Climatch

Land with a climate like Santa Cruz do Rio Pardo

🇧🇷Santa Cruz do Rio Pardo, São Paulo, Brazil

The towns with the closest growing climate to Santa Cruz do Rio Pardo are Assis, Brazil (99% match), Marília and Tupã. About 526,000 sq mi of land in 15 countries matches 80% or better, most of it in Mato Grosso do Sul, Brazil, São Paulo, Brazil and Minas Gerais, Brazil.The towns with the closest growing climate to Santa Cruz do Rio Pardo are Assis, Brazil (99% match), Marília and Tupã. About 1.4 million km² of land in 15 countries matches 80% or better, most of it in Mato Grosso do Sul, Brazil, São Paulo, Brazil and Minas Gerais, Brazil.

Your growing climate

Zone 11a · No frost · 4 chill hours · 53 in rainZone 11a · No frost · 4 chill hours · 1,358 mm rain

What grows in Santa Cruz do Rio Pardo →

Regions with the most land like yours

  1. 1

    🇧🇷Mato Grosso do Sul, Brazil

    82k sq mi213k km² matching 80% or better

    For example Nova Andradina (96), Dourados (95)

  2. 2

    🇧🇷São Paulo, Brazil

    82k sq mi213k km² matching 80% or better

    For example Assis (99), Cândido Mota (99)

  3. 3

    🇧🇷Minas Gerais, Brazil

    81k sq mi210k km² matching 80% or better

    For example Pouso Alegre (97), Borda da Mata (96)

  4. 4

    🇨🇳Yunnan, China

    12k sq mi32k km² matching 80% or better

    For example Mengman (85), Mengla (84)

  5. 5

    🇦🇷Chaco, Argentina

    11k sq mi29k km² matching 80% or better

    For example Resistencia (82), General José de San Martín (81)

  6. 6

    🇦🇷Corrientes, Argentina

    9,800 sq mi25k km² matching 80% or better

    For example Ituzaingó (81), Corrientes (81)

  7. 7

    🇦🇷Misiones, Argentina

    9,600 sq mi25k km² matching 80% or better

    For example Puerto Iguazú (85), Puerto Esperanza (83)

  8. 8

    🇿🇦KwaZulu-Natal, South Africa

    7,600 sq mi20k km² matching 80% or better

    For example Empangeni (87), Mandeni (87)

  9. 9

    🇵🇾Caaguazú Department, Paraguay

    6,200 sq mi16k km² matching 80% or better

    For example Caaguazú (85), Doctor Juan Eulogio Estigarribia (85)

  10. 10

    🇵🇪Junin, Peru

    5,900 sq mi15k km² matching 80% or better

    For example San Martín de Pangoa (84), Satipo (83)

  11. 11

    🇵🇾Concepción, Paraguay

    5,200 sq mi14k km² matching 80% or better

    For example Yby Yaú (85), Concepción (73)

  12. 12

    🇵🇾Misiones Department, Paraguay

    5,100 sq mi13k km² matching 80% or better

    For example San Juan Bautista (80)

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

    🇧🇷AssisSão Paulo, Brazil

    Zone 11a · No frost · 2 chill hours · 47 in rainZone 11a · No frost · 2 chill hours · 1,192 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  2. 2

    🇧🇷MaríliaSão Paulo, Brazil

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

    Shares 23 of your 24 great-fit crops

    99%match
  3. 3

    🇧🇷TupãSão Paulo, Brazil

    Zone 11a · No frost · 1 chill hours · 50 in rainZone 11a · No frost · 1 chill hours · 1,267 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  4. 4

    🇧🇷Cornélio ProcópioParaná, Brazil

    Zone 11a · No frost · 4 chill hours · 49 in rainZone 11a · No frost · 4 chill hours · 1,245 mm rain

    Shares 22 of your 24 great-fit crops

    99%match
  5. 5

    🇧🇷RanchariaSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 49 in rainZone 11a · No frost · 0 chill hours · 1,256 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  6. 6

    🇧🇷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
  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 23 of your 24 great-fit crops

    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 24 great-fit crops

    99%match
  9. 9

    🇧🇷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
  10. 10

    🇧🇷LondrinaParaná, Brazil

    Zone 11a · No frost · 3 chill hours · 59 in rainZone 11a · No frost · 3 chill hours · 1,500 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  11. 11

    🇧🇷AvaréSão Paulo, Brazil

    Zone 11a · No frost · 8 chill hours · 49 in rainZone 11a · No frost · 8 chill hours · 1,233 mm rain

    Shares 22 of your 24 great-fit crops · Also great there: wine grapes

    99%match
  12. 12

    🇧🇷ColoradoParaná, Brazil

    Zone 11a · No frost · 0 chill hours · 49 in rainZone 11a · No frost · 0 chill hours · 1,253 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  13. 13

    🇧🇷Terra RicaParaná, Brazil

    Zone 11a · No frost · 0 chill hours · 47 in rainZone 11a · No frost · 0 chill hours · 1,183 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  14. 14

    🇧🇷Siqueira CamposParaná, Brazil

    Zone 11a · No frost · 10 chill hours · 47 in rainZone 11a · No frost · 10 chill hours · 1,194 mm rain

    Shares 22 of your 24 great-fit crops · Also great there: wine grapes

    99%match
  15. 15

    🇧🇷LoandaParaná, Brazil

    Zone 11a · No frost · 0 chill hours · 49 in rainZone 11a · No frost · 0 chill hours · 1,232 mm rain

    Shares 23 of your 24 great-fit crops

    99%match
  16. 16

    🇧🇷AngatubaSão Paulo, Brazil

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

    Shares 22 of your 24 great-fit crops · Also great there: wine grapes

    98%match
  17. 17

    🇧🇷CampinasSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 49 in rainZone 11a · No frost · 0 chill hours · 1,256 mm rain

    Shares 23 of your 24 great-fit crops

    98%match
  18. 18

    🇧🇷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

    98%match
  19. 19

    🇧🇷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 24 great-fit crops

    98%match
  20. 20

    🇧🇷ItaberáSão Paulo, Brazil

    Zone 10b · No frost · 23 chill hours · 47 in rainZone 10b · No frost · 23 chill hours · 1,188 mm rain

    Shares 20 of your 24 great-fit crops · Also great there: wine grapes

    97%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 Cruz do Rio Pardo: 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.