Climatch

Land with a climate like Tambaú

🇧🇷Tambaú, São Paulo, Brazil

The towns with the closest growing climate to Tambaú are Araraquara, Brazil (99% match), Pradópolis and Ibitinga. About 549,000 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 Tambaú are Araraquara, Brazil (99% match), Pradópolis and Ibitinga. About 1.4 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 · 2 chill hours · 52 in rainZone 11a · No frost · 2 chill hours · 1,318 mm rain

What grows in Tambaú →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    154k sq mi398k km² matching 80% or better

    For example Passos (99), Alfenas (99)

  2. 2

    🇧🇷São Paulo, Brazil

    76k sq mi198k km² matching 80% or better

    For example Matão (99), Araraquara (99)

  3. 3

    🇧🇷Mato Grosso do Sul, Brazil

    59k sq mi153k km² matching 80% or better

    For example Chapadão do Sul (98), Aparecida do Taboado (97)

  4. 4

    🇨🇳Yunnan, China

    17k sq mi43k km² matching 80% or better

    For example Mengman (85), Mangshi (84)

  5. 5

    🇲🇲Shan State, Myanmar

    16k sq mi40k km² matching 80% or better

    For example Kēng Tung (82), Panglong (82)

  6. 6

    🇧🇴Santa Cruz Department, Bolivia

    7,600 sq mi20k km² matching 80% or better

    For example El Torno (80), San Ignacio de Velasco (76)

  7. 7

    🇻🇳Điện Biên Province, Vietnam

    6,400 sq mi17k km² matching 80% or better

    For example Dien Bien Phu (72), Mường Lay (71)

  8. 8

    🇱🇦Xiangkhoang, Laos

    5,100 sq mi13k km² matching 80% or better

    For example Muang Phônsavan (92)

  9. 9

    🇱🇦Oudômxai, Laos

    4,800 sq mi12k km² matching 80% or better

    For example Muang Xay (85)

  10. 10

    🇲🇿Maputo Province, Mozambique

    4,600 sq mi12k km² matching 80% or better

    For example Manhiça (81), Ressano Garcia (81)

  11. 11

    🇱🇦Luang Prabang Province, Laos

    4,500 sq mi12k km² matching 80% or better

    For example Luang Prabang (62)

  12. 12

    🇲🇿Manica, Mozambique

    3,700 sq mi9,500 km² matching 80% or better

    For example Gondola (84), Chimoio (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

    🇧🇷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
  2. 2

    🇧🇷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
  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

    🇧🇷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
  5. 5

    🇧🇷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
  6. 6

    🇧🇷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
  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

    🇧🇷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
  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

    🇧🇷Ribeirão PretoSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 59 in rainZone 11b · No frost · 0 chill hours · 1,500 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  11. 11

    🇧🇷PassosMinas Gerais, Brazil

    Zone 11a · No frost · 7 chill hours · 63 in rainZone 11a · No frost · 7 chill hours · 1,600 mm rain

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

    🇧🇷AlfenasMinas Gerais, Brazil

    Zone 10b · No frost · 38 chill hours · 59 in rainZone 10b · No frost · 38 chill hours · 1,491 mm rain

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

    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

    🇧🇷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

    98%match
  16. 16

    🇧🇷PitangueirasSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 53 in rainZone 11b · No frost · 0 chill hours · 1,344 mm rain

    Shares 21 of your 22 great-fit crops

    98%match
  17. 17

    🇧🇷UberabaMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 65 in rainZone 11b · No frost · 0 chill hours · 1,649 mm rain

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

    98%match
  18. 18

    🇧🇷AparecidaSão Paulo, Brazil

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

    Shares 22 of your 22 great-fit crops

    98%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

    98%match
  20. 20

    🇧🇷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

    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 Tambaú: 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.