Quantifying uncertainties and trends in the climate change trajectory

The characterization of climate change depends on the location and rate of change while its impacts on nature and society also depend on vulnerabilities. This thesis contributes to the quantification of uncertainties, drivers, the spatial variability, and impacts of the climate change trajectory. Results of this work have evolved using a range of data science techniques that combine observations and Earth models aimed at informing adaptation and mitigation policies. In the first chapter, the drivers, timing, and impacts of aridity change over the 21st century are assessed using an ensemble of general circulation models (GCMs) together with population statistics. Results indicate that drier regions are projected to dry earlier, more severely and to a greater extent than humid regions, a result driven by differential changes in precipitation across aridity zones.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2020

Author dc:creator

• Lickley, Megan Jeramaz.

Advisor dc:contributor.advisor

• Susan Solomon.

• Earth, Atmospheric, and Planetary Sciences.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/127143

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/127143