Climatch

Land with a climate like Almeirim

🇧🇷Almeirim, Pará, Brazil

The towns with the closest growing climate to Almeirim are Prainha, Brazil (99% match), Laranjal do Jari and Santana. About 517,000 sq mi of land in 5 countries matches 80% or better, most of it in Pará, Brazil, Amazonas, Brazil and Maranhão, Brazil.The towns with the closest growing climate to Almeirim are Prainha, Brazil (99% match), Laranjal do Jari and Santana. About 1.3 million km² of land in 5 countries matches 80% or better, most of it in Pará, Brazil, Amazonas, Brazil and Maranhão, Brazil.

Your growing climate

Zone 13a · No frost · 0 chill hours · 78 in rainZone 13a · No frost · 0 chill hours · 1,991 mm rain

What grows in Almeirim →

Regions with the most land like yours

  1. 1

    🇧🇷Pará, Brazil

    156k sq mi403k km² matching 80% or better

    For example Prainha (99), Gurupá (99)

  2. 2

    🇧🇷Amazonas, Brazil

    86k sq mi222k km² matching 80% or better

    For example Nhamundá (95), Parintins (95)

  3. 3

    🇧🇷Maranhão, Brazil

    26k sq mi68k km² matching 80% or better

    For example Santa Luzia do Paruá (99), Centro Novo do Maranhão (99)

  4. 4

    🇵🇭Mimaropa, Philippines

    14k sq mi37k km² matching 80% or better

    For example Narra (88), Puerto Princesa (87)

  5. 5

    🇵🇭Central Visayas, Philippines

    12k sq mi31k km² matching 80% or better

    For example Compostela (87), Consolacion (87)

  6. 6

    🇮🇩Southeast Sulawesi, Indonesia

    8,600 sq mi22k km² matching 80% or better

    For example Kendari (82), Raha (80)

  7. 7

    🇵🇭Calabarzon, Philippines

    8,400 sq mi22k km² matching 80% or better

    For example Concepcion Ibaba (88), Candelaria (87)

  8. 8

    🇮🇩Central Sulawesi, Indonesia

    6,300 sq mi16k km² matching 80% or better

    For example Luwuk (85), Bungku (81)

  9. 9

    🇮🇩Aceh, Indonesia

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

    For example Langsa (84), Lhokseumawe (83)

  10. 10

    🇹🇭Songkhla, Thailand

    1,800 sq mi4,600 km² matching 80% or better

    For example Sadao (79), Hat Yai (78)

  11. 11

    🇹🇭Narathiwat, Thailand

    1,500 sq mi3,800 km² matching 80% or better

    For example Ra-ngae (79), Su-ngai Kolok (79)

  12. 12

    🇹🇭Yala, Thailand

    1,200 sq mi3,100 km² matching 80% or better

    For example Betong (79), Yala (78)

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

    🇧🇷PrainhaPará, Brazil

    Zone 13a · No frost · 0 chill hours · 70 in rainZone 13a · No frost · 0 chill hours · 1,768 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  2. 2

    🇧🇷Laranjal do JariAmapá, Brazil

    Zone 13a · No frost · 0 chill hours · 95 in rainZone 13a · No frost · 0 chill hours · 2,421 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  3. 3

    🇧🇷SantanaAmapá, Brazil

    Zone 13b · No frost · 0 chill hours · 98 in rainZone 13b · No frost · 0 chill hours · 2,501 mm rain

    Shares 17 of your 18 great-fit crops

    99%match
  4. 4

    🇧🇷GurupáPará, Brazil

    Zone 13a · No frost · 0 chill hours · 93 in rainZone 13a · No frost · 0 chill hours · 2,370 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  5. 5

    🇧🇷Santa Luzia do ParuáMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 89 in rainZone 13a · No frost · 0 chill hours · 2,256 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: strawberry

    99%match
  6. 6

    🇧🇷Capitão PoçoPará, Brazil

    Zone 13a · No frost · 0 chill hours · 86 in rainZone 13a · No frost · 0 chill hours · 2,174 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: strawberry

    99%match
  7. 7

    🇧🇷Governador Nunes FreireMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 92 in rainZone 13a · No frost · 0 chill hours · 2,342 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: strawberry

    99%match
  8. 8

    🇧🇷São Miguel do GuamáPará, Brazil

    Zone 13a · No frost · 0 chill hours · 86 in rainZone 13a · No frost · 0 chill hours · 2,173 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: strawberry

    99%match
  9. 9

    🇧🇷SantarémPará, Brazil

    Zone 13a · No frost · 0 chill hours · 81 in rainZone 13a · No frost · 0 chill hours · 2,045 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: strawberry

    99%match
  10. 10

    🇧🇷Cachoeira do PiriáPará, Brazil

    Zone 13a · No frost · 0 chill hours · 85 in rainZone 13a · No frost · 0 chill hours · 2,159 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: strawberry

    99%match
  11. 11

    🇧🇷AfuáPará, Brazil

    Zone 13b · No frost · 0 chill hours · 94 in rainZone 13b · No frost · 0 chill hours · 2,389 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  12. 12

    🇧🇷CurralinhoPará, Brazil

    Zone 13a · No frost · 0 chill hours · 96 in rainZone 13a · No frost · 0 chill hours · 2,430 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  13. 13

    🇧🇷Monte AlegrePará, Brazil

    Zone 13b · No frost · 0 chill hours · 66 in rainZone 13b · No frost · 0 chill hours · 1,665 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  14. 14

    🇧🇷AnajásPará, Brazil

    Zone 13a · No frost · 0 chill hours · 101 in rainZone 13a · No frost · 0 chill hours · 2,563 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  15. 15

    🇧🇷BagrePará, Brazil

    Zone 13a · No frost · 0 chill hours · 99 in rainZone 13a · No frost · 0 chill hours · 2,515 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  16. 16

    🇧🇷Mãe do RioPará, Brazil

    Zone 13a · No frost · 0 chill hours · 83 in rainZone 13a · No frost · 0 chill hours · 2,096 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: strawberry

    98%match
  17. 17

    🇧🇷Presidente SarneyMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 85 in rainZone 13a · No frost · 0 chill hours · 2,148 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: strawberry

    98%match
  18. 18

    🇧🇷PortelPará, Brazil

    Zone 13a · No frost · 0 chill hours · 97 in rainZone 13a · No frost · 0 chill hours · 2,465 mm rain

    Shares 18 of your 18 great-fit crops

    98%match
  19. 19

    🇧🇷CastanhalPará, Brazil

    Zone 13b · No frost · 0 chill hours · 99 in rainZone 13b · No frost · 0 chill hours · 2,506 mm rain

    Shares 18 of your 18 great-fit crops

    98%match
  20. 20

    🇧🇷Pedro do RosárioMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 75 in rainZone 13a · No frost · 0 chill hours · 1,912 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: strawberry

    98%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 Almeirim: 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.