Archive for the #agw Category

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario/’s forced signal, but is likely inconsistent with the steepest emission scenario/’s forced signal.

Source: Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise : Scientific Reports : Nature Publishing Group

I suppose it was in the early 90s that I first noticed predictions of global warming and the associated dire warnings of calamities to come. Some of these emanated from the Met Office and so I knew should be treated with a pinch of salt but other sources included NASA, which I then personally still very much respected; despite the space shuttle evidently being the wrong concept poorly executed, their basic scientific expertise seemed unquestionable. In general I was looking forward to the warmer climate predicted for the UK, and assumed that the overall effects for the globe wouldn’t necessarily all be bad.

Source: My personal path to Catastrophic AGW skepticism | Watts Up With That?

Source: The skillful predictions of climate science | The IPCC Report

Lack of warming since 1998 and growing discrepancies with climate model projections

Evidence of decreased climate sensitivity to increases in CO2Evidence that sea level rise in 1920-1950 is of the same magnitude as in 1993-2012

Increasing Antarctic sea ice extent

Low confidence in attributing extreme weather events to anthropogenic global warming

Source: IPCC AR5 weakens the case for AGW | Climate Etc.

Dana Nuccitelli: Global warming since 1990 has fallen within the range of IPCC climate model projections

Source: IPCC model global warming projections have done much better than you think | Dana Nuccitelli | Environment | The Guardian

We analyse global temperature and sea-level data for the past few decades and compare them to projections published in the third and fourth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). The results show that global temperature continues to increase in good agreement with the best estimates of the IPCC, especially if we account for the effects of short-term variability due to the El Niño/Southern Oscillation, volcanic activity and solar variability. The rate of sea-level rise of the past few decades, on the other hand, is greater than projected by the IPCC models. This suggests that IPCC sea-level projections for the future may also be biased low.

Source: Comparing climate projections to observations up to 2011 – IOPscience

IPCC Has Accurately Projected Global Surface WarmingAs Figure 2 shows, the unadjusted data (pink) have tended to fall towards the lower end of IPCC projections in recent years, primarily due to the preponderance of La Niña events and an extended solar cycle minimum, which have short-term cooling influences on global surface temperatures.  However, when these influences are filtered out (red), the observed temperatures fall very close to the central climate model projections, which RFC12 notes are based on greenhouse gas emissions scenarios that accurately reflect the observed CO2 changes over that timeframe.In short, the global climate models used in the IPCC reports have been very good at predicting the underlying human-caused global surface warming trend, beneath the short-term noise which will average out to zero over time.  This suggests that IPCC projections of future global warming, which are based on various possible human greenhouse gas emissions scenarios, are reliable.

Source: Rahmstorf et al. Validate IPCC Temperature Projections, Find Sea Level Rise Underestimated

Climate change and temperature trends and public policy and science evidence

Source: What Evidence Would Persuade You That Man-Made Climate Change Is Real? –

The Limits of Consensus

| June 27th, 2015

The science of subjectivity

Source: The Limits of Consensus

The first installment of the fifth Intergovernmental Panel on Climate Change report was published on Friday, Sept. 27, with more sections to be rolled out over the next year. The IPCC’s broad conclusions have been remarkably consistent since the first report was published in 1990, although details have evolved.

Source: A Beginner’s Guide to the IPCC Climate Change Reports

Source: Koutsoyiannis: Publications in scientific journals – ITIA

Geographically distributed predictions of future climate, obtained through climate models, are widely used in hydrology and many other disciplines, typically without assessing their reliability. Here we compare the output of various models to temperature and precipitation observations from eight stations with long (over 100 years) records from around the globe. The results show that models perform poorly, even at a climatic (30-year) scale. Thus local model projections cannot be credible, whereas a common a

Source: On the credibility of climate predictions – ITIA

IPCC TAR  #agw

| June 27th, 2015

In sum, a strategy must recognize what is possible. In climate research and modelling, we should recognize that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible. The most we can expect to achieve is the prediction of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions. This reduces climate change to the discernment of significant differences in the statistics of such ensembles. The generation of such model ensembles will require the dedication of greatly increased computer resources and the application of new methods of model diagnosis. Addressing adequately the statistical nature of climate is computationally intensive, but such statistical information is essential.

Just because climate science involves physics doesn’t mean its conclusions are as certain as gravity, Jamie Whyte writes in The Wall Street Journal.

Source: Jamie Whyte: Science Says So, Suckers! – WSJ

June 24, 2015 at 02:12PM via CoDoubt