Yesterday NOAA announced with much fanfare that:
The world’s ocean surface temperature was the warmest for any August on record, and the warmest on record averaged for any June-August (Northern Hemisphere summer/Southern Hemisphere winter) season according to NOAA’s National Climatic Data Center in Asheville, N.C. The preliminary analysis is based on records dating back to 1880.
Besides the UAH data for August I cited, Bob Tisdale shows that some other datasets don’t agree with NOAA’s conclusion. – Anthony
Record Sea Surface Temperatures Are Only In NOAA ERSST.v3b Dataset
Guest post by Bob Tisdale
The NOAA press release claims the August Global Sea Surface Temperature (SST) was the warmest on record.
The record ERSST.v3b SST for August can be seen in Figure 1.
http://i32.tinypic.com/2jaiydh.png
Figure 1
And of course SST anomalies, Figure 2, were also at record levels in August 2009.
http://i28.tinypic.com/ive0y1.png
Figure 2
RECORD NOT CONFIRMED BY NOAA SATELLITE SST DATA
August 2009 SST, Figure 3, and SST anomalies, Figure 4, for the NOAA satellite-based OI.v2 SST dataset were not records. NOAA writes about the Optimum Interpolation (OI.v2) data, “The optimum interpolation (OI) sea surface temperature (SST) analysis is produced weekly on a one-degree grid. The analysis uses in situ and satellite SST’s plus SST’s simulated by sea-ice cover. Before the analysis is computed, THE SATELLITE DATA IS ADJUSTED FOR BIASES using the method of Reynolds (1988) and Reynolds and Marsico (1993).” [Emphasis added.]
http://www.cdc.noaa.gov/data/gridded/data.noaa.oisst.v2.html
http://i29.tinypic.com/2zgi8n7.png
Figure 3
############
http://i31.tinypic.com/ajp9ap.png
Figure 4
NOAA does not use satellite data in its ERSST.v3b SST dataset. However, when NOAA originally released the ERSST.v3b dataset in 2008, they included satellite data to supplement the buoy- and ship-based data. This was discussed in my post “Recent Differences Between GISS and NCDC SST Anomaly Data And A Look At The Multiple NCDC SST Datasets” and repeated here:
In “Improvements to NOAA’s Historical Merged Land-Ocean Surface Temperature Analysis (1880-2006)”, Smith et al note the use of satellite data for ERSST.v3 data in their abstract, “Beginning in 1985, improvements are due to the inclusion of bias-adjusted satellite data.” That’s a positive description. They further proclaim, “Of the improvements, the two that have the greatest influence on global averages are better tuning of the reconstruction method and inclusion of bias adjusted satellite data since 1985.” In fact there is a whole subsection in the paper about the satellite adjustments.
But the satellite data was removed because it was felt the satellite data caused a downward bias. Reynolds, Smith, and Liu write in a November 14, 2008 attachment to their main ERSST.v3b webpage, “In the ERSST version 3 on this web page WE HAVE REMOVED SATELLITE DATA from ERSST and the merged product. The addition of satellite data caused problems for many of our users. Although, the satellite data were corrected with respect to the in situ data as described in reprint, there was a residual cold bias that remained as shown in Figure 4 there. The bias was strongest in the middle and high latitude Southern Hemisphere where in situ data are sparse. THE RESIDUAL BIAS LED TO A MODEST DECREASE IN THE GLOBAL WARMING TREND AND MODIFIED GLOBAL ANNUAL TEMPERATURE RANKINGS.” [Emphasis added.]
The link for that quote is here:http://www.ncdc.noaa.gov/oa/climate/research/sst/papers/merged-product-v3.pdf
Note that the “merged product” referenced above is their ERSST.v3b-based land plus sea surface temperature data.
RECORD NOT CONFIRMED BY ANOTHER SHIP- AND BUOY-BASED SST ANOMALY DATASET
The Hadley Centre’s HADSST2 does not show record SST anomalies for July, August, or for the Summer of 2009. Far from it. Refer to Figure 5. The Hadley Centre uses different techniques to smooth and infill missing data. The differences between the Hadley Centre and NOAA methodologies are explained in the NOAA paper about the ERSST.v3b data, “Improvements to NOAA’s Historical Merged Land-Ocean Surface Temperature Analysis (1880-2006)”.
http://i27.tinypic.com/kbuets.png
Figure 5
CLOSING
It appears that the methods used by NOAA to calculate Global SST in their ERSST.v3b dataset and the removal of the satellite data from those calculations created an upward bias.
SOURCES
NOAA’s ERSST.v3b SST anomaly data is available here:
ftp://eclipse.ncdc.noaa.gov/pub/ersstv3b/pdo/aravg.mon.ocean.90S.90N.asc
NOAA’s ERSST.v3b SST data was downloaded from the KNMI Climate Explorer:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
NOAA’s OI.v2 SST and SST anomaly data is available through their NOMADS website:
http://nomad3.ncep.noaa.gov/cgi-bin/pdisp_sst.sh?lite=
THE HADSST2 SST anomaly data is listed in the second column in the following webpage. The other columns list the uncertainty ranges for measurement and grid box sampling, for coverage, for bias, and for the combination of those uncertainties:
http://hadobs.metoffice.com/hadsst2/diagnostics/global/nh+sh/monthly
UPDATE
While doing a visual check of the sources against the graphs, I noticed a difference between the SST anomaly data presented by NOAA for the same dataset. I’m noting it in case someone else spot checks the graphs. The Monthly Global Ocean Temperature Anomalies (degrees C) uses 1901 to 2000 as base years, but the ERSST.v3b data uses 1971 to 2000. Confirmation here:
http://www.ncdc.noaa.gov/oa/climate/research/sst/ersstv3.php
For those who want to split hairs, the difference in the base years changes the rankings of SST anomalies, Figure 6. But it has no impact on the SST data rankings.
http://i30.tinypic.com/5y6xcx.png
Figure 6
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i was cooking tea tonight . I put some fat into my frying pan put the pan on the element truned the power on .After about 3min the fat started to melt. I turned off the power after 6min and the fat still was melting . It was about 30min after i turn the power off that the fat stoped melting and started to harden again.It was back to it normal state in about 70min .
So may be after a time when the sun was giving of more heat. That it has gone less active and we are seeing as it were the fat still melting . And say 7years later the sea temps get back to normal?. ( 6min of xtra heat. then power off takes 70min to get back to normal)
Allan M R MacRae (17:47:32) :
First, let me say that I am a climate skeptic.
Let us put aside whether August 2009 is a SST record or not. I doubt that it is, but no matter.
Is it “almost an SST record” after all the relevent data is included?
Whether it is a rcord or not, there is little doubt SST is on the warm side – much warmer than the ‘recent long term’ average,
If so, is this surprising given the relatively weak El Nino in August 2009?
Not particularly.
What will happen as El Nino strenghens, as is predicted by NOAA?
It will get warmer – but I don’t think it will strenghten too much.
Is this warm SST surprising, considering the quiet Sun?
Not for me as I don’t believe fluctuations in the sun’s activity have much effect on the earth’s temperature. We’re a long way into this minimum and there’s been no discernible change. Peak activity was in the early 1990s. SC23 was nothing to shout about yet the warmest years have all been recorded during that cycle.
These are honest questions for discussion, if there is any interest.
When do we expect SST’s to start falling again?
Apart from ENSO, they might respond to internal ocean oscillations such as PDO, AMO, NAO or whatever but there’s no obvious signal as yet. Following the 1940s PDO shift
Corrections to previous post (I hit the submit early)
“rcord” should be “record”
“strenghten” should be “strengthen”
The last line, i.e. “Following the 1940s PDO shift” should read
Following the 1940s PDO shift the temperatures dropped fairly quickly. By 1951, most of the cooling had already taken place. We need to face up to the fact that a (possible) CO2 signal may reveal itself in the coming years.
Look at the UAH data from Dr. Spencer, nothing alarming there. http://www.drroyspencer.com/
Look at the UNISYS SST data, it looks fairly normal: http://weather.unisys.com/surface/sst_anom.html
Minor warming of .15C since 1979 from UAH but of course this is satellite based and unused by the BIASED scientists at NOAA, and that is the only way to explain their exclusion of data that shows a “cooling bias”, because they are biased against cooling.
However people still get alarmed even if there is minor warming, as if the earth is supposed stay static year after year, century after century. AGW skeptics admit we are warming, but we choose to stay focused on natural global factors rather than blaming man. The CO2=heating crowd does not want to understand that our planet had much higher levels (+1000ppm) of CO2 in the past and the earth did not burn up, there is no corellation to heat. People also dont realise that we have had polar ice caps for about 20% of the planets history, instead they are ready to panic when the icecaps go into their normal seasonal melt. This realease by NOAA is just fuel ahead of the upcoming Copenhagen conference and to support the presidents speech next Tuesday. They have an agenda.
And the fact that people wait breathlessly for the next release of 30 days worth of temperature data shows they have no concept of the age of our planet and the relative significance of 30 days, 30 years or even 3,000 years.
I hope you don’t mind Anthony. I posted this in an earlier thread but I see you have moved on.
From the NOAA press release, just in time for Copenhagen.
Expect more research corruption and spin as the Copenhagen free loaders convention draws near.
What the NOAA data distorters didn’t want you to see.
Only if you remove this.
http://i599.photobucket.com/albums/tt74/MartinGAtkins/UAH-Jun2Aug.jpg
Ditto.
http://i599.photobucket.com/albums/tt74/MartinGAtkins/UAH-Aug.jpg
Mark: Regarding your 02:19:58 comment, let me switch topics to Ocean Heat Content (OHC) for the tropcal Pacific to illustrate a point. The following is a comparison graph of the tropical Pacific OHC (from the Levitus et al 2009 dataset) and NINO3.4 SST anomalies. I’m using the latter to illustrate the timing of El Nino-Southern Oscillation (ENSO) events.
http://i25.tinypic.com/wrz71x.png
The graph is from this post:
http://bobtisdale.blogspot.com/2009/09/enso-dominates-nodc-ocean-heat-content.html
The major swings in OHC in the graph are primarily responses to El Nino events, during which the tropical Pacific discharges heat, and La Nina events, when the tropical Pacific recharges. There is also a recharging of the western tropical Pacific during the El Nino, and this occurs while the eastern tropical Pacific is discharging heat. The recharging occurs due to shifts in cloud cover, allowing more downward shortwave radiation (visible light) to enter the tropical Pacific ocean.
An example: Those swings in downward shortwave radiation from shifts in cloud cover can be as high as 25 watts/sq meter. Now, I don’t know how much of the 11-year cycle in Total Solar Irradiance (TSI) is made up of visible light, but those variations in TSI are only 1 watt/sq meter.
Also, if you were to examine the other subsets in the linked post, you can see how El Nino events shift heat around the nearby oceans, causing step changes.
John Finn: “We’re a long way into this minimum and there’s been no discernible change. Peak activity was in the early 1990s. SC23 was nothing to shout about yet the warmest years have all been recorded during that cycle.”
=============================================
As another post alluded to in it’s discussion of melting fat, the climate doesn’t have an instaneous response to solar activity levels. Another key factor is the DURATION of activity peaks and valleys, not just their magnitude. If you look at cosmic ray levels (as modulated by solar activity and as proposed by Svensmark as a key driver of climate), it is interesting to note the peaks and valleys and their duration:
http://tinyurl.com/q2mpkg
What’s interesting is when you track the cumulative difference between the point in time cosmic ray level and the average. If Svensmark is right, you would expect temperatures to be higher as the inverse of the cumulative difference increases (more rays, more clouds, cooler earth). Well looking at the results (plotted from the start of a posttive trend in late 1966):
http://www.geocities.com/mcmgk/Cumulative_CR_Inverse.jpg
this is what you get:
– You’d expect temperatures would have peaked in the early 1990’s which just might have happened had it not been for Pinatubo.
– Then you get another peak through the early to mid 2000’s before you’d expect temperatures to start dropping off over the last couple of years (which they’ve done)
Of course there are other factors in play (ocean thermal lag, PDO/AMO, El Nino’s and La Nina’s) but the bottom line suggests that focusing on a solar peak in the early 1990’s is the wrong perspective.
Given that CR levels are still at low levels not seen since the Oulo record began, I would expect more cooling once the current El Nino fades. After all we hit a UAH anomaly of zero in June before the El Nino kicked in!
Interesting looking at the graphs and seeing SST peaks at N.H. summer and notches at N.H. winter. I might have guessed it would have been the other way round with so much ocean in the S.H.
“”” Paul Vaughan (23:07:23) :
Re: George E. Smith (18:48:18)
The big dip is NH winter.
You might find figure 1 here interesting:
Each month gets a different average when you change base-periods …so it’s not just one shift of the whole curve, but rather 12 shifts. “””
Thanks for the clarification Paul, and the nifty links; but now I am totally confused.
I thought that instead of recording real temperatures (like in Kelvins or even deg C) that Climatologists like to plot anomalies, being the difference between the actual measured (anomalous) temperature, and the “correct” temperature that it was supposed to be based on the average over some 30 year time period (base period).
If I understand what you seem to be saying now, is that the current temperature is essentially compared to what it was on the corres[ponding day some arbitrary time from the past, and that the “expected” true val;ue changes for each data point, daily, weekly monthly annually or whatever.
Why on earth would anyone suppose that the sequence of actual temperatures from some past era was in any way “normal” ?
No wonder it is impossible to relate any of this temperature data, to thermal energy flows, or air/ocean mass flows that result from real time temperature differences across the planet.
The whole thing sounds to me like an exercise in self flaggelation.
George
And I’m still puzzled; the SH is mostly oceans, so it has the most sea surface area. The earth is further from the sun in SH winter, so SH winters are colder; so if I have more sea surface, and presumably colder sea surface, than in the NH, how could the global average be colder in NH winter ?
That just does not seem to compute to me.
George
Mark (09:01:44) :
John Finn: “We’re a long way into this minimum and there’s been no discernible change. Peak activity was in the early 1990s. SC23 was nothing to shout about yet the warmest years have all been recorded during that cycle.”
=============================================
As another post alluded to in it’s discussion of melting fat, the climate doesn’t have an instaneous response to solar activity levels. Another key factor is the DURATION of activity peaks and valleys, not just their magnitude. If you look at cosmic ray levels (as modulated by solar activity and as proposed by Svensmark as a key driver of climate), it is interesting to note the peaks and valleys and their duration:
I’m not suggesting it should have an instantaneous response – though in some of the solar/climate reconstructions the response is pretty near instantaneous, and in the case of the Dalton Minimum temperatures actually fell before the DM started. The so-called link is iffy.
The Little Ice Age is supposedly due to low solar activity. If true, then the LIA should be clearly defined – except it’s not. There is no firm agreement when it started or when it ended.
http://tinyurl.com/q2mpkg
What’s interesting is when you track the cumulative difference between the point in time cosmic ray level and the average. If Svensmark is right, you would expect temperatures to be higher as the inverse of the cumulative difference increases (more rays, more clouds, cooler earth). Well looking at the results (plotted from the start of a posttive trend in late 1966):
Svensmark appears to be the last throw of the dice. But the trend in GCR is just not there. Ok there has been a slight rise in recent years but the GCR plot looks absolutely nothing like the surface (or satellite) temperature plot.
http://www.geocities.com/mcmgk/Cumulative_CR_Inverse.jpg
this is what you get:
– You’d expect temperatures would have peaked in the early 1990’s which just might have happened had it not been for Pinatubo.
– Then you get another peak through the early to mid 2000’s before you’d expect temperatures to start dropping off over the last couple of years (which they’ve done)
What are the cumulative values as a percentage of the average values. I suspect some selective scaling has gone on here. I’m not convinced your link means very much.
Of course there are other factors in play (ocean thermal lag, PDO/AMO, El Nino’s and La Nina’s) but the bottom line suggests that focusing on a solar peak in the early 1990’s is the wrong perspective.
Given that CR levels are still at low levels not seen since the Oulo record began, I would expect more cooling once the current El Nino fades. After all we hit a UAH anomaly of zero in June before the El Nino kicked in!
An anomaly of zero simply means the average temperature for June in the 1979-1998 period. Also, bear in mind that there appears to be an odd dip in May/June anomalies in the UAH record. John Christy has posted on this issue on WUWT. In any case, any temperature dip was due to the lagged response to the near La Nina conditions a few months earlier.
V Rig (06:28:12) :
Look at the UAH data from Dr. Spencer, nothing alarming there. http://www.drroyspencer.com/
Look at the UNISYS SST data, it looks fairly normal: http://weather.unisys.com/surface/sst_anom.html
Minor warming of .15C since 1979 from UAH
Where does this come from? The least sq trend for UAH since 1979 is ~0.13 deg per decade or a ~0.4 deg total warming over the period of the record.
John Finn (11:03:30) : “the LIA should be clearly defined – except it’s not. There is no firm agreement when it started or when it ended.”
Based on what? The Team? How do you know that the start and end dates of the LIA are “disagreed upon”? What conflicting evidence doesn’t point to anything specific? Sorry, but having read CA I have seen a lot of bunk demolished about the paleoclimate of the last thousand or so years…
George E. Smith (10:10:33) “Why on earth would anyone suppose that the sequence of actual temperatures from some past era was in any way “normal” ?”
They’re trying to ‘remove’ the dominant annual cycle, but in order to do so they are stuck with the untenable assumptions of (a) cyclostationarity and (b) a lack of shared variance with other temporal modes of variation (some of which might be nonstationary &/or conditionally periodic …&/or have periods that are incommensurate with the annual period at the base-period timescale, etc.). Interestingly, they use a different approach to ‘removing’ the diurnal cycle (averaging TMax & TMin instead of subtraction of time-of-day normals).
Cultural conditioning seems to lead to unquestioning acceptance of assumptions. The different methods of ‘removal’ of dominant cycles have consequences for some types of analyses, but in my experience people tend to shape their beliefs about assumptions around what they’ve memorized rather than around conceptual understanding at a fundamental level.
Lucy Skywalker (00:37:21) “lagging […] by ~800 years “
I recommend being careful with that unless you’ve run some really thorough diagnostics on a battery of statistical analyses. (Cautionary note: People in these threads toss around misguided ideas about lags on a regular basis. Bear in mind that most of the lags being discussed have a distribution – and that, furthermore, that distribution is not random.)
Ulric Lyons (10:06:15) “Interesting looking at the graphs and seeing SST peaks at N.H. summer and notches at N.H. winter. I might have guessed it would have been the other way round with so much ocean in the S.H.”
The extreme variability is over land. This relates to water’s high heat-capacity (& thus relative temperature stability). A coastal location is (generally) cool in summer & warm in winter relative to a continental location (i.e. a place inland). NH has a lot of continental monitoring stations (with high variability, particularly in winter) contributing not only to the global average, but also (via circulation) to NH SSTs (which influence NH coastal sites). Keep in mind that Arctic ice works like a continent in this conceptual framework. (During the “big warming” at Spitsbergen ~1920-1940 there was less ice and hence the winters were more maritime and less continental — such dynamics are a huge factor in averages — Arctic ice is the ‘shape-shifting continent’.)
Andrew (12:55:43) :
John Finn (11:03:30) : “the LIA should be clearly defined – except it’s not. There is no firm agreement when it started or when it ended.”
Based on what? The Team? How do you know that the start and end dates of the LIA are “disagreed upon”? What conflicting evidence doesn’t point to anything specific? Sorry, but having read CA I have seen a lot of bunk demolished about the paleoclimate of the last thousand or so years…
Ok – when was it? Define the period for the LIA.
John Finn: I am referring to the below graph John. I did not do a least square fit but after 40 years the temp. anomaly is currently .2C from the average. A straight line fit to the data gives about .15-.2C departure from the average over the time period.
http://www.drroyspencer.com/wp-content/uploads/UAH_LT_1979_thru_Aug_091.jpg
V Rig (18:02:24) :
John Finn: I am referring to the below graph John. I did not do a least square fit but after 40 years the temp. anomaly is currently .2C from the average. A straight line fit to the data gives about .15-.2C departure from the average over the time period.
It’s actually ~30 years – not 40. The current August anomaly is +0.23 above the 1979-1998 average. However, while most of the post-2000 anomalies are ~0.2 above the average, most of the pre-2000 anomalies are below the average. Since the start of the record, there has been an increase in temperatures of between 0.3 and 0.4 deg. UAH state that the decadal trend is ~0.13 deg. You can see this if you scroll down to the bottom of this link
http://vortex.nsstc.uah.edu/data/msu/t2lt/uahncdc.lt
At 0.13 deg per decade the total warming over the 30 year period is 0.39 degrees. GISS, Hadley and RSS show ~0.5 deg warming over the same period.
Paul Vaughan (15:15:38) :
Lucy Skywalker (00:37:21) “lagging […] by ~800 years “
I recommend being careful with that unless you’ve run some really thorough diagnostics on a battery of statistical analyses. (Cautionary note: People in these threads toss around misguided ideas about lags on a regular basis. Bear in mind that most of the lags being discussed have a distribution – and that, furthermore, that distribution is not random.)
I understand that the system is complex, with many lesser cycles that interplay with longer cycles, and that examining the ancient records does not produce a clear fit by displacing CO2 by 800 years, but only a best fit. I put it all here. Can you suggest an improvement of my statement there? I’m not able to do statistical analyses myself but I’d be interested to hear more about your non-random distribution. Anyway, I made the point to emphasise other evidence for thermal inertia effects of the oceans.
Philip_B: You wrote, “I realize I am getting off the seasonal signal in SSTs. Just trying to understand how it all works.”
A good reference page: The NOAA Physical Oceanography Division
Journal Publications webpage has links to more than 90 papers, many of them covering SST variability and the impacts of atmospheric circulation on SST.
http://www.aoml.noaa.gov/phod/docs.php
Without having seen the raw data, it strikes me that each of the graphs is showing the same pattern. Split the graphs into two parts 1981-1997 and 1998-2009. If one draws the single best fit line from 1981 to 2009 one has an upward slope, but if one draws the best fit line for 1981 to 1997 and then from 1998 to 2009 one obtains two horizontal lines.
There is no distinct pattern of warming in either graph but the average in the second graph is significantly (?) higher than in the first. Hence pointing to a step change in 1997/8 rather than to a pattern of consistent warming over the period 1981to 2009.
Bob Tisdale (01:50:54) ” http://www.aoml.noaa.gov/phod/docs.php “
Thanks for that link Bob – found this:
Wang, C.; Lee, S.-K.; & Mechoso, C.R. (2009). Inter-hemispheric influence of the Atlantic warm pool on the Southeastern Pacific. Journal of Climate, in press.
http://www.aoml.noaa.gov/phod/docs/Revision_Wang_etal_2009.pdf
“[…] the effect of the anomalous AWP is to strengthen the regional Hadley-type circulation from the AWP region to the SEP […] may play a role in the initiation of a cool phase of ENSO.”
“Almost of all state-of-the-art coupled ocean-atmosphere models exhibit serious errors in the form of a severe warm bias in simulated SSTs over the SEP […] Many state-of-the-art climate models suffer from serious climate drift in the annual cycle of atmosphere-ocean processes in the AWP region.”
Paul Vaughan (15:30:50) :
Ulric Lyons (10:06:15) “Interesting looking at the graphs and seeing SST peaks at N.H. summer and notches at N.H. winter. I might have guessed it would have been the other way round with so much ocean in the S.H.”
The extreme variability is over land. This relates to water’s high heat-capacity (& thus relative temperature stability). A coastal location is (generally) cool in summer & warm in winter relative to a continental location (i.e. a place inland). NH has a lot of continental monitoring stations (with high variability, particularly in winter) contributing not only to the global average, but also (via circulation) to NH SSTs (which influence NH coastal sites). Keep in mind that Arctic ice works like a continent in this conceptual framework. (During the “big warming” at Spitsbergen ~1920-1940 there was less ice and hence the winters were more maritime and less continental — such dynamics are a huge factor in averages — Arctic ice is the ’shape-shifting continent’.)
Looking at the seasonal variation element in the length of day (LOD) analyses, and the global sea ice record at Cryosphere Today, gives the answer to the graph shape.
I guess the annual shape (big trough, peak, small trough, peak) is not due to temperature variation between north and south, so much as area of ocean exposed by melting ice, which then gains a monthly SST value, and contributes to the long term mean. There is much more southern sea ice than northern to disappear, leaving a large area of cool ocean.
What used to be persistent Arctic ice is now in a grey area as far as gridded temperatures are now concerned – it used to be perhaps thought of as land, and now it is sea, as Paul says – “a shape-shifting continent”, or alternatively, a shape shifting ocean.
Of course, all this seasonal signal disappears when the anomalies are plotted, only the trend and noise remains. The trend will of course change slope when the last few years of low northern sea ice cover SST measurements get included in the comparison baseline period, unless there is a convenient reason to “correct” for diminishing Arctic summertime ice cover.
Re: Lucy Skywalker (01:32:31)
Hi Lucy, My comment is about lags in general. As for the bit about “non-random”: Too many people are eager to cut-corners with untenable assumptions of randomness. (The discipline of statistics needs to keep itself highly-valued – we should all understand their need to market the dogma, which floats on a raft of assumptions and only rests upon a solid foundation in the abstract (i.e. imagination). The stuff can be useful for some purposes, but it isn’t necessarily the best way to make decisions about geophysical phenomena that are not well-understood.) To keep this exchange practical, I suggest using qualifiers like “roughly” & “generally” to deflect potential criticisms.