Climatch

Land with a climate like Ūttukuli

🇮🇳Ūttukuli, Tamil Nadu, India

The towns with the closest growing climate to Ūttukuli are Salem, India (92% match), San Carlos and Dharmapuri. About 281,000 sq mi of land in 14 countries matches 80% or better, most of it in Maranhão, Brazil, Tamil Nadu, India and Apure, Venezuela.The towns with the closest growing climate to Ūttukuli are Salem, India (92% match), San Carlos and Dharmapuri. About 728,000 km² of land in 14 countries matches 80% or better, most of it in Maranhão, Brazil, Tamil Nadu, India and Apure, Venezuela.

Your growing climate

Zone 13a · No frost · 0 chill hours · 50 in rainZone 13a · No frost · 0 chill hours · 1,271 mm rain

What grows in Ūttukuli →

Regions with the most land like yours

  1. 1

    🇧🇷Maranhão, Brazil

    22k sq mi58k km² matching 80% or better

    For example Mirador (86), Colinas (84)

  2. 2

    🇮🇳Tamil Nadu, India

    21k sq mi53k km² matching 80% or better

    For example Vīrnūr (95), Pottaneri Nallakavundanpatti (94)

  3. 3

    🇻🇪Apure, Venezuela

    18k sq mi46k km² matching 80% or better

    For example Guasdualito (88), Elorza (86)

  4. 4

    🇻🇪Anzoátegui, Venezuela

    14k sq mi35k km² matching 80% or better

    For example Soledad (88), San José de Guanipa (85)

  5. 5

    🇻🇪Guárico, Venezuela

    11k sq mi29k km² matching 80% or better

    For example Altagracia de Orituco (84), El Sombrero (82)

  6. 6

    🇮🇩East Java, Indonesia

    8,300 sq mi22k km² matching 80% or better

    For example Madiun (90), Mojoagung (88)

  7. 7

    🇨🇴Cesar Department, Colombia

    6,200 sq mi16k km² matching 80% or better

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

  8. 8

    🇰🇭Kratie, Cambodia

    5,500 sq mi14k km² matching 80% or better

    For example Kratié (86), Snuol (86)

  9. 9

    🇰🇭Kampong Thom, Cambodia

    5,200 sq mi14k km² matching 80% or better

    For example Kampong Thom (88), Phumĭ Tnaôt (88)

  10. 10

    🇨🇴Arauca Department, Colombia

    5,000 sq mi13k km² matching 80% or better

    For example Arauca (90), Tame (69)

  11. 11

    🇨🇴Magdalena Department, Colombia

    5,000 sq mi13k km² matching 80% or better

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

  12. 12

    🇮🇩East Nusa Tenggara, Indonesia

    4,700 sq mi12k km² matching 80% or better

    For example Tambolaka (84), Labuan Bajo (84)

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

    🇮🇳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
  2. 2

    🇻🇪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
  3. 3

    🇮🇳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

    92%match
  4. 4

    🇰🇭PursatCambodia

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

    Shares 15 of your 17 great-fit crops · Also great there: cacao

    91%match
  5. 5

    🇰🇭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 17 great-fit crops

    91%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

    91%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

    91%match
  8. 8

    🇰🇭Prey VengCambodia

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

    Shares 16 of your 17 great-fit crops

    90%match
  9. 9

    🇨🇴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

    90%match
  10. 10

    🇮🇩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 15 of your 17 great-fit crops · Also great there: cacao, tea, macadamia

    90%match
  11. 11

    🇨🇴AraucaArauca Department, Colombia

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

    Shares 15 of your 17 great-fit crops · Also great there: cacao

    90%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

    90%match
  13. 13

    🇰🇭Phnom PenhCambodia

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

    Shares 15 of your 17 great-fit crops · Also great there: cacao

    90%match
  14. 14

    🇰🇭Kampong ChhnangCambodia

    Zone 13a · No frost · 0 chill hours · 65 in rainZone 13a · No frost · 0 chill hours · 1,655 mm rain

    Shares 15 of your 17 great-fit crops · Also great there: cacao

    89%match
  15. 15

    🇰🇭Kampong SpeuKampong Speu Province, Cambodia

    Zone 13b · No frost · 0 chill hours · 48 in rainZone 13b · No frost · 0 chill hours · 1,211 mm rain

    Shares 15 of your 17 great-fit crops

    89%match
  16. 16

    🇮🇳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 17 great-fit crops

    89%match
  17. 17

    🇻🇪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 17 great-fit crops

    89%match
  18. 18

    🇰🇭Siem ReapCambodia

    Zone 12b · No frost · 0 chill hours · 53 in rainZone 12b · No frost · 0 chill hours · 1,342 mm rain

    Shares 14 of your 17 great-fit crops

    89%match
  19. 19

    🇮🇳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

    88%match
  20. 20

    🇰🇭Kampong ChamCambodia

    Zone 13a · No frost · 0 chill hours · 64 in rainZone 13a · No frost · 0 chill hours · 1,629 mm rain

    Shares 15 of your 17 great-fit crops · Also great there: cacao

    88%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 Ūttukuli: 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.