Pacific Dataviz Challenge 2026

Pacific at Risk

Climate Change Is Reshaping Lives Faster Than Economies Can Adapt

A climate-economic vulnerability analysis across 22 Pacific Island Nations — tracking how rising temperatures, sea levels, and disaster losses are reshaping lives and livelihoods across the Pacific.

22
Pacific Nations Analyzed
7
Official Datasets
959M
Total Disaster Loss (USD)
0.72°C
Avg Temp Anomaly (2024)
Scroll
Key Findings

What the data reveals

Across 7 official Pacific Data Hub datasets spanning 55+ years, four critical patterns emerge that define the region's climate-economic vulnerability.

01
The Pacific has warmed by +0.72°C relative to the 1991–2020 climatological baseline in 2024, with acceleration visible after 2015 — a trend consistent with global climate projections.
02
Fiji alone accounts for 64% of total disaster economic loss across all Pacific nations — driven largely by Cyclone Winston in 2016.
03
Average crop yield has declined -2.36% from early years to recent decades, coinciding with a regional rainfall deficit of -0.83 mm below historical averages.
Page 1 of 4 · The Climate Signal

How bad is the warming?

Greenhouse gas emissions, surface temperature anomalies, and sea level rise across Pacific Island Nations since 1990 — all pointing in the same direction.

Country
From
1990
To
2025
Avg GHG per Capita (2024)
7.25 t
Tonnes CO₂ equivalent · Regional average
Avg Temp Anomaly (1990+)
0.32°C
°C deviation from historical baseline
Avg Sea Level Anomaly
0.10 m
Metres · Latest available year (2023)
Mean Surface Temperature Anomaly over Time
°C deviation from baseline · All countries averaged · 1990–2025
Sea Level Anomaly by Year
Metres · Regional Pacific average · 1993–2023
GHG Emissions per Capita by Country · Latest Year (2024)
Tonnes CO₂ equivalent · Palau is a significant outlier at 86.7t due to aviation, tourism, imported fuels, very small denominator (population)
Page 2 of 4 · The Economic Cost

What is climate change costing?

Direct disaster economic losses and persons affected across Pacific nations — quantifying climate risk the way insurers and risk analysts do.

Country
From
2005
To
2023
Total Disaster Economic Loss
959M
USD · All Pacific nations · 2007–2020
Total Persons Affected
2.59M
Cumulative · All disasters · 2005–2023
Avg Loss per Person Affected
370
USD per person affected by disasters
Direct Disaster Economic Loss by Country
USD · All available years · Fiji dominates due to Cyclone Winston 2016
Persons Affected by Disasters over Time
All Pacific countries · 2005–2023
▲ Cyclone Winston 2016 — 633,906 persons affected in Fiji
GHG Emissions vs Disaster Economic Loss by Country
Each bubble = one country · Countries with higher emissions often also report larger economic losses, although this relationship is influenced by economic size, infrastructure, and exposure · Palau & New Caledonia excluded as extreme outliers
Page 3 of 4 · Food & Livelihoods

What is climate disrupting on the ground?

Crop yields are declining and rainfall patterns are shifting across the Pacific — threatening the agricultural livelihoods that millions of islanders depend on.

Country
From
1990
To
2024
Avg Crop Yield (kg/ha)
75.08
Regional average · 1990–2024
Crop Yield Change
-2.36%
Early years vs recent decades comparison
Avg Rainfall Anomaly (1990+)
-0.83 mm
mm deviation · Negative = drier than historical avg
Crop Yield Trend (1990–2024)
kg per hectare · Regional average
Rainfall Anomaly over Time (Regional Avg)
mm deviation · Negative = drier than historical average
Crop Yield by Country · Latest Year
kg/ha · Sorted most vulnerable first · Lower yield = higher food insecurity
Page 4 of 4 · Vulnerability Index

Who is most at risk?

A Custom Climate-Economic Vulnerability Index built from four normalized indicators — GHG emissions, disaster economic loss, persons affected, and crop yield decline — weighted to reflect analytical priority.

Risk Category
Min Score
0
Nations at High Risk
1
Vulnerability Index ≥ 70 · Fiji
Avg Vulnerability Score (0–100)
27.33
Regional average across 21 nations
Avg Disaster Loss
25M
USD per country · All available years
Custom Climate-Economic Vulnerability Index by Country
Composite score 0–100 · Higher = more vulnerable
Risk Distribution across Pacific Nations
Countries by risk category
Vulnerability Score Components by Country
All component scores normalized 0–100 · Weighted composite index
Methodology

How this was built

All data sourced from the Pacific Data Hub's official .Stat Explorer. Seven datasets processed and combined to produce this analysis.

📊
Data Sources
7 official Pacific Data Hub datasets covering GHG emissions, temperature anomalies, sea level, rainfall, crop yield, disaster loss, persons affected, and renewable energy.
🔧
Tools Used
Power BI for interactive dashboard. Python for data cleaning and vulnerability index calculation. HTML/CSS/ECharts for this narrative website.
📐
Vulnerability Index
Min-max normalized composite of 4 indicators: GHG (20%), Disaster Loss (35%), Persons Affected (25%), Crop Yield vulnerability (20%).
🌏
Coverage
22 Pacific Island Countries and Territories. Year ranges vary by dataset: 1850–2025 (temperature), 1961–2024 (crop yield), 2005–2023 (disaster data).
Research Disclaimer
This analysis is based on official datasets from the Pacific Data Hub and presents historical patterns and statistical associations across Pacific Island nations. The custom Climate-Economic Vulnerability Index was developed specifically for this project using min–max normalization and analyst-defined indicator weights. It is intended as an analytical tool for comparison and visualization rather than an official or standardized measure of climate vulnerability. Observed relationships should not be interpreted as evidence of direct causation, as socioeconomic outcomes are influenced by multiple environmental, economic, and policy factors.
Weight
GHG Score: 20%
Higher per-capita emissions = higher score
Weight
Disaster Loss: 35%
Economic loss dominates — highest analytical weight
Weight
Persons Affected: 25% + Crop Score: 20%
Human impact and food security complete the index