Climatch

Land with a climate like Pirajuí

🇧🇷Pirajuí, São Paulo, Brazil

The towns with the closest growing climate to Pirajuí are Tupã, Brazil (99% match), Jaú and Lençóis Paulista. About 622,000 sq mi of land in 20 countries matches 80% or better, most of it in Minas Gerais, Brazil, Mato Grosso do Sul, Brazil and São Paulo, Brazil.The towns with the closest growing climate to Pirajuí are Tupã, Brazil (99% match), Jaú and Lençóis Paulista. About 1.6 million km² of land in 20 countries matches 80% or better, most of it in Minas Gerais, Brazil, Mato Grosso do Sul, Brazil and São Paulo, Brazil.

Your growing climate

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

What grows in Pirajuí →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    128k sq mi331k km² matching 80% or better

    For example Pouso Alegre (96), Poço Fundo (95)

  2. 2

    🇧🇷Mato Grosso do Sul, Brazil

    96k sq mi248k km² matching 80% or better

    For example Aparecida do Taboado (97), Bataguassu (97)

  3. 3

    🇧🇷São Paulo, Brazil

    80k sq mi208k km² matching 80% or better

    For example Pederneiras (99), Barra Bonita (99)

  4. 4

    🇨🇳Yunnan, China

    15k sq mi39k km² matching 80% or better

    For example Mengla (89), Mengman (88)

  5. 5

    🇧🇴Santa Cruz Department, Bolivia

    13k sq mi32k km² matching 80% or better

    For example El Torno (89), Warnes (80)

  6. 6

    🇲🇿Zambezia Province, Mozambique

    8,900 sq mi23k km² matching 80% or better

    For example Milange (84), Gurúè (84)

  7. 7

    🇿🇦KwaZulu-Natal, South Africa

    8,700 sq mi22k km² matching 80% or better

    For example Mandeni (86), Empangeni (85)

  8. 8

    🇦🇷Chaco, Argentina

    8,100 sq mi21k km² matching 80% or better

    For example Juan José Castelli (82), Presidencia Roque Sáenz Peña (79)

  9. 9

    🇲🇲Shan State, Myanmar

    7,800 sq mi20k km² matching 80% or better

    For example Kēng Tung (86), Möng La (85)

  10. 10

    🇻🇳Điện Biên Province, Vietnam

    7,000 sq mi18k km² matching 80% or better

    For example Mường Lay (78), Dien Bien Phu (76)

  11. 11

    🇲🇿Gaza Province, Mozambique

    6,200 sq mi16k km² matching 80% or better

    For example Macia (92), Xai-Xai (84)

  12. 12

    🇲🇿Maputo Province, Mozambique

    5,400 sq mi14k km² matching 80% or better

    For example Manhiça (89), Boane (82)

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

    🇧🇷TupãSão Paulo, Brazil

    Zone 11a · No frost · 1 chill hours · 50 in rainZone 11a · No frost · 1 chill hours · 1,267 mm rain

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

    99%match
  2. 2

    🇧🇷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
  3. 3

    🇧🇷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
  4. 4

    🇧🇷AdamantinaSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 46 in rainZone 11a · No frost · 0 chill hours · 1,160 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  5. 5

    🇧🇷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
  6. 6

    🇧🇷AraraquaraSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 51 in rainZone 11a · No frost · 0 chill hours · 1,301 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  7. 7

    🇧🇷MirandópolisSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 45 in rainZone 11a · No frost · 0 chill hours · 1,144 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  8. 8

    🇧🇷LimeiraSão Paulo, Brazil

    Zone 11a · No frost · 2 chill hours · 49 in rainZone 11a · No frost · 2 chill hours · 1,239 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  9. 9

    🇧🇷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
  10. 10

    🇧🇷AssisSão Paulo, Brazil

    Zone 11a · No frost · 2 chill hours · 47 in rainZone 11a · No frost · 2 chill hours · 1,192 mm rain

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

    99%match
  11. 11

    🇧🇷DracenaSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 47 in rainZone 11b · No frost · 0 chill hours · 1,201 mm rain

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

    99%match
  12. 12

    🇧🇷Rio ClaroSão Paulo, Brazil

    Zone 11a · No frost · 3 chill hours · 49 in rainZone 11a · No frost · 3 chill hours · 1,248 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  13. 13

    🇧🇷OurinhosSão Paulo, Brazil

    Zone 11a · No frost · 4 chill hours · 50 in rainZone 11a · No frost · 4 chill hours · 1,275 mm rain

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

    99%match
  14. 14

    🇧🇷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
  15. 15

    🇧🇷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 22 great-fit crops

    99%match
  16. 16

    🇧🇷CampinasSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 49 in rainZone 11a · No frost · 0 chill hours · 1,256 mm rain

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

    99%match
  17. 17

    🇧🇷MococaSão Paulo, Brazil

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

    Shares 22 of your 22 great-fit crops

    99%match
  18. 18

    🇧🇷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
  19. 19

    🇧🇷PirajuSão Paulo, Brazil

    Zone 11a · No frost · 4 chill hours · 49 in rainZone 11a · No frost · 4 chill hours · 1,245 mm rain

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

    99%match
  20. 20

    🇧🇷PradópolisSão Paulo, Brazil

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

    Shares 21 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 Pirajuí: 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.