Climatch

Land with a climate like Maués

🇧🇷Maués, Amazonas, Brazil

The towns with the closest growing climate to Maués are Borba, Brazil (99% match), Autazes and Rio Preto da Eva. About 1.9 million sq mi of land in 26 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 Maués are Borba, Brazil (99% match), Autazes and Rio Preto da Eva. About 4.9 million km² of land in 26 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 · 79 in rainZone 13b · No frost · 0 chill hours · 1,998 mm rain

What grows in Maués →

Regions with the most land like yours

  1. 1

    🇧🇷Amazonas, Brazil

    198k sq mi513k km² matching 80% or better

    For example Nova Olinda do Norte (99), Borba (99)

  2. 2

    🇧🇷Pará, Brazil

    153k sq mi395k km² matching 80% or better

    For example Itaituba (99), Oriximiná (99)

  3. 3

    🇮🇩Central Kalimantan, Indonesia

    27k sq mi71k km² matching 80% or better

    For example Kualakapuas (93), Sampit (92)

  4. 4

    🇵🇪Loreto, Peru

    25k sq mi66k km² matching 80% or better

    For example Yurimaguas (95), Requena (93)

  5. 5

    🇮🇩Jambi, Indonesia

    19k sq mi50k km² matching 80% or better

    For example Jambi City (90), Simpang (89)

  6. 6

    🇵🇭Mimaropa, Philippines

    19k sq mi50k km² matching 80% or better

    For example Calapan (92), Victoria (92)

  7. 7

    🇧🇷Acre, Brazil

    19k sq mi48k km² matching 80% or better

    For example Mâncio Lima (86), Rio Branco (84)

  8. 8

    🇮🇩South Sumatra, Indonesia

    18k sq mi47k km² matching 80% or better

    For example Baturaja (91), Palembang (91)

  9. 9

    🇵🇭Western Visayas, Philippines

    14k sq mi36k km² matching 80% or better

    For example Mansilingan (95), Maao (95)

  10. 10

    🇵🇭Central Visayas, Philippines

    14k sq mi36k km² matching 80% or better

    For example Bais (96), Tanjay (96)

  11. 11

    🇵🇪Ucayali, Peru

    11k sq mi28k km² matching 80% or better

    For example San Fernando (90), Pucallpa (87)

  12. 12

    🇨🇩Tshopo, Democratic Republic of the Congo

    10k sq mi27k km² matching 80% or better

    For example Basoko (85), Kisangani (84)

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

    🇧🇷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
  2. 2

    🇧🇷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
  3. 3

    🇧🇷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
  4. 4

    🇧🇷ItacoatiaraAmazonas, Brazil

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

    Shares 17 of your 17 great-fit crops

    99%match
  5. 5

    🇧🇷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
  6. 6

    🇧🇷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
  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

    🇧🇷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
  9. 9

    🇧🇷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
  10. 10

    🇧🇷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
  11. 11

    🇧🇷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
  12. 12

    🇧🇷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
  13. 13

    🇧🇷Presidente FigueiredoAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 99 in rainZone 13b · No frost · 0 chill hours · 2,503 mm rain

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

    99%match
  14. 14

    🇧🇷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
  15. 15

    🇧🇷BeruriAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 99 in rainZone 13b · No frost · 0 chill hours · 2,502 mm rain

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

    99%match
  16. 16

    🇧🇷Novo AripuanãAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 98 in rainZone 13b · No frost · 0 chill hours · 2,478 mm rain

    Shares 17 of your 17 great-fit crops

    98%match
  17. 17

    🇧🇷BelémPará, Brazil

    Zone 13b · No frost · 0 chill hours · 107 in rainZone 13b · No frost · 0 chill hours · 2,707 mm rain

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

    97%match
  18. 18

    🇧🇷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

    97%match
  19. 19

    🇧🇷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

    97%match
  20. 20

    🇧🇷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

    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 Maués: 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.