The Decorrelation Length and Time Scale - Diagnostic Tools to Visualize Spatial and Temporal Variability in Geophysical Fields

Atmospheric reanalyses and model data are becoming more commonly used. However, most reanalyses and global climate models have resolutions of ~50 km or lower --- scales too coarse to capture many topographic and coastal effects within various geophysical fields such as precipitation and wind speed. Although attempts have been made to assess the impact of horizontal model resolution, such as downscaling and power spectrum methods, it is still unclear how this impacts the representation of the spatial variability. This thesis presents the Decorrelation Length Scale (DCLS and Decorrelation Time Scale (DCTS), novel techniques to characterize and visualize spatial and temporal variability in geophysical fields at a grid-point level, that is able to investigate this impact. The main strength of the DCLS/DCTS provide insight into both the relative variability and geographical imprint of the source of variability. A set of reanalysis, hindcasts, and analysis datasets with a common lineage and with horizontal resolutions ranging from ~125 km to ~9 km were used in three case studies to validate and explore the utility of this new technique. The first case study validated the DCLS's utility as a diagnostic by showing that there are changes in the spatial variability of the precipitation over the Eastern Pacific that are not reflected in its mean structure. The second case study applied the same analysis technique as the DCLS to visualize temporal variability as well, showing that even resolutions of ~30-km do not capture the wind field's variability, especially in coastal and mountainous regions and also support the historic choice of wind farm development in the UK, namely, the southern/south-western tip of England as well as off the southern shore. Since the DCLS is not subject to uniform model bias, the third case study used this technique to study the spatial variability of the Congo Basin's hydrological cycle. This region has been historically understudied due to a lack of validation data and an interesting candidate for the DCLS analysis. DCLS results revealed that the main source of spatial variability in the P-E field over the Basin was uniformly from the precipitation field and that the spatial scales of the variability are less than 10 km.

Department dc:contributor.department

Physics

Year dc:date.issued

2021

Author dc:creator

• De Benedetti, Marc

Advisor dc:contributor.advisor

• Moore, G.W.K.

Statement dc:rights

• Attribution-NoDerivatives 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by-nd/4.0/

Handle dc:identifier.uri

http://hdl.handle.net/1807/106251

OAI identifier oai:identifier

oai:utoronto.scholaris.ca:1807/106251