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Approaches to climate change study and neural network modelling

Approaches to climate change study and neural network modelling

Approaches to climate change study and neural network modelling. Antonello Pasini CNR - Institute of Atmospheric Pollution Rome, Italy. Outline. Climate science and dynamical modelling ; neural network model; assessment on the past; about predictability in past and future scenarios;

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1.08k views • 87 slides
Prof. Dudley Shallcross ACRG Tim Harrison Bristol ChemLabS 2008

Prof. Dudley Shallcross ACRG Tim Harrison Bristol ChemLabS 2008

Prof. Dudley Shallcross ACRG Tim Harrison Bristol ChemLabS 2008. A Pollutant’s Tale. Comparison of the Earth with other planets Nitrogen and oxygen Temperature structure Tropospheric pollutants. Talk outline. 3 most abundant gases in each planetary atmosphere

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613 views • 38 slides
The Great Channel 4 Swindle

The Great Channel 4 Swindle

The Great Channel 4 Swindle. Robin Hogan Thanks to: Jonathan Gregory, Giles Harrison and Peter Stott. Return. Overview. The following claims were made in “The Great Global Warming Swindle” produced by Martin Durkin: “Concentrations of CO 2 are too small to be important”

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291 views • 20 slides
The Great Channel 4 Swindle

The Great Channel 4 Swindle

The Great Channel 4 Swindle. Robin Hogan Thanks to: Jonathan Gregory, Giles Harrison and Peter Stott. Return. Overview. The following claims were made in “The Great Global Warming Swindle” produced by Martin Durkin: “Concentrations of CO 2 are too small to be important”

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214 views • 20 slides
Chris Forest, Andrei Sokolov, Peter Stone: MIT Myles Allen: University of Oxford

Chris Forest, Andrei Sokolov, Peter Stone: MIT Myles Allen: University of Oxford

Chris Forest, Andrei Sokolov, Peter Stone: MIT Myles Allen: University of Oxford. Limitations of historical data records for constraining the properties of the climate system that are relevant for decadal and longer predictions. VTT Workshop, Asheville, NC October 27, 2003.

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325 views • 17 slides
Dependencia de la humedad de saturación (q*) con la temperatura (T)

Dependencia de la humedad de saturación (q*) con la temperatura (T)

Dependencia de la humedad de saturación (q*) con la temperatura (T). Pendiente crece con la temperatura. Dependencia de la adiabática húmeda con temperatura a presión constante. 2xCO2. IPCC-AR4.

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256 views • 4 slides

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