Wednesday, 9 July 2014

Basic Climate Science Facts

Climate Science Facts

1.      Earth's Global Mean Surface Temperature has increased at approx. 0.6 – 0.8 deg. C per century for the past 300 years in a step-wise fashion with 20-30 year periods of slight cooling interspersed between 25 to 40 years of warming.
2.   The Greenhouse Effect  answers the question "Why doesn't all the heat disappear into space overnight?  Some gases (water vapour, methane, nitrous-oxide and carbon-dioxide) slow heat escaping to space due to their radiative properties. Gravitational effects of the whole atmosphere also help keep us warm.  For detailed explanation see
3.      Carbon-dioxide can cause warming by emitting Infra-Red energy. First CO2 will try using the energy to move away from other molecules, occasionally colliding with them and transferring the energy to them. For latest research into this see New research on atmospheric radiative transfer by Judith Curry which discusses three new papers highlight how atmospheric radiative transfer, particularly how it is treated in climate models, is not ‘settled science.’:-
4.      The sun is the main driver of heating on Earth, but its' variations in amount of radiance are small in comparison to variation in Earth's surface temperature.
5.      The number of sunspots correlates with a warming Earth e.g. the depths of the Little Ice Age were at the Maunder Minimum 1645-1715, and Dalton Minimum, 1790-1830. (Correlation does not indicate causation - it could be coincidence, there could be a 3rd driver etc.)  Sunspots cause additional Ultra-Violet light, magnetic storms and an increase in cosmic rays.
6.      Volcanos can also contribute some warming.  80% of volcanos are under-sea.  The remaining 20% in the atmosphere send so much dust and particles into the atmosphere that overall they cool the planet.  Generally, atmospheric volcanos' cooling effect will last less than 2 years.
7.      The atmospheric and oceanic weather systems move heat from the equator to the poles over a period of time.  They are mathematically chaotic i.e. sensitive to initial conditions (hence unpredictable) and deterministic.
8.      Water vapour is the most active Greenhouse Gas accounting for approx 50% of the Greenhouse effect.
9.      Clouds are the biggest uncertainty in Climate Science.  Low clouds tend to reflect sunlight back to space during the day, thus cooling. It is not understood when, why or how cloud formation takes place.
10.      The Pacific Decadal Oscillator / El Niño-Southern Oscillation moves heat around the Earth, mainly between the equator and the poles and may subduct heat to the ocean deoths causing a lag in heat affecting the surface temperture. Monitoring by NASA calculates an index which is positive when Earth's global surface temperature warms (''El Nino' years) and cools with negative index ('La Nina's'). This creates a lag between the forcing agent and the realisation of heat at Earth's surface.
10. The Atlantic Meridonal Oscillation , like ENSO, affects surface temperature.  It's most well-known component is the warm Gulf Stream which keeps the British Isles warmer than other land at the same latitude.
11.  Statistics methods were developed with the assumption that each instance of a measure (e.g. surface temperature) is independent of every other and has no natural ordering (e.g. tossing a coin).  Thus statistical analysis is unreliable unless the data is either of:-
                                i.            Ergodic Process
                              ii.            Stationary Process
Note that the UK Met Office does not rely solely on statistical models in its detection and attribution of climate change. See JuliaSlingo_May2013 pdf which includes "… the complexity and non-linearity of the holistic climate system, its internal variability and its physical response to external forcing agents …"
12.  General-Circulation computer models have a couple of issues to cope with:-
                                i.            Navier-Stokes Equations are used which need to be approximated before use. See NASA's equations here and from various universities Stanford,  Illinois, CaltechManchester, New York, Colorado

                              ii.            There are too many variables to be able to run the models within a reasonable time, so ' parametrisations' are used for items which don't vary much.
The models are designed for physical processes to be investigated and not for prediction. Many different physical parameters are defined which can be varied and a suite of runs done to compare results.

A simple intro can be found at
And for a more complex look at the pros and cons see the series of posts by Tamsin Edwards, climate modeller
a physicist'sview

Friday, 4 July 2014

The Season or Sun argument for Climate Predictability

You find climate scientists explaining ”we cannot predict the weather one month in advance, we can predict that next winter it will be colder than this month. That a model cannot predict natural variability (weather) does not mean that it cannot predict the long term climate (winter).”

However, the difference between one summer and the next is many magnitudes larger than differences predicted for surface temperatures.

Winter and summer are differentiated by the earth's orbit round the sun giving more sunshine during the summer than winter.  We also know that the sun's sunspot cycle of magnetic storms affects the weather.  The 'consensus' surface temperature variance expected is ~1% with cycles between about 9 and 14 years.  The 'pause' in global warming from 1998 to present has occurred during cycles of low sunspot numbers – an inactive sun. But not as inactive as in the depths of the 'Little Ice Age'

In both cases, the chaotic nature of weather systems means that there is no linear relationship in how much or how little the Earth's surface temperature will be affected. [see recent paper on Sun’s magnetic field Nov 2013]. A few sun researchers predicted slight cooling, yet none of the General Circulation computer models did.

Human emissions of carbon dioxide directly join the atmosphere and take part in weather's chaotic song-and-dance. Thus climatologists can predict that there will be some sort of warming affect but they'll have to be as vague as 'a bit warmer, perhaps'.  There's no chance of being able to give a figure for sensitivity i.e. x degrees increase for doubling of carbon-dioxide.

The climate itself is Fractal and Chaotic.  See paper below by Tim Palmer & Julia Slingo of UK Met Office:-
Phil. Trans. R. Soc. A-2011-Slingo-4751-67.pdf

Unfortunately, climatology is replicating the economics route.  When things go unexpectedly wrong (e.g. 2008) the 'consensus' economists make a big noise of "nobody saw it coming" despite the fact that a handful had done so (cash-flow researchers) so they're able to maintain the ear of politicians and keep the world economy aping a massive Ponzi scheme.  Meanwhile, economists add the missing variable(s) to their computer models and proudly tell each other when they're able to predict the past.

Not Good!