Climatch

Land with a climate like Kasulu

🇹🇿Kasulu, Kigoma, Tanzania

The towns with the closest growing climate to Kasulu are Kibondo, Tanzania (98% match), Kakonko and Uyovu. About 319,000 sq mi of land in 15 countries matches 80% or better, most of it in Minas Gerais, Brazil, Goiás, Brazil and Tanganyika, Democratic Republic of the Congo.The towns with the closest growing climate to Kasulu are Kibondo, Tanzania (98% match), Kakonko and Uyovu. About 826,000 km² of land in 15 countries matches 80% or better, most of it in Minas Gerais, Brazil, Goiás, Brazil and Tanganyika, Democratic Republic of the Congo.

Your growing climate

Zone 11b · No frost · 0 chill hours · 42 in rainZone 11b · No frost · 0 chill hours · 1,077 mm rain

What grows in Kasulu →

Regions with the most land like yours

  1. 1

    🇧🇷Minas Gerais, Brazil

    48k sq mi123k km² matching 80% or better

    For example Monte Carmelo (87), Coromandel (87)

  2. 2

    🇧🇷Goiás, Brazil

    35k sq mi91k km² matching 80% or better

    For example Planaltina (94), Novo Gama (94)

  3. 3

    🇨🇩Tanganyika, Democratic Republic of the Congo

    17k sq mi45k km² matching 80% or better

    For example Kalemie (90), Nyunzu (84)

  4. 4

    🇦🇴Malanje, Angola

    17k sq mi44k km² matching 80% or better

    For example Bailundo (91), Cacuso (89)

  5. 5

    🇹🇿Kigoma, Tanzania

    17k sq mi43k km² matching 80% or better

    For example Kibondo (98), Kakonko (96)

  6. 6

    🇦🇴Kwanza Sul, Angola

    15k sq mi38k km² matching 80% or better

    For example Santa Clara (92), Quibala (89)

  7. 7

    🇦🇴Luanda Norte, Angola

    14k sq mi36k km² matching 80% or better

    For example Cuilo (80), Lubalo (80)

  8. 8

    🇨🇩Haut-Lomami, Democratic Republic of the Congo

    10k sq mi27k km² matching 80% or better

    For example Kamina (82), Kanyama (77)

  9. 9

    🇹🇿Geita, Tanzania

    7,500 sq mi19k km² matching 80% or better

    For example Diobahika (95), Uyovu (94)

  10. 10

    🇨🇲Adamaoua, Cameroon

    7,100 sq mi18k km² matching 80% or better

    For example Ngaoundal (80), Tibati (78)

  11. 11

    🇹🇿Kagera, Tanzania

    5,700 sq mi15k km² matching 80% or better

    For example Rulenge (92), Bugarama (90)

  12. 12

    🇪🇹Oromiya, Ethiopia

    5,300 sq mi14k km² matching 80% or better

    For example Mendī (83), Gimbi (78)

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

    🇹🇿KibondoKigoma, Tanzania

    Zone 11b · No frost · 0 chill hours · 39 in rainZone 11b · No frost · 0 chill hours · 990 mm rain

    Shares 23 of your 23 great-fit crops

    98%match
  2. 2

    🇹🇿KakonkoKigoma, Tanzania

    Zone 12a · No frost · 0 chill hours · 31 in rainZone 12a · No frost · 0 chill hours · 778 mm rain

    Shares 20 of your 23 great-fit crops · Also great there: table and raisin grapes

    96%match
  3. 3

    🇹🇿UyovuGeita, Tanzania

    Zone 12a · No frost · 0 chill hours · 31 in rainZone 12a · No frost · 0 chill hours · 784 mm rain

    Shares 20 of your 23 great-fit crops · Also great there: table and raisin grapes

    94%match
  4. 4

    🇧🇷BrasíliaFederal District, Brazil

    Zone 11b · No frost · 0 chill hours · 56 in rainZone 11b · No frost · 0 chill hours · 1,411 mm rain

    Shares 22 of your 23 great-fit crops

    94%match
  5. 5

    🇧🇷FormosaGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 53 in rainZone 11b · No frost · 0 chill hours · 1,354 mm rain

    Shares 22 of your 23 great-fit crops

    93%match
  6. 6

    🇧🇷LuziâniaGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 59 in rainZone 11b · No frost · 0 chill hours · 1,494 mm rain

    Shares 22 of your 23 great-fit crops

    92%match
  7. 7

    🇧🇷AlexâniaGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 59 in rainZone 11b · No frost · 0 chill hours · 1,493 mm rain

    Shares 22 of your 23 great-fit crops

    92%match
  8. 8

    🇦🇴Santa ClaraKwanza Sul, Angola

    Zone 11b · No frost · 0 chill hours · 43 in rainZone 11b · No frost · 0 chill hours · 1,099 mm rain

    Shares 23 of your 23 great-fit crops

    92%match
  9. 9

    🇧🇷CristalinaGoiás, Brazil

    Zone 11a · No frost · 0 chill hours · 60 in rainZone 11a · No frost · 0 chill hours · 1,524 mm rain

    Shares 21 of your 23 great-fit crops

    91%match
  10. 10

    🇧🇷Cocalzinho de GoiásGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 60 in rainZone 11b · No frost · 0 chill hours · 1,524 mm rain

    Shares 21 of your 23 great-fit crops

    91%match
  11. 11

    🇹🇿BugaramaKagera, Tanzania

    Zone 12a · No frost · 0 chill hours · 31 in rainZone 12a · No frost · 0 chill hours · 786 mm rain

    Shares 18 of your 23 great-fit crops · Also great there: table and raisin grapes

    90%match
  12. 12

    🇹🇿BiharamuloKagera, Tanzania

    Zone 11b · No frost · 0 chill hours · 30 in rainZone 11b · No frost · 0 chill hours · 767 mm rain

    Shares 19 of your 23 great-fit crops · Also great there: table and raisin grapes

    90%match
  13. 13

    🇨🇩KalemieTanganyika, Democratic Republic of the Congo

    Zone 12a · No frost · 0 chill hours · 37 in rainZone 12a · No frost · 0 chill hours · 933 mm rain

    Shares 20 of your 23 great-fit crops · Also great there: table and raisin grapes

    90%match
  14. 14

    🇦🇴QuibalaKwanza Sul, Angola

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

    Shares 23 of your 23 great-fit crops

    89%match
  15. 15

    🇦🇴CaluloKwanza Sul, Angola

    Zone 11b · No frost · 0 chill hours · 48 in rainZone 11b · No frost · 0 chill hours · 1,207 mm rain

    Shares 22 of your 23 great-fit crops

    89%match
  16. 16

    🇦🇴GabelaKwanza Sul, Angola

    Zone 11b · No frost · 0 chill hours · 42 in rainZone 11b · No frost · 0 chill hours · 1,074 mm rain

    Shares 23 of your 23 great-fit crops

    88%match
  17. 17

    🇧🇷SilvâniaGoiás, Brazil

    Zone 11b · No frost · 0 chill hours · 60 in rainZone 11b · No frost · 0 chill hours · 1,526 mm rain

    Shares 21 of your 23 great-fit crops

    88%match
  18. 18

    🇧🇮GitegaBurundi

    Zone 11b · No frost · 0 chill hours · 40 in rainZone 11b · No frost · 0 chill hours · 1,009 mm rain

    Shares 17 of your 23 great-fit crops

    87%match
  19. 19

    🇧🇷Monte CarmeloMinas Gerais, Brazil

    Zone 11b · No frost · 0 chill hours · 62 in rainZone 11b · No frost · 0 chill hours · 1,566 mm rain

    Shares 21 of your 23 great-fit crops

    87%match
  20. 20

    🇦🇴CangandalaMalanje, Angola

    Zone 11a · No frost · 0 chill hours · 46 in rainZone 11a · No frost · 0 chill hours · 1,170 mm rain

    Shares 23 of your 23 great-fit crops

    87%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 Kasulu: 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.