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Welcome to clarkwx.com! I've been meaning to build out a proper personal site for a while now, and here we are.

## What you'll find here

This site is a central hub for my professional work and personal interests:

- **Climate & Health Research** — My work at Duke's Global Health Institute, where I build data infrastructure and analytic tools for climate-health research across four regional observatories.
- **Projects** — From weather dashboards to data harmonization pipelines, I'll showcase the tools and systems I'm building.
- **Plants** — Yes, I also run a plant business. More on that at [plantsbyj.com](https://plantsbyj.com).
- **Blog** — Thoughts on climate data, Python/R workflows, interesting findings, and whatever else comes to mind.

## Why "ClarkWx"?

"Wx" is the standard abbreviation for "weather" in meteorology. It felt like a natural fit — short, memorable, and a nod to my background in atmospheric science.

Stay tuned for more posts. If you want to connect, head over to the [contact page](/contact) or find me on LinkedIn.
4:T6a8,
One of the biggest challenges in climate-health research isn't the science itself — it's the data infrastructure.

## The problem

Climate data and health data live in completely different worlds. Climate datasets are gridded, temporal, and massive (think terabytes of reanalysis products). Health data is tabular, often messy, and collected at wildly different spatial and temporal scales.

When a researcher wants to ask "how did last month's heat wave affect hospital admissions in Moshi, Tanzania?" they need to:

1. Find the right climate dataset for that region
2. Extract and process the relevant variables
3. Align it temporally and spatially with health records
4. Deal with missing data, different time zones, and unit conversions

Each of those steps can take weeks if you're doing it from scratch.

## What we're building

At CGHI, we're building systematic infrastructure to make this easier. That means:

- **Data inventories** — Cataloging what climate and health data exists across our observatory network
- **Standardized pipelines** — Reproducible workflows for extracting and harmonizing data
- **Accessible tools** — Making climate data approachable for health researchers who may never have worked with a NetCDF file

The goal is to reduce the barrier from "weeks of data wrangling" to "run a function and get a clean dataset."

## Why it matters

Climate change is already impacting health outcomes globally. But if researchers can't efficiently access and combine the data they need, we're leaving critical questions unanswered. The infrastructure work isn't glamorous, but it's foundational.

More to come on the specific tools and packages we're developing. Stay tuned.
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