It would be great if there was an update to all of these solar predictions. This is all very interesting. I am not a scientist but I do run an ag innovation fund. The future for ag is important to me. Kind regards, Dave Garrett 9/3/2014
Re: comment by Phil Jones
Although I'm not really interested in criticizing and this would be my first comment ever on line. I could not help but notice the comment in the column on the left and I Quote the text "“We have 25 or so years invested in the work. Why should I make the data available to you, when your aim is to try and find something wrong with it.” - Dear Mr. Jones, I would like to point out what is blatantly obvious to even those that have completed only secondary school and to answer your question, peer review is a fundamental basis of good science in the search for answers to questions humanity feels a need to have answered. To cherry pick or deny results and to shy from critique automatically implies questionable scientific method and diminishes credibility. My observations with attempts to hide from critique at a scientific level appear to result in disillusioned (Grumpy)old men who try to cover up their misinterpretation and blinkered vision by suppression of alternative interpretation, until their retirement fund kicks in and they are forgotten. This approach is one of the great problems of humanity that afflicts the world as we know it. Alternatively one might present good arguments supported by solid, credible data and invoke thought full discussion.Either way- Wow what a way to leave your mark!
I have made the following consideration about average temperature. You seem to be in possession of original untouched data which might be suitable for such analysis. I cannot see that you have combined a larger bulk of you data in a way as described below. What do you think? (PS! I might be offline for some periods As I start my holiday tomorrow) Best Regards DHF I wonder: Are all these adjustments really necessary? How many well designed and reliable points of measurement will you need to get a sufficiently accurate yearly average? Or to be more precise: How many points of measurement will you need to get a measured yearly average with sufficiently low standard uncertainty to be able to detect a positive trend trend of 0,015 K/year (1,5 K/century)? I consider the calculated average of a number of temperature readings, performed at a defined number of identified locations, as a well defined measurand. Hence, the standard uncertainty of the average value can then be calculated as the standard deviation of all your measurements divided by the square root of the number of measurements. ( See the open available ISO standard: Guide to the expression of Uncertainty in Measurements). Let us say that you have 1000 temperature measurement stations. which are read 2 times each day, 365 days each year. You will then have 730 000 samples each year. (Let us disregard potential correlation for a moment.) If we assume that 2 standard deviations for the 730 000 samples is 20 K. (This means that 95 % of the samples are within a temperature range of 40 K.) An estimate for the standard uncertainty for the average value of all samples will then be: 2 Standard uncertainties for the average value = 2 Standard deviations for all measurements / (Square root of number of measurements) 20 K / (square root(730 000)) = 20 K / 854 = 0.02 K. This means that a year to year variation in the average temperature that is larger than 0,02 K cannot reasonably be attributed to uncertainty in the determination of the average. This further means that a variation larger than 0,02 K can reasonably be attributed to the intrinsic variation of the measurand. If I further assume that 2 standard deviations of the yearly average temperature measured at a high number of locations is in order of magnitude 0,1 K (Remaining variation of the feature when trends are removed). This means that 95 % of the calculated yearly average temperatures is within the range + 0,1 K to - 0,1 K from the average of all yearly averages (If trends are removed). Since the standard uncertainty of the measured average (0,02 K) is much less than the standard uncertainty of the feature we are studying ( 0,1 K), I regard the uncertainty to be sufficiently low. Hence 1000 locations and 2 daily readings seems to be sufficiently high for the defined purpose. However, the variation of the measurand, yearly average of your temperature measurements, now seems to be too high to be able to see a trend of 0,01 K / year. One approach can then be to calculate the average over several years. The standard uncertainty of the average temperature for a number of years will then be equal to the standard deviation of the yearly average (0,1 K) divided by the square root of number of years. Let us try an averaging period of 16 years. 2 standard uncertainties for the average temperature for a period of 16 years can then be calculated as 0,1 K / (square root(16)) = 0,1 K / 4 = 0.025 K. If you choose an averaging period of 16 years, the standard uncertainty of the measured average value can now be recalculated, as the number of measurements has increased by 16 times to: 16 * 730 000 = 11 680 000. Two standard uncertainties for the average value is now 0,006 K. Hence the number of measurement locations can be reduced. Even if I select as few as 250 measurement points, 2 standard uncertainties will be as low as 0,01 K. Consequently it seems that we should only need in order of magnitude 250 good temperature measurement locations to be able to identify a trend in the average temperature. Adding more temperature measurement locations does not seem to add significant value, as the year to year variation in temperature seems to be intrinsic to the average temperature and not due to lack of measurement locations. Hence the variation cannot be reduced by adding more measurements. So, if the intended use of the data set is to monitor the development of the average temperature, all the operations that are performed on the data sets seems to be a waste of effort. The effort to calculate temperature fields, compensate for urban heat effect and estimate measurements for discontinued locations all seems to be meaningless. What should be done is to throw over board all the questionable and discontinued measurement locations and keep in order of magnitude 250 good temperature measurement stations randomly spread around the world.
Thank you http://www.bu.edu.eg/
Thanks for input, did you/they present Mörner with this and what was his response to that critique? Joanne Nova asked Mörner for me if my illustrations and points are useful (in 2012) and he answered that my way of presenting things where correct. Therefore I would like to see Mörners response to your link, can you provide this? Or has there been no respone or comments from Mörner on this? I need both sides opinion on your informations before I consider including it. And what is your name? Why do you not tell who you are? Most important: In your own words what is exactly the problems with mörners data that I show, what is the essence in the critique? K.R. Frank
Thank you for your input, very relevant! I have been offline until just recently and I first see the comment now. Where did you take the IMO data from, do you have a link? And i cant see your name etc. So for now you are just "Unknown" K.R. Frank
An aknowledgement would be nice.
Did you see my earlier comment? I don't know. If you replied with "noted", I'd know. Is that too much to ask?
Comparisons of individual stations used by GISS to IMO originals
Sources given in the comments section. Stykkisholmur, Iceland https://www.flickr.com/photos/7360644@N07/11244518635/in/photostream/ Keflavik, Iceland https://www.flickr.com/photos/7360644@N07/11244423904/in/photostream/ Akureyri, Iceland https://www.flickr.com/photos/7360644@N07/11244417413/in/photostream/ Teigarhorn, Iceland https://www.flickr.com/photos/7360644@N07/11244199504/in/photostream/ Holar Hornafirdi, Iceland https://www.flickr.com/photos/7360644@N07/11243965324/in/photostream/ Grimsey is more complicated because some of the data has been shifted by 5 years in some datasets (probably through the WMO). https://www.flickr.com/photos/7360644@N07/11243544765/in/photostream/ https://www.flickr.com/photos/7360644@N07/11243544705/in/photostream/
Damming evidence of fraught...
You have missed at link...
R.S. Nerema, b, Corresponding Author Contact Information, E-mail The Corresponding Author, A. Cazenavec, D.P. Chambersd, L.L. Fue, E.W. Leuliettea and G.T. Mitchumf We feel compelled to respond to the recent article by Mörner (2004) because he makes several major errors in his analysis, and as a result completely misinterprets the record of sea level change from the TOPEX/Poseidon (T/P) satellite altimeter mission. One major criticism we have with the paper is that Mörner does not include a single reference to any altimeter study, all of which refute his claim that there is no apparent change in global mean sea level (GMSL) [see Cazenave and Nerem, (2004) for a summary]. The consensus of all other researchers looking at the T/P and Jason data is that GMSL has been rising at a rate of 3.0 mm/year (Fig. 1) over the last 13 years (3.3 mm/year when corrected for the effects of glacial isostatic adjustment (Tamisiea et al., 2005)). Mörner gives no details for the source of the data or processing strategy he used to produce Fig. 2, other than to say it is based on “raw data”. Because the details of the analysis are not presented in his paper, we are left to speculate on how this result could have been obtained, based on our years of experience as members of the T/P and Jason-1 Science Working Team. Mörner was apparently oblivious to the corrections that must be made to the “raw” altimeter data in order to make correct use of the data. As with any satellite data set, calibration and validation of the data must be performed after launch to determine if there are any instrumental errors, find the source of those errors, and evaluate their behavior over time. Satellite altimetry is somewhat unique in that many adjustments must be made to the raw range measurements to account for atmospheric delays (ionosphere, troposphere), ocean tides, variations in wave height (which can bias how the altimeter measures sea level), and a variety of other effects. In addition, the sea level measurements can be affected by the method used to process the altimeter waveforms, and by the techniques and data used to compute the orbit of the satellite. Early releases of the satellite Geophysical Data Records (GDRs) often contain errors in the raw measurements, the measurement corrections, and the orbit estimates that are later corrected through an on-going calibration/validation process defined by the T/P and Jason Science Working Team. The original release of the T/P GDRs (as well as some subsequent re-releases) contained several errors that directly affect GMSL change. Based on our experience with these issues, and the shape of Fig. 2 in Mörner3s paper, we believe that he used the original release of the T/P GDRs with no attempt to correct for two significant errors. One of the errors is caused by a drift in the TOPEX Microwave Radiometer (TMR). It was first observed in sea level via a comparison to tide gauges (Chambers et al., 1998; Mitchum, 1998), and was verified to be caused by the TMR via comparisons to other orbiting microwave radiometers and radiosondes (Keihm et al., 2000). It caused a drift of nearly −1.2 mm/year in measured GMSL until early 1998, and then a bias of −5 mm. A second major error was introduced when the redundant TOPEX altimeter was turned on in early 1999 due to degradation in the original instrument (Chambers et al., 2003). Since the electronics of the redundant altimeter were different, it caused an apparent bias in the GMSL measurement related to the Sea State Bias (SSB). The sense of the bias was such to cause an incorrect sudden drop in GMSL from the end of 1998 to the beginning of 1999 of nearly 10 mm. This drop is apparent in Fig. 2 of Mörner’s paper (and in comparison to tide gauge data (Mitchum, 2000)). This error is removed when an updated SSB model is applied (Chambers et al., 2003). Data with these corrections applied are available from both the U.S. and French processing centers, as well as products to correct the original GDRs. When care is taken to make these corrections, the rate of sea level change over the entire T/P mission is 3.0± 0.4 mm/year (http://sealevel.colorado.edu), 3.3 mm/year when corrected for the change in ocean volume due to glacial isostatic adjustment (Tamisiea et al., 2005). In light of this, the statement by Mörner that “This means that this data set does not record any general trend (rising or falling) in sea level, just variability around zero plus the temporary ENSO perturbations” is completely false and is based on his erroneous data processing. Mörner’s paper completely misrepresents the results from the T/P mission, and does discredit to the tremendous amount of work that has been expended by the Science Working Team to create a precise, validated, and calibrated sea level data set suitable for studies of climate variations. Finally, Mörner ignores substantial other oceanographic (e.g. Levitus et al., 2001; Antonov et al., 2002;...
Huang et al
I find the question of whether Huang 97 or 2008 more accurately reflects reality fascinating. Have they published anything since 2008 that would shed more light on this ? That seems more or less legit ?
Peter Sawyer still owes me $1000 after the gold futures investment that he encouraged his subscribers to invest in, didnt work out too well. He said that he sold out of it and that a 10% loss was incurred..however he only ever returned 30% of my money and kept the rest for himself in spite of my numerous polite requests for it. Therefore I dont think anything of his reports . He has no credibility after what he did to a loyal subscriber at the time....how many others got stung I wonder
Did you read the Paper "Strong Alpine glacier melt in the 1940s due to enhanced solar radiation"?
You didn’t read the paper, did you? In “Strong Alpine glacier melt in the 1940s due to enhanced solar radiation” is stated: “Between 1960 and 1980 high cloudiness, low global radiation and low air temperatures in the European Alps [Auer et al., 2007] are in line with strongly reduced glacier melt rates (Figure 3), resulting in a short period of balanced mass budget of mountain glaciers worldwide [Kaser et al.,2006]. The enhanced greenhouse effect of terrestrial radiation and the brightening of solar radiation since the early 1980s induced higher air temperatures [Wild et al., 2004; Philipona et al. , 2009] and increasing snow and ice melt over the last decades approaching the maximum of the 1940s (Figure 3a).” It is clearly shown in the paper, that alpine galciers are melting as fast as they were in the 1940s although the shortwave Radiation input is on an average 7% lower in the 2000s than in the 1940s. Astonishing how you state “Glaciers have a complicated life. But if glaiciers are in fact used to determine global warming, there is nothing in the retreat speeds indicating that is should be warmer today than 1940.” If you read eh paper you obviously missed the point Ohmura et al. made.
"The urban areas are too small to have any impact on global warming. "
If the thermometers ARE IN THE CITIES then its the city temperature that counts. Is it that hard to understand?? /Frank
It make no sence about UHI
It's amazing that you can repeat the nonsense about UHI. The science of UHI and global warming has been settled for at long time. The urban areas are too small to have any impact on global warming. In addition, the rate of increase of temperature in the cities and rural areas are the same. It is possible that in the future we may see an effect, when urban areas are growing significantly with the earth's population growth.
Hi There - i did not get your name, but youare very welcome to email me concerning the visit to the Australian National libray. I will giver you some advise etc. Then, the Adelaide back to 1800: I dont remember having used data that old, but my data source is GHCN V2 raw for RUTI: Australia. Actually its not that rare that official data sources of temperature data seems to stitch datasets rather "freshly"... K.R. Frank
TO Mi Cro
Thanks a lot for the kind words, i have checked out your site and it looks very cool indeed. Keep up the good work !! K.R. Frank
Ruti - Adelaide data
Very interesting work you are doing, and it has once again peaked my interest. Having looked at the various Adelaide temperature data sets, I was curious as to where you located the "Adelaide Airport" data, dating back to the late 1800's. Could be wrong, but I dont think we had need of an airport before we had aeroplanes! So what is the data you are using? I am thinking of taking up your challenge to visit our central library and check out some of the original manual records. Has some one already done this that has been in contact with you yet?
Hi Frank, Your article was just pointed out to me, excellent work! I've been working with NCDC's Global Summary of Days data set, and have found that when you use their adjusted data, but look at the day over day changes on a station by station basis, there's no warming trend. I have a number of articles I've put together, the latest is below, you might find some of it interesting. You can contact my by clicking on my name there, and then emailing me. Good Luck with your work! http://www.science20.com/virtual_worlds/blog/global_warming_really_recovery_regional_cooling-121820
It is difficult to understand what the result af all this work is..
No matter how much work Frank Lanser has done, something is missing. No links to data are shown. Therefore data can’t be read in order to control the graphs and the related conclusions. It is virtually certain that misunderstanding and misinterpretation is always present in an analysis. When a link data is missing there will be a lack of credibility. Climate skeptics have repeatedly accused climate scientists not make data available to the public. When they publish something themselves, there is no link to the data they have used. That's what you call hypocrisy! What is the conclusion this analysis?
Is there a way to subscribe to new posts to your site via RSS?
Dear Peter Azlac!!
I have not been working with this site for a very long time and so I first see your comment now. First of all, thankyou very much for refering to My work in many places. You suggest that i use an already known approach to devide geographical areas when estimating temperature trends for regions. I started out doing so (see RUTI South Africa) but i fast came to the conclusion that temperature trends simply dictate that areas should be different than in already known works. BUT! in fact, the concept of having an area defined as being in shelter of ocean air is actually used here and there. I have seen it in a Danish writing from 1945 and in an East German Writing from 1964 and more. I simply need areas of similar temperature trends to be able to remove outliers, see wrong adjustments etcetcetc. And try perhaps to read the end of the conclusion "Original Temperatures: Discussion and conclusion". I hope you will check out the new "Original Temperatures" writings and see if you can follow why I do as I do? K.R. Frank , and again thankyou so much
Ruti and Climate Zones
Hi Frank I should have logged in. Unknown is peter azlac
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|Hi Murray!||By Frank Lansner on 23rd February, 2011 at 12:30:33|
|You write: "I was astonished by your zoom analysis of the DMI summer temperature trend."
Well, I honestly was surpriced myself, and I really did the closer look because i was scientifically interested: How can temperatures 80-90N decline while the general Arctic showed less and less ice?
For one thing, this also supports, that the melting came from below, a warmer Arctic AMO current pushing slightly warmer water under the ice? So what ever causes the AMO to warm appears responsible?
In addition, winds around year 2010-2008 did change to push more ice out of the arctic - but also had the effect of compressing ice North of GreenLand/Canada areas - which includes most of 80N-90N.
So a compressing of ice in 80N-90N might actually diminish the smaller areas occuring with open waters 80N-90N and thereby really explain why temperatures have declined 80-90N.
One of the most important results herea are of course how completely useless the GISS REEEED color 80N-90N rising temperatures in summer apperas. The DMI data (ERA40 etc) clearly show GISS projection over oceans to be crap. So why do GISS use this?? Well it makes a superbe red color in the top of their global warming illustrations....
|Arctic melt season cooling||By Unknown on 22nd February, 2011 at 22:19:22|
|I was astonished by your zoom analysis of the DMI summer temperature trend. I have scanned those annual curves n+1 times and never noticed that, because of the scale I guess. Or maybe it's that you are more observant. Anyway, the cooling starts about 1993, which is just after the peak of solar cycle 22. The first bit of cooling could be consistent with the downside of the 11 year solar cycle. But then we have a much less active cycle 23, and a quiescent cycle 24. Quite probably more cloudy days, a la Svensmark, and thus summer cooling. We see some sign of global SST cooling starting 2003, but for sure after 2005. Long delay time to see the solar effect in SST, and then longer to transport the cooler water to the Arctic, and we get the ice minimum in 2007, 14 years after the cooling start in 1993 that shows up in Arctic summer temperature. WOW! You may have found the "canary in the coal mine". Murray|
|Various||By Unknown on 22nd February, 2011 at 21:51:18|
|Frank, in the left sidebar you have links to UAH,RSS,HadCRUT3, NCDC,GISS etc. The curve the links take you to for RSS, HadCRUT3 and NCDC is the same curve.
CO2 global warming theory postulates that warming will be greatest at night, in winter and at high latitudes. Probably the postulate applies to warming regardless of the driver. For sure DMI shows far greater variation in winter. Average warming for high latitudes is the average of little or no change in summer, and substantially less cold in winter, but still much to cold to melt anything. Similarly global average comes from little or no change in the tropics, and large change, mainly less cold, at high latitudes.
I think the reason the Arctic is near the same in the 2000s as in the late 1930s is because both periods were near the peak of the 60 year climate cycle. In fact, using your analyses, the cooling ca 1944-1976 was near o.4 degrees C. I can just about justify anything from 0.35 to 0.45 degrees, depending on which of your curves to use. It is very likely that real warming, after correcting for all warming biases, from 1976 to ca 2006 was =< 0.4 degrees. Most stations north of 67, after allowance for UHI for some of them, have the highest warm years in the late 1930s, although there are a few that have the warmest cold years in the 2000s. The decade 1998-2008 may have been a bit warmer than the decade 1934-1944, but again, if corrected for all warming biases, I doubt that it would be. Biases like new instruments, new airports, and missing minus signs are very important in the region north of 67.
For more on climate cycles see my blog at http://www.agwnot.blogspot.com/ Nov 16 and Jan 23 posts.
Great source of temp series here
|Peter Sawyer, Australia send this letter||By Unknown on 13th February, 2010 at 16:20:29|
|Peter Sawyer, Australia send me the e-mail below. His attached article is published as "Skeptics" by Peter sawyer.
Congratulations on your website - most fitting name I must say.
I've only just started to work my way through, but so far it is looking
However, as a professional writer for some thirty years, can I be so
bold as to say I think you are making the same fundamental error that
all the other so-called skeptic sites are making?
Not in the "science" itself, which I am sure is spot on, but in the
actual language used.
I note you introduce yourselves as "skeptics or realists", and that is
at least a step in the right direction - further than any of the other
"skeptic" sites have gone.
But there are very good reasons why you should stick solely to being
realists, and stop using the term "skeptic" altogether.
There are other, equally important words that must be avoided at all
costs, and yet others that must be hammered home at every opportunity.
In the hope of enlightening people on the importance of the words used,
I have written an essay which is attached.
I send you a copy for you to use as you see fit - either as an article,
or just for your own edification.
Peter Sawyer - Australia