Princeton University Library Catalog

A Comparison of Statistical Downscaling Methods for the Valdivian Region in Chile

Author/​Artist:
Hardy, Nicole [Browse]
Format:
Senior thesis
Language:
English
Advisor(s):
van Handel, Ramon [Browse]
Department:
Princeton University. Department of Operations Research and Financial Engineering [Browse]
Class year:
2017
Restrictions note:
This content is embargoed until July 1, 2019. For more information contact the Mudd Manuscript Library.
Summary note:
This text attempts to address the issue of creating a climate model at a fine resolution by using statistical methods. It will start by using Principal Component Analysis which will lead to the use of statistical downscaling methods such as Bias Correction Methods and Perfect Prognosis Approach. To conclude, a validation step will be taken for each of the models and a comparison of their individual performances will be carried out to show which models are the most effective in this region and why that may be the case.