Visualizing Climate Change & Resilience
Using data to showcase the importance of tackling climate change. https://challenges.adb.org/en/challenges/dataviz4climate/pages/timeline-process-and-selection-criteria?lang=en

Shuai Hao

Chinese Cities are Suffering from More Extreme Hot Days

Yuqi Liao

Lucy Lu

Sifan Liu

Robin Wang

Winner: Team Data Whale 🐳 -What Happens when El Niño Comes to Vietnam?

Zach Bogart

Periscopic

Runner-Up, Team Periscopic - Building Resilience to Climate Change in South Asia

Mujahid Ali Kayani

AlterFuel

CO₂ Emissions From Burning Of Diesel: A Disasterous Journey from 1965 to 2021

Chay Thawaranont

 Asia’s Regenerative Energy Future

ccdiaz

Mae Acacio

Allysa Marie Federio

Iskolar ng Bayan Para sa Kalikasan

Aquaculture As A Climate-Resilient Option For Sustainable Global Food Production

Cham Mamador

Flowers and Tracks

Ehmil

Pantry Circle

Pantry Circle for the ADB "Visualizing Climate Change & Resilience Challenge"

SUGIMOTO Tatsuo

Are typhoons increasing?

Ryan Joshua Liwag

Finalist, Team Viz - Philippines - Plastic Waste and its Sachet Economy

Tej Charan

vertify

Observable

ADB Visualizing Climate Change & Resilience Challenge Submissions

You may have tried this, but I wonder if connecting the points in temporal order with lines (i.e., a connected scatterplot) here would make this more readable than the error bands.

Robert Kosara

For this one, our analysis doesn't focus much on the time domain but instead with the relationship between annual sea surface temperature and ratio of marine production. To reduce the clutter, we also added a checkbox for this visual so that the user can choose the countries they want to look at. 

For the readability, would it be advisable to instead remove the error bands, keeping just the trend lines?

Very nice! This is much clearer than the previous chart IMHO.

I would add a little preview of the data you're about to show here, just to give people an idea of what to expect. The introduction is fairly general, perhaps you can also pick out a few numbers from what you're showing below as examples to make things a bit more concrete.

TotalASEAN.csv

AverageTempYear.csv

PivotedData@1.csv

JoinedCaptureTemp@1.csv

JoinedTempRatio.csv

AverageTempMonth.csv

homemade-aquaponics.jpeg

Simplified-sketch-of-VAC-farming-system-in-Vietnam-Duong-et-al-2013.png

Influence-of-water-temperature-on-fish-lives.png

IUU.jpeg

CountryEEZLocation@5.csv

CountryProductionPopulation@4.csv

Diagrams-of-the-Bycatch-Reduction-Devices-used-in-the-study-Devices-that-were-used.png