Polymarket weather markets
Polymarket's daily weather series price tomorrow's high or low temperature for cities around the world. Each day is a chain of density buckets, one or two degrees wide with open ended tails, and the set of bucket prices forms an implied probability distribution over the day's temperature.
Marketlens collects every bucket of every chain, so the full distribution reconstructs at any point in time. If you want to compare market implied forecasts against actual weather models, this is the raw material.
This page lists the weather series in the catalog. For what the weather archive holds and how to pull it, see Polymarket weather market data.
Data as of 2026-11-02
All weather series
Highest temperature in Hong Kong
daily · 1,254 markets · $17.1M
Highest temperature in London
daily · 1,288 markets · $13.2M
Highest temperature in Seoul (Incheon)
daily · 1,300 markets · $12.5M
Highest temperature in Shanghai
daily · 1,243 markets · $10.8M
Highest temperature in NYC
daily · 1,282 markets · $10.4M
Highest temperature in Paris
daily · 1,293 markets · $10.3M
Highest temperature in Munich
daily · 1,279 markets · $8.7M
Highest temperature in Wellington
daily · 1,287 markets · $8.3M
Highest temperature in Tokyo
daily · 1,251 markets · $8.2M
Measles cases in U.S
monthly · 13 markets · $7.9M
Highest temperature in Beijing
daily · 1,243 markets · $7.9M
Highest temperature in Shenzhen
daily · 1,243 markets · $7.6M
Highest temperature in Madrid
daily · 1,254 markets · $7.6M
Highest temperature in Miami
daily · 1,281 markets · $6.9M
Highest temperature in Los Angeles
daily · 1,243 markets · $6.8M
Query this category
from marketlens import MarketLens
client = MarketLens()
for market in client.markets.list(category="Weather", status="resolved", take=50):
print(market.question, market.winning_outcome)
# the order book of any market, at any moment of its life
[market] = client.markets.list(
series_id="hong-kong-daily-weather", status="resolved", take=1,
)
book = client.orderbook.get(market.id, at=market.close_time)
print(book.best_bid, book.best_ask, book.midpoint)Common questions
How many Polymarket weather markets does Marketlens have data for?
The archive covers 106,027 weather markets across 108 recurring series, of which 103,264 have resolved. Coverage runs from July 7, 2026 through now.
What data is available for each weather market?
Most markets have full L2 order book history (snapshots plus every price change with millisecond timestamps), trades, and candles; the longest dated books carry full depth snapshots at regular intervals alongside their trades and candles. Every market stores its final resolution outcome. Data is served through the REST API and Python SDK, with bulk Parquet exports for offline work.
How much do these markets trade?
Combined traded volume across the category is $333.6M. Per series volumes are listed in the table on this page.
Can I backtest strategies on weather markets?
Yes. Pass any series slug from this page to client.backtest() in the Python SDK. Execution mode replays the order books tick by tick and fills simulated orders against real depth with queue priority, latency, and fee modelling; Alpha mode replays one bar per market for slower signals over long windows.
Other categories: crypto, sports, esports, or the full catalog.
Try it
Pull weather books in one call
The free tier includes 2M data rows and every market open in the last 7 days, no card required.
$ pip install marketlens