UIB
Universitat de les
Illes Balears
Masters in Physics
SUBJECT DESCRIPTION
Details
Subject
Name of subject: Spatial Analysis, Diagnostics and Simulation in Geophysical Fluids
Code: 10108
Type: Optional
Level: Postgraduate
Year: 1, 2
Semester: 2
Language: Catalan / Spanish. English for reading. The subject may be taught in English,
depending on the students.
Teaching staff
Subject leader
Name: Romualdo Romero March
Other staff
Name: Damià Gomis Bosch
Contact: romu.romero@uib.es
Contact: damia.gomis@uib.es
Pre-requisites:
Bachelor’s degree in Science
Number of ECTS credits: 5
Contact hours: 30
Independent study hours: 95
Key terms:
Objective spatial analysis methods: 2D vs. 3D, univariates and multivariates. Optimal
interpolation. Error assessment. Calculation of derived variables. Dynamic and thermodynamic
diagnosis of meteorological situations. Quasi-geostrophic filtered numerical models. Primitive
equation models and parameterisation of physical processes. Sensitivity and factor separation
techniques: Application to the inversion of potential vorticity.
Subject aims
Subject skills and objectives
Specific:
1. Learn basic spatial and temporal discretisation concepts. Learn statistical concepts.
2. Learn various models of spatial analysis: theoretical basis and practical applications
3. Apply knowledge to concrete problems: design a sampling and analysis strategy for real
data.
4. Be ware of dynamic and thermodynamic diagnosis tools for meteorological situations
and their formulation from objective analysis arranged in a 3D network.
5. Historical view of the problem of numerical weather forecasting. Programming
strategies for filtered models. Compression of formulation of the dynamics and physical
processes in present mesoscale forecasting models. Non-hydrostatic model MM5.
6. Practically apply knowledge: programming filtered models and application to ideal
situations; design of control and sensitivity simulations with MM5 for forecast and
diagnose real situations.
7. Adopt strategies to process large volumes of data.
General:
1. Understand and express meanings in physical, mathematical and programming language.
2. Apply theoretical and practical knowledge to problem solving.
3. Apply information technology.
4. Begin research in field.
Content
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Diagrams of spatial and temporal discretisation in physical space and frequency space
Objective spatial analysis methods: 2D vs. 3D methods. Univariate vs. multivariate
methods
Empirical methods: weight functions depending on distance. Concept of frequential
response of analysis
Optimal interpolation method: theoretical basis and mathematical development. Method
potential and limitations
Interpolation method based on orthogonal empirical functions
Calculation of errors associated with interpolation: separation of observational and
sampling errors
Calculation of derived variables: geostrophic speed, geostrophic vorticity, vertical speed
and geopotential / dynamic height tendency
Practical application: analysis of real meteorological / oceanographic data
Dynamic and thermodynamic meteorological diagnosis. Formulation of dynamic quasigeostrophic forcing and characterisation of convective environments. Practical
application to situation of heavy rain and cyclogenesis
Objective and history of numerical weather forecasting. Comparison with numerical
simulation of case studies
Introduction to numerical resolution methods (finite and spectral differences and finite
elements). Linear and nonlinear numerical instabilities
Filtered methods: quasi-geostrophic barotropic, equivalent barotropic and multi-level
baroclinic models; linear and nonlinear outcome models. Programming filtered models
and application to ideal situations
Primitive equation models: basic equations, simplifications by scale, Reynolds average,
parameterisation of physical processes and some examples. Application of mesoscale
MM5 to the simulation of real situations.
Predictability. Strategies for forecasting by groups
Techniques for the separation and inversion of potential vorticity. Practical application
to intense Mediterranean cyclone with MM5 to study influence of contour factors
(orography), physics (evaporation of the sea) and initial conditions (characteristics of
watercourses at altitude)
Methodology
Subject-specific
Learning
skills
method
Spec. 1, 2, 4, 5, 6, Class
Gen. 1, 2, 3
Spec. 3, Gen. 3
Practical class
Spec. 7, 8, Gen. 3 Computer
laboratory
Gen. 3, 4
Presentation
group work
Spec. 1, 2, 3, 4, 5, Tutorial
6, 7, 8
Gen. 1, 2, 3
Spec. 1, 2, 4, 5, 6, Study of theory
8
Gen. 1, 2, 3
Spec. 3, 7, 8,
Study of practice
Gen. 3
Spec. 3, 7,
Practical work
Gen. 3, 4, 4
Type of group
Student hours
Intermediate
18
Intermediate
Intermediate
4
4
Intermediate
2
Small
2
40
20
35
For this subject, 10% of attendance-based activities will be carried out via e-learning.
Learning agreement and assessment criteria and instruments
Assessment criteria:
1. Gaining and/or fulfilling the subject-specific skills
2. Interest shown throughout course
Assessment instruments:
1. Presentation of a piece of practical work
Marking criteria:
1. 100%: Practical work
Is assessment organised by means of a learning agreement? No
Bibliography, resources and appendices
1. Gomis, D.; Análisis Espacial en Fluidos Geofísicos. Notas editadas del curso.
2. Daley, R., 1991: Atmospheric data analysis. Cambridge Univ. Press, 457 pp.
3. Thiébaux, H. J., Pedder, M. A., 1987: Spatial objective analysis. Academic Press,
London, 299 pp.
4. Gomis, D., M. A. Pedder, 2005: Errors in dynamical fields inferred from synoptic
oceanographic cruise data. Part I: the impact of observation errors and the sampling
distribution. J. Mar. Sys., 56/3-4, 317-333.
5. Gomis, D., M. A. Pedder, A. Pascual, 2005: Errors in dynamical fields inferred from
synoptic oceanographic cruise data. Part II: the impact of the lack of synopticity. J. Mar.
Sys., 56/3-4, 334-351
6. Gomis, D, S. Ruiz: DATOBJETIVO: Una herramienta para el análisis espacial objetivo
y diagnóstico de variables oceanográficas.
http://www.imedea.uib.es/oceanography/html/frames/ frame_facilities.htm
7. Davis, C. A. and K. Emanuel, 1991: Potential vorticity diagnostics of cyclogenesis.
Mon. Wea. Rev., 119, 1929-1953.
8. Haltiner, G. J. y R. T. Willians, 1980: Numerical prediction and dynamic meteorology,
John Wiley & Sons.
9. Holton, J. R., 1992: An introduction to dynamic meteorology, 3rd Edition, Academic
Press.
10. Romero, R., 2003: MM5v3 Modeling System. Notes from course.
11. Pielke, R. A., 1984: Mesoscale meteorological modeling, Academic Press.
12. Romero, R., 2001: Sensitivity of a heavy rain producing Western Mediterranean cyclone
to embedded potential vorticity anomalies. Quart. J. R. Meteorol. Soc., 127, 2559-2597.
13. Stein, U. and P. Alpert, 1993: Factor separation in numerical simulations. J. Atmos. Sci.,
50, 2107-2115.
14. Material available on the web and photocopies provided by tutor