Monte Carlo Simulation Figures for Extreme Precipitation Trends Study

This dataset contains the complete set of figure panels originally presented as Appendix A in the dissertation titled “Multi-Scalar Attribution and Spatiotemporal Deep Learning for Nonstationary Urban Flood Risk Assessment in U.S. Inland Cities.” It provides comprehensive extreme precipitation trend analyses for all investigated HUC12 watersheds across the study cities. Each image file displays six subplots: (a) raw daily precipitation, (b) isolated extreme precipitation events based on the n-largest method, (c) annual frequency of extreme events, (d) annual maximum magnitude, and (e, f) corresponding Monte Carlo simulation histograms for frequency and magnitude trend significance.

Files are organized by city and HUC12 watershed ID (e.g., CityName_HUC12ID.png). Detailed methodological descriptions and interpretations of these subplots are provided in Sections 2.4 and 2.5 of the dissertation. Users may reuse these figures for research and teaching with appropriate citation of this dataset and the associated dissertation.