Sail a historical full-rigged ship in real global weather

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This is a simulator of a frigate from about 1800. It has realistic physics, tuned to match historical performance. The UI is based around commands given in period naval language. Rather than use the current weather, it has a full year's weather data (for 1980 - taken from https://psl.noaa.gov/data/gridded/data.ncep.reanalysis2.html ). This allows the weather to change realistically under time acceleration. To learn the basics of handling a square-rigged ship, start the "Harbour" scenario, click on the instructions button at the bottom left, and follow the instructions to try to get out of Portsmouth harbour. To go for a long sail, start the "The World" scenario. Open the map, control+click anywhere on it to move there; control+click on the compass at the bottom left to turn the ship to that heading; then activate travel acceleration at the bottom right. It's a simulator more than a game - think MS flight simulator. There's no sinking, but you can lose sails or spars in high winds. It's windows only. This was released a couple of years ago, but this is an updated version from the end of January. See the devlog ( https://thapen.itch.io/painted-ocean/devlog ) for the changes. You can also find some discussions there on historical sailing performance numbers.

Visit product View on Hacker NewsFeb 24, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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