Climatch

Land with a climate like Rāmachettipālaiyam

🇮🇳Rāmachettipālaiyam, Tamil Nadu, India

The towns with the closest growing climate to Rāmachettipālaiyam are Dharmapuri, India (95% match), Krishnagiri and Gobichettipalayam. About 249,000 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 Rāmachettipālaiyam are Dharmapuri, India (95% match), Krishnagiri and Gobichettipalayam. About 646,000 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 12b · No frost · 0 chill hours · 46 in rainZone 12b · No frost · 0 chill hours · 1,161 mm rain

What grows in Rāmachettipālaiyam →

Regions with the most land like yours

  1. 1

    🇧🇷Maranhão, Brazil

    25k sq mi64k km² matching 80% or better

    For example Mirador (89), Paraibano (87)

  2. 2

    🇮🇳Tamil Nadu, India

    21k sq mi54k km² matching 80% or better

    For example Pennāgaram (97), Vīrnūr (96)

  3. 3

    🇻🇪Anzoátegui, Venezuela

    14k sq mi37k km² matching 80% or better

    For example Pariaguán (86), San José de Guanipa (86)

  4. 4

    🇻🇪Guárico, Venezuela

    9,100 sq mi24k km² matching 80% or better

    For example Altagracia de Orituco (86), San Juan de los Morros (85)

  5. 5

    🇻🇪Portuguesa, Venezuela

    8,900 sq mi23k km² matching 80% or better

    For example San Rafael de Onoto (92), Araure (90)

  6. 6

    🇧🇷Piauí, Brazil

    8,300 sq mi22k km² matching 80% or better

    For example Regeneração (86), Água Branca (84)

  7. 7

    🇺🇬Northern Region, Uganda

    7,500 sq mi19k km² matching 80% or better

    For example Pakwach (82), Adjumani (81)

  8. 8

    🇮🇩East Java, Indonesia

    6,800 sq mi18k km² matching 80% or better

    For example Madiun (86), Mojoagung (85)

  9. 9

    🇨🇴Cesar Department, Colombia

    5,300 sq mi14k km² matching 80% or better

    For example Agustín Codazzi (88), Valledupar (88)

  10. 10

    🇨🇩Bas-Uele, Democratic Republic of the Congo

    5,100 sq mi13k km² matching 80% or better

    For example Bondo (83), Aketi (76)

  11. 11

    🇨🇫Mbomou, Central African Republic

    5,100 sq mi13k km² matching 80% or better

    For example Bangassou (83)

  12. 12

    🇨🇴Arauca Department, Colombia

    5,000 sq mi13k km² matching 80% or better

    For example Arauca (86), Tame (70)

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 17 great-fit crops

    95%match
  2. 2

    🇮🇳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 17 great-fit crops

    93%match
  3. 3

    🇮🇳GobichettipalayamTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 31 in rainZone 12b · No frost · 0 chill hours · 795 mm rain

    Shares 15 of your 17 great-fit crops

    92%match
  4. 4

    🇻🇪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 17 great-fit crops

    92%match
  5. 5

    🇮🇳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 17 great-fit crops

    92%match
  6. 6

    🇮🇳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 17 great-fit crops

    92%match
  7. 7

    🇮🇳BodināyakkanūrTamil Nadu, India

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

    Shares 17 of your 17 great-fit crops

    92%match
  8. 8

    🇧🇷Mirador↻Seasons flipped. Maranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 47 in rainZone 12b · No frost · 0 chill hours · 1,203 mm rain

    Shares 15 of your 17 great-fit crops

    89%match
  9. 9

    🇮🇳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 17 great-fit crops

    89%match
  10. 10

    🇨🇫BanguiCentral African Republic

    Zone 12b · No frost · 0 chill hours · 51 in rainZone 12b · No frost · 0 chill hours · 1,291 mm rain

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

    88%match
  11. 11

    🇮🇳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 17 great-fit crops

    88%match
  12. 12

    🇨🇴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 15 of your 17 great-fit crops

    88%match
  13. 13

    🇨🇴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 17 great-fit crops

    88%match
  14. 14

    🇧🇷São João dos Patos↻Seasons flipped. Maranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 42 in rainZone 12b · No frost · 0 chill hours · 1,078 mm rain

    Shares 16 of your 17 great-fit crops

    87%match
  15. 15

    🇧🇷Buriti Bravo↻Seasons flipped. Maranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 42 in rainZone 12b · No frost · 0 chill hours · 1,069 mm rain

    Shares 15 of your 17 great-fit crops

    87%match
  16. 16

    🇻🇪TinaquilloCojedes, Venezuela

    Zone 12b · No frost · 0 chill hours · 44 in rainZone 12b · No frost · 0 chill hours · 1,123 mm rain

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

    87%match
  17. 17

    🇻🇪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 17 great-fit crops

    87%match
  18. 18

    🇻🇪YaritaguaYaracuy, Venezuela

    Zone 13a · No frost · 0 chill hours · 40 in rainZone 13a · No frost · 0 chill hours · 1,009 mm rain

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

    87%match
  19. 19

    🇧🇷Colinas↻Seasons flipped. Maranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 44 in rainZone 12b · No frost · 0 chill hours · 1,122 mm rain

    Shares 15 of your 17 great-fit crops

    87%match
  20. 20

    🇻🇪El TocuyoLara, Venezuela

    Zone 12b · No frost · 0 chill hours · 44 in rainZone 12b · No frost · 0 chill hours · 1,118 mm rain

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

    86%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 Rāmachettipālaiyam: 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.