That’s the title from today’s top entry on the NOAA website. And if that’s not interesting enough, the subtitle reads: “Also Warmest January-April”
The combined global land and ocean surface temperature was the warmest on record for both April and for the period from January-April, according to NOAA. Additionally, last month’s average ocean surface temperature was the warmest on record for any April, and the global land surface temperature was the third warmest on record.
The monthly analysis from NOAA’s National Climatic Data Center, which is based on records going back to 1880, is part of the suite of climate services that NOAA provides government, business and community leaders so they can make informed decisions.
Here’s a summary graph:
Figure 1: January-April Global Hemisphere plot. Source: NOAA.
Looks like a pretty pronounced upward trend to me.
Update: Wed., May 19, 7:30am Pacific
From the National Research Council:
National Research Council, “Advancing the Science of Climate Change,” (National Academies Press).
National Research Council, “Limiting the Magnitude of Climate Change,” (National Academies Press).
National Research Council, “Adapting to the Impacts of Climate Change,” (National Academies Press).
Menzie says, “Looks like a pretty pronounced upward trend to me.”
You just need sufficient oil and coal industry money placed on your left shoulder, so that you can be fair and balanced, Menzie.
This is a very timely subject given the cap and trade bill is about to be ‘debated’ in Congress. I accept the claim that global temperature is trending up, (although the series looks like it could be about to turn over), but the climate research to support the claim that it is man-made seems lacking. There are just too many other candidates besides carbon for the trend driver.
I’m all for reducing pollution in a responsible manner. How many times have you heard claims regarding the number of ‘green jobs’ that the new cap and trade bill will create, without a disclaimer about the number of existing jobs that cap and trade will destroy?
Let the bribing begin…
Coverage of the oceans remains, even today, quite incomplete.
I personally prefer the UAH satellite data: http://wattsupwiththat.com/2010/05/05/uah-global-temperature-anomaly-a-bit-cooler-in-april/
GISS and CRU temps are diverging. GISS has April 1st and CRU has it as 5th. How does that happen since they use essentially the same data? Lotsa answers! But look to the poles for a hint. One ignores them due to lack of data and the other ESTIMATES.
Since Climategate the ?raw? data has been reviewed by independent analysts/statisticians. One serious finding is that there is almost no ?raw? data. It is all processed/adjusted and in/back filled in some way.
Findings on the processing is not conducive to adding confidence in the calculated temps. Since these temps are the basis for many of the studies predicting dire results then shouldn’t those predictions be questioned?
Finally, few actually do not expect temps to be rising. We are coming out of the Little Ice Age. In it we lost millions due to starvation and disease. In nearly every historical analysis of these warm periods in mankind’s history we find the greatest advancement.
So, why are we trying to stop or slow this current round of advancement in the human condition?
Oh, and don’t even get me started on the term “unprecedented”. As far as temps go, not hardly.
We had the hardest (coldest) winter in 23 years, snowiest in 100 years. In Latvia.
… and this would be directly relevant to economic statistics by virtue of what?
Of course it is upward, as it has generally been for about 14,000 years now.
BasicallyBlue,
The cap and trade bill has the potential to create significant changes to consumer and producer behavior.
“Looks like a pretty pronounced upward trend to me.”
Well Menzie, looks like you have about matched the sophistication of the AGW community in statistical analysis – now to become a full-fledged AGW “scientist”, just wrap your conclusion with some supporting judicious backfilling, trimming, censoring, calibration, and rounding…!
Then again, I have to say that at least you have the intellectual honesty to say “it looks like“, something the AGW “scientists” traded to the devil to be able to ride Al Gore’s coattails for their 15 years of fame…..
BasicallyBlue,
Actually, I think you could make an argument that there economics and climate have one important thing in common: both are trying to draw conclusions from data that is sparsely sampled and not suitable for controlled experiments. This observation explains why, in both of those fields, people tend to see in the data confirmation of whatever they believed before they looked at the data. There is enough wiggle room to accommodate virtually any point of view.
Menzie,
Were you unaware of the discrepancy between the GISS data set and other comparable data when you made this post? If so, then are you planning to review the other data sets and the controversy surrounding them to determine whether they affect your conclusions in any way?
If you accept biased data in, what result do you expect. Go read back posts on “Musings of the ChiefIO”, where he does what others have been too lazy to do.
He shows actual raw data from hundreds of actual thermometers in clear plots and performs meaningful analysis.
Curious that northern hemisphere winter has a distinct upslope almost everywhere, but northern spring and fall are flat almost everywhere.
Do some homework.
KevinM has a very interesting source, CiefIo. His blog can be found here: http://chiefio.wordpress.com/
While we are on the subject of AGW, the International Conference on Climate Change, the skeptics, is ongoing in Chicago. ChiefIo has this summary of one of the speaker’s presentation:
Habibullo Abdussamatov
His presentation was titled simply The Sun Dictates the Climate. And that does more or less sum it up.
A wonderful man with a quick broad smile. Yet he can scowl at the assertion that CO2 matters in a most effective way. I took an instant liking to him. There is much that American and British climate scientists can learn from this man. He impressed me as a very old school classical scientist. A Mr. McGuire type (for those whove read my stuff for a while).
IMHO, he has the science exactly right.
The downside? He is stating flat out that we are headed for a Little Ice Age. The solar changes dictate cooling. The ocean mass delays it for about 40 years. And were headed for a lot of cold. There is a 200 year periodic decent of Total Solar Irradiance, that causes a Little Ice Age, and were due. The mechanism he asserts is a 250 km decrease in solar radius and that changes solar interior dynamics and processes. A plot of phase and amplitude for both sun spot number and solar radius showed a near perfect match, with the onset of the solar quieting in 1999.
Not the type to be bashful about making clear predictions (no wussy projections for this man!) he stated flat out the New Little Ice Age begins in 2014. Though with various lags from things such as ocean heat content and climate cooling rates, the depth if the NLIA is not reached until 2042 +/- 11 years for the solar minimum and then 2065 +/- 11 years for the temperature minimum.
CoRev: From your 11/23/09 comments to my 11/16/09 post:
Still waiting for that collapse. In any case, I would say by far the greatest damage done to science has been accomplished by those who reject the consensus of dozens of peer reviewed journal articles in favor of their favorite weblog.
By the way, have you ever tried working with the raw GDP data? Think about that for a bit.
wally: Er, second derivatives matter, too.
Basically Blue: See, among other posts, [1], [2].
Menzie,
Pay no attention to the directions towards chiefio’s analysis – Zeke Hausfather (and Lucia) did an extensive analysis of many of chiefio’s spurious claims here and here – E.M.Smith of chiefio refused to address the demonstration of his flawed analysis and has no credibility even amongst those who can seriously be called skeptics.
If the earth isn’t warming then how do you explain disappearing glaciers in the last 100 years? I’m confused about all of the posts above. Do you deny the earth’s temperatures are increasing?
And a sine wave for values from -1 to +1 radians looks like an upward trend as well. When I first glanced at the graphic, particularly the Southern Hemisphere portion, my immediate reaction was that it looked cyclical with a period of about 160 years. Or such a cycle added to a small linear trend.
I’m not really disputing the AGW hypothesis. But given that the system is complex, with feedback loops of varying temporal duration, any assertion of a simple linear response to a stimulus (eg, increased carbon dioxide levels) makes me nervous.
Michael Cain said: “When I first glanced at the graphic, particularly the Southern Hemisphere portion, my immediate reaction was that it looked cyclical with a period of about 160 years.”
Please explain the physical process(es) that under lie the cycle and why it is 160 years.
I suspect you can’t. You have no insight, just an opinion.
Looks like it’s correlated with the spread of vaccination.
Menzie, I must have hit a home run with that earlier comment to have you research and bring it up today. If you want to measure collapse pick your poison, public opinion, collapse of Copenhagen, Mexico City, the Oz ETS, legal assault on the misdealings of the EU carbon trade market, and collapse of pricing for carbon credits on the Chicago exchange, and the VA AG asking for Dr. M Mann’s records while at UVA?
I do have to admit I overstated the impacts, but they have still been severe. Drs Jones and Mann have been investigated for scientific misconduct. Both have been cleared, but not without the damage already done.
IPCC AR4 has become a howler with its lack of “peer review” materials. ~46% of the references in it were to gray (non-peer reviewed) materials. Some references were from non-science magazine articles.
CAGW has been a two front effort, 1) science based, 2) political. The political front is clearly on a fast downward trend. Some might say near collapse. The science, especially that which makes catastrophic predictions, is seriously and successfully being questioned.
You might not like the results from Climategate, but the release has been a turning point, both positive (data previously hidden for no good scientific reason) is now available and negative (better look behind the curtain of that science).
The warm April was caused by the volcano.
Believer said: “If the earth isn’t warming then…” Look again most skeptics agree that the temps are rising; therefore, some of the glaciers are melting. Most skeptics also agree that CO2 has some warming affect. What is in dispute is the amount of warming is caused by ACO2, and the impacts of the climate feedbacks.
Read more carefully, please. I did not see anyone say it was not warming.
First, it is my understanding that many weather measurement stations are in locations that are were once rural and are gradually becoming urbanized with resultant higher-than-normal temperatures.
Second, I have not seen a climate model that accounts for the slow but gradual cooling of the earth’s core. Some of that heat emerges through the earth’s crust and warms us, but the contribution of that heat is going down as the core cools.
RB, please explain to the less aware here that the first reference to Lucia’s blog was early in the recreation phase, when many were trying to replicate the already used methods. Gridding and applying the not-raw data in fashions similar to the official Govt groups proved they were getting similar results. See this comment from your reference: “Nick Stokes took the initiative last week to add Hadley sea surface temperature (HadSST2) data to his land temp reconstruction to produce the first amateur global temp reconstruction (well, apart from CCCs replication). I followed suit with my model, and we can compare our results to the big three (GISTemp, HadCRUT, and NCDC):”
RB also claims that EM Smith refused to address tha analysis of his flawed… In fact, he did respond in comments. Pulled in part from it he says: “…3) A synopsis of my position: I think there is clearly a pattern of bias in the data against high and cold places. Ive demonstrated that. I take no position on motivation (malice, stupidity, ?) as I cant see inside folks minds. I SPECULATE that this would have a warming bias on the data products, especially of things like GIStemp where anomalies are calculated Basket A to different Basket B as Ive run a benchmark that shows such change can leak through to the anomaly maps. Im WORKING ON proof that it does, or does not (via my own version of an anomaly process as a benchmark against which to measure the raw data and the GIStemp transform and via a hypothesis about how that I cant share as Im hoping to actually publish with it). I have no interest in Hypothetical Cows where someone dreams up some anomaly process or another and says it proves there is no bias. Since that says nothing about what the actual codes run (Jones CRU, GIStemp, NCDC) will do, it is really a waste of time. Its even more of a waste of time to argue about it. Proving there are white swans says nothing about the existence of black swans So I STATE there is bias in the data, but do not know the magnitude nor the QUANTITY that makes it through GIStemp (but that it does get through is demonstrated) and Id much rather spend my time actually answering those questions about how much than arguing as folks speculate they are or are not of a particular size. Once you have a Basket A vs Basket B anomaly process, all sorts of raw data bias can leak through. That GIStemp uses the temperatures for all sorts of things prior to the anomaly step (in-fill / homogenizing / UHI for examples) will make that worse. So my interest is focused on the actual code that is being used for policy decisions, not on the Hypothetical Cows….”
The bottom line in RB’s comment above, either he did not understand the difference in the two approached to analyzing the data, or he is biased. Dunno, don’t care.
No one. I repeat no one, including the big three, but EM Smith has done the due diligence needed to analyze the raw data. His is an unique effort that needs to be replicated to be verified, and probably will be in the near future.
The sea level has fluctuated tremendously over millions of years, and we have historical records of this. Most of the data I have read is that sea levels will rise, but it will be over a 100 years. Over a geological history it has been much higher that it is today (300 metres higher). This compares against the maximum estimated rise of 0.59 metres predicted to 2100 by the IPCC 4th report. My thoughts are that society has much more important priorities that we aren’t taking care of today, like millions that die annually of starvation. And frankly, even if there weren’t humans around, climate change would still be occurring. Is it rationale to try and control the climate given what the cost/benefit is? Would farmers have to trade carbon credits, to offset the amount that cows produce in methane gas?
“The different groups have cooperated in a very friendly way to try to understand different conclusions when they arise,” said Dr. James Hansen, head of NASA’s Goddard Institute for Space Studies, in the same 2007 e-mail thread. Earlier this month, in an updated analysis of the surface temperature data, GISS restated that the separate analyses by the different agencies “are not independent, as they must use much of the same input observations.”
http://www.foxnews.com/scitech/2010/03/30/nasa-data-worse-than-climategate-data/
Yes, the NOAA/NCDC figures show April 2010 as the warmest, globally, over their series since 1880. NASA GISTEMP likewise sees April 2010 as the warmest since 1880.
Someone mentioned a preference for the University of Alabama series, historically often cooler than the other main datasets. But UAH shows April 2010 as just the second-warmest April in their record, which goes back to 1978. And the UAH March 2010 was their warmest March.
I don’t have April yet from the Hadley Center’s HadCRU3v, but their March 2010 is the second-warmest on record, going back to 1850.
Dr. Chin’s original point is well taken, and well supported by a great deal of physical science.
So we’ve established that the coldest third of the year has been predictably warmer from 1980 onwards.
(1) What about the other parts of the year?
(2) Can we consider the possibility that since it was on average colder than the reference temperature from 1880 to 1940 (presumably not due to human activity), that the relative warmness from 1980 to 2010 has also not been due to human activity? Or are we to egocentric to be able to observe a phenomenon without attributing it to our own actions?
CoRev:
“First, it is my understanding that many weather measurement stations are in locations that are were once rural and are gradually becoming urbanized with resultant higher-than-normal temperatures.”
Although urban heat islands (UHI) are real, they’ve been widely studied using many kinds of data, and do not explain the trends seen in the global temperature datasets.
For example: If UHI were affecting the trends then we’d expect urban weather stations to show more warming than rural ones in their region, but they don’t. We’d expect weather-station data to diverge from satellite measurements, but they don’t. We’d expect land areas to follow different trends than nearby sea-surface temperatures, but they don’t. We’d expect calm-night temperatures to show a steeper trend than windy-night temperatures, but they don’t.
There’s much more. Climate science is a very active field, with thousands of smart people doing interesting research — it’s not well reflected by journalistic accounts or the blogosphere.
Menzie: You referred “wally” to take a look at the second derivatives. It’s hopeless. Since you can find GW skeptics who are fond of modeling global temperatures change as an ARIMA (p,2,q) process with constant I think it’s safe to conclude that they don’t have a clue about second derivatives and rates of change within rates of change. And they frequently are the same folks who manage to confuse stock variables and flow variables in economics. They make the same mistake in global warming and think comparing historic temperature levels (a stock variable) is somehow meaningful in the context of a discussion about first and second derivatives (flow variables).
CoRev: Since you agree that global temperatures are increasing, the only outstanding question is whether that increase is natural or manmade. While temperature levels are nowhere near all time highs, the rate of temperature increase is without question unprecedented. So that suggests manmade global warming. But the real kicker is that if there is any uncertainty about the likelihood of a fat-tailed event coming true, as there is with some of the dire global warming predictions, then any risk analysis worth its salt should err on the side of caution. In the case of global warming asking about “most likely” events is wrongheaded; the right question is to ask about fat-tailed events. Would you jump out of an airplane if your parachute would most likely open with a 95 percent confidence?
Menzie wrote:
“Looks like a pretty pronounced upward trend to me.”
Here is a graph for annual values (not the Jan-Apr values shown in the graph at the top of this post) without the distracting red and blue bars.
http://woodfortrees.org/plot/hadcrut3vgl/from:1880/plot/gistemp
It is clear that the uptrend has been ongoing from about 1910, far before CO2 emissions began their precipitous rise.
Some commenter earlier suggested that HadCRU did not show record temperatures. That series is also shown in the graph linked above.
Well, Hi there 2slugs. I see you have the same ole argument, so I won’t bite. But you did add a new nuance. 95% certainty???? Care to define?
Ambler, you did not quote me in your response. that was Steve.
But since you brought up UHI, here goes. UHI has been showing up in records by raising night time lows, especially in Winter. This only appearing in the urban data. When we can get to the raw rural data many stations show no history of a rise at all.
The most amazing impact of adjusting for UHI is that the rural station temps are raised and urban mostly unchanged. Think that has an effect temp averages?
Even some here do not want us to read ChiefIO’s articles, his analysis indicates that much of the warming is an artifact from station changes, equipment changes, site changes infilling, and back filling. Quite bluntly processing errors.
The most interesting process is associated with infilling when there are no stations in an adjoining grid. The sparsest stations are in the far North and the next closest stations are usually south. How do you think the affects average temp calcs?
CoRev: …you did add a new nuance. 95% certainty???? Care to define?
For example, see:
http://www.economics.harvard.edu/faculty/weitzman/files/ExtremeUncertaintyCliCh.pdf
or
http://www.economics.harvard.edu/faculty/weitzman/files/1aMultAddLatest.pdf
And keep in mind the distinction between variability (i.e., randomness around an estimable mean) and uncertainty (i.e., you don’t even know the mean).
CoRev, my apologies for the mis-attributed quote, I’m new at this site.
As for Cheifio’s blogging, I have read a few of his pieces. He appears to confuse absolute temperatures with temperature anomalies (as used by GISTEMP), and also about the relationship between GHCN and NASA.
Do you have recent peer-reviewed papers that support your statements about UHI affecting temperature trends? The ones I’m aware of reach different conclusions.
2slugs asked: “…the only outstanding question is whether that increase is natural or manmade.” My answer is both. We’ve already discussed UHI, there’s also farming practices and other land usage issues which are causing some local climate changes. Where there is a station near by, then those local changes are getting picked up.
Discussing rates of change with this data and their manipulations is too much like going out on the frozen pond in late Oct.
To accept your parachute analogy, it must be accepted as a dangerous situation. I wouldn’t second guess using it if I was sitting on a chair in the gym, which is a better analogy. Find the history where warming has been worse than cooling.
CoRev asks: “The most interesting process is associated with infilling when there are no stations in an adjoining grid. The sparsest stations are in the far North and the next closest stations are usually south. How do you think the affects average temp calcs?”
Gee CoRev, don’t you understand that the measurement isn’t the temperature but the temperature anomaly? It says so right on the graph.
Thus, as long as the method is to always extrapolate for uncovered grids from the closest adjacent grid with a station, there is no bias.
“95% certainty???? Care to define?”
He/she means that the prior probability of the parachute opening is 95%. I don’t know, I thought pretty much everyone already had a pretty good idea what terms like “95% certainty/chance/probability” mean – especially people who act like they understand science and quantitative reasoning – but if not really its your job to go find out, not someone else’s to explain it to you. Nonetheless, maybe I can help by making the example more explicit.
Say somebody is going to roll a 20 sided-die. If it lands on 1-19 – we say it will do so with 95% certainty – I give you a dollar. If it lands on 20, I take all of your possessions and chop your legs off.
By far the most likely outcome, if you take the bet, is that you win a dollar. So, its a good bet, right?
Now let the dollar be the extra 1% annual global GDP growth (or whatever it is) we can enjoy by continuing to leave carbon unpriced. Losing all your possessions = the medium-worst case scenarios for devastation to the biosphere and hence the economy.
Even if we “believers” grant you for the sake of argument that the blogosphere is right and nearly every qualified scientist is wrong, and that AGW (either the W or the A) is a myth, with 95% probability, do you still wanna take that bet?
How badly do you want the dollar?
GregL, now that was funny. Saying: “…the measurement isn’t the temperature but the temperature anomaly? It says so right on the graph.” Calculating the anomaly is from what?
Also extrapolating from the next closest station 1200Km to the south and infilling the other grids also not populated between the stations does what to the data again? I realize you need to have some more info re: the specific station to which I am referring and what it’s calculated impact is. But, don’t make too many assumptions, because one station’s data can create a 3,000 Km red blob on the temp maps.
Hey Frost, thanks for that woodfortrees.org link.
Here’s a plot of sunspot acitivty and GISTemp. Notice how the 2 series diverge around WW2 and then again in the late 1980’s to early 1990’s. By the way, that is the same time that the change from glass to digital thermometers took place.
Here I have replaced the GISTemp, with satellite data for the lower tropics. The deviation is smaller, but still there, so this naive comparison suggests thermometer change does fully account for the deviation that begins in the late 1980s.
http://woodfortrees.org/plot/sidc-ssn/from:1920/normalise/plot/rss/from:1920/normalise
Here’s GISTemp with CO2.
http://woodfortrees.org/plot/esrl-co2/from:1920/normalise/plot/gistemp/from:1920/normalise:600
The real message is that there are lots of other potential explanatory variables in addition to CO2. I have to ask if the science is really settled after looking at the relationship between sunspot acitivty and global temperature.
The true puzzle is why the relationship between the global temperature anomaly and sunspot activity broke down for a period that began in the late 1980’s. CO2 was trending up entire time, so I doubt CO2 was the cause of the deviation.
or is actually
2slugs, from your first reference we find: “Throughout the sections of the paper which follow, I want to state clearly at the outset
that every number and every formulation is simplistically derived, subject to a myriad of
caveats, and open to strong criticisms. This is an unavoidable issue for all aspects of extreme
climate change, because we are extrapolating so far outside the realm of ordinary experience
that we are left mostly with thought-experimental guesstimates and suggestive numerical
examples. The degree of my subjectivity is embarrassing.” and this: “Carbon dioxide is not the only GHG, although it is by far the most important.” And finally, the author concludes: “However, in a highly uncertain situation where we are not really sure which one is the more
plausible of two outcomes with highly asymmetric consequences, I think that the possibility
of catastrophic climate change needs to be taken seriously.”
Point one: This paper is based upon, in his own words: “thought-experimental guesstimates and suggestive numerical examples.” This is too often the case upon the basic research upon which his paper is based.
Point two: There is little real proof, outside of models, that the CO2 is the most important GHG. In fact recent, this past year, peer reviewed documents have shown that H2O, in its various forms, is by far the more important GHG.
Point three: The author started with a belief, “I think that the possibility
of catastrophic climate change needs to be taken seriously.” Then proceeded to support with guesstimates and other subjective data to support it.
Since we have had much dialog in the past, I can assume your beliefs lie very close to his. But, his paper is a prime example of “confirmation bias” and your use or it is also. Relying upon a paper with a science-based foundation is not the basis for seriously perturbing or even destroying our economy.
For everyone here. Why do we insist on taking the perverse interpretation of climate, heating is bad and extreme heating is catastrophic? When our own even recent history shows the inverse. Heating is best, cooling can/has been catastrophic, and there is little evidence that extreme heating has EVER occurred?
GregL, how can you make this statement? “Thus, as long as the method is to always extrapolate for uncovered grids from the closest adjacent grid with a station, there is no bias.”
Extrapolating from warmer southern stations to cooler norther stationless grids, then using that extrapolated data to infill when data is missing in the gridded stations does not induce a warming bias? Menzie is talking about one month’s data in this article, and we are talking of that same level of temp change in historical reference.
My view, bias exists and is almost always on the high side.
The melting in Greenland is accelerating at a rapid pace as I read this morning- the amount of arctic sea ice continues to decline- and the decade 2000-2009 was the warmest on record.
The Free Market crowd- American Enterprise Institute among many other conservative organizations will deny forever- even when Miami, New Orleans are under water- and NYC becomes flooded on a yearly basis.
The deniers cherry pick information from the Oil companies. The deniers also have a very well funded campaign.
The conservative element in the USA as time goes in and the data shows conclusively that the planet is warming- with perhaps calamitous results will still be in denial that their Freedoms are being ‘taken away.
Get real- look at the empirical scientific data- it shows numbers that disprove the deniers.
If the period 2010-2020 is warmer then the last decade- then it seems that warming is taking place- some of it may indeed be natural- but most will have been caused by Co2 in the atmosphere- which by the way is the highest in 300,000 years globally.
An increase this decade of .5 F degrees globally- is predicted by most climate models- if this in fact does happen- we are warming at a rate this is very likely going to cause us deep economic problems-let alone bizarre weather events- invest accordingly- The Insurance companies are- and are unloading policies in areas vulnerable to climate change……
they are listening- others on a political crusade are not.
Ambler, welcome. I’m not sure to what you are referencing in the ChiefIO writings re: absolute temps versus their anomalies. You need to use absolute temps to calculate the anomalies. It is his analysis of the absolute temp raw data that is unique.
As far as UHI peer reviewed docs, I’d prefer to not get into a doc reference discussion. If you are interested do an UHI search at Dr Pielke Sr’s site: http://pielkeclimatesci.wordpress.com/ to see what he thinks is relevant. There are many other sources including google, but a relevance filter as Dr. Pielke is never a bad thing.
A brief explanation of why temperature anomalies are used by climatologists appears in this FAQ from NOAA.
http://www.ncdc.noaa.gov/cmb-faq/anomalies.html
“Why use temperature anomalies (departure from average) and not absolute temperature measurements?
Absolute estimates of global average surface temperature are difficult to compile for several reasons. Some regions have few temperature measurement stations (e.g., the Sahara Desert) and interpolation must be made over large, data-sparse regions. In mountainous areas, most observations come from the inhabited valleys, so the effect of elevation on a region’s average temperature must be considered as well. For example, a summer month over an area may be cooler than average, both at a mountain top and in a nearby valley, but the absolute temperatures will be quite different at the two locations. The use of anomalies in this case will show that temperatures for both locations were below average.
Using reference values computed on smaller [more local] scales over the same time period establishes a baseline from which anomalies are calculated. This effectively normalizes the data so they can be compared and combined to more accurately represent temperature patterns with respect to what is normal for different places within a region.
For these reasons, large-area summaries incorporate anomalies, not the temperature itself. Anomalies more accurately describe climate variability over larger areas than absolute temperatures do, and they give a frame of reference that allows more meaningful comparisons between locations and more accurate calculations of temperature trends.”
Ambler, if your latest is in response to my question, I think you may misunderstand the difference I was trying to identify. ChiefIO is analyzing the raw data and the processing done to it. This is necessary to understand the validity or impacts of the processing steps. And, this is necessary because most of the raw data is missing/lost/ or unavailable, and most of the publicly available data is the already initially processed (in/out filled, extrapolated) versions. I and ChiefIO are not aware of the use of anomalies, but, you must start with the raw data to calculate the anomalies. When that raw data s not available, and there are questions re: bias, then raw/absolute temp data is necessary to determine if and where that bias may be introduced.
I hope you realize that there are at least three different anomaly base periods, each different for the big three.
CoRev:
“I hope you realize that there are at least three different anomaly base periods, each different for the big three.”
Of course. For other purposes I was looking at the ‘big three’ datasets (and UAH, which depends on no weather stations) through March or April 2010 just yesterday — that’s what informed my first post on this thread.
As NOAA explains, the regional-anomalies method is used by climatologists working with weather-station data because it offers a practical way to work around gaps and spatial heterogeneity, such as mountains and valleys (which tend to have quite different absolute temperatures, but correlated temperature anomalies). Satellite and other data support the practice, or it would have been abandoned long ago.
Written by CoRev:
IMHO, he has the science exactly right.
You’re making an opinion on something that one cannot opine. Science is either right or wrong, there’s no opinion about it (and in this case, it’s wrong)
Sorry, this: “I and ChiefIO are not aware of the use of anomalies,…” was supposed to be: I and ChiefIO are not unaware of the use of anomalies,….
Also, calculation of the anomaly is done relatively well down the chain of processes. Furthermore, let’s hope the same processes are used on the anomaly data and as the total set. I assume it is, as it is expected that the data for the anomaly is just pulled after processing from the same data set being analyzed. But, then, it is efforts like ChiefIO’s that is showing the truth for that statement, since for most sources it must be culled from the poorly documented and worse maintained spaghetti processing codes.
dubfan, I had to go back and find that comment: “IMHO, he has the science exactly right.” That quote was from ChiefIO at the ICCC. I sh/could have made it more clear by placing it in quotes instead of just referencing him at the beginning like this: “ChiefIo has this summary of one of the speaker’s presentation:… ”
If you disagree, go on over to his house and make your case. If you do so, state your case with your factual backup, he does not like to get into time consuming opinion discussions.
I do have a question though. To what are you disagreeing? That the Sun drives our climate, the predictions, or ChiefIO’s comment: “IMHO, he has the science exactly right.” Remember, the comment is clearly stated as his opinion.
If you are actually disagreeing with the Sun driving our climate then we would probably devolve into a discussion of what came first the Sun or the atmosphere.
As to the predictions and your comment re: science not being based upon opinions, then I would ask this question: If science is either right or wrong, then why does the CAGW climate science community rely so heavily on the opinion/caim it is settled, all the while the debates are raging? Having a debate shows it to be other than settled.
May 19, 2010
U.S. National Academy of Sciences labels as settled facts that the Earth system is warming and that much of this warming is very likely due to human activities
New report confirms failure to act poses “significant risks”
A strong, credible body of scientific evidence shows that climate change is occurring, is caused largely by human activities, and poses significant risks for a broad range of human and natural systems.
Some scientific conclusions or theories have been so thoroughly examined and tested, and supported by so many independent observations and results, that their likelihood of subsequently being found to be wrong is vanishingly small. Such conclusions and theories are then regarded as settled facts. This is the case for the conclusions that the Earth system is warming and that much of this warming is very likely due to human activities.
Those who continue to attack what are essentially settled facts deserve the label that I and others have been using anti-scientific.
CoRev:
“If you are actually disagreeing with the Sun driving our climate then we would probably devolve into a discussion of what came first the Sun or the atmosphere.”
Was that a straw man?
But upon what do you (or cheifio) base your belief that Abdussamatov “has the science exactly right,” in declaring that the current global warming is entirely due to an increase in solar output? Most of the published research I’ve seen suggests otherwise. For example,
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 114, D14101, 18 PP., 2009
doi:10.1029/2008JD011639
Solar trends and global warming
R. E. Benestad
G. A. Schmidt
“We use a suite of global climate model simulations for the 20th century to assess the contribution of solar forcing to the past trends in the global mean temperature. In particular, we examine how robust different published methodologies are at detecting and attributing solar-related climate change in the presence of intrinsic climate variability and multiple forcings. We demonstrate that naive application of linear analytical methods such as regression gives nonrobust results. We also demonstrate that the methodologies used by Scafetta and West (2005, 2006a, 2006b, 2007, 2008) are not robust to these same factors and that their error bars are significantly larger than reported. Our analysis shows that the most likely contribution from solar forcing a global warming is 7+/-1% for the 20th century and is negligible for warming since 1980.”
BALONEY!!! April was the COLDEST month ever in Palm Springs, CA.in 2010. We’ve been going there every April for over 30 years, and this April it was so COLD, we had to double our cotton clothing, which is all we had to wear. Absolutely FREEZING. It used to be so hot there in April that we would burn our hands on the car door handles.
Anonymous: I see. So you subscribe to the view that the plural of anecdote is data?
BALONEY. This April was the COLDEST month EVER in 30 years we have stayed in Palm Springs that time of year. It was FREEZING — we had to double up on cotton clothes because we had never needed warm clothing in April. It used to be so hot at that time of the year, we burned our hands on the car door handles.
It is getting progressively colder in spring in San Diego, as well.
CoRev said: “Calculating the anomaly is from what?”
This a joke, right? You post all the time on climate, so you must understand this. We are interested in the absolute change and the first and second order changes in temperature. We don’t need to get the “correct” temperature measurement, whatever that may be. We need to know if the tempertaure is changing and by how much and how fast. That’s what a temperature anomaly does. The temperature anomaly keeps all the measurements in the same frame of reference.
Lets say that the framework is 10C off (+ or -). It doesn’t matter because the change from last year to this year is still 0.2C under any starting point. And the first and second order rates of change with respect to time are thus also unaffected.
Come on CoRev, you’re just pulling my leg on this; you can’t not know this stuff with all the research you do on the topic.
There are several issues. I’ll taxonomize as
1. is there global warming? I.e. are mean temps increasing?
1.A. over what time period
2. If so, is it caused by anything humans are doing or is it “just one of those things”?
3. Should we care? I.e. what are the likely consequences and is there anything we can do?
Question 1 seems to be pretty well settled as “yes”, over pretty wide range of answers to 1.A. There are disputes, but they don’t seem to be actual scientific disagreements.
Question 2 is harder, but the answer is “probably yes” since we have some ability to guess at cause and effect. Consensus is “yes” but there are some legitimate reasons to think there is a possibility it’s just one of those things.
Question 3 is harder yet, since we guess much more badly at extrapolations. Jim Manzi (http://corner.nationalreview.com/post/?q=NzRlNzJjZjRkOTg2YzhmZDJmZDgxNzEyNjU5NTI3ZDY=)thinks that known cost of mitigation probably is too high compared to cost of not taking action.
http://monthlyreview.org/080728farley.php
outlines a lot of what is known and not known.
The problem with NOAA is a lack of quality control, lousy data, and analysts who miss obvious errors. If we look at the US data we see no material warming since the 1930s.
http://www.mcculloughsite.net/stingray/photos/temp_adjust.gif
It is also interesting to look at where the claimed ‘warming’ trend really comes from. Here is the artificial signal that NOAA adds to the actual temperature measurements. Here is a look at the difference between the final and original data.
http://www.theclimateconspiracy.com/files/images/2010/01/ts-1.ushcn_anom25_diffs_urb-raw_pg.gif
The US is not alone. We have seen similar ‘adjustments’ in New Zealand and Australia.
http://c3headlines.typepad.com/.a/6a010536b58035970c0120a6db68e0970b-800wi
http://c3headlines.typepad.com/.a/6a010536b58035970c0120a769f018970b-pi
Of course, there are other issues as well. Two years the data from the wrong month was used and produced a significant warming for the Arctic that was missed by the data keepers.
http://www.theregister.co.uk/2008/11/19/nasa_giss_cockup_catalog/print.html
We also saw the same failings earlier this year when the minus signs were missed in the Finnish data and GISS reported a record high for Finland even as Finnish authorities were reporting an unusually cold month. You would think that after the previous stupidity GISS would check March values that were off by 11.8 C.
http://climateaudit.org/2010/04/15/giss-warmest-march-ever-in-finland/
Why is it that you fail to see that the AGW scam has been exposed and is no longer taken seriously by anyone who is able to understand basic science and think rationally?
gregL: You said to CoRev:
This a joke, right? You post all the time on climate, so you must understand this. We are interested in the absolute change and the first and second order changes in temperature. We don’t need to get the “correct” temperature measurement, whatever that may be.
As I said yesterday, many folks on CoRev’s side of the aisle do not understand the difference between stock variables and flow variables. You see this confusion in their writings in both economics and climate change. I’m pretty sure that CoRev does not understand your point because if he did then he would know that this same critique applies to his comments on urban heat islands. CoRev understands heat islands in terms of temperature levels. I blame our school system for weak math skills.
CoRev: A couple of comments:
(1) We all know that water vapor is a very strong GHG, but the reason Weitzman put CO2 front and center is because water vapor’s impact on temperature is derivative in nature. It’s CO2 increases temperature in the first order and this temperature increase has a feedback effect in higher water vapor, which further increases temperature. As I told you before, if you want to model this kind of stuff as a time series model, then you have to set things up as a VAR rather than as a univariate model.
(2) He actually cites methane as the longer run problem if near term temperatures release trapped methane. That’s the real doomsday scenario. But again, what kicks all this off are higher CO2 levels. It’s C02 levels that have to initiate things.
(3) You completely misunderstood Weitzman’s paper. He was not making an argument about the science of climate change, he was making an argument about the right way to view risk under conditions of extreme uncertainty and fat-tailed outcomes. He’s an economist, not a climate scientist. He wasn’t trying to make point estimates, he was trying to explain how extreme uncertainty with unlikely but plausible outcomes that are outside of historical experience cannot be evaluated using conventional cost-benefit approaches that assume thin-tailed distributions and estimable means.
2slugs, Uh huh. We’ve had this discussion many times, and there is no need to redo it here. if your a believer, then believe away. Only time will tell either of us.
Ambler quoted a report which said: “We use a suite of global climate model simulations…” Take a historical look at the quality of the model predictions. As I said before I do not want to get into a dueling papers discussion. There are too many that support nearly every viewpoint.
GregL, what is your problem? Yes, Ii do know what an anomaly is and how to calculate it. Which makes me question your statement: “We don’t need to get the “correct” temperature measurement, whatever that may be. We need to know if the tempertaure is changing and by how much and how fast.”
Have you missed my points about the raw data and the raw data processing introducing bias? If you can not determine what is real and what is bias, then the certitude associated with your calculated for: “how much and how fast.” is unknown. How large are the error bars. Is the rise due to bias? How much and how fast? After we get by those tests we can then analyze it for cause and effect of the remaining temp differences.
I don’t know of any process that makes bad data good. There are many that try to measure the goodness.
Let me try to make this point again. Much of the raw data is not available. But when it is available and reviewed it is more common to find NO WARMING in the rural data associated with the long lived stable (fewest equipment changes, site changes, micro-site changes) sites.
CoRev asks: “Have you missed my points about the raw data and the raw data processing introducing bias?”
You real don’t understand, CoRev. Even if there were bias introduced (and I’m not saying any has), it would have to be monotonically changing bias over the study period to affect the calculated anomaly. You haven’t alleged that let alone produced evidence of it. What you did say was:
“The most interesting process is associated with infilling when there are no stations in an adjoining grid. The sparsest stations are in the far North and the next closest stations are usually south. How do you think the affects average temp calcs?”
Your argument above does not allege increasing bias over time. It certainly doesn’t even show bias of any kind. Since the Earth has a finite surface, any computation that doesn’t include all the surface has bias. And since climate change isn’t uniform over the surface of the Earth, ignoring large parts of the surface does introduce bias that can affect the global temperature anomaly.
Your posts don’t support your conclusions.
CoRev: You aren’t understanding the math here. Whether or not there is bias in the raw data is irrelevant because NOAA only uses the deviations. And by definition the anomalies over the baseline for each new site must sum to zero. If the deviations beyond the baseline period are increasing, this means temps are warming.
As to being a believer, that too is irrelevant to Weitzman’s point. Even if you’re 95% sure that global warming is flat out wrong (and even you aren’t that certain), then that 5% uncertainty is a killer. And surely the risk of global warming is at least as great as was the risk of a real estate collapse in mid-2007. Put another way, the same Fox News folks who today are telling us global warming is a hoax were also telling us that warnings about financial bubbles were just so much far left hoohey. Think fat-tails.
Check out the multiple land temp reconstructions with raw unadjusted unhomogenized data here and see how they correlate well with the adjusted Big Three. (BTW, for the whole world, adjusted GHCN gives a slightly lower trend than GHCN raw). BTW, you can check for land/land-ocean reconstructions in the link in my previous post and see that oceans, with no UHI, and which constitute the majority of earth’s surface have an uptrend as well. Therefore, disbelieve analyses that produce results such as these:
it is more common to find NO WARMING in the rural data
Besides, there are multiple observational lines of evidence showing that the world has indeed warmed, regardless of what you think might be the cause of warming.
2slugs, we have gone over this so many times. Saying this: “Even if you’re 95% sure that global warming is flat out wrong (and even you aren’t that certain), then that 5% uncertainty is a killer.” Is just creating your own straw man and then arguing your side of it.
The difference in beliefs is not that there is no global warming, but the impacts of it. None! None! Of the catastrophic predictions have been proven true. Moreover, there is little history that many of those predictions have ever occurred. But, the real issue is NO, ZERO, ZIP, NADA evidence that those predictions are caused by ACO2 warming.
So being absolutely sure of global warming I come to a completely different conclusion regarding the plausibility of the catastrophic impacts. Fat tails? Not likely.
Fat tails due to devastating impacts to our economy from following a policy based upon this science, I believe is nearly 95%. Why? Look to Europe. Why would we want to make the same mistakes?
As far as the anomaly discussion, I think you have completely misunderstood what I have said. You said: “Whether or not there is bias in the raw data is irrelevant because NOAA only uses the deviations.” I have been saying the raw data is not readily available. The data that is available is processed. This level of data is showing bias.
You also said: “And by definition the anomalies over the baseline for each new site must sum to zero. If the deviations beyond the baseline period are increasing, this means temps are warming.” You misunderstand the meaning of anomaly baseline as used by GISSTemp and NCDC. If there is a new site/station, it by definition is not in the baseline. When stations’ equipment, siting/location, micro-environment, Time of Day collection, dropped data, mis-coded data, even encroaching urban development and the myriad of other abnormalities that make weather data noisy are changed, they or at least most, are not in the anomaly baseline.
Now, I have said that many of these changes to sites are handled in the processing of the data, AND MOST ADD BIAS HIGH. For example, the method used for correcting UHI, and several other common data problems is called homogenization. To correct for UHI some stations need to be adjusted. So in very simplistic terms what the GISS and NCDC do is review the stations’ data within a 600 to 1,200 kilometer circle of an urban area and calculate an adjustment factor. Since many, ~80%, are in urban or near urban areas, that means that the urban stations may be lowered somewhat, but the rural stations are surely raised.
Wait, we forgot the basic tenant of the anomaly process. Was that baseline recalculated in the same way? If it was, why? Many in the baseline are different stations, technologies, methods and certainly rural/urban conditions. From this can you decipher the difference in temps, and with any certainty assign that warming to anything but process?
No! For that we have the models. Models that are so bad that 20+ of them need to be averaged to get an estimate. Models that are currently batting nearly zero when we get outside the 10 year window.
So at what level of certainty can we claim April the Hottest on record? The big three can’t even agree on it, and that is to a large extent due to anomalies.
Every time I read the comments of economists or whatevers, as a physicist and natural scientist I realize why economic theory and prediction and policy advocacy is so whacked.
The evidence for human caused climate change is clear, not because of one data set, raw or highly processed, but from thousands of data sets in multiple areas of the ecology spanning millions of years. While many questions remain, the one explanation that is consistent with all the observations is that human activity has changed the climate, and that the rate of change has increased with the burning of coal and then the added burning of petroleum. But the clearing of forests has gone on for thousands of years and that has changed the climate.
Yes, the climate changes for other reasons, like comet strikes and massive volcanoes, both of which cause rapid climate change measured in decades and centuries. But the other drivers of climate change occur over thousands, tens of thousands, and millions of years. The “little ice age” is climate change from a volcano in the best working theory. For a number of reasons, volcanic activity causes cooling – so with several large volcanoes over the past few decades, why don’t we see cooling? With the sun’s activity at a very low level, why don’t we see cooling? With China and India emitting pollution in the US and Europe levels of the 50s-60s, why none of the cooling seen then? With the solar influx declining as the complex earth-solar orbits change to lower levels, why no cooling?
The evidence for climate change cycles is found in many data sets going back tens and hundreds of thousands and millions of years, with many sources of evidence for the events like volcanoes and comets and orbital change and magnetic poles changing, with theory connecting the climate evidence to the evidence of the forcing events. Those provide the background for the general understanding of climate change, over which we lay the evidence of the human activity driving climate change.
We have evidence for the state of the climate over millions of years, and evidence of events, and explanations for the connections between the two. And what is clear from all the evidence for the past few centuries and especially the past few decades is that man is forcing climate change faster than any other events but the catastrophic volcanoes and comet strikes.
That economists throw up their hands when faced with changes in the economy with a number of events occurring and explain them with “theory” like “big government caused it” and offer solutions like “cut taxes” with “theory” backed by no evidence, claiming it is too difficult to collect sufficient economic data over the past century, or the past half century, or the past decade, just astounds me.
But economists seem to think the natural scientists are as lazy as economists when it comes to research, data collection, and analysis. And no where is this illustrated when economists deny the evidence for human driven climate change.
CoRev said: “I have been saying the raw data is not readily available. The data that is available is processed. This level of data is showing bias.”
The raw data is produced (and owned) by a different entity than the ones that do the analysis. GISS (for example) produces global/land-ocean/hemispheric temp anomaly datasets. These datasets and the programs used to produce them are available on the GISS website:
http://data.giss.nasa.gov/gistemp/
The raw data is available from it’s owners (national meteorological organizations usually for land temps). For example, the US data is available for download from NOAA ($). That might mean that it costs a lot of money and takes a lot of effort to collect from all the vendors. But remember, we are talking about the entire globe.
Creating (or re-creating) global temp datasets isn’t a hobbyist activity. To claim that there is something wrong because the person you are criticizing can not do all the hard and expensive work for you is, simply, whining.
ConRev, the failing is in you, not in the analysis (from GISS for example).
CoRev said: “Since many, ~80%, are in urban or near urban areas, that means that the urban stations may be lowered somewhat, but the rural stations are surely raised.”
“may be”, “are surely” That doesn’t sound like you actually have done hands on examination of the issue.
CoRev said: “Models that are so bad that 20+ of them need to be averaged to get an estimate.”
There are that many models because there are that many groups doing the modeling.
The models are slightly different in their construction. Models are simplified representations of the world. The constraints are data and computer processing resources. A constraint isn’t a defect, it’s a reality that researchers adapt to.
Your statement shows a lack of understanding; it is actually quite embarassing.
Menzie,
I find your approach unhelpful. It seems you are enjoying the foodfight, as would be expected from your post.
My 2 cents — I don’t care about the damn trend. If people are so convinced that the economic effects of a warmer planet will be catastrophic (note that I do not deny the warming), then it seems they ought to be required to list where on their priority list “doing something” falls.
Any meaningful mitigation of warming must be costly – it is not simply a matter of taking colder showers. So, will you get governbment out of the schooling business? What about health care? How about cutting defense spending by half? What about ending welfare? Or some combination of programs in exchange for the massive cost increasses that will be coming?
Few people are willing to weigh in on this. Couple the fact that many global warming alarmists live in this unicron world where we can have all the goodies we want, with the fact, yes fact, that global warming regulation will produce the rent seeking orgy of all time and I think “skeptics” ought to be taken a bit more seriously than you seem to be treating them – as loony anti-scientists.
So what are your estimates about the annual US costs to deal with climate change effectively, and then what would you give up in order to make that spending possible?
If you say nothing, then who is acting in the fantasy world of faith and religion? You, or the so called skeptics, who want these questions taken seriously.
I’d also encourage folks to read Richard Tol’s neta-analysis of the changing econmic impacts of global warming over time.
I started my commentary on this article with this: “GISS and CRU temps are diverging. GISS has April 1st and CRU has it as 5th. How does that happen since they use essentially the same data? Lotsa answers! But look to the poles for a hint….”
Coincidentally we find this article at WUWT: GISS Arctic Trends Disagree with Satellite Data” It can be found here: http://wattsupwiththat.com/2010/05/20/giss-arctic-trends-disagree-with-satellite-data/#more-19740
I further explained that much of the heating may be from process artifacts. The referenced article concludes with this:
“Conclusions: GISS explains their increases vs. Had Crut as being due to their Arctic coverage. Their Arctic coverage is poor, and they rely on extrapolations across large distances with no data. Comparisons with other data sources show that GISS extrapolations across the Arctic are likely too high. In short, GISS trends over the last decade are most likely based on faulty extrapolations in the Arctic, and are probably not reliable indicators of global or Arctic temperature trends during that time period.”
Since much of the ?measured? and calculated warming appears at the poles, can we trust the GISS claim of warmest?
There is little doubt that the planet is warming. It has been since the LIA, and that’s a good thing! There is little doubt that mankind is responsible for some of that warming, and some of that is due to ACO2.
There is extreme doubt when we see claims that the warming is unprecedented and that we are responsible. IF WE COULD ACTUALLY MEASURE MAN’S IMPACTS, IT IS CLEAR TO ME THAT WHEN GRAPHED OVER THE PAST MILLION YEARS WE WOULD SEE SOME VERY SMALL PEAKS AND VALLEYS ON THE HUGE SINUSOIDAL GRAPH OF NATURAL CHANGE OF THE GLACIATIONS AND INTERGLACIALS PEROODS.
GregL, sigh. You have not refuted most of my points you cited. if anything you have reinforced them. Saying the raw data is owned/available by the local Met offices completely ignores the facts of central collection points. One of which is CRU who has already admitted that they destroyed/lost the raw data. Their processed data is then stored at NOAA. Your discussion of the models is intriguing in that it again confirms that they are simple, incomplete and limited. Again, confirming my points. Your models comments also confirms that there has been little effort to consolidate and improve.
Anyway, its gotten down to a food fight which is why I preferred not to get into a battle of competing papers. G’day to you.
CoRev:
“IF WE COULD ACTUALLY MEASURE MAN’S IMPACTS, IT IS CLEAR TO ME THAT WHEN GRAPHED OVER THE PAST MILLION YEARS WE WOULD SEE SOME VERY SMALL PEAKS AND VALLEYS ON THE HUGE SINUSOIDAL GRAPH OF NATURAL CHANGE OF THE GLACIATIONS AND INTERGLACIALS PEROODS.”
With so much clarity, and websites chosen to support it, who needs to learn about the science?
So when will the USA adopt no-regret policies to combat climate change and take care of a whole host of other social and economic problems?
A right-wing pundit up here in Canuckland opined the other day that the Greeks should slash their pay-roll taxes and increase coverage for the Value-added sales tax (VAT). Sounds like a good plan for the USA except I would first increase fuel excise taxes to northern European levels.
CoRev said: “Coincidentally we find this article at WUWT: GISS Arctic Trends Disagree with Satellite Data” It can be found here:”
I followed through and saw datasets that did not match up in spatial coverage:
GISS Arctic band: 64N to 90N
RSS Arctic Band: 60.0N to 82.5N
Since the warming increases with latitude, the RSS band would, of course, have a lower temperature anomally that the GISS band.
What say you CoRev?? Defend your source on this outrageous defect in methodology.
Anon, I’m not sure what you are trying to say here: “Since the warming increases with latitude, the RSS band would, of course, have a lower temperature anomally that the GISS band.”
The warming does not increase with latitude. You might make a case the warming TREND might be increasing, but actual Temps/warming works in the inverse. I assume that is what you meant.
Furthermore, it looks like you are asking me to defend NASA for it’s satellite orbits, and NASA/NOAA for their placement and selection of weather stations. For that is the methodology difference.
The article’s author, Steven Goddard, also made this observation: “GISS has explained their steeper temperature slope since 1998 vs. Had-Crut, as being due to the fact that they are willing to extrapolate 1200 km across the Arctic into regions where they may have no data whereas Had-Crut prefers to work with regions of the Arctic where they actually have thermometers.”
Note, neither the satellites nor the GISSTemp have coverage at the poles. If anything the satellites have denser coverage than NOAA/NASA up to 82.5 degrees. There are a handful of stations above 82.5 but most of them are on the coasts. From they admit they are: “…willing to extrapolate 1200 km across the Arctic into regions where they may have no data…” (From the article.
So, no! I can not defend the methodology. It makes no sense.
CoRev said: “The warming does not increase with latitude.”
The temperature anomaly increases with latitude CoRev; everybody agrees with that. Look here at figure 3 for the RSS TLT band data:
http://www.ssmi.com/msu/msu_data_description.html
The spike is extreme as you go further North.
CoRev said: “Furthermore, it looks like you are asking me to defend NASA for it’s satellite orbits, and NASA/NOAA for their placement and selection of weather stations. For that is the methodology difference.”
No I’m asking you to defend your source Watt’s misuse of the NASA and RSS datasets. You presented the Watts link and now you can’t justify it’s methodology.
Take responsibility for your posts CoRev.
CoRev’s chosen Arctic “expert” gained earlier notoriety among actual experts by writing a piece for a newsletter called the IT Register, “Arctic ice refuses to melt as ordered.” Concocting his own data by counting pixels from maps on websites, the pseudonymous author “Steven Goddard” concluded that the National Snow and Ice Data Center’s report on Arctic ice was wrong by a factor of three. His report was gleefully picked up and repeated ’round the Internet, where it still echoes today.
His thesis fell apart almost as soon as it was published, however, as it turned out that his method made no sense, and he hadn’t read what the different websites were showing. NSIDC’s report really was correct, as “Goddard” himself had to concede after a note added by the IT Register’s editors. The original story, rebuttal by a real scientist, embarrassed-sounding editor’s explanation, and author’s grudging retraction are all on this page (worth a quick read):
http://www.theregister.co.uk/2008/08/15/goddard_arctic_ice_mystery/
Anon, nope. Not gonna bite. Tired of the silliness, now going on. Take it up with the author. He has been active on the comment thread.
G’Day to you too.
CoRev: “No! For that we have the models. Models that are so bad that 20+ of them need to be averaged to get an estimate. Models that are currently batting nearly zero when we get outside the 10 year window.”
Why would you expect all models to agree in every detail? A model is not reality, it is a simplification of reality that is supposed to capture the main features of whatever it is that you’re studying. Different models tend to focus on different aspects of a problem, but they necessarily do so at the expense of other important aspects. Combining models is one relatively simple way to aggregate findings. And then there are the practical problems associated with trying to replicate results. And what we see is that while various models differ in particulars and point estimates, they all show generally the same trends and roughly the same order of magnitudes with approximately the same turning points. Given that we’re talking about a stochastic process, that’s about as good as it’s going to get. For a mildly amusing realworld example of the many problems associated with trying to replicate results exactly, here’s something by one of my favorite climate scientists:
http://moregrumbinescience.blogspot.com/2009/11/data-set-reproducibility.html#more
As to climate models not predicting anything outside of a 10 year window…well, you’re just plain wrong. Some of the very earliest IPCC reports predicted:
(1) melting glaciers
(2) decrease in winter snow cover
(3) increasing water vapor
(4) warmer oceans and rising sea levels
(5) shrinking of arctic ice
(6) species migration northward and shifts in seasons
All of those things were predicted by climate scientists many years ago, and all of them are coming true. It is true that scientists didn’t always get the point estimates exactly right, but they have consistently gotten the general direction right. And when they’ve been wrong it’s frequently been because things are getting worser faster than they thought.
Hi again 2slugs. We’ve covered this ground before so no point in belaboring the same areas. Most of your predictions were observational and not GCM-based. But what does it matter? We agree that the planet is warming. With warming comes change.
I went to Lucia’s blog to see what she had done recently comparing the model outputs versus reality. Just picking one of her articles try here: http://rankexploits.com/musings/2009/longish-trends-much-lower-than-models/
As usual she has some great graphs. When you say this: “And what we see is that while various models differ in particulars and point estimates, they all show generally the same trends and roughly the same order of magnitudes with approximately the same turning points.” Actually you are wrong. If volcanoes are not included then the models do not agree with turning points or even trends. To get that out come they must be averaged.
Furthermore saying the models all agree with “same trends” does not show anything if the trend differ from reality.
You seem to h=be having a logic problem. In one area you say: “Different models tend to focus on different aspects of a problem,…” they are different, yes. So why would they “…all show generally the same trends and roughly the same order of magnitudes with approximately the same turning points.”? The do not, and as they extend temporally they diverge. They can differ quite dramatically in orders of magnitude. Some outliers there.
Must read for anyone who still believes that man is the main cause of global warming.
http://pielkeclimatesci.wordpress.com/
“The brief notes below illustrate one of the many examples in my report to the Stern Review that completely demolishes the alarmist predictions by climate change scientists as described in the IPCCs assessment reports.” …
Will Alexander
Professor Emeritus, Department of Civil Engineering, University of Pretoria, South Africa.
Fellow, South African Institution of Civil Engineering
Member, United Nations Scientific and Technical Committee on Natural Disasters, 1994 2000.
[snip]
He spent the past 35 years of his career actively involved in the development of water resource and flood analysis methods as well as in natural disaster mitigation studies. His interest in climate change arose from claims that it would have an adverse effect in these fields. In his subsequent studies of very large hydrometeorological data sets he was unable to detect any adverse human-related changes. He has written more than 200 papers, presentations and books on these subjects. [snip]
Lets move towards solving the problem by creating green jobs…
Oops…
http://pajamasmedia.com/blog/leaked-spanish-report-obamas-model-green-economy-a-disaster-pjm-exclusive/
For anyone who still thinks the climate debate is settled, here’s a link to a SSRN paper:
Global Warming Advocacy Science: A Cross Examination
Jason Scott Johnston
University of Pennsylvania – Law School
May 2010
U of Penn, Inst for Law & Econ Research Paper No. 10-08
“Insofar as establishment climate science has glossed over and minimized such fundamental questions and uncertainties in climate science, it has created widespread misimpressions that have serious consequences for optimal policy design.”
Also, scientists have never been wrong before, especially ones whose salaries are paid by people who benefit from certain results.
An actual climate scientist venturing onto Anthony Watt’s anti-AGW site Watts Up With That, Walt Meier of the National Snow and Ice Data Center offered an accessible summary of the field.
Dr. Meier’s answers to one the questions posed to him address the issue of what is and isn’t settled.
Question 11: Is the science settled?
“This isn’t a particularly well-posed question, for which Willis is not to blame. What ‘science’ are we talking about? If we’re talking about the exact sensitivity of climate to CO2 (and other GHGs), exactly what will be the temperature rise be in the next 100 years, what will happen to precipitation, what will be the regional and local impacts? Then no, the science is not even close to being settled. But if the question is ‘is NH2 still valid?,’ then yes I would say the science is settled.”
[NH2 refers to the null hypothesis that factors that controlled earth’s climate in the past are the the same factors that control it today and will continue to do so into the future.]
And as a result, we also can say the science is settled with respect to the question: ‘have human-emitted GHGs had a discernable effect on climate and can we expect that effect to continue in the future?'”
It’s a tough audience at WUWT and of course they weren’t buying this stuff, but Meier’s talk would have sounded like plain common sense at the American Geophysical Union or any other major science meetings.
http://wattsupwiththat.com/2010/04/08/nsidcs-walt-meier-responds-to-willis/
Ambler said: “[NH2 refers to the null hypothesis that factors that controlled earth’s climate in the past are the the same factors that control it today and will continue to do so into the future.]”
I would quibble about the term “control” versus affect. If we actually know what “controlled” climate, other than heat from the sun, then we would be all about changing that “control.” If we rely on CO2 as being that “control”[restraining/directing influence or regulate/rule], then the theory is falsified with historical evidence. Control implies “lock step” correlation. It isn’t.
Then saying: “And as a result, we also can say the science is settled with respect to the question: ‘have human-emitted GHGs had a discernable effect on climate and can we expect that effect to continue in the future?'” Is undoubtedly true, but the climate community is in debate regarding how to measure the impacts of the affect of human-emitted GHGs.
As in so much of the debate over this subject there is some truth to nearly every side’s position. For the most part I agree with your comment. Please don’t take this comment beyond the quibble over use of wording.
The comments that recent warming is unpredented are strange. It’s technically true, but only because we don’t have enough data to see changes over 30 years periods once you get back more than a few hundred years. As you go back in time, there are less samples and data points are generaly spaced further apart. Data from ice cores are hundreds of years apart and the spacing increases greatly as you go further back.
Aaron, why do you think that ” Data from ice cores are hundreds of years apart” as you write? Where did you get that information? Why do you consider your source trustworthy?
You can look this stuff up for yourself. It’s always smart to be skeptical when someone tells you something like that.
Here, as an example, just to get started:
http://www.google.com/search?q=ice+core+annual+resolution
See? Whoever you trusted, they were wrong or fooling you. Don’t be fooled again. As Mr. Reagan said, “trust — but verify!”
Hank Roberts said: “Aaron, why do you think that ” Data from ice cores are hundreds of years apart” as you write? Where did you get that information? Why do you consider your source trustworthy?”
Hank your own source said this: Upper layers of ice in a core correspond to a single year or sometimes a single season. Deeper into the ice the layers thin and annual layers become indistinguishable….
Dating is a difficult task. Five different dating methods have been used for Vostok cores, with differences such as 300 years at 100 m depth, 600yr at 200 m, 7000yr at 400 m, 5000yr at 800 m, 6000yr at 1600 m, and 5000yr at 1934 m.[24]”
So both of you are correct, but Aaron appears more so.
CoRev:
“So both of you are correct, but Aaron appears more so.”
No, he’s not. It’s true that ice-core chronologies tend to lose resolution as they get deeper, but Aaron’s assertion was this:
“we don’t have enough data to see changes over 30 years periods once you get back more than a few hundred years.”
The Greenland Ice Sheet (GISP2) dataset has a shorter timeline compared with Vostok, but it’s more recent and frequently gets cited both properly and absurdly by people making claims about the medieval climate anomaly. GISP2 is a relatively old project (early 1990s), and others have since improved on its resolution. But I happen to have the GISP2 temperature reconstruction data at hand, and here’s what I see.
0-500 years before present, median gap between samples is 7 years, and the 90th percentile is 8 years.
500-2,000 ybp, median 8 years, 90th percentile 10 years.
2,000-10,000 ybp, median 10 years, 90th percentile 17 years.
10,000-50,000 ybp, median 19 years, 90th 29 years.
It appears that even looking back 10 to 50 thousand years, only 10% of the gaps exceed 29 years.
Ambler, you have pointed out why I do not like to get into dueling papers discussion.
I’ll repeat what I said earlier: “As in so much of the debate over this subject there is some truth to nearly every side’s position. For the most part I agree with your comment.” So now we have three correct answers, your’s, Hank’s and Aaron’s.
My post above describes GISP2 (1988-1993), which improved on the resolution of previous ice cores enough to inspire a new wave of research on “abrupt climate change.”
Resolution has improved quite a bit since the 90s, of course. Steffensen et al. describe a new chronology with sub-annual resolution, in an article in the AAAS flagship journal Science (1 August 2008, 321:680-684):
“High-Resolution Greenland Ice Core Data Show Abrupt Climate Change Happens in Few Years
…The shape and duration of the abrupt climate change at the termination of the last glacial have previously been constrained by Greenland ice core records from DYE-3 (4, 7), Greenland Ice Core Project (GRIP) (8) and Greenland Ice Sheet Project 2 (GISP2) (3, 6, 9), but sampling of these cores did not typically achieve a resolution sufficient to resolve annual layers. Because of new continuous flow analysis (CFA) systems (10-12), impurity and chemical records of the recent NGRIP ice core (1) have been obtained at subannual resolution, which allows for the multiple-proxy identification of annual-layer thickness and the construction of a new Greenland time scale, the Greenland Ice Core Chronology 2005 (GICC05) (2)….”
Hank, the data is available online. Here is the Vostok CO2 data for example: ftp://ftp.ncdc.noaa.gov/pub/data/paleo/icecore/antarctica/vostok/co2nat.txt
Here’s the gateway to the rest of the data:http://www.ncdc.noaa.gov/paleo/icecore/current.html