful rolling 3-month figure to reach the threshold. (N.B. Strictly speaking, the May value should need to reach +0.9o C, but, as NOAA only go down to the first decimal point when talking about the 3-month figure, that +0.75o C would suffice when rounding is taken into consideration.)

However, even if the MAM value reaches +0.5o C, the earliest that NOAA would declare a full el Nino would be if the rolling 3 month value stayed above threshold until the JAS period, i.e. five consecutive rolling 3-month figures.



10
Arctic sea ice / Re: The 2017 melting season
« on: May 02, 2017, 01:45:20 PM »
The NSIDC daily figures have just come in, and they show a rather abrupt loss of ~ 259k sq kms between 30th April and 1st May.

Is this a "1st of the month" effect?

Is it merely a form of "correction" caused by cells dropping out of the >15% threshold, after only losing ~100k over the last 8 or 9 days?

Or is Mr S*%t meeting Mr Fan?

11
Arctic sea ice / Re: IJIS
« on: May 02, 2017, 01:02:19 PM »
I suspect some rapid melt in the next 7 days around greenland

temps well over 0c forecast


Same as i, because not only of temp, also on thickness: http://data.seaiceportal.de/maps/smos/n/2017/thumbs_800/thick_n_20170430.png


It will be interesting to see if this anticipated melting is sufficient to keep 2017 in amongst the "lowest 3 for the day" values.

Here is a variant on Deeenngee's chart at #4178, with data up to, and including, the 1st May (i.e. Day 121).

Tips on interpretation;

Only years with around ~90 (or more) entries in the "lowest 3" are shown.

Generally, each year has 5 columns...
Col 1: status at end of 2015
Col 2: status at end of 2016
Col 3: maximum still possible by end of 2017
Col 4: positions already achieved thus far in 2017 (i.e. "locked")
Col 5: positions held last year between NOW and 31st Dec 2016 (i.e. "vulnerable")

Therefore difference between Col 1 & Col 2 equates to positions lost last year, and the difference between Col 2 & Col 3 equates to positions lost since 1st Jan 2017.

12
Arctic sea ice / Re: Latest PIOMAS update (April)
« on: May 02, 2017, 12:28:33 PM »
...
Thank you Bill. Much appreciated.
First thing I noticed is that you and Random_Weather agree.
Your correlation between PIOMAS April numbers and NSIDC September numbers is R=0.342, which gives R^2=0.117 which is exactly what Random_Weather reported (thank you for that scatter plot RW!).
...
So PIOMAS in April is not a good predictor of September SIE
...

I've said it before, and will doubtless say it again.. D'Oh!!!!  :-[

Sorry for being so slow guys.

Can I just point out that I never said April PIOMAS figures had great skill at predicting the September SIE. The question originally was along the lines of did early month PIOMAS have more skill than early month SIE.

As Rob and I both wrote articles on the ASIB a few years ago discussing how weak (i.e non-existent) the April:September SIE relationship was, the bar was set pretty low to start with.

However, I still think that the April PIOMAS: September SIE correlation can correctly be described as "significant, but weak". Given such a tenuous relationship, it would never occur to me to do a September prediction predicated solely upon a single variable - and certainly not one involving SIE.

13
Arctic sea ice / Re: IJIS
« on: May 01, 2017, 01:59:16 PM »
For those experiencing "cold turkey" whilst ADS is having a little rest...

After spending the 8 days (covering the 22nd to 29th April) languishing in the 13.4xx million sq kms range, the NSIDC single day value plummeted all the way to 13.395 on the 30th.  ;)

ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/daily/data/N_seaice_extent_daily_v2.1.csv

14
Arctic sea ice / Re: The 2017 melting season
« on: May 01, 2017, 11:39:49 AM »
... Not many bergs or floes here in NZ. ... We did have some giant Bergs visit about ten years ago. Larsen remnants I believe they were believed to be ...

It's OT for this thread, but there could be some more en route to a place near you in the not too distant future...
https://forum.arctic-sea-ice.net/index.php/topic,1175.0.html


Shrek's had a haircut?  :'(

15
Antarctica / Re: Rift in Larsen C
« on: May 01, 2017, 11:28:08 AM »
I noticed what looks like a warm foehn wind forecast for the 10th, blowing off the ice shelf. Maybe that will help things along?



Depends on how you are using the word "help".  ;)

See this BBC article (or possibly "antarcticle"?) on the Larsen C and the impact of the Foehn effect thereupon...
http://www.bbc.co.uk/news/science-environment-39759329

The BBC probably used this BAS press release as their source...
https://www.bas.ac.uk/media-post/new-insight-into-what-weakens-antarctic-ice-shelves/

Other BAS articles on the Foehn effect can be found...
https://www.bas.ac.uk/?s=Fohn

16
Arctic sea ice / Re: IJIS
« on: April 30, 2017, 01:23:25 AM »
... NSIDC charctic ...Is this 5-day average? ...

Yes Rot, Tot, Otr, Rto, Ort, Tro, Tor

What appears on the charctic is the rolling 5-day average of this daily data series...

ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/daily/data/N_seaice_extent_daily_v2.1.csv

(No prizes for guessing what you get if you change the "north" to "south", and the "N_seaice" to "S_seaice" in that url.)

The above url is also the source for Feeltheburn's correct statement that the value on 28th April is the 4th lowest for that date. One can easily pull out the 3 lower instances by using the browser's "Find" functionality.

To quickly highlight just the 28th April dates, search for "04,  28", then start searching bottom upwards. (NOTE: the search string needs two spaces between the comma and the 2)


FatFingeredFothergill

17
Arctic sea ice / Re: Latest PIOMAS update (April)
« on: April 30, 2017, 12:54:25 AM »
I agree with the comment from dosibl that this is getting into a statistics discussion, rather than a PIOMAS discussion.

However, if I am making a mistake in the way I try to use the available statistical functions, then I would be more than happy to be educated in their correct use. (Although that is always a difficult task where I'm concerned   :o) .

Therefore, can I just ask why R_W and Jai are NOT using a function such as CORREL?

I am pretty familiar with using the Coefficient of Determination (ie the R2 value) when one plots a traditional dependent variable versus independent variable chart, such as the decline of the September SIE through time, or the rise in global temperature anomaly through time.

When one then adds a trend line, the resultant R2 gives a measure of the unexplained variance. My understanding (again, this is always questionable) is that the fraction of the variance left unexplained is generally treated as being equal to { 1 - R2 }

I don't understand (and, yet again, that could be all down to my lack of in-depth knowledge) why you are choosing to use this metric when plotting two sets of residuals, instead of using a function such as CORREL - especially when it seems that CORREL has been specifically designed to calculate the correlation coefficient between two data series.

http://www.excel-easy.com/examples/correlation.html

https://support.office.com/en-us/article/CORREL-function-995dcef7-0c0a-4bed-a3fb-239d7b68ca92?ui=en-US&rs=en-US&ad=US&fromAR=1


Perhaps we can iron this out using the forum's Messages functionality, rather than clogging the thread?

18
Arctic sea ice / Re: Latest PIOMAS update (April)
« on: April 29, 2017, 06:19:50 PM »
Just for a giggle, I did a quick correlation analysis between the PIOMAS September residuals and the NSIDC SIE September residuals.

The correlation is also going down over the last 2 decades.

Jai, here are the numbers I get when running CORREL on the PIOMAS September residuals and the NSIDC SIE September residuals...

1979-1998 +0.714
1997-2016 +0.808

I then thought you may have meant that the coefficient might have been dropping in a "jerky" fashion, so I locked the start year as 1979 and incremented the finish year...

1998   +0.714
1999   +0.715
2000   +0.717
2001   +0.741
2002   +0.733
2003   +0.736
2004   +0.738
2005   +0.734
2006   +0.734
2007   +0.751
2008   +0.750
2009   +0.745
2010   +0.735
2011   +0.744
2012   +0.773
2013   +0.755
2014   +0.760
2015   +0.758
2016   +0.755


Of course, as as been demonstrated before, it's not unheard of for me to pair up the wrong two columns.

I'll check my homework  ;)



19
Arctic sea ice / Re: The 2017 melting season
« on: April 29, 2017, 05:09:57 PM »
...
You made me feel young (very young) again!  :)

All part of the service  :-[

20
Arctic sea ice / Re: Latest PIOMAS update (April)
« on: April 29, 2017, 05:06:59 PM »
To make clear, April Volume residuals not saying anything about extent residuals in september, here for 1979-2016

You have plotted April PIOMAS residuals against September NSIDC SIE residuals, but I'm not sure what physical reality this is meant to represent. If I was looking for some correlation between the two data series, I would use a function such as Excel's CORREL.

There are 38 data pairs in the 1979-2016 range. On 11 occasions, each member of the pair is negative, and on 14 occasions, each pair member is positive.

I know this is an artificial example, but try thinking in terms of tossing two coins, and getting either 2 heads{2H}, or 2 tails{2T}. Using the cumulative binomial distribution, the chances of only getting {1H + 1T} on 13 (or less) occasions is less than 1.7%

The fact that there is this degree of agreement demonstrates that there IS a positive correlation, and the p-value derived from the correlation coefficient and the number of Degrees of Freedom subsequently demonstrates the level of statistical significance.

If you consider the direction of the slope on your diagram, you will see that this actually corresponds to a preponderance of the data pairs being either, both negative, or, both positive.

21
Arctic sea ice / Re: Latest PIOMAS update (April)
« on: April 29, 2017, 03:22:06 PM »
Just for a giggle, I did a quick correlation analysis between the PIOMAS September residuals and the NSIDC SIE September residuals. The value thus obtained for the correlation coefficient was +0.755

That value would be significant at the 99.9% level (p-value < 0.001) had there been only 16 data pairs, rather than the actual number, which was 38. Had there even been only 7 data pairs, such a correlation coefficient would have been significant at the 95% level.

22
Arctic sea ice / Re: The 2017 melting season
« on: April 29, 2017, 02:15:38 PM »
TotTor, oren, Terry, Rob,  {Oops, just noticed the fat-finger syndrome}

I think there has been some gibbering in Flatland recently concerning the amount of ice around Newfoundland. One suspects that this is export related, and that any such ice is basically "dead man walking".
The ice around Newfoundland is almost certainly the result of collapsing glaciers not sea ice. Its one area where an increase in 'sea ice' can be expected as glacier collapse in Greenland becomes more prevalent.

Yeah. My first response when I saw the comment(s) about ice in the Newfoundland region was that it was almost certainly a mixture of (a) detritus that had calved from a glacier front, and (b) an artefact caused by freshwater lensing as a result of melt.

However, there was also a remark about the thickness being at record level.

Having a totally useless memory, I cannot recall the article source. HOWEVER, I pretty sure it would have been something associated with a very recent entry on the "Arctic Image of the Day" thread. There was a photo (#835) on that thread of a grounded 'berg off the coast near Ferryland. It was just after seeing that image, that I read (somewhere) about there being sea ice of record thickness near Newfoundland.

Being in an unusually generous mood, I was prepared to accept the description as having some basis in fact - as opposed to the normal Flatland bollocks. As I mentioned in the original post, if that genuinely is sea ice - as opposed to glacial ice - then it has come from further north, and is on its way to a rather rapid phase change.

Perhaps I was being overly generous. (Perhaps there is no "perhaps" about it?)

23
Arctic sea ice / Re: The 2017 melting season
« on: April 29, 2017, 10:02:37 AM »
Tot, oren, Terry, Rob,

I think there has been some gibbering in Flatland recently concerning the amount of ice around Newfoundland. One suspects that this is export related, and that any such ice is basically "dead man walking".

24
Arctic sea ice / Re: Latest PIOMAS update (April)
« on: April 29, 2017, 09:56:26 AM »
Here you go, Rob...

April:September correlation coefficients for the period 1979-2016

Using NSIDC SIE monthly values only = -0.109

Using PIOMAS monthly values only = +0.650

Using PIOMAS April: NSIDC SIE September = +0.342


Given the Degrees of Freedom, that {PIOMAS April: NSIDC SIE September} correlation still has a p-value <0.05.

In other words, although the correlation could hardly be described as strong, it's still significant at the 95% confidence level.


{EDIT: Just to be fully explicit, the above correlations are based on the residuals left after each data series was detrended. In each case, the detrending was done by using a bog-standard linear trend line.}

25
Arctic sea ice / Re: Latest PIOMAS update (April)
« on: April 28, 2017, 08:11:01 PM »
However, using Excel's CORREL, the correlation coefficient between the PIOMAS mean March-April-May residuals and the September residuals (1979-2016) comes out at an interesting 0.65

R=0.65 is not bad at all for a March predictor of September SIE.
But what is the SD over the residuals ? And is it better than the SD of 550 k km^2 from the simple linear trend ?
Either way, we should probably take this discussion elsewhere.
You want to take it to the PIOMAS thread ?

Rob, here are the (hopefully) relevant numbers from my PIOMAS spreadsheet. Please let me know if I have managed to misinterpret your question.    :-[

March 1979-2016
Equation of linear trend: Y = -0.264X + 31.921
Mean value = 26.781
SD of residuals (after detrending using the above linear trend) = 1.049
Correlation Coefficient with Sept 1979-2016 = 0.638

April 1979-2016
Equation of linear trend: Y = -0.263X + 32.926
Mean value = 27.805
SD of residuals (after detrending using the above linear trend) = 1.010
Correlation Coefficient with Sept 1979-2016 = 0.650

Average across March, April and May 1979-2016
Equation of linear trend: Y = -0.270X + 32.478
Mean value = 27.209
SD of residuals (after detrending using the above linear trend) = 1.038
Correlation Coefficient with Sept 1979-2016 = 0.692

September 1979-2016
Equation of linear trend: Y = -0.324X + 17.482
Mean value = 11.170
SD of residuals (after detrending using the above linear trend) = 1.434


{With the exception of the coefficients, which are dimensionless natural numbers, all the other values shown above should be expressed in thousands of cubic kms.}

NB In my early post, I wrongly gave the Mar-May correlation with Sept as 0.650. This was a transcription error, and that value (0.650) is actually the April:September correlation coefficient. The averaged (March-May):September correlation comes out at 0.692, as shown immediately above.


Given the Degrees of Freedom for those correlation figures, the p-value for each would be < 0.001, and by a substantial margin.

I hardly need to tell you (although some others might not be as numerate) but there would need to be some appropriate form of normalisation required in order to compare the PIOMAS and NSIDC residuals. However, the fact that the September residuals are larger than those from near the maximum volume period, even before any normalisation based on mean values, is indicative of the increased level of "noise" surrounding the annual minimum.



26
Arctic sea ice / Re: Latest PIOMAS update (April)
« on: April 28, 2017, 12:22:53 AM »
This was originally posted on the 2017 Melting Season thread, but some parts are clearly of relevance to this PIOMAS thread...

...
Either way, and from the graphs posted earlier, it is clear that sea ice 'volume' is on a persistent and potentially catastrophic decline. 2017 is especially noteworthy, because of the current record low PIOMAS numbers.
...
We'll see what September 2017 brings us, but it seems clear that there is a good chance that we are about to find out if the Arctic summer melts ice 'volume' or if it melts 'extent'.

It's an interesting quandary, isn't it Rob?

I was playing about with the monthly figures for PIOMAS, NSIDC Area and NSIDC extent in order to see if I could tease out any clue as to which might be least susceptible to "noise". To do so, I used a simple linear regression in order to obtain a value for the trend, and then subsequently calculated the residuals.

I then compared the Standard Deviation of the residuals with the trend. It's obviously more than a bit crude and simplistic, but my thinking was the higher the value of this ratio, the less time it takes for the genuine underlying trend to emerge from any noise distortion (i.e. natural variability).

The September numbers were...

PIOMAS: Trend = -324 cubic kms per annum, SD of residuals = 1,434 cubic kms

NSIDC area: Trend = -79k sq kms per annum, SD of residuals = 441k sq kms

NSIDC extent: Trend = -87k sq kms per annum, SD of residuals = 550k sq kms


That produces ratios of...
PIOMAS 0.226
NSIDC area 0.18
NSIDC extent 0.159

A possibly more meaningful way of expressing these values might be in terms how many years worth of each trend equates to 2 times the relevant Standard Deviation (i.e. the old 95% confidence level). That comes out as 9 years, 11 years and 12 and a half years respectively.

Using that simplistic approach would suggest that PIOMAS will be the better indicator, as it makes an earlier emergence from the natural variability.

The PIOMAS Daily Arctic Ice Volume graph from Wipneus that you posted is excellent at showing how perilous the end-of-melt-season has become, but, looking at the March-April-May part, it also serves to show that we are still a long way from a totally ice free Arctic. On the 1979-2001 average, the value for the beginning of April is ~ 29,700 cubic kms. The equivalent 2017 value stands at ~ 20,4000 cubic kms - a drop of just over 9,000 cubic kms over a (notional) period of 27 years.

The attached diagrams below show PIOMAS projections for September and for the March-May average volume. If one projects a 2nd order polynomial trend line, the September figure effectively goes to zero in 5 years, but, with a linear projection, this is delayed until about 2032.

The maximum volume is typically attained in April, but with the March-May average and using a 2nd order polynomial fit, the trend does not go to zero until 2050. In fact, the March-May average would still be around 10,000 cubic kms in 20 years time. (Using a linear fit, this trend does not reach zero until almost the end of the 21st Century.)

Anyway, getting back to the melting season aspects, we both know how poor the correlation is for area/extent when the interval gets more than a couple of months. There are various references in the scientific literature to a decorrelation period of just 2 or 3 months for area/extent.

However, using Excel's CORREL, the correlation coefficient between the PIOMAS mean March-April-May residuals and the September residuals (1979-2016) comes out at an interesting 0.65

Rob, I know you asked a follow-up question, but I've been out virtually all day. I'm feeling zonked at the moment, but will provide an answer tomorrow.

There is one "significant" point that I should have mentioned in the original post. There were 38 pairs of values used to generate that correlation coefficient quoted just above. That means the system has, I think, 36 degrees of freedom. Using my old stats workbook, and given that d.f.=36, the generated correlation is established to hold at beyond the 0.001 significance level.

27
Arctic sea ice / Re: Latest PIOMAS update (April)
« on: April 27, 2017, 11:10:33 AM »
Rob, I hope I got the right place.  here is everything in somewhat chronological order.  Hope I got the overall gist of what was wanted . . .

Repost of what was original posted in "melting season".

Question:  I have used the PIOMAS volume and NSIDC area monthly averages to calculate thickness. 


As you already know dj, Wipneus has said that the NSIDC numbers have a "pole hole". This applies only to area, as they already incorporate the hole size into extent values. (i.e. it is taken as read that there is ice of >15% concentration at the pole hole hole.)

If one wishes to apply a correction to the area values, the relevant offsets are given here...
http://nsidc.org/data/docs/noaa/g02135_seaice_index/#pole-hole-size

28
Arctic sea ice / Re: The 2017 melting season
« on: April 27, 2017, 11:00:09 AM »
Dear friends, can we please stay on-topic? There are various threads for discussing PIOMAS, volume, thickness, research.

Melting season.
Sorry if it was my post #949 which was initially responsible for the OT seque.

I had been trying to provide a simplistic analysis concerning which metric (PIOMAS/extent/area) might be the better indicator for the forthcoming - and potentially horrific - melt season.

I'll copy #949 over to the PIOMAS thread, and will provide any relevant responses over there.

29
Arctic sea ice / Re: The 2017 melting season
« on: April 27, 2017, 10:50:53 AM »
Thank you for the comments and the further resources to explore.

And thank you Wipneus for identifying the weakness (incorrectness) of my comparison, and providing the corrected data. 

Neven, apologies for picking the incorrect place to post this.

As Wipneus correctly (natch!  ;)) pointed out, the NSIDC monthly values for area have a "pole hole". (NB This only applies to area; for extent, they work on the basis that the pole hole is fully covered by ice with >15% concentration, and therefore this is already included in the published numbers.)

I utilise the NSIDC monthly numbers in several of my tables, but, before using any of the values, the following offsets are added...

Nov 1978 - Jun 1987      1.19   million sq kms   
Jul 1987 - Dec 2007      0.31   million sq kms   
Jan 2008 - present      0.029 million sq kms   

(NBB By doing this, I am therefore assuming the pole hole is 100% ice covered. That's becoming a highly questionable assumption, but the current pole hole size is so small, it doesn't overly affect things.)

See...
http://nsidc.org/data/docs/noaa/g02135_seaice_index/#pole-hole-size


 

30
Arctic sea ice / Re: The 2017 melting season
« on: April 26, 2017, 10:57:32 AM »
...
Either way, and from the graphs posted earlier, it is clear that sea ice 'volume' is on a persistent and potentially catastrophic decline. 2017 is especially noteworthy, because of the current record low PIOMAS numbers.
...
We'll see what September 2017 brings us, but it seems clear that there is a good chance that we are about to find out if the Arctic summer melts ice 'volume' or if it melts 'extent'.

It's an interesting quandary, isn't it Rob?

I was playing about with the monthly figures for PIOMAS, NSIDC Area and NSIDC extent in order to see if I could tease out any clue as to which might be least susceptible to "noise". To do so, I used a simple linear regression in order to obtain a value for the trend, and then subsequently calculated the residuals.

I then compared the Standard Deviation of the residuals with the trend. It's obviously more than a bit crude and simplistic, but my thinking was the higher the value of this ratio, the less time it takes for the genuine underlying trend to emerge from any noise distortion (i.e. natural variability).

The September numbers were...

PIOMAS: Trend = -324 cubic kms per annum, SD of residuals = 1,434 cubic kms

NSIDC area: Trend = -79k sq kms per annum, SD of residuals = 441k sq kms

NSIDC extent: Trend = -87k sq kms per annum, SD of residuals = 550k sq kms


That produces ratios of...
PIOMAS 0.226
NSIDC area 0.18
NSIDC extent 0.159

A possibly more meaningful way of expressing these values might be in terms how many years worth of each trend equates to 2 times the relevant Standard Deviation (i.e. the old 95% confidence level). That comes out as 9 years, 11 years and 12 and a half years respectively.

Using that simplistic approach would suggest that PIOMAS will be the better indicator, as it makes an earlier emergence from the natural variability.

The PIOMAS Daily Arctic Ice Volume graph from Wipneus that you posted is excellent at showing how perilous the end-of-melt-season has become, but, looking at the March-April-May part, it also serves to show that we are still a long way from a totally ice free Arctic. On the 1979-2001 average, the value for the beginning of April is ~ 29,700 cubic kms. The equivalent 2017 value stands at ~ 20,4000 cubic kms - a drop of just over 9,000 cubic kms over a (notional) period of 27 years.

The attached diagrams below show PIOMAS projections for September and for the March-May average volume. If one projects a 2nd order polynomial trend line, the September figure effectively goes to zero in 5 years, but, with a linear projection, this is delayed until about 2032.

The maximum volume is typically attained in April, but with the March-May average and using a 2nd order polynomial fit, the trend does not go to zero until 2050. In fact, the March-May average would still be around 10,000 cubic kms in 20 years time. (Using a linear fit, this trend does not reach zero until almost the end of the 21st Century.)

Anyway, getting back to the melting season aspects, we both know how poor the correlation is for area/extent when the interval gets more than a couple of months. There are various references in the scientific literature to a decorrelation period of just 2 or 3 months for area/extent.

However, using Excel's CORREL, the correlation coefficient between the PIOMAS mean March-April-May residuals and the September residuals (1979-2016) comes out at an interesting 0.65

31
Consequences / Re: Global Surface Air Temperatures
« on: April 25, 2017, 10:13:04 AM »
Since I first saw this spike in temperatures during WWII and the subsequent drop, I have always wondered why this happened. I doubt it is war related. Can someone with more knowledge than me explain this?

Aerosols to the lot of you.   ;)

There is a wealth of material available on this. A decent starting point is...
https://www.skepticalscience.com/global-cooling-mid-20th-century-basic.htm

(HINT: For those unfamiliar with the SkS series of Climate Change Rebuttals, it is worth going through the Basic/Intermediate/Advanced in that sequence.)

Some more perspective can be gained by looking at these two tables...
https://www.census.gov/population/international/data/worldpop/table_history.php
https://www.census.gov/population/international/data/worldpop/table_population.php


32
Arctic sea ice / Re: IJIS
« on: April 25, 2017, 09:30:28 AM »
A century, and the graph is flat?  Something seems wrong.
It's covering 3 days, since IJIS was down.
As Oren stated, we had a hiatus/pause from April 21 to April 24. The "missing" values can be found on the .csv file

April 22: 12875995
April 23: 12827488
April 24: 12832850

33
Antarctica / Re: Sea Ice Extent around Antarctica
« on: April 24, 2017, 09:03:05 PM »
Quite warm in Antarctica too at the moment....

Also a remarkable anomalies in albedo warming potential- here a site with compairision of several years:
https://sites.google.com/site/cryospherecomputing/warming-potential/Albedo-Warming-Overview

That site is run by Nico Sun, who posts on the ASIF under the handle of "Tealight".

Here is the link to his thread on Albedo Warming Potential...

http://forum.arctic-sea-ice.net/index.php/topic,1749.0.html

34
Arctic sea ice / Re: 2017 sea ice area and extent data
« on: April 23, 2017, 08:10:31 PM »
Is there any correlation between winter sea ice volume maxima and summer minima ?


Using data for 1979-2016,  the correlation between detrended maximum volume and detrended minimum volume is 0.648, which is highly statistically significant (p-value: p < 0.001).

However, this is only true for sea ice volume.  For sea ice extent (rather than volume), the correlation between detrended maxima and detrended minima is very weak.


Thank you Steven. That was a concise and meaningful answer to a perfectly reasonable question.

However, an earlier response to Gerontocrat's question was less helpful.
... Sorry to point out the obvious, but there is no need to calculate a statistical correlation between winter sea ice volume maxima and summer minima, because the two are directly related by a simple formula:
summer ice minimum = (previous) winter ice maximum - total spring/summer melt
...


Instead of answering the question as to the existence (or otherwise) of such a correlation, that was simply a descriptive statement of an obvious equality. A similar example of an obvious equality from the world of finance would be...

Closing share price = Opening share price + Change in share price

Although taken from entirely different spheres, these two equality statements share a common weakness: namely that, in the absence of any reliable form of time travel - other than the usual unidirectional 1 second per second familiar to everyone - the predictive skill of each is precisely zero.

As Steven goes on to stress, although there is a strongly positive correlation when the metric is volume, that breaks down when looking at either extent or area. In the summer of 2013, Rob Dekker and myself independently wrote articles on this subject for Neven's Arctic Sea Ice Blog.

http://neven1.typepad.com/blog/2013/06/problematic-predictions.html
http://neven1.typepad.com/blog/2013/07/problematic-predictions-2.html

Bringing that a bit more up to date, and using Excel's CORREL function on the NSIDC monthly values for both Artic Sea Ice extent and area for September 1979 - March 2017...

Correlation between September extent (year X) and March extent (year X+1) = 0.739
Correlation between September area (year X) and March area (year X+1) = 0.678

However, those seemingly meaningful correlations are largely due to the overall downward trend in the dataset(s).

March extent trend = - 42k sq kms/annum
March area trend = - 32k sq kms/annum

September extent trend = - 87k sq kms/annum
September area trend = - 79k sq kms/annum

Once the data has been de-trended (using a simple least-squares linear regression), the output(s) of the CORREL function change to...

Correlation between September extent (year X) and March extent (year X+1) = -0.068
Correlation between September area (year X) and March area (year X+1) = -0.165

As Steven stated, this represents a pretty weak level of correlation - and it actually comes out as being weakly negative.


N.B. As mentioned earlier, during those array comparisons, the average September value of (year X) would be paired with the average March value of (year X+1). The reason for this particular arrangement was because Gerontocrat's original question concerned the correlation if only the freezing season was considered. Had the question pertained to the melting season, then March and September values from the same year would have been compared.

However, it would not really have made much difference, as the de-trended correlations for the March - September melt season are also very weak...

extent = 0.000
area = -0.022

35
Consequences / Re: Global Surface Air Temperatures
« on: April 23, 2017, 04:19:29 PM »
From CCI-Reanalyzer:-
World Temp Anomaly     0.31 degrees Celsius,
World SST anomaly        0.39 degrees Celsius.

I first noticed this yesterday. Is it unusual for global temperature anomaly to be less than global SST anomaly?

Using HadCRUT and HadSST monthly values...

From Jan 1850 to Feb 2017 (inclusive), there were 862 occasions (out of 2006 pairs of values) in which the SST value was higher.

From Jan 2000 to Feb 2017, the ratio plummets to just 11 from 206.

The last such occurrence was October 2016, and the time before that was July 2014.

36
Consequences / Re: Global Surface Air Temperatures
« on: April 23, 2017, 01:12:15 AM »
Berkeley Earth have just updated their BEST figures. No prizes for guessing which year has the 2nd highest March value.

2016 +1.227 deg C
2017 +1.123 deg C
2002 +0.867 deg C
2010 +0.866 deg C
2015 +0.826 deg C

2016 & 2017 are streets ahead in terms of y-t-d anomaly.


http://berkeleyearth.lbl.gov/auto/Global/Land_and_Ocean_complete.txt

37
Arctic sea ice / Re: The 2017 melting season
« on: April 21, 2017, 10:28:25 AM »
Great chart.  One more idea... fwiw:  If you went 3D and made the z axis the ytd measure.  So the 3D chart grows in depth each day of the year.

Thanks. I've played about a bit with the 3-D idea, but the presentation looks messy.

It seems a bit of a no-brainer to use the Y-axis for the dependent variable (number of days in "lowest 3") and use the X- and Z-axes for each of the independent variables (i.e. the year, and the day/date within year). Swapping the X- & Z-axes obviously radically alters the appearance, but neither looks good.

I've also had a bit of problem trying to implement a stacked display (i.e. showing cumulative lowest, 2nd lowest & 3rd lowest stacked on top of each other) using the 3-D format.

However, I have a cunning plan on how to circumvent this limitation, and will try it out tonight or tomorrow.


Thanks again for the f/b.

38
Arctic sea ice / Re: Arctic Image of the Day
« on: April 20, 2017, 11:38:11 PM »
RE: The Ferryland iceberg photo posted by Bairgon...
... 46 m highest point ...

and

That is just the 10% above the water!

true, while the base under water is most probably wider similar to tree roots, else it's getting ready to topple :-)

If that was sea ice, rather than a chunk of calved glacier, AND ...

if the Lebedev formula for ice growth still had some skill over such an extreme range, then ...

if we said it had an average thickness of ~ 400 metres, then ...

the number of Freezing Degree Days necessary would be approximately 50 million.


That would just require a temperature of -50 degrees Celsius, for about 27 or 28 centuries.

Even I might be prepared to accept a small wager that such a prolonged cool snap is not on the immediate horizon.


39
Arctic sea ice / Re: Home brew AMSR2 extent & area calculation
« on: April 20, 2017, 08:59:54 PM »
Nares has suddenly cleared.

In the post-BREXIT UK, some might see that as another export opportunity.

40
Arctic sea ice / Re: Arctic Image of the Day
« on: April 20, 2017, 08:07:29 PM »
...
A good reminder of how the North Atlantic Drift keeps me warm in England at 52 N. Just once in the extraordinary winter of  62-63 there were ice floes under Brighton pier on the South Coast of England. But not 46 m high.

Ah, the winter of 62/63 - fond memories indeed.  :)

Went head-over-heels outside my house in Glasgow, and ended up with a fractured coccyx.  >:(


... Beautiful, yes, but they keep the water and the air so cold and can ruin the summer. Ice also can play havoc with fishing gear...

Still, there are worse things in this world than a berg made of ice. Imagine waking up one morning, and finding one of these right in the middle of your view...

http://www.bbc.co.uk/news/uk-23584833        :-X


41
Arctic sea ice / Re: IJIS
« on: April 20, 2017, 06:20:12 PM »
IJIS:

13,033,695 km2(April 19, 2017)down 18,800 km2 and 2nd lowest measured for the date.

That minor drop on the 19th takes the 2017 extent to just below that clocked up by April 23rd 2007. Unless the extent actually rises during the next four days, the number of appearances in the "lowest 3 for the date" category for 2017 will rise from 107 to 111 by the 23rd. Simultaneously, the number of appearances in the "lowest 3" for 2007 will drop from 113 to 110.

By that stage, only 2012 and 2016 will have more appearances in the "lowest 3" - with 171 and 312 respectively.

42
Arctic sea ice / Re: Arctic Image of the Day
« on: April 20, 2017, 05:30:57 PM »
... battling sea ice at Twillingate, a couple hundred km north of that spectacular berg in Ferryland. ...

When people describe Twillingate as the "iceberg capital of the world", I assume they are NOT referring to a variety of lettuce.   ;)


43
Consequences / Re: Global Surface Air Temperatures
« on: April 19, 2017, 08:20:57 PM »
NOAA's NCEI March temperature anomaly does not make comfortable reading. Possibly the only surprise is just how much it is ahead of 3rd place.


44
Arctic sea ice / Re: Arctic Image of the Day
« on: April 19, 2017, 10:48:29 AM »
Grounded iceberg near Ferryland, Newfoundland - see http://www.bbc.co.uk/news/world-us-canada-39632047



Ha! I just came onto this thread in order to post that image!

One doesn't see a sight like that very often in South West England these days. (It's been a while since the LGM.)

45
Arctic sea ice / Re: The 2017 melting season
« on: April 17, 2017, 08:29:24 PM »
I know that there are many excellent examples being given on this thread demonstrating in exquisite detail how the melt season is progressing.

At a far more "broad-brush" level, and in response to a suggestion from Tor Bejnar, here is an updated version of a stacked bar chart showing how many "lowest 3 values for the date" are currently logged against the various years.

Here is a quick overview as to how one interprets the chart, and changes from the previous version.

1) Only 2006, 2007, 2010, 2011, 2012, 2015, 2016 and 2017 have meaningful numbers in the "lowest 3" categories, so all other years have been lumped together as "misc".

2) With the (hopefully) obvious exceptions of 2016 and 2017, each of the years has a group of 5 columns.

3) The first column in each year group shows the status at the end of 2015 - for the particular year indicated.

4) The second column shows the status at the end of 2016. The difference between cols 1 and cols 2 for each year therefore equates to the change wrought during 2016.

5) The third column shows the status as at the day/date indicated on the bottom right of the chart. The difference between this and the second column therefore indicates the impact that 2017 has had thus far.

6) The fourth column (marked "locked") indicates the number of "lowest 3" positions that have already been confirmed at the date the chart was generated. (In this case, Day 106, or 16th April)

7) The fifth column (marked "vulnerable") indicates the additional numbers that could hypothetically still be clocked up by December 31st 2017 - as long as there are no changes to positions from the equivalent dates last year. However, every additional day that 2017 has in the "lowest 3" will adversely impact at least one of the previous years.


For example, the first group of 5 relates to 2006. It can be seen that 2017 has already seen slightly more overall losses from the "lowest 3" than experienced in all of 2016. Additionally, although approximately half of the current instances have been "locked" by Day 106, approximately the same number could still be lost during the remainder of the year - i.e. they are vulnerable.

On the other hand, although 2010 lost ground during 2016, it has seen absolutely no change yet during 2017.


I hope this might help with the big picture perspective.


46
Arctic sea ice / Re: The 2017 melting season
« on: April 15, 2017, 04:03:30 PM »
What should be painfully clear is that there is a double whammy going on. Not only is the average maximum value decreasing, but the average loss leading up to the minimum is increasing. As a consequence, the ice remaining at the September minimum is feeling the pinch - from both sides.

Bill - Today I sent a link to Jim's PIOMAS chart that you "plagiarized" to a concerned but non-ice-obsessed neighbor, as I thought it was an excellent graphic.  I titled the email "A classic pincer move," a term from military strategy where you attack an enemy from two flanks simultaneously.

The phrase "classic pincer move" was exactly what went through my mind when I first saw Jim's PIOMAS chart.

47
Arctic sea ice / Re: The 2017 melting season
« on: April 15, 2017, 04:00:56 PM »
@Bill Fothergill
... I assume you allow that I posted those on my facebook profile, else let me know

Magnamentis, apologies for not giving positive confirmation earlier. No real excuse, other than senility.  :P

Please feel free to use as you see fit.

48
Arctic sea ice / Re: IJIS
« on: April 15, 2017, 11:11:56 AM »
@Bill,

That chart of "lowest three" ice extents - does it measure the lowest three so far up to the year in question or does it consider future years too? ie if 2012 set a record for a given day which 2016 subsequently beat, would the day be ranked as a "lowest" or a "second lowest" for 2012?

Paddy,
As David correctly stated above, the stacked bar chart updates as each new data point for 2017 comes in. However, that's only the case for the chart on my computer; the one shown in yesterday's comment is merely a static GIF representation.

Since the data for Day 104 (April 14th) has been added, the number of "lowest" places for 2017 has risen from 55 to 56. However, this introduces a "shuffle effect", with 2016 losing a "lowest" but gaining a "2nd", 2004 losing a "2nd" but gaining a "3rd", and 2007 losing a "3rd".

My intention is to re-post an updated version of the stacked bar chart each time something significant happens. I suspect the next such instance will be when 2017 overtakes 2007 in terms of  total number of appearances in the lowest 3.

49
Arctic sea ice / Re: IJIS
« on: April 15, 2017, 08:58:36 AM »
We read the Arctic Sea Ice Forum here on Pluto too, you know. Earth bigot!

P.S. Pluto is so a planet.

Clyde Tombaugh sends his regards. (Or would, were he still amongst us.)

50
Consequences / Re: Global Surface Air Temperatures
« on: April 14, 2017, 07:30:50 PM »
...
Conclusions: March 2017 will with a 99% likelyhood (my own opinion) be the 2nd warmest on record. I expect the March anomaly from GISS NASA to be somewhere in the range 1,05-1,12oC above the 1951-1980 average.

...
 This number make me believe that a NASA GISS anomaly around 1,07-1,15oC above the average seems quite reasonable.

NASA's Gistemp LOTI has been updated in the last couple of hours. When the March temperatures are ranked, the 6 warmest years are...

2016 +1.28 deg C
2017 +1.12 deg C
2010 +0.92 deg C
2002 +0.91 deg C
2015 +0.90 deg C
2014 +0.77 deg C

Nice one, LMV. I think that can safely be given the accolade of "good call".


Interestingly, and more than a trifle worryingly, is the fact that each of the 4 most recent years features in that short list.

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