# Designing an Interactive Visual Analytics System for
## 5 Interactive Precipitation Data Analysis System
### Multi-Site Analysis Interface
#### 5.2.2 Annual PCA Analysis  
Annual PCA analysis visualization supports understanding the patterns on multiple weather stations. Figure 11 shows the analyzed PCA projections of the annual precipitation  
Figure 10: Precipitation trend analysis for IAD and DCA weather stations (1997–2023). (**A**) Visualization with precipitation events (colored circles) and fitted trend lines. (**B**) Trend lines without precipitation events for enhanced trend visibility, resulting in a rescaled y-axis from \(0\sim 15.0\) to \(0\sim 1.2\). Figure 9: Multi-site analysis interface for comparing precipitation data between two weather stations in Virginia, U.S. The interface integrates multiple control panels and virtualizations. (**A,B**) station selection panels with geographic context maps, (**C**) interactive IETD parameter controls for precise precipitation event definition through date range and threshold adjustments, (**D**) comprehensive tabular representation of IETD precipitation events, (**E**) synchronized line graphs visualizing temporal precipitation intensity at each station, and (**F**) quantitative visualizations of annual and monthly precipitation trends. data in IDA and DCA. To perform this analysis, several comprehensive precipitation features are extracted for each station and year. To find annual and seasonal characteristics, the data are evaluated annually and seasonally. The annual analysis measures annual average precipitation volumes, durations, and their standard deviations. Additionally, the total count of distinct precipitation events, cumulative annual precipitation volume, maximum single event volume, and mean precipitation intensity (volume/duration) are also determined. For the seasonal analysis, the data are analyzed based on seasonal information. For each season, eight features are extracted as the average volume of precipitation events, variability of precipitation volumes, the average duration of precipitation events, variability in event durations, average rate of precipitation (volume per hour), largest single precipitation volume observed, total number of precipitation events, and cumulative precipitation volume. Figure 11 shows PCA visualizations of precipitation data from two weather stations spanning from 1997 to 2023. Each circle represents annual precipitation data with corresponding year labels positioned nearby and connected to it. To address visual clutter caused by overlapping labels, an adaptive label placement algorithm is applied to evaluate eight directional positions around each circle to find optimal placement, increasing distance when necessary (Figure 11A). Due to space limitations, all weather stations are represented with abbreviated notation combining state initials and system-assigned station ID numbers. Detailed information about each station appears when highlighted on the station legend located at the bottom (as shown in Figure 11D). The visualization supports a basic user interaction technique, highlighting, to help users understand the represented information more clearly. Figure 11B highlights the visual glyphs of the year 2022 in the visualization. Detailed information of each visual glyph is displayed when highlighted (Figure 11C). To help users conduct comparative analysis on yearly patterns, a colored year panel allows users to highlight glyphs only for a selected year. To help users understand the overall annual trends of each station, highlighting only each station's data is also supported. Figure 11D shows all precipitation data related to the DCA airport are highlighted with  
Figure 11: Multi-station precipitation pattern analysis through PCA visualization. (**A**) Global view of annual precipitation patterns across two weather stations and years, revealing regional climate clustering. (**B**) Temporal filtered view highlighting precipitation data specifically on 2022, demonstrating annual variation between stations. (**C**) Detailed glyph interpretation guide showing how dimensional attributes map to visual elements.