Recent southwest monsoon advancement across Uttar Pradesh has introduced increased cloud cover, humidity, and scattered rainfall over Lucknow, moderating daytime heating and anchoring trader-implied odds near 34–36 °C. The monsoon trough’s position and embedded cyclonic circulations determine local precipitation timing and intensity; stronger convective activity or an active phase reduces solar insolation and caps maximum temperatures, while any temporary break favors slightly higher readings. Official IMD guidance and ensemble model runs indicate typical July monsoon conditions with highs around the 33–35 °C range, creating tight clustering among the leading outcomes as traders weigh the latest forecast updates against historical climatology for the Indo-Gangetic plain.
Resumo experimental gerado por IA com dados do Polymarket. Isto não é aconselhamento de trading e não tem qualquer papel na resolução deste mercado. · AtualizadoTemperatura mais alta em Lucknow em 14 de julho?
36°C 30%
35°C 30%
34°C 16%
33°C 8%
31°C or below
<1%
32°C
3%
33°C
8%
34°C
17%
35°C
30%
36°C
30%
37°C
7%
38°C
5%
39°C
1%
40°C
1%
41°C or higher
<1%
36°C 30%
35°C 30%
34°C 16%
33°C 8%
31°C or below
<1%
32°C
3%
33°C
8%
34°C
17%
35°C
30%
36°C
30%
37°C
7%
38°C
5%
39°C
1%
40°C
1%
41°C or higher
<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 Aberto: Jul 12, 2026, 1:03 AM ET
Fonte de resolução
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.
Fonte de resolução
https://www.wunderground.com/history/daily/in/lucknow/VILKResolver
0x69c47De9D...Recent southwest monsoon advancement across Uttar Pradesh has introduced increased cloud cover, humidity, and scattered rainfall over Lucknow, moderating daytime heating and anchoring trader-implied odds near 34–36 °C. The monsoon trough’s position and embedded cyclonic circulations determine local precipitation timing and intensity; stronger convective activity or an active phase reduces solar insolation and caps maximum temperatures, while any temporary break favors slightly higher readings. Official IMD guidance and ensemble model runs indicate typical July monsoon conditions with highs around the 33–35 °C range, creating tight clustering among the leading outcomes as traders weigh the latest forecast updates against historical climatology for the Indo-Gangetic plain.
Resumo experimental gerado por IA com dados do Polymarket. Isto não é aconselhamento de trading e não tem qualquer papel na resolução deste mercado. · Atualizado
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