Climatch

Land with a climate like Santo Antônio do Monte

🇧🇷Santo Antônio do Monte, Minas Gerais, Brazil

The towns with the closest growing climate to Santo Antônio do Monte are Piumhi, Brazil (99% match), Campo Belo and Oliveira. About 396,000 sq mi of land in 18 countries matches 80% or better, most of it in Minas Gerais, Brazil, São Paulo, Brazil and Goiás, Brazil.The towns with the closest growing climate to Santo Antônio do Monte are Piumhi, Brazil (99% match), Campo Belo and Oliveira. About 1.0 million km² of land in 18 countries matches 80% or better, most of it in Minas Gerais, Brazil, São Paulo, Brazil and Goiás, Brazil.

Your growing climate

Zone 10b · No frost · 28 chill hours · 55 in rainZone 10b · No frost · 28 chill hours · 1,388 mm rain

What grows in Santo Antônio do Monte →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    146k sq mi379k km² matching 80% or better

    For example Carmópolis de Minas (99), Piumhi (99)

  2. 2

    🇧🇷São Paulo, Brazil

    65k sq mi168k km² matching 80% or better

    For example Caconde (99), São José do Rio Pardo (98)

  3. 3

    🇧🇷Goiás, Brazil

    34k sq mi88k km² matching 80% or better

    For example Ipameri (92), Cristalina (91)

  4. 4

    🇨🇳Yunnan, China

    19k sq mi49k km² matching 80% or better

    For example Nongzhang (84), Yingjiang (84)

  5. 5

    🇲🇲Shan State, Myanmar

    16k sq mi41k km² matching 80% or better

    For example Panglong (84), Kutkai (80)

  6. 6

    🇱🇦Xiangkhoang, Laos

    5,100 sq mi13k km² matching 80% or better

    For example Muang Phônsavan (89)

  7. 7

    🇻🇳Điện Biên Province, Vietnam

    4,400 sq mi12k km² matching 80% or better

    For example Mường Lay (60), Dien Bien Phu (57)

  8. 8

    🇲🇽Chiapas, Mexico

    2,000 sq mi5,200 km² matching 80% or better

    For example Las Rosas (86), Teopisca (86)

  9. 9

    🇧🇴Santa Cruz Department, Bolivia

    2,000 sq mi5,200 km² matching 80% or better

    For example Camiri (53), El Torno (52)

  10. 10

    🇱🇦Houaphan, Laos

    2,000 sq mi5,100 km² matching 80% or better

    For example Xam Nua (79)

  11. 11

    🇨🇩Tanganyika, Democratic Republic of the Congo

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

    For example Kalima (59), Kalemie (56)

  12. 12

    🇱🇦Oudômxai, Laos

    1,700 sq mi4,300 km² matching 80% or better

    For example Muang Xay (70)

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

    🇧🇷PiumhiMinas Gerais, Brazil

    Zone 10b · No frost · 34 chill hours · 59 in rainZone 10b · No frost · 34 chill hours · 1,501 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  2. 2

    🇧🇷Campo BeloMinas Gerais, Brazil

    Zone 10b · No frost · 24 chill hours · 58 in rainZone 10b · No frost · 24 chill hours · 1,481 mm rain

    Shares 24 of your 24 great-fit crops

    99%match
  3. 3

    🇧🇷OliveiraMinas Gerais, Brazil

    Zone 10b · No frost · 18 chill hours · 60 in rainZone 10b · No frost · 18 chill hours · 1,523 mm rain

    Shares 20 of your 24 great-fit crops

    99%match
  4. 4

    🇧🇷São GotardoMinas Gerais, Brazil

    Zone 11a · No frost · 8 chill hours · 61 in rainZone 11a · No frost · 8 chill hours · 1,557 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  5. 5

    🇧🇷Pará de MinasMinas Gerais, Brazil

    Zone 11a · No frost · 3 chill hours · 53 in rainZone 11a · No frost · 3 chill hours · 1,349 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  6. 6

    🇧🇷CaetéMinas Gerais, Brazil

    Zone 11a · No frost · 3 chill hours · 54 in rainZone 11a · No frost · 3 chill hours · 1,373 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  7. 7

    🇧🇷Conselheiro LafaieteMinas Gerais, Brazil

    Zone 11a · No frost · 14 chill hours · 54 in rainZone 11a · No frost · 14 chill hours · 1,366 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  8. 8

    🇧🇷IbiáMinas Gerais, Brazil

    Zone 11a · No frost · 2 chill hours · 62 in rainZone 11a · No frost · 2 chill hours · 1,564 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  9. 9

    🇧🇷PassosMinas Gerais, Brazil

    Zone 11a · No frost · 7 chill hours · 63 in rainZone 11a · No frost · 7 chill hours · 1,600 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  10. 10

    🇧🇷Carmo do Rio ClaroMinas Gerais, Brazil

    Zone 10b · No frost · 25 chill hours · 60 in rainZone 10b · No frost · 25 chill hours · 1,523 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  11. 11

    🇧🇷LavrasMinas Gerais, Brazil

    Zone 10b · No frost · 18 chill hours · 60 in rainZone 10b · No frost · 18 chill hours · 1,514 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  12. 12

    🇧🇷Carmo do ParanaíbaMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 59 in rainZone 11a · No frost · 0 chill hours · 1,506 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  13. 13

    🇧🇷Belo HorizonteMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 56 in rainZone 11a · No frost · 0 chill hours · 1,428 mm rain

    Shares 24 of your 24 great-fit crops

    99%match
  14. 14

    🇧🇷São João del ReiMinas Gerais, Brazil

    Zone 11a · No frost · 12 chill hours · 56 in rainZone 11a · No frost · 12 chill hours · 1,425 mm rain

    Shares 21 of your 24 great-fit crops

    99%match
  15. 15

    🇧🇷Três CoraçõesMinas Gerais, Brazil

    Zone 10b · No frost · 70 chill hours · 55 in rainZone 10b · No frost · 70 chill hours · 1,397 mm rain

    Shares 20 of your 24 great-fit crops

    99%match
  16. 16

    🇧🇷AraxáMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 66 in rainZone 11a · No frost · 0 chill hours · 1,678 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  17. 17

    🇧🇷AlfenasMinas Gerais, Brazil

    Zone 10b · No frost · 38 chill hours · 59 in rainZone 10b · No frost · 38 chill hours · 1,491 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  18. 18

    🇧🇷VarginhaMinas Gerais, Brazil

    Zone 10b · No frost · 54 chill hours · 56 in rainZone 10b · No frost · 54 chill hours · 1,421 mm rain

    Shares 21 of your 24 great-fit crops

    99%match
  19. 19

    🇧🇷Sete LagoasMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 49 in rainZone 11a · No frost · 0 chill hours · 1,233 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  20. 20

    🇧🇷São Sebastião do ParaísoMinas Gerais, Brazil

    Zone 11a · No frost · 5 chill hours · 61 in rainZone 11a · No frost · 5 chill hours · 1,559 mm rain

    Shares 23 of your 24 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 Santo Antônio do Monte: 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.