Webpage of the course: Climate Modeling (LMAST)  A.A. 2019/20  (I Sem.)
G. Redaelli (gianluca.redaelli@aquila.infn.it)
L. Sangelantoni
TEXTBOOKS:
J. Wallace and P. Hobbs, Atmospheric Science: An introductory survey, Academic PressLessons
1 
Tu 01 October 
GR 
Introduction to the course 
2 
Tu 15 October 
GR  Present day climate. Temperature, pressure, winds. Surface winds and SST. The climate system. 
3 
Tu 22 October 
GR  Black Body, spectra and radiative properties of the atmosphere. Calculation of the Effective Emission Temperature of the Earth. Greenhouse effect. 
4 
Tu
29 October 
GR  Radiative
Forcing. Climate Equilibria,
Sensitivity and Feedback.
Climate feedback factors. 
5 
Tu 5 November 
GR  Transient versus equilibrium response. Daisyworld. 
6 
Tu
12 November 
GR  GHGs and GWP. Evidences of the buiding of GHGs and of global warming. Anthropogenic forcings. 
7 8 
Tu
19 November 
GR LS 
Climate sensitivity (TCR, ECS and ESS) from model and experimental data Components and phenomena in the climate system. Modeling the climate system and providing climate information at different temporal scale: WeatherSeasonaClimate projections 
9 
We 20 November 
LS 
From global to regional scale, dynamical downscaling. RegCM. Run a seasonal climate forecast 
10  Th 21 November 
LS 
Statistical
methods applied to
atmospheric sciences.
Background of the
Empirical Distributions
and Exploratory Data
Analysis; graphical
summary techniques,
empirical cumulative
distribution functions.
Reexpression, standardized
anomalies 
11 12 
Tu 26 November 
GR LS 
Climate tipping points. Basic types of climate models. Exploratory Techniques for Paired Data:Scatterplots, Pearson Correlation, Spearman Rank Correlation and Kendall’s τ Exploratory Techniques for HigherDimensional Data: the Glyph Scatterplot, Bivariate histograms, The Correlation Matrix. MatLab laboratory: empirical distributions representation techniques applied to ensemble seasonal forecasting. 
13  We 27 November 
GR  1D Energy Balance Model (EBM) for the calculation of Ts: numerical solution. 
14  Th 28 November 
LS  MatLab laboratory: Ensemble seasonal forecasting: how to derive a probabilistic forecast regarding mean and distribution tails anomalies 
15  Tu 3 December 
LS  Parametric
Distribution
Models.
Introduction to
climate extremes
and expected
changes due to
the
anthropogenic
forcing. 
16 17 
We 4 December 
LS AR 
Computational
laboratory
exercises:
computing climate
extremes with CDO
programming
language in Unix
environment (shell
scripting) Oceanic General Circulation 
18  Th 5 December 
GR 
Model's design and application. Hierarchy and evolution of climate models. 
19 20 
Tu 10 December 
GR LS 
Finite
grid vs spectral
formulation for
AGCMs. Climate extreme indices' computation. Practical session 
21 22 
We 11 December 
LS AR 
Climate
extreme indices'
computation.
Practical
session Oceanic General Circulation 
23  Th 12 December 
GR 
From
primitive
equations to
general
circulation in
an Aquaplanet
atmosphere.
Patterns and
indices of
Climate
Variability. 
24  Tu 17 December 
LS

Climate extreme indices' computation. Practical session 
25 
We 18
December

BT 
ChyM
Hydrological
Model 
26  Th 19 December 
GR  Climate modelling activities of CETEMPS 