About this paper

Appears in:
Pages: 4855-4860
Publication year: 2018
ISBN: 978-84-09-02709-5
ISSN: 2340-1117
doi: 10.21125/edulearn.2018.1204

Conference name: 10th International Conference on Education and New Learning Technologies
Dates: 2-4 July, 2018
Location: Palma, Spain

AN INTEGRATED STATISTICAL MODELING FRAMEWORK OF MARITIME DATA IN A CLIMATE CHANGE CONTEXT: APPLICATION TO MSC. TEACHING

Climate change has been the focus of research of several different disciplines over the past few decades. In recent years there has been an increase in the study of maritime climate variables highly motivated by the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC, 2013) which forecasts an increase in the significant wave height and the frequency and intensity of extreme weather events.

In maritime engineering, the traditional design practice is based on the statistical analysis of isolated climate variables such as the significant wave height without taking into account the dependance between different forcing agents nor their time variation. Nevertheless, most of the climate variables have the same origin and should not be treated as independent in a climate change scenario. Therefore, there is an increasing demand of data and climate services that provide projections at different time and spatial scales as well as the analysis of its impact using more advanced statistical techniques that take into account the complex interaction and prediction of maritime climate variables.

This work presents the teaching tools developed in the module Foundations and applied methods in Environmental Hydraulics of the Master's Program of Hydraulic Engineering of the University of Granada (Spain). The complexity of these studies make them a particularly difficult topic for students to learn in a compelling way. Teachers are required not only to have a strong theoretical background but also to be capable to develop and use software tools especific for data analysis. The methodology and tools are designed to give the students a stastistical modeling framework of maritime data simulation from the assimilation of mathematical and statistical concepts, their implementation in a programming language, up to its application to coastal structures design.

Using past and future climate projections of wave and wind data, we propose an integrated modeling approach involving marginal and multivariate statistical analysis, vector autorregresive model, numerical modeling and downscaling techniques for maritime climate simulations and uncertainty analysis taking into account different scenarios of climate change. A series of programming tools have been developed and are used as means for teaching complex features in a hands-on and interactive way, proving to be an efficient way for students to learn and simulate different climate change scenarios and their implications on coastal systems.

We have received an overall positive feedback from students although we have concluded that it can be quite challenging at the beginning of the course, mostly for students who lack programming basis and skills. To overcome this, we are planning on restructuring the module in shorter and simpler lessons i.e. interactive notebooks and user-friendly interfaces that combine theoretical and practical exercises. We have also found that this course has acted as a bridge to bring cutting-edge research methodologies closer to students.

References:
[1] IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovern- mental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp.
@InProceedings{LIRALOARCA2018ANI,
author = {Lira Loarca, A. and Cobos Budia, M. and Maga{\~n}a Redondo, P. and Millares Valenzuela, A. and Baquerizo Azofra, A.},
title = {AN INTEGRATED STATISTICAL MODELING FRAMEWORK OF MARITIME DATA IN A CLIMATE CHANGE CONTEXT: APPLICATION TO MSC. TEACHING},
series = {10th International Conference on Education and New Learning Technologies},
booktitle = {EDULEARN18 Proceedings},
isbn = {978-84-09-02709-5},
issn = {2340-1117},
doi = {10.21125/edulearn.2018.1204},
url = {http://dx.doi.org/10.21125/edulearn.2018.1204},
publisher = {IATED},
location = {Palma, Spain},
month = {2-4 July, 2018},
year = {2018},
pages = {4855-4860}}
TY - CONF
AU - A. Lira Loarca AU - M. Cobos Budia AU - P. Magaña Redondo AU - A. Millares Valenzuela AU - A. Baquerizo Azofra
TI - AN INTEGRATED STATISTICAL MODELING FRAMEWORK OF MARITIME DATA IN A CLIMATE CHANGE CONTEXT: APPLICATION TO MSC. TEACHING
SN - 978-84-09-02709-5/2340-1117
DO - 10.21125/edulearn.2018.1204
PY - 2018
Y1 - 2-4 July, 2018
CI - Palma, Spain
JO - 10th International Conference on Education and New Learning Technologies
JA - EDULEARN18 Proceedings
SP - 4855
EP - 4860
ER -
A. Lira Loarca, M. Cobos Budia, P. Magaña Redondo, A. Millares Valenzuela, A. Baquerizo Azofra (2018) AN INTEGRATED STATISTICAL MODELING FRAMEWORK OF MARITIME DATA IN A CLIMATE CHANGE CONTEXT: APPLICATION TO MSC. TEACHING, EDULEARN18 Proceedings, pp. 4855-4860.
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