81754 - CLIMATOLOGY

Learning outcomes

At the end of the course the student: - knows the basics of physical climatology; - knows the main statistical methods used in climate analysis; - can use the results of both numerical global climate simulations and regional climate models for future climate scenarios evaluation: - acquires abilities in communication on the subject and becomes familiar with the English terminology used in climatology; - knows how to use scientific literature.

Course contents

The course is organized in two modules delivered by two instructors run in parallel (2+2 hours of each module per week)

Module 1: Prof Michele Brunetti
Module 2: Prof. Erika Brattich

Below the course contents for the two modules:

 

Module 1

The Global Energy Balance

• The nature of electromagnetic radiation and the physical laws of radiation
• Planck’s Law of Blackbody Emission
• Emission temperature of a planet
• Greenhouse effect
• Distribution of insolation
• The global energy balance (incoming solar radiation, outgoing long-wave radiation, albedo)

Atmospheric Energy Transfer and Climate

• Selective Absorption and Emission by Atmospheric Gases
• The Lambert-Bouguet-Beer Law
• Absorption rate and heating rate
• Schwarzchild's Equation
• Heuristic Model of Radiative Equilibrium
• Radiative-Convective Equilibrium Temperature Profiles

Clouds and radiation

• The radiative properties of clouds
• A Simple Model for the Net Radiative Effect of Cloudiness
• Observed Role of Clouds in the Energy Balance of Earth

The Energy Balance of the Surface

• The Surface Energy Budget
• Storage of Heat in the Surface
• Sensible and Latent Heat Fluxes
• Variation of Energy Balance Components with Latitude

Aerosols and Climate

• Aerosol distribution
• Volcanic Eruptions and Stratospheric Aerosols
• Anthropogenic Aerosols and Atmospheric Sulfur

The Hydrologic Cycle

• Water in the climate system
• Terrestrial branch of the hydrologic cycle
• Atmospheric branch of the hydrologic cycle
• Latitudinal distribution of the water balance
• The concept of evapotranspiration

The General Circulation of the Atmosphere

• The energy balance of the atmosphere and the general circulation
• The mean meridional circulation
• Eddy circulation
• The meridional transport of energy
• The meridional transport of moisture
• Angular momentum balance

The Orbital Parameter Theory of Ice Ages

• Historical introduction
• Eccentricity and the Sun-Earth distance
• Obliquity and insolation
• The variation of annual mean insolation
• Orbital parameter evolution
• Testing the theory
• The middle pleistocene transition

The Earth Observation

• The International Geophysical Year and the Global Observation System
• A brief history of the ground base observation networks with a focus on the Italian network

Proxy Data

• What proxy data are
• Documentary reconstructions
• The delta-O18 isotope ratio
• Some examples of proxies: Corals, Palynology, Dendroclimatology, Ice cores, Sediments

The Problem of the Data Quality in Climatology

• The importance of data quality in climatology
• The example of ground based stations
• Data error sources (instruments change, instrument and station relocation, solar radiation sheltering, in situ changes, observation rules changes)
• The metadata
• Some homogenization techniques

Principal Component Analysis/Empirical Orthogonal Functions (PCA/EOF)

• What PCA is
• Diagonalization of the covariance matrix (eigenvalues and eigenvectors)
• Covariance and correlation matrix
• Varimax rotation
• Some example of PCA
• Extreme Events Theory
• General aspects of the extreme events theory
• Extremal Types Theorem
• The Generalized Extreme Value (GEV) distribution
• Above threshold models and the Generalized Pareto distribution

Stochastic Processes

• Temporal series and stochastic processes
• Basic definitions (characteristic time, stationary processes, weakly stationary processes, weakly cyclo-stationary processes, ergodicity)
• Autoregressive processes: mean and variance of an AR(p) process, AR(1), AR(2), Stationarity of AR Processes
• Moving Average Processes
• Auto-regressive Moving Average Processes
• Autocovariance function
• The Yule–Walker Equations for an AR(p) Process
• Autocovariance function of an AR(1) and an AR(2)
• The spectrum (definition and properties)

 

Module 2

Introduction

• Components of the climate system
• Introduction to GCMs.
• Purpose and limitations of climate modelling
• Historical development
• Examples: Simulation of the 20th century to quantify the link between the increases in atmospheric CO2 concentrations and changes in temperature; CO2 emissions permitted for prescribed atmospheric concentration.

Climate variability

• Intro to climate variability (ENSO, NAO)
• IPCC scenarios and emissions: Climate variability and weather forecasting

Climate feedback (F) and sensitivity (S)

• Climate sensitivity and climate feedback: definitions and mathematical derivation.
• Calculations of F and S due to: Change of S0 by 1%; Change of 1% in planetary albedo; Change of 1% in greenhouse parameter; Stefan Boltzmann feedback; Water vapour feedback; Ice albedo feedback; Cloud feedback; Energy-balance climate model ( Budyko-Sellers model).
• The biogeochemical feedback: the Daisy-world model; The Budiko-Sellers model.

Large-scale circulation in the ocean

• Physical and chemical characteristics of the ocean
• The “mixed layer”
• Wind driven circulation
• Density driven deep thermohaline
• Density driven deep thermohaline circulation
• Shallow water equations
• Different types of grids in climate models.

Atmosphere-Ocean interactions

• Coupling of physical model components
• Thermal boundary conditions
• Hydrological boundary conditions
• Momentum fluxes
• Mixed boundary conditions
• Coupled models
• Multiple equilibria in the climate system
• Abrupt climate change recorded in polar ice cores

The paleoclimate (some aspects of this are analysed in module 1)

• Evolution of climate and analyses of different eras in terms of feedbacks
• Radioactive dating of the rocks and proxy data
• Open questions
• Uses of paleoclimatic data

Statistics in climate

• Review of basic probability concepts
• The Axioms of Probability
• Independence
• Persistence
• Empirical Distributions and Exploratory Data Analysis.
• Bayes’sTheorem and inference in climate
• Indicators of position, dispersion and symmetry
• Pearson correlation
• Spearman rank correlation.
• Parametric Probability Distributions
• Discrete distributions
• Continuous distributions
• Parameter Fitting Using Maximum Likelihood (The Likelihood
• Function, The Newton-Raphson Method, Sampling Distribution of
• Maximum-Likelihood Estimates)
• Statistical Simulations (Uniform Random Number Generators,
• Non-uniform Random Number Generation by Inversion, Nonuniform
• Random Number Generation by Rejection, Box-Muller Method for
• Gaussian Random Number Generation)
• Hypothesis testing
• Elements of statistical forecasting
  
  

Readings/Bibliography

Dennis L. Hartmann: Global Physical Climatology ; Academic Press

Peixoto and Oort: Physics of Climate; American Institute of Physics; 1st edition (February 1, 1992)

Wilks: Statistical Methods in the Atmospheric Sciences, 3rd Edition (2011)

Teaching methods

Frontal lectures

Assessment methods

The final exam is intended to verify the understanding/comprehension of all phenomenological, mathematical/statistical aspects of the topics dealt during the two modules.

The final exam consists in an oral examination during which the student will be asked generally three questions selected between the two modules.

The student may be able to choose one topic.

Teaching tools

PC and Projector

Office hours

See the website of Michele Brunetti

See the website of Erika Brattich