Climate Change Trends Visualization using ggplot2

Introduction

This project demonstrates the use of the ggplot2 package in R for visualizing climate change data such as temperature anomalies, CO₂ levels, and sea level rise from 1980 to 2020.

Package Overview

ggplot2 is a data visualization package for the statistical programming language R. It is based on the grammar of graphics and allows users to layer components to build complex plots easily.

Data Description

The dataset contains: - Temperature Anomaly (°C): Difference from average global temperature - CO2 Level (ppm): Carbon dioxide concentration - Sea Level Rise (mm): Relative increase in sea levels

Demonstration

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.4.3

library(dplyr)

## Warning: package 'dplyr' was built under R version 4.4.3

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(tidyr)

## Warning: package 'tidyr' was built under R version 4.4.3

# Simulated Climate Data
climate_df <- data.frame(
  Year = 1980:2020,
  Temp_Anomaly = c(0.12, 0.14, 0.18, 0.2, 0.22, 0.25, 0.27, 0.28, 0.31, 0.33,
                   0.35, 0.38, 0.4, 0.41, 0.43, 0.45, 0.47, 0.5, 0.52, 0.55,
                   0.57, 0.59, 0.6, 0.62, 0.65, 0.67, 0.68, 0.7, 0.72, 0.74,
                   0.76, 0.78, 0.8, 0.81, 0.83, 0.85, 0.87, 0.9, 0.91, 0.93, 0.95),
  CO2_Level = c(338, 340, 342, 344, 346, 349, 351, 353, 355, 357,
                360, 362, 364, 367, 369, 371, 373, 375, 377, 380,
                382, 384, 386, 389, 391, 393, 395, 398, 400, 403,
                405, 407, 409, 412, 414, 417, 419, 421, 423, 425, 428),
  Sea_Level = c(0, 1, 2, 3, 5, 6, 7, 9, 10, 12,
                14, 15, 17, 18, 20, 22, 23, 25, 26, 28,
                30, 32, 33, 35, 36, 38, 40, 41, 43, 45,
                47, 48, 50, 51, 53, 55, 56, 58, 59, 61, 63)
)

# Convert to long format for plotting
climate_long <- pivot_longer(climate_df, cols = -Year, names_to = "Metric", values_to = "Value")

# Plot
ggplot(climate_long, aes(x = Year, y = Value, color = Metric)) +
  geom_line(size = 1) +
  geom_point(size = 1.5) +
  facet_wrap(~ Metric, scales = "free_y") +
  labs(
    title = "Climate Change Trends (1980–2020)",
    subtitle = "Global Temperature Anomaly, CO2 Concentration, and Sea Level Rise",
    x = "Year",
    y = "Value",
    caption = "Simulated data for STAT 484 project"
  ) +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 16, face = "bold"),
    strip.text = element_text(size = 12, face = "bold"),
    legend.position = "none"
  )

## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

Conclusion