Climatch

Land with a climate like Santa Juliana

🇧🇷Santa Juliana, Minas Gerais, Brazil

The towns with the closest growing climate to Santa Juliana are Carmo do Paranaíba, Brazil (99% match), Ibiá and Pedregulho. About 430,000 sq mi of land in 12 countries matches 80% or better, most of it in Minas Gerais, Brazil, Goiás, Brazil and São Paulo, Brazil.The towns with the closest growing climate to Santa Juliana are Carmo do Paranaíba, Brazil (99% match), Ibiá and Pedregulho. About 1.1 million km² of land in 12 countries matches 80% or better, most of it in Minas Gerais, Brazil, Goiás, Brazil and São Paulo, Brazil.

Your growing climate

Zone 11a · No frost · 0 chill hours · 65 in rainZone 11a · No frost · 0 chill hours · 1,657 mm rain

What grows in Santa Juliana →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    148k sq mi385k km² matching 80% or better

    For example Carmo do Paranaíba (99), Ibiá (99)

  2. 2

    🇧🇷Goiás, Brazil

    65k sq mi168k km² matching 80% or better

    For example Catalão (98), Cristalina (97)

  3. 3

    🇧🇷São Paulo, Brazil

    52k sq mi135k km² matching 80% or better

    For example Pedregulho (99), Altinópolis (98)

  4. 4

    🇨🇩Tanganyika, Democratic Republic of the Congo

    7,400 sq mi19k km² matching 80% or better

    For example Kalima (74), Nyunzu (71)

  5. 5

    🇲🇲Shan State, Myanmar

    7,300 sq mi19k km² matching 80% or better

    For example Taunggyi (80), Heho (79)

  6. 6

    🇱🇦Xiangkhoang, Laos

    5,100 sq mi13k km² matching 80% or better

    For example Muang Phônsavan (92)

  7. 7

    🇹🇿Kigoma, Tanzania

    2,700 sq mi7,000 km² matching 80% or better

    For example Kibondo (83), Kasulu (78)

  8. 8

    🇦🇴Cuanza Norte, Angola

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

    For example Camabatela (81), Dondo (80)

  9. 9

    🇱🇦Luang Prabang Province, Laos

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

  10. 10

    🇻🇳Điện Biên Province, Vietnam

    2,200 sq mi5,800 km² matching 80% or better

    For example Mường Lay (62), Dien Bien Phu (60)

  11. 11

    🇧🇮Gitega, Burundi

    2,100 sq mi5,400 km² matching 80% or better

    For example Gitega (84), Zanandore (83)

  12. 12

    🇱🇦Oudômxai, Laos

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

    For example Muang Xay (71)

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

    🇧🇷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 23 great-fit crops

    99%match
  2. 2

    🇧🇷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 23 great-fit crops

    99%match
  3. 3

    🇧🇷PedregulhoSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 64 in rainZone 11a · No frost · 0 chill hours · 1,614 mm rain

    Shares 23 of your 23 great-fit crops

    99%match
  4. 4

    🇧🇷CoromandelMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 63 in rainZone 11b · No frost · 0 chill hours · 1,591 mm rain

    Shares 21 of your 23 great-fit crops

    99%match
  5. 5

    🇧🇷Patos de MinasMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 57 in rainZone 11b · No frost · 0 chill hours · 1,443 mm rain

    Shares 23 of your 23 great-fit crops · Also great there: fig

    99%match
  6. 6

    🇧🇷TupaciguaraMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 61 in rainZone 11b · No frost · 0 chill hours · 1,547 mm rain

    Shares 21 of your 23 great-fit crops

    99%match
  7. 7

    🇧🇷AraguariMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 64 in rainZone 11b · No frost · 0 chill hours · 1,636 mm rain

    Shares 21 of your 23 great-fit crops

    99%match
  8. 8

    🇧🇷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 23 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 23 great-fit crops

    99%match
  10. 10

    🇧🇷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 23 great-fit crops

    99%match
  11. 11

    🇧🇷SabaráMinas Gerais, Brazil

    Zone 11a · No frost · 0 chill hours · 52 in rainZone 11a · No frost · 0 chill hours · 1,315 mm rain

    Shares 21 of your 23 great-fit crops · Also great there: fig

    98%match
  12. 12

    🇧🇷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 23 great-fit crops · Also great there: fig

    98%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 23 of your 23 great-fit crops · Also great there: fig

    98%match
  14. 14

    🇧🇷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 23 great-fit crops

    97%match
  15. 15

    🇧🇷CristalinaGoiás, Brazil

    Zone 11a · No frost · 0 chill hours · 60 in rainZone 11a · No frost · 0 chill hours · 1,524 mm rain

    Shares 21 of your 23 great-fit crops

    97%match
  16. 16

    🇧🇷BatataisSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 61 in rainZone 11a · No frost · 0 chill hours · 1,557 mm rain

    Shares 23 of your 23 great-fit crops

    97%match
  17. 17

    🇧🇷MineirosGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 64 in rainZone 11b · No frost · 0 chill hours · 1,616 mm rain

    Shares 23 of your 23 great-fit crops

    97%match
  18. 18

    🇧🇷Nova SerranaMinas Gerais, Brazil

    Zone 11a · No frost · 6 chill hours · 52 in rainZone 11a · No frost · 6 chill hours · 1,331 mm rain

    Shares 21 of your 23 great-fit crops · Also great there: fig

    97%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 21 of your 23 great-fit crops · Also great there: fig

    97%match
  20. 20

    🇧🇷DivinópolisMinas Gerais, Brazil

    Zone 11a · No frost · 3 chill hours · 54 in rainZone 11a · No frost · 3 chill hours · 1,367 mm rain

    Shares 22 of your 23 great-fit crops · Also great there: fig

    97%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 Santa Juliana: 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.