Climatch

Land with a climate like São Miguel do Tapuio

🇧🇷São Miguel do Tapuio, Piauí, Brazil

The towns with the closest growing climate to São Miguel do Tapuio are Campos Sales, Brazil (99% match), Assaré and Quiterianópolis. About 160,000 sq mi of land in 6 countries matches 80% or better, most of it in Piauí, Brazil, Ceará, Brazil and Maranhão, Brazil.The towns with the closest growing climate to São Miguel do Tapuio are Campos Sales, Brazil (99% match), Assaré and Quiterianópolis. About 414,000 km² of land in 6 countries matches 80% or better, most of it in Piauí, Brazil, Ceará, Brazil and Maranhão, Brazil.

Your growing climate

Zone 12b · No frost · 0 chill hours · 27 in rainZone 12b · No frost · 0 chill hours · 698 mm rain

What grows in São Miguel do Tapuio →

Regions with the most land like yours

  1. 1

    🇧🇷Piauí, Brazil

    44k sq mi115k km² matching 80% or better

    For example Pio IX (99), Ipueiras (99)

  2. 2

    🇧🇷Ceará, Brazil

    27k sq mi70k km² matching 80% or better

    For example Campos Sales (99), Farias Brito (99)

  3. 3

    🇧🇷Maranhão, Brazil

    24k sq mi61k km² matching 80% or better

    For example Estreito (88), Fortuna (86)

  4. 4

    🇲🇿Cabo Delgado Province, Mozambique

    12k sq mi30k km² matching 80% or better

    For example Macomia (84), Chiúre (84)

  5. 5

    🇹🇿Mtwara, Tanzania

    7,000 sq mi18k km² matching 80% or better

    For example Lukuledi (93), Nanganga (91)

  6. 6

    🇹🇿Lindi, Tanzania

    5,900 sq mi15k km² matching 80% or better

    For example Nachingwea (89), Nyangao (86)

  7. 7

    🇮🇳Karnataka, India

    5,500 sq mi14k km² matching 80% or better

    For example Bāgepalli (84), Madhugiri (81)

  8. 8

    🇮🇳Andhra Pradesh, India

    3,200 sq mi8,300 km² matching 80% or better

    For example Madanapalle (83), Gorantla (82)

  9. 9

    🇹🇿Ruvuma, Tanzania

    2,100 sq mi5,300 km² matching 80% or better

    For example Tunduru (65)

  10. 10

    🇲🇿Nampula, Mozambique

    900 sq mi2,300 km² matching 80% or better

    For example Namapa-erati (81), Monapo (75)

  11. 11

    🇲🇽Oaxaca, Mexico

    900 sq mi2,200 km² matching 80% or better

    For example Ixtepec (78), Heroica Ciudad de Juchitán de Zaragoza (74)

  12. 12

    🇲🇼Northern Region, Malawi

    300 sq mi800 km² matching 80% or better

    For example Karonga (77)

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

    🇧🇷Campos SalesCeará, Brazil

    Zone 12b · No frost · 0 chill hours · 21 in rainZone 12b · No frost · 0 chill hours · 527 mm rain

    Shares 13 of your 16 great-fit crops

    99%match
  2. 2

    🇧🇷AssaréCeará, Brazil

    Zone 12b · No frost · 0 chill hours · 25 in rainZone 12b · No frost · 0 chill hours · 644 mm rain

    Shares 15 of your 16 great-fit crops

    99%match
  3. 3

    🇧🇷QuiterianópolisCeará, Brazil

    Zone 12b · No frost · 0 chill hours · 22 in rainZone 12b · No frost · 0 chill hours · 570 mm rain

    Shares 14 of your 16 great-fit crops · Also great there: wheat

    98%match
  4. 4

    🇧🇷ParambuCeará, Brazil

    Zone 12b · No frost · 0 chill hours · 23 in rainZone 12b · No frost · 0 chill hours · 583 mm rain

    Shares 14 of your 16 great-fit crops · Also great there: wheat

    97%match
  5. 5

    🇧🇷Valença do PiauíPiauí, Brazil

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

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

    97%match
  6. 6

    🇧🇷CrateúsCeará, Brazil

    Zone 12b · No frost · 0 chill hours · 26 in rainZone 12b · No frost · 0 chill hours · 667 mm rain

    Shares 16 of your 16 great-fit crops

    97%match
  7. 7

    🇧🇷JaicósPiauí, Brazil

    Zone 12b · No frost · 0 chill hours · 23 in rainZone 12b · No frost · 0 chill hours · 572 mm rain

    Shares 14 of your 16 great-fit crops

    96%match
  8. 8

    🇧🇷PicosPiauí, Brazil

    Zone 12b · No frost · 0 chill hours · 26 in rainZone 12b · No frost · 0 chill hours · 657 mm rain

    Shares 13 of your 16 great-fit crops

    96%match
  9. 9

    🇧🇷Várzea AlegreCeará, Brazil

    Zone 12b · No frost · 0 chill hours · 35 in rainZone 12b · No frost · 0 chill hours · 881 mm rain

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

    94%match
  10. 10

    🇧🇷IpueirasCeará, Brazil

    Zone 13a · No frost · 0 chill hours · 30 in rainZone 13a · No frost · 0 chill hours · 771 mm rain

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

    93%match
  11. 11

    🇧🇷Juazeiro do NorteCeará, Brazil

    Zone 12b · No frost · 0 chill hours · 36 in rainZone 12b · No frost · 0 chill hours · 912 mm rain

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

    93%match
  12. 12

    🇧🇷TauáCeará, Brazil

    Zone 12b · No frost · 0 chill hours · 20 in rainZone 12b · No frost · 0 chill hours · 503 mm rain

    Shares 13 of your 16 great-fit crops

    93%match
  13. 13

    🇧🇷AltosPiauí, Brazil

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

    Shares 14 of your 16 great-fit crops · Also great there: sugarcane

    92%match
  14. 14

    🇧🇷AraripinaPernambuco, Brazil

    Zone 12a · No frost · 0 chill hours · 25 in rainZone 12a · No frost · 0 chill hours · 639 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: wheat

    92%match
  15. 15

    🇧🇷OeirasPiauí, Brazil

    Zone 12b · No frost · 0 chill hours · 31 in rainZone 12b · No frost · 0 chill hours · 797 mm rain

    Shares 14 of your 16 great-fit crops · Also great there: sugarcane

    92%match
  16. 16

    🇧🇷OuricuriPernambuco, Brazil

    Zone 12a · No frost · 0 chill hours · 21 in rainZone 12a · No frost · 0 chill hours · 522 mm rain

    Shares 13 of your 16 great-fit crops

    92%match
  17. 17

    🇧🇷Brejo SantoCeará, Brazil

    Zone 12b · No frost · 0 chill hours · 29 in rainZone 12b · No frost · 0 chill hours · 740 mm rain

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

    92%match
  18. 18

    🇹🇿NangangaMtwara, Tanzania

    Zone 12b · No frost · 0 chill hours · 33 in rainZone 12b · No frost · 0 chill hours · 826 mm rain

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

    91%match
  19. 19

    🇹🇿NangombaMtwara, Tanzania

    Zone 12a · No frost · 0 chill hours · 36 in rainZone 12a · No frost · 0 chill hours · 912 mm rain

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

    91%match
  20. 20

    🇹🇿MasasiMtwara, Tanzania

    Zone 12a · No frost · 0 chill hours · 36 in rainZone 12a · No frost · 0 chill hours · 925 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: sugarcane, wheat

    91%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 Miguel do Tapuio: 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.