Climatch

Land with a climate like Monte Alegre, Brazil

🇧🇷Monte Alegre, Pará, Brazil

The towns with the closest growing climate to Monte Alegre, Brazil are Santarém, Brazil (99% match), Pedro do Rosário and Almeirim. About 399,000 sq mi of land in 7 countries matches 80% or better, most of it in Pará, Brazil, Amazonas, Brazil and Maranhão, Brazil.The towns with the closest growing climate to Monte Alegre, Brazil are Santarém, Brazil (99% match), Pedro do Rosário and Almeirim. About 1.0 million km² of land in 7 countries matches 80% or better, most of it in Pará, Brazil, Amazonas, Brazil and Maranhão, Brazil.

Your growing climate

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

What grows in Monte Alegre, Brazil →

Regions with the most land like yours

  1. 1

    🇧🇷Pará, Brazil

    165k sq mi428k km² matching 80% or better

    For example Santarém (99), Almeirim (99)

  2. 2

    🇧🇷Amazonas, Brazil

    44k sq mi114k km² matching 80% or better

    For example Nhamundá (94), Urucará (93)

  3. 3

    🇧🇷Maranhão, Brazil

    42k sq mi108k km² matching 80% or better

    For example Pedro do Rosário (99), Matinha (99)

  4. 4

    🇵🇭Mimaropa, Philippines

    13k sq mi33k km² matching 80% or better

    For example Narra (90), Puerto Princesa (90)

  5. 5

    🇮🇩Southeast Sulawesi, Indonesia

    8,900 sq mi23k km² matching 80% or better

    For example Raha (84), Katobu (83)

  6. 6

    🇵🇭Calabarzon, Philippines

    5,800 sq mi15k km² matching 80% or better

    For example San Pascual (86), Bauan (86)

  7. 7

    🇮🇩East Java, Indonesia

    2,100 sq mi5,400 km² matching 80% or better

    For example Bangkalan (81), Sumenep (80)

  8. 8

    🇵🇭Central Visayas, Philippines

    2,100 sq mi5,300 km² matching 80% or better

    For example Compostela (82), Liloan (82)

  9. 9

    🇮🇩Central Sulawesi, Indonesia

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

    For example Luwuk (80), Bungku (67)

  10. 10

    🇹🇿Pwani, Tanzania

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

    For example Kilindoni (83), Vikindu (73)

  11. 11

    🇹🇭Surat Thani, Thailand

    900 sq mi2,300 km² matching 80% or better

    For example Tha Kham (81), Surat Thani (81)

  12. 12

    🇵🇬Western Province, Papua New Guinea

    600 sq mi1,500 km² matching 80% or better

    For example Daru (75)

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

    🇧🇷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
  2. 2

    🇧🇷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

    99%match
  3. 3

    🇧🇷AlmeirimPará, Brazil

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

    Shares 18 of your 18 great-fit crops

    99%match
  4. 4

    🇧🇷ÓbidosPará, Brazil

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

    Shares 17 of your 18 great-fit crops

    98%match
  5. 5

    🇧🇷Zé DocaMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 72 in rainZone 13a · No frost · 0 chill hours · 1,835 mm rain

    Shares 17 of your 18 great-fit crops · Also great there: strawberry

    98%match
  6. 6

    🇧🇷VianaMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 69 in rainZone 13a · No frost · 0 chill hours · 1,764 mm rain

    Shares 16 of your 18 great-fit crops

    98%match
  7. 7

    🇧🇷JurutiPará, Brazil

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

    Shares 17 of your 18 great-fit crops

    98%match
  8. 8

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

    97%match
  9. 9

    🇧🇷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 17 of your 18 great-fit crops

    97%match
  10. 10

    🇧🇷RosárioMaranhão, Brazil

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

    Shares 17 of your 18 great-fit crops

    97%match
  11. 11

    🇧🇷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

    97%match
  12. 12

    🇧🇷TuriaçuMaranhão, Brazil

    Zone 13b · No frost · 0 chill hours · 80 in rainZone 13b · No frost · 0 chill hours · 2,044 mm rain

    Shares 15 of your 18 great-fit crops · Also great there: strawberry

    97%match
  13. 13

    🇧🇷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

    96%match
  14. 14

    🇧🇷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

    96%match
  15. 15

    🇧🇷AltamiraPará, Brazil

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

    Shares 17 of your 18 great-fit crops · Also great there: strawberry

    96%match
  16. 16

    🇧🇷AnajatubaMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 62 in rainZone 13a · No frost · 0 chill hours · 1,571 mm rain

    Shares 16 of your 18 great-fit crops

    96%match
  17. 17

    🇧🇷Santa HelenaMaranhão, Brazil

    Zone 13b · No frost · 0 chill hours · 92 in rainZone 13b · No frost · 0 chill hours · 2,343 mm rain

    Shares 15 of your 18 great-fit crops

    96%match
  18. 18

    🇧🇷ParagominasPará, Brazil

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

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

    96%match
  19. 19

    🇧🇷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

    96%match
  20. 20

    🇧🇷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

    96%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 Monte Alegre, Brazil: 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.