Climatch

Land with a climate like Paracatu

🇧🇷Paracatu, Minas Gerais, Brazil

The towns with the closest growing climate to Paracatu are Vazante, Brazil (99% match), Pires do Rio and Unaí. About 758,000 sq mi of land in 11 countries matches 80% or better, most of it in Minas Gerais, Brazil, Goiás, Brazil and Mato Grosso, Brazil.The towns with the closest growing climate to Paracatu are Vazante, Brazil (99% match), Pires do Rio and Unaí. About 2.0 million km² of land in 11 countries matches 80% or better, most of it in Minas Gerais, Brazil, Goiás, Brazil and Mato Grosso, Brazil.

Your growing climate

Zone 11b · No frost · 0 chill hours · 53 in rainZone 11b · No frost · 0 chill hours · 1,357 mm rain

What grows in Paracatu →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    137k sq mi354k km² matching 80% or better

    For example Vazante (99), Unaí (99)

  2. 2

    🇧🇷Goiás, Brazil

    115k sq mi297k km² matching 80% or better

    For example Pires do Rio (99), Morrinhos (99)

  3. 3

    🇧🇷Mato Grosso, Brazil

    91k sq mi236k km² matching 80% or better

    For example Alto Araguaia (94), Poxoréu (93)

  4. 4

    🇨🇩Tanganyika, Democratic Republic of the Congo

    25k sq mi65k km² matching 80% or better

    For example Nyunzu (90), Kalima (90)

  5. 5

    🇦🇴Luanda Norte, Angola

    22k sq mi57k km² matching 80% or better

    For example Cuilo (83), Lucapa (83)

  6. 6

    🇨🇩Haut-Lomami, Democratic Republic of the Congo

    14k sq mi35k km² matching 80% or better

    For example Kamina (84), Kanyama (83)

  7. 7

    🇦🇴Malanje, Angola

    12k sq mi32k km² matching 80% or better

    For example Cacuso (88), Bailundo (85)

  8. 8

    🇹🇿Kigoma, Tanzania

    12k sq mi32k km² matching 80% or better

    For example Uvinza (87), Mwandiga (86)

  9. 9

    🇨🇩Lomami, Democratic Republic of the Congo

    5,000 sq mi13k km² matching 80% or better

    For example Luputa (77), Kabinda (76)

  10. 10

    🇹🇿Geita, Tanzania

    4,800 sq mi12k km² matching 80% or better

    For example Diobahika (82), Buseresere (81)

  11. 11

    🇹🇭Nan, Thailand

    4,500 sq mi12k km² matching 80% or better

    For example Nan (67)

  12. 12

    🇹🇭Chiang Mai, Thailand

    4,200 sq mi11k km² matching 80% or better

    For example San Kamphaeng (71), Hang Dong (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

    🇧🇷VazanteMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 56 in rainZone 11b · No frost · 0 chill hours · 1,424 mm rain

    Shares 21 of your 21 great-fit crops

    99%match
  2. 2

    🇧🇷Pires do RioGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 58 in rainZone 11b · No frost · 0 chill hours · 1,483 mm rain

    Shares 21 of your 21 great-fit crops · Also great there: potato

    99%match
  3. 3

    🇧🇷UnaíMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 50 in rainZone 11b · No frost · 0 chill hours · 1,272 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  4. 4

    🇧🇷João PinheiroMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 50 in rainZone 11b · No frost · 0 chill hours · 1,262 mm rain

    Shares 21 of your 21 great-fit crops

    99%match
  5. 5

    🇧🇷MorrinhosGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 60 in rainZone 11b · No frost · 0 chill hours · 1,523 mm rain

    Shares 20 of your 21 great-fit crops · Also great there: potato

    99%match
  6. 6

    🇧🇷Caldas NovasGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 59 in rainZone 11b · No frost · 0 chill hours · 1,496 mm rain

    Shares 21 of your 21 great-fit crops · Also great there: potato

    99%match
  7. 7

    🇧🇷IpameriGoiás, Brazil

    Zone 11a · No frost · 0 chill hours · 58 in rainZone 11a · No frost · 0 chill hours · 1,473 mm rain

    Shares 21 of your 21 great-fit crops · Also great there: potato

    99%match
  8. 8

    🇧🇷Três MariasMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 40 in rainZone 11b · No frost · 0 chill hours · 1,014 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  9. 9

    🇧🇷GoiatubaGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 61 in rainZone 11b · No frost · 0 chill hours · 1,538 mm rain

    Shares 20 of your 21 great-fit crops · Also great there: potato

    99%match
  10. 10

    🇧🇷AbaetéMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 50 in rainZone 11a · No frost · 0 chill hours · 1,262 mm rain

    Shares 21 of your 21 great-fit crops

    99%match
  11. 11

    🇧🇷CatalãoGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 57 in rainZone 11b · No frost · 0 chill hours · 1,457 mm rain

    Shares 21 of your 21 great-fit crops · Also great there: potato

    99%match
  12. 12

    🇧🇷São SebastiãoFederal District, Brazil

    Zone 11b · No frost · 0 chill hours · 57 in rainZone 11b · No frost · 0 chill hours · 1,439 mm rain

    Shares 21 of your 21 great-fit crops · Also great there: potato

    99%match
  13. 13

    🇧🇷SilvâniaGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 60 in rainZone 11b · No frost · 0 chill hours · 1,526 mm rain

    Shares 20 of your 21 great-fit crops · Also great there: potato

    99%match
  14. 14

    🇧🇷BuritisMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 43 in rainZone 11b · No frost · 0 chill hours · 1,099 mm rain

    Shares 19 of your 21 great-fit crops

    99%match
  15. 15

    🇧🇷PontalinaGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 60 in rainZone 11b · No frost · 0 chill hours · 1,516 mm rain

    Shares 18 of your 21 great-fit crops

    98%match
  16. 16

    🇧🇷ItumbiaraGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 58 in rainZone 11b · No frost · 0 chill hours · 1,485 mm rain

    Shares 19 of your 21 great-fit crops

    98%match
  17. 17

    🇧🇷PompéuMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 46 in rainZone 11a · No frost · 0 chill hours · 1,167 mm rain

    Shares 21 of your 21 great-fit crops · Also great there: potato

    98%match
  18. 18

    🇧🇷Bom Jesus de GoiásGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 60 in rainZone 11b · No frost · 0 chill hours · 1,516 mm rain

    Shares 19 of your 21 great-fit crops

    98%match
  19. 19

    🇧🇷Brasilândia de MinasMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 42 in rainZone 11b · No frost · 0 chill hours · 1,069 mm rain

    Shares 19 of your 21 great-fit crops

    98%match
  20. 20

    🇧🇷ArinosMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 43 in rainZone 11b · No frost · 0 chill hours · 1,099 mm rain

    Shares 19 of your 21 great-fit crops

    98%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 Paracatu: 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.