“Carbon Emissions” Warm The Atmosphere Faster Than We Thought Or Something

While the vast majority of legitimate research seems to prove that CO2 doesn’t cause the warming that the Cult of Climastrology thinks it does, Treehugger’s Sami Grove is both Very Concerned and Very Elated about other research

Cutting emissions slows climate change faster than we thought

Global carbon emissions stalled last year. China’s coal use is falling. Solar power is becoming increasingly competitive. Heck, even some forward thinking utilities arerethinking their reliance on fossil fuels.

For the first Earth Day in a very long time, I am hopeful we might see some very real progress on cutting carbon emissions, much quicker than we ever thought possible. And yet, every time I voice this optimism, the pessimists pipe up:

“We’ll never cut emissions fast enough… Runaway climate change is already upon us… Carbon emissions hang around in the atmosphere for decades… etc etc ”

I too had been under the impression that emissions cuts can take many, many decades to have an impact on the climate. So while tooling around on the internet last night, and trying to avoid annoying EArth Day press releases, I was excited to read oabout new research that came out in December last year, which suggests that CO2 emissions warm the climate quicker than we thought.

Why would he be happy about that? Because, Sami believes that if it warms it quicker, removing it can stop the warming quicker. Hey, maybe that’s the reason for this?

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6 Responses to ““Carbon Emissions” Warm The Atmosphere Faster Than We Thought Or Something”

  1. Jeffery says:

    While the vast majority of legitimate research seems to prove that CO2 doesn’t cause the warming that the Cult of Climastrology thinks it does

    Well that’s great news… but why don’t you share some of that “legitimate research” with the rest of the world? It’s not fair to keep it to yourself.

    I see you continue to recite the broken meme that the Earth has stopped warming. The RSS dataset, which purports to measure the atmospheric temperature several kilometers above the Earth’s surface, and which shows much more variability than the other datasets, is the only one that gives you the result you crave so desperately. Datasets that rely on surface temperatures show continued warming that matches quite nicely with CO2 increases, thank you very much.

    The residual Deniers are looking more and more like the Flat Earth Society.

  2. john says:

    Teach why would you think that satellites 100 miles from Earth measuring the atmosphere where almost no one lives would be more reliable than thermometers on the planet surface where I and most everyone else lives ?
    The “Lord” Monckton has a powerful hold on his devotees. That seem to overlook his claims that his quack medicine doesn’t cure HIV and multiple sclerosis It even cures Graves disease, that causes bulging bug eyes, most notably in Marty Feldman the comedian. It hasn’t seemed to help all that much in the case that the “Lord” Monckton exhibits.
    And did you know he is a birther? well of course he just HAS to be
    http://dailycaller.com/2012/03/22/lord-monckton-im-no-birther-but-obama-birth-certificate-plainly-a-forgery/

  3. Kevin says:

    Jeffrey or John said,
    “Teach why would you think that satellites 100 miles from Earth measuring the atmosphere where almost no one lives would be more reliable than thermometers on the planet surface where I and most everyone else lives?”

    Surface thermometers are ‘adjusted’ to report whatever the adjuster wants to report. Satellite data is not.

  4. Jeffery says:

    Surface thermometers are ‘adjusted’ to report whatever the adjuster wants to report. Satellite data is (sic) not.

    Both statements are false.

    Will you please explain how satellite data are gathered?

  5. Kevin says:

    Poorly and inaccurately placed ‘sic’. I forgive you though.

    “Will you please explain how satellite data are gathered?”

    Nope. But data ‘is’ gathered. not ‘are’ gathered. It’s a tricky rule in English, upon which you are falling on the wrong side.

    If you didn’t know before this that surface thermometer temps are ‘adjusted’, then you are far out of your league here, Jeffrey.

  6. Jeffery says:

    You are almost right on “data is” and I was clearly wrong for correcting you! My go to grammarian, the scrupulously correct “Grammar Girl”, says:

    As I said, both usages are standard. The count noun datum and its plural data, meaning “a given fact or assumption,” were adopted from Latin into English by the seventeenth century; however, it wasn’t till the late nineteenth century that data took on the modern sense of facts and figures. This shift in meaning also led some to start treating data as a mass noun.

    In my real job we treat data as a “count” noun.

    I didn’t say I didn’t know about data adjustments, so your snarky evasion is surprising. The question was for you to explain how satellite data are not adjusted and hence, superior to surface thermometer data.

    Are YOU aware of the maladjustments in the early UAH satellite as adjusted by Drs. Spencer and Christy, right? If the satellite measurements are direct (they clearly are not) how could the adjustments ever be wrong?? In fact, the only proven significant errors in data adjustment was from in the satellite data of deniers Christy and Spencer! That’s not to say they fudged the data, just that they mistakenly “adjusted” the data, resulting in an underestimation of the atmospheric (not surface) temperature.

    Do you have any evidence to support your accusation that the surface (thermometer) temperature readings are falsified?

    Here’s a simple summary of the RSS process, obviously leaving out many steps:

    Processing Approach

    Calculating TB (Brightness Temperature) from raw radiometer counts is a complex, multi-step process in which a number of effects must be accurately characterized and adjustments made to account for them. These effects include radiometer non-linearity, imperfections in the calibration targets, emission from the primary antenna, and antenna pattern adjustments. RSS TB are consistently calibrated so that the TB measurements for all sensors can be used to construct a multi-decadal time series. A rain-free ocean is used as the absolute calibration reference and our state-of-the-art radiative transfer model (RTM) of the ocean and intervening atmosphere in the absence of rain can predict the top-of-the-atmosphere TB to a high degree of accuracy. A complete description of the calibration of all SSM/I is available. Though the document describes on SSM/I sensors, the approach applies to the other radiometers.

    Several of the steps necessary are summarized in the table below by microwave radiometer and are discussed further below.

    Calibration Steps for Microwave Radiometers

    Geolocation Analysis

    Attitude Adjustment

    Along-scan Correction

    Absolute Calibration

    Hot Load Correction

    Antenna Emissivity

    SSM/I NRL/RSS No Yes APC No 0
    SSMIS RSS No Yes APC Yes 0.5-3.5%
    TMI GSFC Dynamic Yes APC No 3.5%
    WindSat NRL/RSS Fixed Yes APC Yes 0
    AMSRE RSS Fixed Yes APC Yes 0
    AMSR2 RSS No Yes APC Yes 0

    The first step is geolocation. Knowing the exact location of each measurement is required for any subsequent collocations or comparisons performed. We use ascending minus descending values and look at small ocean islands and ensure they do not ‘move’. Geolocation is not always performed by RSS as is shown in the table [ NRL = Naval Research Lab, GSFC = Goddard Space Flight Center]. The correction for geolocation is different from a correction for instrument mounting errors (also called role/pitch/yaw corrections) which must also be addressed.

    The remaining corrections listed in the table are performed by comparing antenna temperatures with those simulated by our radiative transfer model. The Remote Sensing Systems’ atmospheric radiative transfer model (RTM) for the ocean surface and intervening atmosphere has been continually developed and refined for more than 30 years, and is highly accurate in the 1-100 GHz (microwave) spectrum for ocean observations. The ocean surface model components include polarimetric wind speed and direction with dependencies on surface emissivity and scattering. The atmospheric components of our RTM rely on the most recent and relevant measurements of oxygen and vapor.

    Attitude adjustment includes correcting for spacecraft pointing errors. Spacecraft pointing is determined by a number of different methods, the preferred being a star tracker. Another method is horizon balancing sensor. For SSM/I no pointing information was given, so it was assumed to be correct. TMI has a dynamic pointing correction that changes within an orbit because the horizon sensor used prior to the orbit boost is not as accurate as a star tracker. After orbit boost, the horizon sensor was disabled and pointing was determined from two on-board gyroscopes, also not as accurate as a star tracker. AMSR-E had no pointing problems, as the AQUA satellite had a star tracker. The AMSR on ADEOS-II needed a dynamic correction, while WindSat needed a simple fixed correction to the roll/pitch/yaw.

    As the mirror rotates, at the edge of the earth scene view will begin to contain obstructions such as the satellite itself or part of the cold mirror. Additionally, during the scan, the antenna sidelobe pattern may result in contributions from different parts of the spacecraft. Every instrument needs this along-scan correction.

    Next we perform an antenna pattern correction (APC). The APC is determined pre-launch and consists of spill over and cross-polarization values. After launch, the spill over and cross-polarization values are adjusted so that the measured antenna temperatures match the RTM simulated antenna temperatures. This correction is needed for all instruments.

    Only some of the radiometers need hot load thermal gradient corrections. The determination of TB from counts for microwave radiometers is completed using two known temperatures to infer the Earth scene temperature. For each scan, the antenna feedhorns view a mirror that reflects cold space (a known temperature of 2.7 K) and a hot absorber measured by several thermistors. Assuming a linear response, the Earth scene temperatures are then determined by fitting a slope to these two known measurements (hot and cold). This 2-point calibration system continuously compensates for variations in the radiometer gain and noise temperatures. This seemingly simple calibration methodology is fraught with subtle difficulties. The cold mirror is relatively trouble-free as long we note when the moon intrudes on the cold space view and remove moon-affected values. The hot absorber has been more problematic. The thermistors often do not adequately measure thermal gradients across the hot absorber. For example, a hot load correction is required for AMSR-E because of a design flaw in the AMSR-E hot load. The hot load acts as a blackbody emitter and its temperature is measured by precision thermistors. Unfortunately, during the course of an orbit, large thermal gradients develop within the hot load due to solar heating making it difficult to determine the average effective temperature from the thermistor readings. The thermistors themselves measure these gradients and may vary by up to 15 K. Several other radiometers have had similar, but smaller, issues.

    Lastly, the main reflector is assumed to be a perfect reflector with an emissivity of 0.0, but this is not always the case. A bias in the TMI measurements was attributed to the degradation of the primary antenna as atomic oxygen present at TMI’s low altitude (350 km) led to rapid oxidization of the thin, vapor-deposited aluminum coating on the graphite primary antenna. The measured radiation is therefore comprised of the reflected Earth scene and antenna emissions. Emissivity of the antenna was deduced during the calibration procedure to be 3.5%. The antenna emissivity correction utilizes additional information from instrument thermistors to estimate the antenna temperature, thereby reducing the effect of the temporal variance. This emissivity is constant for all the TMI channels. The SSMIS instruments also has an emissive antenna where the emissivity appears to increase as a function of frequency, changing from 0.5 to 3.5 %.

    A first grader can be taught to read a thermometer, a technology that is many centuries old.

    That charlatan windbag, Load Munchkin of Bitchly (according to denier commenter, j), risibly stated that the satellites use very sophisticated platinum resistance thermometers! I don’t think you know much about the topic and are just repeating a denier myth – that temperature data showing warming is fudged.

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