ATMO 632: Week 1
Review of Concepts in Probability & Statistics
http://www.cgd.ucar.edu/~svn/atmo632/week1.htm
Events, sample, population
Event: daytime high temperature above 100 F
Sample: The last 10 summers
Population: The last 1000 summers
Dependent and independent events
Days when power consumption is very high
Days when the stock market is up
Probability properties
Non-negative, sum to unity
Independent events
Probability distribution function (PDF)
Mean, mode, median
Expectations & moments, moment generating function
Discrete distributions (Binomial, Poisson)
Continuous distributions (Gaussian, Student-t, Chi-square)
The difference between weather and climate
PDF of Lorenz system vs. North Atlantic Oscillation
Lorenz system: bimodal PDF
NAO: Unimodal PDF
Central Limit Theorem
Hypothesis testing
Degrees of freedom
z, t, and chi-square statistics (Please Turn Over)
103, 101, 111, 99, 107, 109, 11, 104, 108
“Extra credit”
Write a program to solve the Lorenz system of equations
dX/dt = s (Y – X)
dY/dt = -XZ + rX – Y
dZ/dt = XY – bZ
for parameter values s = 10, r = 28, b = 8/3. Starting from a random initial condition, integrate for a long time (i.e., until the trajectory has spanned the two lobes of the attractor several hundred times or more). Plot the (X,Y) trajectory and the probability distribution function (PDF) of the X coordinate. Repeat the same starting from an ensemble of 100 different randomly-chosen initial conditions, but plot the “ensemble-mean trajectory”, i.e., the trajectory defined by the average of the (X,Y) values of each of the 100 individual trajectories. Plot the PDF of the X coordinate for the ensemble-mean trajectory.