Climatch

Land with a climate like Sertãozinho

🇧🇷Sertãozinho, São Paulo, Brazil

The towns with the closest growing climate to Sertãozinho are Catanduva, Brazil (99% match), São José do Rio Preto and Votuporanga. About 650,000 sq mi of land in 19 countries matches 80% or better, most of it in Minas Gerais, Brazil, Mato Grosso do Sul, Brazil and Mato Grosso, Brazil.The towns with the closest growing climate to Sertãozinho are Catanduva, Brazil (99% match), São José do Rio Preto and Votuporanga. About 1.7 million km² of land in 19 countries matches 80% or better, most of it in Minas Gerais, Brazil, Mato Grosso do Sul, Brazil and Mato Grosso, Brazil.

Your growing climate

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

What grows in Sertãozinho →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    135k sq mi351k km² matching 80% or better

    For example Conceição das Alagoas (99), Frutal (99)

  2. 2

    🇧🇷Mato Grosso do Sul, Brazil

    84k sq mi217k km² matching 80% or better

    For example Paranaíba (99), Cassilândia (99)

  3. 3

    🇧🇷Mato Grosso, Brazil

    75k sq mi193k km² matching 80% or better

    For example Alto Araguaia (97), Chapada dos Guimarães (96)

  4. 4

    🇧🇴Santa Cruz Department, Bolivia

    22k sq mi58k km² matching 80% or better

    For example El Torno (90), San Ignacio de Velasco (88)

  5. 5

    🇲🇲Shan State, Myanmar

    10k sq mi26k km² matching 80% or better

    For example Möng Yawng (86), Möng La (85)

  6. 6

    🇨🇳Yunnan, China

    5,800 sq mi15k km² matching 80% or better

    For example Yunjinghong (87), Mengla (86)

  7. 7

    🇱🇦Luang Prabang Province, Laos

    5,100 sq mi13k km² matching 80% or better

    For example Luang Prabang (77)

  8. 8

    🇱🇦Oudômxai, Laos

    5,000 sq mi13k km² matching 80% or better

    For example Muang Xay (89)

  9. 9

    🇲🇿Zambezia Province, Mozambique

    4,900 sq mi13k km² matching 80% or better

    For example Gurúè (80), Alto Molocue (79)

  10. 10

    🇧🇴La Paz Department, Bolivia

    4,300 sq mi11k km² matching 80% or better

    For example Caranavi (91)

  11. 11

    🇱🇦Bokeo, Laos

    4,200 sq mi11k km² matching 80% or better

    For example Ban Khoan (71), Ban Houakhoua (70)

  12. 12

    🇻🇳Điện Biên Province, Vietnam

    3,600 sq mi9,400 km² matching 80% or better

    For example Dien Bien Phu (75), Mường Lay (74)

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

    🇧🇷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 21 great-fit crops

    99%match
  2. 2

    🇧🇷São José do Rio PretoSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 50 in rainZone 11b · No frost · 0 chill hours · 1,261 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  3. 3

    🇧🇷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 21 great-fit crops

    99%match
  4. 4

    🇧🇷PirassunungaSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 51 in rainZone 11a · No frost · 0 chill hours · 1,285 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  5. 5

    🇧🇷BarretosSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 53 in rainZone 11b · No frost · 0 chill hours · 1,338 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  6. 6

    🇧🇷OlímpiaSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 52 in rainZone 11b · No frost · 0 chill hours · 1,314 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  7. 7

    🇧🇷José BonifácioSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 45 in rainZone 11b · No frost · 0 chill hours · 1,155 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  8. 8

    🇧🇷Conceição das AlagoasMinas Gerais, Brazil

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

    Shares 19 of your 21 great-fit crops

    99%match
  9. 9

    🇧🇷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 21 great-fit crops

    99%match
  10. 10

    🇧🇷FrutalMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 63 in rainZone 11b · No frost · 0 chill hours · 1,602 mm rain

    Shares 19 of your 21 great-fit crops

    99%match
  11. 11

    🇧🇷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 21 great-fit crops

    99%match
  12. 12

    🇧🇷IturamaMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 49 in rainZone 11b · No frost · 0 chill hours · 1,249 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  13. 13

    🇧🇷ParanaíbaMato Grosso do Sul, Brazil

    Zone 11b · No frost · 0 chill hours · 55 in rainZone 11b · No frost · 0 chill hours · 1,396 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  14. 14

    🇧🇷CassilândiaMato Grosso do Sul, Brazil

    Zone 11b · No frost · 0 chill hours · 57 in rainZone 11b · No frost · 0 chill hours · 1,454 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  15. 15

    🇧🇷MococaSão Paulo, Brazil

    Zone 11a · No frost · 2 chill hours · 54 in rainZone 11a · No frost · 2 chill hours · 1,371 mm rain

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

    99%match
  16. 16

    🇧🇷ItuveravaSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 60 in rainZone 11b · No frost · 0 chill hours · 1,530 mm rain

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

    99%match
  17. 17

    🇧🇷PrataMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 60 in rainZone 11b · No frost · 0 chill hours · 1,525 mm rain

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

    99%match
  18. 18

    🇧🇷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 21 great-fit crops

    99%match
  19. 19

    🇧🇷Santa Fé do SulSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 47 in rainZone 11b · No frost · 0 chill hours · 1,206 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  20. 20

    🇧🇷São SimãoGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 56 in rainZone 11b · No frost · 0 chill hours · 1,411 mm rain

    Shares 20 of your 21 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 Sertãozinho: 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.