Climatch

Land with a climate like Guapimirim

🇧🇷Guapimirim, Rio de Janeiro, Brazil

The towns with the closest growing climate to Guapimirim are Conceição de Macabu, Brazil (99% match), Macaé and Araruama. About 433,000 sq mi of land in 28 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 Guapimirim are Conceição de Macabu, Brazil (99% match), Macaé and Araruama. About 1.1 million km² of land in 28 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 · 55 in rainZone 11b · No frost · 0 chill hours · 1,399 mm rain

What grows in Guapimirim →

Regions with the most land like yours

  1. 1

    🇧🇷São Paulo, Brazil

    69k sq mi179k km² matching 80% or better

    For example Tremembé (93), Itariri (93)

  2. 2

    🇧🇷Mato Grosso do Sul, Brazil

    58k sq mi150k km² matching 80% or better

    For example Nova Andradina (90), Itaporã (90)

  3. 3

    🇧🇷Minas Gerais, Brazil

    36k sq mi95k km² matching 80% or better

    For example Mantena (95), Mutum (95)

  4. 4

    🇲🇽Veracruz, Mexico

    9,300 sq mi24k km² matching 80% or better

    For example Córdoba (90), Tlapacoyan (89)

  5. 5

    🇺🇸Florida, United States

    8,300 sq mi21k km² matching 80% or better

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

  6. 6

    🇿🇦KwaZulu-Natal, South Africa

    6,000 sq mi16k km² matching 80% or better

    For example Richards Bay (90), eSikhaleni (90)

  7. 7

    🇵🇪San Martín Department, Peru

    4,700 sq mi12k km² matching 80% or better

    For example Rioja (84), Moyobamba (83)

  8. 8

    🇨🇳Yunnan, China

    4,400 sq mi11k km² matching 80% or better

    For example Mengla (84), Hekou (84)

  9. 9

    🇵🇾Concepción, Paraguay

    4,400 sq mi11k km² matching 80% or better

    For example Yby Yaú (82), Concepción (69)

  10. 10

    🇨🇳Hainan, China

    4,000 sq mi10k km² matching 80% or better

    For example Wuzhishan (82), Yinggen (81)

  11. 11

    🇹🇿Tanga, Tanzania

    3,600 sq mi9,300 km² matching 80% or better

    For example Handeni (87), Chanika (87)

  12. 12

    🇵🇪Junin, Peru

    3,500 sq mi9,100 km² matching 80% or better

    For example Satipo (84), San Martín de Pangoa (83)

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

    🇧🇷Conceição de MacabuRio de Janeiro, Brazil

    Zone 11b · No frost · 0 chill hours · 45 in rainZone 11b · No frost · 0 chill hours · 1,153 mm rain

    Shares 21 of your 25 great-fit crops

    99%match
  2. 2

    🇧🇷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
  3. 3

    🇧🇷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 25 great-fit crops

    99%match
  4. 4

    🇧🇷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 24 of your 25 great-fit crops

    99%match
  5. 5

    🇧🇷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 25 great-fit crops

    98%match
  6. 6

    🇧🇷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

    98%match
  7. 7

    🇧🇷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

    97%match
  8. 8

    🇧🇷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 25 great-fit crops

    97%match
  9. 9

    🇧🇷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

    96%match
  10. 10

    🇧🇷Volta RedondaRio de Janeiro, Brazil

    Zone 11a · No frost · 0 chill hours · 55 in rainZone 11a · No frost · 0 chill hours · 1,397 mm rain

    Shares 24 of your 25 great-fit crops

    96%match
  11. 11

    🇧🇷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
  12. 12

    🇧🇷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 25 great-fit crops

    96%match
  13. 13

    🇧🇷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
  14. 14

    🇧🇷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

    95%match
  15. 15

    🇧🇷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

    95%match
  16. 16

    🇧🇷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 25 great-fit crops

    95%match
  17. 17

    🇧🇷São Francisco de ItabapoanaRio de Janeiro, Brazil

    Zone 12a · No frost · 0 chill hours · 38 in rainZone 12a · No frost · 0 chill hours · 957 mm rain

    Shares 20 of your 25 great-fit crops · Also great there: table and raisin grapes

    95%match
  18. 18

    🇧🇷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

    95%match
  19. 19

    🇧🇷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 25 great-fit crops

    95%match
  20. 20

    🇧🇷Armação dos BúziosRio de Janeiro, Brazil

    Zone 12a · No frost · 0 chill hours · 49 in rainZone 12a · No frost · 0 chill hours · 1,242 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 Guapimirim: 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.