Climatch

Land with a climate like Chākuliā

🇮🇳Chākuliā, Jharkhand, India

The towns with the closest growing climate to Chākuliā are Durgapur, India (99% match), Āmlāgora and Chāībāsa. About 156,000 sq mi of land in 5 countries matches 80% or better, most of it in Odisha, India, Chhattisgarh, India and West Bengal, India.The towns with the closest growing climate to Chākuliā are Durgapur, India (99% match), Āmlāgora and Chāībāsa. About 405,000 km² of land in 5 countries matches 80% or better, most of it in Odisha, India, Chhattisgarh, India and West Bengal, India.

Your growing climate

Zone 11a · No frost · 0 chill hours · 56 in rainZone 11a · No frost · 0 chill hours · 1,411 mm rain

What grows in Chākuliā →

Regions with the most land like yours

  1. 1

    🇮🇳Odisha, India

    50k sq mi130k km² matching 80% or better

    For example Dera Colliery Township (99), Ghantapada (99)

  2. 2

    🇮🇳Chhattisgarh, India

    25k sq mi65k km² matching 80% or better

    For example Jūnāgarh (96), Kotapārh (88)

  3. 3

    🇮🇳West Bengal, India

    23k sq mi60k km² matching 80% or better

    For example Bānkura (99), Bishnupur (99)

  4. 4

    🇹🇭Udon Thani, Thailand

    3,100 sq mi8,100 km² matching 80% or better

    For example Udon Thani (83), Ban Phan Don (82)

  5. 5

    🇧🇩Rajshahi Division, Bangladesh

    1,900 sq mi4,900 km² matching 80% or better

    For example Nawābganj (86), Shibganj (85)

  6. 6

    🇹🇭Kalasin, Thailand

    1,700 sq mi4,500 km² matching 80% or better

    For example Khao Wong (82), Kuchinarai (81)

  7. 7

    🇹🇭Nong Bua Lamphu, Thailand

    1,100 sq mi3,000 km² matching 80% or better

    For example Na Klang (80), Nong Bua Lamphu (80)

  8. 8

    🇧🇩Khulna Division, Bangladesh

    1,100 sq mi2,800 km² matching 80% or better

    For example Kushtia (80), Bherāmāra (79)

  9. 9

    🇱🇦Savannakhet Province, Laos

    900 sq mi2,200 km² matching 80% or better

    For example Savannakhet (82), Ban Xénô (80)

  10. 10

    🇲🇲Nay Pyi Taw, Myanmar

    300 sq mi700 km² matching 80% or better

    For example Nay Pyi Taw (78), Pyinmana (77)

  11. 11

    🇲🇲Sagaing Region, Myanmar

    300 sq mi700 km² matching 80% or better

    For example Kanbalu (79), Kalemyo (76)

Regions are states and provinces, counting land within 75 km of a town. At most three per country, so the list covers the world.

Closest towns

  1. 1

    🇮🇳DurgapurWest Bengal, India

    Zone 11a · No frost · 1 chill hours · 53 in rainZone 11a · No frost · 1 chill hours · 1,336 mm rain

    Shares 16 of your 16 great-fit crops

    99%match
  2. 2

    🇮🇳ĀmlāgoraWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 54 in rainZone 11a · No frost · 0 chill hours · 1,363 mm rain

    Shares 16 of your 16 great-fit crops

    99%match
  3. 3

    🇮🇳ChāībāsaJharkhand, India

    Zone 11a · No frost · 1 chill hours · 55 in rainZone 11a · No frost · 1 chill hours · 1,395 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: wheat

    99%match
  4. 4

    🇮🇳ChittaranjanWest Bengal, India

    Zone 10b · No frost · 4 chill hours · 51 in rainZone 10b · No frost · 4 chill hours · 1,294 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: wheat

    99%match
  5. 5

    🇮🇳KultiWest Bengal, India

    Zone 11a · No frost · 2 chill hours · 49 in rainZone 11a · No frost · 2 chill hours · 1,244 mm rain

    Shares 16 of your 16 great-fit crops

    99%match
  6. 6

    🇮🇳PuruliyaWest Bengal, India

    Zone 10b · No frost · 3 chill hours · 53 in rainZone 10b · No frost · 3 chill hours · 1,345 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: wheat

    99%match
  7. 7

    🇮🇳AngulOdisha, India

    Zone 11a · No frost · 0 chill hours · 58 in rainZone 11a · No frost · 0 chill hours · 1,480 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: wheat

    99%match
  8. 8

    🇮🇳BolpurWest Bengal, India

    Zone 11a · No frost · 2 chill hours · 56 in rainZone 11a · No frost · 2 chill hours · 1,425 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: wheat

    99%match
  9. 9

    🇮🇳BarddhamānWest Bengal, India

    Zone 11a · No frost · 1 chill hours · 57 in rainZone 11a · No frost · 1 chill hours · 1,438 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: wheat

    98%match
  10. 10

    🇮🇳KāmākhyānagarOdisha, India

    Zone 11b · No frost · 0 chill hours · 61 in rainZone 11b · No frost · 0 chill hours · 1,545 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: wheat, canola (rapeseed)

    98%match
  11. 11

    🇮🇳BūnduJharkhand, India

    Zone 10b · No frost · 4 chill hours · 52 in rainZone 10b · No frost · 4 chill hours · 1,310 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: wheat

    97%match
  12. 12

    🇮🇳DumkaJharkhand, India

    Zone 10b · No frost · 8 chill hours · 55 in rainZone 10b · No frost · 8 chill hours · 1,387 mm rain

    Shares 16 of your 16 great-fit crops

    97%match
  13. 13

    🇮🇳KaranjiāOdisha, India

    Zone 11a · No frost · 2 chill hours · 64 in rainZone 11a · No frost · 2 chill hours · 1,628 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: wheat, barley, canola (rapeseed)

    97%match
  14. 14

    🇮🇳DeogarhOdisha, India

    Zone 11a · No frost · 0 chill hours · 64 in rainZone 11a · No frost · 0 chill hours · 1,636 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: wheat

    97%match
  15. 15

    🇮🇳KātoyaWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 58 in rainZone 11a · No frost · 0 chill hours · 1,462 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: wheat

    96%match
  16. 16

    🇮🇳ArāmbāghWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 51 in rainZone 11a · No frost · 0 chill hours · 1,306 mm rain

    Shares 16 of your 16 great-fit crops

    96%match
  17. 17

    🇮🇳Rampur HatWest Bengal, India

    Zone 10b · No frost · 3 chill hours · 58 in rainZone 10b · No frost · 3 chill hours · 1,479 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: wheat, barley

    96%match
  18. 18

    🇮🇳BhawānipatnaOdisha, India

    Zone 11a · No frost · 0 chill hours · 63 in rainZone 11a · No frost · 0 chill hours · 1,597 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: wheat

    96%match
  19. 19

    🇮🇳BalāngīrOdisha, India

    Zone 11a · No frost · 0 chill hours · 59 in rainZone 11a · No frost · 0 chill hours · 1,509 mm rain

    Shares 15 of your 16 great-fit crops

    96%match
  20. 20

    🇮🇳DhanbadJharkhand, India

    Zone 10b · No frost · 3 chill hours · 49 in rainZone 10b · No frost · 3 chill hours · 1,239 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: wheat

    95%match

Any town over 15,000 people, skipping those within 75 km of you. ↻ = seasons flipped across the equator.

How matching works

We compare all twelve months of average highs and lows, rain, humidity and sunshine, the same way as Climatch's places-like search, but weighted for growing: winter lows count most, since frost, chill and hardiness decide which perennials survive, then summer highs and rain. Humidity counts least.

Scores show how unusual a match this close is: 80 or better is closer than all but about 2% of random pairs of places. Across the equator seasons are lined up (↻), so a southern farm's January is compared with a northern July. Climate is only part of it: check soil, water and day length (it matters for photoperiod crops) before buying land.

Looking for land?

We're building detailed reports on land like Chākuliā: frost risk year by year, water, and how each match's climate is shifting by 2050.

We'll only use your email for the report and related updates.

Climate data: TerraClimate 1991–2020 monthly averages (Abatzoglou, J.T. et al., 2018, Scientific Data 5:170191). Humidity is derived from TerraClimate vapor pressure; “sunshine” is solar radiation.

Places: GeoNames (CC BY 4.0). Map: © OpenStreetMap contributors, tiles by OpenFreeMap.

Grower tools: crop ranges from FAO ECOCROP and university extension guides (cited per crop). Daily weather, frost dates and chill are estimated from the monthly averages; chill portions use the Dynamic Model (Fishman, Erez & Couvillon, 1987), hardiness zones follow the USDA definition.