ClimateSearch

Kalol, Gujarat

India · 134k people · 77 m elevation · Northern Hemisphere

Every month in detail

Thirty-year averages for each calendar month.

Monthly climate normals. Values shown as an em dash are missing from the source data.
MonthJanFebMarAprMayJunJulAugSepOctNovDec
Average high82°F (28°C)88°F (31°C)96°F (36°C)103°F (39°C)107°F (42°C)102°F (39°C)92°F (33°C)89°F (32°C)91°F (33°C)96°F (35°C)92°F (33°C)85°F (30°C)
Average low53°F (12°C)57°F (14°C)66°F (19°C)74°F (23°C)81°F (27°C)82°F (28°C)78°F (26°C)77°F (25°C)76°F (25°C)70°F (21°C)61°F (16°C)55°F (13°C)
Dew point46°F (8°C)46°F (8°C)47°F (8°C)52°F (11°C)63°F (17°C)72°F (22°C)75°F (24°C)74°F (24°C)73°F (23°C)63°F (17°C)54°F (12°C)49°F (9°C)
Rainfall0.1 in (1 mm)0 in (1 mm)0.2 in (6 mm)0 in (1 mm)0.2 in (4 mm)3.7 in (95 mm)17.2 in (438 mm)10 in (255 mm)6 in (152 mm)0.6 in (15 mm)0 in (1 mm)0.1 in (3 mm)
Rainy days00100413106100
Snowfall0 in (0 cm)0 in (0 cm)0 in (0 cm)0 in (0 cm)0 in (0 cm)0 in (0 cm)0 in (0 cm)0 in (0 cm)0 in (0 cm)0 in (0 cm)0 in (0 cm)0 in (0 cm)
Sunshine285 h272 h301 h306 h334 h227 h90 h91 h200 h285 h261 h263 h

Scroll the table sideways for all twelve months.

Projected change, 2031–2050

Model projection, not an observation

How this city’s climate may change, measured against the same models’ own 1995–2014 output. Nothing here affects the match score above.

Change in summer afternoon highs

+1.6°F (+0.9°C)

Models range from +1.3°F (+0.7°C) to +2.2°F (+1.2°C)

Days above 90°F (32°C) a year

181 → 197

About 1.1× as many

Warming by month
  • January: +0.7°F (+0.4°C)
  • February: +1.0°F (+0.5°C)
  • March: +1.0°F (+0.5°C)
  • April: +0.9°F (+0.5°C)
  • May: +1.1°F (+0.6°C)
  • June: +1.9°F (+1.0°C)
  • July: +2.1°F (+1.2°C)
  • August: +0.9°F (+0.5°C)
  • September: +0.3°F (+0.2°C)
  • October: −0.2°F (−0.1°C)
  • November: −0.1°F (−0.1°C)
  • December: +0.5°F (+0.3°C)
Scenario
SSP5-8.5 (high emissions)
Models
4 · CMIP6 HighResMIP, downscaled

This is a high-emissions pathway — the upper end of plausible futures, not a central estimate. Changes are measured by each model against its own past output and then applied to the observed record, which cancels each model’s bias but not the genuine uncertainty about how much warming occurs. Where the models disagree widely, the range above is the honest answer.