Climatch

Land with a climate like Belūr

🇮🇳Belūr, Karnataka, India

The towns with the closest growing climate to Belūr are Kushālnagar, India (99% match), Khānāpur and Sirsi. About 80,000 sq mi of land in 15 countries matches 80% or better, most of it in Karnataka, India, Kigoma, Tanzania and Bago Region, Myanmar.The towns with the closest growing climate to Belūr are Kushālnagar, India (99% match), Khānāpur and Sirsi. About 208,000 km² of land in 15 countries matches 80% or better, most of it in Karnataka, India, Kigoma, Tanzania and Bago Region, Myanmar.

Your growing climate

Zone 12a · No frost · 0 chill hours · 64 in rainZone 12a · No frost · 0 chill hours · 1,622 mm rain

What grows in Belūr →

Regions with the most land like yours

  1. 1

    🇮🇳Karnataka, India

    20k sq mi51k km² matching 80% or better

    For example Kushālnagar (99), Piriyāpatna (97)

  2. 2

    🇹🇿Kigoma, Tanzania

    5,100 sq mi13k km² matching 80% or better

    For example Mwandiga (81), Uvinza (80)

  3. 3

    🇲🇲Bago Region, Myanmar

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

    For example Paungde (53), Zigon (53)

  4. 4

    🇬🇳Mamou Region, Guinea

    3,200 sq mi8,400 km² matching 80% or better

    For example Pita (89), Mamou (88)

  5. 5

    🇮🇳Maharashtra, India

    2,600 sq mi6,700 km² matching 80% or better

    For example Ajara (87), Gadhinglaj (84)

  6. 6

    🇹🇭Tak, Thailand

    2,600 sq mi6,700 km² matching 80% or better

    For example Mae Ramat (60), Mae Sot (58)

  7. 7

    🇲🇲Kayah State, Myanmar

    2,500 sq mi6,600 km² matching 80% or better

    For example Loikaw (80)

  8. 8

    🇮🇳Andhra Pradesh, India

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

    For example Punganūru (57), Kuppam (57)

  9. 9

    🇹🇭Chiang Mai, Thailand

    2,000 sq mi5,100 km² matching 80% or better

    For example San Kamphaeng (61), Hang Dong (60)

  10. 10

    🇧🇷Tocantins, Brazil

    1,800 sq mi4,600 km² matching 80% or better

    For example Dianópolis (81), Paraíso do Tocantins (76)

  11. 11

    🇧🇷Goiás, Brazil

    1,400 sq mi3,700 km² matching 80% or better

    For example Pirenópolis (79), Santo Antônio do Descoberto (79)

  12. 12

    🇲🇲Shan State, Myanmar

    1,400 sq mi3,600 km² matching 80% or better

    For example Pèkon (84), Yawnghwe (78)

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

    🇮🇳KushālnagarKarnataka, India

    Zone 12a · No frost · 0 chill hours · 60 in rainZone 12a · No frost · 0 chill hours · 1,532 mm rain

    Shares 24 of your 24 great-fit crops

    99%match
  2. 2

    🇮🇳KhānāpurKarnataka, India

    Zone 12a · No frost · 0 chill hours · 91 in rainZone 12a · No frost · 0 chill hours · 2,317 mm rain

    Shares 19 of your 24 great-fit crops

    94%match
  3. 3

    🇮🇳SirsiKarnataka, India

    Zone 12a · No frost · 0 chill hours · 118 in rainZone 12a · No frost · 0 chill hours · 3,007 mm rain

    Shares 16 of your 24 great-fit crops

    91%match
  4. 4

    🇮🇳DandeliKarnataka, India

    Zone 12a · No frost · 0 chill hours · 82 in rainZone 12a · No frost · 0 chill hours · 2,074 mm rain

    Shares 18 of your 24 great-fit crops

    91%match
  5. 5

    🇮🇳ShivamoggaKarnataka, India

    Zone 12a · No frost · 0 chill hours · 41 in rainZone 12a · No frost · 0 chill hours · 1,050 mm rain

    Shares 16 of your 24 great-fit crops · Also great there: fig

    90%match
  6. 6

    🇸🇻Santa AnaSanta Ana Department, El Salvador

    Zone 12a · No frost · 0 chill hours · 66 in rainZone 12a · No frost · 0 chill hours · 1,679 mm rain

    Shares 19 of your 24 great-fit crops

    90%match
  7. 7

    🇮🇳GudalurTamil Nadu, India

    Zone 12a · No frost · 0 chill hours · 104 in rainZone 12a · No frost · 0 chill hours · 2,650 mm rain

    Shares 22 of your 24 great-fit crops

    89%match
  8. 8

    🇬🇳PitaMamou Region, Guinea

    Zone 11b · No frost · 0 chill hours · 65 in rainZone 11b · No frost · 0 chill hours · 1,660 mm rain

    Shares 21 of your 24 great-fit crops

    89%match
  9. 9

    🇮🇳TīrthahalliKarnataka, India

    Zone 12a · No frost · 0 chill hours · 153 in rainZone 12a · No frost · 0 chill hours · 3,893 mm rain

    Shares 12 of your 24 great-fit crops

    89%match
  10. 10

    🇮🇳SāgarKarnataka, India

    Zone 12a · No frost · 0 chill hours · 134 in rainZone 12a · No frost · 0 chill hours · 3,411 mm rain

    Shares 14 of your 24 great-fit crops

    88%match
  11. 11

    🇸🇻San SalvadorSan Salvador Department, El Salvador

    Zone 12a · No frost · 0 chill hours · 76 in rainZone 12a · No frost · 0 chill hours · 1,928 mm rain

    Shares 19 of your 24 great-fit crops

    88%match
  12. 12

    🇬🇳MamouMamou Region, Guinea

    Zone 12a · No frost · 0 chill hours · 65 in rainZone 12a · No frost · 0 chill hours · 1,650 mm rain

    Shares 18 of your 24 great-fit crops

    88%match
  13. 13

    🇮🇳HunsūrKarnataka, India

    Zone 12a · No frost · 0 chill hours · 36 in rainZone 12a · No frost · 0 chill hours · 903 mm rain

    Shares 17 of your 24 great-fit crops · Also great there: fig, table and raisin grapes

    88%match
  14. 14

    🇮🇳HirekerūrKarnataka, India

    Zone 12a · No frost · 0 chill hours · 39 in rainZone 12a · No frost · 0 chill hours · 991 mm rain

    Shares 15 of your 24 great-fit crops · Also great there: fig

    86%match
  15. 15

    🇮🇳Bail-HongalKarnataka, India

    Zone 12a · No frost · 0 chill hours · 54 in rainZone 12a · No frost · 0 chill hours · 1,367 mm rain

    Shares 16 of your 24 great-fit crops · Also great there: fig

    86%match
  16. 16

    🇬🇹JutiapaGuatemala

    Zone 12a · No frost · 0 chill hours · 56 in rainZone 12a · No frost · 0 chill hours · 1,434 mm rain

    Shares 19 of your 24 great-fit crops · Also great there: fig

    85%match
  17. 17

    🇮🇳BengaluruKarnataka, India

    Zone 12a · No frost · 0 chill hours · 36 in rainZone 12a · No frost · 0 chill hours · 914 mm rain

    Shares 18 of your 24 great-fit crops · Also great there: fig, table and raisin grapes

    85%match
  18. 18

    🇸🇻San VicenteSan Vicente Department, El Salvador

    Zone 12b · No frost · 0 chill hours · 81 in rainZone 12b · No frost · 0 chill hours · 2,059 mm rain

    Shares 17 of your 24 great-fit crops

    84%match
  19. 19

    🇸🇻ChalatenangoChalatenango Department, El Salvador

    Zone 12b · No frost · 0 chill hours · 73 in rainZone 12b · No frost · 0 chill hours · 1,863 mm rain

    Shares 17 of your 24 great-fit crops

    84%match
  20. 20

    🇮🇳ShiggaonKarnataka, India

    Zone 12a · No frost · 0 chill hours · 37 in rainZone 12a · No frost · 0 chill hours · 944 mm rain

    Shares 15 of your 24 great-fit crops · Also great there: fig, table and raisin grapes

    84%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 Belūr: 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.