Gray ABSTRACT
Three of the four methods of measuring global temperature show no signs of global warming
Proxy measurements (tree rings, sediments etc) for the past 1000 years
Weather balloons (radiosondes) for the past 44 years
Satellites (MSU Units) for the past 21 years.
The fourth method, surface measurement at weather stations, gives an averaged mean global rise of a mere 0.6°C over 140 years, but is intermittent and irregular. Individual records are highly variable, regional, and sometimes, particularly in remote areas, show no change, or even a fall in temperature.
It is concluded that temperature measurements carried out away from human influence show no evidence of global warming.
The small and irregular rise shown by many surface stations must therefore be caused by changes in their thermal environment over long periods of time, such as better heating, larger buildings, darkening of surfaces, sealing of roads, increases in vehicles and aircraft, increased shielding from the atmosphere and deterioration of painted surfaces.
Global temperature measurements remote from human habitation and activity show no evidence of a warming during the last century. Such sites include “proxy” measurements such as tree rings, marine sediments and ice cores, weather balloons and satellite measurements in the lower atmosphere, and many surface sites where human influence is minimal. The small average and highly irregular individual warming displayed by surface measurements is therefore caused by changes in the thermal environment of individual measurement stations over long periods of time, and not by changes in the background climate.
Since the proxy measurements were all from remote areas and most of the surface measurements were close to buildings, this comparison confirms the likelihood that the increase in the amalgamated surface readings is due to their proximity to human habitation. The statistical comparison is somewhat dubious however, since the proxy measurements do not appear to take proper account of the well established Medieval Warm Period and Little Ice Age which are featured in other studies.
The conclusion that the rise in the amalgamated surface measurements is caused by proximity to human habitation is confirmed if the proxy measurements are continued to the present day
Most of the observed warming over the last 50 years is likely to have been due to the increase in greenhouse gas concentrations.
The existing dilemma can be traced to the pioneering work of Spencer and Christy 5
(1990). They compiled a record of satellite-derived tropospheric temperatures and noted 6
that the rate of warming from the satellite record was negligible, especially when 7
compared to surface temperature increases. This curious result was most prominent in 8
the tropical and subtropical regions (Fig.1). Spencer and Christy (hereafter referred to as 9
the University of Alabama at Huntsville Team --- UAH) took advantage of the 10
Microwave Sounding Unit (MSU) aboard NOAA polar orbiters. The MSU data provided 11
an all-weather integrated measure of temperature for various atmospheric layers. There 12
were four MSU channels, and their weighting functions are depicted in Fig. 2 for 13
channels 2 and 4, for both the MSU and the Advanced MSU (AMSU) instrument. These 14
two channels have been used to depict both tropospheric and stratospheric temperature 15
trends. UAH derived a synthetic channel called MSU2LT which was formed by 16
differencing view-angles of MSU2 and AMSU5. For the lowest layers, the microwave 17
data are affected by changes in surface emissivity, but above the surface layer this is not a 18
factor. Hence some of the MSU2LT signal comes directly from surface emissions: about 19
10% over ocean and 20% over land. Over land the radiances are affected by changes in 20
moisture, and over mountains even more signal comes from the surface, so MSU2LT 21
values, although they are weighted for the lower half of the troposphere are subject to 22
increased noise over mountainous terrain, including the Himalayas, Greenland and 23
Antarctica. However, UAH also compute a MSU2 temperature, which reflects the mid 24
and upper troposphere although some stratospheric emissions are included. 25
26
Trends in channel 4 have been produced and show the marked cooling in the lower 27
stratosphere that have been linked to ozone depletion and increases in greenhouse gases 28
(IPCC, 2001). Such trends influence MSU2, so examination of these other channels is 29
also needed to provide confidence that the ozone signal is being properly simulated. It 30
would also provide evidence as to whether the volcanic signal (especially the aerosol 31
signal of stratospheric warming) is correctly included in models. These trends are quite 32
large relative to any observational uncertainty, but understanding the causes of these 33
trends is linked to understanding tropospheric and surface trends. 34
35
Several other issues emerge, however, when assembling a homogenous record of 36
tropospheric temperatures. Each of the eleven satellites used to measure temperature 37
since 1979, has unique, local sampling times that have changed over its lifetimes. This 38
introduces a diurnal temperature bias, even for temperatures well above the surface layer, 39
and substantial adjustments are required to homogenize the data (Fig. 3). Moreover, each 40
sounding unit on the various satellites has some calibration uncertainties that had to be 41
assessed. The errors in the calibration of MSU have been addressed through numerous 42
analyses (Mo et al., 2001; Christy et al., 2002; Wentz et al., 2001; Mears et al., 2002). 43
44
DISCUSSION DRAFT
7
Wentz et al. (1998) found that in addition to biases related to calibration and changes in 1
diurnal sampling there were biases introduced into the data due to decays in satellite 2
orbit. Episodic solar wind events reduce orbit altitude, and this significantly affects the 3
tropospheric temperature trends, especially those of the low to mid troposphere. This 4
correction was applied by the Wentz team (hereafter referred to as Remote Sensing 5
Systems --- RSS) in their satellite derived temperature trends and also applied by UAH in 6
the latest versions (D and 5) of their data sets. Since 1995, UAH have at different times 7
calculated the 95% confidence interval of the decadal trend of tropospheric temperature. 8
These estimates range from 0.03°C/decade to 0.06°C/decade, and the UAH temperature 9
trends during 1979-2001 for the two tropospheric layers MSU2LT (surface to about 10
400hPa) and MSU2 (approximately Sfc to 100hPa) are 0.06 and 0.01°C/decade, 11
respectively. In contrast, MSU2 as processed by RSS finds a warming of approximately 12
0.10°C/decade. 13
14
The difficulty of adequately resolving the temperature trend issue is attested to by the 15
number of revisions to the original data set of UAH and the magnitude of the corrections 16
to the original data that are required (Fig. 4). UAH have just issued version 5 of their 17
MSU temperature record (5 revisions over a 13-year period). RSS, in work submitted for 18
publication, has just released version 1. The rate of warming estimated by from these 19
two science teams is significantly different, despite the dedication of each team to 20
produce the most accurate temperature time series possible. There are at least two 21
differences in the techniques applied to generate the respective time series. First, to 22
correct diurnal drift errors, UAH rely on adjustments derived from satellite measurements 23
themselves made at the appropriate diurnal time slots while RSS employs information 24
from a high-resolution climate model simulation (Fig.3) to apply appropriate corrections. 25
Secondly, the instrument calibration adjustments depend upon temperature differences 26
observed by two satellites simultaneously. RSS use all periods of simultaneous 27
observations while UAH set thresholds to eliminate some overlaps e.g., minimum of one- 28
year overlap and a minimum level of error reduction during the overlap. The resulting 29
calibration adjustments for each instrument are quite similar between the two techniques 30
except for one satellite, NOAA-9 which had short overlaps with other satellites (Fig. 5). 31
The difference in the adjustment for NOAA 9 accounts for about 65% of the total 32
difference of the two MSU2 trends. Currently, RSS and UAH are sharing data and 33
computational algorithms to help explain the difference. 34
35
UAH, in searching for independent methods to assess error statistics, compared their 36
satellite record with radiosonde (weather balloon) instrumental data and with radiosonde- 37
guided datasets such as the global analyses produced by the National Centers for 38
Environmental Prediction. UAH contend that the similarity of temperature trends 39
between the radiosonde-based data and the satellite-derived temperatures from UAH is 40
important corroborative evidence to help bolster the confidence in the tropospheric trends 41
produced by their team. In these UAH comparisons, controls were established to 42
eliminate stations with inhomogeneities. However, in large compilations of radiosonde 43
data, complications arise, because the weather balloon data are also subject to time- 44
dependent biases because of numerous changes in instrumentation, site location, 45
proprietary calibrations and adjustments, and ground-station processing methods. These 46
DISCUSSION DRAFT
8
changes are known to have introduced significant time dependent biases in the 1
temperature record, most clearly visible in the stratosphere, and corrections are not free 2
of error. For example, Free et al. (2000) reported on the results of several different 3
research teams who attempted to adjust the weather balloon data for time-dependent 4
biases. Inter-comparison of the various adjustments applied by the different teams 5
showed considerable disagreement among the teams related to both the timing and 6
magnitude of adjustments required (Fig.6) during both the satellite and pre-satellite era. 7
[Note: If two teams identify a discontinuity at a station separated by as much as five 8
years within any pentad, this would be considered agreement, at least in terms of 9
calculating multi-decadal trends (Fig. 6)] Despite these problems, the trends from UAH 10
compare favorably with the radiosonde temperature trends. The greatest agreement is for 11
the lowest layer temperatures where radiosonde inhomogeneities are smallest. Other 12
investigators (Wentz et al., 2002; Santer 2002) do not consider the UAH record to be 13
completely independent of the radiosonde record, particularly with regards to decadal 14
trends. Many of the radiosondes used by UAH are in the temperate Northern 15
Hemisphere, where the RSS and UAH results are quite similar, although UAH’s 16
comparisons with the trends in the tropics also show exceptional agreement.
GLOBAL TEMPERATURE FROM WEATHER BALLOONS
Weather balloons (radiosondes) have been measuring temperature in the lower atmosphere since 1956. There are three sets of records which agree fairly well.
Figure 7 shows the temperature record of weather balloons (HadRT2.0 T2LT) of Parker et al (1997, updated). It is plotted together with the satellite (MSU) measurements which closely agree and are discussed below.
It will be seen that the readings fell below zero between 1960 and 1980, but rose again to the level of 1956 until the present day. These results have been interpreted as showing a temperature rise, but the fluctuations are likely to be due to natural variability. WHAT ARE THEY? The overall change over the 1956-2000 period is surely zero.
Similar remarks apply to the results of Angell (1999). He tries to argue that the top series in Figure 8 show a rise similar to that of the surface measurements; but in fact they actually show no rise at all since 1956, but fluctuations down and then up.
Vincent Gray has written that:
Quote:The models predict increased warming, equally, at both the North and South Poles. The measurements show that the two poles are completely different. The North Pole is warming the South Pole is cooling. The models predict much greater warming than is observed, and the only way they can get out of it is to assume a large cooling influence of clouds and aerosols, Since these are concentrated in the Northern Hemisphere, there should be greater net warming in the South than in the North. The observations show the opposite.
But, the models can, and do, account for lots of warming at the Arctic and not much at the Antarctic.
Polar Amplification
http://www.realclimate.org/index.php?p=234
Quote:The failure of the Antarctic to warm is pretty well understood. It is linked to the marked strengthening which has occurred in the southern annular mode. The "southern annular mode" is a fancy name for the strength of the Antarctic low pressure trough and westerly winds (the roaring forties, furious fifties, screaming sixties).
... Over the last 30 years we have seen a very marked intensification of the trough - most of this happened in a short period of time from around 1970 to 1990. This is believed to be due to the loss of ozone in the polar stratosphere which caused a very strong cooling of the stratosphere and upper troposphere over the Antarctic. This cooling lead to a strong increase in the temperature gradient between the equator and poles, which through the dynamics must strengthen the westerly winds (this is summarised in a fairly basic dynamical equation called the "thermal wind" relationship).
The strengthened westerlies has a number of effects. These include enhanced warming on the northern side of the trough (the trough typically being near 65S). This explains the spectacular warming over the Antarctic Peninsula (which is occurring much faster than one might expect from the simple greenhouse effect). On the southern side, the reverse happens; i.e. cooling.
For the last 20 years of so, this cooling has been sufficient to offset the enhanced greenhouse effect. This is a great example of the thermodynamics (temperature changes) and dynamics (winds etc) operating in different directions. Another effect of the stronger westerlies is that the increase the equator wards drift of sea ice (through a process called Ekman drift) which probably explains why sea ice in the southern hemisphere appears to have retreated extensively from around 1900 to 1970 and stabilized and in fact expanded subsequently.
There is a real cautionary tale here about non-linearity’s in climate change.
There is also a real cautionary tale in the new paper by Keppler et al. in science journal Nature as summarized in the Editorial:
Quote:The unexpectedly high levels of the green-house gas methane over tropical forests, and the recent decline in the atmospheric growth rate of methane concentrations, cannot be readily explained with the accepted global methane budget. Now a genuinely surprising discovery provides a possible explanation for these phenomena, and may have implications for modelling past and future climates. It was thought that methane formed naturally only in anaerobic conditions, in marshes for instance. In fact living plants, as well as plant litter, emit methane to the atmosphere under oxic conditions. This additional source of methane could account for 10-30 percent of the annual methane source strength and has been overlooked in previous studies.
Vincent Gray has remarked with respect to this new finding that:
Quote:The answer to the fact that climate models cannot simulate actual global temperature change may be due to a fact I have been emphasizing for many years. The models all assume that greenhouse gases are "well-mixed", however, they are not "well-mixed", so that temperatures cannot be adequately calculated by using average greenhouse gas concentrations. You should use actual concentrations over the particular region. ... Of course, average methane concentrations in the atmosphere have apparently stabilised, so this present scare does not add any extra greenhouse gases to the atmosphere. It does cast into serious doubt current models supposedly relating emissions of methane to atmospheric concentrations, though.
The answer to the fact that climate models cannot simulate actual global temperature change may be due to a fact I have been emphasizing for many years.
This statement is counter factual. The important greenhouse gases are very well mixed in the troposphere. Models do broadly simulate the distribution of temperature change when they include greenhouse gases, aerosols, ozone, solar variability, and volcanism. They do not when you include greenhouse gases only; this is hardly surprising as greenhouse gases lay down the broad pattern of warming, but the local details are often laid down by the lesser forcing agents.
I am surprised that the various statements being made attacking the mainstream science are not backed up by reference to any studies which compare modern climate model simulations with observed warming patterns. Such studies do exist... Surely, the overturning of a 100+ year old theory requires some evidence?
Yes, Mr. Kuvasz- I read your posts and respond to your links but you seem to be actually frightened to respond to my evidence. Because of that, I will repost my evidence. Would you be so good as to attempt to rebut it? Now-from your link_ You see I do read them--
The most commonly considered indicator of climate change is the surface air temperature. Extensive efforts have been made to examine the trends in global and regional mean temperatures over time [Ghil and Vautard, 1991; Hasselmann, 1993; North and Kim, 1995; North et al., 1995; Schlesinger and Ramankutty, 1994] and in the global patterns of temperature change [Hegerl et al., 1997; Hegerl et al., 1996; Jones and Hegerl, 1998; Santer et al., 1995
I do hope that you read my post and Okie's post. I will reiterate.
Global temperature measurements remote from human habitation and activity show no evidence of a warming during the last century. Such sites include “proxy” measurements such as tree rings, marine sediments and ice cores, weather balloons and satellite measurements in the lower atmosphere, and many surface sites where human influence is minimal. The small average and highly irregular individual warming displayed by surface measurements is therefore caused by changes in the thermal environment of individual measurement stations over long periods of time, and not by changes in the background climate.
Since the proxy measurements were all from remote areas and most of the surface measurements were close to buildings, this comparison confirms the likelihood that the increase in the amalgamated surface readings is due to their proximity to human habitation. The statistical comparison is somewhat dubious however, since the proxy measurements do not appear to take proper account of the well established Medieval Warm Period and Little Ice Age which are featured in other studies.
The conclusion that the rise in the amalgamated surface measurements is caused by proximity to human habitation is confirmed if the proxy measurements are continued to the present day
IF the most commonly considered indicator of climate change is the surface air temperature( I ALREADY STATED THIS BUT YOU CHOSE TO IGNORE IT--WHY????)
then there is a huge problem--As Okie pointed out in his link, the surface temperatures can be misleading and the satellite temperatures do not, as far as I am aware, show any rise.
The time series shows the combined global land and marine surface temperature record from 1856 to 2005. The year 2005 was the second warmest on record, exceeded by 1998. This time series is being compiled jointly by the Climatic Research Unit and the UK Met. Office Hadley Centre. The record is being continually up-dated and improved. The principal reason is to detect climate change due to global warming through an increase in temperature in the instrumental record. Increased concentrations of greenhouse gases in the atmosphere due to human activities are most likely the underlying cause of warming in the 20th century.
The key references for this time series are:
Jones, P.D., New, M., Parker, D.E., Martin, S. and Rigor, I.G., 1999:
Surface air temperature and its changes over the past 150 years.
Reviews of Geophysics, 37, 173-199.
Jones, P.D. and Moberg, A., 2003:
Hemispheric and large-scale surface air temperature variations: An extensive revision and an update to 2001.
Journal of Climate, 16, 206-223.
The 1990s were the warmest decade in the series. The warmest year of the entire series has been 1998 (El Nino year), with a temperature of 0.58°C above the 1961-90 mean. Nine of the ten warmest years in the series have now occurred in the past ten years (1995-2004). The only year in the last ten not among the warmest ten is 1996 (replaced in the warm list by 1990).
Analyses of over 400 proxy climate series (from trees, corals, ice cores and historical records) show that the 1990s is the warmest decade of the millennium and the 20th century the warmest century. The warmest year of the millennium was 1998, and the coldest was probably 1601.
The Inter-governmental Panel on Climate Change(IPCC) in its most recent report stated:
”most of the observed warming over the last 50 years is likely to have been due to the increase in greenhouse gas concentrations.”
There is also a long record of temperature for Central England. This is based on a paper by Gordon Manley:
Manley, G., 1974:
Central England temperatures: monthly means 1659 to 1973.
Quarterly Journal of the Royal Meteorological Society, 100, 389-405.
This series is being continually up-dated. It shows that 1990 and 1999 have been jointly the warmest years recorded in 341 years over Central England, with temperatures of 10.63°C. Following a warm 2002 (annual mean temperature 10.60°C), 2003 was slightly cooler overall at 10.50°C. The 2004 value was 10.51°C.
The surface temperatures can be affected by the local heating produced by growing, mechanized cities. YOU DID NOT RESPOND TO THIS POINT..WHY?
You also did not respond to the problem pointed out by both Okie and myself that your own data show a rise in the surface warming between 1890 and 1940 which was followed by a pronounced cooling followed by warnings from scientists as recently as 1975( I ALSO POSTED THIS EVIDENCE AND YOU DID NOT RESPOND TO IT--WHY?) that we were headed for a mini-Ice Age.
Now, I will give you a quote- I CHALLENGE YOU TO RESPOND TO IT.
You spoke about Intellectual Honesty. Well, I will question yours unless you respond to this very, very important finding from the most auspicious( I am sure you will agree) NATIONAL ACADEMY OF SCIENTISTS.[sic]
Here it is:
The Intergovernmental Panel on Climate Change (IPCC) concluded that global warming in the last 50 years is likely the result of increases in greenhouse gases, which accurately reflects the current thinking of the scientific community, the committee said. However, it also cautioned that uncertainties about this conclusion remain because of the level of natural variability inherent in the climate on time scales from decades to centuries, the questionable ability of models to simulate natural variability on such long time scales, and the degree of confidence that can be placed on estimates of temperatures going back thousands of years based on evidence from tree rings or ice cores.
I am certain that you will not miss the line which says that the IPCC( THE BODY YOU CITED SEVERAL TIMES AS A RELIABLE SOURCE) that UNCERTAINTIES about this conclusion(global warming in the last 50 years is LIKELY the result of increases in greenhouse gases but IT IS ALSO CAUTIONED THAT U N C E R T A I N T I E S ABOUT THIS CONCLUSION REMAIN BECAUSE OF THE L E V E L O F N A T U R A L V A R I A B I L I T Y INHERENT IN THE CLIMATE ON TIME SCALES FROM DECADES TO CENTURIES------THE QUESTIONABLE ABILITIES OF MODELS TO SIMULATE NATURAL VARIABLITY, AND THE DEGREE OF CONFIDENCE THAT CAN BE PLACED ON THE ESTIMATES OF TEMPERATURES GOING BACK THOUSANDS OF YEARS BASED ON EVIDENCE FROM TREE RINGS AND ICE CORES>
Would you please, sir, utilize the Intellectual Honesty you mentioned and respond to this directly??????
YOU NEVER RESPONDED TO THAT DIRECTLY BUT INSTEAD GAVE STUDIES WHICH PURPORTED THAT THE CO2 INDEED CAME FROM MAN MADE SOURCES---This is held in doubt by the paragraph above from the IPCC.
Mr.Kuvasz wrote:
Sure, why not? First noted is your demand for a strict, literal translation when it is not of any value in this discussion or any in science. Many people want certainties to persuade them, and those science does not to have to offer; science is a human project, not the word of God. But when it comes to the physical world, the uncertainties of scientific consensus have proven consistently more accurate than any source perceived as certain.
And this is a central problem of persuading people to act on scientific evidence. Science can never quite say "we know for sure". But if, for instance, one is calculating the path of a cannonball, physics is what one is to relies on if one wants to know when to duck. And perhaps some new & unexpected thing will happen and the cannonball will miss. But one does not stake one's life on that. But maybe you should.
What do you mean we don't know for sure?
As a scientist, I am certain you are aware that when Albert Einstein proposed that his own equations on gravitational fields MUST BE VERIFIED BY EMPIRICAL OBSERVATION. He said:
"If it were proved that this effect does not exist in nature, then the whole theory will have to be abandoned." In fact, the red shift was confirmed by the Mount Wilson Observatory.
New York City has NOT been flooded!!!!!!!
Strike One, Mr. Kuvasz!
Now. let us go to the next point:
My quote:
All of this "reconstruction" referred to in the article is, of course, based on "Computer modeling", which means, that data is fed into the computer and then, as the article says--"A 21st century global warming projection FAR EXCEEDS( IT DOES NOT SAY WHAT FAR EXCEEDS MEANS) the natural variability of the past 1000 years.
"Climate models are imperfect, Their simulation skill is limited by uncertainties in their formulation, the limited size of their calculations and the difficulty in interpreting their answers that exhibit almost as much complexity as in nature"
You know how to read- then, REBUT IT AND WHEN I SAY REBUT IT, I MEAN SHOW DECISIVELY WHY IT IS INCORRECT!!!
W I T H O U T C O M P U T E R M O D E L S, THERE WOULD BE NO EVIDENCE OF GLOBAL WARMING.
By simulating the climate on giant, ultra-fast comput4ers scholars try to find out how it will react to each new stimulus--like a doubling of CO2. AN IDEAL COMPUTER MODEL WOULD HOWEVER, HAVE TO TRACK FIVE MILLION PARAMETERS, FIVE MILLION PARAMETERS, FIVE MILLION PARAMETERS, OVER THE SURFACE OF THE EARTH AND THROUGH THE ATMOSPHERE, AND INCORPORATE ALL RELEVENT INTERACTIONS AMONG LAND, SEA, AIR, ICE AND VEGETATION, ALL RELEVANT INTERACTIONS AMONG LAND, SEA, AIR, ICE AND VEGETATION.
ACCORDING TO ONE RESEARCHER, SUCH A MODEL WOULD DEMAND TEN MILLION TRILLION DEGREES OF FREEDOM TO SOLVE, TEN MILLION TRILLION DEGREES OF FREEDOM TO SOLVE, A C A M P U T A T I O N A L I M P O S S I B I L I T Y E V E N O N T H E M O S T A D V A N C E D S U P E R C O M P U T E R.
You did not, Mr.Kuvasz, respond to the report from the Chicago Tribune that " P R E V I O U S C L I M A T E S I M U L A T I O N S D I D N O T S U G G E S T A N A N C I E N T A R C T I C T H A T W A S N E A R L Y S O W A R M.
Now, since without computer modeling there would be no evidence of global warming and since the previous climate simulations in the Arctic were so far off, it is not at all out of the question that the SIMULATIONS done by the Scientist about future warming MAY ALSO BE IN ERROR.
Perhaps, the Scientists who are making tons of money out of this wouldn't agree with this but the average person who discovers that computer simulations have been wrong before will reason that they can be wrong again.
STRIKE TWO, MR. KUVASZ
And, now, Mr; Kuvasz--Again, I ask you to present evidence that shows how much of the alleged "global warming" comes from Man-Made sources and how much comes from Natural sources. I need evidence that shows, for example, that " 0.2 to 0.4 F of the global warming since 1960 has come from Man made sources and 0.1 to 0.3 of the global warming since 1960 has come from Natural Sources>" In the light of the enormous changes made by NATURAL sources--quote
"The samples also chronicle the subsequent cooling, WITH MANY U P S AND D O W N S that the researchers say began about 45 Million years ago and led to the C Y C L E S O F I C E A G E S A N D B R I E F W A R M S P E L L S of the last several million years" are you really asking us to believe that there has been NO natural sources at work in the last century?
You talk of science but yet you completely disregard the fact that NASA SATELLITES HAVE UNCOVERED THE FACT THAT THE SUN'S CHANGING MECHANISM OVER THE COURSE OF ITS SUNSPOT CYCLE IS ACCOMPANIED BY A CHANGE IN TOTAL ENERGY OUTPUT.
Certainly, as a trained scientist you know that the amount of energy reaching us increases or decreases as the sun brightens or fades, and the change in solar magnetism, or total energy output, is HIGHLY CORRELATED with changes in the temperature of the Northern Hemisphere going back 240 years, THE SUN TODAY IS AS MAGNETICALLY ACTIVE AS IT HAS BEEN IN 400 YEARS OF DIRECT TELESCOPE OBSERVATIONS. If the earth has been warming slightly it may be that the sun is heating the earth.
The sun provides 99.998% of the energy to the Earth's climate (the rest coming from geothermal heat sources). The circulation patterns of the tropical Hadley Cell, the mid latitude storm tracks the polar high and the resulting climate zones are all driven by the gradients of solar heating as a function of latitude. So of course any significant change to solar output is bound to affect the climate, it stands to reason! Since we can see that there are changes in solar activity, it's therefore just a question of finding the link. Researchers for over a century have therefore taken any climate records they can find and searched for correlations to the sunspots, the solar-cycle length, geomagnetic indices, cosmogenic isotopes or smoothed versions thereof (and there are many ways to do the smoothing, and you don't even need to confine yourself to one single method per record). At the same time, estimates of solar output in the past are extremely uncertain, and so there is a great deal of scope in blaming any unexplained phenomena on solar changes without fear of contradiction.
Astute readers will notice that there is a clear problem here. The widespread predisposition to believe that there must be a significant link and a lack of precise knowledge of past changes are two ingredients that can prove, err...., scientifically troublesome. Unfortunately they lead to a tendency to keep looking for the correlation until one finds one. When that occurs (as it will if you look hard enough even in random data) it gets published as one more proof of the significant impact that solar change has on climate. Never do the authors describe how many records and how many different smoothing methods they went through before they found this one case where the significance is greater than 95%. Of course, if they went through more than 20, the chances of randomly stumbling onto this level of significance is quite high.
The proof that this often happens is shown by the number of these published correlations that fall apart once another few years of data are added, cosmic rays (which are modulated by solar activity) and cloudiness for instance.
Sometimes even papers in highly respected journals fall into the same trap. Friis-Christensen and Lassen (Science, 1991) was a notorious paper that purported to link solar-cycle length (i.e. the time between sucessive sunspot maxima or minima) to surface temperatures that is still quoted widely. As discussed at length by Peter Laut and colleagues, the excellent correlation between solar cycle length and hemispheric mean temperature only appeared when the method of smoothing changed as one went along. The only reason for doing that is that it shows the relationship (that they 'knew' must be there) more clearly. And, unsurprisingly, with another cycle of data, the relationship failed to hold up.
The potential for self-delusion is significantly enhanced by the fact that climate data generally does have a lot of signal in the decadal band (say between 9 and 15 years). This variability relates to the incidence of volcanic eruptions, ENSO cycles, the Pacific Decadal Oscillation (PDO) etc. as well as potentially the solar cycle. So another neat trick to convince yourself that you found a solar-climate link is to use a very narrow band pass filter centered around 11 years, to match the rough periodicity of the sun spot cycle, and then show that your 11 year cycle in the data matches the sun spot cycle. Often these correlations mysteriously change phase with time, which is usually described as evidence of the non-linearity of the climate system, but in fact is the expected behaviour when there is no actual coherence. Even if the phase relationship is stable, the amount of variance explained in the original record is usually extremely small.
This is not to say that there is no solar influence on climate change, only that establishing such a link is more difficult then many assume. What is generally required is a consistent signal over a number of cycles (either the 11 year sunspot cycle or more long term variations), similar effects if the timeseries are split, and sufficient true degrees of freedom that the connection is significant and that it explains a non-negligible fraction of the variance. These are actually quite stiff hurdles and so the number of links that survive this filter are quite small. In some rough order of certainty we can consider that the 11 year solar cycle impacts on the following are well accepted: stratospheric ozone, cosmogenic isotope production, upper atmospheric geopotential heights, stratospheric temperatures and (slightly less certain and with small magnitudes ~0.1 deg C) tropospheric and ocean temperatures. More marginal are impacts on wintertime tropospheric circulation (like the NAO). It is also clear that if there really was a big signal in the data, it would have been found by now. The very fact that we are still arguing about statisitical significance implies that whatever signal there is, is small.
Over the multi-decadal time scales, there is more reasonable evidence for an NAO and surface temperature response to solar changes though the magnitudes are still small. Over even longer time scales (hundreds of years) there are a number of paleo-records that correlate with records of cosmogenic isotopes (particularly 10Be and 14C), however, these records are somewhat modulated by climate processes themselves (the carbon cycle in the case of 14C, aerosol deposition and transport processes for 10Be) and so don't offer an absolutely clean attribution. Nonetheless, by comparing with both isotopes and trying to correct for climate (and geomagnetic) effects, some coherent signals have been seen.
One of the main planks of the argument that CRF is responsible for the most recent warming is based on figure 14b in Veizer (2005), where there appears to be a trend in CRF from eg Climax neutron monitor (also, see plots at this URL). This CRF-curve was a surprise to me, and furthermore, it’s at odds with CRF-evolution presented in figure 17 in the very same paper (showing no systematic change) - how can these accounts be so different? The inconsistency becomes even more apparent when it is argued that the ‘balloon and satellite data ([Veizer, 2005] Fig. 17) do not show any clear temperature trend... Instead, their interannual temperature oscillations correlate clearly with … CRF’ (p. 22, 2nd column). Again, no long-term trend in the CRF-data. It has been argued earlier on RealClimate that there is no long-term trend in the modern CRF measurements. The lack of systematic trends in CRF and other solar activity proxies is well-known and published in the scientific literature (eg. Richardson et al, 2002). In fact, the CRF curves presented by some of the key cosmic-ray hypothesis proponents, Marsh & Svensmark, do not exhibit any trend, yet it has been claimed that CRF is responsible for the most recent warming (Marsh & Svensmark say that the wiggles correlate, but don't discuss the [or lack of] observed trends).
There are other aspects which appear as problematic for the CRF-interpretation for the recent global warming. First of all, according to IPCC (2001) the night-time temperatures have in general increased more than the day-time temperature (the diurnal temperature range, DTR, has decreased in most areas, except over middle Canada, and parts of southern Africa, south-west Asia, Europe, and the western tropical Pacific Islands). Since individual clouds have a life time of hours, and the CRF-interpretation involves changes in the reflected light as well as ionisation, a climatic response from change in CRF is hypothetically almost instantaneous, and it is a challenge to explain why the night side (where there is no sunlight and hence reflection cannot play a role) warms more strongly than the dayside, if the CRF were to drive the recent warming trend. Another equally important challenge is the fact that there are pronounced ~11-year variations in the CRF, but the presence of ~11-year variations in the global mean temperature are much less pronounced than the trend over the 3--4 most recent decades. If the CRF were so important (and the cloud response near-instantaneous) why do we not see more pronounced ~11-year variations in the global mean temperature?
The paper also gives the impression that there is no trend in satellite-based temperatures (MSU), which is wrong. There are various analyses of the satellite trends, all of which indicating a warming trend in the troposphere.
When Veizer summarises in bold type face ‘(above) empirical observations on all time scales point to celestial phenomena as the principal driver of climate’, he neglects to discuss the fact that the stratosphere has been cooling, which at higher levels is consistent with an enhanced greenhouse effect (most of the cooling in the lower stratosphere is related to changes in ozone) but inconsistent with enhanced solar activity and his CRF-hypothesis. Another argument Veizer uses to support his hypothesis is that the correlation between the proxy indicators for CRF is better correlated with ‘climate’ than between CO2 and climate. Yet he does not provide any references or justify his argument.
There is little evidence for a connection between solar activity (as inferred from trends in galactic cosmic rays) and recent global warming. Since the paper by Friis-Christensen and Lassen (1991), there has been an enhanced controversy about the role of solar activity for earth's climate. Svensmark (1998) later proposed that changes in the inter-planetary magnetic fields (IMF) resulting from variations on the sun can affect the climate through galactic cosmic rays (GCR) by modulating earth's cloud cover. Svensmark and others have also argued that recent global warming has been a result of solar activity and reduced cloud cover. Damon and Laut have criticized their hypothesis and argue that the work by both Friis-Christensen and Lassen and Svensmark contain serious flaws. For one thing, it is clear that the GCR does not contain any clear and significant long-term trend (e.g. Fig. 1, but also in papers by Svensmark).
Svensmark's failure to comment on the lack of a clear and significant long-term downward GCR trend, and how changes in GCR can explain a global warming without containing such a trend, is one major weakness of his argument that GCR is responsible for recent global warming. This issue is discussed in detail in Benestad (2002). Moreover, the lack of trend in GCR is also consistent with little long-term change in other solar proxies, such as sunspot number and the solar cycle length, since the 1960s, when the most recent warming started.
GCR counts from Climax (red) and the aa-index (blue). The straight lines show the best linear-fit against time estimated through linear regression. The GCR measurements are shown in solid black line, from which a trend of -180 +/- 253 counts/decade is estimated, and this is associated with a p-value (the probability of this being different to the null-hypothesis: zero trend) of 0.477 (not statistically significant at the 5% level). The aa-index is represented by the blue line, and the corresponding trend of 1.5 +/- 0.4/decade is associated with a p-value of 0.0002 (highly statistically significant). A regression analysis points to a clear link between GCR and the aa-index, and the analysis of variance yields R2 = 0.1466 and the p-value= 0. The yellow line shows the global mean temperature from CRU for comparison.
Data source: http://ulysses.uchicago.edu/NeutronMonitor/neutron_mon.html
http://www.cru.uea.ac.uk/cru/data/temperature/
http://ftp.ngdc.noaa.gov/STP/SOLAR_DATA'].
References:
Benestad, R.E. (2002) Solar Activity and Earth's Climate, Praxis-Springer, Berlin and Heidelberg, 287pp, ISBN: 3-540-43302-3
Damon, P.E. and P. Laut (2004), Pattern of Strange Errors Plagues Solar Activity and Terrestrial Climate Data, Eos, vol 85, num 39, p. 370
Friis-Christensen, E. and K. Lassen (1991), Length of the solar cycle: an indicator of solar activity closely associated with climate, Science 254: 698-700
Meehl, G.A., W.M. Washington, T.M.L. wigley, J.M. Arblaster, A. Dai (2003): Solar and Greenhouse Gas Forcing and Climate Response in the Twentieth Century, J. Climate, 6: 426-444
Shindell, D., D. Rind, N. Balachandran, J. Lean and P. Lonergan (1999): Solar Cycle Variability, Ozone and Climate, Science, 284: 305-308
Svensmark, H. (1998), Influence of Cosmic Rays on Earth's Climate, Physical Review Letters, vol 81, num 22, 5027-5030
In Geophysical Research Letters, Scafetta & West (S&W) estimate that as much as 25-35% of the global warming in the 1980-2000 period can be attributed changes in the solar output. They used some crude estimates of 'climate sensitivity' and estimates of Total Solar Irradiance (TSI) to calculate temperature signal (in form of anomalies). They also argue that their estimate, which is based on statistical models only, has a major advantage over physically based considerations (theoretical models), because the latter would require a perfect knowledge about the underlying physical and chemical mechanisms.
In their paper, they combine Lean et al (1995) proxy data for the TSI with recent satellite TSI composites from either Willson & Mordvinov (2003) [which contains a trend] and of Fröhlich & Lean (1998) [data from the same source, but the analysis doesn't contain a trend, henceforth referred to as 'FL98']. From 1980 and afterwards, they see a warming associated with solar forcing, even when basing their calculations on the FL98 data. The fact that the FL98 data doesn't contain any trend makes this finding seem a bit odd. Several independent indices on solar activity " which are direct modern measurement rather than estimations - indicate that there has been no trend in the level of solar activity since 1950s.
But, S&W have assumed a lagged response (which they state is tS4~4.3 years), so that the increase prior to 1980 seems to have a delayed effect on the temperature. The delayed action is a property of the climate system, which also affects greenhouse gases, and is caused by the oceans which act as a flywheel due to their great heat capacity and thermal inertia. The oceans thus cause a planetary imbalance. When the forcing levels off, the additional response is expected to taper off as a decaying function of time. In contrast, the global mean temperature, however, has increased at a fairly steady rate (Fig. 1). The big problem is to explain a lag of more than 30 years when direct measurements of quantities (galactic cosmic rays, 10.7 cm solar radio, magnetic index, level of sunspot numbers, solar cycle lengths) do not indicate any trend in the solar activity since the 1950s.
In order to shed light on these inconsistencies, we need to look more closely at the methods and results in the GRL paper. The S&W temperature signal, when closely scrutinized (their Fig. 3), starts at the 0K anomaly-level in 1900, well above the level of the observed 1900 temperature anomalies, which lie in the range -3K < T < -1K in Fig. 1. In 1940, their temperature [anomaly] reconstruction intercepts the temperature axis near 0.12K, which is slightly higher than the GISS-curve in Fig. 1 suggests. The S&W temperature peaks at 0.3K in 1960, and diverge significantly from the observations. By not plotting the curves on the same graph, the reader may easily get the wrong impression that the construction follows the observations fairly closely. The differences between the curves have not been discussed in the paper, nor the time difference for when the curves indicate maxima (global mean temperature peaks in 1945, while the estimated solar temperature signal peaks in 1960). Hence, the decrease in global temperature in the period 1945 - 1960 is inconsistent with the continued rise in the calculated solar temperature signal.
Another more serious weakness is a flawed approach to obtain their 'climate sensitivity', and especially so for 'Zeq' in their Equation 4. They assume a linear relationship between the response and the forcing Zeq=288K/1365Wm-2. For one thing, the energy balance between radiative forcing and temperature response gives a non-linear relation between the forcing, F, and temperature to the fourth power, T4 (the Stefan-Boltzmann law). This is standard textbook climate physics as well as well-known physics. However, there is an additional shortcoming due to the fact that the equilibrium temperature is also affected by the ratio of the Earth's geometrical cross-section to its surface area as well as how much is reflected, the planetary albedo (A). The textbook formulae for a simple radiative balance model is:
F (1-A)/4 = s T4, where 's' here is the Boltzmann constant (~5.67 x 10-8 J/s m2K4).
('=' moved after Scafetta pointed out this error. )
S&W's sun-climate sensitivity (Zeq =0.21K/Wm-2), on which the given solar influence estimates predominantly depend, is thus based solely on a very crude calculation that contradicts the knowledge of climate physics.
The "equilibrium" sensitivity of the global surface temperature to solar irradiance variations, which is calculated simply by dividing the absolute temperature on the earth's surface (288K) by the solar constant (1365Wm-2), is based on the assumption that the climate response is linear in the whole temperature band starting at the zero point. This assumption is far from being true. S&W argue further that this sensitivity does not only represent the direct solar forcing, but includes all the feedback mechanisms. It is well known, that these feedbacks are highly non-linear. Let's just mention the ice-albedo feedback, which is very different at (hypothetically) e.g. 100K surface temperature with probably 'snowball earth' and at 300K with no ice at all. In their formula for the calculation of the sun-related temperature change, the long-term changes are determined by Zeq, while their 'climate transfer sensitivity to slow secular solar variations' (ZS4) is only used to correct for a time-lag. The reason for this remains unclear.
In order to calculate the terrestrial response to more ephemeral solar variations, S&W introduce another type of 'climate sensitivity' which they calculate separately for each of two components representing frequency ranges 7.3-14.7 and 14.7-29.3 year ranges respectively. They take the ratios of the amplitude of band-passed filtered global temperatures to similarly band-passed filtered solar signal as the estimate for the 'climate sensitivity'. This is a very unusual way of doing it, but S&W argue that similar approach has been used in another study. However, it's not as simple as that calculating the climate senstivity (see here, here, here, and here). Hence, there are serious weaknesses regarding how the 'climate sensitivities' for the 11-year and the 22-year signals were estimated. For linear systems, different frequency bands may be associated with different forcings having different time scales, but chaotic systems and systems with convoluted response are usually characterised with broad power spectra. Furthermore, it's easy to show that band-pass filtering of two unrelated series of random values can produce a range of different values for the ratio of their amplitudes just by chance (Fig. 2). As an aside, it is also easy to get an apparent coherence between two band-pass filtered stochastic series of finite extent which are unrelated by definition - a common weakness in many studies on solar-terrestrial climate connection. There is little doubt that the analysis involved noisy data.
The fact that there is poor correspondence between the individual amplitudes of the band-passed filtered signals (Fig. 4 in Scafetta & West, 2005) is another sign indicating that the fluctuations associated with a frequency band in temperature is not necessarily related to solar variability. In fact, the 7.3-14.7 and 14.7-29.3 frequency bands may contain contributions from El Niño Southern Oscillation (ENSO), although the time scale of ENSO is from 3-8 years. The fact that the amplitude of the events vary from time to time implies slower variations, just like modulations of the sunspot number has led to the proposition of the Gleissberg cycles (80-90 years). There is also volcanic activity, and the last major eruption in 1982 and 1991 are almost 10 years apart, and may contribute to the variance in the 7.3-14.7 year frequency range. S&W argue that their method eliminates influences of ENSO and volcanoes because their calculated sensitivity in the higher frequency band is similar to the one derived by Douglass and Clader (2002) by regression analysis (0.11 K/Wm-2). This conclusion is not valid. Having signals of different frequencies in the 7-15 years band, the amplitude of the signal in the higher band may correspond roughly to the 11-year signal by accident, but that doesn't mean that there are no other influences.
S&W combined two different types of data, and it is well-known that such combinations in themselves may introduce spurious trends. The paper does not address this question.
From regression analysis cited by the authors (Douglass and Clader 2002, White et al. 1997), it seems possible that the sensitivity of global surface temperature to variations of total solar irradiance might be about 0.1K/Wm-2. S&W do not present any convincing result that would point to noticeably higher sensitivities to long-term variations. Their higher values are based on unrealistic assumptions. If they would use a more realistic climate transfer sensitivity of 0.11K/Wm-2, or even somewhat higher (0.12 or 0.13) for the long-term, and use trends instead of smooth curve points, they would end up with solar contributions of 10% or less for 1950-2000 and near 0% and about 10% in 1980-2000 using the PMOD and ACRIM data, respectively.
Now, as a trained scientist, Mr. Kuvasz. It is your job to present articles that say that the contribution of natural causes as opposed to man-made causes is in such and such a ratio, or that there is no contribution of natural causes to the warming and that the sun cannot be the cause of any warming. Failure to do that will result in strike three- You will be OUT!!!
12.3 Qualitative Comparison of Observed and Modeled Climate Change
12.3.1 Introduction
This section presents a qualitative assessment of consistencies and inconsistencies between the observed climate changes identified in Chapter 2 and model projections of anthropogenic climate change described in Chapter 9.
Most formal detection and attribution studies concentrate on variables with high climate change signal-to-noise ratios, good observational data coverage, and consistent signals from different model simulations, mainly using mean surface air temperatures or zonal mean upper-air temperatures. To enhance the signal-to-noise ratio, they generally consider variations on large spatial scales and time-scales of several decades or longer.
There are many studies that have identified areas of qualitative consistency and inconsistency between observed and modeled climate change. While the evidence for an anthropogenic influence on climate from such studies is less compelling than from formal attribution studies, a broad range of evidence of qualitative consistency between observed and modeled climate change is also required. In addition, areas of qualitative consistency may suggest the possibility for further formal detection and attribution study.
12.3.2 Thermal Indicators
Surface temperature
Global mean surface air temperature has been used in many climate change detection studies. The warming shown in the instrumental observations over the last 140 years is larger than that over a comparable period in any of the multi-century control simulations carried out to date (e.g., Figure 12.1; Stouffer et al., 2000). If the real world internal variability on this time-scale is no greater than that of the models, then the temperature change over the last 140 years has been unusual and therefore likely to be externally forced. This is supported by palaeo-reconstructions of the last six centuries (Mann et al., 1998) and the last 1,000 years (Briffa et al., 1998; 2000; Jones et al., 1998; Crowley, 2000; Crowley and Lowery, 2000; Mann et al., 2000), which show that the 20th century warming is highly unusual. Three of the five years (1995, 1996 and 1998) added to the instrumental record since the SAR are the warmest globally in the instrumental record, consistent with the expectation that increases in greenhouse gases will lead to sustained long-term warming.
When anthropogenic factors are included, models provide a plausible explanation of the changes in global mean temperature over the last hundred years (Figure 12.7). It is conceivable that this agreement between models and observations is spurious. For example, if a model’s response to greenhouse gas increases is too large (small) and the sulphate aerosol forcing too large (small), these errors could compensate. Differences in the spatio-temporal patterns of response to greenhouse gases and sulphate forcing nevertheless allow some discrimination between them, so this compensation is not complete. On the other hand, when forced with known natural forcings, models produce a cooling over the second half of the 20th century (see Figure 12.7) rather than the warming trend shown in the observed record. The discrepancy is too large to be explained through model estimates of internal variability and unlikely to be explained through uncertainty in forcing history (Tett et al., 2000). Schneider and Held (2001) applied a technique to isolate those spatial patterns of decadal climate change in observed surface temperature data over the 20th century which are most distinct from interannual variability. They find a spatial pattern which is similar to model-simulated greenhouse gas and sulphate aerosol fingerprints in both July and December. The time evolution of this pattern shows a strong trend with little influence of interannual variability. (Note that this technique is related to optimal fingerprinting, but does not use prior information on the pattern of expected climate change.)
Other thermal indicators
While most attention in formal detection and attribution studies has been paid to mean surface air temperatures, a number of other thermal indicators of climate variations are also discussed in Chapter 2. Many of these, including warming in sub-surface land temperatures measured in bore holes, warming indicators in ice cores and corresponding bore holes, warming in sub-surface ocean temperatures, retreat of glaciers, and reductions in Arctic sea-ice extent and in snow cover, are consistent with the recent observed warming in surface air temperatures and with model projections of the response to increasing greenhouse gases. Other observed changes in thermal indicators include a reduction in the mean annual cycle (winters warming faster than summers) and in the mean diurnal temperature range (nights warming faster than days) over land (see Chapter 2). While the changes in annual cycle are consistent with most model projections, the observed changes in diurnal temperature range are larger than simulated in most models for forcings due to increasing greenhouse gases and sulphate aerosols this century (see Chapters 2 and 8). However, the spatial and temporal coverage of data for changes in observed diurnal temperature range is less than for changes in mean temperatures, leading to greater uncertainty in the observed global changes (Karoly and Braganza, 2001; Schnur, 2001). Also, the observed reductions in diurnal temperature range are associated with increases in cloudiness (see Chapter 2), which are not simulated well by models. Few models include the indirect effects of sulphate aerosols on clouds.
Changes in sea-ice cover and snow cover in the transition seasons in the Northern Hemisphere are consistent with the observed and simulated high latitude warming. The observed trends in Northern Hemisphere sea-ice cover (Parkinson et al., 1999) are consistent with those found in climate model simulations of the last century including anthropogenic forcing (Vinnikov et al., 1999). Sea-ice extent in the Southern Hemisphere does not show any consistent trends.
Compatibility of surface and free atmosphere temperature trends
There is an overall consistency in the patterns of upper air temperature changes with those expected from increasing greenhouse gases and decreasing stratospheric ozone (tropo-spheric warming and stratospheric cooling). It is hard to explain the observed changes in the vertical in terms of natural forcings alone, as discussed in Section 12.2.3.2 (see Figure 12.8). However, there are some inconsistencies between the observed and modelled vertical patterns of temperature change. Observations indicate that, over the last three to four decades, the tropical atmosphere has warmed in the layer up to about 300 hPa and cooled above (Parker et al., 1997; Gaffen et al., 2000). Model simulations of the recent past produce a warming of the tropical atmosphere to about 200 hPa, with a maximum at around 300 hPa not seen in the observations. This discrepancy is less evident when co-located model and radiosonde data are used (Santer et al., 2000), or if volcanic forcing is taken into account, but does not go away entirely (Bengtsson et al., 1999; Brown et al., 2000b). The MSU satellite temperature record is too short and too poorly resolved in the vertical to be of use here.
Comparison of upper air and surface temperature data in Chapter 2 shows that the lower to mid-troposphere has warmed less than the surface since 1979. The satellite-measured temperature over a broad layer in the lower troposphere around 750 hPa since 1979 shows no significant trend, in contrast to the warming trend measured over the same time period at the surface. This disparity has been assessed recently by a panel of experts (National Academy of Sciences, 2000). They concluded that “the troposphere actually may have warmed much less rapidly than the surface from 1979 to the late 1990s, due both to natural causes (e.g., the sequence of volcanic eruptions that occurred within this particular 20-year period) and human activities (e.g., the cooling in the upper troposphere resulting from ozone depletion in the stratosphere)” (see also Santer et al., 2000). They also concluded that “it is not currently possible to determine whether or not there exists a fundamental discrepancy between modelled and observed atmospheric temperature changes since the advent of satellite data in 1979”. Over the last 40 years, observed warming trends in the lower troposphere and at the surface are similar, indicating that the lower troposphere warmed faster than the surface for about two decades prior to 1979 (Brown et al., 2000a; Gaffen et al., 2000). However, in the extra-tropical Eurasian winter some additional warming of the surface relative to the lower or mid-troposphere might be expected since 1979. This is due to an overall trend towards an enhanced positive phase of the Arctic Oscillation (Thompson et al., 2000) which has this signature.
Model simulations of large-scale changes in tropospheric and surface temperatures are generally statistically consistent with the observed changes (see Section 12.4). However, models generally predict an enhanced rate of warming in the mid- to upper troposphere over that at the surface (i.e., a negative lapse-rate feedback on the surface temperature change) whereas observations show mid-tropospheric temperatures warming no faster than surface temperatures. It is not clear whether this discrepancy arises because the lapse-rate feedback is consistently over-represented in climate models or because of other factors such as observational error or neglected forcings (Santer et al., 2000). Note that if models do simulate too large a negative lapse-rate feedback, they will tend to underestimate the sensitivity of climate to a global radiative forcing perturbation.
You are making the case for global warming based on man-made or, as the literature puts it, anthropogenic sources. YOU PROVE IT.
First of all, the PREDICTED CO2 GROWTH CAUSED BY NATURAL AND MAN MADE CAUSES ARE COMPUTER MODELS, I THINK THERE HAS BEEN ENOUGH EVIDENCE TO SHOW THAT THOSE MODELS ARE NOT ALWAYS CORRECT AND CAN SOMETIMES BE VERY VERY MISLEADING.,I REJECT THEM AS D E F I N I T I V E AND I N C O N T R O V E R T I B L E EVIDCENCE AS A RESULT.
Here are the questions that you have not answered. Please do not refer me to the ambiguous and often contradictory literature again, As you will see, I have read enough of it to find that there is no certainty in it and as the IPCC A POINT YOU WILL NOT, WILL NOT ADMIT, EVEN THOUGH YOUR OWN IPCC SAID IT--UNCERTAINTY. YOU DO KNOW WHAT THAT WORD MEANS- DONT YOU?
Let us proceed:
You never explained(post 2074543) how the Co2 increase has come LARGELY FROM FOSSIL FUEL AND CEMENT PRODUCTION. I have asked you several times to precisely QUANTIFY THE MEANING OF LARGELY AND ALSO TO QUANTIFY THE NATURAL EFFECTS ON THE CO2 AS DISTINCT FROMTHE FOSSIL FUEL AND CEMENT PRODUCTION.
This question keeps coming back, although we know the answer very well: all of the recent CO2 increase in the atmosphere is due to human activities, in spite of the fact that both the oceans and the land biosphere respond to global warming. There is a lot of evidence to support this statement which has been explained in a previous posting here and in a letter in Physics Today . However, the most convincing arguments for scientists (based on isotopes and oxygen decreases in the atmosphere) may be hard to understand for the general public because they require a high level of scientific knowledge. I present simpler evidence of the same statement based on ocean observations, and I explain how we know that not only part of the atmospheric CO2 increase is due to human activities, but all of it.
On time-scales of ~100 years, there are only two reservoirs that can naturally exchange large quantities of CO2 with the atmosphere: the oceans and the land biosphere (forests and soils). The mass of carbon (carbon is the "C" in CO2) must be conserved. If the atmospheric CO2 increase was caused, even in part, by carbon emitted from the oceans or the land, we would measure a carbon decrease in these two reservoirs.
Number of observations of carbon decreasing in the global oceans: zero.
Number of observations of carbon increasing in the global oceans: more than 20 published studies using 6 independent methods.
The methods are:
(1) direct observations of the partial pressure of CO2 at the ocean surface (Takahashi et al. 2002),
(2) observations of the spatial distribution of atmospheric CO2 which show how much carbon goes in and out of the different oceanic regions (Bousquet et al. 2000),
(3) observations of carbon, oxygen, nutrients and CFCs combined to remove the mean imprint of biological processes (Sabine et al. 2004),
(4) observations of carbon and alkalinity for two time-periods combined with an estimate of water age based on CFCs (McNeil et al. 2002), and the simultaneous observations of atmospheric CO2 increase and the decrease in (5) oxygen (Keeling et al. 1996), and (6) carbon 13 (Ciais et al. 1995) in the atmosphere.
The principle of the last two methods is that both fossil fuel burning and biospheric respiration consume oxygen and reduce carbon 13 as they produce CO2, but the exchange of CO2 with the oceans has only a small impact on atmospheric oxygen and carbon 13. The measure of atmospheric CO2 increase together with oxygen or carbon 13 decrease gives the distribution between the different reservoirs.
All the estimates show that the carbon content of the oceans is increasing by ~ 2±1 PgC every year (current burning of fossil fuel is ~7 PgC per year). One method is able to go back in time and shows that the carbon content of the oceans has increased by 118±19 PgC in the last 200 years. There is some uncertainty about the exact amount that the oceans have taken up, but not about the direction of the change. The oceans cannot be a source of carbon to the atmosphere, because we observe them to be a sink of carbon from the atmosphere.
What about the land biosphere? We know that deforestation has contributed to the increase in atmospheric CO2. Yet because carbon needs to be conserved, observations of the carbon increase in the atmosphere and the oceans combined with estimates of fossil fuel burning tell us that deforestation has been largely compensated by enhanced growth by the land biosphere. For example, during 1980 to 1999, fossil fuel burning was 117±5 PgC, and the carbon increase in the atmosphere and the oceans were 65±1 and 37±8 PgC, respectively. Thus that leaves 15±9 PgC that has been taken up by the land. This 15±9 PgC includes deforestation (and other land-use changes) which reduced the land biosphere by 24±12 PgC, and an additional land uptake of 39±18 PgC in response to elevated CO2 and climate changes (Sabine et al. 2004). Here also there is some uncertainty about the exact amount, but there is no uncertainty that the land biosphere has taken up a quantity of CO2 that is roughly equivalent to the deforestation.
Why are the ocean and land taking up carbon, when we know that warming of the oceans reduces the solubility of CO2 and warming of the land accelerates bacterial degradation of the soils? The answer is that warming is not the only process that influences the oceans and land biosphere. The dominant process in the oceans is the response to increasing atmospheric CO2 itself. If the oceans had not warmed, they might have taken up even more carbon, although we cannot say for sure because warming may have other impacts, for example on marine biota. On land, bacterial degradation of the soils may have increased in response to warming, but for the moment this effect is smaller than the land response to other processes (for example fertilization by CO2 and nitrogen, changes in precipitation, etc).
Is this consistent with what we know of the glaciations? Yes. During glaciations, the balance of processes was very different. Cooling and other climate changes occurred first. The response of the oceans and land biosphere to climate caused the atmospheric CO2 to decrease, which caused more cooling (more on the feedbacks between temperature and CO2 can be found here). During glaciations, there were no external changes in atmospheric CO2 and the oceans and land biosphere responded primarily to climate change. In the last 200 years, there have been large changes in atmospheric CO2 as a result of human activities, and the oceans and land biosphere respond primarily to rising CO2.
In summary, we know that the rise in atmospheric CO2 is entirely caused by fossil fuel burning and deforestation because many independent observations show that the carbon content has also increased in both the oceans and the land biosphere (after deforestation). If the oceans or land had contributed to the rise in atmospheric CO2, they would hold less carbon. Their response to warming may be real, but it is less than their response to increasing CO2 and other climate changes for the moment.
More on the carbon budget can be found in the last IPCC report here, which includes budgets and uncertainties for different time periods and additional numbers for the small contribution of volcanoes and other geological reservoirs.
References:
Bousquet et al. (2000), Regional changes of CO2 fluxes over land and oceans since 1980, Science, Vol 290, 1342-1346.
Ciais et al. (1995), A Large Northern Hemisphere Terrestrial CO2 Sink Indicated by the 13C/12C Ratio of atmospheric CO2, Science, Vol 269, pp. 1098-1102.
Keeling, Piper and Heimann (1996), Global and hemispheric CO2 sinks deduced from changes in atmospheric O2 concentration, Nature, Vol 381, 218-221.
McNeil et al. (2003), Anthropogenic CO2 uptake by the ocean based on the global chlorofluorocarbon data set, Science, Vol 299, 235-239.
Takahashi et al. (2002), Global sea-air CO2 flux based on climatological surface ocean pCO2, and seasonal biological and temperature effects, Deep Sea Research, Vol 49, 1601-1622.
Additionally, you must explain how these quantifications were determined--ANY USE OF COMPUTER SIMULATIONS IN THESE QUANTIFICATIONS MAKE THEM SUSPECT IS CLEAR FROM MY EVIDENCE.
'You did not present any evidence that the Surface temperatures obtained are NOT in ANY WAY tainted by the "heat island" effect. You do know what ANY WAY, means, of course.
You never showed that the "heat island" effect did not contaminate the surface temperature readings and you did not rebut the irrefutable fact that in spite of the rapid increase in co2 some cities close to each other like New York and Albany did not have similar temperatures and that indeed; Albany's temperatures went down since 1930. THIS IS GLOBAL WARMING????
You did not rebut the statement made by the IPCC--the group you refer to often as the authority, concerning the QUESTIONABLE ABILITY OF MODELS TO SIMULATE NATURAL VARIABLITY" This is their comment not mind so please do not refer again to "we're getting better. The IPCC said--Questionable ability. You do understand the meaning of the word questionable, of course.
You did not show exactly how, even though I asked you again and again, exactly how the scientists separated natural effects from manmade effects.
The truth is that nobody knows exactly how much of the present warming trend might be a natural phenomenon and how much might be manmade.
If you think you know it, and I am sure you are a brilliant scientist, you can say--Using xyz, scientists have found that 92% of the warming from 1990 to the present is anthropogenic and 8% is natural.
THERE IS NO SUCH STUDY THAT CAN GIVE THOSE NUMBERS WITH COMPLETE ACCURACY AND YOU KNOW IT, MR. KUVASZ-
REMEMBER WHAT THE IPPC SAID--"Questionable ability of models to simulate natural variability.
Your post on Satellite data refers to 1994data, If you reference my post on Satellite data from NASA, you will find it is after your data and is shows NO WARMING!!!
You have failed to explain completely why the earth was warmer from 1890 to 1960 even though the production of CO2 was lesser. You mumbled something about Krakatau but it was unpersuasive. YOU KNOW THAT THE THEORY OF GLOBAL WARMING DEPENDS ON THE FACT THAT CO2 IS SUPPOSED TO BE THE GREENHOUSE GAS THAT WARMS THE EARTH--What warmed it from 1890 to 1960-- YOUR OWN TEMPERATURE FIGURES SHOW A RISE CULMINATING IN 1960--followed, of course, by the lemming scientists who predicted an ice age in 1975--very accurate- very accurate---
Your comment about Krakatoa was revealing. Can you be certain that there will not be another such occurrence in the near future? What would this do to the Warming trend? Or hasn't that ASSUMPTION BEEN FED INTO THE COMPUTERS OF THE IPCC?
When I commented on the IPCC's statement about Uncertainties- you said that the uncertainties of scientific consensus have become more certain.
SURE- Just like the model computer extrapolations on what the Arctic was like 55 Million years ago--THE ONLY PROBLEM THERE WAS THAT THEY WERE WAY OFF>
Astonishing!!!!
Some of your blurbs indicated that the CO2 growth is due to human activities and that there is no NATURAL VARIABLITIES that can account for it.
THAT IS FALSE AND YOUR OWN SOURCES SAY SO--
QUOTE-“This is not to say that THERE IS NO SOLAR AFFECT ON CLIMATE CHANGE ONLY THAT IT IS MORE DIFFICULT TO DETECT THAN SOME MAY THINK.”
The present atmospheric CO2 increase is caused by anthropogenic emissions of CO2. Climate Change 2001 P185
So there MAY be Solar effect on climate only it is difficult to ascertain.
Therefore, the POSSIBLITY must be left open( ACCORDING TO YOUR OWN SOURCES) that Solar activity may indeed affect climate change>
Do you begin to see how many holes there are in your thesis, Mr.Kuvasz?
When you claim that my statement about climate models was out of context, I not only gave you the IPCC quote about the questionability of computer models but a statement on the ideal computer model needed to track "five million parameters over the surface of the earth"
YOU NEVER REBUTTED THIS STATEMENT.
The statement was made--We don't know for sure--The truest statement in all of this verbiage.
There has been no rebuttal of the statement made by Dr. Lindzen that--the computer simulations ALL ASSUME that water vapor will amplify the small bit of warming expected from an increase of carbon dioxide in the air. Indeed, the National Academy of Sciences has stated that:
THE NATURE AND MAGNITUDE OF THESE HYDROLOGICAL FEEDBACKS GIVE RISE TO THE LARGEST SOURCE OF UNCERTAINTY ABOUT CLIMATE SENSITIVITY"
Whenever three or more contrarians are gathered together, one will inevitably claim that water vapour is being unjustly neglected by 'IPCC' scientists. "Why isn't water vapour acknowledged as a greenhouse gas?", "Why does anyone even care about the other greenhouse gases since water vapour is 98% of the effect?", "Why isn't water vapour included in climate models?", "Why isn't included on the forcings bar charts?" etc. Any mainstream scientist present will trot out the standard response that water vapour is indeed an important greenhouse gas, it is included in all climate models, but it is a feedback and not a forcing. From personal experience, I am aware that these distinctions are not clear to many, and so here is a more in-depth response (see also this other attempt).
First some basics. Long-wave (or thermal) radiation is emitted from the surface of the planet and is largely absorbed in the atmosphere. Water vapour is the principle absorber of this radiation (and acknowledged as such by everybody). But exactly how important is it? In terms of mass, water vapour is much more prevalent (about 0.3% of atmospheric mass, compared to about 0.06% for CO2), and so is ~80% of all greenhouse gases by mass (~90% by volume). However, the radiative importance is less (since all molecules are not created equal). One way to quantify this is to take a radiation model and remove each long-wave absorber (principally the greenhouse gases, but also clouds and aerosols) and see what difference it makes to the amount of long-wave absorbed. This gives the minimum effect from each component. The complementary calculation, using only each particular absorber in turn, gives the maximum effect. Generally these will not be equal because of overlaps in the absorbing spectra (i.e. radiation at a particular frequency can either be absorbed by water vapour or CO2).
The table @ http://www.realclimate.org/index.php/archives/2005/04/water-vapour-feedback-or-forcing/
shows the instantaneous change in long-wave aborption when each component or combination of components is removed using the radiation code from the GISS GCM. (The source code is available for those who have the patience to get it to work). This isn't a perfect calculation but it's quick and easy and is close enough to the right answer for our purposes. (N.B. This is very similar to what was done by Ramanathan and Coakley (1978) using a single column model - their numbers are in the table for reference). Because of the overlaps, the combined changes are larger than the changes due to each individual component. Another calculation is the instantaneous radiative forcing at the tropopause, but that is complicated for clouds, O3 and Aerosols which have impacts on solar radiation as well as the long wave, so I only give that value for the 'pure' greenhouse gases.
The overlaps complicate things, but it's clear that water vapour is the single most important absorber (between 36% and 66% of the greenhouse effect), and together with clouds makes up between 66% and 85%. CO2 alone makes up between 9 and 26%, while the O3 and the other minor GHG absorbers consist of up to 7 and 8% of the effect, respectively. The remainders and uncertainties are associated with the overlaps which could be attributed in various ways that I'm not going to bother with here. Making some allowance (+/-5%) for the crudeness of my calculation, the maximum supportable number for the importance of water vapour alone is about 60-70% and for water plus clouds 80-90% of the present day greenhouse effect. (Of course, using the same approach, the maximum supportable number for CO2 is 20-30%, and since that adds up to more than 100%, there is a slight problem with such estimates!).
Since we are looking at the whole of the present-day greenhouse effect (around 33 C), it is not surprising that the radiative forcings are very large compared to those calculated for the changes in the forcing. The factor of ~2 greater importance for water vapour compared to CO2 is consistent with the first calculation.
So where does the oft quoted "98%" number come from? This proves to be a little difficult to track down. Richard Lindzen quoted it from the IPCC (1990) report in a 1991 QJRMS review* as being the effect of water vapour and stratiform clouds alone, with CO2 being less than 2%. However, after some fruitless searching I cannot find anything in the report to justify that (anyone?). The calculations here (and from other investigators) do not support such a large number and I find it particularly odd that Lindzen's estimate does not appear to allow for any overlap.
While water vapour is indeed the most important greenhouse gas, the issue that makes it a feedback (rather than a forcing) is the relatively short residence time for water in the atmosphere (around 10 days). To demonstrate how quickly water reacts, I did a GCM experiment where I removed all the water in the atmosphere and waited to see how quickly it would fill up again (through evaporation from the ocean) . The result is shown in the figure. It's not a very exciting graph because the atmosphere fills up very quickly. At Day 0 there is zero water, but after only 14 days, the water is back to 90% of its normal value, and after 50 days it's back to within 1%. That's less than 3 months. Compared to the residence time for perturbations to CO2 (decades to centuries) or CH4 (a decade), this is a really short time.
Only the stratosphere is dry enough and with a long enough residence time (a few years) for the small anthropogenic inputs to be important. In this case (and in this case only) those additions can be considered a forcing. Oxidation of anthropogenic methane (which is a major source of stratospheric water) and, conceviably, direct deposition of water from increases in aircraft in the lower stratosphere, can increase stratospheric water and since that gives a radiative forcing effect, they do appear on the forcings bar chart (under "H2O from CH4"). Some scientists have argued that changes to irrigation and other land use changes (which effect evaporation) are also direct forcings to water vapour amounts, but I think it's cleaner to think of that as an indirect water vapour response to the change.
When surface temperatures change (whether from CO2 or solar forcing or volcanos etc.), you can therefore expect water vapour to adjust quickly to reflect that. To first approximation, the water vapour adjusts to maintain constant relative humidity. It's important to point out that this is a result of the models, not a built-in assumption. Since approximately constant relative humidity implies an increase in specific humidity for an increase in air temperatures, the total amount of water vapour will increase adding to the greenhouse trapping of long-wave radiation. This is the famed 'water vapour feedback'. A closer look reveals that for a warming (in the GISS model at least) relative humidity increases slightly in the tropics, and decreases at mid latitudes.
How do we know that the magnitude of this feedback is correctly simulated? A good test case is the response to the Pinatubo eruption. This caused cooling for up to 3 years after the eruption - plenty of time for water vapour to equilibriate to the cooler sea surface temperatures. Thus if models can simulate the observed decrease of water vapour at this time, it would be a good sign that they are basically correct. A good paper that demonstrated this was Soden et al (2002) (and the accompanying comment by Tony DelGenio). They found that using the observed volcanic aerosols as forcing the model produced very similar cooling to that observed. Moreover, the water vapour in the total column and in the upper troposphere decreased in line with satellite observations, and helped to increase the cooling by about 60% - in line with projections for increasing greenhouse gases.
To be sure there are still some lingering uncertainties. Some recent data indicates that tropical upper tropopsheric water vapour does not quite keep up with constant relative humidity (Minschwaner and Dessler, 2004) (though they still found that the feedback was positive). Moist convection schemes in models are constantly being refined, and it's possible that newer schemes will change things . However, given the Pinatubo results, the models are probably getting the broader picture reasonably correct
It is your job to prove that CO2 is increasing rapidly due to man-made effects, so then you must show, Mr.Kuvacs, evidence that indicates that there IS NO, I REPEAT, NO UNCERTAINTY ABOUT CLIMATE SENSITIVITY.
The ball is in your court, Mr. Kuvasz and please, you are a trained scientist. I know you can explain all of these questions completely,precisely and without extra verbiage.
Finally, There is a comment, which I am sure you will reject, but it is a comment which I am sure is true, made by a climatologist named Patrick J. Michaels, professor of environmental sciences at the University of Virginia.
Quote:"NO ONE GETS LARGE GRANTS BY SAYING SOMETHING ISN'T A PROBLEM.MEANWHILE, THE TEN BILLION( T E N B I L L I O N???) THROWN AT CLIMATE MODELING RESEARCH IN THE LAST 15 YEARS WAS WASTED"...PICTURE THIS, IT'S 1992 AND THERE'S A HEARING, SENATOR ALBERT GORE SAYS HE THINKS GLOBAL WARMING IS A SERIOUS ISSUE AND WOULD IT BE WORTHWHILE TO SPEND $1 BILLION OR SO STUDYING IT? NO ONE IS GOING TO SPEAK UP AND SAY IT'S AN OVERBLOWN PROBLEM, IF HE DID ALL HIS COLLEGUES WOULD TAKE OUT THEIR KNIVES AND THROW THEM INTO HIS BACK BEFORE HE COULD LEAVE THE ROOM".
