Climatch

Land with a climate like São João do Soter

🇧🇷São João do Soter, Maranhão, Brazil

The towns with the closest growing climate to São João do Soter are Presidente Dutra, Brazil (99% match), Altos and Parnarama. About 205,000 sq mi of land in 12 countries matches 80% or better, most of it in Maranhão, Brazil, Piauí, Brazil and Guárico, Venezuela.The towns with the closest growing climate to São João do Soter are Presidente Dutra, Brazil (99% match), Altos and Parnarama. About 531,000 km² of land in 12 countries matches 80% or better, most of it in Maranhão, Brazil, Piauí, Brazil and Guárico, Venezuela.

Your growing climate

Zone 13a · No frost · 0 chill hours · 50 in rainZone 13a · No frost · 0 chill hours · 1,280 mm rain

What grows in São João do Soter →

Regions with the most land like yours

  1. 1

    🇧🇷Maranhão, Brazil

    81k sq mi211k km² matching 80% or better

    For example Presidente Dutra (99), Matões (99)

  2. 2

    🇧🇷Piauí, Brazil

    32k sq mi83k km² matching 80% or better

    For example José de Freitas (99), Altos (99)

  3. 3

    🇻🇪Guárico, Venezuela

    16k sq mi41k km² matching 80% or better

    For example Valle de La Pascua (87), Tucupido (86)

  4. 4

    🇧🇷Pará, Brazil

    13k sq mi34k km² matching 80% or better

    For example Rondon do Pará (88), Bom Jesus do Tocantins (85)

  5. 5

    🇻🇪Anzoátegui, Venezuela

    8,300 sq mi21k km² matching 80% or better

    For example Pariaguán (86), Aragua de Barcelona (85)

  6. 6

    🇮🇳Andhra Pradesh, India

    7,200 sq mi19k km² matching 80% or better

    For example Pīleru (83), Kuppam (83)

  7. 7

    🇮🇳Tamil Nadu, India

    6,100 sq mi16k km² matching 80% or better

    For example Jalārpet (87), Krishnagiri (86)

  8. 8

    🇻🇪Cojedes, Venezuela

    3,200 sq mi8,400 km² matching 80% or better

    For example San Carlos (83), El Pao (83)

  9. 9

    🇮🇩East Java, Indonesia

    2,700 sq mi6,900 km² matching 80% or better

    For example Mojokerto (87), Soko (87)

  10. 10

    🇹🇿Morogoro, Tanzania

    2,400 sq mi6,100 km² matching 80% or better

    For example Ifakara (80), Kidodi (77)

  11. 11

    🇹🇿Mtwara, Tanzania

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

    For example Lukuledi (86), Nanganga (84)

  12. 12

    🇬🇳Kindia, Guinea

    900 sq mi2,300 km² matching 80% or better

    For example Forécariah (70), Kindia (67)

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

    🇧🇷Presidente DutraMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 45 in rainZone 13a · No frost · 0 chill hours · 1,150 mm rain

    Shares 15 of your 15 great-fit crops

    99%match
  2. 2

    🇧🇷AltosPiauí, Brazil

    Zone 13a · No frost · 0 chill hours · 49 in rainZone 13a · No frost · 0 chill hours · 1,242 mm rain

    Shares 15 of your 15 great-fit crops

    99%match
  3. 3

    🇧🇷ParnaramaMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 47 in rainZone 13a · No frost · 0 chill hours · 1,200 mm rain

    Shares 14 of your 15 great-fit crops

    99%match
  4. 4

    🇧🇷Buriti BravoMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 42 in rainZone 12b · No frost · 0 chill hours · 1,069 mm rain

    Shares 15 of your 15 great-fit crops

    99%match
  5. 5

    🇧🇷ColinasMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 44 in rainZone 12b · No frost · 0 chill hours · 1,122 mm rain

    Shares 15 of your 15 great-fit crops

    99%match
  6. 6

    🇧🇷EsperantinópolisMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 63 in rainZone 13a · No frost · 0 chill hours · 1,603 mm rain

    Shares 14 of your 15 great-fit crops

    99%match
  7. 7

    🇧🇷RegeneraçãoPiauí, Brazil

    Zone 12b · No frost · 0 chill hours · 46 in rainZone 12b · No frost · 0 chill hours · 1,163 mm rain

    Shares 15 of your 15 great-fit crops

    99%match
  8. 8

    🇧🇷Lago da PedraMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 59 in rainZone 13a · No frost · 0 chill hours · 1,506 mm rain

    Shares 13 of your 15 great-fit crops

    99%match
  9. 9

    🇧🇷Barra do CordaMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 41 in rainZone 12b · No frost · 0 chill hours · 1,048 mm rain

    Shares 15 of your 15 great-fit crops

    99%match
  10. 10

    🇧🇷UniãoPiauí, Brazil

    Zone 13a · No frost · 0 chill hours · 55 in rainZone 13a · No frost · 0 chill hours · 1,405 mm rain

    Shares 14 of your 15 great-fit crops · Also great there: date palm

    98%match
  11. 11

    🇧🇷PedreirasMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 59 in rainZone 13a · No frost · 0 chill hours · 1,492 mm rain

    Shares 14 of your 15 great-fit crops · Also great there: date palm

    98%match
  12. 12

    🇧🇷TimonMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 50 in rainZone 13a · No frost · 0 chill hours · 1,258 mm rain

    Shares 14 of your 15 great-fit crops

    98%match
  13. 13

    🇧🇷MiradorMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 47 in rainZone 12b · No frost · 0 chill hours · 1,203 mm rain

    Shares 15 of your 15 great-fit crops

    98%match
  14. 14

    🇧🇷CoroatáMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 54 in rainZone 13a · No frost · 0 chill hours · 1,379 mm rain

    Shares 14 of your 15 great-fit crops · Also great there: date palm

    97%match
  15. 15

    🇧🇷São Mateus do MaranhãoMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 61 in rainZone 13a · No frost · 0 chill hours · 1,555 mm rain

    Shares 13 of your 15 great-fit crops · Also great there: date palm

    97%match
  16. 16

    🇧🇷BacabalMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 62 in rainZone 13a · No frost · 0 chill hours · 1,580 mm rain

    Shares 13 of your 15 great-fit crops · Also great there: date palm

    96%match
  17. 17

    🇧🇷PiripiriPiauí, Brazil

    Zone 13a · No frost · 0 chill hours · 53 in rainZone 13a · No frost · 0 chill hours · 1,341 mm rain

    Shares 15 of your 15 great-fit crops

    96%match
  18. 18

    🇧🇷Jenipapo dos VieirasMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 40 in rainZone 12b · No frost · 0 chill hours · 1,023 mm rain

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

    96%match
  19. 19

    🇧🇷São João dos PatosMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 42 in rainZone 12b · No frost · 0 chill hours · 1,078 mm rain

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

    95%match
  20. 20

    🇧🇷BarrasPiauí, Brazil

    Zone 13a · No frost · 0 chill hours · 59 in rainZone 13a · No frost · 0 chill hours · 1,508 mm rain

    Shares 13 of your 15 great-fit crops · Also great there: date palm

    95%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 João do Soter: 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.