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| Content Provider | Springer Nature Link |
|---|---|
| Author | Richardson, Mark Hausfather, Zeke Nuccitelli, Dana A. Rice, Ken Abraham, John P. |
| Copyright Year | 2015 |
| Abstract | Monckton of Brenchley et al. (Sci Bull 60:122–135, 2015) (hereafter called M15) use a simple energy balance model to estimate climate response. They select parameters for this model based on semantic arguments, leading to different results from those obtained in physics-based studies. M15 did not validate their model against observations, but instead created synthetic test data based on subjective assumptions. We show that M15 systematically underestimate warming: since 1990, most years were warmer than their modelled upper limit. During 2000–2010, RMS error and bias are approximately 150 % and 350 % larger than for the CMIP5 median, using either the Berkeley Earth or Cowtan and Way surface temperature data. We show that this poor performance can be explained by a logical flaw in the parameter selection and that selected parameters contradict observational estimates. M15 also conclude that climate has a near-instantaneous response to forcing, implying no net energy imbalance for the Earth. This contributes to their low estimates of future warming and is falsified by Argo float measurements that show continued ocean heating and therefore a sustained energy imbalance. M15’s estimates of climate response and future global warming are not consistent with measurements and so cannot be considered credible. |
| Starting Page | 1370 |
| Ending Page | 1377 |
| Page Count | 8 |
| File Format | |
| ISSN | 20959273 |
| Journal | Chinese Science Bulletin |
| Volume Number | 60 |
| Issue Number | 15 |
| e-ISSN | 20959281 |
| Language | English |
| Publisher | Science China Press |
| Publisher Date | 2015-05-31 |
| Publisher Place | Beijing |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Climate sensitivity Global warming Climate change Climate model Climate feedback Science Life Sciences Physics Chemistry/Food Science Earth Sciences Engineering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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