Climatch

Land with a climate like Āchāripallam Vāniyakudi

🇮🇳Āchāripallam Vāniyakudi, Tamil Nadu, India

The towns with the closest growing climate to Āchāripallam Vāniyakudi are Shenkottai, India (96% match), Montería and Magangué. About 343,000 sq mi of land in 29 countries matches 80% or better, most of it in Zulia, Venezuela, Tamil Nadu, India and Southeast Sulawesi, Indonesia.The towns with the closest growing climate to Āchāripallam Vāniyakudi are Shenkottai, India (96% match), Montería and Magangué. About 888,000 km² of land in 29 countries matches 80% or better, most of it in Zulia, Venezuela, Tamil Nadu, India and Southeast Sulawesi, Indonesia.

Your growing climate

Zone 13b · No frost · 0 chill hours · 57 in rainZone 13b · No frost · 0 chill hours · 1,456 mm rain

What grows in Āchāripallam Vāniyakudi →

Regions with the most land like yours

  1. 1

    🇻🇪Zulia, Venezuela

    14k sq mi36k km² matching 80% or better

    For example San Timoteo (93), Machiques (92)

  2. 2

    🇮🇳Tamil Nadu, India

    11k sq mi29k km² matching 80% or better

    For example Shenkottai (96), Vadakarai Kīl Pidāgai (94)

  3. 3

    🇮🇩Southeast Sulawesi, Indonesia

    8,000 sq mi21k km² matching 80% or better

    For example Baubau (86), Raha (82)

  4. 4

    🇨🇴Antioquia, Colombia

    8,000 sq mi21k km² matching 80% or better

    For example San Juan de Urabá (91), Turbo (87)

  5. 5

    🇨🇴Córdoba, Colombia

    8,000 sq mi21k km² matching 80% or better

    For example Montería (95), Cotorra (94)

  6. 6

    🇨🇴Cesar Department, Colombia

    7,700 sq mi20k km² matching 80% or better

    For example Pailitas (94), Curumaní (93)

  7. 7

    🇹🇭Surat Thani, Thailand

    7,100 sq mi18k km² matching 80% or better

    For example Tha Kham (93), Surat Thani (93)

  8. 8

    🇮🇩Central Java, Indonesia

    6,500 sq mi17k km² matching 80% or better

    For example Cepu (88), Blora (88)

  9. 9

    🇮🇩East Java, Indonesia

    6,200 sq mi16k km² matching 80% or better

    For example Madiun (88), Ngawi (88)

  10. 10

    🇻🇳An Giang, Vietnam

    5,600 sq mi14k km² matching 80% or better

    For example Tịnh Biên (93), Châu Đốc (92)

  11. 11

    🇻🇪Barinas, Venezuela

    4,100 sq mi11k km² matching 80% or better

    For example Barinitas (83), Socopó (82)

  12. 12

    🇹🇭Trang, Thailand

    3,900 sq mi10,000 km² matching 80% or better

    For example Huai Yot (89), Trang (87)

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

    🇮🇳ShenkottaiTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 63 in rainZone 13a · No frost · 0 chill hours · 1,598 mm rain

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

    96%match
  2. 2

    🇨🇴MonteríaCórdoba, Colombia

    Zone 13b · No frost · 0 chill hours · 55 in rainZone 13b · No frost · 0 chill hours · 1,400 mm rain

    Shares 17 of your 18 great-fit crops

    95%match
  3. 3

    🇨🇴MaganguéBolívar, Colombia

    Zone 13b · No frost · 0 chill hours · 64 in rainZone 13b · No frost · 0 chill hours · 1,627 mm rain

    Shares 15 of your 18 great-fit crops

    94%match
  4. 4

    🇻🇪San TimoteoZulia, Venezuela

    Zone 13b · No frost · 0 chill hours · 40 in rainZone 13b · No frost · 0 chill hours · 1,019 mm rain

    Shares 16 of your 18 great-fit crops

    93%match
  5. 5

    🇨🇴CurumaníCesar Department, Colombia

    Zone 13b · No frost · 0 chill hours · 61 in rainZone 13b · No frost · 0 chill hours · 1,554 mm rain

    Shares 15 of your 18 great-fit crops

    93%match
  6. 6

    🇹🇭Surat ThaniThailand

    Zone 13a · No frost · 0 chill hours · 68 in rainZone 13a · No frost · 0 chill hours · 1,730 mm rain

    Shares 17 of your 18 great-fit crops

    93%match
  7. 7

    🇰🇭TakeoCambodia

    Zone 13b · No frost · 0 chill hours · 55 in rainZone 13b · No frost · 0 chill hours · 1,388 mm rain

    Shares 17 of your 18 great-fit crops

    93%match
  8. 8

    🇨🇴El BancoMagdalena Department, Colombia

    Zone 13b · No frost · 0 chill hours · 71 in rainZone 13b · No frost · 0 chill hours · 1,791 mm rain

    Shares 15 of your 18 great-fit crops

    93%match
  9. 9

    🇨🇴San OnofreSucre Department, Colombia

    Zone 13b · No frost · 0 chill hours · 47 in rainZone 13b · No frost · 0 chill hours · 1,205 mm rain

    Shares 14 of your 18 great-fit crops

    93%match
  10. 10

    🇨🇴TierraltaCórdoba, Colombia

    Zone 13b · No frost · 0 chill hours · 70 in rainZone 13b · No frost · 0 chill hours · 1,780 mm rain

    Shares 17 of your 18 great-fit crops

    92%match
  11. 11

    🇨🇴LoricaCórdoba, Colombia

    Zone 13b · No frost · 0 chill hours · 50 in rainZone 13b · No frost · 0 chill hours · 1,258 mm rain

    Shares 16 of your 18 great-fit crops

    92%match
  12. 12

    🇨🇴SincelejoSucre Department, Colombia

    Zone 13b · No frost · 0 chill hours · 47 in rainZone 13b · No frost · 0 chill hours · 1,184 mm rain

    Shares 16 of your 18 great-fit crops

    92%match
  13. 13

    🇻🇪MachiquesZulia, Venezuela

    Zone 13a · No frost · 0 chill hours · 48 in rainZone 13a · No frost · 0 chill hours · 1,214 mm rain

    Shares 15 of your 18 great-fit crops

    92%match
  14. 14

    🇨🇴SahagúnCórdoba, Colombia

    Zone 13b · No frost · 0 chill hours · 49 in rainZone 13b · No frost · 0 chill hours · 1,249 mm rain

    Shares 15 of your 18 great-fit crops

    92%match
  15. 15

    🇨🇴Planeta RicaCórdoba, Colombia

    Zone 13b · No frost · 0 chill hours · 62 in rainZone 13b · No frost · 0 chill hours · 1,569 mm rain

    Shares 16 of your 18 great-fit crops

    92%match
  16. 16

    🇱🇰ChilawNorth Western Province, Sri Lanka

    Zone 13a · No frost · 0 chill hours · 66 in rainZone 13a · No frost · 0 chill hours · 1,685 mm rain

    Shares 17 of your 18 great-fit crops

    91%match
  17. 17

    🇨🇴La Jagua de IbiricoCesar Department, Colombia

    Zone 13b · No frost · 0 chill hours · 58 in rainZone 13b · No frost · 0 chill hours · 1,472 mm rain

    Shares 16 of your 18 great-fit crops

    91%match
  18. 18

    🇹🇭KrabiThailand

    Zone 13b · No frost · 0 chill hours · 83 in rainZone 13b · No frost · 0 chill hours · 2,120 mm rain

    Shares 17 of your 18 great-fit crops

    91%match
  19. 19

    🇹🇭SadaoSongkhla, Thailand

    Zone 13b · No frost · 0 chill hours · 76 in rainZone 13b · No frost · 0 chill hours · 1,931 mm rain

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

    91%match
  20. 20

    🇨🇴San Juan de UrabáAntioquia, Colombia

    Zone 13b · No frost · 0 chill hours · 60 in rainZone 13b · No frost · 0 chill hours · 1,533 mm rain

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

    91%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 Āchāripallam Vāniyakudi: 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.