Introduction

This report addresses HU14 ANLY 512 — Lab 2: Data Exploration and Visualization (Climate Change). The goal is to explore climate change data, visualize patterns, and evaluate results while explicitly following the maximum marks rubric (CRIT 0.1b, CRIT 0.2b, CRIT 0.3f, INFO 0.1c, ANMS 1.1, ANMS 1.3).

We use a synthetic dataset (1950–2020) representing atmospheric CO2, global temperature anomaly, sea level rise, Arctic sea ice extent, and global CO2 emissions. While synthetic, this mirrors real-world climate trends to demonstrate analytical and visualization techniques.

Data Generation

Sample of synthetic climate dataset (1950–2020)
Year CO2_ppm GlobalTempAnomaly_C SeaLevel_mm ArcticSeaIce_Mkm2 CO2_emissions_Gt
1950 312.74 -0.007 -4.45 10.479 6.022
1951 310.57 0.068 2.81 10.594 6.294
1952 314.13 -0.040 2.06 10.449 7.470
1953 316.37 0.011 20.43 10.377 5.951
1954 317.61 0.118 7.59 10.749 5.423
1955 318.29 0.151 11.17 10.296 6.737

Summary Statistics

Summary statistics for climate indicators
CO2_ppm GlobalTempAnomaly_C SeaLevel_mm ArcticSeaIce_Mkm2 CO2_emissions_Gt
Min. :310.6 Min. :-0.0400 Min. : -4.45 Min. : 8.044 Min. : 5.423
1st Qu.:336.7 1st Qu.: 0.3235 1st Qu.: 51.11 1st Qu.: 8.945 1st Qu.: 8.222
Median :368.8 Median : 0.6380 Median :114.64 Median : 9.473 Median :10.078
Mean :369.6 Mean : 0.6232 Mean :107.82 Mean : 9.456 Mean :10.173
3rd Qu.:401.5 3rd Qu.: 0.9280 3rd Qu.:158.66 3rd Qu.: 9.972 3rd Qu.:12.089
Max. :428.7 Max. : 1.2840 Max. :234.27 Max. :10.749 Max. :14.526

Exploratory Visualizations

CO2 Concentration Over Time

Global Temperature Anomaly Over Time

Sea Level Rise

CO2 vs Temperature

## `geom_smooth()` using formula = 'y ~ x'

Temperature vs Sea Level

## `geom_smooth()` using formula = 'y ~ x'

Correlation Matrix

Histograms

Arctic Sea Ice by Decade

Analysis & Interpretation

CRIT 0.1b (Manage Information): We synthesized multiple variables and evaluated how CO2, temperature, sea level, and ice interact.

CRIT 0.2b (Identify Main Conclusion): Rising CO2 correlates strongly with higher global temperatures, sea level rise, and declining Arctic sea ice. This mirrors real-world climate evidence.

CRIT 0.3f (Review Results): Results are coherent, but further work with real NOAA/NASA datasets and advanced models (time-series regression, attribution studies) is needed.

INFO 0.1c (Reevaluate Collected Info): While synthetic data was sufficient for demonstration, real-world data is required for valid scientific conclusions.

ANMS 1.1 (Problem ↔︎ Analytical Framework): The climate change problem was translated into a quantitative framework using time series, correlations, and statistical visualization.

ANMS 1.3 (Assess Value of Information): The synthetic dataset is valuable for illustration, but the next step is to validate with empirical observations.

Conclusion

The analysis demonstrated:

CO2 concentrations increased steadily from ~310 ppm (1950) to ~410 ppm (2020).

Global temperature anomalies rose accordingly, reflecting anthropogenic climate change.

Sea levels increased significantly, while Arctic sea ice declined.

Main Conclusion: Rising greenhouse gases are tightly linked with warming, sea level rise, and cryosphere loss.