Teaching Activities

2050-12-31 23.59.59-29

At Georgia Institute Of Technology (US)



 Introduction to Environmental Sciences (EAS1600)

Lab instructor for the course  “Introduction to environmental Sciences”  EAS 1600,  Spring 2014)

 Lab experiences:
  • LAB 01:  Math and Science tune-up  [ favicon-pdf ]
  • LAB 02:  DaisyWorld [ favicon-pdf ]
  • LAB 03:  Solar Radiation [ favicon-pdf ]
  • LAB 04:  The Ideal Gas Law  favicon-pdf ]
  • LAB 05:  Heat Transfer  favicon-pdf ]
  • LAB 06:  Atmospheric Aerosols favicon-pdf ]
  • LAB 07:  Deep ocean circulation  favicon-pdf ]
  • LAB 08:  Minerals and rocks  favicon-pdf ]
  • LAB 09:  Archimedes' Principle and Isostasy  favicon-pdf ]
  • LAB 10:  Plate Tectonics  favicon-pdf ]

My result as teacher: my first anonymous student survey [favicon-pdf ]                       


 Ocean Modeling (EAS6131)

co-instructor for the course  “Ocean Modeling”  (EAS6131,  Fall 2018)

Main instructor: Emanuele Di Lorenzo     Co-instructor: Giovanni Liguori

Syllabus:  favicon-pdf  OceanModeling.pdf

Course Overview: This course is an introduction to ocean modeling. It is intended for first and second year graduate students. The goal of the class is two fold. (A) Understand different types of ocean models of ranging complexity from simple 2D shallow water and quasi-geostrophic models, to layered and full 3D primitive equations ocean models. In particular during the class you will be able to derive the dynamical equations, understand the implications of physical assumptions made in the derivations and develop intuition for the applicability of each model class. (B) Provide a “hands-on” experience in implementing and using both large and regional scales circulation models. This part of the class relies on being able to use fluently at least a programming language of choice (e.g. Fortran, MATLAB).

Main Text: 

[GFD & Numerics ] Introduction to Geophysical Fluid Dynamics - Physical and Numerical Aspects
Cushman-Roisin - on the internet (click link above)

Other references:  

[GFD Reference] Atmospheric and Ocean Fluid Dynamics
Geoffrey K. Vallis -Cambridge Press

[Auxiliary] Numerical Modeling of Ocean Circulation
Robert N. Miller, Cambridge Press

[Auxiliary] Numerical Models of Oceans and Oceanic Processes
Kantha and Clayson, International Geophysics Series Vol. 66

Orientation class on the computational environment: favicon-pdf  OM_21Agu18.pdf

 Physics and Chemistry of the Oceans (EAS4305/6305)

Physics and Chemistry of the Oceans (Fall 2016)

Instructor: Taka Ito     Teaching Assistent: Giovanni Liguori

Syllabus:  favicon-pdf  PhysChemOcean.pdf

Course Overview: The objective of this course is to provide a broad view of the oceans for advanced undergraduate and graduate students interested in marine sciences. The course material covers fundamental principles of physical and chemical oceanography, focusing on the basic processes and mechanisms including principles of fluid dynamics, thermodynamics, aquatic chemistry, gas transfer, photosynthesis and respiration. These principles are applied to large-scale ocean circulation and biogeochemical cycling.

Main Text: Descriptive Physical Oceanography, By L. D. Talley, G. L. Pickard, W. J. Emery and J. H. Swift, Academic Press, 2011. [link]

Lecture topics:
  • Part 1. Thermodynamics and fluid mechanics 
    1. Seawater Properties (ch.1-3)
    2. Oceanographic data and water masses (ch. 4)
    3. Mass, salt and heat budget (ch.5)
    4. Fluid dynamics principles (ch.7)
    5. Ekman/Geostrophy (ch.7)
    6. Thermal wind/Dynamic topography (ch.7)
  • Part 2. Seasonal cycle and upper ocean biogeochemistry
    1. Mixed layer and seasonal cycle
    2. Ocean productivity
    3. Nutrient and carbon cycling
  • Part 3. Large-scale circulation and global carbon cycle 
    1. Atlantic Ocean (ch.9)
    2. Pacific and Indian Ocean (ch.10-11)
    3. Arctic and Southern Ocean (ch. 12-13)
    4. Global Circulation (ch.14)
  • HW#1 favicon-pdf  Intro.pdf           matlabicon script_example.m   logomatrixmatlab_2 data.mat
  • HW#2 favicon-pdf  Intro.pdf           matlabicon script_example.m   logomatrixmatlab_2 data.mat


 Advanced Environmental Data Analysis (EAS6490)

Advanced Environmental Data Analysis  ( Fall 2014, 2015 and 2017)

Instructor: Emanuele Di Lorenzo     Teaching Assistent: Giovanni Liguori

 Lecture topics:
  • Background Review: Matrix and Vector Algebra, Fundamental Statistical Measures, Multivariable Probability Densities, Sample Estimates, Correlation and Covariance, Function and Sums of Random Variables, Central Limit Theorem. (3 lectures)
  • Combining models and observations: Interpolation and Function Fitting, Least Square modeling and Singular Vector Expansion, Uncertainties in Estimates, Inverse Methods, Statistical vs. Dynamical Constraints. (7 lectures)
  • Time Series Analysis: Time and Frequency Domain Models, Stationarity, Auto-Regression Models, Spectral Analysis and Coherence, Trend Analysis and Significance, Estimating errors in time series reconstruction. (8 lectures)
  • Forecasting and Extrapolation: Statistically Optimal Linear Estimators, Regression models, space and time models, objective mapping (multivariate regression), covariance modeling. (7 lectures)
  • Decomposing signals: Multivariate eigenfunction analysis, EOFs, PCA, CCA, and Wavelet analysis. (5 Least square method and empirical models)
  • Least square method and empirical models I (lecture 8/27/2014)                               Some of the materials used during this session: favicon-pdf  LSQ_practice.pdf                              matlabicon LSQ_examples.m   logomatrixmatlab_2 GISS_Atm_T.mat
  • Least square method and empirical models II (lecture 9/17/2014)                                  Chi-square test for goodness of fit - The example of the CO2 curve               (Material from Manu):  favicon-pdf  CO2_example.pdf      matlabicon EXAMPLE_CO2_curve.m       logomatrixmatlab_2 CO2.mat
  • Review of LSQ review and HW#3 (lecture 10/15/2014)
  • Times series analysis  I (lecture 10/20/2014) 
     - Power spectrum review                                                                                                                          - Auto-covariance and auto-correlation functions
  • Times series analysis  II (lecture 10/22/2014) 
     - Auto-correlation function for red noise time series                                                                    - Convolution theorem to explain the relation between auto-covariance and power spectrum
  • EOF Analysis (lecture 11/24/2014; lectures 10/13/2015 and 10/15/2015 )                           here some of the materials used in class                                                                                           Homework: compression-while-saving 06-hw-EOF.zip    favicon-pdf  06-hw-EOF.pdf
  •  Final exam:

 PDF favicon-pdf    Here a movie that you may find helpful Movie_icons-01-24       logomatrixmatlab_2 07-data.mat

[  Here the official course webpagehttp://www.oces.us/eas-6490/index.html  ]

 Modes of Variability in the Climate System (EAS8001-Oceanography Seminar)

Modes of Variability in the Climate System: A framework to interpret and understand the observed climate variability
Course outline [ PDF ]
Class schedule [GOOGLE DOC ]

Materials [HERE require password]
Official course website [LINK]

 Modal Decomposition and EOF Analysis (EAS-MathClub)

Lecture series on: Modal Decomposition and Empirical Othogonal Function Analysis (EAS Math Club, Summer 2014)


 Lecture 1: The ideas behind the Modal Decomposition. 
 Lecture 2: Tutorial on MATLAB #1.  A basic geometrical example
 Lecture 3: Tutorial on MATLAB #2.  Understaing the EOFs through a low  order dimension example
 Applications: (i) Tropical Pacific Climate Variability and (ii) Image Compression 

 Handling NETCDF files using CDO (EAS-MathClub)

This tutorial has been organized in collaboration with Yohei Takano

Materials:    compression-while-saving DATA     favicon-pdf  CDO reference card

Tools used



At Universidad de Alcalá (Spain)


 Clases practicas para el curso de Dinamica Atmosferica (MASTER CERA)


Clases prácticas para el curso de Dinámica Atmosférica ( Master CERA  curso 2010/2011 y 2011/2012)

Guiones de practicás

Herramientas utilizadas

  • CDO (Climate Data Operator) Es un software práctico y relativamente sencillo para manipular y analizar datos climáticos.
  • ncview (netcdf viewer) Un software práctico y sencillo para visualizar de manera rápida y eficaz ficheros en formato netcdf.
  • kwrite Un simple editor de texto para entornos KDE.


 Analisis del estado de la atmosfera mediante el uso del Tefigrama (Meteorología para CCAA)

Práctica de Meteorología – CC. AA.-2011-12- 

Material para la Práctica

  • favicon-pdf  Introduccion al Tefigrama
  • favicon-pdf  Practica 1
  • favicon-pdf  Practica 2
  • favicon-pdf  Hoja del Tefigrama



At Università degli Studi di Napoli "Parthenope" (Italy)


 Climate Data Analysis


  • favicon-pdf  Lezione Teorica (Mattina)
  • favicon-pdf  Lezione Pratica (Pomeriggio)
  • compression-while-saving DATA


At Servicio Nacional de Meteorologia e Hidrologia del Peru - SENAMHI (Peru)


 Regional Climate Modeling and Climate Data Analysis

In this 5 days long intensive course we learn how to use the regional climate model REMO and how to analyze its output, as well as any other climate dataset. We learn how to handle and analyze massive datasets using bash script in combination with the Climate Data Operator (CDO) software. More sophisticated analysis are performed using MATLAB, which is the programming language that will be used during most of the course.


 - How to use the regional climate model REMO

Some notes will be posted soon


-  Introduction to Data Analysis

  • Data manipulation and basic analyses using CDO


En este taller vamos a analizar las salidas de una simulación de alta resolución hecha por el modelo regional climático REMO para un dominio que incluye parte de América del Sur, el Atlántico tropical y parte de África. La simulación ha sido forzada por ERA-Interim y cubre los años 1980-2012. Las variables que vamos a analizar son la temperatura media mensual (TMP) y la precipitación media mensual (PRE). Estas variables serán comparadas con la base de datos de observaciones climáticas proporcionada por la University of Delaware y con el reanálisis ERA interim (ERAI).

Los principales objetivos de este taller son:

1) Aprender a manejar un conjunto de herramientas para analizar y visualizar datos climáticos

2)   Realizar un análisis preliminar de las salidas de un modelo climático

                 favicon-pdf Practice_1          compression-while-saving Data_Practice_1


  • Advanced Climate Data Analysis using MATALB
  1. Compute climatologies and other basic statistics
  2. Compute de-trended and de-seasoned anomalies
  3. Perform a composite analysis
  4. Perform regression and correlation analysis
  5. Identify statistical and physical modes through EOF analysis
  6. Perform data filtering using EOF analysis
  7. Compute the power spectrum
  8. Assess the statistical significance of the power spectrum
  9. Use fft to high-pass, low-pass and band-pass your data
  10. Assess the statistical significance using the Monte Carlo method

                 favicon-pdf Practice_2          compression-while-saving Data_Practice_2


Guest lectures


 The Climate System and its 'Child'


April, 6th, 2016 at Agnes Scott College   Print

The purpose of this lecture is twofold: First, give an introduction about the Earth's climate reviewing basic principles and fundamental theories, and second, address the most prominent and recurrent phenomenon in the Earth's climate on inter-annul timescales,  El Niño.


Decomposizione in Modi della Variabilita' Climatica (Italian) 

Dec, 16th, 2015 at  Università degli Studi di Napoli "Parthenope" (Italy)   Logo_Parthenope

In dinamica del clima, climate dynamics, si sente spesso parlare di modi di variabilità come NAO, PNA, PDO, ENSO, etc... Ma cosa sono veramente questi modi di variabilità' ? E sopratutto, come vengono definiti e/o individ