Climatch

Land with a climate like Pinheiral

🇧🇷Pinheiral, Rio de Janeiro, Brazil

The towns with the closest growing climate to Pinheiral are Três Rios, Brazil (99% match), Além Paraíba and Afonso Cláudio. About 411,000 sq mi of land in 14 countries matches 80% or better, most of it in Minas Gerais, Brazil, São Paulo, Brazil and Mato Grosso do Sul, Brazil.The towns with the closest growing climate to Pinheiral are Três Rios, Brazil (99% match), Além Paraíba and Afonso Cláudio. About 1.1 million km² of land in 14 countries matches 80% or better, most of it in Minas Gerais, Brazil, São Paulo, Brazil and Mato Grosso do Sul, Brazil.

Your growing climate

Zone 11a · No frost · 2 chill hours · 52 in rainZone 11a · No frost · 2 chill hours · 1,331 mm rain

What grows in Pinheiral →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    108k sq mi280k km² matching 80% or better

    For example Lajinha (99), Além Paraíba (99)

  2. 2

    🇧🇷São Paulo, Brazil

    82k sq mi214k km² matching 80% or better

    For example Taubaté (99), Caçapava (99)

  3. 3

    🇧🇷Mato Grosso do Sul, Brazil

    41k sq mi106k km² matching 80% or better

    For example Nova Andradina (87), Aparecida do Taboado (86)

  4. 4

    🇨🇳Yunnan, China

    8,300 sq mi22k km² matching 80% or better

    For example Mengzi (81), Mengla (80)

  5. 5

    🇿🇦KwaZulu-Natal, South Africa

    8,100 sq mi21k km² matching 80% or better

    For example Mandeni (88), Tongaat (87)

  6. 6

    🇻🇳Điện Biên Province, Vietnam

    7,000 sq mi18k km² matching 80% or better

    For example Mường Lay (81), Dien Bien Phu (73)

  7. 7

    🇱🇦Oudômxai, Laos

    4,500 sq mi12k km² matching 80% or better

    For example Muang Xay (80)

  8. 8

    🇱🇦Xiangkhoang, Laos

    3,900 sq mi10k km² matching 80% or better

    For example Muang Phônsavan (79)

  9. 9

    🇻🇳Sơn La Province, Vietnam

    3,900 sq mi10k km² matching 80% or better

    For example Chiềng Cơi (89), Thị Trấn Thuận Châu (89)

  10. 10

    🇱🇦Houaphan, Laos

    3,400 sq mi8,700 km² matching 80% or better

    For example Xam Nua (82)

  11. 11

    🇲🇿Maputo Province, Mozambique

    3,000 sq mi7,700 km² matching 80% or better

    For example Manhiça (84), Matola (77)

  12. 12

    🇻🇳Nghệ An Province, Vietnam

    2,800 sq mi7,300 km² matching 80% or better

    For example Bản Na Hỷ (76), Thái Hòa (55)

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

    🇧🇷Três RiosRio de Janeiro, Brazil

    Zone 11a · No frost · 0 chill hours · 56 in rainZone 11a · No frost · 0 chill hours · 1,417 mm rain

    Shares 24 of your 24 great-fit crops

    99%match
  2. 2

    🇧🇷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

    99%match
  3. 3

    🇧🇷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
  4. 4

    🇧🇷CarangolaMinas Gerais, Brazil

    Zone 11a · No frost · 4 chill hours · 46 in rainZone 11a · No frost · 4 chill hours · 1,165 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  5. 5

    🇧🇷CruzeiroSão Paulo, Brazil

    Zone 11a · No frost · 2 chill hours · 56 in rainZone 11a · No frost · 2 chill hours · 1,416 mm rain

    Shares 24 of your 24 great-fit crops

    99%match
  6. 6

    🇧🇷CaratingaMinas Gerais, Brazil

    Zone 11a · No frost · 8 chill hours · 45 in rainZone 11a · No frost · 8 chill hours · 1,136 mm rain

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

    99%match
  7. 7

    🇧🇷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

    99%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 24 great-fit crops

    98%match
  9. 9

    🇧🇷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

    98%match
  10. 10

    🇧🇷Juiz de ForaMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 54 in rainZone 11a · No frost · 0 chill hours · 1,384 mm rain

    Shares 22 of your 24 great-fit crops

    98%match
  11. 11

    🇧🇷IúnaEspírito Santo, Brazil

    Zone 11a · No frost · 10 chill hours · 45 in rainZone 11a · No frost · 10 chill hours · 1,155 mm rain

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

    98%match
  12. 12

    🇧🇷AparecidaSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 52 in rainZone 11a · No frost · 0 chill hours · 1,313 mm rain

    Shares 22 of your 24 great-fit crops

    98%match
  13. 13

    🇧🇷PirangaMinas Gerais, Brazil

    Zone 11a · No frost · 5 chill hours · 50 in rainZone 11a · No frost · 5 chill hours · 1,261 mm rain

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

    97%match
  14. 14

    🇧🇷Lima DuarteMinas Gerais, Brazil

    Zone 11a · No frost · 5 chill hours · 52 in rainZone 11a · No frost · 5 chill hours · 1,327 mm rain

    Shares 21 of your 24 great-fit crops

    97%match
  15. 15

    🇧🇷UbáMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 48 in rainZone 11a · No frost · 0 chill hours · 1,230 mm rain

    Shares 22 of your 24 great-fit crops

    97%match
  16. 16

    🇧🇷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

    97%match
  17. 17

    🇧🇷MaríliaSão Paulo, Brazil

    Zone 11a · No frost · 4 chill hours · 50 in rainZone 11a · No frost · 4 chill hours · 1,273 mm rain

    Shares 23 of your 24 great-fit crops

    97%match
  18. 18

    🇧🇷ConchasSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 46 in rainZone 11a · No frost · 0 chill hours · 1,168 mm rain

    Shares 22 of your 24 great-fit crops

    97%match
  19. 19

    🇧🇷Barão de CocaisMinas Gerais, Brazil

    Zone 11a · No frost · 4 chill hours · 53 in rainZone 11a · No frost · 4 chill hours · 1,358 mm rain

    Shares 22 of your 24 great-fit crops

    97%match
  20. 20

    🇧🇷AngatubaSão Paulo, Brazil

    Zone 11a · No frost · 5 chill hours · 47 in rainZone 11a · No frost · 5 chill hours · 1,187 mm rain

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

    97%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 Pinheiral: 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.