Climatch

Land with a climate like Kātoya

🇮🇳Kātoya, West Bengal, India

The towns with the closest growing climate to Kātoya are Arāmbāgh, India (99% match), Dumka and Sonāmukhi. About 220,000 sq mi of land in 6 countries matches 80% or better, most of it in Odisha, India, West Bengal, India and Bihar, India.The towns with the closest growing climate to Kātoya are Arāmbāgh, India (99% match), Dumka and Sonāmukhi. About 569,000 km² of land in 6 countries matches 80% or better, most of it in Odisha, India, West Bengal, India and Bihar, India.

Your growing climate

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

What grows in Kātoya →

Regions with the most land like yours

  1. 1

    🇮🇳Odisha, India

    44k sq mi115k km² matching 80% or better

    For example Baripāda (97), Jaleshwar (96)

  2. 2

    🇮🇳West Bengal, India

    33k sq mi85k km² matching 80% or better

    For example Arāmbāgh (99), Nalhāti (99)

  3. 3

    🇮🇳Bihar, India

    23k sq mi61k km² matching 80% or better

    For example Bānka (96), Purnia (95)

  4. 4

    🇲🇲Sagaing Region, Myanmar

    13k sq mi33k km² matching 80% or better

    For example Kalemyo (88), Mawlaik (86)

  5. 5

    🇧🇩Rajshahi Division, Bangladesh

    7,300 sq mi19k km² matching 80% or better

    For example Nawābganj (99), Shibganj (99)

  6. 6

    🇧🇩Chittagong, Bangladesh

    5,500 sq mi14k km² matching 80% or better

    For example Khagrachhari (88), Manikchari (86)

  7. 7

    🇹🇭Udon Thani, Thailand

    5,400 sq mi14k km² matching 80% or better

    For example Ban Nong Wua So (85), Nam Som (85)

  8. 8

    🇧🇩Khulna Division, Bangladesh

    5,200 sq mi14k km² matching 80% or better

    For example Bherāmāra (96), Kushtia (96)

  9. 9

    🇲🇲Kachin State, Myanmar

    5,200 sq mi13k km² matching 80% or better

    For example Bhamo (88), Shwegu (87)

  10. 10

    🇹🇭Kalasin, Thailand

    4,900 sq mi13k km² matching 80% or better

    For example Kuchinarai (84), Khao Wong (84)

  11. 11

    🇱🇦Savannakhet Province, Laos

    3,200 sq mi8,200 km² matching 80% or better

    For example Savannakhet (85), Ban Xénô (84)

  12. 12

    🇹🇭Sakon Nakhon, Thailand

    2,900 sq mi7,400 km² matching 80% or better

    For example Sawang Daen Din (86), Warichaphum (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

    🇮🇳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 17 great-fit crops

    99%match
  2. 2

    🇮🇳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 17 great-fit crops

    99%match
  3. 3

    🇮🇳SonāmukhiWest Bengal, India

    Zone 11a · No frost · 2 chill hours · 52 in rainZone 11a · No frost · 2 chill hours · 1,328 mm rain

    Shares 16 of your 17 great-fit crops

    99%match
  4. 4

    🇧🇩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 17 great-fit crops · Also great there: barley

    99%match
  5. 5

    🇧🇩RajshahiRajshahi Division, Bangladesh

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

    Shares 16 of your 17 great-fit crops · Also great there: barley

    99%match
  6. 6

    🇮🇳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 17 great-fit crops

    99%match
  7. 7

    🇮🇳MaldaWest Bengal, India

    Zone 10b · No frost · 3 chill hours · 56 in rainZone 10b · No frost · 3 chill hours · 1,411 mm rain

    Shares 16 of your 17 great-fit crops

    99%match
  8. 8

    🇮🇳KharagpurWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 59 in rainZone 11a · No frost · 0 chill hours · 1,495 mm rain

    Shares 16 of your 17 great-fit crops

    98%match
  9. 9

    🇮🇳GoddaJharkhand, India

    Zone 10b · Frost 1 years in 10 · 16 chill hours · 51 in rainZone 10b · Frost 1 years in 10 · 16 chill hours · 1,297 mm rain

    Shares 17 of your 17 great-fit crops

    98%match
  10. 10

    🇧🇩MohammadpurRajshahi Division, Bangladesh

    Zone 10b · No frost · 7 chill hours · 62 in rainZone 10b · No frost · 7 chill hours · 1,566 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: barley, avocado

    98%match
  11. 11

    🇮🇳BānkuraWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 49 in rainZone 11a · No frost · 0 chill hours · 1,245 mm rain

    Shares 16 of your 17 great-fit crops

    97%match
  12. 12

    🇮🇳UluberiyaWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 64 in rainZone 11a · No frost · 0 chill hours · 1,623 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: barley

    97%match
  13. 13

    🇮🇳BaripādaOdisha, India

    Zone 11a · No frost · 0 chill hours · 65 in rainZone 11a · No frost · 0 chill hours · 1,662 mm rain

    Shares 16 of your 17 great-fit crops

    97%match
  14. 14

    🇮🇳KolkataWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 68 in rainZone 11a · No frost · 0 chill hours · 1,736 mm rain

    Shares 16 of your 17 great-fit crops

    96%match
  15. 15

    🇮🇳HābraWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 68 in rainZone 11a · No frost · 0 chill hours · 1,730 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: barley, canola (rapeseed)

    96%match
  16. 16

    🇮🇳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 17 great-fit crops

    95%match
  17. 17

    🇮🇳EgraWest Bengal, India

    Zone 11b · No frost · 0 chill hours · 63 in rainZone 11b · No frost · 0 chill hours · 1,592 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: canola (rapeseed)

    95%match
  18. 18

    🇮🇳DeogharJharkhand, India

    Zone 10b · Frost 1 years in 10 · 14 chill hours · 50 in rainZone 10b · Frost 1 years in 10 · 14 chill hours · 1,272 mm rain

    Shares 16 of your 17 great-fit crops

    95%match
  19. 19

    🇮🇳PurniaBihar, India

    Zone 10b · No frost · 15 chill hours · 61 in rainZone 10b · No frost · 15 chill hours · 1,539 mm rain

    Shares 15 of your 17 great-fit crops

    95%match
  20. 20

    🇮🇳BhāgalpurBihar, India

    Zone 10b · No frost · 15 chill hours · 46 in rainZone 10b · No frost · 15 chill hours · 1,177 mm rain

    Shares 16 of your 17 great-fit crops

    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 Kātoya: 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.