Climatch

Land with a climate like Buriti Bravo

🇧🇷Buriti Bravo, Maranhão, Brazil

The towns with the closest growing climate to Buriti Bravo are Mirador, Brazil (99% match), Pastos Bons and Regeneração. About 324,000 sq mi of land in 15 countries matches 80% or better, most of it in Maranhão, Brazil, Piauí, Brazil and Guárico, Venezuela.The towns with the closest growing climate to Buriti Bravo are Mirador, Brazil (99% match), Pastos Bons and Regeneração. About 839,000 km² of land in 15 countries matches 80% or better, most of it in Maranhão, Brazil, Piauí, Brazil and Guárico, Venezuela.

Your growing climate

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

What grows in Buriti Bravo →

Regions with the most land like yours

  1. 1

    🇧🇷Maranhão, Brazil

    84k sq mi217k km² matching 80% or better

    For example Mirador (99), Pastos Bons (99)

  2. 2

    🇧🇷Piauí, Brazil

    39k sq mi100k km² matching 80% or better

    For example Água Branca (99), Regeneração (99)

  3. 3

    🇻🇪Guárico, Venezuela

    18k sq mi47k km² matching 80% or better

    For example El Sombrero (89), Valle de La Pascua (89)

  4. 4

    🇮🇳Karnataka, India

    17k sq mi44k km² matching 80% or better

    For example Kanakapura (89), Gauribidanur (88)

  5. 5

    🇧🇷Pará, Brazil

    15k sq mi40k km² matching 80% or better

    For example Rondon do Pará (89), Bom Jesus do Tocantins (86)

  6. 6

    🇻🇪Anzoátegui, Venezuela

    8,000 sq mi21k km² matching 80% or better

    For example Pariaguán (87), Aragua de Barcelona (84)

  7. 7

    🇮🇳Tamil Nadu, India

    7,900 sq mi20k km² matching 80% or better

    For example Pennāgaram (88), Krishnagiri (88)

  8. 8

    🇻🇪Portuguesa, Venezuela

    6,200 sq mi16k km² matching 80% or better

    For example Píritu (84), San Rafael de Onoto (84)

  9. 9

    🇮🇳Andhra Pradesh, India

    6,100 sq mi16k km² matching 80% or better

    For example Kuppam (88), Hindupur (86)

  10. 10

    🇬🇳Kindia, Guinea

    5,000 sq mi13k km² matching 80% or better

    For example Kolenté (80), Télimélé (78)

  11. 11

    🇹🇿Mtwara, Tanzania

    4,700 sq mi12k km² matching 80% or better

    For example Lukuledi (89), Nanganga (88)

  12. 12

    🇲🇲Mandalay Region, Myanmar

    4,500 sq mi12k km² matching 80% or better

    For example Yamethin (84), Pyawbwe (83)

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

    🇧🇷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

    99%match
  2. 2

    🇧🇷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 15 great-fit crops

    99%match
  3. 3

    🇧🇷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
  4. 4

    🇧🇷São João do SoterMaranhão, Brazil

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

    Shares 15 of your 15 great-fit crops

    99%match
  5. 5

    🇧🇷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
  6. 6

    🇧🇷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
  7. 7

    🇧🇷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
  8. 8

    🇧🇷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

    98%match
  9. 9

    🇧🇷Demerval LobãoPiauí, Brazil

    Zone 13a · No frost · 0 chill hours · 48 in rainZone 13a · No frost · 0 chill hours · 1,216 mm rain

    Shares 14 of your 15 great-fit crops

    97%match
  10. 10

    🇧🇷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

    97%match
  11. 11

    🇧🇷GrajaúMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 43 in rainZone 12b · No frost · 0 chill hours · 1,097 mm rain

    Shares 15 of your 15 great-fit crops

    97%match
  12. 12

    🇧🇷FlorianoPiauí, Brazil

    Zone 12b · No frost · 0 chill hours · 36 in rainZone 12b · No frost · 0 chill hours · 910 mm rain

    Shares 14 of your 15 great-fit crops

    96%match
  13. 13

    🇧🇷Valença do PiauíPiauí, Brazil

    Zone 12b · No frost · 0 chill hours · 35 in rainZone 12b · No frost · 0 chill hours · 878 mm rain

    Shares 15 of your 15 great-fit crops · Also great there: table and raisin grapes, avocado

    96%match
  14. 14

    🇧🇷ArameMaranhão, Brazil

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

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

    95%match
  15. 15

    🇧🇷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 15 great-fit crops

    95%match
  16. 16

    🇧🇷Formosa da Serra NegraMaranhão, Brazil

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

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

    95%match
  17. 17

    🇧🇷CaxiasMaranhão, Brazil

    Zone 13a · No frost · 0 chill hours · 56 in rainZone 13a · No frost · 0 chill hours · 1,414 mm rain

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

    94%match
  18. 18

    🇧🇷ImperatrizMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 53 in rainZone 12b · No frost · 0 chill hours · 1,338 mm rain

    Shares 14 of your 15 great-fit crops

    94%match
  19. 19

    🇧🇷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

    94%match
  20. 20

    🇧🇷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

    94%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 Buriti Bravo: 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.