Climatch

Land with a climate like Kanchanpur

🇮🇳Kanchanpur, Tripura, India

The towns with the closest growing climate to Kanchanpur are Habiganj, Bangladesh (99% match), Agartala and Silchar. About 232,000 sq mi of land in 8 countries matches 80% or better, most of it in Assam, India, West Bengal, India and Kachin State, Myanmar.The towns with the closest growing climate to Kanchanpur are Habiganj, Bangladesh (99% match), Agartala and Silchar. About 601,000 km² of land in 8 countries matches 80% or better, most of it in Assam, India, West Bengal, India and Kachin State, Myanmar.

Your growing climate

Zone 11a · No frost · 0 chill hours · 80 in rainZone 11a · No frost · 0 chill hours · 2,026 mm rain

What grows in Kanchanpur →

Regions with the most land like yours

  1. 1

    🇮🇳Assam, India

    28k sq mi74k km² matching 80% or better

    For example Silchar (99), Hailākāndi (99)

  2. 2

    🇮🇳West Bengal, India

    19k sq mi48k km² matching 80% or better

    For example Bangaon (94), Gobārdānga (94)

  3. 3

    🇲🇲Kachin State, Myanmar

    18k sq mi48k km² matching 80% or better

    For example Myitkyina (96), Mogaung (96)

  4. 4

    🇲🇲Sagaing Region, Myanmar

    15k sq mi39k km² matching 80% or better

    For example Tamu (97), Tatkon (96)

  5. 5

    🇧🇩Chittagong, Bangladesh

    13k sq mi33k km² matching 80% or better

    For example Shāhbāzpur Town (99), Brāhmanbāria (99)

  6. 6

    🇧🇩Khulna Division, Bangladesh

    8,800 sq mi23k km² matching 80% or better

    For example Kushtia (96), Kālīganj (96)

  7. 7

    🇧🇩Dhaka Division, Bangladesh

    7,400 sq mi19k km² matching 80% or better

    For example Bhairab Bāzār (99), Nagar Naluākot (99)

  8. 8

    🇮🇳Mizoram, India

    6,300 sq mi16k km² matching 80% or better

    For example Lunglei (83), Lawngtlai (80)

  9. 9

    🇱🇦Bokeo, Laos

    4,500 sq mi12k km² matching 80% or better

    For example Ban Khoan (84), Ban Houakhoua (83)

  10. 10

    🇱🇦Vientiane, Laos

    3,700 sq mi9,500 km² matching 80% or better

    For example Vang Vieng (86)

  11. 11

    🇹🇭Nan, Thailand

    3,400 sq mi8,800 km² matching 80% or better

    For example Nan (76)

  12. 12

    🇹🇭Loei, Thailand

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

    For example Loei (81), Wang Saphung (79)

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

    🇧🇩HabiganjSylhet Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 95 in rainZone 11a · No frost · 0 chill hours · 2,402 mm rain

    Shares 21 of your 21 great-fit crops

    99%match
  2. 2

    🇮🇳AgartalaTripura, India

    Zone 11a · No frost · 1 chill hours · 82 in rainZone 11a · No frost · 1 chill hours · 2,071 mm rain

    Shares 19 of your 21 great-fit crops

    99%match
  3. 3

    🇮🇳SilcharAssam, India

    Zone 11a · No frost · 0 chill hours · 92 in rainZone 11a · No frost · 0 chill hours · 2,336 mm rain

    Shares 19 of your 21 great-fit crops

    99%match
  4. 4

    🇧🇩ComillaChittagong, Bangladesh

    Zone 11a · No frost · 0 chill hours · 86 in rainZone 11a · No frost · 0 chill hours · 2,186 mm rain

    Shares 21 of your 21 great-fit crops

    99%match
  5. 5

    🇧🇩GazipurDhaka Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 84 in rainZone 11a · No frost · 0 chill hours · 2,145 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  6. 6

    🇧🇩NāgarpurDhaka Division, Bangladesh

    Zone 11a · No frost · 2 chill hours · 73 in rainZone 11a · No frost · 2 chill hours · 1,855 mm rain

    Shares 18 of your 21 great-fit crops

    99%match
  7. 7

    🇧🇩KhagrachhariChittagong, Bangladesh

    Zone 11a · No frost · 0 chill hours · 89 in rainZone 11a · No frost · 0 chill hours · 2,250 mm rain

    Shares 18 of your 21 great-fit crops

    98%match
  8. 8

    🇧🇩TangailDhaka Division, Bangladesh

    Zone 11a · No frost · 2 chill hours · 73 in rainZone 11a · No frost · 2 chill hours · 1,847 mm rain

    Shares 18 of your 21 great-fit crops

    98%match
  9. 9

    🇮🇳GuwahatiAssam, India

    Zone 11a · No frost · 0 chill hours · 68 in rainZone 11a · No frost · 0 chill hours · 1,739 mm rain

    Shares 21 of your 21 great-fit crops

    98%match
  10. 10

    🇧🇩FarīdpurDhaka Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 78 in rainZone 11a · No frost · 0 chill hours · 1,988 mm rain

    Shares 18 of your 21 great-fit crops

    98%match
  11. 11

    🇧🇩NetrakonaMymensingh Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 100 in rainZone 11a · No frost · 0 chill hours · 2,537 mm rain

    Shares 21 of your 21 great-fit crops

    98%match
  12. 12

    🇮🇳BarpetaAssam, India

    Zone 11a · No frost · 0 chill hours · 88 in rainZone 11a · No frost · 0 chill hours · 2,246 mm rain

    Shares 21 of your 21 great-fit crops

    98%match
  13. 13

    🇧🇩PābnaRajshahi Division, Bangladesh

    Zone 10b · No frost · 2 chill hours · 67 in rainZone 10b · No frost · 2 chill hours · 1,700 mm rain

    Shares 18 of your 21 great-fit crops

    97%match
  14. 14

    🇲🇲TamuSagaing Region, Myanmar

    Zone 11a · No frost · 1 chill hours · 91 in rainZone 11a · No frost · 1 chill hours · 2,322 mm rain

    Shares 18 of your 21 great-fit crops

    97%match
  15. 15

    🇧🇩MymensinghMymensingh Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 89 in rainZone 11a · No frost · 0 chill hours · 2,252 mm rain

    Shares 19 of your 21 great-fit crops

    97%match
  16. 16

    🇧🇩SunāmganjSylhet Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 127 in rainZone 11a · No frost · 0 chill hours · 3,225 mm rain

    Shares 18 of your 21 great-fit crops · Also great there: potato

    97%match
  17. 17

    🇮🇳NalbāriAssam, India

    Zone 11a · No frost · 0 chill hours · 88 in rainZone 11a · No frost · 0 chill hours · 2,234 mm rain

    Shares 21 of your 21 great-fit crops · Also great there: potato

    97%match
  18. 18

    🇮🇳MangaldaiAssam, India

    Zone 11a · No frost · 0 chill hours · 67 in rainZone 11a · No frost · 0 chill hours · 1,696 mm rain

    Shares 21 of your 21 great-fit crops

    97%match
  19. 19

    🇮🇳DimāpurNagaland, India

    Zone 10b · No frost · 11 chill hours · 62 in rainZone 10b · No frost · 11 chill hours · 1,581 mm rain

    Shares 19 of your 21 great-fit crops

    97%match
  20. 20

    🇧🇩NarayanganjDhaka Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 86 in rainZone 11a · No frost · 0 chill hours · 2,196 mm rain

    Shares 19 of your 21 great-fit crops

    97%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 Kanchanpur: 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.