Climatch

Land with a climate like Xinguara

🇧🇷Xinguara, Pará, Brazil

The towns with the closest growing climate to Xinguara are Redenção, Brazil (99% match), Cumaru do Norte and Parauapebas. About 1.6 million sq mi of land in 23 countries matches 80% or better, most of it in Mato Grosso, Brazil, Pará, Brazil and Rondônia, Brazil.The towns with the closest growing climate to Xinguara are Redenção, Brazil (99% match), Cumaru do Norte and Parauapebas. About 4.2 million km² of land in 23 countries matches 80% or better, most of it in Mato Grosso, Brazil, Pará, Brazil and Rondônia, Brazil.

Your growing climate

Zone 12b · No frost · 0 chill hours · 66 in rainZone 12b · No frost · 0 chill hours · 1,664 mm rain

What grows in Xinguara →

Regions with the most land like yours

  1. 1

    🇧🇷Mato Grosso, Brazil

    138k sq mi356k km² matching 80% or better

    For example Colniza (98), Aripuanã (98)

  2. 2

    🇧🇷Pará, Brazil

    111k sq mi286k km² matching 80% or better

    For example Redenção (99), Ourilândia do Norte (99)

  3. 3

    🇧🇷Rondônia, Brazil

    81k sq mi210k km² matching 80% or better

    For example Rolim de Moura do Guaporé (97), São Francisco do Guaporé (97)

  4. 4

    🇨🇩Kwilu, Democratic Republic of the Congo

    27k sq mi70k km² matching 80% or better

    For example Masi-Manimba (91), Bulungu (88)

  5. 5

    🇨🇲East, Cameroon

    22k sq mi57k km² matching 80% or better

    For example Batouri (93), Bertoua (92)

  6. 6

    🇨🇩Bas-Uele, Democratic Republic of the Congo

    16k sq mi43k km² matching 80% or better

    For example Bondo (84), Aketi (84)

  7. 7

    🇨🇲Centre, Cameroon

    16k sq mi42k km² matching 80% or better

    For example Nanga Eboko (93), Bafia (92)

  8. 8

    🇨🇩Kasai, Democratic Republic of the Congo

    15k sq mi40k km² matching 80% or better

    For example Ilebo (85), Mweka (85)

  9. 9

    🇧🇴Beni Department, Bolivia

    14k sq mi36k km² matching 80% or better

    For example Guayaramerín (90), Riberalta (89)

  10. 10

    🇨🇮Montagnes, Ivory Coast

    12k sq mi30k km² matching 80% or better

    For example Logoualé (91), Gohouo (91)

  11. 11

    🇨🇬Likouala, Republic of the Congo

    9,000 sq mi23k km² matching 80% or better

    For example Mindouli (85), Bétou (85)

  12. 12

    🇨🇮Sassandra-Marahoue, Ivory Coast

    8,900 sq mi23k km² matching 80% or better

    For example Pélézi (89), Belleville (89)

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

    🇧🇷RedençãoPará, Brazil

    Zone 12b · No frost · 0 chill hours · 67 in rainZone 12b · No frost · 0 chill hours · 1,710 mm rain

    Shares 16 of your 17 great-fit crops

    99%match
  2. 2

    🇧🇷Cumaru do NortePará, Brazil

    Zone 12b · No frost · 0 chill hours · 71 in rainZone 12b · No frost · 0 chill hours · 1,794 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  3. 3

    🇧🇷ParauapebasPará, Brazil

    Zone 13a · No frost · 0 chill hours · 66 in rainZone 13a · No frost · 0 chill hours · 1,672 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  4. 4

    🇧🇷AraguaínaTocantins, Brazil

    Zone 12b · No frost · 0 chill hours · 62 in rainZone 12b · No frost · 0 chill hours · 1,570 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  5. 5

    🇧🇷TucumãPará, Brazil

    Zone 12b · No frost · 0 chill hours · 70 in rainZone 12b · No frost · 0 chill hours · 1,770 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  6. 6

    🇧🇷Eldorado dos CarajásPará, Brazil

    Zone 13a · No frost · 0 chill hours · 62 in rainZone 13a · No frost · 0 chill hours · 1,569 mm rain

    Shares 15 of your 17 great-fit crops

    99%match
  7. 7

    🇧🇷São Félix do XinguPará, Brazil

    Zone 12b · No frost · 0 chill hours · 73 in rainZone 12b · No frost · 0 chill hours · 1,847 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  8. 8

    🇧🇷Novo ProgressoPará, Brazil

    Zone 13a · No frost · 0 chill hours · 85 in rainZone 13a · No frost · 0 chill hours · 2,167 mm rain

    Shares 15 of your 17 great-fit crops

    99%match
  9. 9

    🇧🇷ColnizaMato Grosso, Brazil

    Zone 12b · No frost · 0 chill hours · 78 in rainZone 12b · No frost · 0 chill hours · 1,987 mm rain

    Shares 16 of your 17 great-fit crops

    98%match
  10. 10

    🇧🇷São Geraldo do AraguaiaPará, Brazil

    Zone 12b · No frost · 0 chill hours · 54 in rainZone 12b · No frost · 0 chill hours · 1,364 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: fig

    98%match
  11. 11

    🇧🇷AripuanãMato Grosso, Brazil

    Zone 12b · No frost · 0 chill hours · 80 in rainZone 12b · No frost · 0 chill hours · 2,027 mm rain

    Shares 16 of your 17 great-fit crops

    98%match
  12. 12

    🇧🇷Colinas do TocantinsTocantins, Brazil

    Zone 12b · No frost · 0 chill hours · 65 in rainZone 12b · No frost · 0 chill hours · 1,645 mm rain

    Shares 16 of your 17 great-fit crops

    98%match
  13. 13

    🇧🇷Rolim de Moura do GuaporéRondônia, Brazil

    Zone 12b · No frost · 0 chill hours · 59 in rainZone 12b · No frost · 0 chill hours · 1,493 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: macadamia, tea, fig

    97%match
  14. 14

    🇧🇷São Francisco do GuaporéRondônia, Brazil

    Zone 12b · No frost · 0 chill hours · 64 in rainZone 12b · No frost · 0 chill hours · 1,620 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: tea

    97%match
  15. 15

    🇧🇷EstreitoMaranhão, Brazil

    Zone 12b · No frost · 0 chill hours · 56 in rainZone 12b · No frost · 0 chill hours · 1,419 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: fig

    97%match
  16. 16

    🇧🇷CerejeirasRondônia, Brazil

    Zone 12a · No frost · 0 chill hours · 73 in rainZone 12a · No frost · 0 chill hours · 1,851 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: tea, wheat

    96%match
  17. 17

    🇧🇷São Miguel do GuaporéRondônia, Brazil

    Zone 12b · No frost · 0 chill hours · 69 in rainZone 12b · No frost · 0 chill hours · 1,741 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: tea, macadamia

    96%match
  18. 18

    🇧🇷Conceição do AraguaiaPará, Brazil

    Zone 12b · No frost · 0 chill hours · 64 in rainZone 12b · No frost · 0 chill hours · 1,634 mm rain

    Shares 15 of your 17 great-fit crops

    96%match
  19. 19

    🇧🇷Monte NegroRondônia, Brazil

    Zone 12b · No frost · 0 chill hours · 83 in rainZone 12b · No frost · 0 chill hours · 2,096 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: tea

    96%match
  20. 20

    🇧🇷São Domingos do AraguaiaPará, Brazil

    Zone 13a · No frost · 0 chill hours · 60 in rainZone 13a · No frost · 0 chill hours · 1,536 mm rain

    Shares 15 of your 17 great-fit crops

    96%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 Xinguara: 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.