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Back in 2020, after having spent the best of the past two decades in bioinformatics (first in academia, then in industry), tinkering with machine learning and data science to cure cancer™, I decided it was time to move onto the next challenge: solving climate change™.

Ideation phase took a while, and wasn’t as smooth as planned, due to some, err, unforeseen circumstances. Things went a bit like:

  1. First half of 2020: getting asked about 5 times a week to join in on some new medtech/pharmatech venture “planning for the next pandemic”. 😑
  2. Summer 2020: “hmm, I wonder if that whole climate thing might not be the next big thing we need to worry about. Perhaps this might just be the right intersection of personally care about, topical to my skillset, and might get paid for. Dare I say ikigai!?”
  3. Late 2020: exploring the space and spending endless hours on video calls with everyone I know somehow involved in climate and climate tech. Realising that:
    • Consumer advocacy apps are great, but not my jam.
    • Carbon counting is a bit of a scam <cough>greenwashing</cough>, and by 2023, there will be more carbon counting apps/websites/services than humans on earth.
    • Mitigation (carbon capture and other cool hardware moonshots) is great, but my physics/mechanical engineering days are a little too far in my past…
    • Everyone is so busy putting little Carbon Neutral by 2050 stickers on their website and recycling coffee pods at the office, that literally no one has a real clue how climate change is impacting us now. And very clearly it is.
  4. New Year’s Eve 2020: settling on the decidedly unsexy but intriguing challenge of modelling the economic impacts of climate change. On business (a girl’s gotta eat). The real fun begins: which impacts (weather disasters? geopolitical strifes? taxes? regulation?), which businesses (mustard seed growers? semiconductor manufacturers? logistics companies?), which regions (South East Asia? Europe? North America?)… Deciding to keep it simple and do it all.

And here I am, 18 months later, working with a team of brilliant people, building some very cool models and data products centred around climate, risk, and economics.

My personal outlook on the climate crisis is considerably more bearish than the IPCC consensus (itself a lot darker than the mainstream view). In the immortal words of my old friend John Maynard: in the long run, we’re all fucked. In the fairly short run: also.

But one of my few bright hopeful spots in that bleak landscape, is the potential for existing technologies to assist us with resilience: remote sensing data that can predict in near-real-time when and where crops will fail, roads will flood, or factories will shut down, and help us find the best way to minimise these impacts. We will need that level of scale and precision, to measure and adequately respond to the global crisis currently unfolding.

As I often do when having to name a new project, I lazily dug into Japanese for this one.

Kikō (気候), the word for climate, was a little too generic for trademark purposes, but Tenkō (天候) a concept halfway between climate and weather (天気, tenki) had both a nice ring to it, and some auspicious homonyms (転向: change of direction…).

As it turns out, the choice was fitting: Tenko (the company) is not really about climate or climate change (this vague and distant threat that people keep pushing to some distant horizon in 20 or 30 years). Rather, it is about climate-related impacts (and particularly the weather, but not only).

More generally, Tenko is about using data (of which there is a lot) to measure risks (of which there are a lot).