Climatch

Land with a climate like São Domingos do Capim

🇧🇷São Domingos do Capim, Pará, Brazil

The towns with the closest growing climate to São Domingos do Capim are Anajás, Brazil (99% match), Limoeiro do Ajuru and Capitão Poço. About 870,000 sq mi of land in 15 countries matches 80% or better, most of it in Pará, Brazil, Amazonas, Brazil and Maranhão, Brazil.The towns with the closest growing climate to São Domingos do Capim are Anajás, Brazil (99% match), Limoeiro do Ajuru and Capitão Poço. About 2.3 million km² of land in 15 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 · 87 in rainZone 13b · No frost · 0 chill hours · 2,222 mm rain

What grows in São Domingos do Capim →

Regions with the most land like yours

  1. 1

    🇧🇷Pará, Brazil

    160k sq mi414k km² matching 80% or better

    For example Garrafão do Norte (99), Nova Esperança do Piriá (99)

  2. 2

    🇧🇷Amazonas, Brazil

    108k sq mi280k km² matching 80% or better

    For example Urucurituba (97), Parintins (97)

  3. 3

    🇧🇷Maranhão, Brazil

    24k sq mi61k km² matching 80% or better

    For example Centro Novo do Maranhão (99), Maranhãozinho (99)

  4. 4

    🇵🇭Mimaropa, Philippines

    17k sq mi45k km² matching 80% or better

    For example Puerto Princesa (87), Narra (86)

  5. 5

    🇮🇩Central Kalimantan, Indonesia

    16k sq mi42k km² matching 80% or better

    For example Kualakapuas (83), Sampit (80)

  6. 6

    🇵🇭Central Visayas, Philippines

    13k sq mi34k km² matching 80% or better

    For example Compostela (87), Santa Catalina (86)

  7. 7

    🇮🇩Central Sulawesi, Indonesia

    12k sq mi32k km² matching 80% or better

    For example Bungku (85), Luwuk (85)

  8. 8

    🇵🇭Western Visayas, Philippines

    12k sq mi30k km² matching 80% or better

    For example Passi (86), Iloilo (86)

  9. 9

    🇮🇩Southeast Sulawesi, Indonesia

    11k sq mi29k km² matching 80% or better

    For example Kendari (86), Raha (79)

  10. 10

    🇨🇩Équateur, Democratic Republic of the Congo

    9,600 sq mi25k km² matching 80% or better

    For example Basankusu (82), Mbandaka (81)

  11. 11

    🇨🇩Tshopo, Democratic Republic of the Congo

    6,300 sq mi16k km² matching 80% or better

    For example Basoko (80), Kisangani (78)

  12. 12

    🇲🇾Kedah, Malaysia

    6,200 sq mi16k km² matching 80% or better

    For example Sik (86), Gurun (86)

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

    🇧🇷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
  2. 2

    🇧🇷Limoeiro do AjuruPará, Brazil

    Zone 13a · No frost · 0 chill hours · 98 in rainZone 13a · No frost · 0 chill hours · 2,491 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  3. 3

    🇧🇷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
  4. 4

    🇧🇷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
  5. 5

    🇧🇷AbaetetubaPará, Brazil

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

    Shares 17 of your 18 great-fit crops

    99%match
  6. 6

    🇧🇷CametáPará, Brazil

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

    Shares 18 of your 18 great-fit crops

    99%match
  7. 7

    🇧🇷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
  8. 8

    🇧🇷MuanáPará, Brazil

    Zone 13b · No frost · 0 chill hours · 108 in rainZone 13b · No frost · 0 chill hours · 2,752 mm rain

    Shares 16 of your 18 great-fit crops

    99%match
  9. 9

    🇧🇷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

    99%match
  10. 10

    🇧🇷VigiaPará, Brazil

    Zone 13b · No frost · 0 chill hours · 113 in rainZone 13b · No frost · 0 chill hours · 2,863 mm rain

    Shares 15 of your 18 great-fit crops

    99%match
  11. 11

    🇧🇷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
  12. 12

    🇧🇷Cachoeira do ArariPará, Brazil

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

    Shares 17 of your 18 great-fit crops

    99%match
  13. 13

    🇧🇷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
  14. 14

    🇧🇷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
  15. 15

    🇧🇷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
  16. 16

    🇧🇷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
  17. 17

    🇧🇷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

    99%match
  18. 18

    🇧🇷Porto de MozPará, Brazil

    Zone 13a · No frost · 0 chill hours · 95 in rainZone 13a · No frost · 0 chill hours · 2,412 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  19. 19

    🇧🇷BelémPará, Brazil

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

    Shares 17 of your 18 great-fit crops

    99%match
  20. 20

    🇧🇷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

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 São Domingos do Capim: 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.