New paper is predicting hotter temperatures from "natural variability" for the next few years

Read the gobbledygook below in the abstract of the paper published in Nature.

"Natural variability" is incredibly vague and they are comparing with climate forcing based in computer modelling which has been shown to be completely wrong.

The 'conspiracy theorist' in me thinks this may be a way to prepare the public for the abrupt climate change that is already underway without admitting to the fact that all their predictions have been completely wrong. 

They continue the myth of a 'hiatus' in warming. There was no 'hiatus'. 

NOAA Study: No Hiatus In Global Warming

What do they think is going to happen after 2022?  Do they think we will return to the mythical gradual, 'steady-as-you go' curve to 2100?!

Our local experts continue to bullshit us even after this paper.

Radio NZ thought this was worth a full 2 minutes of their broadcast time

Get ready, NZ, for a years-long warm spell

Stuff,

15 August, 2018

Several more warm years could be on the way, if a new statistical temperature forecasting system turns out to be accurate.

The system predicts it'll be unusually warm from this year until 2022, even without including the impact of climate change.

The researchers from France, the United Kingdom and the Netherlands say they confirmed the accuracy of their system in a series of historical hindcasts from 1880 to 2016. In particular, a retrospective prediction using the system - called Procast - was able to capture the decade-long global warming hiatus after 1998.

The new system predicts global mean air and sea surface temperatures. A paper describing the research has been published in Nature, which said natural variability in the climate system was harder to predict than external forcing, such as greenhouse gas emissions.

"Florian Sevellec and Sybren Drijfhout develop a statistical approach based on transfer operators - an established statistical analysis method that rationalises the chaotic behaviour of a system - that captures natural variability," Springer said.

"A forecast for 2018‒2022 indicates that warming owing to natural variability will temporarily reinforce the long term global warming trend, leading to an increase in the likelihood of temperature extremes."

Niwa chief scientist, climate, atmosphere and hazards Dr Sam Dean said the article was suggesting extra warming should be expected on top of what would be expected from ongoing climate change.

"Another way to think of this is that there is less chance of having fortuitously cool years thanks to natural processes. We can't be sure of course but we do know that predictions like this are usually a bit better than guessing, because of variability in ocean circulation that can change slowly over many years.

"As an example, during the 2000s the world had more La Ninas, which led to cooler global temperatures, and the oceans took up lots of extra heat. Since 2014 this appears to have changed, with more El Ninos and much hotter years," Dean said.

As far as New Zealand was concerned, not every year that was warmer than usual globally was hot in this country.

"This is because whether we get hot weather or cold is also dependent on whether our wind blows more from the north or the south, and this is a very local effect," Dean said.

"But it is also true that all things being equal the odds of a hot year here are higher when global mean temperatures are higher. For example, 2016 was the hottest year globally since records began, and it was also the hottest year recorded here in the Niwa national temperature series."

Professor James Renwick of Victoria University said it would be interesting to see if the system worked well.

"Statistical models are attractive as they can be run very quickly on any laptop or phone, while global climate model simulations take days or weeks on supercomputers. The downside is that statistical models do not capture the physics of the climate, so can be unreliable when used to extrapolate," Renwick said.

The paper suggested the coming few years were likely to see extremes of heat and dryness continue. "If the warming trend caused by greenhouse gas emissions continues, years like 2018 will be the norm in the 2040s, and would be classed as cold by the end of the century."

Here is the introduction to the paper in Nature.

A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend

Nature,com,

14 August, 2018

Abstract

In a changing climate, there is an ever-increasing societal demand for accurate and reliable interannual predictions. Accurate and reliable interannual predictions of global temperatures are key for determining the regional climate change impacts that scale with global temperature, such as precipitation extremes, severe droughts, or intense hurricane activity, for instance. However, the chaotic nature of the climate system limits prediction accuracy on such timescales. Here we develop a novel method to predict global-mean surface air temperature and sea surface temperature, based on transfer operators, which allows, by-design, probabilistic forecasts. The prediction accuracy is equivalent to operational forecasts and its reliability is high. The post-1998 global warming hiatus is well predicted. For 2018–2022, the probabilistic forecast indicates a warmer than normal period, with respect to the forced trend. This will temporarily reinforce the long-term global warming trend. The coming warm period is associated with an increased likelihood of intense to extreme temperatures. The important numerical efficiency of the method (a few hundredths of a second on a laptop) opens the possibility for real-time probabilistic predictions carried out on personal mobile devices.

Introduction

Many studies have focused on the attribution of climate change from global to local scales1. These studies relate variations in observations with variations in external forcing to explain, or partially explain, the observed changes. For example, changes in global-mean surface air temperature (GMT) can be partially attributed to variations in external climatic forcing, such as volcanic eruptions or aerosol and greenhouse gas emissions2 (Fig. 1). However, there still remains a residual to this forced component (Fig. 1e), which can be interpreted as the internal variability of the climate. This variability, because of its dominance over the forced trend on interannual to decadal timescales (Fig. 1g), is at the heart of interannual climate prediction3,4, and the goal of our study. Moreover, since volcanic eruptions are unpredictable by essence and aerosol and greenhouse gas emissions depend on socio-economic choices, further improvement of climate predictions will mainly occur through better, more accurate predictions of the internal variability. This conclusion is also true for the global-mean sea surface temperature (SST) studied here (Fig. 1).

Fig. 1

Attribution of observed global-mean surface air temperature (GMT) and sea surface temperature (SST). a, b The total (red) annual, (purple) 5-year and (blue) 10-year variations in GMT and SST measured from 1880 are decomposed (through an attribution method based on multivariate linear regression onto volcanic eruptions, aerosol concentration, and greenhouse gas concentration2) into c, d a forced contribution and e, f a residual. g, hRelative variance of forced and residual GMT and SST changes as a function of the duration of these changes. Variations are mainly controlled by the residual, rather than forcing on interannual to decadal timescales. The observed GMT are from NASA GISS temperature data, and SST is from the NOAA ERSSTv5 record

In this study, we predict this internal variability through the use of transfer operators trained by GMT and SST variations simulated by 10 climate models from the Coupled Model Intercomparison Project phase 5 (CMIP5)5. This methods allows to determine skillful and reliable probabilistic forecasts of GMT and SST. Using this method to predict the future, the outcome is that the current climate has a large likelihood to reach a warmer than normal period over the next 5 years on top of the forced global warming trend.