Climatch

Land with a climate like Pindaré-Mirim

🇧🇷Pindaré-Mirim, Maranhão, Brazil

The towns with the closest growing climate to Pindaré-Mirim are Itapecuru Mirim, Brazil (99% match), Vargem Grande and Paragominas. About 602,000 sq mi of land in 18 countries matches 80% or better, most of it in Pará, Brazil, Maranhão, Brazil and Amazonas, Brazil.The towns with the closest growing climate to Pindaré-Mirim are Itapecuru Mirim, Brazil (99% match), Vargem Grande and Paragominas. About 1.6 million km² of land in 18 countries matches 80% or better, most of it in Pará, Brazil, Maranhão, Brazil and Amazonas, Brazil.

Your growing climate

Zone 13a · No frost · 0 chill hours · 72 in rainZone 13a · No frost · 0 chill hours · 1,837 mm rain

What grows in Pindaré-Mirim →

Regions with the most land like yours

  1. 1

    🇧🇷Pará, Brazil

    175k sq mi454k km² matching 80% or better

    For example Paragominas (99), Ulianópolis (98)

  2. 2

    🇧🇷Maranhão, Brazil

    59k sq mi152k km² matching 80% or better

    For example Anajatuba (99), Miranda do Norte (99)

  3. 3

    🇧🇷Amazonas, Brazil

    33k sq mi86k km² matching 80% or better

    For example Nhamundá (92), Urucará (91)

  4. 4

    🇮🇩East Java, Indonesia

    14k sq mi36k km² matching 80% or better

    For example Sampang (92), Bangkalan (92)

  5. 5

    🇻🇪Bolívar, Venezuela

    14k sq mi36k km² matching 80% or better

    For example Ciudad Piar (84), La Paragua (83)

  6. 6

    🇵🇭Mimaropa, Philippines

    11k sq mi28k km² matching 80% or better

    For example Puerto Princesa (86), Narra (86)

  7. 7

    🇻🇪Anzoátegui, Venezuela

    10k sq mi26k km² matching 80% or better

    For example Clarines (86), Puerto Píritu (84)

  8. 8

    🇻🇪Monagas, Venezuela

    10k sq mi26k km² matching 80% or better

    For example Maturín (85), Caripito (84)

  9. 9

    🇮🇩Southeast Sulawesi, Indonesia

    9,800 sq mi25k km² matching 80% or better

    For example Baubau (90), Raha (88)

  10. 10

    🇮🇩Central Java, Indonesia

    9,500 sq mi25k km² matching 80% or better

    For example Dukuhturi (90), Bulakamba (90)

  11. 11

    🇨🇴Córdoba, Colombia

    5,300 sq mi14k km² matching 80% or better

    For example Montería (84), Planeta Rica (83)

  12. 12

    🇲🇽Campeche, Mexico

    4,300 sq mi11k km² matching 80% or better

    For example Ciudad del Carmen (86), Escárcega (77)

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

    🇧🇷Itapecuru MirimMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 63 in rainZone 13a · No frost · 0 chill hours · 1,611 mm rain

    Shares 13 of your 16 great-fit crops

    99%match
  2. 2

    🇧🇷Vargem GrandeMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 78 in rainZone 13a · No frost · 0 chill hours · 1,987 mm rain

    Shares 15 of your 16 great-fit crops

    99%match
  3. 3

    🇧🇷ParagominasPará, Brazil

    Zone 13a · No frost · 0 chill hours · 75 in rainZone 13a · No frost · 0 chill hours · 1,901 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: tea, macadamia, strawberry

    99%match
  4. 4

    🇧🇷RosárioMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 72 in rainZone 13a · No frost · 0 chill hours · 1,817 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: tea

    98%match
  5. 5

    🇧🇷UlianópolisPará, Brazil

    Zone 13a · No frost · 0 chill hours · 68 in rainZone 13a · No frost · 0 chill hours · 1,737 mm rain

    Shares 14 of your 16 great-fit crops

    98%match
  6. 6

    🇧🇷Ipixuna do ParáPará, Brazil

    Zone 13a · No frost · 0 chill hours · 77 in rainZone 13a · No frost · 0 chill hours · 1,948 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: macadamia, tea, strawberry

    97%match
  7. 7

    🇧🇷Tomé-AçuPará, Brazil

    Zone 13a · No frost · 0 chill hours · 83 in rainZone 13a · No frost · 0 chill hours · 2,103 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: macadamia, tea

    97%match
  8. 8

    🇧🇷São Vicente FerrerMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 71 in rainZone 13a · No frost · 0 chill hours · 1,810 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: tea

    97%match
  9. 9

    🇧🇷TailândiaPará, Brazil

    Zone 13a · No frost · 0 chill hours · 92 in rainZone 13a · No frost · 0 chill hours · 2,333 mm rain

    Shares 16 of your 16 great-fit crops

    97%match
  10. 10

    🇧🇷Urbano SantosMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 64 in rainZone 13a · No frost · 0 chill hours · 1,619 mm rain

    Shares 14 of your 16 great-fit crops

    97%match
  11. 11

    🇧🇷BrejoMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 62 in rainZone 13a · No frost · 0 chill hours · 1,584 mm rain

    Shares 13 of your 16 great-fit crops

    96%match
  12. 12

    🇧🇷ÓbidosPará, Brazil

    Zone 13a · No frost · 0 chill hours · 76 in rainZone 13a · No frost · 0 chill hours · 1,924 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: tea

    96%match
  13. 13

    🇧🇷Goianésia do ParáPará, Brazil

    Zone 13a · No frost · 0 chill hours · 85 in rainZone 13a · No frost · 0 chill hours · 2,169 mm rain

    Shares 15 of your 16 great-fit crops

    96%match
  14. 14

    🇧🇷Vitória do XinguPará, Brazil

    Zone 13a · No frost · 0 chill hours · 81 in rainZone 13a · No frost · 0 chill hours · 2,069 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: tea

    96%match
  15. 15

    🇧🇷TucuruíPará, Brazil

    Zone 13a · No frost · 0 chill hours · 94 in rainZone 13a · No frost · 0 chill hours · 2,383 mm rain

    Shares 16 of your 16 great-fit crops

    95%match
  16. 16

    🇧🇷CametáPará, Brazil

    Zone 13a · No frost · 0 chill hours · 93 in rainZone 13a · No frost · 0 chill hours · 2,363 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: tea, macadamia

    95%match
  17. 17

    🇧🇷AlenquerPará, Brazil

    Zone 13a · No frost · 0 chill hours · 64 in rainZone 13a · No frost · 0 chill hours · 1,617 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: macadamia, tea, strawberry

    95%match
  18. 18

    🇧🇷ChapadinhaMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 62 in rainZone 13a · No frost · 0 chill hours · 1,581 mm rain

    Shares 13 of your 16 great-fit crops

    95%match
  19. 19

    🇧🇷AltamiraPará, Brazil

    Zone 13a · No frost · 0 chill hours · 81 in rainZone 13a · No frost · 0 chill hours · 2,059 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: tea, strawberry

    95%match
  20. 20

    🇧🇷JurutiPará, Brazil

    Zone 13b · No frost · 0 chill hours · 83 in rainZone 13b · No frost · 0 chill hours · 2,111 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: tea

    95%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 Pindaré-Mirim: 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.