Climatch

Land with a climate like Seropédica

🇧🇷Seropédica, Rio de Janeiro, Brazil

The towns with the closest growing climate to Seropédica are Macaé, Brazil (99% match), Casimiro de Abreu and Nova Venécia. About 703,000 sq mi of land in 23 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 Seropédica are Macaé, Brazil (99% match), Casimiro de Abreu and Nova Venécia. About 1.8 million km² of land in 23 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 · 55 in rainZone 11b · No frost · 0 chill hours · 1,389 mm rain

What grows in Seropédica →

Regions with the most land like yours

  1. 1

    🇧🇷Mato Grosso do Sul, Brazil

    95k sq mi246k km² matching 80% or better

    For example Itaporã (95), Nova Andradina (94)

  2. 2

    🇧🇷São Paulo, Brazil

    60k sq mi156k km² matching 80% or better

    For example Rosana (95), Presidente Epitácio (94)

  3. 3

    🇧🇷Bahia, Brazil

    32k sq mi83k km² matching 80% or better

    For example Itanhém (97), Medeiros Neto (96)

  4. 4

    🇺🇸Florida, United States

    20k sq mi51k km² matching 80% or better

    For example Port Saint Lucie (88), Belle Glade (88)

  5. 5

    🇧🇴Santa Cruz Department, Bolivia

    19k sq mi50k km² matching 80% or better

    For example Villa Yapacaní (88), El Torno (87)

  6. 6

    🇵🇪San Martín Department, Peru

    10k sq mi27k km² matching 80% or better

    For example Rioja (89), Moyobamba (86)

  7. 7

    🇲🇽Veracruz, Mexico

    9,800 sq mi25k km² matching 80% or better

    For example Coatzintla (89), Cerro Azul (87)

  8. 8

    🇨🇩Maniema, Democratic Republic of the Congo

    9,600 sq mi25k km² matching 80% or better

    For example Kampene (83), Kindu (81)

  9. 9

    🇵🇾Concepción, Paraguay

    8,200 sq mi21k km² matching 80% or better

    For example Yby Yaú (91), Concepción (82)

  10. 10

    🇧🇴Beni Department, Bolivia

    8,100 sq mi21k km² matching 80% or better

    For example Trinidad (79), San Borja (76)

  11. 11

    🇨🇩Sankuru, Democratic Republic of the Congo

    7,200 sq mi19k km² matching 80% or better

    For example Lodja (82), Lukula (82)

  12. 12

    🇵🇪Ucayali, Peru

    5,600 sq mi14k km² matching 80% or better

    For example Atalaya (82), San Fernando (69)

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 24 great-fit crops

    99%match
  2. 2

    🇧🇷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 24 great-fit crops

    99%match
  3. 3

    🇧🇷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 24 great-fit crops

    99%match
  4. 4

    🇧🇷ItaboraíRio de Janeiro, Brazil

    Zone 11b · No frost · 0 chill hours · 45 in rainZone 11b · No frost · 0 chill hours · 1,131 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  5. 5

    🇧🇷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 24 great-fit crops

    99%match
  6. 6

    🇧🇷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 24 great-fit crops

    99%match
  7. 7

    🇧🇷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 24 great-fit crops

    99%match
  8. 8

    🇧🇷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 24 great-fit crops

    99%match
  9. 9

    🇧🇷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 24 great-fit crops

    98%match
  10. 10

    🇧🇷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 24 great-fit crops

    98%match
  11. 11

    🇧🇷CariacicaEspírito Santo, Brazil

    Zone 12a · No frost · 0 chill hours · 46 in rainZone 12a · No frost · 0 chill hours · 1,171 mm rain

    Shares 22 of your 24 great-fit crops

    98%match
  12. 12

    🇧🇷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: potato

    97%match
  13. 13

    🇧🇷NanuqueMinas Gerais, Brazil

    Zone 12a · No frost · 0 chill hours · 40 in rainZone 12a · No frost · 0 chill hours · 1,012 mm rain

    Shares 19 of your 24 great-fit crops

    97%match
  14. 14

    🇧🇷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 24 great-fit crops

    97%match
  15. 15

    🇧🇷Baixo GuanduEspírito Santo, Brazil

    Zone 12a · No frost · 0 chill hours · 40 in rainZone 12a · No frost · 0 chill hours · 1,025 mm rain

    Shares 18 of your 24 great-fit crops

    97%match
  16. 16

    🇧🇷AraruamaRio de Janeiro, Brazil

    Zone 12a · No frost · 0 chill hours · 43 in rainZone 12a · No frost · 0 chill hours · 1,103 mm rain

    Shares 22 of your 24 great-fit crops

    97%match
  17. 17

    🇧🇷MutumMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 42 in rainZone 11b · No frost · 0 chill hours · 1,061 mm rain

    Shares 20 of your 24 great-fit crops

    96%match
  18. 18

    🇧🇷Medeiros NetoBahia, Brazil

    Zone 12a · No frost · 0 chill hours · 38 in rainZone 12a · No frost · 0 chill hours · 975 mm rain

    Shares 19 of your 24 great-fit crops · Also great there: table and raisin grapes

    96%match
  19. 19

    🇧🇷São FidélisRio de Janeiro, Brazil

    Zone 11b · No frost · 0 chill hours · 39 in rainZone 11b · No frost · 0 chill hours · 1,001 mm rain

    Shares 19 of your 24 great-fit crops

    96%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 21 of your 24 great-fit crops

    96%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 Seropédica: 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.