YoVDO

Pragmatically Ambitious Multiscale Global Temperature Reconstruction - Finn Lindgren, Edinburgh

Offered By: Alan Turing Institute via YouTube

Tags

Uncertainty Quantification Courses Data Analysis Courses Linear Approximation Courses Climate Modeling Courses Ensemble Methods Courses

Course Description

Overview

Explore a pragmatically ambitious approach to multiscale global temperature reconstruction in this 41-minute conference talk by Finn Lindgren from Edinburgh. Delve into the complexities of uncertainty quantification and Gaussian Process emulation as applied to climate modeling. Learn about various data sources, challenges with data scarcity, and the intricacies of heat equation models and satellite observations. Examine model variability across different scales, non-Gaussian modeling techniques, and bias correction methods. Discover how daily temperature ranges are incorporated and various approximation techniques, including linear approximations and local approximate solves. Understand the application of Takahashi recursion, multiscale complements, and block update methods in improving model accuracy. Analyze error sources and the use of ensemble outputs to enhance the robustness of global temperature reconstructions.

Syllabus

Intro
Pragmatically ambitious
Data sources
Lack of data
Models
Heat equation
Satellite observations
Model variability
Model scales
Hand tuning
Non Gaussian model
Bias Correction
Daily Ranges
Approximations
Linear approximations
Local approximate solves
Takahashi recursion
Multiscale complements
Block update method
Error
Ensemble output


Taught by

Alan Turing Institute

Related Courses

Social Network Analysis
University of Michigan via Coursera
Intro to Algorithms
Udacity
Data Analysis
Johns Hopkins University via Coursera
Computing for Data Analysis
Johns Hopkins University via Coursera
Health in Numbers: Quantitative Methods in Clinical & Public Health Research
Harvard University via edX