It was warmer during the Holocene Climatic Optimum than it is today — without any human influence.

the cause is understood (orbital forcing), just as today’s cause is understood (CO2 emissions), and these causes are very different.

One hundred and some years of global surface temperatures is not long enough to draw any conclusions from or worry about anyway.

The reliable instrumental record only goes back 150 years. It is possible to make reconstructions of temperature much further back. These include things like tree rings, ocean sediment, coral growth, layers in stalagmites, and others. The reconstructions available are all slightly different and provide sometimes more and sometimes less global versus regional coverage over the last one or two thousand years. We can reasonably conclude that it is warmer now than any time in at least the last 500 years.

Despite what the computer models tell us, there is actually no evidence of significant global warming.

Global warming is not only an output of computer models. It is based on observations of many global indicators. By far the most straightforward evidence is the actual surface temperature record. While there are places that have records going back several centuries, major global temperature analyses can only go back around 150 years due to their requirements for both quantity and distribution of temperature recording stations.

So 2018 was a record year. Records are set all the time. One really warm year is not global warming.

This is actually not an unreasonable point — single years taken by themselves can not establish or refute a trend. A specific year being the hottest globally averaged temperature on record is not convincing.

You can check: The ten-year mean global temperature in 1900 was about 1 degrees Celsius lower than the ten-year mean in 2015.

Every year since 1992 has been warmer than 1992, the ten hottest years on record occurred in the last 15 years, every year since 1976 has been warmer than 1976, the 20 hottest years on record occurred in the last 25

Climate models are based on parameterizations. How do you know that they are valid for climate change scenarios?

Can we trust proxy records as they tell us only indirect evidences?

Resolution of climate models is not enough to make any reliable projection of local climate change!

Pros and cons of anthropogenic global warming, as well as other opinions are suppressed by scientists in order to get more money for their research

What we do in Germany and Europe is irrelevant. Look how many people live in China and India.

Before we shall make any political action, we need better science. Feedbacks with the ocean, land surface are not well understood.

Any climate prediction is useless. The weather forcast is already a problem for the next days!

During the Cenozoic we had already warmer climate than today. What is the problem?

Adaptation to climate change would be much cheaper than a complete change of our global energy cycle.

In contrast, most cultures in the past had a positive development for warmer than for colder climates.

We still have time and can trust in the innovative ideas of scientists.

Without CO2 the climate would be too cold, CO2 helps us to live on the Earth.

Climate scientists are not reliable. They are traveling a lot and emitting CO2. If they would trust in their own predictions, they would not buy houses in Northern Germany for instance.

Some arguments

In the 1980s, scientists warn the world of climate change’s threat. Over more than 30 years since, as scientific consensus grew, the research community butted heads with deniers, as companies and industries poured money into denial and disinformation campaigns.

Yet there are still plenty who deny climate change exists, suggesting that snow proves the planet’s not getting warmer, or that climate change is nothing new, so we’ll adapt as we always have. Others claim that volcanoes, or the sun, or heat coming from below the earth’s surface - anything but humans - is responsible.

Exxon’s public position was marked by continued refusal to acknowledge the dangers of climate change, and its continued financial support for climate denial. Over the years, Exxon spent more than $30m on thinktanks and researchers that promoted climate denial. Exxon said that it now acknowledges the risk of climate change and does not fund climate change denial groups. Some climate campaigners have likened the industry to the conduct of the tobacco industry which for decades resisted the evidence that smoking causes cancer.


"There is a lot of psychology involved in this, whether people accept things or not … We’ve been attacked by so-called sceptics about things, who just clearly don’t want to believe, and don’t want to understand the science, who can’t do the maths but aren’t prepared to accept anything we tell them," he says.


No one in the climate science community is debating whether or not changes in atmospheric CO2 concentrations alter the greenhouse effect


Climate is complicated and there are lots of competing theories and unsolved mysteries. Until this is all worked out, one can’t claim there is consensus on global warming theory. Until there is, we should not take any action.

The Earth’s climate is characterized by many modes of variability, in the atmosphere, ocean, cryosphere and biosphere. The generation of low-frequency variability is crucial to allow a separation of anthropogenic signals from natural variability, thereby increasing the ability to recognize and improve attribute anthropogenic climate change. We first consider the response of the system to regular multi-millennia orbital forcing, and then go to shorter time scales down to daily weather events. Using an Earth System model, we evaluate how the climate system reacts to local insolation forcing under interglacial background conditions, but variable orbital forcing. Our model results show a pronounced polar amplification of the orbital forcing. In the frequency domain, temperature and precipitation variability at mid-latitudes are dominated by precession, high latitudes by obliquity. The precessional response is related to nonlinearities and/or seasonal biases in the climate system.

On millennial timescales, decaying Northern Hemisphere ice sheets during the last deglaciation affects the high latitude hydrological balance in the North Atlantic and therefore the ocean circulation after the Last Glacial Maximum. Global sea level reconstructions indicate marked abrupt changes within several hundred years, raising the sea level during the Boelling warm interval. Another clue for millennial climate variability comes from the spatio-temporal structure and their representation in models. Using a multi-scale climate model with high resolution near the coast, we investigate the response of the ocean circulation to deglacial freshwater discharges. In our experiments, we find a strong sensitivity of the ocean circulation depending where the deglacial meltwater is injected.
Meltwater injections via the Missisippi and near Labrador hardly affect the AMOC. The reduced sensitivity of the overturning circulation against freshwater perturbations following the Mississippi route provides a consistent representation of the deglacial climate evolution.
A subpolar North Atlantic Ocean freshening, mimicking a transport of water by icebergs, yields a quasi-shutdown. For Heinrich events, the freshwater is therefore more effective.

DO-like variability is seen in a handful of model simulations, including even some pre-industrial simulations. As a mechanism, the subsurface is warmed by the downward mixing of the warmer overlying water during an AMOC weak state, until the surface became more dense than at mid-depth and deep ventilation is initiated. In further model developments, the large oscillations in the Labrador Sea mixing were reduced. However, it might be that the centennial-to-millennial oscillations are required to explain climate variability as expressed e.g. by the Little Ice age and the Mideval Warm Event during the last 1000 years. Recent model development is mainly done with a particular focus on the present and future climate. It could be that a de-tuning of the models is necessary in order to exhibit irregular oscillations on centennial-to-millennial time-scales. Although a systematical analysis of the mechanisms leading to centennial-to-millennial variability remains open, numerical experiments suggest that at least in the Labrador Sea and other sensitive areas the high resolution can play an important role in realistically simulating the variability in the mixed layer depth affecting AMOC.

One can question regularities found in DO-events occurrence and statistically analysed the distribution of inter-event waiting times. To estimate the statistical significance of detected event patterns, we construct a simple stochastic process in which events are triggered each time a threshold criterion is fulfilled. For a given time interval each event occurs therefore stochastically independent of another meaning that the probability of one abrupt warming does not affect the probability distribution of any other warming events in that interval. Those sequences were obtained from preceding research and additionally we applied a Bayesian change-point algorithm with the motivation of estimating uncertainties of event location and number. Given the recent glacial DO€“ event recurrence pattern we are only able to reject the exponential distribution in case of a thresholded DO-sequence. Additionally, novel periodicities of \(\sim 900\) and \(\sim 1150\) yrs in the NGRIP record are reported besides the prominent 1500 yrs cycle, but demonstrate that although a high periodicity reflected in a high Rayleigh R can be found in the data it remains indistinguishable from a simple stationary random Poisson process. These are quite interesting findings as \(\sim 1500\) and \(\sim 900\) yrs periods are visible throughout the Holocene.

Observed and simulated statistics of extreme events shall be compared between different model configurations and observations to evaluate if, and under what conditions climate models are reliable for simulating future changes. Through a combination of paleoclimate records with the analysis of climate-model simulations, we can contribute to a better understanding of the long-term evolution of climate variability modes and their linkage to synoptic events. Such strategy can overcome our current knowledge gaps, with special emphasis on the role of ocean circulation, climate modes of variability, and regional extreme climatic events. Numerical climate models operate on increasingly finer grid sizes as the performance of parallelized super computers increases. Whether a model can represent a geophysical process depends on the model formulation and discretization. Since the spatial scale of oceanic eddies is O(1-100) km (first baroclinic Rossby radius of deformation), the ocean model grid resolution needs to be on the same order to represent these ubiquitous small-scale features. Alternatively, their effects must be parameterized as in state-of-the-art general circulation models, the oceanic components run on horizontal resolutions of about 1 degree. One of the critical feedback mechanisms for long-term variability is the interaction of Arctic sea ice and the global ocean circulation, which can affect climate variability on short timescales and might lead to relatively rapid climate change. It is likely that the variability on synoptic time scales can have a large effect on decadal-to-multidecadal variability and vice versa.

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