Climatch

Land with a climate like Diamond Harbour

🇮🇳Diamond Harbour, West Bengal, India

The towns with the closest growing climate to Diamond Harbour are Bhātpāra, India (99% match), Basirhat City and Balasore. About 178,000 sq mi of land in 6 countries matches 80% or better, most of it in West Bengal, India, Odisha, India and Chittagong, Bangladesh.The towns with the closest growing climate to Diamond Harbour are Bhātpāra, India (99% match), Basirhat City and Balasore. About 462,000 km² of land in 6 countries matches 80% or better, most of it in West Bengal, India, Odisha, India and Chittagong, Bangladesh.

Your growing climate

Zone 11a · No frost · 0 chill hours · 67 in rainZone 11a · No frost · 0 chill hours · 1,691 mm rain

What grows in Diamond Harbour →

Regions with the most land like yours

  1. 1

    🇮🇳West Bengal, India

    30k sq mi77k km² matching 80% or better

    For example Badūria (99), Hābra (99)

  2. 2

    🇮🇳Odisha, India

    26k sq mi67k km² matching 80% or better

    For example Balasore (99), Jaleshwar (99)

  3. 3

    🇧🇩Chittagong, Bangladesh

    11k sq mi29k km² matching 80% or better

    For example Bibir Hat (94), Hāthazāri (93)

  4. 4

    🇲🇲Sagaing Region, Myanmar

    10k sq mi26k km² matching 80% or better

    For example Tatkon (87), Mawlaik (85)

  5. 5

    🇧🇩Khulna Division, Bangladesh

    9,100 sq mi24k km² matching 80% or better

    For example Sātkhira (98), Jhingergācha (97)

  6. 6

    🇧🇩Dhaka Division, Bangladesh

    7,400 sq mi19k km² matching 80% or better

    For example Tangail (92), Tungipara (92)

  7. 7

    🇮🇳Andhra Pradesh, India

    7,400 sq mi19k km² matching 80% or better

    For example Ichchāpuram (90), Sompeta (88)

  8. 8

    🇲🇲Kachin State, Myanmar

    4,600 sq mi12k km² matching 80% or better

    For example Mogaung (86), Shwegu (84)

  9. 9

    🇹🇭Udon Thani, Thailand

    4,000 sq mi10k km² matching 80% or better

    For example Ban Dung (84), Nam Som (83)

  10. 10

    🇹🇭Nakhon Ratchasima, Thailand

    3,500 sq mi9,000 km² matching 80% or better

    For example Khon Buri (83), Ban Huai Thalaeng (81)

  11. 11

    🇱🇦Savannakhet Province, Laos

    3,400 sq mi8,900 km² matching 80% or better

    For example Ban Xénô (81), Savannakhet (80)

  12. 12

    🇹🇭Bueng Kan, Thailand

    2,000 sq mi5,200 km² matching 80% or better

    For example Seka (84)

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

    🇮🇳BhātpāraWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 65 in rainZone 11a · No frost · 0 chill hours · 1,656 mm rain

    Shares 17 of your 18 great-fit crops

    99%match
  2. 2

    🇮🇳Basirhat CityWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 67 in rainZone 11a · No frost · 0 chill hours · 1,713 mm rain

    Shares 16 of your 18 great-fit crops

    99%match
  3. 3

    🇮🇳BalasoreOdisha, India

    Zone 11b · No frost · 0 chill hours · 67 in rainZone 11b · No frost · 0 chill hours · 1,711 mm rain

    Shares 17 of your 18 great-fit crops

    99%match
  4. 4

    🇮🇳BangaonWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 67 in rainZone 11a · No frost · 0 chill hours · 1,705 mm rain

    Shares 17 of your 18 great-fit crops

    99%match
  5. 5

    🇮🇳JaleshwarOdisha, India

    Zone 11b · No frost · 0 chill hours · 65 in rainZone 11b · No frost · 0 chill hours · 1,646 mm rain

    Shares 17 of your 18 great-fit crops

    99%match
  6. 6

    🇮🇳ShāntipurWest Bengal, India

    Zone 11a · No frost · 1 chill hours · 60 in rainZone 11a · No frost · 1 chill hours · 1,514 mm rain

    Shares 17 of your 18 great-fit crops

    97%match
  7. 7

    🇮🇳BhadrakOdisha, India

    Zone 11b · No frost · 0 chill hours · 69 in rainZone 11b · No frost · 0 chill hours · 1,756 mm rain

    Shares 17 of your 18 great-fit crops

    96%match
  8. 8

    🇮🇳Parādīp GarhOdisha, India

    Zone 11b · No frost · 0 chill hours · 62 in rainZone 11b · No frost · 0 chill hours · 1,586 mm rain

    Shares 16 of your 18 great-fit crops · Also great there: avocado

    96%match
  9. 9

    🇧🇩PābnaRajshahi Division, Bangladesh

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

    Shares 17 of your 18 great-fit crops · Also great there: avocado

    96%match
  10. 10

    🇧🇩JessoreKhulna Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 70 in rainZone 11a · No frost · 0 chill hours · 1,771 mm rain

    Shares 17 of your 18 great-fit crops

    96%match
  11. 11

    🇧🇩RajshahiRajshahi Division, Bangladesh

    Zone 10b · No frost · 3 chill hours · 63 in rainZone 10b · No frost · 3 chill hours · 1,591 mm rain

    Shares 17 of your 18 great-fit crops

    96%match
  12. 12

    🇮🇳JataniOdisha, India

    Zone 11b · No frost · 0 chill hours · 68 in rainZone 11b · No frost · 0 chill hours · 1,721 mm rain

    Shares 16 of your 18 great-fit crops

    95%match
  13. 13

    🇧🇩KhulnaKhulna Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 74 in rainZone 11a · No frost · 0 chill hours · 1,887 mm rain

    Shares 15 of your 18 great-fit crops · Also great there: avocado

    95%match
  14. 14

    🇧🇩Pār NaogaonRajshahi Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 66 in rainZone 11a · No frost · 0 chill hours · 1,676 mm rain

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

    95%match
  15. 15

    🇮🇳BhubaneswarOdisha, India

    Zone 11b · No frost · 0 chill hours · 69 in rainZone 11b · No frost · 0 chill hours · 1,752 mm rain

    Shares 16 of your 18 great-fit crops

    95%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 15 of your 18 great-fit crops · Also great there: fig

    95%match
  17. 17

    🇮🇳BaharampurWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 59 in rainZone 11a · No frost · 0 chill hours · 1,486 mm rain

    Shares 17 of your 18 great-fit crops · Also great there: fig

    94%match
  18. 18

    🇧🇩NawābganjRajshahi Division, Bangladesh

    Zone 10b · No frost · 3 chill hours · 58 in rainZone 10b · No frost · 3 chill hours · 1,461 mm rain

    Shares 17 of your 18 great-fit crops · Also great there: fig

    94%match
  19. 19

    🇮🇳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 18 great-fit crops · Also great there: fig

    93%match
  20. 20

    🇮🇳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 18 great-fit crops · Also great there: fig

    93%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 Diamond Harbour: 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.