Climatch

Land with a climate like Registro

🇧🇷Registro, São Paulo, Brazil

The towns with the closest growing climate to Registro are Itanhaém, Brazil (99% match), Angra dos Reis and Caraguatatuba. About 153,000 sq mi of land in 14 countries matches 80% or better, most of it in Mato Grosso do Sul, Brazil, São Paulo, Brazil and Paraná, Brazil.The towns with the closest growing climate to Registro are Itanhaém, Brazil (99% match), Angra dos Reis and Caraguatatuba. About 396,000 km² of land in 14 countries matches 80% or better, most of it in Mato Grosso do Sul, Brazil, São Paulo, Brazil and Paraná, Brazil.

Your growing climate

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

What grows in Registro →

Regions with the most land like yours

  1. 1

    🇧🇷Mato Grosso do Sul, Brazil

    26k sq mi67k km² matching 80% or better

    For example Dourados (86), Fátima do Sul (86)

  2. 2

    🇧🇷São Paulo, Brazil

    21k sq mi53k km² matching 80% or better

    For example Peruíbe (99), Itanhaém (99)

  3. 3

    🇧🇷Paraná, Brazil

    16k sq mi43k km² matching 80% or better

    For example Morretes (97), Antonina (96)

  4. 4

    🇨🇳Guangdong, China

    3,900 sq mi10,000 km² matching 80% or better

    For example Pingshan (80), Humen (80)

  5. 5

    🇹🇼Taiwan

    3,300 sq mi8,500 km² matching 80% or better

    For example Hsinchu (87), Zhubei (86)

  6. 6

    🇵🇾Concepción, Paraguay

    2,500 sq mi6,400 km² matching 80% or better

    For example Yby Yaú (81), Concepción (67)

  7. 7

    🇲🇽Veracruz, Mexico

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

    For example Misantla (84), Tlapacoyan (84)

  8. 8

    🇵🇫Îles du Vent, French Polynesia

    1,700 sq mi4,400 km² matching 80% or better

    For example Punaauia (80), Faaa (79)

  9. 9

    🇵🇾Amambay Department, Paraguay

    1,700 sq mi4,300 km² matching 80% or better

    For example Pedro Juan Caballero (77)

  10. 10

    🇵🇾Caazapá, Paraguay

    1,600 sq mi4,200 km² matching 80% or better

    For example Caazapá (79)

  11. 11

    🇺🇸Florida, United States

    1,600 sq mi4,100 km² matching 80% or better

    For example Port Saint Lucie (83), Fort Pierce (82)

  12. 12

    🇵🇪Junin, Peru

    1,200 sq mi3,000 km² matching 80% or better

    For example Satipo (79), Santa Rosa (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

    🇧🇷ItanhaémSão Paulo, Brazil

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

    Shares 24 of your 24 great-fit crops

    99%match
  2. 2

    🇧🇷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

    96%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

    94%match
  4. 4

    🇧🇷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
  5. 5

    🇧🇷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

    94%match
  6. 6

    🇧🇷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

    94%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

    92%match
  8. 8

    🇧🇷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

    92%match
  9. 9

    🇧🇷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

    92%match
  10. 10

    🇧🇷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

    92%match
  11. 11

    🇧🇷Cerro AzulParaná, Brazil

    Zone 11a · No frost · 5 chill hours · 46 in rainZone 11a · No frost · 5 chill hours · 1,172 mm rain

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

    91%match
  12. 12

    🇧🇷Rio de JaneiroBrazil

    Zone 12a · No frost · 0 chill hours · 43 in rainZone 12a · No frost · 0 chill hours · 1,092 mm rain

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

    91%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

    🇧🇷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

    90%match
  15. 15

    🇧🇷Rio das OstrasRio de Janeiro, Brazil

    Zone 12a · No frost · 0 chill hours · 48 in rainZone 12a · No frost · 0 chill hours · 1,209 mm rain

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

    90%match
  16. 16

    🇧🇷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

    89%match
  17. 17

    🇧🇷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

    88%match
  18. 18

    🇧🇷SaquaremaRio de Janeiro, Brazil

    Zone 12a · No frost · 0 chill hours · 42 in rainZone 12a · No frost · 0 chill hours · 1,064 mm rain

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

    87%match
  19. 19

    🇧🇷CorupáSanta Catarina, Brazil

    Zone 11a · No frost · 4 chill hours · 63 in rainZone 11a · No frost · 4 chill hours · 1,589 mm rain

    Shares 22 of your 24 great-fit crops

    87%match
  20. 20

    🇧🇷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 24 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 Registro: 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.