Climatch

Land with a climate like Santa Rosa de Viterbo

🇧🇷Santa Rosa de Viterbo, São Paulo, Brazil

The towns with the closest growing climate to Santa Rosa de Viterbo are Araraquara, Brazil (99% match), São João da Boa Vista and Jaboticabal. About 609,000 sq mi of land in 22 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 Santa Rosa de Viterbo are Araraquara, Brazil (99% match), São João da Boa Vista and Jaboticabal. About 1.6 million km² of land in 22 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 · 55 in rainZone 11a · No frost · 0 chill hours · 1,388 mm rain

What grows in Santa Rosa de Viterbo →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    153k sq mi397k km² matching 80% or better

    For example Passos (99), Uberaba (99)

  2. 2

    🇧🇷Mato Grosso do Sul, Brazil

    79k sq mi205k km² matching 80% or better

    For example Chapadão do Sul (99), Aparecida do Taboado (98)

  3. 3

    🇧🇷São Paulo, Brazil

    78k sq mi201k km² matching 80% or better

    For example Aguaí (99), Araraquara (99)

  4. 4

    🇲🇲Shan State, Myanmar

    17k sq mi43k km² matching 80% or better

    For example Kēng Tung (84), Möng La (84)

  5. 5

    🇨🇳Yunnan, China

    16k sq mi42k km² matching 80% or better

    For example Mengman (86), Mengla (85)

  6. 6

    🇧🇴Santa Cruz Department, Bolivia

    7,400 sq mi19k km² matching 80% or better

    For example El Torno (84), San Ignacio de Velasco (78)

  7. 7

    🇻🇳Điện Biên Province, Vietnam

    6,700 sq mi17k km² matching 80% or better

    For example Mường Lay (75), Dien Bien Phu (74)

  8. 8

    🇱🇦Luang Prabang Province, Laos

    5,100 sq mi13k km² matching 80% or better

    For example Luang Prabang (66)

  9. 9

    🇱🇦Oudômxai, Laos

    5,000 sq mi13k km² matching 80% or better

    For example Muang Xay (87)

  10. 10

    🇲🇿Zambezia Province, Mozambique

    4,900 sq mi13k km² matching 80% or better

    For example Milange (80), Gurúè (79)

  11. 11

    🇱🇦Xiangkhoang, Laos

    4,800 sq mi12k km² matching 80% or better

    For example Muang Phônsavan (92)

  12. 12

    🇲🇿Maputo Province, Mozambique

    4,300 sq mi11k km² matching 80% or better

    For example Manhiça (83), Ressano Garcia (79)

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 24 great-fit crops

    99%match
  2. 2

    🇧🇷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 24 of your 24 great-fit crops

    99%match
  3. 3

    🇧🇷JaboticabalSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 53 in rainZone 11b · No frost · 0 chill hours · 1,335 mm rain

    Shares 21 of your 24 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 24 great-fit crops

    99%match
  5. 5

    🇧🇷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 24 great-fit crops

    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 24 great-fit crops

    99%match
  7. 7

    🇧🇷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 24 great-fit crops

    99%match
  8. 8

    🇧🇷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 24 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 24 great-fit crops

    99%match
  10. 10

    🇧🇷PassosMinas Gerais, Brazil

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

    Shares 23 of your 24 great-fit crops

    99%match
  11. 11

    🇧🇷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 24 great-fit crops

    99%match
  12. 12

    🇧🇷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 23 of your 24 great-fit crops

    99%match
  13. 13

    🇧🇷UberabaMinas Gerais, Brazil

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

    Shares 23 of your 24 great-fit crops

    99%match
  14. 14

    🇧🇷LinsSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 48 in rainZone 11a · No frost · 0 chill hours · 1,224 mm rain

    Shares 23 of your 24 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 22 of your 24 great-fit crops

    99%match
  16. 16

    🇧🇷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 24 great-fit crops

    99%match
  17. 17

    🇧🇷AlfenasMinas Gerais, Brazil

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

    Shares 23 of your 24 great-fit crops

    99%match
  18. 18

    🇧🇷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 23 of your 24 great-fit crops

    99%match
  19. 19

    🇧🇷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 24 great-fit crops

    99%match
  20. 20

    🇧🇷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 24 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 Santa Rosa de Viterbo: 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.