Open Mind

MSU

December 31, 2007 · 35 Comments

Surface air temperature is monitored using thermometers. Temperature above the surface can also be measured with thermometers using radiosondes, radio transmitters which relay weather information to the ground from instruments usually attached to balloons and allowed to rise through the atmosphere. However, there are some distinct problems with balloon-borne radiosonde data: there’s poor coverage, especially over the oceans, and both instruments and procedures have changed over the years, making it difficult to determine long-term trends with accuracy. But since late 1978, temperature in various layers of the atmosphere has been measured by satellites carrying a microwave sounding unit (MSU), or its more advanced cousin the advanced microwave sounding unit (AMSU). The satellite missions were intended to aid weather studies rather than climate studies, but the data they have returned has been examined for its implications relating to climatic change in earth’s atmosphere.


Of course the satellite measurements are not without their difficulties too. The data come not from a single satellite but from more than a dozen, starting with TIROS-N in late 1978 and extending through NOAA-17 and AQUA. This leads to the tricky problem of pieceing the various data sets together into a continuous time series. Also, the instruments age over time, and more important the orbit changes. Not only have the satellite orbits slowly decayed (getting a bit lower as the years pass), they have also drifted. Drift affects the time at which the satellite crosses the equator, and hence the time of day at which measurements apply; since temperature depends strongly on the diurnal cycle (it’s hotter at noon than midnight!) it’s necessary to correct carefully for satellite drift in order to have a good representative measure of the atmosphere’s temperature which is not affected by the day-night cycle.

And as if that weren’t complicated enough, satellites don’t measure the temperature in a thin atmospheric layer but in a large region. The two microwave “channels” which have been most studied for climate information are MSU channels 2 and 4. Channel 2 (giving temperature T2) measures mostly the troposphere but is also affected by the surface and the stratosphere, while channel 4 (giving temperature T4) is almost entirely reflective of temperature in the stratosphere.

The initial studies of MSU data indicated that the troposphere wasn’t warming nearly as fast as the surface, in fact it wasn’t clear that the troposphere was warming at all. But by 2000 some of the problems with handling the data had been identified and attempts were made to compensate for them. Much of this work was carried out by a team at the University of Alabama at Huntsville, the UAH team. They attempted to correct for some of the effect of orbit decay and drift, and of stratospheric influence on the tropospheric T2 channel, by combining data taken at different viewing angles. Using information from observations straight downward (nadir) and those taken near the horizon, they devised a method to compensate some of the influence which was stratospheric rather than tropospheric (Christy et al. 2000). They also created a time series designed to represent the temperature, not in the mid-troposphere, but in the lower troposphere, creating the “T2LT” data set, which is not directly observed by the satellite instruments but is derived by transforming other satellite observations. By 2000 they estimated that the trend in tropospheric temperature from 1979 onward was 0.04 K/decade while the lower-troposphere trend was 0.06 K/decade (the surface trend from that time is about 0.17 K/decade).

The warming trends found were less than expected. Computer models of global climate predicted that the troposphere should warm faster than the surface; for the globe as a whole the tropospheric warming should be about 20% larger than surface warming (Hansen et al. 2002, J. Geophys. Res. 107, doi:10.1029/2001JD001143), and in the tropics the tropospheric warming should be about 50% larger (Hegerl & Wallace 2002, J. Clim. 15, 2412–2428). It’s important to emphasize that this is not a prediction which depends on global warming being due to man-made greenhouse gases. Enhanced tropospheric warming is common to all causes of global warming, be it due to greenhouse gases, solar variability, or whatever. Hence enhanced tropospheric warming cannot be used to determine the cause of global warming.

A complete re-analysis of MSU/AMSU data was done by a team at Remote Sensing Systems, leading to a rival of the UAH data set, the RSS time series (Mears et al. 2003). Using what they consider to be superior corrections for orbital changes, and a better way of merging the various satellite data sets, by 2003 the RSS data showed considerably more tropospheric warming than the UAH data, but still not as much as expected from computer models. Mears et al. summarize the differences thus:

RSS UAH
Diurnal adjustment: origin Derived using hourly output from the CCM3 climate model, and a radiative transfer model Derived using observed cross-scan differences measured by the MSU instruments
Diurnal adjustment: methodology Adjustments all made to a single reference time (noon, local time) Adjustments made to different reference times for each satellite (local time of first observation for each moth of instrument operation)
Determination of target factors All valid 5-day averages with simultaneous observations for two or more satellites used in least squares regression procedure Only long-term periods of satellite overlap used; some target factors set to zero if their improvement to the intersatellite differences are insufficient to warrant use
Determination of intersatellite offsets Determined in a unified way during the regression procedure for determining target factors Determined using a single path or ‘‘backbone’’ that links together the various satellites
Smoothing before target factor determination 5-day averages 60–120-day averages

All the differences in methodology lead to differences in the result, but the primary difference arises from the different methods of merging different satellite data sets:


A more important difference between our methodologies is the way in which we determine the intersatellite merging parameters. We use a unified approach where each overlapping pentad average is treated with equal weight to determine both the target factors and the intersatellite offsets. The equal weighting of each 5-day overlap serves to deemphasize periods of short overlap without ignoring them altogether. Christy et al. (2000, 2003) impose a minimum time period over which an overlap must occur before it can be taken into account to help determine the merging parameters. This leads CS to discard the TIROS-N–NOAA-6, NOAA-7–NOAA-9, NOAA-8–NOAA-9, NOAA-9–NOAA-10, and NOAA-10–NOAA-12 overlaps when determining their target factors. Their intersatellite offsets are then determined by evaluating the mean difference between coorbiting satellites utilizing a single path that connects all the satellites in question.

Writing in 2003, Mears et al. estimated the global tropospheric warming trend at 0.097 +/- 0.02 K/decade; by that time the UAH group had updated their procedures such that their estimated trend was 0.09 K/decade, higher than their previous estimate but still lower than that of the RSS group and that expected from computer model simulations.

Meanwhile Vinnikov & Grody, in yet another analysis, suggested that the method used by the UAH group was insufficient to compensate for the impact of the diurnal cycle on the observations. As they say, “Christy’s group used the MSU measurements by themselves to evaluate the diurnal cycle. Unfortunately, however, the diurnal cycle cannot be validated with in situ data because of insufficient observations.” Using simultaneous determination of the instrument calibrations and effect of the diurnal cycle to create yet another data set which I will call the VG data. Vinnikov & Grody estimated the global tropospheric temperature trend at 0.22 to 0.26 deg.C/decade, actually larger than predicted by climate models. In more recent work, they apply modified least squares rather than ordinary least squares, which reduces the estimated trends to 0.21 K/decade for the tropics and 0.20 K/decade for the globe as a whole.

But it was still not clear that these procedures remove all the influence of the stratosphere from the T2 data, to give a time series which truly represents the troposphere without stratospheric influence. For this reason, Qiang Fu and colleagues at the University of Washington produced yet another version of estimated tropospheric temperature based on satellite observations (Fu et al. 2004). They estimate the stratospheric contribution to MSU channel 2 temperatures using MSU channel 4, which records only stratospheric temperatures, calibrating the correction using radiosonde measurements. As they say in the abstract, “The resulting trend of reconstructed tropospheric temperatures from satellite data is physically consistent with the observed surface temperature trend. For the tropics, the tropospheric warming is ~1.6 times the surface warming, as expected for a moist adiabatic lapse rate.” Hence a time series of tropospheric temperature was published which did not contradict computer model predictions of faster warming in the troposphere than at the surface (slightly faster globally, much faster tropically).

The University of Washington analysis can be applied to both the RSS and UAH data sets, leading to two further time series of tropospheric temperature, the UW-RSS and UW-UAH data sets. The UW method can also be applied to the analysis of Vinnikov & Grody, yielding a very large estimated tropospheric warming trend of 0.33–0.37 K per decade.

Most of the T2 data sets are available online, including RSS, UAH, UW-RSS, UW-UAH, and VG. I decided to determine the trend rates from each with the most up-to-date data sets, and simply to examine the data to see how they portray temperature evolution in the troposphere. The monthly averages have so much noise that to plot the different data sets together simply creates a confusion of dots, but by smoothing the data (on a 1/2-year time scale) we can get a better idea of their time evolution:

smooth.jpg

The most obvious thing is that all the data series tend to rise and fall together, and show considerable short-timescale detail. Hence they give a very good picture of the changes which are related to weather rather than climate, so fulfilling their intended purpose admirably. But in terms of long-term trends, there is considerable disagreement, with the VG series showing stronger warming than the others and the UAH series showing considerably weaker warming.

Linear regression (on the data rather than the smoothed series) gives us an idea of the trend rates using the most up-to-date data, and their probable errors. I emphasize that these errors (which are two standard deviations) reflect only the uncertainty due to the regression alone, they do not reflect any uncertainty in the data values themselves. The global trends (in addition to the surface warming rate from NASA GISS data) are:

trend11.jpg

The trends for the tropics only are:

trend21.jpg

All the analyses except UAH are compatible with computer model projections of tropospheric warming; the error ranges include the values expected from model simulations. The UAH analysis, however, is incompatible with model simulations, showing warming which is just too little to accord with model results.

Which of the data sets it to be believed? Frankly, I don’t know. I would say that the UW analysis seems to me to have a much better way of compensating for the stratospheric influence on the T2 channel than its predecessors, and I would also say that in my opinion, the VG method for computing the diurnal effect seems by far the most logical. However, the RSS and UAH analyses are more often referred to in the scientific literature; whether this is due to their having been first, and having existed in the literature longer, I don’t know. I also don’t know enough about the details of how the instrument biases are corrected, or how the different satellite data sets are combined, to say with confidence which analysis is closer to the truth.

Categories: Global Warming · climate change

35 responses so far ↓

  • Barton Paul Levenson // December 31, 2007 at 8:04 pm

    Welcome back, Tamino.

    The tropospheric temperature data interests me. Someone, I forget whether it was on RealClimate or somewhere here, was insisting that the troposphere wasn’t warming as fast as the surface and therefore that global warming wasn’t happening, or something of the sort. Hope he reads this.

  • Heretic // January 1, 2008 at 5:34 am

    That argument is common, BPL, I’ve seen it several times. It’s always hard to refute before Tamino actually gets down to doing the leg work. Infinite thanks from the lazy and mathematically challenged (I know that’s not you, BPL) to our host.

  • jacob l // January 1, 2008 at 5:34 am

    happy new year tamino
    how much of the “controversy’s” in the past year are because for most of the past century weather data was for weather and not climate ???

    2 other questions .

    1. would having more satellites in the sky help?
    2. how many thermometers are needed to measure the earth’s temperature??

    thanks for all of your hard work .

    [Response: More satellites would definitely help, especially if designed to observe important climate-related parameters.

    I have heard it said that the global temperature field has about 60 “degrees of freedom” so that’s the minimum number of thermometers necessary to characterize the global temperature field. But more is better.]

  • fred // January 1, 2008 at 9:18 am

    Tamino, many thanks. Excellent clear summary which would have taken days or weeks to get to without your work. Hope finishing it didn’t wreak too much havoc on your family festivities!

  • ChrisC // January 1, 2008 at 9:59 am

    Jacob l and Tamino:

    I’ve got a (little) bit of experience using ATOVS (Advanced TRIOS Operational Vertical Sounder) data, which is a satellite sounder run by NOAA aboard the GOES11 (I think) satellite, primarily for the assimilation of data into numerical weather models from data sparse regions (espcially over the ocean as Tamino mentioned).

    Extraction of a vertical atmospheric profile is ahighly underdetermined problem. I think 60 degrees of freedom is likely an underestimate (from memory I think it’s closer to 90) . ATOVS has 20 IR channels and 20 microwave channels.

    As such, you first need a reliable “guess” of the vertical profile (a so called “weight function”), which is (sort of) a guess of which level of the atmosphere you will be measuring at a certain wavelength. However, if you are using satellite derived data to plug into weather models, you can’t very well use weather model output to determine your weight function!

    So here is where issues in obtaining and using this data creep in. For many satellite systems, this “guess” profile is built up from a data base of previously measured profiles over the last couple of days at a similar lattitude and longitude (a rolling database), combined with advanced radiative transfer models. However, this is no gauantee that your guess today reflects reality. This system works quite well for “weather”.

    Longterm profile databases are generally not as usefull compared to “rolling databases” when determining atmospheric profiles for using in the determination of “weather”. Many of the issues surrounding error performance of satellite data seems to stem from the guess profiles. As of yet, I’m not as confident using data obtained from satellite measurements as from good ol’ weather balloons, although in data sparse regions, I don’t really have a choice.

    More satellites would definatly be an advantage. Along with getting more measurements in different electromagnetic channels to tie down degrees of freedom, AMSU deveices are generally placed abaord polar obting vehicles. More vehicles = more coverage.

    As an aside, satellite sounding measurements are obtained using the very similar radiative transfer models to those found in climate models. It’s subtlties like this that lay skeptics seem to miss.

  • Bob // January 1, 2008 at 3:47 pm

    BPL and Heretic,

    I think you are confused. What Tamino has done is compare the lower trop (near surface) data with the surface record, a very welcome, informative and interesting post by the way. The recent argument you refer to is that the middle troposphere (about 5 to 10 km above the surface) is not warming at a rate predicted by the models and global warming theory and physics.

    [Response: No, all the trends calculated here are for the mid-troposphere. The UAH and RSS teams also provide lower-troposphere data, but UW and VG do not. All mid-troposphere data sets are compatible with computer model projections except that from the UAH team.]

  • Bob // January 2, 2008 at 12:04 am

    Tamino,

    My appologies on the earlier post. At the risk of wearing out my welcome, can you elaborate on your statement: “All the analyses except UAH are compatible with computer model projections of tropospheric warming; the error ranges include the values expected from model simulations.” I have seen a discussion at RC where the average computer model predicts an amplification of over 3, whereas AR4 figure 9.1 suggests an amplification of about 2 from one particular model. I am particularly interested as to how one correctly compares data sets with error bars, and I presume you can shed some light on this. Thanks for your efforts.

    [Response: I saw the post on RC, the graph which gives much larger tropospheric amplification was for 2xCO2, not for modern conditions. It seemed likely to me that warming to this point in time must be less, more in line with that given in the references included in this post.

    I looked at IPCC AR4 wg1 fig. 9.1c (for greenhouse-gas warming), and tropospheric warming in the tropics seems to be about 2x surface warming at *some* (considerable) levels of the troposphere, but not at all levels. As far as I know, the definition of “troposphere” used for numerical estimates of tropospheric amplification (and by the various groups processing satellite data) extends from about 850 to 300 hP, which includes a good portion which shows less than the 2x amplification and excludes much of the 2x or more amplified region of fig. 9.1c from IPCC AR4 wg1. Unfortunately I don’t have the detailed results of model simulations to compute the numbers myself.

    Only the analysis of VG *with* the correction used by UW for stratospheric influence, is in complete agreement with 2x tropical tropospheric warming. While both their methodologies (the VG correction for diurnal cycle and the UW correction for stratospheric influence) make very good sense to me, my impression is that the combined VG-UW data set (which unfortunately I haven’t found online yet) is considered too much warming to be realistic, as much above what models predict as the UAH analysis is below — but I may be mistaken in this impression. If models really do predict 2x warming for the tropical troposphere (which is not impossible, since the reference given for about 50% greater warming is a few years old) then only this analysis is in complete agreement, but the RSS and UW-RSS results are still compatible if the tropospheric tropical warming is on the high side of the error range and/or the tropical surface trend is on the low end. Then of course there’s the sizeable issue that the error bars are for the regression only, and don’t include uncertainties in the processing which leads up to the data. And — it’s well to bear in mind that the computer model results are well outside my area of extpertise!

    Properly to compare results from two data sources, one should compute their difference or ratio (depending on which one wishes to estimate), and compute the expected variation in that difference or ratio. For a difference, variances are additive (and standard deviations are the square root of variances); for a ratio, they are most assuredly not additive but if the variances are not large compared to the values themselves, then the ratio of variance to value is approximately the sum of the ratios of variance to values for the numerator and denominator. In this case, the variances are big enough compared to the values themselves that this only a rough approximation. And all of that applies only if the quantities being compared are independent; if not, one must take into account the CO-variances of the quantities. I’d say that this post is an informative and indicative cursory look at the results, but the statistical treatment wouldn’t pass muster for peer review.]

  • EliRabett // January 2, 2008 at 1:53 am

    FWIW, ch4 of the AMSU is in trouble.
    http://daac.gsfc.nasa.gov/AIRS/amsu_ch4_noise_increase.shtml

    [Response: Just a note: channel 4 of the AMSU is not the same as channel 4 of the MSU; for the AMSU ch4 peaks at 850 hP (low troposphere) but for MSU ch4 peaks at more like 60 hP (upper stratosphere).]

  • Bob // January 2, 2008 at 2:34 pm

    this paper appears to be timely and on topic:

    Randall, R. M., and B. M. Herman (2007), Using Limited Time Period Trends as a Means to Determine Attribution of Discrepancies in Microwave Sounding Unit Derived Tropospheric Temperature Time Series, J. Geophys. Res., doi:10.1029/2007JD008864, in press

    with the abstract

    “Limited Time Period (LTP) running trends are created from various Microwave Sounding Unit (MSU) difference time series between the University of Alabama in Huntsville (UAH) and Remote Sensing System (RSS) group’s lower troposphere (LT) and mid troposphere to lower stratosphere (MT) channels. This is accomplished in an effort to determine the causes of the greatest discrepancies between the two data sets.

    Results indicate the greatest discrepancies were over time periods where NOAA-11 through NOAA-15 adjustments were applied to the raw LT data over land. Discrepancies in the LT channel are shown to be dominated by differences in diurnal correction methods due to orbital drift; however, discrepancies from target parameter differences are also present.

    Comparison of MSU data with the a reduce RATPAC radiosonde dataset indicates that RSS’s method (use of climate model) of determining diurnal effects is likely overestimating the correction in the LT channel. Diurnal correction signatures still exist in the RSS LT time series and are likely affecting the long term trend with a warm bias. Our findings enhance the importance of understanding temporal changes in the atmospheric temperature trend profile and their implications on current climate studies.”

  • dhogaza // January 2, 2008 at 3:40 pm

    You got that from Pielke Sr’s website, I imagine? :)

    Look what he says about the paper:

    While both UAH and RSS are outstanding research groups, with respect to the assessment of multi-decadal tropospheric temperature trends, the independent comparison reported in Randall and Herman indicates that the trend values of the UAH group are more accurate.

    Just like that, one paper establishes the UAH data is more accurate. He doesn’t wait for any rebuttal or response, just, BOOM! They’re right! RSS is wrong!

    Given that UAH has made a series of fundamental errors in their work, including a sign error in a term in an equation (9th grade algebra), which Tamino was kind enough not to recount in his objective analysis of the competing analyses, I’d say it’s premature to say that suddenly UAH is more accurate than RSS. UAH has claimed this before and RSS has always gotten the best of them AFAIK …
    I notice that he himself has a paper published in JGR that trots out, among other things, the surface temp siting stuff being touted by CA & the surface stations folk.

    Something tells me that the combined effort to show that warming isn’t really happening (only an artifact of thermometer siting and, for satellite data, errors by RSS) is going to be a very hard sell in a world where there are so many other independent lines of evidence that point to global warming.

    And, of course, note who he’s in bed with …

    This analysis, as well as other studies such as the McKitrick and Michaels JGR paper, should be a wake up call that erroneous information is being communicated to policymakers and others on the actual radiative imbalance of the climate system. The 2007 IPCC ignored assesing these unresolved issues which, as a consequence, result in a warm bias in their conclusions on the magnitude of global warming.

    Oh oh, it’s M&M again.

  • Eli Rabett // January 2, 2008 at 5:38 pm

    Yeah, which means big trouble if this is a loss of insulation or coolant problems.

  • Paul S // January 2, 2008 at 9:18 pm

    == dhogaza says:==

    =”Just like that, one paper establishes the UAH data is more accurate. He doesn’t wait for any rebuttal or response, just, BOOM! They’re right! RSS is wrong!”=

    Why not read the paper before commenting dhogaza?

    What are YOU saying? Is the paper right or wrong? Or, as it appears, are you just venting your spleen with some off the cuff character assassination?

    Why not go for the gusto and shred R. M. Randall and B. M. Herman? Don’t worry about facts, the important thing is YOU don’t like what they say, so shred them too. Go crazy.

    [Response: Perhaps Pielke has made the mistake of believing that Randall & Herman are correct based on his disbelief of AGW rather than an objective review of their paper, and that’s what dhogaza is objecting to.

    Randall & Herman’s work should be judged on its own merits, apart from preconceptions. So I paid to download the paper, and will comment on it after I’ve reviewed it thoroughly.]

  • Paul S // January 2, 2008 at 10:42 pm

    Tamino, you give dhogaza too much credit. Pielke wasn’t even a part of the thread until dhogaza used his mind reading skills to bring him into to it.

    Glad to hear you will comment on the paper and thans for your blog; it is one of the few on climate that I visit on a regular basis.

  • Hank Roberts // January 2, 2008 at 11:45 pm

    > mind reading skills

    RP’s writing style is easy to recognize.
    Google for this, taken from g’s posting as a quoted string:

    “Comparison of MSU data with the a reduce RATPAC radiosonde dataset indicates”

    As of just now, Google found it only once, so they haven’t indexed this thread yet. Tomorrow they’ll also find it here twice. Nowhere else in the world.

    Climate Science: Roger Pielke Sr. Research Group News » 2008 » January
    Comparison of MSU data with the a reduce RATPAC radiosonde dataset indicates that RSS’s method (use of climate model) of determining diurnal effects is …
    climatesci.colorado.edu/2008/01/

  • Hank Roberts // January 2, 2008 at 11:46 pm

    Oh, and, Tamino — thanks from me too for paying for and reading the original. If you take PayPal for weblog tips, I’d be glad to contribute to encourage your doing this.

    [Response: That’s very kind of you. But like most things worth doing, this is its own reward.]

  • Hank Roberts // January 3, 2008 at 12:33 am

    PS, checking my assumption, I mistoko that for RP’s typing looking for a search string, but, in fact, RP did quote that directly from the abstract.

    It’s paywalled if you look for it via the AGU cite, but via the link to it on RP’s website I could download the PDF file:
    http://www.agu.org/journals/pip/jd/2007JD008864-pip.pdf

  • dhogaza // January 3, 2008 at 8:11 am

    What are YOU saying? Is the paper right or wrong? Or, as it appears, are you just venting your spleen with some off the cuff character assassination?

    I’m not saying the paper is right, nor wrong.

    I’m saying it’s premature to say “this proves that the UAH people are right, and the RSS people wrong, therefore the IPCC is overestimating warming and policymakers worldwide are being misled and should ignore them”.

    Remember the UAH people are those who shouted to the world that the satellite record shows cooling, not warming, back around the turn of the century. This was paraded around the right-wing world, with the Wall Street Journal proclaiming in a widely-quoted editorial that the UAH work was “the wooden stake in the heart of the global warming myth”.

    Unfortunately, RSS and others proved that the UAH people had made some remarkably boneheaded errors in their analysis, errors they would’ve probably caught if they weren’t driven by their right-wing fundamentalist christian political views (Spencer, for instance, is a creationist who denies evolution).

    So pardon me if I am skeptical of a new paper that proclaims that RSS, and, as Tamino’s analysis above shows, by extension others, are wrong this time and UAH right.

  • Alan Woods // January 3, 2008 at 10:57 am

    What use would an Open Mind thread be without the usual dhogaza melodrama?

    Pielke Sr didn’t say that RSS was “wrong”, he asserted that UAH was more accurate. I’m sure you can tell the difference.
    And, with the RSS anomaly currently 0.22 degrees cooler than UAH, you might soon be agreeing with him.

  • dhogaza // January 3, 2008 at 12:40 pm

    Pielke Sr didn’t say that RSS was “wrong”, he asserted that UAH was more accurate. I’m sure you can tell the difference.

    Oh, pardon me for my sins.

    Let me rephrase my comment, then.

    I’m saying it’s premature to say “this proves that the UAH people are generating more accurate results than the RSS people.”

    Happy?

    Pielke Sr’s position is clear. And he cherry-picks papers to support that position. That is clear, too.

  • fred // January 3, 2008 at 2:23 pm

    “Spencer, for instance, is a creationist who denies evolution”

    You are never going to understand, are you, that the validity of an argument offered by X does not depend on what you think of X’s religion, race, gender, national origin.

    I for instance am a Christian Democrat of mixed race living in Europe. Now, tell me what that entitles you to conclude about my argument on the merits of Ruby versus Perl for web applications.

  • tamino // January 3, 2008 at 3:55 pm

    I for instance am a Christian Democrat of mixed race living in Europe. Now, tell me what that entitles you to conclude about my argument on the merits of Ruby versus Perl for web applications.

    Nothing at all.

    But if you claimed that evolution is wrong, that instead all species (including humans) were created “as is” by God, then I’d conclude that you’re a religious extremist who fails to understand the nature of rational thought or scientific proof, and that your opinions on scientific matters are suspect.

    As it is I think your suggestion that criticism of fundamentalist anti-scientific belief is like unto bigotry, even to the point that you raise the spectre of race, gender, and national origin, is both mean-spirited and bone-headed.

  • Hank Roberts // January 3, 2008 at 3:57 pm

    Is Christian Democrat an organized religious political party, or a statement about religious preference and political preference? Sorry, don’t know what they think about web design.

  • dhogaza // January 3, 2008 at 4:13 pm

    You are never going to understand, are you, that the validity of an argument offered by X does not depend on what you think of X’s religion, race, gender, national origin.

    No. However, the fact that Spencer IS a professed science denier, who admits to the fact that his religious beliefs inform his denialism, does raise questions about his objectivity and his ability to evaluate scientific evidence, doesn’t it?

    Christy is on record as saying he believes that warming will be good for us. He bases this to a significant degree on his experience working in Africa on a baptist mission and his belief in the bible, and has said so in writing.

    His science has to be evaluated objectively, of course, but when people, in writing, discuss how their religious world views inform their opinions about science, who are we to dismiss those statements?

  • dhogaza // January 3, 2008 at 4:28 pm

    Argh, where’s the edit button?

    I meant “No, the validity of an argument doesn’t depend on one’s beliefs”, not “No, I’ll never understand”.

    Once again, shooting myself in the foot.

  • JesusChristHimself // January 3, 2008 at 5:23 pm

    If your doctor does not believe in transfusions on religious grounds, and you have observed you’ve lost a lot of blood, the logical thing to do if he claims you do not need a transfusion is to get a second opinion. If the same doctor says he prefers PCs over Macs, entertain him for a few moments by asking why.

  • Paul S // January 3, 2008 at 10:12 pm

    =dhogaza said:=

    =”I’m not saying the paper is right, nor wrong.=”

    Of course not. You are simply using the paper as a prop to sidetrack the thread into a completely irrelevant topic. Whether it is right or wrong is irrelevant to you.

    =dhogaza also said:=

    =”I’m saying it’s premature to say “this proves that the UAH people are right, and the RSS people wrong, therefore the IPCC is overestimating warming and policymakers worldwide are being misled and should ignore them”.”=

    Why not say that then and leave all the other crap out of your post?

    =dhogaza goes on to say:=

    =”Remember the UAH people are those who blah blah blah blah. This was paraded around the right-wing world, with the Wall Street Journal proclaiming blah blah blah blah.’”=

    Who care what the WS Journal says? Tamino started an interesting thread and you decided to throw a tantrum in it. Take your rant elsewhere. There are lots of blogs for blowhards like yourself.

    =dhogaza concludes:=

    =”So pardon me if I am skeptical of a new paper that proclaims that RSS, and, as Tamino’s analysis above shows, by extension others, are wrong this time and UAH right.”=

    Well, it’s not a wrong/right dichotomy. It is an analysis of very complicated data with the goal of improving its integrity. But go ahead, change the to topic to creationism.

    =”Once again, shooting myself in the foot.”=

    No kidding.

  • dhogaza // January 4, 2008 at 7:04 am

    Of course not. You are simply using the paper as a prop to sidetrack the thread into a completely irrelevant topic.

    I didn’t bring the paper into the discussion.

    Why not say that then and leave all the other crap out of your post?

    Why don’t you stop telling me what to do?

    Whether it is right or wrong is irrelevant to you.

    True in the sense that it’s too early to claim that this paper shows that UAH is more accurate than RSS.

    And UAH’s track record is relevant in this regard. A batting average of around .200 isn’t very good even in baseball, when it’s your average for getting the analysis of the data of your own pet project right, it’s downright abysmal.

    Time will tell who is right or wrong, but I’ll make two predictions:

    1. The right-wing blogosphere will be trumpeting this paper as though it’s the stone tablet-delivered word of God.

    2. No matter whether or not the results hold, they will continue to claim the paper has it right for years. This will include political figures of considerable power such as Inhofe.

    Who care what the WS Journal says?

    A LOT of people. You didn’t know that?

    Beyond this, the point is that Christy and Spencer have not simply published scientific results, but (Christy especially) play a very visible role in the politics of climate science.

    Once a scientist enters the political realm and becomes an advocate, as Christy has done (first for the outright denialist position, more recently for the “less warming than the mainstream says and all the CO2 will cause an explosion of crop prodictivity” position), he is fair game.

    Likewise, Spencer has used his position as a darling of the right to advocate for a form of creationism. His public advocacy makes him fair game.

    In other words, if you don’t want to take a hit, don’t walk on the field. And if you do, take your helmet.

    Take your rant elsewhere.

    I missed the part where Tamino appointed you blogczar.

    Linky? Hmmm … it’s probably over at CA.

  • tamino // January 4, 2008 at 1:03 pm

    I’m reading the paper by Randall & Herman now, and processing some of the data so I can better follow their argument. It’s a fair amount of work, but that’s what I do.

    I’ll post my own opinion on their work after I’ve formed one, probably in 2 or 3 days.

  • Paul S // January 5, 2008 at 1:15 am

    Looking forward to it tamino. And since it’s your blog, do you mind if I put dhagoza on a leash until you publish your results? ;)

    [Response: I’d prefer that the two of you both refrain from provocative statements, at least until I can offer my opinion on the work of Randell & Herman.]

  • fred // January 5, 2008 at 7:24 am

    My point is, it would be more productive to focus on the arguments. That way, you’d have a chance of refuting them. Whereas pointing out Christy or Spencer’s religious or political affiliations only prompts a yawn. We are not trying to figure out who to trust as an authority, we are trying to figure out which arguments are correct. Who offered them or why is simply immaterial.

    People also can have absolutely idiotic sets of ideas about some things and be right about others. You have to take them on their merits. Newton was a crazed alchemist, Leibniz was the model for Pangloss in Candide. But we use calculus every day, and the bridges (mostly) stay up. Falsifying Spencer’s climate views will significantly increase our knowledge of climate. That is what we need to get on with.

    [Response: I agree. The more we can keep focus on the relevant arguments, the better our chances to learn.]

  • dhogaza // January 5, 2008 at 8:52 am

    do you mind if I put dhagoza on a leash until you publish your results?

    PaulS, I have refrained from making any personal comments about you on this thread, despite several posts on your part that consist primarily of personal attacks.

    If you’d wish that I continue doing so, would you please put a stopper in it?

    This will be my last post until Tamino posts his results. I thought about posting so earlier but didn’t think it was necessary, but given the tone of PaulS’s comment …

    If, afterwards, PaulS insists on sniping at me on a personal level, I shall return the favor in spades.

    [Response: I’d prefer that the two of you both refrain from provocative statements.]

  • Carrick // January 5, 2008 at 10:11 pm

    Christy has a more recent publication that you may be interested in.

    You’re still using least-squares fit though to analyze trends on this data. Tisk tisk.

    [Response: See the response to your previous comment.]

  • John Finn // January 11, 2008 at 12:30 pm

    Dhogaza says

    “Just like that, one paper establishes the UAH data is more accurate. He doesn’t wait for any rebuttal or response, just, BOOM! They’re right! RSS is wrong”

    Ok - RSS is right and UAH wrong in which case we have a cooling trend in the troposphere over the past decade and the coolest Nov/Dec combined since 1992 and the fall-out from Pinatubo.

    Take your pick

  • Hank Roberts // February 25, 2008 at 10:46 am

    > Randall & Herman

    How’d that look?

  • Eric Swanson // March 3, 2008 at 11:13 pm

    Interesting discussion, especially the part about Spencer being a Creationist. I’ve often thought that Christy’s views might be biased, especially as he began as a Baptist preacher and missionary. One must remember that Huntsville is in the Bible Belt…

    I just wanted to mention the fact that Spencer and Christy have not yet addressed the problem I found with their MSU data over the Antarctic. RSS exclude data over the Antarctic, that is, poleward of 70S. I think that’s reasonable, but that might not be enough. Here’s the reference to my 2003 paper:

    R. E. Swanson (2003), “Evidence of possible sea-ice influence on Microwave Sounding Unit 2 tropospheric temperature trends in polar regions”, Geophys. Res. Let., VOL. 30, NO. 20, 2040, doi:10.1029/2003GL017938.

    I also offered comments during the CCSP SAP1-1 review (Temperature Trends in the Lower Atmosphere), in which I mentioned these problems and also the fact that the MSU ch 2 data did not exhibit the unusual annual cycle seen in the T2LT product. That observation (along with the graph I submitted, which was edited out of my comments) was ignored.

    E. S.

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