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Wednesday, 4 September 2013

New paper appears to corroborate Spencer & Braswell's paper on misdiagnosis of climate feedbacks

Posted on 09:10 by Unknown
A paper published today in Theoretical and Applied Climatology appears to corroborate Spencer & Braswell's 2011 paper concluding that "atmospheric feedback diagnosis of the climate system remains an unsolved problem, due primarily to the inability to distinguish between radiative forcing and radiative feedback in satellite radiative budget observations." 



The new paper also finds a problem of misdiagnosis of climate feedbacks due to "noise" from natural variation, stating, "we see that the [natural] non-feedback variation plays the most significant role in distorting the curve in the lagged correlation graph, thus obscuring the exact value of climate feedback" and "The estimated noise levels in both CERES (>13 %) and climate models (11–28 %) are found to be far above the critical level (~5 %) that begins to misrepresent climate feedback." Spencer & Braswell had suggested that the misdiagnosis of climate feedback meant that the "missing heat" at the heart of global warming theory had instead been lost to space:




Climate models get energy balance wrong, make too hot forecasts of global warming 


HUNTSVILLE, Ala. (July 26, 2011) — Data from NASA’s Terra satellite shows that when the climate warms, Earth’s atmosphere is apparently more efficient at releasing energy to space than models used to forecast climate change have been programmed to “believe.” 


The result is climate forecasts that are warming substantially faster than the atmosphere, says Dr. Roy Spencer, a principal research scientist in the Earth System Science Center at The University of Alabama in Huntsville. 


The previously unexplained differences between model-based forecasts of rapid global warming and meteorological data showing a slower rate of warming have been the source of often contentious debate and controversy for more than two decades. 


In research published this week in the journal “Remote Sensing” http://www.mdpi.com/2072-4292/3/8/1603/pdf, Spencer and UA Huntsville’s Dr. Danny Braswell compared what a half dozen climate models say the atmosphere should do to satellite data showing what the atmosphere actually did during the 18 months before and after warming events between 2000 and 2011. 


“The satellite observations suggest there is much more energy lost to space during and after warming than the climate models show,” Spencer said. “There is a huge discrepancy between the data and the forecasts that is especially big over the oceans.” 


Not only does the atmosphere release more energy than previously thought, it starts releasing it earlier in a warming cycle. The models forecast that the climate should continue to absorb solar energy until a warming event peaks. Instead, the satellite data shows the climate system starting to shed energy more than three months before the typical warming event reaches its peak. 


“At the peak, satellites show energy being lost while climate models show energy still being gained,” Spencer said. 


This is the first time scientists have looked at radiative balances during the months before and after these transient temperature peaks. 


Applied to long-term climate change, the research might indicate that the climate is less sensitive to warming due to increased carbon dioxide concentrations in the atmosphere than climate modelers have theorized. A major underpinning of global warming theory is that the slight warming caused by enhanced greenhouse gases should change cloud cover in ways that cause additional warming, which would be a positive feedback cycle. 


Instead, the natural ebb and flow of clouds, solar radiation, heat rising from the oceans and a myriad of other factors added to the different time lags in which they impact the atmosphere might make it impossible to isolate or accurately identify which piece of Earth’s changing climate is feedback from manmade greenhouse gases. 


“There are simply too many variables to reliably gauge the right number for that,” Spencer said. “The main finding from this research is that there is no solution to the problem of measuring atmospheric feedback, due mostly to our inability to distinguish between radiative forcing and radiative feedback in our observations.”

Paper published today:







Theoretical and Applied Climatology

September 2013


Influence of non-feedback variations of radiation on the determination of climate feedback




  • Yong-Sang Choi, 

  • Heeje Cho, 

  • Chang-Hoi Ho, 

  • Richard S. Lindzen, 

  • Seon Ki Park, 

  • Xing Yu









Recent studies have estimated the magnitude of climate feedback based on the correlation between time variations in outgoing radiation flux and sea surface temperature (SST). This study investigates the influence of the natural non-feedback variation (noise) of the flux occurring independently of SST on the determination of climate feedback. The observed global monthly radiation flux is used from the Clouds and the Earth's Radiant Energy System (CERES) for the period 2000–2008. In the observations, the time lag correlation of radiation and SST shows a distorted curve with low statistical significance for shortwave radiation while a significant maximum at zero lag for longwave radiation over the tropics. This observational feature is explained by simulations with an idealized energy balance model where we see that the [natural] non-feedback variation plays the most significant role in distorting the curve in the lagged correlation graph, thus obscuring the exact value of climate feedback. We also demonstrate that the climate feedback from the tropical longwave radiation in the CERES data is not significantly affected by the noise. We further estimate the standard deviation of radiative forcings (mainly from the noise) relative to that of the non-radiative forcings, i.e., the noise level from the observations and atmosphere–ocean coupled climate model simulations in the framework of the simple model. The estimated noise levels in both CERES (>13 %) and climate models (11–28 %) are found to be far above the critical level (~5 %) that begins to misrepresent climate feedback.


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