Climatch

Land with a climate like Potim

🇧🇷Potim, São Paulo, Brazil

The towns with the closest growing climate to Potim are Piracicaba, Brazil (99% match), Jaú and Limeira. About 577,000 sq mi of land in 21 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 Potim are Piracicaba, Brazil (99% match), Jaú and Limeira. About 1.5 million km² of land in 21 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 11b · No frost · 0 chill hours · 51 in rainZone 11b · No frost · 0 chill hours · 1,305 mm rain

What grows in Potim →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    126k sq mi327k km² matching 80% or better

    For example Inhapim (95), Rio Pomba (95)

  2. 2

    🇧🇷Mato Grosso do Sul, Brazil

    94k sq mi243k km² matching 80% or better

    For example Aparecida do Taboado (95), Bataguassu (94)

  3. 3

    🇧🇷São Paulo, Brazil

    83k sq mi214k km² matching 80% or better

    For example Americana (99), Igaraçu do Tietê (99)

  4. 4

    🇿🇦KwaZulu-Natal, South Africa

    13k sq mi35k km² matching 80% or better

    For example eMuziwezinto (88), Mandeni (87)

  5. 5

    🇨🇳Yunnan, China

    8,300 sq mi22k km² matching 80% or better

    For example Mengla (86), Mengman (82)

  6. 6

    🇧🇴Santa Cruz Department, Bolivia

    7,100 sq mi18k km² matching 80% or better

    For example El Torno (87), San Ignacio de Velasco (79)

  7. 7

    🇻🇳Điện Biên Province, Vietnam

    7,000 sq mi18k km² matching 80% or better

    For example Mường Lay (84), Dien Bien Phu (80)

  8. 8

    🇲🇿Zambezia Province, Mozambique

    5,200 sq mi13k km² matching 80% or better

    For example Milange (80), Gurúè (79)

  9. 9

    🇲🇿Gaza Province, Mozambique

    5,200 sq mi13k km² matching 80% or better

    For example Macia (91), Xai-Xai (84)

  10. 10

    🇲🇿Maputo Province, Mozambique

    5,100 sq mi13k km² matching 80% or better

    For example Manhiça (89), Matola (81)

  11. 11

    🇱🇦Luang Prabang Province, Laos

    5,100 sq mi13k km² matching 80% or better

    For example Luang Prabang (72)

  12. 12

    🇱🇦Oudômxai, Laos

    5,000 sq mi13k km² matching 80% or better

    For example Muang Xay (87)

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

    🇧🇷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
  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

    🇧🇷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
  4. 4

    🇧🇷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
  5. 5

    🇧🇷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
  6. 6

    🇧🇷LemeSão Paulo, Brazil

    Zone 11a · No frost · 1 chill hours · 51 in rainZone 11a · No frost · 1 chill hours · 1,293 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  7. 7

    🇧🇷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
  8. 8

    🇧🇷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
  9. 9

    🇧🇷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
  10. 10

    🇧🇷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
  11. 11

    🇧🇷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
  12. 12

    🇧🇷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
  13. 13

    🇧🇷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
  14. 14

    🇧🇷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
  15. 15

    🇧🇷BrotasSão Paulo, Brazil

    Zone 11a · No frost · 3 chill hours · 50 in rainZone 11a · No frost · 3 chill hours · 1,280 mm rain

    Shares 22 of your 22 great-fit crops

    98%match
  16. 16

    🇧🇷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

    98%match
  17. 17

    🇧🇷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

    98%match
  18. 18

    🇧🇷Volta RedondaRio de Janeiro, Brazil

    Zone 11a · No frost · 0 chill hours · 55 in rainZone 11a · No frost · 0 chill hours · 1,397 mm rain

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

    98%match
  19. 19

    🇧🇷SaltoSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 47 in rainZone 11a · No frost · 0 chill hours · 1,205 mm rain

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

    98%match
  20. 20

    🇧🇷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

    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 Potim: 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.