Loading in 2 Seconds...
Loading in 2 Seconds...
Climate Modeling: MEA-719 DATE OF EXAM: MAY 05, 2003 TIME OF EXAM: 9-11am. REVIEW FOR FINAL EXAM. Grading scheme. Homework assignments: 20% Mid-term test: 20% Final exam: 30% Term paper: 30% (10%o/20%w). Organization of the Course.
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
REVIEW FOR FINAL EXAM
Course divided into the following components ~
International climate research organizational structure
Climate model predictions (SIP; Paleo climate; CC projections)
Climate modeling (observational)
Climate modeling (prediction)
Climate modeling applications (end-user)
TOPIC 1: International organization of climate research and applications programs
TOPIC 2: SESONAL-TO-INTERANNUAL VARIABILITY & PREDICTABILITY OF THE GLOBAL OCEAN-ATMOSPHERE-LAND SYSTEM (GOALS)~observations-diagnosis-models-applications
TOPIC 3: DECADAL TO CENTENNIAL TIME SCALES (DecCen)
TOPIC 4: ANTHROPOGENIC CLIMATE CHANGE
Should be familiar with all the guiding questions given at the beginning of the class notes for each major course topic
Basic structure of the CLIVAR- World Climate Research Program - WCRP (see schematic diagram
Scientific functions of each principal component
Time evolution of the anomalies
Time series & pattern correlation analysis
Root mean square error analysis
Hit/false alarm rates (& ROC)
Decision modeling (added value)
Need to be familiar with the primary steps for implementing the EOF method
Construction of standardized data matrix
Construction of covariance or correlation matrix (R)
Solve characteristic equation for the covariance/correlation matrix to obtain eigen value/eigen vector pairs
Determine cutoff for “noise” & signal E0Fs. A rule of thumb is to retain only those components with variance () greater than one or that explain at least a proportion 1/p of the total variance. This rule doesn’t always work & more sophisticated criteria exist.
Plot (i) Histogram for eigen values & separation between ‘noise’ & ‘signal’ modes may show
(ii) E0F patterns for dominant modes
(iii) E0F time series for dominant modes
6. If needed reconstruct data matrix by combining contribution of a subset of eigen modes. This is one way of filtering the original data set by ignoring the ‘noise’ modes
data map at t=k(k Column)
E0Fi , amp 1
amp (E0Fi , t=k)
E0Fi , ampi
E0Fi , ampp
(i) Derivation of simple decision model
(ii) Main assumptions (concept of ensemble forecasting)
(iii) Interpretation extreme conditions
Identity C & L
DECISION IF $ IS
IMPORTANT TO SECTOR
- Vorticity equation model
(i) Basic assumptions, (ii) terms in governing equations, and (iii) simple numerical schemes (in class reviewed centered differencing scheme)
Local such that represents the value of
at a particular point in space
Finite difference equations determine the evolution
Based on global functions
Basis functions determine the amplitudes and phases such that when summed up determine spatial distribution of dependant variables…difference between Spectral & Finite Difference Methods…
: ENSO : AA-Monsoon
: VAMOS (North America)
- Models have smaller pattern correlations and larger rmsd relative to the observational uncertainty
EOF-1: associated with the northward shift of the Tropical Convergence Zone (TCZ)
EOF-2: associated with the southward shift of the Tropical Convergence Zone (TCZ)
Should be familiar with the main steps involved in the assessment of the understanding of climate change, including how scenarios of human activities can cause such changes, future projections
Current state of understanding for @ step
Palaeoclimatic reconstructions for the last 1,000 years indicate that the 20th century warming is highly unusual, even taking into account the large uncertainties in these reconstructions
Observations vs Observations
The observed warming is inconsistent with model estimates of natural internal climate variability. It is therefore unlikely (bordering on very unlikely) that natural internal variability alone can explain the changes in global climate over the 20th century
Observations vs Models (natural variability)
The observed warming in the latter half of the 20th century appears to be inconsistent with natural external (solar and volcanic) forcing of the climate system.
Observations vs Models (with external forcing)
Anthropogenic factors do provide an explanation of 20th century temperature change.
Observations vs. Models (with external forcing)
Write a report on the following climate aspects for the country assigned to you.
Geographical location and features of the country
National meteorological observational network
Main characteristics of the mean climatic conditions
Dominant modes and sources of climate variability
Performance of current dynamical models in simulating and predicting the climate?
Deficiencies of dynamical models that account for inadequacies in the simulation of climate?
How well the climatic impacts of the 2002/2003 ENSO were predicted for your country
National climate research programs
Involvement in international climate programs
The report should not exceed 6 pages of text and 2 pages of diagrams. The report should have a one paragraph summary, an introduction, main body of the text, conclusions, and references. The deadline for submitting the reports is May/01/2003. You will be expected to give a power point presentation on May/01/2003. The countries will be assigned in a ballot.
Give all references and sources of your information (not part of page limit)
Your search for information may include (i) the CLIVAR WebPages for country summaries [http://www.clivar.org/publications/other_pubs/clivar_conf/clivar_conf.htm#NAT], (ii) publications and websites referenced in the course, and (iii) other sources.
Find 2 examples of previous years power point presentations generated by graduate students, at the course webpage. Note that the specific of the example assignments were different. These examples are meant only to give you some appreciation of the scope and quality of power point presentation that is expected.
(1) Chenjie Huang: 11.20-11.35
Break: 5 minutes
(2) Ryan Boyles: 11.40-11.55
Break: 5 minutes
(3) Katie Robertson: 12.00-12.15
Break: 5 minutes
(4) Shu-Yun Chen: 12.20-12.35
Note: The deadline for submitting the term paper write-up reports is May/01/2003