Climate data nerds, check out Climate TRACE

Bridging academic knowledge and approach with industry has its challenges. The post below outlines a commonly held view from climate scientists. I agree with most critiques, even though there are other very relevant aspects to the industry that are non-existent in academia: The "use case" drives the conversation. Are the data used to write a disclosure report? is it increase the boards' awareness about physical risk? or is it for designing a bridge? (the latter never occurred to me in 5 years of clients' engagement, the vast majority is the 2nd case). Some investors seek to develop "initial IP" to then sell it to big financial players, who also have teams who can evaluate the code and developing it. In this case, code transparency (upon selling) is more important than "accuracy". They aim at beginning to turn the wheel and define the language in which physical risk is spoken. Because currently, it is largely still not priced in. Nearly nobody in industry wants to talk about downscaling methods, uncertainties, model parametrizations and cloud physics. Embedding physical climate risk into decision making, reporting, and increased awareness require usefulness of the data output for the clients' and investors' use cases. Actually, many in the industry would place more value on a report by a reputable consulting firm than on the IPCC. Personally, I opt for merging both, but that is an ongoing mission, rather than an existing reality.

Climate data has its limits, but not all private sector data providers want to talk about that. How should investors navigate the complex and unregulated climate data landscape? How can one discern which data vendors have real chops, and which are overselling their best guesses? For our second edition of Let's Get Geophysical, I’ve collected my criticisms + a wishlist for a rigorous, decision-ready climate services industry. 

"Frankly, it is hard to accept property level risk scores or projections at face value. The presentation of a precise number (i.e. 7 Flood Factor) at the address level obscures underlying uncertainties and context. At what spatial scale is the underlying climate information reliable?" good write up!

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The "climate data industrial complex" is booming. How much of it is built on hype instead of substance? From governments to first-time home buyers, people are making big-dollar climate decisions without knowing what climate models can actually predict—and what they can't. Check out our second edition of Let's Get Geophysical, where Jane Smyth dives into the importance of transparency and public data in using climate data for decision-making.

"It is essential that climate data providers do not overstate certainty, as these data support decision making and could drive maladaptation. Fathom, which specializes in flood risk, sets a positive example here: they provide 1-10 certainty ranks for each component of their model. This disclosure and context makes data more usable, not less. While the resolution limits of climate science are frustrating, I believe it is wiser to have a sober view of the uncertainty than to make decisions with a false sense of confidence." Jane Smyth - Man Group All models are wrong, but some are useful. Feel free to share your own experiences if you have them! https://lnkd.in/eP6wWRhB

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Here is what AI says about the US Department of Energy "Critical Review of Impacts of Greenhouse Gas Emissions on the U.S. Climate" The "Critical Review of Impacts of Greenhouse Gas Emissions on the U.S. Climate," published by the Department of Energy, is highly controversial and has faced significant criticism for allegedly misrepresenting climate science. While the report, authored by five scientists known for their contrarian views, claims that the effects of greenhouse gas emissions on the US climate are less severe than commonly believed, many scientists and organizations argue that it selectively presents data and ignores the established scientific consensus on climate change. Here's a breakdown of the issues: Controversial Authors: The report was drafted by a group of five scientists with a history of questioning mainstream climate science, handpicked by the Energy Secretary. Cherry-Picked Data: Critics accuse the report of highlighting uncertainties and selectively using data to downplay the impacts of climate change. Rejection of Consensus: The report challenges the established scientific consensus on the severity of climate change and the impact of greenhouse gas emissions. Economic Impact Claims: It claims that the economic impact of CO2-induced warming is less severe than commonly believed and that aggressive mitigation strategies could be more harmful than beneficial. External Review: While the report underwent an internal review, it's expected to undergo a more formal external peer review. "Red Team" Approach: The report is described as a "red team" assessment, meaning it aims to challenge existing assumptions and arguments rather than present a comprehensive overview, according to Roger Pielke Jr.. Many scientists and organizations, like The Union of Concerned Scientists, argue that the report contains "climate denial tropes," misrepresents data, and disregards the established scientific consensus on climate change.