Climatch

Land with a climate like Mangaratiba

🇧🇷Mangaratiba, Rio de Janeiro, Brazil

The towns with the closest growing climate to Mangaratiba are Macaé, Brazil (99% match), Guapimirim and Rio de Janeiro. About 606,000 sq mi of land in 30 countries matches 80% or better, most of it in Mato Grosso do Sul, Brazil, São Paulo, Brazil and Bahia, Brazil.The towns with the closest growing climate to Mangaratiba are Macaé, Brazil (99% match), Guapimirim and Rio de Janeiro. About 1.6 million km² of land in 30 countries matches 80% or better, most of it in Mato Grosso do Sul, Brazil, São Paulo, Brazil and Bahia, Brazil.

Your growing climate

Zone 11b · No frost · 0 chill hours · 57 in rainZone 11b · No frost · 0 chill hours · 1,449 mm rain

What grows in Mangaratiba →

Regions with the most land like yours

  1. 1

    🇧🇷Mato Grosso do Sul, Brazil

    74k sq mi190k km² matching 80% or better

    For example Itaporã (94), Fátima do Sul (94)

  2. 2

    🇧🇷São Paulo, Brazil

    51k sq mi131k km² matching 80% or better

    For example Peruíbe (94), Miracatu (94)

  3. 3

    🇧🇷Bahia, Brazil

    33k sq mi84k km² matching 80% or better

    For example Posto da Mata (96), Guaratinga (95)

  4. 4

    🇺🇸Florida, United States

    15k sq mi39k km² matching 80% or better

    For example Port Saint Lucie (87), Florida Ridge (86)

  5. 5

    🇵🇪San Martín Department, Peru

    13k sq mi33k km² matching 80% or better

    For example Rioja (91), Moyobamba (89)

  6. 6

    🇲🇽Veracruz, Mexico

    8,700 sq mi23k km² matching 80% or better

    For example Tlapacoyan (91), Misantla (90)

  7. 7

    🇨🇩Maniema, Democratic Republic of the Congo

    8,700 sq mi22k km² matching 80% or better

    For example Kampene (82), Kindu (80)

  8. 8

    🇧🇴Santa Cruz Department, Bolivia

    8,000 sq mi21k km² matching 80% or better

    For example Villa Yapacaní (84), El Torno (82)

  9. 9

    🇿🇦KwaZulu-Natal, South Africa

    6,500 sq mi17k km² matching 80% or better

    For example Mtubatuba (92), Richards Bay (91)

  10. 10

    🇵🇾Concepción, Paraguay

    6,300 sq mi16k km² matching 80% or better

    For example Yby Yaú (88), Concepción (77)

  11. 11

    🇵🇾Caaguazú Department, Paraguay

    6,200 sq mi16k km² matching 80% or better

    For example Coronel Oviedo (82), Doctor Juan Eulogio Estigarribia (81)

  12. 12

    🇨🇩Sankuru, Democratic Republic of the Congo

    6,000 sq mi15k km² matching 80% or better

    For example Lodja (80), Lukula (80)

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

    🇧🇷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 22 of your 25 great-fit crops

    99%match
  2. 2

    🇧🇷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 25 of your 25 great-fit crops

    99%match
  3. 3

    🇧🇷Rio de JaneiroBrazil

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

    Shares 21 of your 25 great-fit crops

    99%match
  4. 4

    🇧🇷SerraEspírito Santo, Brazil

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

    Shares 23 of your 25 great-fit crops

    98%match
  5. 5

    🇧🇷Casimiro de AbreuRio de Janeiro, Brazil

    Zone 11b · No frost · 0 chill hours · 46 in rainZone 11b · No frost · 0 chill hours · 1,177 mm rain

    Shares 21 of your 25 great-fit crops

    98%match
  6. 6

    🇧🇷PinheirosEspírito Santo, Brazil

    Zone 12a · No frost · 0 chill hours · 43 in rainZone 12a · No frost · 0 chill hours · 1,089 mm rain

    Shares 21 of your 25 great-fit crops

    97%match
  7. 7

    🇧🇷QuissamãRio de Janeiro, Brazil

    Zone 12a · No frost · 0 chill hours · 42 in rainZone 12a · No frost · 0 chill hours · 1,071 mm rain

    Shares 20 of your 25 great-fit crops

    97%match
  8. 8

    🇧🇷Nova VenéciaEspírito Santo, Brazil

    Zone 12a · No frost · 0 chill hours · 41 in rainZone 12a · No frost · 0 chill hours · 1,051 mm rain

    Shares 21 of your 25 great-fit crops

    97%match
  9. 9

    🇧🇷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 21 of your 25 great-fit crops

    97%match
  10. 10

    🇧🇷LinharesEspírito Santo, Brazil

    Zone 12a · No frost · 0 chill hours · 45 in rainZone 12a · No frost · 0 chill hours · 1,131 mm rain

    Shares 21 of your 25 great-fit crops

    96%match
  11. 11

    🇧🇷GuarapariEspírito Santo, Brazil

    Zone 12a · No frost · 0 chill hours · 43 in rainZone 12a · No frost · 0 chill hours · 1,104 mm rain

    Shares 21 of your 25 great-fit crops

    96%match
  12. 12

    🇧🇷Cachoeiro de ItapemirimEspírito Santo, Brazil

    Zone 11b · No frost · 0 chill hours · 42 in rainZone 11b · No frost · 0 chill hours · 1,057 mm rain

    Shares 20 of your 25 great-fit crops

    96%match
  13. 13

    🇧🇷Posto da MataBahia, Brazil

    Zone 12a · No frost · 0 chill hours · 47 in rainZone 12a · No frost · 0 chill hours · 1,199 mm rain

    Shares 21 of your 25 great-fit crops

    96%match
  14. 14

    🇧🇷ColatinaEspírito Santo, Brazil

    Zone 12a · No frost · 0 chill hours · 42 in rainZone 12a · No frost · 0 chill hours · 1,062 mm rain

    Shares 20 of your 25 great-fit crops

    96%match
  15. 15

    🇧🇷PancasEspírito Santo, Brazil

    Zone 11b · No frost · 0 chill hours · 42 in rainZone 11b · No frost · 0 chill hours · 1,057 mm rain

    Shares 20 of your 25 great-fit crops

    95%match
  16. 16

    🇧🇷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 21 of your 25 great-fit crops

    95%match
  17. 17

    🇧🇷EcoporangaEspírito Santo, Brazil

    Zone 12a · No frost · 0 chill hours · 40 in rainZone 12a · No frost · 0 chill hours · 1,013 mm rain

    Shares 19 of your 25 great-fit crops

    94%match
  18. 18

    🇧🇷Barra de São FranciscoEspírito Santo, Brazil

    Zone 11b · No frost · 0 chill hours · 40 in rainZone 11b · No frost · 0 chill hours · 1,022 mm rain

    Shares 20 of your 25 great-fit crops

    94%match
  19. 19

    🇧🇷MiracatuSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 65 in rainZone 11b · No frost · 0 chill hours · 1,643 mm rain

    Shares 23 of your 25 great-fit crops

    94%match
  20. 20

    🇧🇷RosanaSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 47 in rainZone 11b · No frost · 0 chill hours · 1,182 mm rain

    Shares 23 of your 25 great-fit crops

    94%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 Mangaratiba: 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.