2016 Scientific Consensus: Climate Models Aren’t Working
By Kenneth Richard
In a 2015 editorial on the dire consequences of human-caused climate change, Marcia McNutt, editor of the journal Science, stated with conviction that “the time for debate has ended.” It’s the “action” of reducing our CO2 emissions that is now “urgently needed” instead of debating what apparently is “settled” science. She even laced her opined declaration that the scientific debate is now over with some religious imagery, seemingly characterizing the “treacherous offenders” who remain skeptical or unconcerned about climate change as “sinners” deserving the hottest, innermost sections of Hell.
The time for debate has ended. Action is urgently needed. … In Dante’s Inferno, he describes the nine circles of Hell, each dedicated to different sorts of sinners, with the outermost being occupied by those who didn’t know any better, and the innermost reserved for the most treacherous offenders. I wonder where in the nine circles Dante would place all of us who are borrowing against this Earth in the name of economic growth, accumulating an environmental debt by burning fossil fuels, the consequences of which will be left for our children and grandchildren to bear? Let’s act now, to save the next generations from the consequences of the beyond-two-degree inferno.”
Apparently McNutt’s activist admonitions haven’t convinced scientists publishing papers in other journals that scientific debate about climate change is over.
The year isn’t even half over yet, and already there have been over 20 peer-reviewed papers published that confirm that the climate models relied upon by those advocating that the debate is over (a) do not match observations, (b) leave out important factors affecting climate, (c) don’t have predictive skill, (d) failed to simulate the warming “pause” or “hiatus” of the 21st century, (e) have large uncertainties and biases that impinge on their reliability, and/or (f) are based on assumptions that have been found to be wrong.
Here are some quick-hit examples of statements undermining the validity of climate models found in recently published papers:
- “[C]onstraints are needed to guide model development and reduce uncertainty in estimates of the radiative forcing. Unfortunately, the preindustrial observations needed to constrain the sensitivities are not available.”
- “[C]limate model runs … indicate no skill at replicating long-term temperature and precipitation changes.”
- “This finding suggests that much work remains before we can model hydroclimate variability accurately.”
- “The idea that the young Earth had a thicker atmosphere turns out to be wrong. … The results … reverse the commonly accepted idea that the early Earth had a thicker atmosphere to compensate for weaker sunlight.”
- “There is this mismatch between what the climate models are producing and what the observations are showing … the rate of warming slowed down at a time when greenhouse-gas emissions were rising dramatically.”
- “Climate models, however, have large uncertainties in representing dehydration and cloud processes in the TTL [tropical tropopause layer], and thus their feedback with surface climate, prohibiting an accurate projection of future global and regional climate changes”
- “They found that the wave-like movements of the mantle are occurring at a rate that is an order of magnitude faster than had been previously predicted.”
Perhaps the scientists who have the audacity to report on the considerable uncertainty and unreliability inherent in climate models — or the wrongness of their previously-held assumptions about the Earth-Atmosphere system — can be excused for their lack of understanding of “settled science.” After all, as Marcia McNutt declares, the debate is over; the climate models tell us so; it’s now time to act.
Fortunately, those scientists who “don’t know any better” about the debate being over may be able to escape to the outermost corridors of Hell rather than the innermost ones — where apparently it’s much, much hotter. That’s apparently where we can find those who don’t yet agree that the debate is over, and that activism is now science.
Obviously, there are valid and very substantial reasons why many are skeptical.
21 Papers From 2016
Below are 21 papers published so far in 2016 (through mid-June) that do not support the contention that climate modeling is “settled science,” or that the scientific debate is now over.
Three time series of average summer daily maximum temperature (TMax JJA) are developed for three interior regions of Alabama (AL) from stations with varying periods-of-record and unknown inhomogeneities. The time frame is 1883-2014. … Varying the parameters of the construction methodology creates 333 time series with a central trend-value based on the largest group of stations of -0.07 °C decade-1 with a best-guess estimate of measurement uncertainty being -0.12 to -0.02 °C decade-1. This best-guess result is insignificantly different (0.01 C decade-1) from a similar regional calculation using NOAA nClimDiv data beginning in 1895. … Finally, 77 CMIP-5 climate model runs are examined for Alabama and indicate no skill at replicating long-term temperature and precipitation changes since 1895.”
It has been claimed that the early-2000s global warming slowdown or hiatus, characterized by a reduced rate of global surface warming, has been overstated, lacks sound scientific basis, or is unsupported by observations. The evidence presented here contradicts these claims.”
There is this mismatch between what the climate models are producing and what the observations are showing,” says lead author John Fyfe, a climate modeller at the Canadian Centre for Climate Modelling and Analysis in Victoria, British Columbia. “We can’t ignore it.” … Susan Solomon, a climatologist at the Massachusetts Institute of Technology in Cambridge, says that Fyfe’s framework helps to put twenty-first-century trends into perspective, and clearly indicates that the rate of warming slowed down at a time when greenhouse-gas emissions were rising dramatically.“
The authors demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model’s convection parameterization, processes that are only crudely accounted for in GCMs. In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere–land model by increasing sea surface temperatures uniformly and examining the response in the top-of-atmosphere energy balance. The effect can be quantified through a bulk convective detrainment efficiency, which measures the ability of cumulus convection to generate condensate per unit precipitation. The model differences, dominated by shortwave feedbacks, come from broad regimes ranging from large-scale ascent to subsidence regions. Given current uncertainties in representing convective precipitation microphysics and the current inability to find a clear observational constraint that favors one version of the authors’ model over the others, the implications of this ability to engineer climate sensitivity need to be considered when estimating the uncertainty in climate projections.”
We find a larger percentage of land area with relatively wetter conditions in the ninth to eleventh and the twentieth centuries, whereas drier conditions are more widespread between the twelfth and nineteenth centuries. Our reconstruction reveals that prominent seesaw patterns of alternating moisture regimes observed in instrumental data across the Mediterranean, western USA, and China have operated consistently over the past twelve centuries. …. [T]he intensification of the twentieth-century-mean hydroclimate anomalies in the simulations, as compared to previous centuries, is not supported by our new multi-proxy reconstruction. This finding suggests that much work remains before we can model hydroclimate variability accurately, and highlights the importance of using palaeoclimate data to place recent and predicted hydroclimate changes in a millennium-long context.”
According to a new study, the Northern Hemisphere has experienced considerably larger variations in precipitation during the past twelve centuries than in the twentieth century. Researchers from Sweden, Germany, and Switzerland have found that climate models overestimated the increase in wet and dry extremes as temperatures increased during the twentieth century.”
A large number of processes are involved in the chain from emissions of aerosol precursor gases and primary particles to impacts on cloud radiative forcing. … However, we are most interested in the radiative forcing since the preindustrial era. Because few relevant measurements are available from that era, relationships from recent variability have been assumed to be applicable to the preindustrial to present-day change. …
Given the diversity of the relationships, constraints are needed to guide model development and reduce uncertainty in estimates of the radiative forcing. Unfortunately, the preindustrial observations needed to constrain the sensitivities are not available. … One method would be to use recent trends in regions where emissions have changed substantially during the period when reliable measurements are available. For example, Cherian et al. used measurements of trends in the downward solar radiance at European sites from the period 1990–2005, when SO2 emissions declined threefold, to constrain global estimates of aerosol radiative forcing since the preindustrial era. Although such an analysis is highly informative, it does not provide guidance on removing biases in models that overestimate or underestimate the downward solar trend over Europe, which could be due to errors in any of the factors that produce the cloud radiative forcing change or the clear-sky change, as well as natural variability in cloud cover. Removing those biases is necessary if climate models are to be used for simulations of future climate change. Additional data characterizing each of the factors and components are needed. Some of the necessary data (L, re, aerosol optical depth) are available from 1990, but reliable estimates of Nd, τ, and R are not available for years before 2001, when the Earth Observing System satellite constellation was launched.”
The low agreement between models in simulating the impacts of solar variations on SAT in several regions suggests the different dynamical responses in these models, possibly associated with inaccurate parameterization of the processes related to solar forcing. Our analysis suggests that internal climate variability played a more significant role than external forcings in short-term SAT variability in the regions of the North Atlantic, the North Pacific, the Arctic, the Antarctic Peninsula, and its surrounding oceans. The possibility of long-term impacts of external forcings on SAT and the uncertainties that might be contained due to effects of internal climate modes other than El Niño–Southern Oscillation underscore the necessity for a more detailed understanding of the dynamical response of SAT to external forcings.”
The ocean has absorbed 41 per cent of all anthropogenic carbon emitted as a result of fossil fuel burning and cement manufacture. The magnitude and the large-scale distribution of the ocean carbon sink is well quantified for recent decades. In contrast, temporal changes in the oceanic carbon sink remain poorly understood. It has proved difficult to distinguish between air-to-sea carbon flux trends that are due to anthropogenic climate change and those due to internal climate variability. Here we use a modelling approach that allows for this separation, revealing how the ocean carbon sink may be expected to change throughout this century in different oceanic regions. Our findings suggest that, owing to large internal climate variability, it is unlikely that changes in the rate of anthropogenic carbon uptake can be directly observed in most oceanic regions at present, but that this may become possible between 2020 and 2050 in some regions.”
Irreducible uncertainty in near-term climate projections
Abstract: These results suggest that climate projections need to be performed with many more ensemble members than at present, using a range of ocean initial conditions, if the uncertainty in near-term regional climate is to be adequately quantified.
Summary and Discussion: The presence of initial condition uncertainty and non-linearity produces significant irreducible uncertainty in future regional climate changes. For trends of 20 years, the climate change signal rarely emerges from the noise of internal variability in FAMOUS. Uncertainty in future trends of temperature and precipitation reduce for longer trends as the initial condition uncertainty saturates.”
Our power spectral analysis reveals significant discrepancies between observed and predicted dynamic topography.”
Map of flow within the Earth’s mantle finds the surface moving up and down ‘like a yo-yo’
Researchers have compiled the first global set of observations of the movement of the Earth’s mantle, the 3000-kilometre-thick layer of hot silicate rocks between the crust and the core, and have found that it looks very different to predictions made by geologists over the past 30 years. … They found that the wave-like movements of the mantle are occurring at a rate that is an order of magnitude faster than had been previously predicted. The results, reported in the journal Nature Geoscience, have ramifications across many disciplines including the study of ocean circulation and past climate change.”
10. Som et al., 2016
Our data indicate a surprisingly low surface atmospheric pressure of Patm = 0.23 ± 0.23 (2σ) bar, and combined with previous studies suggests ~0.5 bar as an upper limit to late Archaean Patm. The result implies that the thin atmosphere was rich in auxiliary greenhouse gases and that Patm [surface atmospheric pressure] fluctuated over geologic time to a previously unrecognized extent.”
Early Earth’s air weighed less than half of today’s atmosphere
The idea that the young Earth had a thicker atmosphere turns out to be wrong. New research from the University of Washington uses bubbles trapped in 2.7 billion-year-old rocks to show that air at that time exerted at most half the pressure of today’s atmosphere. The results, published online May 9 in Nature Geoscience, reverse the commonly accepted idea that the early Earth had a thicker atmosphere to compensate for weaker sunlight. The finding also has implications for which gases were in that atmosphere, and how biology and climate worked on the early planet. […]
For the longest time, people have been thinking the atmospheric pressure might have been higher back then, because the sun was fainter,” said lead author Sanjoy Som, who did the work as part of his UW doctorate in Earth and space sciences. “Our result is the opposite of what we were expecting. […]
“We’re still coming to grips with the magnitude of this,” Buick said. “It’s going to take us a while to digest all the possible consequences.” Other geological evidence clearly shows liquid water on Earth at that time, so the early atmosphere must have contained more heat-trapping greenhouse gases, like methane and carbon dioxide, and less nitrogen.”
Palaeoclimate assessment has demonstrated that changes in large-scale features of climate that are governed by the energy and water balance show consistent responses to changes in forcing in different climate states, and these consistent responses are reproduced by climate models. However, state-of-the-art models are still largely unable to reproduce observed changes in climate at a regional scale reliably. While palaeoclimate analyses of state-of-the-art climate models suggest an urgent need for model improvement, much work is also needed on extending and improving palaeoclimate reconstructions and quantifying and reducing both numerical and interpretative uncertainties.”
Comparisons of the observed global-scale cooling following recent volcanic eruptions to that simulated by climate models from the Coupled Model Intercomparison Project 5 (CMIP5) indicate that the models overestimate the magnitude of the global temperature response to volcanic eruptions. Here we show that this overestimation can be explained as a sampling issue, arising because all large eruptions since 1951 coincided with El Niño events, which cause global-scale warming that partially counteracts the volcanically induced cooling. By subsampling the CMIP5 models according to the observed El Niño–Southern Oscillation (ENSO) phase during each eruption, we find that the simulated global temperature response to volcanic forcing is consistent with observations. Volcanic eruptions pose a particular challenge for the detection and attribution methodology, as their surface impacts are short-lived and hence can be confounded by ENSO. Our results imply that detection and attribution studies must carefully consider sampling biases due to internal climate variability.”
Introduction: Estimates of the relative contributions by anthropogenic and natural forcings inform our attempts to constrain transient and equilibrium climate sensitivity [Collins et al., 2013]. Yet such attempts are inherently complicated by the fact that we observe only one of many possible climate trajectories. With internal variability contributing significantly to decadal-scale trends in certain quantities and regions, robust attribution of climate change can become challenging and sensitive to the particular realization of variability sampled in the observational record [Deser et al., 2012a].”
Temperatures in Asia, and globally, are very likely to increase with greenhouse gas emissions, but future projections of rainfall are far more uncertain. Here we investigate the linkage between temperature and precipitation in Asia on interannual to multicentennial timescales using instrumental data, late Holocene paleoclimate proxy data and climate model simulations. We find that in the instrumental and proxy data, the relationship between temperature and precipitation is timescale-dependent. While on annual to decadal timescales, negative correlations dominate and thus cool summers tend to be rainy summers, on longer timescales precipitation and temperature are positively correlated; cool centuries tend to be dryer centuries in monsoonal Asia. In contrast, the analyzed CMIP5/PMIP3 climate model simulations show a negative correlation between precipitation and temperature on all timescales. Although many uncertainties exist in the interpretation of the proxy data, there is consistency between them and the instrumental evidence. This, and the persistence of the result across independent proxy datasets, suggests that the climate model simulations might be considerably biased, overestimating the short-term negative associations between regional rainfall and temperature and lacking long-term positive relationships between them.”
14. Hand, 2016
Models suggest that climate change should weaken the AMOC as warmer Arctic temperatures, combined with buoyant freshwater from Greenland’s melting ice cap, impede the formation of deep currents. But so far, limited ocean measurements show the AMOC to be far more capricious than the models have been able to capture.”
An accurate assessment of the role of solar variability is a key step towards a proper quantification of natural and anthropogenic climate change. To this end, climate models have been extensively used to quantify the solar contribution to climate variability. However, owing to its large computational cost, the bulk of modeling studies to date have been performed without interactive stratospheric photochemistry: the impact of this simplification on the modeled climate system response to solar forcing remains largely unknown. Here we quantify this impact, by comparing the response of two model configurations, with and without interactive ozone chemistry. Using long integrations, we first obtain robust surface temperature and precipitation responses to an idealized irradiance increase. Then, we show that the inclusion of interactive stratospheric chemistry significantly reduces the surface warming (by about one third) and the accompanying precipitation response. This behavior is linked to photochemically-induced stratospheric ozone changes, and their modulation of the surface solar radiation. Our results suggest that neglecting stratospheric photochemistry leads to a sizable overestimate of the surface response to changes in solar irradiance. This has implications for simulations of the climate in the Last Millennium and geoengineering applications employing irradiance changes larger than those observed over the 11-year sunspot cycle, where models often use simplified treatments of stratospheric ozone that are inconsistent with the imposed solar forcing.”
16. Stier, 2016
Aerosol–cloud interactions are considered a key uncertainty in our understanding of climate change (Boucher et al., 2013). Knowledge of the global abundance of cloud condensation nuclei (CCN) is fundamental to determine the strength of the anthropogenic climate perturbation. Direct measurements are limited and sample only a very small fraction of the globe so that remote sensing from satellites and ground-based instruments is widely used as a proxy for cloud condensation nuclei (Nakajima et al., 2001; Andreae, 2009; Clarke and Kapustin, 2010; Boucher et al., 2013). However, the underlying assumptions cannot be robustly tested with the small number of measurements available so that no reliable global estimate of cloud condensation nuclei exists. This study overcomes this limitation using a self-consistent global model (ECHAM-HAM) of aerosol radiative properties and cloud condensation nuclei. An analysis of the correlation of simulated aerosol radiative properties and cloud condensation nuclei reveals that common assumptions about their relationships are violated for a significant fraction of the globe: 71 % of the area of the globe shows correlation coefficients between CCN0.2 % at cloud base and aerosol optical depth (AOD) below 0.5, i.e. AOD variability explains only 25 % of the CCN variance. This has significant implications for satellite based studies of aerosol–cloud interactions. The findings also suggest that vertically resolved remote-sensing techniques, such as satellite-based high spectral resolution lidars, have a large potential for global monitoring of cloud condensation nuclei.”
The early twentieth century Arctic warming (ETCAW) between 1920 and 1940 is an exceptional feature of climate variability in the last century. Its warming rate was only recently matched by recent warming in the region. Unlike recent warming largely attributable to anthropogenic radiative forcing, atmospheric warming during the ETCAW was strongest in the mid-troposphere and is believed to be triggered by an exceptional case of natural climate variability. Nevertheless, ultimate mechanisms and causes for the ETCAW are still under discussion. Here we use state of the art multi-member global circulation models, reanalysis and reconstruction datasets to investigate the internal atmospheric dynamics of the ETCAW. We investigate the role of boreal winter mid-tropospheric heat transport and circulation in providing the energy for the large scale warming. Analyzing sensible heat flux components and regional differences, climate models are not able to reproduce the heat flux evolution found in reanalysis and reconstruction datasets. These datasets show an increase of stationary eddy heat flux and a decrease of transient eddy heat flux during the ETCAW. Moreover, tropospheric circulation analysis reveals the important role of both the Atlantic and the Pacific sectors in the convergence of southerly air masses into the Arctic during the warming event. Subsequently, it is suggested that the internal dynamics of the atmosphere played a major role in the formation in the ETCAW.”
18. Kim et al., 2016
Cirrus clouds in the tropical tropopause layer (TTL) and water vapor transported into the stratosphere have significant impacts on the global radiation budget and circulation patterns. Climate models, however, have large uncertainties in representing dehydration and cloud processes in the TTL, and thus their feedback with surface climate, prohibiting an accurate projection of future global and regional climate changes. Here, we use unprecedented airborne measurements over the Pacific to reveal atmospheric waves as a strong modulator of ice clouds in the TTL. Wave-induced cold and/or cooling conditions are shown to exert a nearly ubiquitous influence on cirrus cloud occurrence at altitudes of 14-18 km, except when air was very recently influenced by convective hydration. We further observe that various vertical scales of cloud layers are associated with various vertical scales of waves, suggesting the importance of representing TTL waves in models.”
[T]here are still large [uncertainties] in current observational and meteorological reanalysis datasets, so accurate quantification of the influence of solar flux variability on the climate system remains an open scientific question.”
20. Sterl, 2016
The large heat capacity of the ocean as compared to the atmosphere provides a memory in the climate system that might have the potential for skilful climate predictions a few years ahead. However, experiments so far have only found limited predictability after accounting for the deterministic forcing signal provided by increased greenhouse gas concentrations. One of the problems is the drift that occurs when the model moves away from the initial conditions towards its own climate. This drift is often larger than the decadal signal to be predicted. In this paper we describe the drift occurring in the North Atlantic Ocean in the EC-Earth climate model and relate it to the lack of decadal predictability in that region. While this drift may be resolution dependent and disappear in higher resolution models, we identify a second reason for the low predictability. A subsurface heat content anomaly can only influence de atmosphere if (deep) convection couples it to the surface, but the occurrence of deep convection events is random and probably mainly determined by unpredictable atmospheric noise.“
The ocean dominates the planetary heat budget and takes thousands of years to equilibrate to perturbed surface conditions, yet those long time scales are poorly understood. Here we analyze the ocean response over a range of forcing levels and time scales in a climate model of intermediate complexity and in the CMIP5 model suite. We show that on century to millennia time scales the response time scales, regions of anomalous ocean heat storage, and global thermal expansion depend non-linearly on the forcing level and surface warming. As a consequence, it is problematic to deduce long term from short term heat uptake or scale the heat uptake patterns between scenarios. These results also question simple methods to estimate long term sea level rise from surface temperatures, and the use of deep sea proxies to represent surface temperature changes in past climate.”