Climatch

Land with a climate like Sapezal

🇧🇷Sapezal, Mato Grosso, Brazil

The towns with the closest growing climate to Sapezal are Comodoro, Brazil (99% match), Vilhena and Campo Novo do Parecis. About 798,000 sq mi of land in 12 countries matches 80% or better, most of it in Mato Grosso, Brazil, Rondônia, Brazil and Goiás, Brazil.The towns with the closest growing climate to Sapezal are Comodoro, Brazil (99% match), Vilhena and Campo Novo do Parecis. About 2.1 million km² of land in 12 countries matches 80% or better, most of it in Mato Grosso, Brazil, Rondônia, Brazil and Goiás, Brazil.

Your growing climate

Zone 11b · No frost · 0 chill hours · 79 in rainZone 11b · No frost · 0 chill hours · 2,003 mm rain

What grows in Sapezal →

Regions with the most land like yours

  1. 1

    🇧🇷Mato Grosso, Brazil

    157k sq mi407k km² matching 80% or better

    For example Comodoro (99), Campo Novo do Parecis (99)

  2. 2

    🇧🇷Rondônia, Brazil

    72k sq mi186k km² matching 80% or better

    For example Vilhena (99), Colorado do Oeste (99)

  3. 3

    🇧🇷Goiás, Brazil

    49k sq mi127k km² matching 80% or better

    For example Jataí (89), Quirinópolis (89)

  4. 4

    🇨🇲East, Cameroon

    11k sq mi28k km² matching 80% or better

    For example Abong Mbang (83), Bertoua (82)

  5. 5

    🇬🇳Nzérékoré Region, Guinea

    10k sq mi27k km² matching 80% or better

    For example Lola (93), Nzérékoré (92)

  6. 6

    🇨🇮Montagnes, Ivory Coast

    7,700 sq mi20k km² matching 80% or better

    For example Biankouma (89), Mahapleu (88)

  7. 7

    🇨🇩Kwilu, Democratic Republic of the Congo

    6,300 sq mi16k km² matching 80% or better

    For example Idiofa (79), Masi-Manimba (75)

  8. 8

    🇬🇳Faranah, Guinea

    6,200 sq mi16k km² matching 80% or better

    For example Yende Millimou (91), Kissidougou (89)

  9. 9

    🇨🇩Tanganyika, Democratic Republic of the Congo

    5,700 sq mi15k km² matching 80% or better

    For example Kalima (79), Kongolo (78)

  10. 10

    🇸🇱Eastern Province, Sierra Leone

    5,000 sq mi13k km² matching 80% or better

    For example Koidu (88), Kenema (80)

  11. 11

    🇧🇴Santa Cruz Department, Bolivia

    4,300 sq mi11k km² matching 80% or better

    For example San Ignacio de Velasco (81), Ascención de Guarayos (70)

  12. 12

    🇨🇩Kwango, Democratic Republic of the Congo

    4,200 sq mi11k km² matching 80% or better

    For example Kasongo-Lunda (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

    🇧🇷ComodoroMato Grosso, Brazil

    Zone 11b · No frost · 0 chill hours · 77 in rainZone 11b · No frost · 0 chill hours · 1,955 mm rain

    Shares 21 of your 21 great-fit crops · Also great there: barley, coffee (arabica)

    99%match
  2. 2

    🇧🇷VilhenaRondônia, Brazil

    Zone 12a · No frost · 0 chill hours · 81 in rainZone 12a · No frost · 0 chill hours · 2,070 mm rain

    Shares 21 of your 21 great-fit crops

    99%match
  3. 3

    🇧🇷Campo Novo do ParecisMato Grosso, Brazil

    Zone 11b · No frost · 0 chill hours · 79 in rainZone 11b · No frost · 0 chill hours · 2,002 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  4. 4

    🇧🇷Colorado do OesteRondônia, Brazil

    Zone 12a · No frost · 0 chill hours · 75 in rainZone 12a · No frost · 0 chill hours · 1,911 mm rain

    Shares 20 of your 21 great-fit crops

    99%match
  5. 5

    🇧🇷Tangará da SerraMato Grosso, Brazil

    Zone 11b · No frost · 0 chill hours · 65 in rainZone 11b · No frost · 0 chill hours · 1,650 mm rain

    Shares 17 of your 21 great-fit crops

    99%match
  6. 6

    🇧🇷Rolim de MouraRondônia, Brazil

    Zone 12a · No frost · 0 chill hours · 69 in rainZone 12a · No frost · 0 chill hours · 1,751 mm rain

    Shares 19 of your 21 great-fit crops

    98%match
  7. 7

    🇧🇷CacoalRondônia, Brazil

    Zone 12a · No frost · 0 chill hours · 81 in rainZone 12a · No frost · 0 chill hours · 2,062 mm rain

    Shares 18 of your 21 great-fit crops

    97%match
  8. 8

    🇧🇷JuínaMato Grosso, Brazil

    Zone 12a · No frost · 0 chill hours · 81 in rainZone 12a · No frost · 0 chill hours · 2,048 mm rain

    Shares 17 of your 21 great-fit crops

    97%match
  9. 9

    🇧🇷Nova MutumMato Grosso, Brazil

    Zone 12a · No frost · 0 chill hours · 73 in rainZone 12a · No frost · 0 chill hours · 1,854 mm rain

    Shares 17 of your 21 great-fit crops

    97%match
  10. 10

    🇧🇷BrasnorteMato Grosso, Brazil

    Zone 12a · No frost · 0 chill hours · 83 in rainZone 12a · No frost · 0 chill hours · 2,111 mm rain

    Shares 17 of your 21 great-fit crops

    97%match
  11. 11

    🇧🇷Ouro Preto do OesteRondônia, Brazil

    Zone 12a · No frost · 0 chill hours · 80 in rainZone 12a · No frost · 0 chill hours · 2,024 mm rain

    Shares 20 of your 21 great-fit crops

    96%match
  12. 12

    🇧🇷JaciaraMato Grosso, Brazil

    Zone 11b · No frost · 0 chill hours · 61 in rainZone 11b · No frost · 0 chill hours · 1,541 mm rain

    Shares 17 of your 21 great-fit crops

    95%match
  13. 13

    🇧🇷DiamantinoMato Grosso, Brazil

    Zone 12a · No frost · 0 chill hours · 63 in rainZone 12a · No frost · 0 chill hours · 1,605 mm rain

    Shares 16 of your 21 great-fit crops

    95%match
  14. 14

    🇧🇷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 19 of your 21 great-fit crops

    95%match
  15. 15

    🇧🇷RondonópolisMato Grosso, Brazil

    Zone 11b · No frost · 0 chill hours · 61 in rainZone 11b · No frost · 0 chill hours · 1,541 mm rain

    Shares 17 of your 21 great-fit crops

    94%match
  16. 16

    🇧🇷TapurahMato Grosso, Brazil

    Zone 12a · No frost · 0 chill hours · 85 in rainZone 12a · No frost · 0 chill hours · 2,160 mm rain

    Shares 19 of your 21 great-fit crops

    94%match
  17. 17

    🇧🇷Barra do BugresMato Grosso, Brazil

    Zone 12a · No frost · 0 chill hours · 54 in rainZone 12a · No frost · 0 chill hours · 1,384 mm rain

    Shares 16 of your 21 great-fit crops · Also great there: fig

    94%match
  18. 18

    🇧🇷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 21 great-fit crops

    94%match
  19. 19

    🇧🇷JaruRondônia, Brazil

    Zone 12b · No frost · 0 chill hours · 82 in rainZone 12b · No frost · 0 chill hours · 2,086 mm rain

    Shares 18 of your 21 great-fit crops

    94%match
  20. 20

    🇧🇷Ji ParanáRondônia, Brazil

    Zone 12a · No frost · 0 chill hours · 85 in rainZone 12a · No frost · 0 chill hours · 2,168 mm rain

    Shares 18 of your 21 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 Sapezal: 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.