Climatch

Land with a climate like Ilha Solteira

🇧🇷Ilha Solteira, São Paulo, Brazil

The towns with the closest growing climate to Ilha Solteira are Paranaíba, Brazil (99% match), Votuporanga and Araçatuba. About 857,000 sq mi of land in 21 countries matches 80% or better, most of it in Mato Grosso do Sul, Brazil, Minas Gerais, Brazil and Mato Grosso, Brazil.The towns with the closest growing climate to Ilha Solteira are Paranaíba, Brazil (99% match), Votuporanga and Araçatuba. About 2.2 million km² of land in 21 countries matches 80% or better, most of it in Mato Grosso do Sul, Brazil, Minas Gerais, Brazil and Mato Grosso, Brazil.

Your growing climate

Zone 11b · No frost · 0 chill hours · 48 in rainZone 11b · No frost · 0 chill hours · 1,217 mm rain

What grows in Ilha Solteira →

Regions with the most land like yours

  1. 1

    🇧🇷Mato Grosso do Sul, Brazil

    101k sq mi262k km² matching 80% or better

    For example Paranaíba (99), Água Clara (99)

  2. 2

    🇧🇷Minas Gerais, Brazil

    96k sq mi249k km² matching 80% or better

    For example Iturama (99), Frutal (98)

  3. 3

    🇧🇷Mato Grosso, Brazil

    80k sq mi207k km² matching 80% or better

    For example Pedra Preta (94), Poconé (93)

  4. 4

    🇧🇴Santa Cruz Department, Bolivia

    29k sq mi75k km² matching 80% or better

    For example San Ignacio de Velasco (95), El Torno (95)

  5. 5

    🇲🇿Zambezia Province, Mozambique

    12k sq mi32k km² matching 80% or better

    For example Morrumbala (81), Alto Molocue (81)

  6. 6

    🇵🇾Concepción, Paraguay

    11k sq mi28k km² matching 80% or better

    For example Yby Yaú (85), Concepción (84)

  7. 7

    🇲🇿Sofala, Mozambique

    8,800 sq mi23k km² matching 80% or better

    For example Gorongosa (87), Dondo (82)

  8. 8

    🇲🇿Gaza Province, Mozambique

    7,300 sq mi19k km² matching 80% or better

    For example Macia (89), Chibuto (86)

  9. 9

    🇲🇲Shan State, Myanmar

    7,300 sq mi19k km² matching 80% or better

    For example Möng Yawng (91), Möng La (87)

  10. 10

    🇨🇳Yunnan, China

    5,600 sq mi14k km² matching 80% or better

    For example Mengla (92), Yunjinghong (91)

  11. 11

    🇹🇭Nan, Thailand

    5,100 sq mi13k km² matching 80% or better

    For example Nan (74)

  12. 12

    🇱🇦Luang Prabang Province, Laos

    5,100 sq mi13k km² matching 80% or better

    For example Luang Prabang (90)

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

    🇧🇷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 22 great-fit crops

    99%match
  2. 2

    🇧🇷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 22 great-fit crops

    99%match
  3. 3

    🇧🇷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
  4. 4

    🇧🇷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
  5. 5

    🇧🇷DracenaSão Paulo, Brazil

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

    Shares 22 of your 22 great-fit crops

    99%match
  6. 6

    🇧🇷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
  7. 7

    🇧🇷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 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

    🇧🇷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
  10. 10

    🇧🇷Água ClaraMato Grosso do Sul, Brazil

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

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

    99%match
  11. 11

    🇧🇷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 22 great-fit crops

    99%match
  12. 12

    🇧🇷PenápolisSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 48 in rainZone 11a · No frost · 0 chill hours · 1,219 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  13. 13

    🇧🇷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
  14. 14

    🇧🇷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 22 great-fit crops

    99%match
  15. 15

    🇧🇷BataguassuMato Grosso do Sul, Brazil

    Zone 11b · No frost · 0 chill hours · 47 in rainZone 11b · No frost · 0 chill hours · 1,186 mm rain

    Shares 22 of your 22 great-fit crops

    99%match
  16. 16

    🇧🇷Presidente EpitácioSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 45 in rainZone 11b · No frost · 0 chill hours · 1,151 mm rain

    Shares 21 of your 22 great-fit crops

    99%match
  17. 17

    🇧🇷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 20 of your 22 great-fit crops · Also great there: potato

    99%match
  18. 18

    🇧🇷Rio Verde de Mato GrossoMato Grosso do Sul, Brazil

    Zone 11b · No frost · 0 chill hours · 54 in rainZone 11b · No frost · 0 chill hours · 1,375 mm rain

    Shares 20 of your 22 great-fit crops

    99%match
  19. 19

    🇧🇷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 22 great-fit crops

    99%match
  20. 20

    🇧🇷TaquaritingaSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 51 in rainZone 11b · No frost · 0 chill hours · 1,303 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 Ilha Solteira: 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.