Climatch

Land with a climate like Itacoatiara

🇧🇷Itacoatiara, Amazonas, Brazil

The towns with the closest growing climate to Itacoatiara are Urucará, Brazil (99% match), Oriximiná and Autazes. About 1.5 million sq mi of land in 24 countries matches 80% or better, most of it in Amazonas, Brazil, Pará, Brazil and Central Kalimantan, Indonesia.The towns with the closest growing climate to Itacoatiara are Urucará, Brazil (99% match), Oriximiná and Autazes. About 4.0 million km² of land in 24 countries matches 80% or better, most of it in Amazonas, Brazil, Pará, Brazil and Central Kalimantan, Indonesia.

Your growing climate

Zone 13b · No frost · 0 chill hours · 86 in rainZone 13b · No frost · 0 chill hours · 2,191 mm rain

What grows in Itacoatiara →

Regions with the most land like yours

  1. 1

    🇧🇷Amazonas, Brazil

    194k sq mi503k km² matching 80% or better

    For example Urucará (99), Autazes (99)

  2. 2

    🇧🇷Pará, Brazil

    171k sq mi444k km² matching 80% or better

    For example Oriximiná (99), Terra Santa (99)

  3. 3

    🇮🇩Central Kalimantan, Indonesia

    26k sq mi67k km² matching 80% or better

    For example Kualakapuas (91), Palangkaraya (88)

  4. 4

    🇵🇭Mimaropa, Philippines

    26k sq mi66k km² matching 80% or better

    For example Mamburao (91), Victoria (91)

  5. 5

    🇵🇪Loreto, Peru

    23k sq mi59k km² matching 80% or better

    For example Yurimaguas (92), Contamana (88)

  6. 6

    🇧🇷Maranhão, Brazil

    19k sq mi49k km² matching 80% or better

    For example Santa Luzia do Paruá (93), Zé Doca (92)

  7. 7

    🇮🇩South Sumatra, Indonesia

    17k sq mi43k km² matching 80% or better

    For example Baturaja (88), Palembang (87)

  8. 8

    🇵🇭Central Visayas, Philippines

    14k sq mi35k km² matching 80% or better

    For example Santa Catalina (96), Bayawan (95)

  9. 9

    🇮🇩Jambi, Indonesia

    13k sq mi35k km² matching 80% or better

    For example Jambi City (84), Simpang (83)

  10. 10

    🇵🇭Western Visayas, Philippines

    13k sq mi34k km² matching 80% or better

    For example Iloilo (95), Kabankalan (95)

  11. 11

    🇵🇪Ucayali, Peru

    9,500 sq mi24k km² matching 80% or better

    For example San Fernando (87), Pucallpa (84)

  12. 12

    🇧🇴Beni Department, Bolivia

    7,900 sq mi20k km² matching 80% or better

    For example San Borja (83), Guayaramerín (82)

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

    🇧🇷UrucaráAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 81 in rainZone 13b · No frost · 0 chill hours · 2,061 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  2. 2

    🇧🇷OriximináPará, Brazil

    Zone 13b · No frost · 0 chill hours · 92 in rainZone 13b · No frost · 0 chill hours · 2,334 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  3. 3

    🇧🇷AutazesAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 90 in rainZone 13b · No frost · 0 chill hours · 2,296 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  4. 4

    🇧🇷ManausAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 92 in rainZone 13b · No frost · 0 chill hours · 2,341 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  5. 5

    🇧🇷NhamundáAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 95 in rainZone 13b · No frost · 0 chill hours · 2,424 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  6. 6

    🇧🇷MauésAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 79 in rainZone 13b · No frost · 0 chill hours · 1,998 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  7. 7

    🇧🇷ParintinsAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 98 in rainZone 13b · No frost · 0 chill hours · 2,480 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  8. 8

    🇧🇷ItaitubaPará, Brazil

    Zone 13a · No frost · 0 chill hours · 79 in rainZone 13a · No frost · 0 chill hours · 2,016 mm rain

    Shares 16 of your 17 great-fit crops

    99%match
  9. 9

    🇧🇷CareiroAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 88 in rainZone 13b · No frost · 0 chill hours · 2,234 mm rain

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

    99%match
  10. 10

    🇧🇷BorbaAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 80 in rainZone 13b · No frost · 0 chill hours · 2,036 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  11. 11

    🇧🇷Rio Preto da EvaAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 97 in rainZone 13b · No frost · 0 chill hours · 2,470 mm rain

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

    99%match
  12. 12

    🇧🇷ManacapuruAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 87 in rainZone 13b · No frost · 0 chill hours · 2,211 mm rain

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

    99%match
  13. 13

    🇧🇷BarreirinhaAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 103 in rainZone 13b · No frost · 0 chill hours · 2,616 mm rain

    Shares 16 of your 17 great-fit crops

    99%match
  14. 14

    🇧🇷AveiroPará, Brazil

    Zone 13a · No frost · 0 chill hours · 76 in rainZone 13a · No frost · 0 chill hours · 1,931 mm rain

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

    99%match
  15. 15

    🇧🇷AcaráPará, Brazil

    Zone 13b · No frost · 0 chill hours · 90 in rainZone 13b · No frost · 0 chill hours · 2,277 mm rain

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

    99%match
  16. 16

    🇧🇷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 17 great-fit crops

    99%match
  17. 17

    🇧🇷Novo AirãoAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 93 in rainZone 13b · No frost · 0 chill hours · 2,361 mm rain

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

    99%match
  18. 18

    🇧🇷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 17 of your 17 great-fit crops · Also great there: macadamia, strawberry

    99%match
  19. 19

    🇧🇷AbaetetubaPará, Brazil

    Zone 13b · No frost · 0 chill hours · 105 in rainZone 13b · No frost · 0 chill hours · 2,669 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: macadamia

    99%match
  20. 20

    🇧🇷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 17 great-fit crops

    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 Itacoatiara: 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.