Climatch

Land with a climate like Paracambi

🇧🇷Paracambi, Rio de Janeiro, Brazil

The towns with the closest growing climate to Paracambi are Cachoeiras de Macacu, Brazil (99% match), Afonso Cláudio and Casimiro de Abreu. About 496,000 sq mi of land in 22 countries matches 80% or better, most of it in São Paulo, Brazil, Mato Grosso do Sul, Brazil and Minas Gerais, Brazil.The towns with the closest growing climate to Paracambi are Cachoeiras de Macacu, Brazil (99% match), Afonso Cláudio and Casimiro de Abreu. About 1.3 million km² of land in 22 countries matches 80% or better, most of it in São Paulo, Brazil, Mato Grosso do Sul, Brazil and Minas Gerais, Brazil.

Your growing climate

Zone 11b · No frost · 0 chill hours · 58 in rainZone 11b · No frost · 0 chill hours · 1,481 mm rain

What grows in Paracambi →

Regions with the most land like yours

  1. 1

    🇧🇷São Paulo, Brazil

    80k sq mi206k km² matching 80% or better

    For example Tremembé (97), Taubaté (96)

  2. 2

    🇧🇷Mato Grosso do Sul, Brazil

    68k sq mi177k km² matching 80% or better

    For example Nova Andradina (93), Dourados (92)

  3. 3

    🇧🇷Minas Gerais, Brazil

    61k sq mi158k km² matching 80% or better

    For example Além Paraíba (95), Mutum (95)

  4. 4

    🇺🇸Florida, United States

    9,000 sq mi23k km² matching 80% or better

    For example Florida Ridge (84), Vero Beach South (83)

  5. 5

    🇿🇦KwaZulu-Natal, South Africa

    7,800 sq mi20k km² matching 80% or better

    For example Empangeni (91), eSikhaleni (91)

  6. 6

    🇵🇪Junin, Peru

    5,600 sq mi14k km² matching 80% or better

    For example Satipo (84), San Martín de Pangoa (84)

  7. 7

    🇵🇪San Martín Department, Peru

    5,300 sq mi14k km² matching 80% or better

    For example Rioja (83), Moyobamba (81)

  8. 8

    🇨🇳Yunnan, China

    5,300 sq mi14k km² matching 80% or better

    For example Mengla (83), Hekou (80)

  9. 9

    🇦🇷Corrientes, Argentina

    4,800 sq mi12k km² matching 80% or better

    For example Corrientes (80), Ituzaingó (80)

  10. 10

    🇵🇾Concepción, Paraguay

    4,700 sq mi12k km² matching 80% or better

    For example Yby Yaú (84), Concepción (67)

  11. 11

    🇻🇳Điện Biên Province, Vietnam

    4,400 sq mi12k km² matching 80% or better

    For example Mường Lay (80), Dien Bien Phu (68)

  12. 12

    🇵🇾Caaguazú Department, Paraguay

    4,300 sq mi11k km² matching 80% or better

    For example Doctor Juan Eulogio Estigarribia (80), Caaguazú (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

    🇧🇷Cachoeiras de MacacuRio de Janeiro, Brazil

    Zone 11b · No frost · 0 chill hours · 48 in rainZone 11b · No frost · 0 chill hours · 1,211 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  2. 2

    🇧🇷Afonso CláudioEspírito Santo, Brazil

    Zone 11a · No frost · 0 chill hours · 44 in rainZone 11a · No frost · 0 chill hours · 1,115 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  3. 3

    🇧🇷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

    98%match
  4. 4

    🇧🇷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 23 of your 24 great-fit crops · Also great there: cacao

    98%match
  5. 5

    🇧🇷CasteloEspírito Santo, Brazil

    Zone 11b · No frost · 0 chill hours · 42 in rainZone 11b · No frost · 0 chill hours · 1,079 mm rain

    Shares 21 of your 24 great-fit crops

    97%match
  6. 6

    🇧🇷AlegreEspírito Santo, Brazil

    Zone 11b · No frost · 0 chill hours · 43 in rainZone 11b · No frost · 0 chill hours · 1,093 mm rain

    Shares 21 of your 24 great-fit crops

    97%match
  7. 7

    🇧🇷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 24 great-fit crops

    97%match
  8. 8

    🇧🇷ResendeRio de Janeiro, Brazil

    Zone 11a · No frost · 0 chill hours · 58 in rainZone 11a · No frost · 0 chill hours · 1,461 mm rain

    Shares 24 of your 24 great-fit crops

    97%match
  9. 9

    🇧🇷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

    96%match
  10. 10

    🇧🇷CantagaloRio de Janeiro, Brazil

    Zone 11a · No frost · 3 chill hours · 48 in rainZone 11a · No frost · 3 chill hours · 1,229 mm rain

    Shares 23 of your 24 great-fit crops

    96%match
  11. 11

    🇧🇷São José dos CamposSão Paulo, Brazil

    Zone 11a · No frost · 2 chill hours · 49 in rainZone 11a · No frost · 2 chill hours · 1,244 mm rain

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

    95%match
  12. 12

    🇧🇷Além ParaíbaMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 49 in rainZone 11a · No frost · 0 chill hours · 1,250 mm rain

    Shares 22 of your 24 great-fit crops

    95%match
  13. 13

    🇧🇷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

    95%match
  14. 14

    🇧🇷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 24 great-fit crops

    95%match
  15. 15

    🇧🇷TupãSão Paulo, Brazil

    Zone 11a · No frost · 1 chill hours · 50 in rainZone 11a · No frost · 1 chill hours · 1,267 mm rain

    Shares 23 of your 24 great-fit crops

    94%match
  16. 16

    🇧🇷MuriaéMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 50 in rainZone 11a · No frost · 0 chill hours · 1,280 mm rain

    Shares 21 of your 24 great-fit crops

    94%match
  17. 17

    🇧🇷LinsSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 48 in rainZone 11a · No frost · 0 chill hours · 1,224 mm rain

    Shares 23 of your 24 great-fit crops

    94%match
  18. 18

    🇧🇷ColoradoParaná, Brazil

    Zone 11a · No frost · 0 chill hours · 49 in rainZone 11a · No frost · 0 chill hours · 1,253 mm rain

    Shares 23 of your 24 great-fit crops

    94%match
  19. 19

    🇧🇷Terra RicaParaná, Brazil

    Zone 11a · No frost · 0 chill hours · 47 in rainZone 11a · No frost · 0 chill hours · 1,183 mm rain

    Shares 23 of your 24 great-fit crops

    94%match
  20. 20

    🇧🇷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

    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 Paracambi: 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.