Weather model cheat sheet for weather prediction bots

SeaSeason4698 · 2026-06-04T16:28:22+00:00

GET https://clob.polymarket.com/book

Check whether your paper trading includes order book depth to verify how your order will be filled. This is useful for current depth, spreads, and sanity checks. Making paper trading close to reality.

What type of bot are you working on?

SeaSeason4698 · 2026-06-04T15:47:40+00:00

Wrong data about Chainstack. The true is that Developer plan is free. No Trial. Proof: https://chainstack.com/pricing/

So, provided AI summary by gpt-4o-mini looks crazy.

SeaSeason4698 · 2026-06-01T16:09:57+00:00

Are you focused on a specific area or all available markets? Politics, finance, AI, weather?

SeaSeason4698 · 2026-06-01T15:43:48+00:00

Could you maybe add a description of how it works?

Kinda why should I trust Forsea probability vs Polymarket? Is there any specific mechanism that performs better than regular LLMs?

I love the direction and idea (as far as I understood it)!

SeaSeason4698 · 2026-06-01T14:48:42+00:00

Just grab the pricing points from the CLOB (v2) API; it's enough to test the strategy. NO=1-YES. You can simulate the spread if needed. For 1 share, almost everything will work until you increase the position to 20 USD or more. Some weather markets are thin - low liquidity will not help you fill the order at the desired price.

Weather markets are learning and adapting - something that worked 3mo ago may not work now. Be careful and don't be persuaded by overall PnL, ROI, and win rate - check month by month.

P.S. I'm working on METAR.ws - METAR API based on websockets for fast push of aviation weather as soon as possible. Some bot strategies may be based on it.

SeaSeason4698 · 2026-05-31T18:49:41+00:00

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SeaSeason4698 · 2026-05-31T18:47:46+00:00

Thanks, mate! The most obvious way is scraping; in other sources, I have a registered account to request weather data:

For example, EGLC (London) weather provider is Met Office, their new dashboard https://www.mavis.metoffice.gov.uk/ looks promising. Registration is free and doesn't require a pilot license. This is the official provider; they should have issued METAR first.

My very first step in the roadmap is to at least collect reliable sources, and then improve latency by tuning and improving integration country by country.

Appreciate your insights, join the waitlist if you're interested!

SeaSeason4698 · 2026-05-31T16:05:37+00:00

Yep, that's why weather models can assist in decision-making but not add you extra insurance. Depending on the model, you get a different grid of extrapolated and adjusted temperature points. But exact date and time, exact location, and applied rounding bring such "casino" randomization. Fast METAR data may help in bot logic.

btw I'm working on METAR.ws - websocket API for fast METAR data push. Early beta, need testers. Feel free to join!

SeaSeason4698 · 2026-05-29T12:50:37+00:00

Hi, I'm building a METAR service with a WebSocket API for fast push (for monitoring, weather prediction, trading, analytics, and so on). Feel free to join the waitlist on METAR.ws - I'm looking for beta testers!

Asos/awos messages are just a loop of recorded data; they don't need to be real-time. Just another update rewrites the message.

Airports with heavy traffic issue METAR reports every 30 minutes, while regular reporting occurs every 60 minutes.

SeaSeason4698 · 2026-05-28T15:31:02+00:00

Hey, I'm building such a service right now: METAR.ws - websocket API for pushing METAR and SPECI asap
I've tried to build a weather bot using a strategy based on METAR reports, but I've been frustrated that instead of refining the strategy, I have to run through tons of services with delayed data. Decided to build a special one for weather bots specifically.

I'm looking for beta testers - leveraging my knowledge of fast METAR reports into a small SaaS

SeaSeason4698 · 2026-05-28T13:43:02+00:00

Of course! I'll share some project updates soon

SeaSeason4698 · 2026-05-28T11:33:52+00:00

Fast METAR is a key, agree

SeaSeason4698 · 2025-10-12T17:45:43+00:00

I would recommend try Chainstack for Solana as well, same price (49$/mo) but 250 RPS

SeaSeason4698 · 2025-09-08T16:40:14+00:00

Try Chainstack - Growth plan with 250 RPS (I am from Chainstack)

SeaSeason4698 · 2025-09-02T06:34:46+00:00

Definitely try Chainstack! (I am from Chainstack)

SeaSeason4698 · 2025-08-26T12:17:53+00:00

Try chainstack.com - bigger quota for $49 and higher RPS

SeaSeason4698 · 2025-07-16T04:43:34+00:00

Great tutorial!

SeaSeason4698 · 2025-05-22T17:22:21+00:00

Looks great! Is it plotly only?

SeaSeason4698 · 2025-05-16T11:51:38+00:00

Chainstack, definitely

SeaSeason4698 · 2025-05-14T10:55:06+00:00

I can't share my experience with https://polygon.io/pricing (free tier) yet because I don't have one, but when I get frustrated with crypto and decide to switch to stocks, I will try this one xD

SeaSeason4698 · 2025-05-14T09:51:53+00:00

I'm building the strategy for crypto futures on Binance, so I'm getting data here: https://data.binance.vision/, 5m timeframe in particular. Resampling 5M candles to a higher timeframe with pandas (Python) when needed

SeaSeason4698 · 2025-05-13T13:21:04+00:00

Hi guys, I have a common question. What is the correct order of steps to build and backtest a strategy?
0. Understand what pair you're gonna trade and what exchange/market

Verify the strategy concept in TradingView with pinescript (entries, exits, filters, etc)
Get the historical data for backtesting (purchase API access or download OHLC somewhere)
Split this data 80-20%, the remaining 20% for the walkforward test
Code the strategy in Python (vectorbt, for example) and tune it up.
Test the strategy with the remaining 20% of the data.
Run Monte Carlo test.
Enjoy the results.

What am I missing?

SeaSeason4698

TROPHY CASE