Climatch

Land with a climate like Formosa da Serra Negra

🇧🇷Formosa da Serra Negra, Maranhão, Brazil

The towns with the closest growing climate to Formosa da Serra Negra are Amarante do Maranhão, Brazil (99% match), Riachão and João Lisboa. About 428,000 sq mi of land in 16 countries matches 80% or better, most of it in Maranhão, Brazil, Tocantins, Brazil and Mato Grosso, Brazil.The towns with the closest growing climate to Formosa da Serra Negra are Amarante do Maranhão, Brazil (99% match), Riachão and João Lisboa. About 1.1 million km² of land in 16 countries matches 80% or better, most of it in Maranhão, Brazil, Tocantins, Brazil and Mato Grosso, Brazil.

Your growing climate

Zone 12a · No frost · 0 chill hours · 45 in rainZone 12a · No frost · 0 chill hours · 1,132 mm rain

What grows in Formosa da Serra Negra →

Regions with the most land like yours

  1. 1

    🇧🇷Maranhão, Brazil

    70k sq mi183k km² matching 80% or better

    For example Amarante do Maranhão (99), Sítio Novo (99)

  2. 2

    🇧🇷Tocantins, Brazil

    47k sq mi121k km² matching 80% or better

    For example Tocantinópolis (98), Palmas (94)

  3. 3

    🇧🇷Mato Grosso, Brazil

    45k sq mi117k km² matching 80% or better

    For example Vila Rica (85), Cuiabá (82)

  4. 4

    🇻🇪Guárico, Venezuela

    6,500 sq mi17k km² matching 80% or better

    For example San Juan de los Morros (81), Valle de La Pascua (80)

  5. 5

    🇹🇭Lampang, Thailand

    4,800 sq mi13k km² matching 80% or better

    For example Lampang (84), Thoen (80)

  6. 6

    🇹🇭Tak, Thailand

    4,000 sq mi10k km² matching 80% or better

    For example Mae Ramat (81), Mae Sot (79)

  7. 7

    🇲🇲Bago Region, Myanmar

    4,000 sq mi10k km² matching 80% or better

    For example Zigon (80), Paungde (79)

  8. 8

    🇹🇿Kigoma, Tanzania

    3,300 sq mi8,500 km² matching 80% or better

    For example Mwandiga (84), Kigoma (84)

  9. 9

    🇹🇭Phayao, Thailand

    2,800 sq mi7,300 km² matching 80% or better

    For example Phayao (83), Dok Kham Tai (81)

  10. 10

    🇹🇿Lindi, Tanzania

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

    For example Nachingwea (82), Ruangwa (81)

  11. 11

    🇮🇳Karnataka, India

    2,300 sq mi6,000 km² matching 80% or better

    For example Shivamogga (81), Bhadrāvati (81)

  12. 12

    🇲🇲Nay Pyi Taw, Myanmar

    2,300 sq mi5,800 km² matching 80% or better

    For example Nay Pyi Taw (79), Lewe (79)

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

    🇧🇷Amarante do MaranhãoMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 46 in rainZone 12b · No frost · 0 chill hours · 1,177 mm rain

    Shares 16 of your 16 great-fit crops

    99%match
  2. 2

    🇧🇷RiachãoMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 45 in rainZone 12b · No frost · 0 chill hours · 1,145 mm rain

    Shares 16 of your 16 great-fit crops

    99%match
  3. 3

    🇧🇷João LisboaMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 50 in rainZone 12b · No frost · 0 chill hours · 1,282 mm rain

    Shares 15 of your 16 great-fit crops

    99%match
  4. 4

    🇧🇷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 16 of your 16 great-fit crops

    98%match
  5. 5

    🇧🇷EstreitoMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 56 in rainZone 12b · No frost · 0 chill hours · 1,419 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: banana, cacao

    97%match
  6. 6

    🇧🇷Santa LuziaMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 51 in rainZone 12b · No frost · 0 chill hours · 1,287 mm rain

    Shares 15 of your 16 great-fit crops

    97%match
  7. 7

    🇧🇷AçailândiaMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 55 in rainZone 12b · No frost · 0 chill hours · 1,399 mm rain

    Shares 16 of your 16 great-fit crops

    97%match
  8. 8

    🇧🇷ArameMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 44 in rainZone 12b · No frost · 0 chill hours · 1,130 mm rain

    Shares 16 of your 16 great-fit crops

    96%match
  9. 9

    🇧🇷São Raimundo das MangabeirasMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 40 in rainZone 12b · No frost · 0 chill hours · 1,025 mm rain

    Shares 15 of your 16 great-fit crops

    96%match
  10. 10

    🇧🇷Pastos BonsMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 45 in rainZone 12b · No frost · 0 chill hours · 1,146 mm rain

    Shares 15 of your 16 great-fit crops

    96%match
  11. 11

    🇧🇷CarolinaMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 56 in rainZone 12b · No frost · 0 chill hours · 1,425 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: banana, cacao

    96%match
  12. 12

    🇧🇷São Domingos do MaranhãoMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 41 in rainZone 12b · No frost · 0 chill hours · 1,053 mm rain

    Shares 15 of your 16 great-fit crops

    96%match
  13. 13

    🇧🇷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 16 great-fit crops

    96%match
  14. 14

    🇧🇷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 16 great-fit crops

    95%match
  15. 15

    🇧🇷BalsasMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 43 in rainZone 12b · No frost · 0 chill hours · 1,102 mm rain

    Shares 15 of your 16 great-fit crops

    95%match
  16. 16

    🇧🇷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 16 of your 16 great-fit crops

    95%match
  17. 17

    🇧🇷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 16 great-fit crops

    95%match
  18. 18

    🇧🇷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 16 great-fit crops

    95%match
  19. 19

    🇧🇷PalmasTocantins, Brazil

    Zone 12a · No frost · 0 chill hours · 61 in rainZone 12a · No frost · 0 chill hours · 1,548 mm rain

    Shares 15 of your 16 great-fit crops

    94%match
  20. 20

    🇧🇷AraguatinsTocantins, Brazil

    Zone 13a · No frost · 0 chill hours · 56 in rainZone 13a · No frost · 0 chill hours · 1,424 mm rain

    Shares 14 of your 16 great-fit crops · Also great there: banana, cacao

    93%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 Formosa da Serra Negra: 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.