Windhoek, Namibia
Quantitative climate
intelligence from the ground up.
All models are wrong, but some are useful.
— George Box
I build statistical pipelines that turn climate hazard data into infrastructure investment risk, built specifically for African markets where existing models quietly fail. My tools are open, my methods are auditable, and the problem I am solving is real.
About
I am a quantitative analyst from Windhoek, Namibia, working at the edge of climate science and infrastructure finance. I hold a BSc in Applied Mathematics and Statistics and a BSc Honours in Applied Statistics, both from NUST.
My Honours thesis modelled extreme wind speed events across Namibia using statistical methods that most climate risk practitioners in Africa have never applied to local data, and that gap is exactly what I am spending my career closing.
One published piece of work at a time.
Work & projects
Namibia Station Monitor
A living data-quality audit of every Namibian weather station in the NOAA global archive. Recomputes a Data Quality Score (DQS v1.0) for all 56 stations on the 1st of each month via automated pipeline. Confirms Lüderitz present in ISD metadata since 1949, returns HTTP 404 in GHCND. Citable dataset: Igulu (2026), DOI 10.5281/zenodo.21229782.
The Namibian station audit: what the global climate archive actually contains
I pulled and quality-scored every Namibian record in NOAA's global daily archive. Three of ten stations reach the present day. Ondangwa is missing the 1990s. Lüderitz is not in the archive at all. The audit behind the shadow map and the article below.
Modelling Wind Speed Extremes Using Extreme Value Theory: A Case Study for Namibia
Applied Peaks-Over-Threshold and Generalized Pareto Distribution methods to model extreme wind speed events across Namibian meteorological stations. Produced return-level estimates with uncertainty bounds directly applicable to renewable energy infrastructure siting and insurance pricing. Accepted for publication in Wind (MDPI).
Namibian Climate Risk Sandbox
An open, reproducible pipeline from raw NOAA station records and CMIP6 projections to boardroom-ready physical risk assessments for a real Windhoek asset, the Goreangab Water Reclamation Plant. Station audit and CMIP6 bias-correction phases complete; extreme value and financial layers in build on a published schedule.
SACRF - Sparse-Adaptive Climate Risk Framework
Built on peer-reviewed extreme value research (Wind/MDPI, 2026). A Bayesian engine for honest climate-risk estimation in data-scarce African markets, where prior precision adapts to station-level data quality so that short records and long records are treated with appropriate uncertainty. Financial translation layer and pre-registered calibration experiment in design.
Automated data pipelines for urban development research
Engineered end-to-end data pipelines connecting KoboToolbox field collection to Power BI reporting via Power Query API, eliminating manual handling across multi-site development programmes. Built spatial maps in QGIS and interactive dashboards for programme impact monitoring.
Data visualisations
Namibia Station Monitor - live DQS feed
56 Namibian weather stations scored monthly by Data Quality Score. Filter by usability tier or GHCND status. Lüderitz confirmed absent from the global daily archive despite ISD registration since 1949.
Skills
Statistical & mathematical
Data & engineering
Climate & finance
Currently learning
Writing
Why Namibia's weather stations are a development finance problem
Twenty long-record stations, 825,000 km², a shadow map covering 64% of the country. What that means for infrastructure lending in southern Africa.
Currently
- Building The Namibian Climate Risk Sandbox, an open pipeline from raw station data to climate-adjusted NPV and the SACRF working paper behind it
- Education BSc Applied Mathematics and Statistics — NUST, May 2025 · BSc Honours Applied Statistics — NUST, May 2026
- Learning Python for climate data pipelines · Yale Financial Markets (Coursera) · Wharton Finance & Accounting · Climate Change and Sustainable Investing SDA (Bocconi / Coursera)
- Reading Coles (2001) — An Introduction to Statistical Modeling of Extreme Values · Knaflic (2015) — Storytelling with Data
Contact
I am always happy to talk about climate risk in Africa, what I am building, where I am trying to go, or anything in between. If you have a project or role that matches the work above, reach out directly.