Recent forecasts from the India Meteorological Department and models like those referenced by NDTV and BBC indicate light rain and partly cloudy conditions for Lucknow on July 13, driven by active southwest monsoon flow across the Gangetic plains. This setup typically suppresses maximum temperatures through increased cloud cover, reduced solar insolation, and evaporative cooling, aligning with the July climatological average high near 33–35 °C. Trader probabilities cluster on 36–37 °C because short-term model runs show modest variability in rainfall timing and intensity that could allow brief clearing and slight warming, while probabilities drop sharply above 38 °C given the low likelihood of prolonged dry spells this early in peak monsoon season.
Resumen experimental generado por IA con datos de Polymarket. Esto no es asesoramiento de trading y no influye en cómo se resuelve este mercado. · Actualizado¿La temperatura más alta en Lucknow el 13 de julio?
36°C 30%
37°C 28%
38°C 18%
35°C 16%
32°C o menos
1%
33°C
<1%
34°C
11%
35°C
16%
36°C
30%
37°C
28%
38°C
18%
39°C
6%
40°C
<1%
41°C
<1%
42°C o más
<1%
36°C 30%
37°C 28%
38°C 18%
35°C 16%
32°C o menos
1%
33°C
<1%
34°C
11%
35°C
16%
36°C
30%
37°C
28%
38°C
18%
39°C
6%
40°C
<1%
41°C
<1%
42°C o más
<1%
The resolution source for this market will be information from Wunderground, specifically the highest temperature recorded for all times on this day for the Chaudhary Charan Singh Intl Airport Station, available here: https://www.wunderground.com/history/daily/in/lucknow/VILK.
To toggle between Fahrenheit and Celsius, click the gear icon next to the search bar and switch the Temperature setting between °F and °C.
This market can not resolve until the first data point for the following date has been published on the resolution source.
The resolution source for this market measures temperatures to whole degrees Celsius (eg, 9°C). Thus, this is the level of precision that will be used when resolving the market.
Revisions to temperatures recorded within this market's timeframe will be considered until the first datapoint for the following date has been published, after which any alterations will not be considered.
Mercado abierto: Jul 11, 2026, 1:02 AM ET
Fuente de resolución
https://www.wunderground.com/history/daily/in/lucknow/VILKResolver
0x69c47De9D...The resolution source for this market will be information from Wunderground, specifically the highest temperature recorded for all times on this day for the Chaudhary Charan Singh Intl Airport Station, available here: https://www.wunderground.com/history/daily/in/lucknow/VILK.
To toggle between Fahrenheit and Celsius, click the gear icon next to the search bar and switch the Temperature setting between °F and °C.
This market can not resolve until the first data point for the following date has been published on the resolution source.
The resolution source for this market measures temperatures to whole degrees Celsius (eg, 9°C). Thus, this is the level of precision that will be used when resolving the market.
Revisions to temperatures recorded within this market's timeframe will be considered until the first datapoint for the following date has been published, after which any alterations will not be considered.
Fuente de resolución
https://www.wunderground.com/history/daily/in/lucknow/VILKResolver
0x69c47De9D...Recent forecasts from the India Meteorological Department and models like those referenced by NDTV and BBC indicate light rain and partly cloudy conditions for Lucknow on July 13, driven by active southwest monsoon flow across the Gangetic plains. This setup typically suppresses maximum temperatures through increased cloud cover, reduced solar insolation, and evaporative cooling, aligning with the July climatological average high near 33–35 °C. Trader probabilities cluster on 36–37 °C because short-term model runs show modest variability in rainfall timing and intensity that could allow brief clearing and slight warming, while probabilities drop sharply above 38 °C given the low likelihood of prolonged dry spells this early in peak monsoon season.
Resumen experimental generado por IA con datos de Polymarket. Esto no es asesoramiento de trading y no influye en cómo se resuelve este mercado. · Actualizado
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