This is Hansen et al’s end of year summary for 2009 (with a couple of minor edits). Update: A final version of this text is available here.
If It’s That Warm, How Come It’s So Damned Cold?
by James Hansen, Reto Ruedy, Makiko Sato, and Ken Lo
The past year, 2009, tied as the second warmest year in the 130 years of global instrumental temperature records, in the surface temperature analysis of the NASA Goddard Institute for Space Studies (GISS). The Southern Hemisphere set a record as the warmest year for that half of the world. Global mean temperature, as shown in Figure 1a, was 0.57°C (1.0°F) warmer than climatology (the 1951-1980 base period). Southern Hemisphere mean temperature, as shown in Figure 1b, was 0.49°C (0.88°F) warmer than in the period of climatology.
Figure 1. (a) GISS analysis of global surface temperature change. Green vertical bar is estimated 95 percent confidence range (two standard deviations) for annual temperature change. (b) Hemispheric temperature change in GISS analysis. (Base period is 1951-1980. This base period is fixed consistently in GISS temperature analysis papers – see References. Base period 1961-1990 is used for comparison with published HadCRUT analyses in Figures 3 and 4.)
The global record warm year, in the period of near-global instrumental measurements (since the late 1800s), was 2005. Sometimes it is asserted that 1998 was the warmest year. The origin of this confusion is discussed below. There is a high degree of interannual (year‐to‐year) and decadal variability in both global and hemispheric temperatures. Underlying this variability, however, is a long‐term warming trend that has become strong and persistent over the past three decades. The long‐term trends are more apparent when temperature is averaged over several years. The 60‐month (5‐year) and 132 month (11‐year) running mean temperatures are shown in Figure 2 for the globe and the hemispheres. The 5‐year mean is sufficient to reduce the effect of the El Niño – La Niña cycles of tropical climate. The 11‐year mean minimizes the effect of solar variability – the brightness of the sun varies by a measurable amount over the sunspot cycle, which is typically of 10‐12 year duration.
Figure 2. 60‐month (5‐year) and 132 month (11‐year) running mean temperatures in the GISS analysis of (a) global and (b) hemispheric surface temperature change. (Base period is 1951‐1980.)
There is a contradiction between the observed continued warming trend and popular perceptions about climate trends. Frequent statements include: “There has been global cooling over the past decade.” “Global warming stopped in 1998.” “1998 is the warmest year in the record.” Such statements have been repeated so often that most of the public seems to accept them as being true. However, based on our data, such statements are not correct. The origin of this contradiction probably lies in part in differences between the GISS and HadCRUT temperature analyses (HadCRUT is the joint Hadley Centre/University of East Anglia Climatic Research Unit temperature analysis). Indeed, HadCRUT finds 1998 to be the warmest year in their record. In addition, popular belief that the world is cooling is reinforced by cold weather anomalies in the United States in the summer of 2009 and cold anomalies in much of the Northern Hemisphere in December 2009. Here we first show the main reason for the difference between the GISS and HadCRUT analyses. Then we examine the 2009 regional temperature anomalies in the context of global temperatures.
Figure 3. Temperature anomalies in 1998 (left column) and 2005 (right column). Top row is GISS analysis, middle row is HadCRUT analysis, and bottom row is the GISS analysis masked to the same area and resolution as the HadCRUT analysis. [Base period is 1961‐1990.]
Figure 3 shows maps of GISS and HadCRUT 1998 and 2005 temperature anomalies relative to base period 1961‐1990 (the base period used by HadCRUT). The temperature anomalies are at a 5 degree‐by‐5 degree resolution for the GISS data to match that in the HadCRUT analysis. In the lower two maps we display the GISS data masked to the same area and resolution as the HadCRUT analysis. The “masked” GISS data let us quantify the extent to which the difference between the GISS and HadCRUT analyses is due to the data interpolation and extrapolation that occurs in the GISS analysis. The GISS analysis assigns a temperature anomaly to many gridboxes that do not contain measurement data, specifically all gridboxes located within 1200 km of one or more stations that do have defined temperature anomalies.
The rationale for this aspect of the GISS analysis is based on the fact that temperature anomaly patterns tend to be large scale. For example, if it is an unusually cold winter in New York, it is probably unusually cold in Philadelphia too. This fact suggests that it may be better to assign a temperature anomaly based on the nearest stations for a gridbox that contains no observing stations, rather than excluding that gridbox from the global analysis. Tests of this assumption are described in our papers referenced below.
Figure 4. Global surface temperature anomalies relative to 1961‐1990 base period for three cases: HadCRUT, GISS, and GISS anomalies limited to the HadCRUT area. [To obtain consistent time series for the HadCRUT and GISS global means, monthly results were averaged over regions with defined temperature anomalies within four latitude zones (90N‐25N, 25N‐Equator, Equator‐25S, 25S‐90S); the global average then weights these zones by the true area of the full zones, and the annual means are based on those monthly global means.]
Figure 4 shows time series of global temperature for the GISS and HadCRUT analyses, as well as for the GISS analysis masked to the HadCRUT data region. This figure reveals that the differences that have developed between the GISS and HadCRUT global temperatures during the past few decades are due primarily to the extension of the GISS analysis into regions that are excluded from the HadCRUT analysis. The GISS and HadCRUT results are similar during this period, when the analyses are limited to exactly the same area. The GISS analysis also finds 1998 as the warmest year, if analysis is limited to the masked area. The question then becomes: how valid are the extrapolations and interpolation in the GISS analysis? If the temperature anomaly scale is adjusted such that the global mean anomaly is zero, the patterns of warm and cool regions have realistic‐looking meteorological patterns, providing qualitative support for the data extensions. However, we would like a quantitative measure of the uncertainty in our estimate of the global temperature anomaly caused by the fact that the spatial distribution of measurements is incomplete. One way to estimate that uncertainty, or possible error, can be obtained via use of the complete time series of global surface temperature data generated by a global climate model that has been demonstrated to have realistic spatial and temporal variability of surface temperature. We can sample this data set at only the locations where measurement stations exist, use this sub‐sample of data to estimate global temperature change with the GISS analysis method, and compare the result with the “perfect” knowledge of global temperature provided by the data at all gridpoints.
| 1880‐1900 | 1900‐1950 | 1960‐2008 | |
|---|---|---|---|
| Meteorological Stations | 0.2 | 0.15 | 0.08 |
| Land‐Ocean Index | 0.08 | 0.05 | 0.05 |
Table 1. Two‐sigma error estimate versus period for meteorological stations and land‐ocean index.
Table 1 shows the derived error due to incomplete coverage of stations. As expected, the error was larger at early dates when station coverage was poorer. Also the error is much larger when data are available only from meteorological stations, without ship or satellite measurements for ocean areas. In recent decades the 2‐sigma uncertainty (95 percent confidence of being within that range, ~2‐3 percent chance of being outside that range in a specific direction) has been about 0.05°C. The incomplete coverage of stations is the primary cause of uncertainty in comparing nearby years, for which the effect of more systematic errors such as urban warming is small.
Additional sources of error become important when comparing temperature anomalies separated by longer periods. The most well‐known source of long‐term error is “urban warming”, human‐made local warming caused by energy use and alterations of the natural environment. Various other errors affecting the estimates of long‐term temperature change are described comprehensively in a large number of papers by Tom Karl and his associates at the NOAA National Climate Data Center. The GISS temperature analysis corrects for urban effects by adjusting the long‐term trends of urban stations to be consistent with the trends at nearby rural stations, with urban locations identified either by population or satellite‐observed night lights. In a paper in preparation we demonstrate that the population and night light approaches yield similar results on global average. The additional error caused by factors other than incomplete spatial coverage is estimated to be of the order of 0.1°C on time scales of several decades to a century, this estimate necessarily being partly subjective. The estimated total uncertainty in global mean temperature anomaly with land and ocean data included thus is similar to the error estimate in the first line of Table 1, i.e., the error due to limited spatial coverage when only meteorological stations are included.
Now let’s consider whether we can specify a rank among the recent global annual temperatures, i.e., which year is warmest, second warmest, etc. Figure 1a shows 2009 as the second warmest year, but it is so close to 1998, 2002, 2003, 2006, and 2007 that we must declare these years as being in a virtual tie as the second warmest year. The maximum difference among these in the GISS analysis is ~0.03°C (2009 being the warmest among those years and 2006 the coolest). This range is approximately equal to our 1‐sigma uncertainty of ~0.025°C, which is the reason for stating that these five years are tied for second warmest.
The year 2005 is 0.061°C warmer than 1998 in our analysis. So how certain are we that 2005 was warmer than 1998? Given the standard deviation of ~0.025°C for the estimated error, we can estimate the probability that 1998 was warmer than 2005 as follows. The chance that 1998 is 0.025°C warmer than our estimated value is about (1 – 0.68)/2 = 0.16. The chance that 2005 is 0.025°C cooler than our estimate is also 0.16. The probability of both of these is ~0.03 (3 percent). Integrating over the tail of the distribution and accounting for the 2005‐1998 temperature difference being 0.61°C alters the estimate in opposite directions. For the moment let us just say that the chance that 1998 is warmer than 2005, given our temperature analysis, is at most no more than about 10 percent. Therefore, we can say with a reasonable degree of confidence that 2005 is the warmest year in the period of instrumental data.
Figure 5. (a) global map of December 2009 anomaly, (b) global map of Jun‐Jul‐Aug 2009 anomaly. #4 and #2 indicate that December 2009 and JJA are the 4th and 2nd warmest globally for those periods.
What about the claim that the Earth’s surface has been cooling over the past decade? That issue can be addressed with a far higher degree of confidence, because the error due to incomplete spatial coverage of measurements becomes much smaller when averaged over several years. The 2‐sigma error in the 5‐year running‐mean temperature anomaly shown in Figure 2, is about a factor of two smaller than the annual mean uncertainty, thus 0.02‐0.03°C. Given that the change of 5‐year‐mean global temperature anomaly is about 0.2°C over the past decade, we can conclude that the world has become warmer over the past decade, not cooler.
Why are some people so readily convinced of a false conclusion, that the world is really experiencing a cooling trend? That gullibility probably has a lot to do with regional short‐term temperature fluctuations, which are an order of magnitude larger than global average annual anomalies. Yet many lay people do understand the distinction between regional short‐term anomalies and global trends. For example, here is comment posted by “frogbandit” at 8:38p.m. 1/6/2010 on City Bright blog:
“I wonder about the people who use cold weather to say that the globe is cooling. It forgets that global warming has a global component and that its a trend, not an everyday thing. I hear people down in the lower 48 say its really cold this winter. That ain’t true so far up here in Alaska. Bethel, Alaska, had a brown Christmas. Here in Anchorage, the temperature today is 31[ºF]. I can’t say based on the fact Anchorage and Bethel are warm so far this winter that we have global warming. That would be a really dumb argument to think my weather pattern is being experienced even in the rest of the United States, much less globally.”
What frogbandit is saying is illustrated by the global map of temperature anomalies in December 2009 (Figure 5a). There were strong negative temperature anomalies at middle latitudes in the Northern Hemisphere, as great as ‐8°C in Siberia, averaged over the month. But the temperature anomaly in the Arctic was as great as +7°C. The cold December perhaps reaffirmed an impression gained by Americans from the unusually cool 2009 summer. There was a large region in the United States and Canada in June‐July‐August with a negative temperature anomaly greater than 1°C, the largest negative anomaly on the planet.
Figure 6. Arctic Oscillation (AO) Index. Positive values of the AO index indicate high low pressure in the polar region and thus a tendency for strong zonal winds that minimize cold air outbreaks to middle latitudes. Blue dots are monthly means and the red curve is the 60‐month (5‐year) running mean.
How do these large regional temperature anomalies stack up against an expectation of, and the reality of, global warming? How unusual are these regional negative fluctuations? Do they have any relationship to global warming? Do they contradict global warming?
It is obvious that in December 2009 there was an unusual exchange of polar and mid‐latitude air in the Northern Hemisphere. Arctic air rushed into both North America and Eurasia, and, of course, it was replaced in the polar region by air from middle latitudes. The degree to which Arctic air penetrates into middle latitudes is related to the Arctic Oscillation (AO) index, which is defined by surface atmospheric pressure patterns and is plotted in Figure 6. When the AO index is positive surface pressure is high low in the polar region. This helps the middle latitude jet stream to blow strongly and consistently from west to east, thus keeping cold Arctic air locked in the polar region. When the AO index is negative there tends to be low high pressure in the polar region, weaker zonal winds, and greater movement of frigid polar air into middle latitudes.
Figure 6 shows that December 2009 was the most extreme negative Arctic Oscillation since the 1970s. Although there were ten cases between the early 1960s and mid 1980s with an AO index more extreme than ‐2.5, there were no such extreme cases since then until last month. It is no wonder that the public has become accustomed to the absence of extreme blasts of cold air.
Figure 7. Temperature anomaly from GISS analysis and AO index from NOAA National Weather Service Climate Prediction Center. United States mean refers to the 48 contiguous states.
Figure 7 shows the AO index with greater temporal resolution for two 5‐year periods. It is obvious that there is a high degree of correlation of the AO index with temperature in the United States, with any possible lag between index and temperature anomaly less than the monthly temporal resolution. Large negative anomalies, when they occur, are usually in a winter month. Note that the January 1977 temperature anomaly, mainly located in the Eastern United States, was considerably stronger than the December 2009 anomaly. [There is nothing magic about a 31 day window that coincides with a calendar month, and it could be misleading. It may be more informative to look at a 30‐day running mean and at the Dec‐Jan‐Feb means for the AO index and temperature anomalies.]
The AO index is not so much an explanation for climate anomaly patterns as it is a simple statement of the situation. However, John (Mike) Wallace and colleagues have been able to use the AO description to aid consideration of how the patterns may change as greenhouse gases increase. A number of papers, by Wallace, David Thompson, and others, as well as by Drew Shindell and others at GISS, have pointed out that increasing carbon dioxide causes the stratosphere to cool, in turn causing on average a stronger jet stream and thus a tendency for a more positive Arctic Oscillation. Overall, Figure 6 shows a tendency in the expected sense. The AO is not the only factor that might alter the frequency of Arctic cold air outbreaks. For example, what is the effect of reduced Arctic sea ice on weather patterns? There is not enough empirical evidence since the rapid ice melt of 2007. We conclude only that December 2009 was a highly anomalous month and that its unusual AO can be described as the “cause” of the extreme December weather.
We do not find a basis for expecting frequent repeat occurrences. On the contrary. Figure 6 does show that month‐to‐month fluctuations of the AO are much larger than its long term trend. But temperature change can be caused by greenhouse gases and global warming independent of Arctic Oscillation dynamical effects.
Figure 8. Global maps 4 season temperature anomalies for ~2009. (Note that Dec is December 2008. Base period is 1951‐1980.)
Figure 9. Global maps 4 season temperature anomaly trends for period 1950‐2009.
So let’s look at recent regional temperature anomalies and temperature trends. Figure 8 shows seasonal temperature anomalies for the past year and Figure 9 shows seasonal temperature change since 1950 based on local linear trends. The temperature scales are identical in Figures 8 and 9. The outstanding characteristic in comparing these two figures is that the magnitude of the 60 year change is similar to the magnitude of seasonal anomalies. What this is telling us is that the climate dice are already strongly loaded. The perceptive person who has been around since the 1950s should be able to notice that seasonal mean temperatures are usually greater than they were in the 1950s, although there are still occasional cold seasons.
The magnitude of monthly temperature anomalies is typically 1.5 to 2 times greater than the magnitude of seasonal anomalies. So it is not yet quite so easy to see global warming if one’s figure of merit is monthly mean temperature. And, of course, daily weather fluctuations are much larger than the impact of the global warming trend. The bottom line is this: there is no global cooling trend. For the time being, until humanity brings its greenhouse gas emissions under control, we can expect each decade to be warmer than the preceding one. Weather fluctuations certainly exceed local temperature changes over the past half century. But the perceptive person should be able to see that climate is warming on decadal time scales.
This information needs to be combined with the conclusion that global warming of 1‐2°C has enormous implications for humanity. But that discussion is beyond the scope of this note.
References:
Hansen, J.E., and S. Lebedeff, 1987: Global trends of measured surface air temperature. J. Geophys. Res., 92, 13345‐13372.
Hansen, J., R. Ruedy, J. Glascoe, and Mki. Sato, 1999: GISS analysis of surface temperature change. J. Geophys. Res., 104, 30997‐31022.
Hansen, J.E., R. Ruedy, Mki. Sato, M. Imhoff, W. Lawrence, D. Easterling, T. Peterson, and T. Karl, 2001: A closer look at United States and global surface temperature change. J. Geophys. Res., 106, 23947‐23963.
Hansen, J., Mki. Sato, R. Ruedy, K. Lo, D.W. Lea, and M. Medina‐Elizade, 2006: Global temperature change. Proc. Natl. Acad. Sci., 103, 14288‐14293.
News flash: A typo in a 400 page document does not change fundamental physics.
Neither do emails suggesting that a well known denialist sports the latest in rectal haberdashery.
And there’s no Easter Bunny of Tooth fairy either.
You’re only showing the record from 1880 on because this was the time when instrumental weather recordings started. But taking into account other records as for example ice core record, one would clearly see, that the recorded warming during the 20th century follows a cold period, the little ice age, which was preceded by the medieval warm period. So, is that recent warming related to human activity or is it just a natural variation as earth history experienced lots of in the last, say, millions of years. Recent climate scientist, and these are the only ones you hear of in public, are just to much concerned about proving the human made climate change and forgot to look at the other side, towards possibilities that might exclude a men-made climate change and just involve natural causes.
Particularly relevant to Richard Steckis 3rd and 5th point combined:
“What’s the use of having developed a science well enough to make predictions, if in the end, all we’re willing to do is stand around and wait for them to come true!”
Sherwoord Rowland, Nobel Laureate, referring to ozone depletion by CFC’s.
Gavin@133 regarding IPCC Glaciers Issue:
“It is not mentioned in the WG1 (the climate science section), nor in the Synthesis report, nor in any of the summaries for policy makers.”
The NYT is reporting this appeared in the summaries:
“The summaries said only that the Himalayan glaciers “could decay at very rapid rates” if warming continued.”
http://www.nytimes.com/2010/01/19/science/earth/19climate.html
Obviously they toned it down, but still used. This item was picked up by the NYT, Wall Street Journal, BBC, ABC, Bloomberg, most major newspapers in Britain, Australia(not sure on this one), so the media seems to be paying closer attention now. I understand what the science feels is really important is different than the public, but AGW proponents are going to be hearing about this every time they use IPCC as a defense of the science, valid or not.
It is kind of comical though the way it changes over time, this may not be totally accurate, but is close.
Indian Scientist: A glacier is melting very quickly
New Science: A glacier may melt by 2035
WWF: All glaciers may melt by 2035
IPCC: Very likely all glaciers will melt by 2035.
And the final irony: A British newspaper is reporting the Indian scientist is now working on a $500,000 grant to study the rapid glacier retreat. (this may have happened anyway, but it is an interesting end-point)
Another minor thing: the updated Global Annual Mean Surface Air Temperature Change graph here: http://data.giss.nasa.gov/gistemp/graphs/ has an open symbol for 2009 in the GIF version but a filled symbol in the PDF version (didn’t check the PS version).
Andreas: “So, is that recent warming related to human activity or is it just a natural variation as earth history experienced lots of it”
The MWP has an explanation and that explanation isn’t CO2 products.
The LIA has an explanation and that explanation isn’t CO2 products.
The recent warming has no explanation that doesn’t include CO2 products.
My grannie died on the operating table. My grandad from old age.
This doesn’t prove Jamie Bulger http://en.wikipedia.org/wiki/Murder_of_James_Bulger died of natural causes or hospital accidents.
RE #207, Sam, and “What I don’t understand is that people on the pro AGW side of this issue will assume that any side effect of predicted global warming are negative. Isn’t it at the simplest (and perhaps most accurate) level just as likely that the side effects might be positive?”
Not really.
I guess the most positive thing might be crop increase in northern places like the northern U.S., Canada, Europe, and Russia, due to CO2 fertiliation and longer growing seasons, BUT that is only for about 40 years, after which a sharp decline is expected; crop decline is expected for much of the rest of world due to GW even earlier than this.
RE CO2*: it will not have as much crop benefit as expected, acc to recent experiments; C3 plants (incl weeds) do better than C4 crops, however, experiments in Japan found it causes floret sterility in rice (a C3 plant), reducing yield by up to 40%; it makes crops less nutritious, some crops more toxic; it becomes carbonic acid and acidifies & harms the soil (along with other pollutants-turned-acid that are also emitted along with CO2); it acidifies the ocean, harming sea life & coral reefs (home to 1/4 of sealife); some places where CO2 increases seaplant life, like algae, it will cause too much, pushing plants out of the sunlight, where they will intake & deplete oxygen, contribute to ocean dead zones, killing fish.
RE warming*: it will harm crops through heat stress, droughts, floods, loss of irrigation from glaciers & snowpacks (on which 1 billion of the world’s population, incl much of California, depend).
And there are other considerations — GW is now and will greatly contribute to species extinction, and many of those species are vital to healthy ecosystems. The scientists don’t even know how many tears can be rent in the web of creation before the whole thing pretty much collapses. Take bees — there is some idea that hive collapse may be exacerbated by GW (more research needs to be done) — but without them a huge chunk of our crops and fruit/nut trees won’t get fertilized. It could be a really huge loss.
But not all species will be so harmed — it seems lots of tropical disease vectors will be moving into new territories, causing illness and death.
And this is just the beginning of pretty much the end. Since a portion of CO2 can stay up in the atmosphere up to 100,000 years (see https://www.realclimate.org/index.php/archives/2005/03/how-long-will-global-warming-last/langswitch_lang/in ), and warming causes release of methane (25 more potent GHG than CO2, but lasting about 10 years) and CO2 by melting permafrost and ocean hydrates, the warming could very greatly spiral very high. This happened (tho by natural causes) 251 million years ago at the end-Permian, when 95% of life died — the final kicker was the warming caused super depletion of ocean oxygen, which cause outgassing of hydrogen sulfide, a deadly gas.
Then there is the possibility that if we burn all fossil fuels, we could trigger eventual runaway warming as on Venus, in which all life dies — partly because the sun is brighter than 251 mill yrs ago, and also bec of the rapidity with which we are emitting GHGs (lickity-split in geological terms) – see esp p. 24 of http://www.columbia.edu/~jeh1/2008/AGUBjerknes_20081217.pdf
So anyway, if we pay money for insurance against harm to our property & ill health, I think it is a wise insurance policy to reduce our GHGs, even if one doesn’t think what I said is very likely. And reducing GHGs, also reduce the other co-pollutants that cause acid rain and local pollution & harm, and, best of all, reduction can be done while saving money & not lowering living standards, at least up to a 70% reduction.
__________
* Note: I have peer-reviewed sources for these claims, and if anyone wants any of them, let me know.
Blog commenter “rewinn” has got the cause of this supposed temperature rise thing quite figured out.
Hey, Ralphie …
1980-1989 was warmer than 1970-1979
1990-1999 was warmer than 1980-1989
2000-2009 was warmer than 1990-1999
Do you see a pattern here? I do. So does Hansen …
On what basis do you jump to the conclusion that there’s no evidence to suggest that Hansen’s claim is true?
[Response: Hansen’s claim is not based on linear extrapolation, but from reasonable confidence that the drivers of the recent trends are known and that those drivers will continue in the same direction for the next few decades too. – gavin]
@254: Tom: I think you missed the publication in the November issue of Science which already gave an overview of Himalayan glacier retreat, it concluded: Most Himalayan glaciers decay very slow, some decay rapidly, some are stable and some actually grow. which makes the irony even bigger…
RalphieGM said:
I suspect either you didn’t read the whole article at all, or that if you did, you simply failed to grasp what it says. The conclusion is amply supported by the evidence – but Hansen’s highly technical analysis isn’t perhaps the best way to make the point to non-scientists.
Fortunately, Tamino has an excellent way of visualising these things. Look at the 10 year averages. http://tamino.files.wordpress.com/2009/01/10yrave.jpg?w=488&h=360 Clearly, they have been rising steadily for decades now. All the complexity that Hansen tried to explain can be disregarded – his conclusion is based on the big picture, not the fine detail.
Septic Matthew: I think you will find this relevant: http://tamino.wordpress.com/2009/08/06/graph-jam/
245 Barton Paul Levenson says:
19 January 2010 at 7:03 AM
BPL: You need 30 years to tell a climate trend. 10 years tells you nothing at all.
Temperature has risen strongly over the past 30 years.
Don Shor: Right. 1/3 of the period is irrelevant. Got it.
BPL: Can’t you read? Temperature has risen strongly COUNTING the last ten years (20 + 10 = 30). The TREND is strongly up. The last ten years don’t tell you the TREND any more than the first ten years or ten years picked at random. It’s not a big enough sample size.
The trend is still STRONGLY up. Deal with it.
Clearly you didn’t read my posts carefully, nor most of the subsequent ones on the topic. And apparently you can’t look at graphs, either.
“Deal with it?” What is this, junior high school?
Fascinating discussions.
I remember, many, many moons ago, while at university, ( UCSC), taking a “science for humanities” class and hearing about “global warming”. This was round about 1971 or so.
The main point was that increased amounts of gases from industry etc; were going to cause increased overall temperature etc;
Also, I remember that ocean currents were going to be affected to the point that they might actually stop circulating.
I also remeber watching James Burke’s little series on Global Warming. It’s amazing that such a series, ( done 20+ years ago), was so accurate in predicting, not the climate change, but the politics, national and international, that would occur.
> Don Shor
> “apparently you can’t look at graphs, either.”
Nobody who’s passed Statistics 101 can’t look at graphs the same way either.
Seriously, until you doubt your own eyes’ ability to detect patterns, you don’t understand what people are trying to explain to you here.
Please make the effort to lose the illusion that every pattern you see is really there. Learning to see the world with mathematics does change everything to some degree.
Can we get a thread going that explains why headlines like this are appearing all over the world?
“World Misled Over Himalayan Glacier Meltdown”
http://www.timesonline.co.uk/tol/news/environment/article6991177.ece
112 Gilles: The #1 kill mechanism is famine. See “The Long Summer” by Brian Fagan and “Collapse” by Jared Diamond. You will not be a survivor. Moving is pointless. Your only hope is to stop global warming. Get radical about stopping coal fired power plants.
Fig 2b, comparing NH and SH, suggests a lazy question. How are aerosol forcings input into models? Are aerosols in the models uniformly distributed around the globe, or are there spatial distributions? If the latter, is the spatial nature a fixed input, or are the models allowed to blow the aerosols around?
[Response: The spatial distribution of aerosols is very important, and so we have always used estimates of their distribution and properties both horizontally and vertically. It used to be that these distributions were calculated separately and then imposed on the GCMs, but these days, they are calculated as part of the GCM itself given just the emissions data. Unfortunately, there isn’t enough observed data to prescribe this purely from observations, and so the direct measurements (from stations and satellites) are used to evaluate the model-derived distributions. – gavin]
> why headlines like this are appearing all over the world?
Try using Google to search for phrases from the places you find it; it looks like a very effective press release/copypaste operation. I wish I knew how to find time stamps with Google. I think there’s a way to chart the prevalence over time of particular search strings.
… about 18,600 for climate media funding Himalayan Glacier Meltdown.
Gavin: “resettle a big fraction of Bangladesh”
NO. It just doesn’t work that way. According to Tim Flannery, “Now or Never”, the population of humans is already 25% above the carrying capacity of the Earth. The “Green Revolution” made the situation worse.
Have you ever studied population biology? Populations of ALL species oscillate up and down. Overpopulations result in population crashes. Homo Sap is no different. Trying to make it different is suicidal. Being too “ethical” is as unethical as you can be. See “The Genetics of Altruism” by Lumsden and Wilson. Altruism directed toward the wrong people is suicide.
THERE WILL BE A POPULATION CRASH. There is nothing you can do to stop it. [edit – calm down]
Well Don, maybe if you hadn’t jumped in (17 and 67) with your claims regarding how Figure 4 somehow invalidated the text statement that there had been a strong and persistent rise in T over the last 3 decades (actually 3.5), you would have saved yourself some time. Notwithstanding the fact that said statement was not made wrt Fig 4, nor is the long term trend per se even the point of Fig. 4.
RE: 239 Completely Fed Up says:
sam: “I bet it will continue to snow in the himalayas for a long long long time and this snow will have to go somewhere.”
But that’s not a bet on the table, sam. Nobody in the IPCC and AGW science says that snow won’t fall.
But the snow line is gaining elevation:
MONITORING OF HIMALAYAN GLACIERS AND SNOW COVER
http://www.slideshare.net/equitywatch/kulkarni-glacier-august27-revised
“Elevation of the snow line from 4900 to 5300 meters since 1970 means many glaciers are without accumulation area and may experience terminal retreat due to lack of formation of new ice.”
FWIW, posts #s 1123 & 1132 in “unforced variations 2” include much information regarding Himalayan glaciers
RE BPL
The new and improved MWP. To the manor born.
I think the interdependence of our civilization is taken for granted some times. Evolution of H. sapiens is really the story about the survival of societies of people, not individuals; a point that people like Randians seem to forget.
265
Hank Roberts says:
19 January 2010 at 11:21 AM
> Don Shor
> “apparently you can’t look at graphs, either.”
Nobody who’s passed Statistics 101 can’t look at graphs the same way either.
Seriously, until you doubt your own eyes’ ability to detect patterns, you don’t understand what people are trying to explain to you here.
Please make the effort to lose the illusion that every pattern you see is really there.
As we subsequently discussed, the pattern I see in the last decade, which is clearly there, is possibly explained by Latif et al. This would be an improvement to the models. In fact, explaining the decadal changes in global warming would be of great use to those who have to make risk assessments and policy decisions resulting from climate change.
You, BPL, and Dr. Hansen apparently want the last decade to be a statistical fluke, not worthy of consideration. But it is there, there is a possible explanation, and to ignore it is imprecise. Which was my original point.
Re: 266 AJ says:
“Can we get a thread going that explains why headlines like this are appearing all over the world?”
It would be redundant, but, comment #1123 & #1132 in “unforced variations 2” & #221 in “2009 temperatures by Jim Hansen” include much information regarding this specific subject as well as the status of melting Himalayan glaciers.
J asks:”Can we get a thread going that explains why headlines like this are appearing all over the world?
“World Misled Over Himalayan Glacier Meltdown” ”
World Misled by TimesOnline Headline.
266 AJ says:
19 January 2010 at 11:42 AM
Can we get a thread going that explains why headlines like this are appearing all over the world?
“World Misled Over Himalayan Glacier Meltdown”
Roger Pielke, Jr. is discussing this in detail at his blog. For once, the headline is reasonably accurate. The world was misled over the pace of the melting of Himalayan glaciers. Unfortunately, another black eye for the IPCC and its chairman, Dr. Pachauri.
So in figure 3, I’m looking at the top row of Arctic grid cells in the HadCRUT 2005 chart. An eyeball estimate shows me that more than 50% is not covered. I see two cells that are covered by the +6.5 anomaly. In the GISS portion of the chart I see that the same line of grid cells has been expanded to where there are about 25 cells with an anomaly of +6.5. In fact, there are even 6 HadCRUT cells that show cooling than show the maximum +6.5 warming in the GISS map. In fact, looking at the available cells in the top row for the HadCRUT data, I cannot see how such a hot top row for GISS could be interpolated or extrapolated from the available cells.
I’m assuming that HadCRUT masking means that we take all the cells that don’t have coverage in HadCRUT and also count them as having no coverage in GISS. But when I look at the GISS/HadCRUT mask map, I see that some of the GISS cells have actually had their values changed from the GISS stand alone. Why would masking produce such an effect. It seems that the masking not only dropped out the HadCRUT cells, but it also cooled many of the GISS cells. So the total difference ends up being more than just a coverage difference.
Very interesting paper, thank you.
One thing which puzzles me, and this maybe a naive question, is whether we might expect greater variability in the climate in future – or whether we can more likely expect the same sort of variability but a few degrees warmer? This is a rephrasing of an issue which was debated in the UK parliament on Jan 5, 2010 and in the British media at that time.
A fuller description of this query can be found at my Haddock Research blog:
Going beyond averages in describing climate – http://tinyurl.com/yl3pcdr
No one of the reviewers spotted a freaking TYPO of this magnitude? Whatever the case the whole thing is disgusting. The error between 2035 and 2350 is 315 years. This stood for 3 years! There’s no defense, though some scientists expressed doubts, and some of us tried on the merits of the research we found.
We don’t need denialists to cast doubt on the science. The IPCC seems to doing plenty well by itself.
“CLIMATE: Indian minister slams IPCC over Himalayan glacier warning”
http://www.eenews.net/Greenwire/2010/01/19/6/
(01/19/2010)
“India’s environment minister, Jairam Ramesh, harshly criticized the United Nations’ top climate research body in remarks published today, saying the group’s warning about the abrupt disappearance of the Himalayan glaciers lacked “scientific evidence.”
Ramesh’s critique focuses on a claim in the Intergovernmental Panel on Climate Change’s (IPCC) 2007 report that said the chances of Himalayan glaciers “disappearing by the year 2035 and perhaps sooner is very high.”
“The IPCC claim that glaciers will vanish by 2035 was not based on an iota of scientific evidence,” Ramesh told the Hindustan Times. “The IPCC has to do a lot of answering on how it reached the 2035 figure, which created such a scare,” he added.
Yesterday, IPCC’s chairman said the panel would review the 2035 figure.
“Ramesh felt “vindicated,” he said, after reports began surfacing that the glacier figure may have surfaced from a typo or other error (Greenwire, Jan. 18). He also conceded that “most glaciers are in a poor state” but are receding at different rates, with some even advancing (AFP/Yahoo News, Jan. 19). — PV”
[Response: Note that the Ramesh report said nothing about the IPCC or the 2035 number and was still a little odd. Not really sure how much ‘vindication’ should be allotted.- gavin]
This does not bode well.
SENATE: Climate is dead, but energy bill lives — Dorgan
http://www.eenews.net/Greenwire/2010/01/19/2/
(01/19/2010)
Mike Soraghan, E&E reporter
A leading Democratic senator on energy issues is contradicting his party leadership’s assertions that it can pass a climate change bill this year.
Sen. Byron Dorgan (D-N.D.), who recently announced his retirement, said today in a conference call sponsored by Securing America’s Energy Future that after the bitter battle over health care, there won’t be enough political will left to undertake such a contested bill.
[…]
Since all these people are bought and sold I’m not sure this is accurate either.
For Peter Winters, the question about variability comes up often; for example
https://www.realclimate.org/?s=augura
Brief excerpt (far more in that thread):
“saying it this way — that “climate is becoming more unpredictable” is misleading. In fact, climate may, if anything, become more predictable as anthropogenic forcing becomes even more dominant (as greenhouse gas concentrations increase), relative to natural forcing and variability. And what is definitely not the case — but might be inferred from the article — is that weather is becoming more unpredictable. Weather prediction is based on observations just a few days in advance — climate and climate trends have nothing to do with it.
The point here is not that we shouldn’t be concerned about the fate of insects and birds in the UK (that would be the kind of conclusion that only the most willfully ignorant would draw.) They have been in decline for a long time (mostly due to land use change and pesticides) and there is little doubt that climate change will continue to add insult to injury. But it is simply wrong to confuse a year or even two years of unfavorable weather with a change in climate, and it is irresponsible to headline an article that is really about weather with the provocative juxtaposition of “climate” and “devastates”. Doing so gives the average reader the sense that their personal observations about “weird weather patterns” or fewer sightings of Parus caeruleus represent definitive manifestations of climate change. The fact is, climate changes are — so far — small enough in most places, relative to the natural variability, that one’s personal experience is a very poor guide to what is happening over the long term (observations of sea ice changes by those that live in the high Arctic notwithstanding).”
#266, Hi AJ, you’re perhaps right that we may need some post on this issue. Hopefully glaciologists will step in give us a good analysis of the actual state of Himalayan and/or world glaciers.
However, I’m thinking this fiasco is sort of ridiculous.
For instance why are they suddenly discovering this glitch in the 2007 IPCC report, which has been out for years? Precisely. That’s what I thought. No one (except me) has actually read p. 493 of WG2, Ch. 10 Asia until recently. Perhaps because few people have time to read beyond the executive summaries (which did not contain that 2035 claim). I only read p. 493 of Ch. 10 of Working Group II because I was writing a paper on food rights and climate change.
So it’s not like “the world” has been misled all along, as those news stories claim. And it looks like the fiasco will shortly clear up any problems or confusions — just as science is supposed to work. Problem solved, except in the media’s bloated head.
Furthermore, even I (seemingly the only reader of page 493 in the yrs before someone else recently discovered it) was NOT MISLED. I noted that the 2035 date seemed pretty cutting edge soon for such large glaciers (and I’m just your average citizen, not a climate scientist), so I looked at the source, and it seemed too flimsy for me to include in my paper, or even to use in my harange about global warming in informal contexts. As much as I rail against scientific conservatism & its fear of the false positive, when I myself am doing something for peer-review, I want my sources on critical and startling claims to be from peer-reviewed sources. Okay I’m the pot calling the kettle black; I’m myself guilty of scientific conservatism.
Anyway, who really knows, maybe the glacial mass will actually shrink from 500,000 km3 to 100,000 km3 by 2035 (as claimed on that IPCC page), since we know that other factors are involved, aside from mere heat. Gravity and break up of glaciers gives us more surface area to melt, and water melting on top, leaking down to the bottom, lubricates the flow and break-up, etc.
And four-fifths of the glacial mass doesn’t melt by 2035, it might happen by 2046 or 2093 or 2157 or later (or never if we get on the dime and drastically reduce our GHGs). Glacier retreat is in (geologically speaking) speedy process now. That we know.
Considering that many laypersons seem to think GW and its effects are so slow as not to be of concern, if they had read and believed that 2035 date at which 4/5 of Himalay glaciers would be melted, they would have possibly thought — “That’s so far off intp the furture, too slow for my concern.” It seems those types of lay perceptions are in more dire need of change, than the 2035 claim (which should be corrected, mind you).
So the real Q is why certain media make such big deals out of such things and why they present them in such ways (need to intrigue readers and sell product, who’s funding them, etc), and how many readers/viewers are they able to bamboozle into thinking GW is not real or threatening, and thus into stopping (or not starting) efforts to reduce GHGs. That’s the big, important story.
“Unfortunately, another black eye for the IPCC and its chairman, Dr. Pachauri.”
Funny how there’s never a black eye for the denialist talking heads like Monckton:
http://www.altenergyaction.org/Monckton.html
when he gets it wrong, or McIntyre:
http://scienceblogs.com/deltoid/2009/10/mcintyre_had_the_data_all_alon.php
Or, indeed, Lindzen and Choi:
https://www.realclimate.org/index.php/archives/2010/01/lindzen-and-choi-unraveled
Jim Bullis, Miastrada Co. says: 18 January 2010 at 8:14 PM
So if I take your meaning correctly, absorption of heat by the oceans will moderate effects of AGW for us air breathers.
That does not seem controversial. It also has been taken into account by models. Gavin could say with authority, but my lay perspective says we’d be looking at wildly inaccurate model predictions if the gross effects of warming the oceans were not taken into account.
Regarding “burping heat”, right after posting that I realized it’s not really necessary to go digging for confirmation of that, we’re in an El Nino year after all. The processes manifested there are drivers of variability at least on a regional scale, and those processes include shedding of heat energy from the ocean. Without a fully developed model it does not seem reasonable to hypothesize that heat released from the ocean during an El Nino event is exactly balanced by absorption elsewhere on a time scale of months, so perhaps an El Nino event drives variability on a global scale too.
Seeing as how models have apparently successfully taken into account the lump effect of heat absorption by the oceans, it does not seem to me that we’ll see an additional buffering effect beyond what we’ve already got unless we can hypothesize some sort of more rapid overturning or other transfer effect that will speed the arrival of heat at deeper levels of the ocean.
An increased vertical thermal gradient seems a likely candidate for increasing the rate of transfer of heat into the deep ocean, which is what I think you might be driving at.
As I said earlier, looking at the ocean as a lump we should see absorption of heat in the ocean decrease, albeit slowly, if again we’re prepared to look at the ocean as a lump. It seems reasonable to imagine this would be offset by speedier transfer of heat downward if indeed a vertical thermal gradient is increased over time.
What’s the net result of those temporarily competing effects? Is that modeled? Maybe that’s the ultimate answer you’re looking for.
El Nino and like events tell us that over a shorter period the ocean is no entirely lumpen and is capable of displaying dynamic effects. Are bulkier dynamic processes accounted for? I don’t know, to me it seems it’s probably not a good idea to count on that sort of cavalry charge.
Jim Hansen:
“The GISS analysis assigns a temperature anomaly to many gridboxes that do not contain measurement data, specifically all gridboxes located within 1200 km of one or more stations that do have defined temperature anomalies.
The rationale for this aspect of the GISS analysis is based on the fact that temperature anomaly patterns tend to be large scale.”
How do we reconcile this with the fact that there are gridboxes right next to each other that have a difference of 4.5 C for the annual mean anomaly in the HadCRUT data.
[Response: But mostly they are not. You can do the spatial correlations for yourself – it doesn’t have to have an r^2 of 1.0 to be useful. – gavin]
Am I doing something wrong?
The top right half of the paper is hidden by the recent comments/links section.
Any suggestions would be appreciated.
[Response: what browser are you using? – gavin]
Don projects into others: “You, BPL, and Dr. Hansen apparently want the last decade to be a statistical fluke,”
Nope, just that there’s nothing proving the models are wrong in the last decade.
E.g. 2009 and 2005 are as warm or warmer than 1998. Despite a “perfect storm” of warmings that even your friend Bob Carter said that using 1998 was wrong (admittedly it was wrong to use it to show warming because of a confluence of factors).
That was before 2005, mind, and the “it’s been cooling since 1998” meme got thought up.
Don Shor says: 19 January 2010 at 1:11 PM
If it’s adroitly handled by one party and fumbled by another, the world can indeed be misled over an trivial error. In this case an error has been exploited to mislead. Thus “world misled” is quite true, in a twisted sort of way.
Combating bad faith is always done from a defensive position; fiction is impossible to anticipate in detail.
[Response: what browser are you using? – gavin]
IE version 6.0
[Response: Can you email me a screen shot (at contrib -at- realclimate.org) and I’ll investigate. In the meantime – upgrade to Firefox! – gavin]
Tom, your conclusion doesn’t follow. There is ample support in the literature (and, though I don’t have time to check this moment, I’m willing to bet in the AR4 bibliography too) for the statement that you quote, that “Himalayan glaciers “could decay at very rapid rates” if warming continued.”
Don, the world may have been “misled” by the error, but clearly unintentionally so. That’s what you meant, I presume?
Tilo, yes–as I understand it, there are differences in detail between the Hadley and GISS algorithms, so yes–the anomalies at specific locations can vary a bit. (Glad you figured that out.) But the graph also shows that the coverage difference can account for the difference in the global value–and demonstrates that the global value is robust to those differences.
280 Completely Fed Up says:
19 January 2010 at 1:58 PM
Funny how there’s never a black eye for the denialist talking heads like Monckton [etc]
What’s your point?
Monckton (who I’ve never read), McIntyre, and the others speak for themselves only, and don’t even purport to represent any body of evidence.
“Because of its scientific and intergovernmental nature, the IPCC embodies a unique opportunity to provide rigorous and balanced scientific information to decision makers. By endorsing the IPCC reports, governments acknowledge the authority of their scientific content. The work of the organization is therefore policy-relevant and yet policy-neutral, never policy-prescriptive.”
re 272 and you know what he’ll consider “still snowing in the Himalayas”?
There is snow hitting the ground.
Don Shor —
There have been four IPCC reports, next one is number five.
None of them have been perfect. The next one won’t be either.
This is how science works.
287
Completely Fed Up says:
19 January 2010 at 2:11 PM
Don projects into others: “You, BPL, and Dr. Hansen apparently want the last decade to be a statistical fluke,”
Nope, just that there’s nothing proving the models are wrong in the last decade.
Nobody (here) said they were. The rate of temperature increase over the last decade has been at the low end of the range of the models.
290 Kevin McKinney says:
19 January 2010 at 2:15 PM
Don, the world may have been “misled” by the error, but clearly unintentionally so. That’s what you meant, I presume?
I hope so. But it’s hard to tell so far exactly what the authors knew and when they knew it. http://rogerpielkejr.blogspot.com/2010/01/stranger-and-stranger.html
#285:
Uh-oh, there goes the neighborhood.
RE #285 & “How do we reconcile this with the fact that there are gridboxes right next to each other that have a difference of 4.5 C for the annual mean anomaly in the HadCRUT data.”
It just occurred to me that the dubbed in warming anomolies could just as well be underestimated as overestimated — maybe the lacking data on the whole tends to be warmer than is dubbed in.
Of course, if the errors are unbiased and unsystematic then they would tend to cancel each other out.
RalphieGM (225) — There is pllenty of evidence, but not all of it can be presented in a short essay.
Don Shor, before stating as though it were a fact that people like Monckton “speak for themselves only, and don’t even purport to represent any body of evidence”
you should try pasting your own belief into the Google search box.
It will pop right up with their sponsors and what they claim as evidence.
“It’s a poor sort of memory that only works backwards.” Paste what you think into Google to see what’s new–and whether your source was reliable.
Lord Monckton Debunks Global Warming
See the SPPI website for details of Lord Monckton’s evidence, scientific papers. scienceandpublicpolicy.org/. You can buy the video DVD …
That’s from “Accuracy in Media” — http://www.aim.org
Who’s “aim.org”? Glad you asked:
Accuracy in Media (AIM) has grown from a one-person crusade to a million-dollar-a-year operation by attacking the mainstream media …
http://www.sourcewatch.org/index.php?title=Accuracy_in_Media
You’re thinking the little lord is speaking only for his own opinions?
He’s moving his lips to the tune of a highly orchestrated PR program.
Try to understand what’s written, and why, instead of casting aspersions Don. You’ll save yourself and others some grief. If you don’t like the melt rate in the Himalaya, check back in a few years or decades. On the other hand, you are quite correct in saying that Monckton and McIntyre don’t represent any body of evidence.
Maybe when y’all are done blamestorming about the latest typo–one that you guys didn’t even find–we can get back to actually considering evidence.