Climatch

Land with a climate like Vite

🇮🇳Vite, Maharashtra, India

The towns with the closest growing climate to Vite are Lonand, India (99% match), Athani and Gokak. About 101,000 sq mi of land in 6 countries matches 80% or better, most of it in Karnataka, India, Maharashtra, India and Piauí, Brazil.The towns with the closest growing climate to Vite are Lonand, India (99% match), Athani and Gokak. About 262,000 km² of land in 6 countries matches 80% or better, most of it in Karnataka, India, Maharashtra, India and Piauí, Brazil.

Your growing climate

Zone 11b · No frost · 0 chill hours · 27 in rainZone 11b · No frost · 0 chill hours · 681 mm rain

What grows in Vite →

Regions with the most land like yours

  1. 1

    🇮🇳Karnataka, India

    36k sq mi93k km² matching 80% or better

    For example Sadalgi (99), Raybag (99)

  2. 2

    🇮🇳Maharashtra, India

    34k sq mi89k km² matching 80% or better

    For example Lonand (99), Sāsvad (97)

  3. 3

    🇧🇷Piauí, Brazil

    6,500 sq mi17k km² matching 80% or better

    For example Bom Jesus (76), Inhuma (76)

  4. 4

    🇮🇳Andhra Pradesh, India

    5,500 sq mi14k km² matching 80% or better

    For example Rāyadrug (84), Kalyandurg (84)

  5. 5

    🇹🇿Tabora, Tanzania

    4,800 sq mi12k km² matching 80% or better

    For example Tumbi (81), Mabama (79)

  6. 6

    🇬🇳Labé Region, Guinea

    2,100 sq mi5,300 km² matching 80% or better

    For example Donghol-Sigon (77), Tougué (74)

  7. 7

    🇹🇿Katavi, Tanzania

    1,500 sq mi3,800 km² matching 80% or better

    For example Mpanda (80), Usevia (67)

  8. 8

    🇪🇹Oromiya, Ethiopia

    900 sq mi2,300 km² matching 80% or better

  9. 9

    🇬🇳Faranah, Guinea

    600 sq mi1,500 km² matching 80% or better

    For example Dabola (73), Dinguiraye (72)

  10. 10

    🇹🇿Kigoma, Tanzania

    300 sq mi800 km² matching 80% or better

    For example Nguruka (68), Uvinza (52)

  11. 11

    🇪🇹Bīnshangul Gumuz, Ethiopia

    300 sq mi800 km² matching 80% or better

    For example Mambuk (69), Āsosa (59)

  12. 12

    🇬🇳Boké Region, Guinea

    300 sq mi800 km² matching 80% or better

    For example Wendou Borou (66), Koumbia (63)

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

    🇮🇳LonandMaharashtra, India

    Zone 11b · No frost · 0 chill hours · 21 in rainZone 11b · No frost · 0 chill hours · 537 mm rain

    Shares 14 of your 16 great-fit crops

    99%match
  2. 2

    🇮🇳AthaniKarnataka, India

    Zone 12a · No frost · 0 chill hours · 34 in rainZone 12a · No frost · 0 chill hours · 856 mm rain

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

    98%match
  3. 3

    🇮🇳GokakKarnataka, India

    Zone 12a · No frost · 0 chill hours · 38 in rainZone 12a · No frost · 0 chill hours · 972 mm rain

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

    95%match
  4. 4

    🇮🇳NipāniMaharashtra, India

    Zone 11b · No frost · 0 chill hours · 46 in rainZone 11b · No frost · 0 chill hours · 1,177 mm rain

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

    95%match
  5. 5

    🇮🇳BārāmatiMaharashtra, India

    Zone 11b · No frost · 0 chill hours · 21 in rainZone 11b · No frost · 0 chill hours · 541 mm rain

    Shares 14 of your 16 great-fit crops

    95%match
  6. 6

    🇮🇳AklūjMaharashtra, India

    Zone 11b · No frost · 0 chill hours · 24 in rainZone 11b · No frost · 0 chill hours · 617 mm rain

    Shares 14 of your 16 great-fit crops

    95%match
  7. 7

    🇮🇳PuneMaharashtra, India

    Zone 11a · No frost · 0 chill hours · 37 in rainZone 11a · No frost · 0 chill hours · 949 mm rain

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

    94%match
  8. 8

    🇮🇳SirūrMaharashtra, India

    Zone 11a · No frost · 0 chill hours · 22 in rainZone 11a · No frost · 0 chill hours · 547 mm rain

    Shares 14 of your 16 great-fit crops

    94%match
  9. 9

    🇮🇳PandharpurMaharashtra, India

    Zone 11b · No frost · 0 chill hours · 28 in rainZone 11b · No frost · 0 chill hours · 701 mm rain

    Shares 15 of your 16 great-fit crops

    94%match
  10. 10

    🇮🇳ShrīgondaMaharashtra, India

    Zone 11a · No frost · 0 chill hours · 23 in rainZone 11a · No frost · 0 chill hours · 578 mm rain

    Shares 14 of your 16 great-fit crops

    93%match
  11. 11

    🇮🇳KalambMaharashtra, India

    Zone 11a · No frost · 0 chill hours · 31 in rainZone 11a · No frost · 0 chill hours · 786 mm rain

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

    92%match
  12. 12

    🇮🇳NargundKarnataka, India

    Zone 12a · No frost · 0 chill hours · 31 in rainZone 12a · No frost · 0 chill hours · 783 mm rain

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

    92%match
  13. 13

    🇮🇳MudholKarnataka, India

    Zone 12a · No frost · 0 chill hours · 32 in rainZone 12a · No frost · 0 chill hours · 823 mm rain

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

    92%match
  14. 14

    🇮🇳MuddebihālKarnataka, India

    Zone 12a · No frost · 0 chill hours · 33 in rainZone 12a · No frost · 0 chill hours · 839 mm rain

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

    91%match
  15. 15

    🇮🇳KoppalKarnataka, India

    Zone 12a · No frost · 0 chill hours · 31 in rainZone 12a · No frost · 0 chill hours · 778 mm rain

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

    91%match
  16. 16

    🇮🇳SaundattiKarnataka, India

    Zone 12a · No frost · 0 chill hours · 41 in rainZone 12a · No frost · 0 chill hours · 1,039 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: sugarcane, avocado

    91%match
  17. 17

    🇮🇳LingsugūrKarnataka, India

    Zone 12a · No frost · 0 chill hours · 29 in rainZone 12a · No frost · 0 chill hours · 727 mm rain

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

    91%match
  18. 18

    🇮🇳SavanūrKarnataka, India

    Zone 12a · No frost · 0 chill hours · 32 in rainZone 12a · No frost · 0 chill hours · 820 mm rain

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

    91%match
  19. 19

    🇮🇳HubballiKarnataka, India

    Zone 12a · No frost · 0 chill hours · 35 in rainZone 12a · No frost · 0 chill hours · 895 mm rain

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

    90%match
  20. 20

    🇮🇳KushtagiKarnataka, India

    Zone 12a · No frost · 0 chill hours · 34 in rainZone 12a · No frost · 0 chill hours · 852 mm rain

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

    90%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 Vite: 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.