Climatch

Land with a climate like Sūleswaranpatti

🇮🇳Sūleswaranpatti, Tamil Nadu, India

The towns with the closest growing climate to Sūleswaranpatti are Dharmapuri, India (93% match), Salem and Bodināyakkanūr. About 261,000 sq mi of land in 14 countries matches 80% or better, most of it in Maranhão, Brazil, Tamil Nadu, India and Anzoátegui, Venezuela.The towns with the closest growing climate to Sūleswaranpatti are Dharmapuri, India (93% match), Salem and Bodināyakkanūr. About 675,000 km² of land in 14 countries matches 80% or better, most of it in Maranhão, Brazil, Tamil Nadu, India and Anzoátegui, Venezuela.

Your growing climate

Zone 13a · No frost · 0 chill hours · 46 in rainZone 13a · No frost · 0 chill hours · 1,178 mm rain

What grows in Sūleswaranpatti →

Regions with the most land like yours

  1. 1

    🇧🇷Maranhão, Brazil

    26k sq mi67k km² matching 80% or better

    For example Mirador (87), Matões (86)

  2. 2

    🇮🇳Tamil Nadu, India

    23k sq mi60k km² matching 80% or better

    For example Vīrnūr (96), Pottaneri Nallakavundanpatti (96)

  3. 3

    🇻🇪Anzoátegui, Venezuela

    14k sq mi36k km² matching 80% or better

    For example Soledad (87), Clarines (86)

  4. 4

    🇻🇪Apure, Venezuela

    13k sq mi35k km² matching 80% or better

    For example Guasdualito (86), Elorza (84)

  5. 5

    🇻🇪Bolívar, Venezuela

    10k sq mi27k km² matching 80% or better

    For example Caicara del Orinoco (84), Ciudad Bolívar (83)

  6. 6

    🇧🇷Piauí, Brazil

    8,000 sq mi21k km² matching 80% or better

    For example Regeneração (84), Água Branca (82)

  7. 7

    🇮🇩East Java, Indonesia

    7,700 sq mi20k km² matching 80% or better

    For example Madiun (88), Mojoagung (87)

  8. 8

    🇨🇴Cesar Department, Colombia

    5,900 sq mi15k km² matching 80% or better

    For example Valledupar (90), Agustín Codazzi (90)

  9. 9

    🇰🇭Kratie, Cambodia

    5,300 sq mi14k km² matching 80% or better

    For example Kratié (84), Snuol (83)

  10. 10

    🇨🇴Arauca Department, Colombia

    5,000 sq mi13k km² matching 80% or better

    For example Arauca (88), Tame (67)

  11. 11

    🇰🇭Kampong Thom, Cambodia

    5,000 sq mi13k km² matching 80% or better

    For example Phumĭ Tnaôt (86), Kampong Thom (86)

  12. 12

    🇨🇴Magdalena Department, Colombia

    4,100 sq mi11k km² matching 80% or better

    For example Nueva Granada (87), Plato (86)

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

    🇮🇳DharmapuriTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 39 in rainZone 12b · No frost · 0 chill hours · 982 mm rain

    Shares 15 of your 16 great-fit crops

    93%match
  2. 2

    🇮🇳SalemTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 41 in rainZone 12b · No frost · 0 chill hours · 1,048 mm rain

    Shares 15 of your 16 great-fit crops

    93%match
  3. 3

    🇮🇳BodināyakkanūrTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 40 in rainZone 13a · No frost · 0 chill hours · 1,020 mm rain

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

    93%match
  4. 4

    🇮🇳TiruchengodeTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 35 in rainZone 12b · No frost · 0 chill hours · 899 mm rain

    Shares 15 of your 16 great-fit crops

    93%match
  5. 5

    🇻🇪San CarlosCojedes, Venezuela

    Zone 13a · No frost · 0 chill hours · 50 in rainZone 13a · No frost · 0 chill hours · 1,263 mm rain

    Shares 14 of your 16 great-fit crops

    92%match
  6. 6

    🇮🇳SathyamangalamTamil Nadu, India

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

    Shares 15 of your 16 great-fit crops

    92%match
  7. 7

    🇮🇳KrishnagiriTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 35 in rainZone 12b · No frost · 0 chill hours · 883 mm rain

    Shares 15 of your 16 great-fit crops

    91%match
  8. 8

    🇨🇴ValleduparCesar Department, Colombia

    Zone 13a · No frost · 0 chill hours · 44 in rainZone 13a · No frost · 0 chill hours · 1,116 mm rain

    Shares 14 of your 16 great-fit crops

    90%match
  9. 9

    🇮🇳ErodeTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 33 in rainZone 13a · No frost · 0 chill hours · 844 mm rain

    Shares 15 of your 16 great-fit crops

    90%match
  10. 10

    🇨🇴Agustín CodazziCesar Department, Colombia

    Zone 13a · No frost · 0 chill hours · 49 in rainZone 13a · No frost · 0 chill hours · 1,257 mm rain

    Shares 14 of your 16 great-fit crops · Also great there: banana

    90%match
  11. 11

    🇰🇭PursatCambodia

    Zone 13a · No frost · 0 chill hours · 55 in rainZone 13a · No frost · 0 chill hours · 1,396 mm rain

    Shares 14 of your 16 great-fit crops · Also great there: banana, cacao

    90%match
  12. 12

    🇻🇪El PaoCojedes, Venezuela

    Zone 13a · No frost · 0 chill hours · 50 in rainZone 13a · No frost · 0 chill hours · 1,262 mm rain

    Shares 14 of your 16 great-fit crops

    89%match
  13. 13

    🇰🇭BattambangCambodia

    Zone 13a · No frost · 0 chill hours · 52 in rainZone 13a · No frost · 0 chill hours · 1,333 mm rain

    Shares 14 of your 16 great-fit crops

    89%match
  14. 14

    🇮🇳AmburTamil Nadu, India

    Zone 12a · No frost · 0 chill hours · 37 in rainZone 12a · No frost · 0 chill hours · 943 mm rain

    Shares 15 of your 16 great-fit crops

    89%match
  15. 15

    🇻🇪AcariguaPortuguesa, Venezuela

    Zone 13a · No frost · 0 chill hours · 41 in rainZone 13a · No frost · 0 chill hours · 1,044 mm rain

    Shares 15 of your 16 great-fit crops

    88%match
  16. 16

    🇮🇩Madiun↻Seasons flipped. East Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 78 in rainZone 13a · No frost · 0 chill hours · 1,980 mm rain

    Shares 14 of your 16 great-fit crops · Also great there: cacao, banana, tea

    88%match
  17. 17

    🇰🇭Phnom PenhCambodia

    Zone 13b · No frost · 0 chill hours · 54 in rainZone 13b · No frost · 0 chill hours · 1,359 mm rain

    Shares 14 of your 16 great-fit crops · Also great there: banana, cacao

    88%match
  18. 18

    🇰🇭Prey VengCambodia

    Zone 13b · No frost · 0 chill hours · 52 in rainZone 13b · No frost · 0 chill hours · 1,309 mm rain

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

    88%match
  19. 19

    🇨🇴AraucaArauca Department, Colombia

    Zone 13a · No frost · 0 chill hours · 69 in rainZone 13a · No frost · 0 chill hours · 1,763 mm rain

    Shares 14 of your 16 great-fit crops · Also great there: cacao, banana

    88%match
  20. 20

    🇨🇴San Juan del CesarLa Guajira Department, Colombia

    Zone 13a · No frost · 0 chill hours · 40 in rainZone 13a · No frost · 0 chill hours · 1,012 mm rain

    Shares 14 of your 16 great-fit crops

    87%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 Sūleswaranpatti: 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.