Climatch

Land with a climate like Santa Rita do Passa Quatro

🇧🇷Santa Rita do Passa Quatro, São Paulo, Brazil

The towns with the closest growing climate to Santa Rita do Passa Quatro are Matão, Brazil (99% match), Monte Alto and Ibitinga. About 565,000 sq mi of land in 17 countries matches 80% or better, most of it in Minas Gerais, Brazil, São Paulo, Brazil and Mato Grosso do Sul, Brazil.The towns with the closest growing climate to Santa Rita do Passa Quatro are Matão, Brazil (99% match), Monte Alto and Ibitinga. About 1.5 million km² of land in 17 countries matches 80% or better, most of it in Minas Gerais, Brazil, São Paulo, Brazil and Mato Grosso do Sul, Brazil.

Your growing climate

Zone 11a · No frost · 0 chill hours · 54 in rainZone 11a · No frost · 0 chill hours · 1,370 mm rain

What grows in Santa Rita do Passa Quatro →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    149k sq mi386k km² matching 80% or better

    For example Guaranésia (99), Monte Santo de Minas (99)

  2. 2

    🇧🇷São Paulo, Brazil

    77k sq mi199k km² matching 80% or better

    For example Matão (99), Monte Alto (99)

  3. 3

    🇧🇷Mato Grosso do Sul, Brazil

    77k sq mi199k km² matching 80% or better

    For example Chapadão do Sul (99), Aparecida do Taboado (98)

  4. 4

    🇲🇲Shan State, Myanmar

    14k sq mi36k km² matching 80% or better

    For example Kēng Tung (84), Möng La (83)

  5. 5

    🇨🇳Yunnan, China

    14k sq mi35k km² matching 80% or better

    For example Mengman (85), Mengla (84)

  6. 6

    🇧🇴Santa Cruz Department, Bolivia

    7,600 sq mi20k km² matching 80% or better

    For example El Torno (84), San Ignacio de Velasco (78)

  7. 7

    🇻🇳Điện Biên Province, Vietnam

    6,400 sq mi17k km² matching 80% or better

    For example Mường Lay (74), Dien Bien Phu (74)

  8. 8

    🇱🇦Luang Prabang Province, Laos

    5,100 sq mi13k km² matching 80% or better

    For example Luang Prabang (66)

  9. 9

    🇱🇦Oudômxai, Laos

    5,000 sq mi13k km² matching 80% or better

    For example Muang Xay (86)

  10. 10

    🇱🇦Xiangkhoang, Laos

    4,800 sq mi12k km² matching 80% or better

    For example Muang Phônsavan (92)

  11. 11

    🇲🇿Maputo Province, Mozambique

    4,000 sq mi10k km² matching 80% or better

    For example Manhiça (83), Ressano Garcia (80)

  12. 12

    🇧🇴La Paz Department, Bolivia

    4,000 sq mi10k km² matching 80% or better

    For example Caranavi (84)

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

    🇧🇷MatãoSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 52 in rainZone 11a · No frost · 0 chill hours · 1,313 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  2. 2

    🇧🇷Monte AltoSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 52 in rainZone 11b · No frost · 0 chill hours · 1,311 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  3. 3

    🇧🇷IbitingaSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 47 in rainZone 11a · No frost · 0 chill hours · 1,198 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  4. 4

    🇧🇷São João da Boa VistaSão Paulo, Brazil

    Zone 11a · No frost · 5 chill hours · 56 in rainZone 11a · No frost · 5 chill hours · 1,420 mm rain

    Shares 22 of your 22 great-fit crops · Also great there: banana, tea

    99%match
  5. 5

    🇧🇷SertãozinhoSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 56 in rainZone 11b · No frost · 0 chill hours · 1,427 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  6. 6

    🇧🇷Novo HorizonteSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 48 in rainZone 11b · No frost · 0 chill hours · 1,209 mm rain

    Shares 20 of your 22 great-fit crops

    99%match
  7. 7

    🇧🇷JaúSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 49 in rainZone 11a · No frost · 0 chill hours · 1,243 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  8. 8

    🇧🇷BatataisSão Paulo, Brazil

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

    Shares 21 of your 22 great-fit crops · Also great there: tea, banana

    99%match
  9. 9

    🇧🇷São PedroSão Paulo, Brazil

    Zone 11a · No frost · 1 chill hours · 50 in rainZone 11a · No frost · 1 chill hours · 1,277 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  10. 10

    🇧🇷Mogi GuaçuSão Paulo, Brazil

    Zone 11a · No frost · 4 chill hours · 52 in rainZone 11a · No frost · 4 chill hours · 1,329 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  11. 11

    🇧🇷BauruSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 45 in rainZone 11b · No frost · 0 chill hours · 1,143 mm rain

    Shares 21 of your 22 great-fit crops · Also great there: banana

    99%match
  12. 12

    🇧🇷PirajuíSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 46 in rainZone 11a · No frost · 0 chill hours · 1,170 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  13. 13

    🇧🇷PiracicabaSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 48 in rainZone 11a · No frost · 0 chill hours · 1,230 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  14. 14

    🇧🇷CatanduvaSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 50 in rainZone 11b · No frost · 0 chill hours · 1,280 mm rain

    Shares 20 of your 22 great-fit crops

    99%match
  15. 15

    🇧🇷Lençóis PaulistaSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 47 in rainZone 11a · No frost · 0 chill hours · 1,185 mm rain

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

    99%match
  16. 16

    🇧🇷LinsSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 48 in rainZone 11a · No frost · 0 chill hours · 1,224 mm rain

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

    99%match
  17. 17

    🇧🇷VotuporangaSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 49 in rainZone 11b · No frost · 0 chill hours · 1,232 mm rain

    Shares 20 of your 22 great-fit crops

    99%match
  18. 18

    🇧🇷AraçatubaSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 48 in rainZone 11a · No frost · 0 chill hours · 1,213 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  19. 19

    🇧🇷Chapadão do SulMato Grosso do Sul, Brazil

    Zone 11b · No frost · 0 chill hours · 60 in rainZone 11b · No frost · 0 chill hours · 1,531 mm rain

    Shares 21 of your 22 great-fit crops · Also great there: banana, tea

    99%match
  20. 20

    🇧🇷JalesSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 46 in rainZone 11b · No frost · 0 chill hours · 1,173 mm rain

    Shares 20 of your 22 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 Santa Rita do Passa Quatro: 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.