Climatch

Land with a climate like Peruíbe

🇧🇷Peruíbe, São Paulo, Brazil

The towns with the closest growing climate to Peruíbe are Santos, Brazil (99% match), Registro and Caraguatatuba. About 147,000 sq mi of land in 21 countries matches 80% or better, most of it in Bahia, Brazil, Mato Grosso do Sul, Brazil and Espírito Santo, Brazil.The towns with the closest growing climate to Peruíbe are Santos, Brazil (99% match), Registro and Caraguatatuba. About 380,000 km² of land in 21 countries matches 80% or better, most of it in Bahia, Brazil, Mato Grosso do Sul, Brazil and Espírito Santo, Brazil.

Your growing climate

Zone 11b · No frost · 0 chill hours · 77 in rainZone 11b · No frost · 0 chill hours · 1,961 mm rain

What grows in Peruíbe →

Regions with the most land like yours

  1. 1

    🇧🇷Bahia, Brazil

    18k sq mi45k km² matching 80% or better

    For example Posto da Mata (86), Mucuri (86)

  2. 2

    🇧🇷Mato Grosso do Sul, Brazil

    12k sq mi32k km² matching 80% or better

    For example Fátima do Sul (84), Dourados (83)

  3. 3

    🇧🇷Espírito Santo, Brazil

    12k sq mi32k km² matching 80% or better

    For example Serra (90), Vila Velha (90)

  4. 4

    🇹🇼Taiwan

    5,200 sq mi13k km² matching 80% or better

    For example Hualien City (93), Xiulin (92)

  5. 5

    🇯🇵Okinawa, Japan

    4,600 sq mi12k km² matching 80% or better

    For example Chatan (84), Tomigusuku (84)

  6. 6

    🇲🇽Veracruz, Mexico

    3,100 sq mi8,000 km² matching 80% or better

    For example Tlapacoyan (90), Misantla (90)

  7. 7

    🇵🇪Junin, Peru

    2,600 sq mi6,800 km² matching 80% or better

    For example Satipo (80), Santa Rosa (80)

  8. 8

    🇲🇬Atsinanana, Madagascar

    2,500 sq mi6,600 km² matching 80% or better

    For example Vohibinany (80), Marolambo (77)

  9. 9

    🇺🇸Florida, United States

    2,400 sq mi6,200 km² matching 80% or better

    For example Jupiter (82), Fort Pierce (82)

  10. 10

    🇵🇫Îles du Vent, French Polynesia

    2,300 sq mi5,900 km² matching 80% or better

    For example Punaauia (88), Faaa (86)

  11. 11

    🇲🇬Vatovavy Region, Madagascar

    2,200 sq mi5,800 km² matching 80% or better

    For example Sahavato (79), Ifanadiana (77)

  12. 12

    🇫🇯Western, Fiji

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

    For example Sigatoka (80), Nadi (78)

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

    🇧🇷SantosSão Paulo, Brazil

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

    Shares 24 of your 24 great-fit crops

    99%match
  2. 2

    🇧🇷RegistroSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 63 in rainZone 11b · No frost · 0 chill hours · 1,593 mm rain

    Shares 24 of your 24 great-fit crops

    99%match
  3. 3

    🇧🇷CaraguatatubaSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 85 in rainZone 11b · No frost · 0 chill hours · 2,162 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  4. 4

    🇧🇷UbatubaSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 96 in rainZone 11b · No frost · 0 chill hours · 2,444 mm rain

    Shares 24 of your 24 great-fit crops

    98%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 24 of your 24 great-fit crops

    98%match
  6. 6

    🇧🇷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 24 of your 24 great-fit crops

    98%match
  7. 7

    🇧🇷GuaratubaParaná, Brazil

    Zone 11b · No frost · 0 chill hours · 78 in rainZone 11b · No frost · 0 chill hours · 1,988 mm rain

    Shares 22 of your 24 great-fit crops

    95%match
  8. 8

    🇧🇷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 24 great-fit crops

    95%match
  9. 9

    🇧🇷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 24 great-fit crops

    94%match
  10. 10

    🇹🇼Hualien City↻Seasons flipped. Taiwan, Taiwan

    Zone 11b · No frost · 0 chill hours · 82 in rainZone 11b · No frost · 0 chill hours · 2,087 mm rain

    Shares 24 of your 24 great-fit crops

    93%match
  11. 11

    🇧🇷Duque de CaxiasRio de Janeiro, Brazil

    Zone 11b · No frost · 0 chill hours · 57 in rainZone 11b · No frost · 0 chill hours · 1,458 mm rain

    Shares 23 of your 24 great-fit crops · Also great there: fig

    93%match
  12. 12

    🇧🇷MacaéRio de Janeiro, Brazil

    Zone 12a · No frost · 0 chill hours · 49 in rainZone 12a · No frost · 0 chill hours · 1,243 mm rain

    Shares 21 of your 24 great-fit crops · Also great there: fig

    92%match
  13. 13

    🇧🇷GuapimirimRio de Janeiro, Brazil

    Zone 11b · No frost · 0 chill hours · 55 in rainZone 11b · No frost · 0 chill hours · 1,399 mm rain

    Shares 24 of your 24 great-fit crops · Also great there: fig

    91%match
  14. 14

    🇧🇷Cabo FrioRio de Janeiro, Brazil

    Zone 12a · No frost · 0 chill hours · 46 in rainZone 12a · No frost · 0 chill hours · 1,162 mm rain

    Shares 20 of your 24 great-fit crops · Also great there: fig

    91%match
  15. 15

    🇧🇷ItaguaíRio de Janeiro, Brazil

    Zone 11b · No frost · 0 chill hours · 51 in rainZone 11b · No frost · 0 chill hours · 1,303 mm rain

    Shares 23 of your 24 great-fit crops · Also great there: fig

    90%match
  16. 16

    🇹🇴Nuku‘alofaTongatapu, Tonga

    Zone 12b · No frost · 0 chill hours · 81 in rainZone 12b · No frost · 0 chill hours · 2,045 mm rain

    Shares 23 of your 24 great-fit crops

    90%match
  17. 17

    🇧🇷SerraEspírito Santo, Brazil

    Zone 12a · No frost · 0 chill hours · 47 in rainZone 12a · No frost · 0 chill hours · 1,204 mm rain

    Shares 22 of your 24 great-fit crops · Also great there: fig

    90%match
  18. 18

    🇲🇽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 23 of your 24 great-fit crops

    90%match
  19. 19

    🇨🇰AvaruaRarotonga, Cook Islands

    Zone 12b · No frost · 0 chill hours · 81 in rainZone 12b · No frost · 0 chill hours · 2,052 mm rain

    Shares 23 of your 24 great-fit crops

    88%match
  20. 20

    🇧🇷São MateusEspírito Santo, Brazil

    Zone 12a · No frost · 0 chill hours · 47 in rainZone 12a · No frost · 0 chill hours · 1,190 mm rain

    Shares 20 of your 24 great-fit crops · Also great there: fig

    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 Peruíbe: 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.