Climatch

Land with a climate like San Fernando, Peru

🇵🇪San Fernando, Ucayali, Peru

The towns with the closest growing climate to San Fernando, Peru are Contamana, Peru (99% match), Yurimaguas and La Banda. About 2.3 million sq mi of land in 22 countries matches 80% or better, most of it in Amazonas, Brazil, Pará, Brazil and Acre, Brazil.The towns with the closest growing climate to San Fernando, Peru are Contamana, Peru (99% match), Yurimaguas and La Banda. About 6.1 million km² of land in 22 countries matches 80% or better, most of it in Amazonas, Brazil, Pará, Brazil and Acre, Brazil.

Your growing climate

Zone 13a · No frost · 0 chill hours · 70 in rainZone 13a · No frost · 0 chill hours · 1,769 mm rain

What grows in San Fernando, Peru →

Regions with the most land like yours

  1. 1

    🇧🇷Amazonas, Brazil

    218k sq mi563k km² matching 80% or better

    For example Eirunepé (97), Guajará (96)

  2. 2

    🇧🇷Pará, Brazil

    49k sq mi127k km² matching 80% or better

    For example Trairão (93), Itaituba (92)

  3. 3

    🇧🇷Acre, Brazil

    46k sq mi119k km² matching 80% or better

    For example Marechal Thaumaturgo (99), Rio Branco (98)

  4. 4

    🇨🇩Mai-Ndombe, Democratic Republic of the Congo

    26k sq mi67k km² matching 80% or better

    For example Inongo (92), Kutu (91)

  5. 5

    🇵🇪Loreto, Peru

    25k sq mi66k km² matching 80% or better

    For example Contamana (99), Yurimaguas (99)

  6. 6

    🇮🇩Central Kalimantan, Indonesia

    25k sq mi64k km² matching 80% or better

    For example Sampit (85), Palangkaraya (84)

  7. 7

    🇨🇩Tshopo, Democratic Republic of the Congo

    22k sq mi58k km² matching 80% or better

    For example Kisangani (93), Basoko (92)

  8. 8

    🇧🇴Beni Department, Bolivia

    22k sq mi56k km² matching 80% or better

    For example San Borja (92), Trinidad (91)

  9. 9

    🇮🇩South Sumatra, Indonesia

    19k sq mi49k km² matching 80% or better

    For example Baturaja (85), Lubuklinggau (84)

  10. 10

    🇨🇬Cuvette, Republic of the Congo

    19k sq mi49k km² matching 80% or better

    For example Mossaka (90), Oyo (90)

  11. 11

    🇮🇩Jambi, Indonesia

    19k sq mi49k km² matching 80% or better

    For example Jambi City (85), Muara Bungo (85)

  12. 12

    🇨🇩Mongala, Democratic Republic of the Congo

    17k sq mi45k km² matching 80% or better

    For example Bumba (89), Lisala (85)

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

    🇵🇪ContamanaLoreto, Peru

    Zone 13a · No frost · 0 chill hours · 68 in rainZone 13a · No frost · 0 chill hours · 1,716 mm rain

    Shares 17 of your 19 great-fit crops

    99%match
  2. 2

    🇵🇪YurimaguasLoreto, Peru

    Zone 13a · No frost · 0 chill hours · 84 in rainZone 13a · No frost · 0 chill hours · 2,137 mm rain

    Shares 17 of your 19 great-fit crops

    99%match
  3. 3

    🇵🇪La BandaSan Martín Department, Peru

    Zone 13a · No frost · 0 chill hours · 58 in rainZone 13a · No frost · 0 chill hours · 1,485 mm rain

    Shares 18 of your 19 great-fit crops · Also great there: fig

    99%match
  4. 4

    🇧🇷Marechal ThaumaturgoAcre, Brazil

    Zone 12b · No frost · 0 chill hours · 71 in rainZone 12b · No frost · 0 chill hours · 1,803 mm rain

    Shares 19 of your 19 great-fit crops

    99%match
  5. 5

    🇵🇪JuanjuíSan Martín Department, Peru

    Zone 13a · No frost · 0 chill hours · 56 in rainZone 13a · No frost · 0 chill hours · 1,426 mm rain

    Shares 18 of your 19 great-fit crops · Also great there: fig

    99%match
  6. 6

    🇧🇷Rio BrancoAcre, Brazil

    Zone 12b · No frost · 0 chill hours · 68 in rainZone 12b · No frost · 0 chill hours · 1,724 mm rain

    Shares 19 of your 19 great-fit crops

    98%match
  7. 7

    🇧🇷EirunepéAmazonas, Brazil

    Zone 13a · No frost · 0 chill hours · 98 in rainZone 13a · No frost · 0 chill hours · 2,500 mm rain

    Shares 19 of your 19 great-fit crops

    97%match
  8. 8

    🇵🇪Puerto MaldonadoMadre de Dios, Peru

    Zone 12b · No frost · 0 chill hours · 88 in rainZone 12b · No frost · 0 chill hours · 2,242 mm rain

    Shares 19 of your 19 great-fit crops

    97%match
  9. 9

    🇧🇷Cruzeiro do SulAcre, Brazil

    Zone 12b · No frost · 0 chill hours · 82 in rainZone 12b · No frost · 0 chill hours · 2,088 mm rain

    Shares 19 of your 19 great-fit crops

    97%match
  10. 10

    🇵🇪RequenaLoreto, Peru

    Zone 13a · No frost · 0 chill hours · 98 in rainZone 13a · No frost · 0 chill hours · 2,477 mm rain

    Shares 19 of your 19 great-fit crops

    97%match
  11. 11

    🇵🇪AtalayaUcayali, Peru

    Zone 12b · No frost · 0 chill hours · 62 in rainZone 12b · No frost · 0 chill hours · 1,565 mm rain

    Shares 19 of your 19 great-fit crops

    96%match
  12. 12

    🇧🇷Plácido de CastroAcre, Brazil

    Zone 12b · No frost · 0 chill hours · 69 in rainZone 12b · No frost · 0 chill hours · 1,746 mm rain

    Shares 19 of your 19 great-fit crops

    96%match
  13. 13

    🇧🇷IpixunaAmazonas, Brazil

    Zone 13a · No frost · 0 chill hours · 98 in rainZone 13a · No frost · 0 chill hours · 2,499 mm rain

    Shares 19 of your 19 great-fit crops

    96%match
  14. 14

    🇧🇷TapauáAmazonas, Brazil

    Zone 13a · No frost · 0 chill hours · 94 in rainZone 13a · No frost · 0 chill hours · 2,389 mm rain

    Shares 18 of your 19 great-fit crops

    95%match
  15. 15

    🇵🇪TocacheSan Martín Department, Peru

    Zone 12b · No frost · 0 chill hours · 90 in rainZone 12b · No frost · 0 chill hours · 2,298 mm rain

    Shares 19 of your 19 great-fit crops

    95%match
  16. 16

    🇵🇭Kidapawan↻Seasons flipped. Soccsksargen, Philippines

    Zone 13a · No frost · 0 chill hours · 86 in rainZone 13a · No frost · 0 chill hours · 2,189 mm rain

    Shares 19 of your 19 great-fit crops

    95%match
  17. 17

    🇧🇷TarauacáAcre, Brazil

    Zone 12b · No frost · 0 chill hours · 94 in rainZone 12b · No frost · 0 chill hours · 2,387 mm rain

    Shares 19 of your 19 great-fit crops

    94%match
  18. 18

    🇧🇷CarauariAmazonas, Brazil

    Zone 13a · No frost · 0 chill hours · 102 in rainZone 13a · No frost · 0 chill hours · 2,585 mm rain

    Shares 19 of your 19 great-fit crops

    94%match
  19. 19

    🇧🇷Porto AcreAcre, Brazil

    Zone 12b · No frost · 0 chill hours · 72 in rainZone 12b · No frost · 0 chill hours · 1,825 mm rain

    Shares 19 of your 19 great-fit crops

    94%match
  20. 20

    🇧🇷CoariAmazonas, Brazil

    Zone 13b · No frost · 0 chill hours · 93 in rainZone 13b · No frost · 0 chill hours · 2,358 mm rain

    Shares 18 of your 19 great-fit crops

    94%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 San Fernando, Peru: 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.