Climatch

Land with a climate like Ilhabela

🇧🇷Ilhabela, São Paulo, Brazil

The towns with the closest growing climate to Ilhabela are Itariri, Brazil (99% match), Antonina and Iguape. About 90,000 sq mi of land in 14 countries matches 80% or better, most of it in São Paulo, Brazil, Santa Catarina, Brazil and Paraná, Brazil.The towns with the closest growing climate to Ilhabela are Itariri, Brazil (99% match), Antonina and Iguape. About 232,000 km² of land in 14 countries matches 80% or better, most of it in São Paulo, Brazil, Santa Catarina, Brazil and Paraná, Brazil.

Your growing climate

Zone 11b · No frost · 0 chill hours · 86 in rainZone 11b · No frost · 0 chill hours · 2,179 mm rain

What grows in Ilhabela →

Regions with the most land like yours

  1. 1

    🇧🇷São Paulo, Brazil

    14k sq mi35k km² matching 80% or better

    For example Itariri (99), Iguape (99)

  2. 2

    🇧🇷Santa Catarina, Brazil

    11k sq mi29k km² matching 80% or better

    For example Itapoá (99), Garuva (99)

  3. 3

    🇧🇷Paraná, Brazil

    8,200 sq mi21k km² matching 80% or better

    For example Guaratuba (99), Matinhos (99)

  4. 4

    🇹🇼Taiwan

    5,500 sq mi14k km² matching 80% or better

    For example Daxi (87), Bade (86)

  5. 5

    🇵🇬Morobe Province, Papua New Guinea

    2,400 sq mi6,100 km² matching 80% or better

    For example Bulolo (72)

  6. 6

    🇮🇩Jambi, Indonesia

    2,100 sq mi5,400 km² matching 80% or better

    For example Sungai Penuh (83)

  7. 7

    🇵🇭Cordillera, Philippines

    2,000 sq mi5,200 km² matching 80% or better

    For example Bontoc (90), Mankayan (83)

  8. 8

    🇲🇬Atsinanana, Madagascar

    2,000 sq mi5,100 km² matching 80% or better

    For example Vohibinany (78), Marolambo (75)

  9. 9

    🇮🇩West Sumatra, Indonesia

    1,500 sq mi3,900 km² matching 80% or better

    For example Padangpanjang (82), Bukittinggi (81)

  10. 10

    🇵🇬Eastern Highlands Province, Papua New Guinea

    1,200 sq mi3,100 km² matching 80% or better

    For example Goroka (81)

  11. 11

    🇲🇬Vatovavy Region, Madagascar

    1,100 sq mi2,900 km² matching 80% or better

    For example Ifanadiana (78), Sahavato (72)

  12. 12

    🇮🇩Bengkulu, Indonesia

    900 sq mi2,300 km² matching 80% or better

    For example Curup (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

    🇧🇷ItaririSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 72 in rainZone 11b · No frost · 0 chill hours · 1,829 mm rain

    Shares 22 of your 22 great-fit crops · Also great there: mango

    99%match
  2. 2

    🇧🇷AntoninaParaná, Brazil

    Zone 11b · No frost · 0 chill hours · 75 in rainZone 11b · No frost · 0 chill hours · 1,895 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  3. 3

    🇧🇷IguapeSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 77 in rainZone 11b · No frost · 0 chill hours · 1,965 mm rain

    Shares 22 of your 22 great-fit crops · Also great there: mango

    99%match
  4. 4

    🇧🇷ParanaguáParaná, Brazil

    Zone 11b · No frost · 0 chill hours · 81 in rainZone 11b · No frost · 0 chill hours · 2,050 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  5. 5

    🇧🇷ParatyRio de Janeiro, Brazil

    Zone 11b · No frost · 0 chill hours · 90 in rainZone 11b · No frost · 0 chill hours · 2,297 mm rain

    Shares 22 of your 22 great-fit crops · Also great there: cacao, mango

    98%match
  6. 6

    🇧🇷JoinvilleSanta Catarina, Brazil

    Zone 11a · No frost · 0 chill hours · 71 in rainZone 11a · No frost · 0 chill hours · 1,800 mm rain

    Shares 22 of your 22 great-fit crops

    98%match
  7. 7

    🇧🇷SantosSão Paulo, Brazil

    Zone 12a · No frost · 0 chill hours · 100 in rainZone 12a · No frost · 0 chill hours · 2,541 mm rain

    Shares 22 of your 22 great-fit crops · Also great there: cacao, mango

    96%match
  8. 8

    🇧🇷FlorianópolisSanta Catarina, Brazil

    Zone 11a · No frost · 0 chill hours · 65 in rainZone 11a · No frost · 0 chill hours · 1,659 mm rain

    Shares 22 of your 22 great-fit crops

    96%match
  9. 9

    🇧🇷ItajaíSanta Catarina, Brazil

    Zone 11a · No frost · 5 chill hours · 67 in rainZone 11a · No frost · 5 chill hours · 1,713 mm rain

    Shares 22 of your 22 great-fit crops

    96%match
  10. 10

    🇧🇷São João BatistaSanta Catarina, Brazil

    Zone 11a · No frost · 8 chill hours · 66 in rainZone 11a · No frost · 8 chill hours · 1,666 mm rain

    Shares 22 of your 22 great-fit crops

    95%match
  11. 11

    🇧🇷BlumenauSanta Catarina, Brazil

    Zone 11a · No frost · 4 chill hours · 67 in rainZone 11a · No frost · 4 chill hours · 1,703 mm rain

    Shares 22 of your 22 great-fit crops

    94%match
  12. 12

    🇧🇷JuquiáSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 62 in rainZone 11b · No frost · 0 chill hours · 1,586 mm rain

    Shares 22 of your 22 great-fit crops · Also great there: mango

    94%match
  13. 13

    🇧🇷ItanhaémSão Paulo, Brazil

    Zone 12a · No frost · 0 chill hours · 79 in rainZone 12a · No frost · 0 chill hours · 2,018 mm rain

    Shares 22 of your 22 great-fit crops · Also great there: cacao, mango

    94%match
  14. 14

    🇧🇷ImbitubaSanta Catarina, Brazil

    Zone 11a · No frost · 0 chill hours · 62 in rainZone 11a · No frost · 0 chill hours · 1,563 mm rain

    Shares 22 of your 22 great-fit crops

    94%match
  15. 15

    🇧🇷TubarãoSanta Catarina, Brazil

    Zone 11a · No frost · 6 chill hours · 59 in rainZone 11a · No frost · 6 chill hours · 1,499 mm rain

    Shares 22 of your 22 great-fit crops

    94%match
  16. 16

    🇧🇷PomerodeSanta Catarina, Brazil

    Zone 11a · No frost · 6 chill hours · 66 in rainZone 11a · No frost · 6 chill hours · 1,674 mm rain

    Shares 22 of your 22 great-fit crops

    93%match
  17. 17

    🇧🇷Angra dos ReisRio de Janeiro, Brazil

    Zone 11b · No frost · 0 chill hours · 70 in rainZone 11b · No frost · 0 chill hours · 1,768 mm rain

    Shares 22 of your 22 great-fit crops · Also great there: cacao, mango

    93%match
  18. 18

    🇧🇷CajatiSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 70 in rainZone 11b · No frost · 0 chill hours · 1,769 mm rain

    Shares 22 of your 22 great-fit crops · Also great there: mango, cacao

    91%match
  19. 19

    🇵🇭Bontoc↻Seasons flipped. Cordillera, Philippines

    Zone 12a · No frost · 0 chill hours · 126 in rainZone 12a · No frost · 0 chill hours · 3,206 mm rain

    Shares 18 of your 22 great-fit crops

    90%match
  20. 20

    🇲🇽Tlapacoyan↻Seasons flipped. Veracruz, Mexico

    Zone 11b · No frost · 0 chill hours · 76 in rainZone 11b · No frost · 0 chill hours · 1,922 mm rain

    Shares 22 of your 22 great-fit crops · Also great there: mango

    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 Ilhabela: 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.