Climatch

Land with a climate like Andirá

🇧🇷Andirá, Paraná, Brazil

The towns with the closest growing climate to Andirá are Paraguaçu Paulista, Brazil (99% match), Piraju and Colorado. About 527,000 sq mi of land in 17 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 Andirá are Paraguaçu Paulista, Brazil (99% match), Piraju and Colorado. About 1.4 million km² of land in 17 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 · 45 in rainZone 11a · No frost · 4 chill hours · 1,132 mm rain

What grows in Andirá →

Regions with the most land like yours

  1. 1

    🇧🇷Mato Grosso do Sul, Brazil

    79k sq mi204k km² matching 80% or better

    For example Nova Andradina (97), Naviraí (96)

  2. 2

    🇧🇷São Paulo, Brazil

    76k sq mi197k km² matching 80% or better

    For example Paraguaçu Paulista (99), Fartura (99)

  3. 3

    🇧🇷Minas Gerais, Brazil

    46k sq mi120k km² matching 80% or better

    For example Pouso Alegre (92), Santa Rita do Sapucaí (91)

  4. 4

    🇦🇷Corrientes, Argentina

    18k sq mi47k km² matching 80% or better

    For example Ituzaingó (85), Saladas (85)

  5. 5

    🇦🇷Chaco, Argentina

    16k sq mi42k km² matching 80% or better

    For example Resistencia (85), General José de San Martín (84)

  6. 6

    🇺🇸Florida, United States

    15k sq mi38k km² matching 80% or better

    For example Haines City (84), Lake Wales (84)

  7. 7

    🇦🇷Misiones, Argentina

    13k sq mi33k km² matching 80% or better

    For example Puerto Iguazú (88), Jardín América (87)

  8. 8

    🇿🇦KwaZulu-Natal, South Africa

    8,900 sq mi23k km² matching 80% or better

    For example Empangeni (90), Mandeni (88)

  9. 9

    🇨🇳Yunnan, China

    8,600 sq mi22k km² matching 80% or better

    For example Mengman (83), Mengla (82)

  10. 10

    🇵🇾Concepción, Paraguay

    7,400 sq mi19k km² matching 80% or better

    For example Yby Yaú (89), Concepción (79)

  11. 11

    🇵🇾Caaguazú Department, Paraguay

    6,800 sq mi18k km² matching 80% or better

    For example Caaguazú (89), Doctor Juan Eulogio Estigarribia (89)

  12. 12

    🇵🇪Junin, Peru

    5,300 sq mi14k km² matching 80% or better

    For example San Martín de Pangoa (83), Satipo (82)

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

    🇧🇷Paraguaçu PaulistaSão Paulo, Brazil

    Zone 11a · No frost · 0 chill hours · 48 in rainZone 11a · No frost · 0 chill hours · 1,221 mm rain

    Shares 23 of your 23 great-fit crops

    99%match
  2. 2

    🇧🇷PirajuSão Paulo, 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 23 great-fit crops

    99%match
  3. 3

    🇧🇷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 23 great-fit crops

    99%match
  4. 4

    🇧🇷TaquaritubaSão Paulo, Brazil

    Zone 11a · No frost · 7 chill hours · 47 in rainZone 11a · No frost · 7 chill hours · 1,202 mm rain

    Shares 22 of your 23 great-fit crops · Also great there: wine grapes

    99%match
  5. 5

    🇧🇷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 23 great-fit crops

    99%match
  6. 6

    🇧🇷LondrinaParaná, Brazil

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

    Shares 22 of your 23 great-fit crops · Also great there: tea

    99%match
  7. 7

    🇧🇷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 23 great-fit crops

    99%match
  8. 8

    🇧🇷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 23 great-fit crops

    99%match
  9. 9

    🇧🇷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 23 great-fit crops · Also great there: wine grapes

    99%match
  10. 10

    🇧🇷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 23 great-fit crops

    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 23 of your 23 great-fit crops

    99%match
  12. 12

    🇧🇷Mirante do ParanapanemaSão Paulo, Brazil

    Zone 11b · No frost · 0 chill hours · 45 in rainZone 11b · No frost · 0 chill hours · 1,153 mm rain

    Shares 22 of your 23 great-fit crops

    98%match
  13. 13

    🇧🇷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 23 great-fit crops

    98%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 23 great-fit crops

    98%match
  15. 15

    🇧🇷ParanavaíParaná, Brazil

    Zone 11a · No frost · 4 chill hours · 48 in rainZone 11a · No frost · 4 chill hours · 1,219 mm rain

    Shares 22 of your 23 great-fit crops

    98%match
  16. 16

    🇧🇷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 23 great-fit crops

    98%match
  17. 17

    🇧🇷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 23 great-fit crops · Also great there: wine grapes

    97%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 23 great-fit crops

    97%match
  19. 19

    🇧🇷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 23 great-fit crops

    97%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 22 of your 23 great-fit crops

    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 Andirá: 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.