## Code

```
library(bggjphd)
library(tidyverse)
library(GGally)
library(cowplot)
library(glue)
library(leaflet)
theme_set(theme_bggj())
```

The data used in this research are downloaded from the CEDA Archive:

The raw data contain climate projections for the UK on a 5km grid from 1980 to 2080 for a high emissions scenario, *RCP8.5*, and contain hourly precipitation rates of \(43.920\) squares on a \(180 \times 244\) grid. The projections are calculated for \(1980 - 2000\), \(2020 - 2040\), and \(2060 - 2080\), thus giving \(60 \times 365 \times 24 \times 180 \times 244 \approx 2.3 \cdot 10^{10}\) data points.

The raw data were processed by calculating the yearly maximum over the hourly precipitation rates for each station, thus reducing the number of data points to \(60 \times 180 \times 244 \approx 2.6 \cdot 10^6\).

```
p <- full_data |>
ggplot(aes(max_precip, y = after_stat(density))) +
geom_histogram(bins = 100) +
scale_x_continuous(
limits = c(0, NA),
expand = expansion()
) +
scale_y_continuous(
expand = expansion()
) +
labs(
x = NULL,
y = NULL,
title = "Distribution of station-wise maximum precipitation over the period"
)
ggsave(
plot = p,
filename = "Figures/figure1.png",
width = 8, height = 0.621 * 8, scale = 1.3
)
```