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.
This one is for Barton Paul Levenson.
Have you not considered that another reason for the decline in Krill may be due to the increase in Whale populations (their main food by the way for baleen whales) since the close of whaling in Antarctica? Part of that 30% loss may be just bringing the Krill population back to pre-whaling levels.
RS should have read more.
From the link he gave:
“The “take-home message, “ says Cohen, is that “we can’t assume that elevated CO2 causes a proportionate decline in calcification of all calcifying organisms.””
But RS wants to take home the message that this
a) causes no decline in calcification in all organisms
b) causes no decline in some organisms (if he can’t get you to swallow a)
And later on it says:
“Conversely, some organisms—such as the soft clam and the oyster—showed a clear reduction in calcification in proportion to increases in CO2.”
Do we eat “red and green algae, limpets and temperate urchins”?
And later still
“But there were a couple that didn’t respond to CO2 or didn’t respond till it was sky-high—about 2,800 parts per million. We’re not expecting to see that [CO2 level] anytime soon.””
A couple.
Yeah, that’s enough to keep a viable ecosystem going…
I just heard on NPR that it is so warm in Vancouver that there may not be enough snow for the Winter Olympics. Those who are cold in the US should take a nice warm vacation to the north. On the other hand, the mud ski enthusiasts could do well in the competition.
Steve
“he did specify “practical” consequences,”
But he didn’t say “in my lifetime, for me, here in $WHEREVER”.
A practical consequence is that what he is doing now will harm people living after him.
A car driver doing 50 past a school hits a kid and kills them.
But apart from having to clean the car and take out the dents, the driver is fine.
So why do we prosecute merely *driving* fast past a school???
Why do we expect *good* drivers to care about harm done to SOMEONE ELSE by THEIR driving?
“Richard Steckis says:
21 January 2010 at 11:25 AM
This one is for Barton Paul Levenson.
Have you not considered that another reason for the decline in Krill may be due to the increase in Whale populations”
Have you checked that it’s not the inclusion of more raunchy videos on MTV from Lady Gaga?
OK, that was silly, but you can’t just go out and give “it could be X” if you don’t know whether the change can explain the result you wish to attribute it to.
Doing so is lazy and I can’t be arsed putting more effort into making you look an idiot if you can’t expend at least SOME effort in trying not to act like one.
“Yes and this one is no different. That is why we now have to get out and observe in nature.”
And how do you know what you should be observing in nature if you don’t PREDICT what should happen?
And didn’t Arrhenius do just this? Predict there should be some warming, then we measure that there was?
So isn’t this AGW science really the science you’re complaining that it isn’t?
I’ve got to get off this site and do some work, but–
Don Shor wrote “I guess all of the folks who moved from New Orleans to Houston and other areas — some 25% of the city’s population, by some estimate — are also “climate refugees” whose displacement was caused by climate change?”
Well, maybe, in part at least. As far as I know, there has been no formal attribution of Katrina to climate change, and maybe the methodology to do so doesn’t even exist. So there’s no way to claim “scientifically” that Katrina was a climate change influenced event. And obviously, infrastructure inadequacy and (engineered) wetland loss played big roles.
But it cuts both ways–there’s also no way to prove that Katrina wasn’t influenced by climate change. And on the face of it, I don’t think it’s an unreasonable speculation that, given a generally cooler climate, the “unusually warm” waters that fuelled Katrina from Cat 3 to Cat 5 in about 9 hours might have been a bit cooler too–and that consequently, Katrina might have made landfall with a smaller surge, one that didn’t result in catastrophic failure of the levees.
We need to avoid “false positives” in attribution, but also “false negatives.”
What we can say is that with continuation of the observed sea level rise, a lot of other large cities are going to be in New Orlean’s position over the coming decades. (Mike Tidwell points this out at length in his book “The Ravaging Tide.”) And New Orlean’s position is going to be much worse, particularly as it has been reported that the repairs to the levees–about $15 billion worth!–are such that another Katrina would predictably cause failure. (BTW, the number I found for the direct cost of Katrina was $110 billion–I’m not sure exactly what is, or is not, included in that estimate.)
And they say mitigation is too expensive. . .
CM: #426
“Tilo (#401) counted colored dots in fig. 3 and said:”
I didn’t just count colored dots. I computed the average anomaly values for those dots.
CM:
“No, even if your count is a valid approach, surely it would only say that GISS and HadCRUT gets different results, which was the point of the original post.”
No, it’s not a take your pick scenario at all. HadCRUT gives us results where they have measurements. And those results have a close relationship with those measurements. GISS gives us results that have been produced by interpolation, extrapolation and the UHI algorithms. And those are giving irrational results at the poles. Look at the row of cooled HadCRUT cells in the top 2005 row. GISS has changed them by 6.7 C or more. What could possibly justify such a difference. The point of the article was to explain that the difference between the two data sets was infill. It didn’t exlain why the process gave such drastically different results for cells that were represented by both data sets. And it didn’t explain why the extrapolations were so far from available measured values.
Now look at the top right area of GISS 98 and look at the same top right area of GISS 05. That shows you that there are a bunch of cells up there that have changed their values by +6.7 C in 7 years – when there was no warming for the rest of the globe. Look at the change of the lowest Antarctic line for GISS 98 and for GISS 05. The change is almost as drastic in the + direction and equally as irrational. So the GISS interpolation extrapolation algorithms don’t make sense – even when they are compared to themselves.
CM
“It wouldn’t say which one of them better reflects reality.”
If you look at the middle areas of both HadCRUT and GISS it looks like there is a smoothing effect that is done due to the GISS algorithms. Some hot HadCRUT cells are cooled and some cool HadCRUT cells are warmed. There is no obvious bias that I can see. So I think that we could say that if one reflect reality, the other probably does also. This seems to break down at the poles. There is definitely a GISS bias. The outcome looks very very different from the available HadCRUT cells. And we have to assume that the available HadCRUT cells are a product of the available stations. But the GISS bias doesn’t look like it’s a one sided bias. It looks like it’s more of an effect amplification bias. In 1998 it produced a couple of polar areas that look like they are a little cooler than they should be. And in 05 it looks like they produced polar areas that are much hotter than they should be.
[edit]
[Response: Tilo, this is beyond silly. The full data sets are available online where you can analyse them exactly instead of getting into dumb arguments about pixels and contour intervals. Then you can do exactly the same exercise as Hansen did and make a proper determination of whether the extrapolation is valid or not. You will never do that from squinting at two low resolution jpgs on a blog post. If you want to make serious points, do serious analysis. – gavin]
If I may make a humble suggestion to my fellow commenters here, the release of the NASA-GISS data provides an opportunity to educate the public about the science, and to at least highlight the bogus-ness (is that a word?) of the “global cooling” claim. There is major legislation pending here in the US and we should make our voices heard.
We are scattered around the world and while we may not have the stature of someone like Gavin but we can at least make the scientific case to our local newspapers. I wrote a letter to the editor of our local paper that I believe will be published (the editor just called me for confirmation), and there are so many knowledgeable and persuasive writers here who can do the same, if you are not already doing so. We can send copies to our elected leaders; it may help.
OK, enough advocacy – back to the science.
As Igor points out:
Steckis: “Organisms displaying such improvement also included calcifying red and green algae, limpets and temperate urchins.”
Mmmmm! Those do sound tastey, don’t they!!!
Too bad about things we actually could eat.
“Conversely, some organisms—such as the soft clam and the oyster—showed a clear reduction in calcification in proportion to increases in CO2.”
Apologies if this has been answered already (I can’t read all 457 comments, most of which seem to be off-topic!) but how does Hansen justify the dark red area at the North pole in fig 3? And the corresponding spike at 90N that is not in this article but is quite striking in the plot if you go to the GISS web page. Clearly this cannot arise through interpolation. I don’t think he has explained this adequately.
[Response: You are mistaken, there is nothing else going on except interpolation. Look at the maps with the 250km radius of influence and you will see that the northernmost stations were extremely warm in December. The North Pole number in the 1200km map is smaller than the value of the northernmost latitude in the sparser dataset as you would expect from an interpolation routine. – gavin]
Richard Steckis, your sources don’t support your argument. Tough luck – citation-mining isn’t enough. You have to read it, and make sure you don’t ignore all the details.
From your own link:
“The bottom line is that we really need to bring down CO2 levels in the atmosphere.”
FU – “A practical consequence is that what he is doing now will harm people living after him.”
As you obviously have no idea what he’s doing now, that’s total assumption, ignoring what he actually said, which seemed to me to indicate he was living at a way lower consumption level than yer average yank. This site is about AGW globally and historically and scientifically, but that doesn’t preclude individual, personal, political, practical level discussion does it? Allow for folks who already have a lifestyle way less problematic than your countrymates but want to understand practical aspects of how they might contribute to a solution, beyond consuming different technology.
It’d be helpful to see a little less of the attack dog mentality in the comments here. Some one questioning in an apparently naive way isn’t necessarily a denialer, or attacking the science or the scientists or humanity, they’re searching for understandable information and direction – and some can’t express themselves any more clearly than your usually cryptic offerings. What relation does speeding in a school zone bear to his question about time scales and a possible personal response to the constant predictions of disaster and mayhem from some concerning AGW? do you know he even uses a car much or at all?
Gavin, I don’t think this can be right. The bit above Svalbard is pale orange in the masked version. Then it goes to dark brown in the final version!
Secondly, if it is just interpolation, why does Hansen speak of ‘interpolation and extrapolation’?
[Response: Psychic I am not, but the NP number is interpolated from surrounding stations. – gavin]
RE #230, Richard, &:
You sound exactly like my senator in her responses to me — Sen. Kathryn Bailey Hutchison (R, TX), the most highly paid politico by the oil industry. See her “environmental record” at http://en.wikipedia.org/wiki/Kay_Bailey_Hutchison .
I hope you’re getting also something out of it, and that you don’t have grandchildren to be concerned about.
“Some one questioning in an apparently naive way isn’t necessarily a denialer, or attacking the science or the scientists or humanity,”
Someone questioning would be better served with the “Start Here” button in most cases.
And so many of those turning up with doe-eyes then turn around when answered in a way that shows AGW is robust to their query, they then turn all attack dog.
Guys, the images are not the data. The images are low-resolution representations of the data. You are “looking at the finger, not at the moon.”
Please do what Gavin suggests and look at the data.
[Response: I doubt that will help. He appears to think that HadCRUT mask is the same thing as the HadCRUT temperatures and thinks that the interpolation is changing HadCRUT cold temps into warm temps. However, it’s obvious to me that the ‘cold’ boxes in question are SST data, not met station data, and thus come from two different sources Reynolds vs. HadISST2. Thus the differences in that location between GISTEMP and HadCRUT are not due in the slightest to interpolation issues, but to source data issues – and I’m going to guess – the difference in how the two SST products deal with partially ice covered ocean. – gavin]
Richard Steckis – You won’t like this one either.
in situ study confirms predictions of deleterious effects of elevated pCO2 on ecosystems
http://www.bioexpress.ac.cn/upload/20080704-nature07051.pdf
oh yes, my favorite for the denialists, so listen attentively too Mr.Steckis: CO2 up 38%, nutritious value of wheats due that 38% increase in atmospheric CO2, 8% down. 9 Billion it won’t be by 2050, talking about the successor to homo erectus!
Gavin:
“The full data sets are available online where you can analyse them exactly instead of getting into dumb arguments about pixels and contour intervals.”
Actually, I’ve been doing just that. I’ve been looking for stations that justify the extremes in extrapolation and I can’t seem to find any. The one that comes closest and that covers 98 and 05 and is way way north is Vize Island. It has a difference of about 4.5 C between 98 and 05. But that’s still not the 6.7 C between 98 and 05 that the chart shows. Much more typical for the far north stations on the Russian side is a difference of 2 to 2.5 C between 98 and 05.
[Response: It’s because the differences are in the SST not the stations data at all. The clue is in the fact that there isn’t any land there. It’s got nothing to do with any interpolation procedure. – gavin]
If GCMs had predicted the cold winter, this all might have a hint of legitimacy. However, The Met Office forecast a warm winter, continuing a long streak of seasonal mispredictions.
[Response: Seasonal forecasts are a whole different set of models, a different set of problems, and different people doing it – it has very little (i.e. nothing) to do with either temperature records or climate projections. – gavin]
Richard Steckis & others — This paper
Atmospheric CO2 concentrations during ancient greenhouse climates were similar to those predicted for A.D. 2100
http://www.pnas.org/content/107/2/576
suggessts, at a minimum, that we cannot be certain that atmospheric CO2 levels were ever much above 1000 ppm.
@443
So all we know is at least 7 percent of the known species don’t have problems with acidification.
And their take-home message is still:
“The bottom line is that we really need to bring down CO2 levels in the atmosphere.”
Gavin:
“He appears to think that HadCRUT mask is the same thing as the HadCRUT temperatures”
No, I think that the HadCRUT mask is a mask that takes the HadCRUT gridcells with no coverage and then changes the corresponding GISS gridcells to also have no coverage. Do I have that wrong? But if I am right, then why do GISS gridcells that are not removed by the HadCRUT mask change their values?
Gavin:
“and thinks that the interpolation is changing HadCRUT cold temps into warm temps.”
No, I’m looking at HadCRUT cells to give me an idea of about what the measurements for the GISS gridcells would be if they had not been run through the GISS algorithms. I’m then assuming that the difference between the GISS gridcells and the HadCRUT gridcells is mostly due to the algorithms.
“However, it’s obvious to me that the ‘cold’ boxes in question are SST data, not met station data, and thus come from two different sources”
Interesting point. You may be right about that. I can’t find the land based stations that would justify those cool cells in HadCRUT. I was trying to figure out if the difference might be USHCN adjustments. Your explanation is more likely. But I wonder, if SST data is available for that area, why wouldn’t GISS also use it instead of extrapolating to the sea from the land. When I look at the rest of the globe I don’t see any sharp temperature distinctions when moving from land cells to sea cells. If having partially ice covered ocean produces a difference in sea surface temperature, then is it appropriate to extrapolate land based values to the ocean.
[Response: Have you read any of the papers on GISTEMP? All of this is explained. – gavin]
Gavin:
“It’s because the differences are in the SST not the stations data at all. The clue is in the fact that there isn’t any land there. It’s got nothing to do with any interpolation procedure. – gavin]”
Sorry Gavin, we may be talking at cross purposes now. In the post you are addressing I was comparing GISS 98 to GISS 05. If you look at the area north of Siberia, the gridcells show a change from 98 to 05 of 6.7 C for a large group of cells. I was trying to find Siberian stations that justified such a change. But I couldn’t. It looks like 2.5 C is more realistic.
Just to be sure that I haven’t got your answer wrong – might you be saying that those cells are also represented by SST in GISS. And if that is so, then why wouldn’t HadCRUT also have those cells filled with SST data?
[Response: This is like nailing jelly to the wall. I really should be doing something different…. You started off talking about ‘6 boxes’ of cooler temps in HadCRUT being changed by the GISTEMP interpolation. Do I take it that this is no longer your concern? (Perhaps you might want to update them at WTF). Now you are talking about eyeballing the difference between two years, when you could just calculate the difference. There is nothing mysterious here – go look at the code. – gavin]
Re #430. Did the reduction of weather sites change the trend? As D’aleo and Smith seem to contend that there is a bias, have they presented any data to dispute the existing findings? I’m sure data from all sites are available(for a price of course). Proof of this should be incredibly easy (but timec-consuming) to come by if there has been meaningful cherry picking (accidental or otherwise.
On a side note at least the site in Canada mentioned in the article is not in the vicinity of an airport (unlike almost all other Arctic sites in Canada).
[Response: No. – gavin]
I’d like to ask, what is your point to answer schleptics like Tilo Reber or Richard Steckis again and again and again and again. These guys are noise machines: nothing new, just dead-beaten horse corpsesn all over again. Is this some sort of educational stuff, huh?
Tilo,
it’s not a compelling objective argument that it “looks like” the GISS analysis produced polar areas that are much hotter than in your personal opinion they “should be”. And after Gavin’s pointed out that the two using different SST products (#467 and #470), I’m not going to lose sleep about those top-row pixels.
“This statement is wrong on many counts.
1. You are confusing statistical probability (95% confidence) with scientific interpretation.
2. The IPCC is not conservative times 1000 because many scientists who disagree with an interpretation are ignored.
3. We can and should wait until the science is in (and it isn’t) before making any decisions on climate change.
4. The situation is not as urgent as you make it out to be.
5. Why do we have science at all when we have people like yourself saying let’s go with our gut rather than wait for the truth? You are basically saying that gut feelings are more important than the science.
Comment by Richard Steckis — 19 January 2010 @ 12:22 AM”
You needs to do yerself sum larnin’ ’bout risk assessment. Where the worst possible case is bad enough, it must be dealt with. Ex.:
Hurricane coming.
Tides 25 – 30 ft.
House at 27.
Winds at 120 – 150mph.
House good to 135.
What d’ya do?
Here’s ACC:
No mitigation = very changed planet
Mitigation = possibly very changed planet
Deep and fast changes = fair possibility of stabilizing planet at levels close enough to current to not disrupt the planetary system so much that there is systemic change/collapse that we cannot adjust to in a timely fashion.
Given the polls I’ve seen all show climate scientists largely doubting we will succeed in stabilizing at or near 2C above pre-industrial, I strongly suggest you…
Pull yer hed outta yer butte.
And, do some reading on Rapid Climate Change, what we know of tipping points, and non-linear systems.
Tilo, you seem to have missed the point that there is not a one-to-one correspondence between GISS (8000 equal-area cells) and Hadley grid cells (5,184 5×5 degree unequal-area cells.) So there is no “corresponding grid cell.”
Also, you seem to miss the point made by Gavin that the the algorithms use different SST datasets. Ie., GISS doesn’t usually “extrapolate from land.”
See steps 4 & 5 in this discussion:
http://data.giss.nasa.gov/gistemp/sources/gistemp.html
Petro, I’ve been asking myself the same question. Must be addictive, I suppose.
TH says: 21 January 2010 at 3:06 PM
“If GCMs had predicted the cold winter, this all might have a hint of legitimacy. However, The Met Office forecast a warm winter, continuing a long streak of seasonal mispredictions.”
Better to speak from an informed perspective. Before you say another thing, be sure to read this:
http://www.aip.org/history/climate/GCM.htm
Unless you’ve got a solid grasp of the major content of that article, you’re going to be prone to making poor comparisons such as that in your comment.
The title of the essay is already a bit outdated. It’s been mild in the U.S. recently.
http://www.esrl.noaa.gov/psd/map/images/rnl/sfctmpmer_07a.rnl.html
I guess the ice age is over.
Riesz says: 21 January 2010 at 3:44 PM
“I’m sure data from all sites are available(for a price of course).”
Yes, and while I could say I’m mystified as to why doubters don’t substitute money for endless yapping and buy the data, I’d be dishonest.
Doubting meteorologists in particular will be well familiar with sources for data, the commercial limitations on access and distribution of data, yet they choose to tout accusations of incompetence if not conspiracy theories to advance their agenda of doubt.
So no mystery, instead only a couple of alternative interpretations. Either the objective is to deceive, or doubters don’t care to find out what’s really going on because it’ll be contrary to their message.
Pass the hat, doubters. Buy the data, build a case if you can.
Didactylos: “I really wish you hadn’t said that. In essence it means that you are only interested in yourself, and that you are not even slightly concerned about the future welfare of other people.”
Didactylos, first I’m sorry, English is not my native language indeed and I can be misunderstood.
Note first that I asked a precise question just before (it was actually addressing BPL imaginary world : in which kind of scenario would people in 50 years have an almost vanishing fossile consumption AND a catastrophic AGW ? this is a nonsense for me).
Second ; I just try to be honest. I am fairly concerned about other people. Meaning that I try to do as less harm as possible, and I give reasonable amounts of money to charity organizations. I have raised my children honestly, giving them what I think is a good education. But of course it has some limits, I won’t get poor with all my family just for the sake of chinese and Bengladeshi people; and honestly you won’t either, because there are a lot of people NOW (totally independantly of AGW) whose welfare is much less than yours and it doesn’t prevent you to sleep. So I can’t really see the argument that welfare of people in 50 years is much more important than that of currently living people.
But there is more : it seems obvious for you that MY action will have a strong impact on the guys living in 50 years. Hmmm … strange idea after all. The future of GW depends essentially of the amount of fossile fuels burnt above some limit, which is not exactly known but should be around 5 or 600 GtC, say, may be we can offer up to 1000 GtC. But how can I control NOW if people IN 50 YEARS will burn – or not – some 1000 ou 2000 GtC more of fossile -essentially coal actually – and worst, unknown coal. I don’t know AT ALL which people will burn it or why, and how the hell could I influence that in any way , PRACTICALLY ? think of the inverse problem : how can YOUR current standard of living be influenced in any way by what some chinese people did 50 years ago in a far country ????
There is a very, very, very strange theory among the economists : that growth is fixed anyway by some magical law, and that we could change the total amount of fossile we will burn in the future just by adapting energy intensity. That’s a very very strange theory because it assumes that the fuel you don’t burn now will NEVER be burnt, neither now nor in the future , by ANYBODY – and particularly this possible huge amount of coal that nobody knows where it is. But wait .. things have NEVER worked like that ! each time we have made improvement in energy use, we just use this opportunity to produce more goods and a better life for more people, with all the energy we can produce. Not the same wealth with fewer energy, but a larger wealth with the same energy. we have never stopped- to my knowledge – extracting oil, coal, or gas when some was still left in the ground, before they were exhausted. And certainly not under the pretext that somebody did not use it 50 years ago and so nobody should use it again -which is of course totally impossible to evaluate and is most obviously something nobody cares AT ALL. So explain me how anything I can do NOW will have the slightest influence on the welfare of people living in 50 years – or equivalently, please tell me what a chinese guy should have done 50 years ago to improve your welfare now exactly ?
“So explain me how anything I can do NOW will have the slightest influence on the welfare of people living in 50 years”
Cut your energy use, change to non-fossil fuels.
That portion of the population that thinks warmer global temps are a good thing, and don’t think it will have any significant effect might want to reconsider: http://www.npr.org/templates/story/story.php?storyId=120498442
“It’s like our map of the area vulnerable to 27 inches of sea level rise looks like someone took a razor to the state right above Miami and sliced off everything below that,” said Frank Ackerman, a senior economist at the Stockholm Environment Institute, who has studied what impact climate change — and sea level rise — will have on Florida. His model calls for a sea level rise of just over 2 feet by 2060.
Under that scenario, Ackerman says Florida stands to lose almost 10 percent of its land area and the homes of 1.5 million people.
“The zone that’s vulnerable to 27 inches turns out to include a whole lot of buildings that people would probably rather save,” said Ackerman. “There’s residential real estate worth $130 billion in that, half of Florida’s beaches, two nuclear reactors, three prisons, 37 nursing homes, and on and on.”
1.5 million people displaced, two nuclear reactors affected, billions in real estate impacted… no big deal, right? And that’s just in Florida, and assuming only a 27 inch rise in sea level. Extrapolate that over the Eastern seaboard, Gulf Coast, West Coast…then extrapolate that globally…
Don Shor. Please present some evidence. You are saying the Indian government says the fence being built between Bangladesh and India is due to the vague term “national security”…That does not exclude masses of climate refugees. Do they say it is *not* due to climate?
How many reliable sources say it is not due to climate? Below is an Indian government authority (which you conviently chose to ignore) who says Bangladesh climate change refugees are a threat to India’s national security…and everyone agrees the fence is being built because of national security and refugees.
An Indian retired Air Marshal states on record:
“If one-third of Bangladesh is flooded, India can soak in some of the refugees, but not all,” Retired Air Marshal A.K. Singh, the former commander of India’s air force, told a London conference recently. “Low-lying coastal area flooding is a national security issue.” (Scientific American).
If that isn’t the Indian government admitting that climate change refugees from Bangladesh aren’t a national security threat, I don’t know what is.
Scientific American quotes from a native that Bangladesh immigration vs. climate change is such a touchy issue that no one in government wants to talk about it.
A Bangladesh villager interviewed states:
“We are in trouble here. If the water comes up, we will have to move, as well,” said Shushanto, who lost part of her home in a September flood. “I don’t really want to go, but if the situation arises where I have to go, that’s where we’ll go (India).” (Scientific American).
Multiple outside sources investigating in situ, say it is a complex problem including climate refugees and the finishing of the unfinished fence is due to climate refugees.
You are saying that “it ain’t so” with no evidence, and you’re not even personally on the scene in Bangladesh and India talking to witnesses from both countries, nor quoting multiple published sources stating “the fence is not due to climate change” and changing your story (from “Its mostly from blogs”, “there is no evidence” and then to a “common tendency to link everything to climate change, no matter how far-fetched.”) [are all demonstrably false]. I’d say an Indian government official who “fessed up” and interviews with the locals admitting to it is pretty strong.
So where are we I this “discussion”? You say the Indian government is not saying it is not climate change. I have an Indian government official on record directly saying Bangladesh climate change refugees are a national security threat as well as five or six major newspapers here and abroad and a university saying it, villagers saying it is as well as a publishing scientist who is going to lose his credibility, his career and his income if he is lying (see below). He links the fence to climate change.
I do not know if it will help, however a non-peer reviewed paper (published on-line) written by a peer-reviewed publishing author (M. Shahidul Islam) for the University of Singapore who has in the past published in the peer-reviewed journals Quaternary International, 1999 titled “Coastal and sea-level changes during the Holocene in Bangladesh” (24 citations); Bangladesh demographic and health survey 1993-1994 (73 citations); National Institute of Population (73 citations); Biochemical and Biophysical Research Communications 1997 (52 citations), Asiatic Society of Bangladesh titled “Sea-level changes in Bangladesh: the last ten thousand years”, 2001 (15 citations); Bioscience, 2002 (15 citations); Marine pollution, 2004 (9 citations) was also written (on line) mentioning the Bangladesh fence’s “illegal immigrants are believed to be environmental refuges.”
He writes exactly as shown below (including exact paragraph divisions) in 2007:
“The issue of illegal immigration from Bangladesh to India has become a major bone of contention between New Delhi and Dhaka, and many of these immigrants are believed to be environmental refuges. To curb illegal immigration, India has been fencing the porous Bangladesh border. Floods in the Ganges, caused by melting glaciers in the Himalayas and the changing pattern of monsoons in South Asia, displace thousands of people in Bangladesh every year.
The sea-level rise can create millions of environmental refuges across the world. In South Asia, 60 million people live in coastal flood zones.”
Definition of reasonable person links:
http://books.google.com/books?id=hUgwAAAAIAAJ&pg=PA87&lpg=PA87&dq=english+common+law+based+on+a+rational+person&source=bl&ots=KffmbibM6y&sig=ZuMcBL_wXx05ItxJRi4rHmY1qMs&hl=en&ei=K7FYS77FFsG0tgew_fS2BA&sa=X&oi=book_result&ct=result&resnum=4&ved=0CBEQ6AEwAw#v=onepage&q=prudent%20and%20rational%20person%20&f=false
http://en.wikipedia.org/wiki/Reasonable_person
M. Shahidul Islam publication links:
http://docs.google.com/viewer?a=v&q=cache:JcSJv6Jm10AJ:se1.isn.ch/serviceengine/Files/ISN/44524/ipublicationdocument_singledocument/3EE945CD-81AB-461C-8EDC-1007E22952E9/en/28.pdf+M.+Shahidul+Islam+Climate+Change,+Conflict+over+Scarce+Resources&hl=en&gl=us&pid=bl&srcid=ADGEESgKR-0Sxup10LDYFGXClPKBNAXiyZSWut5rnr7RFnuEiAgaZrfpkG1hoHhbAhJcnai83eHLhHIGVcyuk0ceg7XWcfx9aGWVgc1WA-aC8hw-i8eiEywdT4ek1u5JodZaQMHZot8o&sig=AHIEtbTZvU9MJOkC2x7uywm3IXtJsBSjOQ
http://scholar.google.com/scholar?q=M.+Shahidul+Islam&hl=en&btnG=Search&as_sdt=2001&as_sdtp=on
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6WBK-45P0MJK-CH&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&_docanchor=&view=c&_searchStrId=1175857649&_rerunOrigin=scholar.google&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=6c30641140daad304d7f9748165fa5dc
http://scholar.google.com/scholar?cluster=2553622110813658337&hl=en&as_sdt=2000
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V6N-49YCYND-4&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&_docanchor=&view=c&_searchStrId=1175876262&_rerunOrigin=scholar.google&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=897e223d0b1637e70ac676716c582fc0
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V6N-49YCYND-4&_user=10&_rdoc=1&_fmt=&_orig=search&_sort=d&_docanchor=&view=c&_searchStrId=1175884945&_rerunOrigin=scholar.google&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=56bea5a5d70ad6243dcf24b94b94d330
Don’t worry, we’ll have another “Ice Age” next winter! :)
Gavin:
“Do I take it that this is no longer your concern?”
As far as the 6 boxes goes, yes that is still a concern. The difference is huge, regardless of what the reason and the data sources are. I just went to the Reynolds SST site. It looks like Reynolds reports 0 anomaly when an area freezes over. The 6 cells that we are talking about are north of Svalbard and we know that freezes over for part of the year. But if you look at the Reynolds months that do have values, they don’t seem to show an anomaly larger than about 1.5C for any month. And annual average looks to be close to zero. The NASA GISS site says:
“Areas covered occasionally by sea ice are masked using a time-independent mask.”
So I’m assuming that those 6 cells wouldn’t use SST data – at least for GISS. I need to find out what the HadCRUT rules are for using their
HadISST2 data.
Re. the India Bangladesh border fence is due to climate change refugees. Re. Don Shor
Here is some peer-reviewed scientific evidence that the Bangladesh wall is being built against climate change refugees. Here are two peer reviewed articles as well as the one by a publishing scientist published on the Internet.
This is not to mention the 4-5 major newspaper from two different countries and the Canadian University stating this.
“Fencing the border
At the other extreme is India’s 4,095 kilometre fence along the Bangladeshi border. In 1985 a fence along the porous Indian-Bangladesh border was first discussed to stop smuggling, trafficking and illegal immigration (which Delhi estimates at 20 million people annually).128 Construction started in 2002 and was due to finish in mid 2007. The 3.6 metre high, double wire fence, built at a cost 11 billion rupees also serves the purpose of controlling the flow of future forced climate migrants.129
Syed Sajjad Ali (2006) “Fencing the Porous Bangladesh Border”, Worldpress.org, India, 14 December 2006
Climate change and forced migration: Observations, projections and implications
Oli Brown UNDP 2007 (cited by 13) including the the Lancet, 2009, and Norwegian Ministry of Foreign Affairs
The (non-peer-reviewed) article on the Internet by the publishing scientist M. Shahidul Islam entitled “Climate Change, Conflict over Scarce Resources and the Nobel Peace Prize.”
“The issue of illegal immigration from Bangladesh to India has become a major bone of contention between New Delhi and Dhaka, and many of these immigrants are believed to be environmental refuges. To curb illegal immigration, India has been fencing the porous Bangladesh border. Floods in the Ganges, caused by melting glaciers in the Himalayas and the changing pattern of monsoons in South Asia, displace thousands of people in Bangladesh every year.
The sea-level rise can create millions of environmental refuges across the world. In South Asia, 60 million people live in coastal flood zones.”
Published on the Internet by (M. Shahidul Islam) for the University of Singapore who has in the past published in the peer-reviewed journals Quaternary International, 1999 titled “Coastal and sea-level changes during the Holocene in Bangladesh” (24 citations); Bangladesh demographic and health survey 1993-1994 (73 citations); National Institute of Population (73 citations); Biochemical and Biophysical Research Communications 1997 (52 citations), Asiatic Society of Bangladesh titled “Sea-level changes in Bangladesh: the last ten thousand years”, 2001 (15 citations); Bioscience, 2002 (15 citations); Marine pollution, 2004 (9 citations) was also written (on line) mentioning the Bangladesh fence’s “illegal immigrants are believed to be environmental refuges.”
http://www.climate-adaptation.info/wp-content/uploads/2008/09/gechs-report-3-08-disaster-risk-reduction-climate-change-adaptation-and-human-security.pdf
http://scholar.google.com/scholar?cites=12952396060527229659&hl=en&as_sdt=2000
M. Shahidul Islam publication links:
http://docs.google.com/viewer?a=v&q=cache:JcSJv6Jm10AJ:se1.isn.ch/serviceengine/Files/ISN/44524/ipublicationdocument_singledocument/3EE945CD-81AB-461C-8EDC-1007E22952E9/en/28.pdf+M.+Shahidul+Islam+Climate+Change,+Conflict+over+Scarce+Resources&hl=en&gl=us&pid=bl&srcid=ADGEESgKR
Please present some evidence. I did.
Gilles@484 No raindrop thinks that it is the cause of the flood.
Kevin: #480
“Tilo, you seem to have missed the point that there is not a one-to-one correspondence between GISS (8000 equal-area cells) and Hadley grid cells (5,184 5×5 degree unequal-area cells.) So there is no “corresponding grid cell.””
No, I got that part. But the charts in figure 3 are all 72 by 36, having 2592 gridcells. The gridcell resolution on the chart is a problem however. A dark red cell can have a value of 3.01 or 6.5. Big difference when you are trying to figure out if it is a reasonable extrapolation.
Kevin:
“Also, you seem to miss the point made by Gavin that the the algorithms use different SST datasets. Ie., GISS doesn’t usually “extrapolate from land.””
I went and looked at the Reynolds SST data that GISS uses, and it has values of 0 for iced over areas. Also, GISS says that they don’t use SST data from areas that are covered with ice for any part of the year. The oceans at the northern part of Russia freeze right to the edge of the land. So I don’t see how there is any choice but to extrapolate from the land to the sea ice if your are going to get that coverage. The cool cells that HadCRUT has north of Svalbard for 05 are in an area that freezes over for part of the year. I think that means that GISS would not cover those areas using SST. I don’t yet know what HadCRUT does concerning areas that ice over for part of the year. Okay, I’m out of here for a little while. I need to find some HadCRUT info.
well we aussies are not as stupid as i look it seems
a morgan poll showed that while 31% of those aged 14+ feel that the effects of climate change might be overstated. only 3.5% of those do not accept the science.
this gives a figure of only 200,000 nationwide
Schwartz new paper , temp should have increased by 3.8degC has them all crowing again,
490
Richard Ordway says:
21 January 2010 at 8:27 PM
Re. the India Bangladesh border fence is due to climate change refugees.
First, thanks for the links. They were interesting to read.
But they tend to show how unprovable, unverifiable conclusions take on the patina of being verified, peer-reviewed facts.
From the links you provided:
The Oli Brown article makes the following statement: “The … fence….also serves the purpose of controlling the flow of future forced climate migrants” with a footnote 129. That footnote goes to a blog post. The blog says nothing at all about climate change as a reason for the fence.
Here is what you DO find at the blog article at footnote 129:
http://www.worldpress.org/Asia/2603.cfm
“In 1985 the government of India mooted the idea of constructing a fence along their common international frontier in the eastern part of the country. Subsequently, after deliberations at the highest policy-making levels, the decision was made to erect barbed wire fencing along entire common boundary with Bangladesh. The move to put up a barrier along the border was made to check illegal infiltration, contain smuggling and to frustrate militants who were using the border route to cross over into India to commit subversive acts.”
Is there agreement on this issue in India and Bangladesh? From another article:
“This question of migration to India is one of the topics that is a heated debate in our country, because we believe people are not moving to India,” said Abdul Kalam Azad, a senior research fellow at the Bangladesh Institute of International and Strategic Studies. He and others describe climate migration as a distant issue earning an inordinate amount of media hype.
Bangladesh officials insist that they haven’t detected any new dynamic in such back-and-forth border crossings.
“Even their tigers traverse the same territory,” said Azad. “Given the fact that there’s a porous border, there could be some possibility that people are moving to India, but moving for a job and coming back.”
Bangladesh officials, meanwhile, say the fence and everything it represents are just distractions. The country needs to build embankments, they say. It needs cyclone shelters and rice research. And it needs to address the already explosive internal migration to its capital city, Dhaka, an issue that rarely makes it into dramatic climate change reports.
http://www.eenews.net/special_reports/bangladesh/part_four
The Mr. Islam who wrote the overview for the ISAS brief does not appear to be the same Dr. Islam you are citing at the other links. This Mr. Islam is an economist. He does indeed say “to curb illegal immigration, India has been fencing the porous Bangladesh border.” It is his analysis or opinion that “many of these immigrants are believed to be environmental refugees” but he provides no evidence for this.
Moreover, it is neither provable nor falsifiable. They are just as likely to be economic refugees. Will rising sea level make more of them try to cross the border? Perhaps, if no adaptive strategies are employed. But there is no evidence whatsoever that this is a primary or secondary reason that India embarked on their border fence.
“You say the Indian government is not saying it is not climate change.”
The fence is to prevent illegal immigration, smuggling of weapons and narcotics, and block the movement of terrorists. That is usually the purpose of barrier fences. Any other purpose is being ascribed to the Indian government without factual basis.
India has built a 300+ mile fence along the border with Kashmir. Is that to prevent climate refugees? They are considering one along the border with Pakistan.
Here is why governments build separation barriers: http://en.wikipedia.org/wiki/Separation_barrier#Current_barriers
Does this mean I believe that rising sea level will not be a problem for Bangladesh? Of course I don’t believe that. Bangladesh will need to develop adaptive strategies for sea level rise (regardless of whether the nations of the world agree to reduce CO2 output). Otherwise they will continue to have the calamitous human disasters associated with poverty and lack of infrastructure in low-lying flood plains that they already have on a regular basis.
@John Byatt #493. We aussie women seem to be holding the flag for climate change. And we older aussies are a bit slow to follow suit, compared to the younger folk :D
The trends are falling unfortunately, but this issue will not be front of mind all the time. My thinking is it depends to some extent on the weather. This summer has not been as difficult so far as last year was (despite still getting hottest days and nights), at least in the south east (where a lot of the population lives) and not as many big fires so far. With the rain and subsequent growth, next year might be a very difficult fire season, especially if it dries out before next summer. That will remind people of climate change again.
Unfortunately we are getting too used to breaking ‘hottest day’ and ‘most hot days’ records in this part of the world. It’s becoming the norm. If we don’t keep breaking new heat records every week in summer, many people think it’s getting cooler :D
http://www.roymorgan.com/news/polls/2010/4459/
After my previous post I got to thinking, people really only sit up and take note of events that affect large populations. Eg South eastern Australia has had major fires burning huge areas in at least 3 of the past six years (where I live we got the lot), but the one that grabbed the headlines was, of course, the one that devasted outer Melbourne last year. It was by no means the largest area and by no means the only fire that day, but all the fires in Victoria that day (there were several) were totally off the charts in intensity. Other fires in Australia can be larger and just as intense but have little impact because they affect fewer people. (I noticed the fire that burnt the largest area of the state in the past six years was only picked up by the media when the smoke distressed those in Melbourne.) South eastern Australia has just suffered the longest drought, but most people are not aware of the fact and it has had little media coverage. People are becoming aware of the plight of the Murray River (arguable the nation’s most important), but probably not sure why it’s in strife. (It is far from most capital cities.)
Same with Katrina. I expect there have been other cat 5 hurricanes – but that one affected several large population centres, being most well-known for the impact on New Orleans. Other hurricanes that bypass major population centres are quickly forgotten by most people, I expect.
Likewise the recent cold weather hitting some of the most densely populated areas in the world – highly visible.
It’s just the way we are, I suppose.
Don Shor says
“But they tend to show how unprovable, unverifiable conclusions take on the patina of being verified, peer-reviewed facts.”
*You* are the only one making this idiotic statement. Science is never settled.
You don’t have the slightest idea of what you are talking about. We just upgraded from non-peer reviewed newspapers and powerpoints to science with peer reviewed published articles. Our opinions don’t matter any more, it’s what’s in the peer review. That’s how science works, guy. The Lancet citation, the UN publication and 13 citations show that it is a legitimate source.
Obviously, nothing is ever settled in peer review. Much too little has been written on this fence vs. climate change refugees issue in peer review (that I could find) to say that it is strong yet. However, unless you find something in peer review to counter it, it is very good, solid evidence. However the newness of the 2006, 2007, 2009 publications also show that it has not been around long enough to have been tested much scientifically.
Read my lips, show me the money. We just stepped it up to peer review. The ball is in your court now to show a peer review response…not amataterish opinions any more, gibberish and excuses… You obviously do not understand peer review and are applying double standards.
Science accepted two economist’s peer reviewed articles on the climate change science of Mann et al.s MBH98 reconstruction [McIntyre, McKitrick]. You should know better.
If it is in peer review, it doesn’t matter who writes it…that is the beauty of mainstream science and you should know it. Anyone can write and it will be evaluated. So I say again stop playing games…show me the peer review responses and don’t make any more excuses.
The Brown UNDP 2007 paper, and Norwegian Ministry of Foreign Affairs article was published, and quoted Syed Sajjad Ali (2006) and had 13 citations including the world renowned Lancet.
This is also the third time you have changed your position. So what is it? “Only blogs are reporting it?”; “There is no evidence?; “It shows
how unprovable, unverifiable conclusions take on the patina of being verified, peer-reviewed facts.”
486, Witgren: 1.5 million people displaced, two nuclear reactors affected, billions in real estate impacted… no big deal, right?
Are you sure that they can’t build levees? Levees are not unknown in the Netherlands, along the central US rivers like the Ohio, Mississippi, and Missouri, and their tributaries, and in the California central valley. Levees at least 6 feet tall, 20 feet broad and covered in trees are not unknown. By 2030 there ought to be plenty of evidence whether that forecast of a 27 inch rise by 2060 is realistic, and the building of any necessary levees can be started.
More problematical by far are Calcutta, Bangladesh and Venice.
Re: 419 Richard Steckis says:
“There is recent research where it has been observed that many mollusc species have actually increased their shell densities in the lower pH environs.”
What research? Other research points to ocean acidification being harmful to many forms of life.
What Life Forms Will Be Affected?
http://www.global-greenhouse-warming.com/ocean-acidification.html
“Some of the most abundant lifeforms that could be affected by ocean acidification are a type of phytoplankton called coccolithophorids, which are covered with small plates of calcium carbonate and are commonly found floating near the surface of the ocean (where they use the abundant sunlight for photosynthesis). Other important examples are planktonic organisms called foraminifera (which are related to amoeba) and pteropods (small marine snails).
“…free-swimming planktonic molluscs form a calcium carbonate shell made of aragonite. They are an important food source for juvenile North Pacific salmon and also are eaten by mackerel, herring and cod.
“Experiments carried out at sea have shown that the shells of live pteropods dissolve when seawater reaches corrosive levels. Ocean acidification is detrimental to high-latitude ecosystems and highly acidic conditions could develop within decades, not centuries as suggested previously.
“A fall in the numbers of pteropods could cause a chain reaction since they make up the basic food for organisms from zooplankton to whales, as well as for species that are important commercially, such as North Pacific salmon. For example, the plankton on which cod larvae feed would disappear, and the cod would then go too, and something else not linked heavily to the food chain – like jellyfish – will move into their niche in the ecosystem.”
see also:
Planktic foraminiferal shell thinning in the Arabian Sea due to anthropogenic ocean acidification? (update)
http://oceanacidification.wordpress.com/2009/09/24/planktic-foraminiferal-shell-thinning-in-the-arabian-sea-due-to-anthropogenic-ocean-acidification-update/
Published 24 September 2009
(excerpt)
“We found that light, thin-walled shells from the surface sediment are younger (based on 14C and ?13C measurements) than the heavier, thicker-walled shells. Shells in the upper, bioturbated, sediment layer were significantly lighter compared to shells found below this layer.”
see also:
Ocean Acidification and Biological Consequences
http://www.science.fau.edu/biology/koch/Documents/Climate%20Change%20Presentations/Ocean%20acidification.pdf
Conclusion
• Increasing atmospheric CO2 leads to an increase in ocean acidity as well as in dissolved CO2
• Increase in CO2 likely beneficial for photosynthesis and/or calcification of phytoplankton, zooplankton, and aquatic plants
• Increase in CO2 harmful for oxygen-breathing marine animals
• Increase in acidity likely harmful for all, but especially aragonite calcifiers
• Of those, coral reefs and the aragonite pteropod-based Southern Ocean ecosystem are in most immediate peril
Completely Fed up : “Cut your energy use, change to non-fossil fuels.”
is my English that poor or haven’t you read at all what I said ? i just said : I don’t understand why cutting MY fossil fuel use now will influence in any way that of chinese or indian people in 50 years (especially that of coal which we only use in very tiny amounts in France anyway) , and you answer : nevermind, just do it !
do you think really it can be considered as an explanation?
Ray Ladbury : Gilles@484 No raindrop thinks that it is the cause of the flood.
OK, let consider the whole water : What could the 500 millions Chinese people have done 50 years ago to change YOUR life now ?
in other , more scientific words : what is the correlation length and time in the way different people live in the world ?
and how do you insure the fuels that you don’t burn now will never be extracted in the future ?
sorry, I need to be sure of that before cutting anything in my life : somebody answered that he didn’t give his money to present poor people because it was useless. So it’s natural to ask if it is really efficient to cut anything.
Of course, there is no harm in doing conservation and adopting more efficient techniques consuming less carbon – that’s obvious for anybody , even if CO2 would not absorb IR radiation , just because fossil fuels are finite and precious. That’s not an issue; the issue is that I can’t understant why these fuels won’t be use by somebody else, either elswhere (in poor countries that need it), or later (when they will be almost exhausted, and people will fight against their depletion, do you think they will let them in the ground ?)
so I need to understand that, has anybody a (convincing) answer ?