Climatch

Land with a climate like Hortolândia

🇧🇷Hortolândia, São Paulo, Brazil

The towns with the closest growing climate to Hortolândia are São Pedro, Brazil (99% match), Conchas and Jaú. About 526,000 sq mi of land in 20 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 Hortolândia are São Pedro, Brazil (99% match), Conchas and Jaú. About 1.4 million km² of land in 20 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 · 47 in rainZone 11a · No frost · 0 chill hours · 1,196 mm rain

What grows in Hortolândia →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    125k sq mi323k km² matching 80% or better

    For example Jacutinga (97), Pouso Alegre (97)

  2. 2

    🇧🇷São Paulo, Brazil

    85k sq mi220k km² matching 80% or better

    For example São Pedro (99), Conchas (99)

  3. 3

    🇧🇷Mato Grosso do Sul, Brazil

    77k sq mi199k km² matching 80% or better

    For example Chapadão do Sul (93), Aparecida do Taboado (92)

  4. 4

    🇿🇦KwaZulu-Natal, South Africa

    14k sq mi37k km² matching 80% or better

    For example eMuziwezinto (88), Pinetown (87)

  5. 5

    🇨🇳Yunnan, China

    14k sq mi37k km² matching 80% or better

    For example Mengman (85), Mengla (83)

  6. 6

    🇻🇳Điện Biên Province, Vietnam

    7,000 sq mi18k km² matching 80% or better

    For example Mường Lay (79), Dien Bien Phu (76)

  7. 7

    🇱🇦Oudômxai, Laos

    5,000 sq mi13k km² matching 80% or better

    For example Muang Xay (84)

  8. 8

    🇲🇲Shan State, Myanmar

    5,000 sq mi13k km² matching 80% or better

    For example Kēng Tung (80), Möng La (78)

  9. 9

    🇱🇦Xiangkhoang, Laos

    4,800 sq mi12k km² matching 80% or better

    For example Muang Phônsavan (87)

  10. 10

    🇧🇴Santa Cruz Department, Bolivia

    4,300 sq mi11k km² matching 80% or better

    For example El Torno (83), Warnes (71)

  11. 11

    🇱🇦Luang Prabang Province, Laos

    4,200 sq mi11k km² matching 80% or better

    For example Luang Prabang (63)

  12. 12

    🇲🇿Maputo Province, Mozambique

    4,000 sq mi10k km² matching 80% or better

    For example Manhiça (84), Matola (77)

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

    🇧🇷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
  2. 2

    🇧🇷ConchasSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 46 in rainZone 11a · No frost · 0 chill hours · 1,168 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  3. 3

    🇧🇷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
  4. 4

    🇧🇷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
  5. 5

    🇧🇷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
  6. 6

    🇧🇷TaubatéSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 50 in rainZone 11a · No frost · 0 chill hours · 1,258 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  7. 7

    🇧🇷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
  8. 8

    🇧🇷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
  9. 9

    🇧🇷São CarlosSão Paulo, Brazil

    Zone 11a · No frost · 2 chill hours · 54 in rainZone 11a · No frost · 2 chill hours · 1,369 mm rain

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

    99%match
  10. 10

    🇧🇷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
  11. 11

    🇧🇷GuaratinguetáSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 53 in rainZone 11b · No frost · 0 chill hours · 1,336 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  12. 12

    🇧🇷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
  13. 13

    🇧🇷TatuíSão Paulo, Brazil

    Zone 11a · No frost · 4 chill hours · 46 in rainZone 11a · No frost · 4 chill hours · 1,158 mm rain

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

    99%match
  14. 14

    🇧🇷MaríliaSão Paulo, Brazil

    Zone 11a · No frost · 4 chill hours · 50 in rainZone 11a · No frost · 4 chill hours · 1,273 mm rain

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

    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

    99%match
  16. 16

    🇧🇷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
  17. 17

    🇧🇷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
  18. 18

    🇧🇷AngatubaSão Paulo, Brazil

    Zone 11a · No frost · 5 chill hours · 47 in rainZone 11a · No frost · 5 chill hours · 1,187 mm rain

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

    99%match
  19. 19

    🇧🇷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

    98%match
  20. 20

    🇧🇷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

    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 Hortolândia: 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.