Climatch

Land with a climate like Merelani

🇹🇿Merelani, Arusha, Tanzania

The towns with the closest growing climate to Merelani are Taveta, Kenya (99% match), Same and Hedaru. About 77,000 sq mi of land in 4 countries matches 80% or better, most of it in Bahia, Brazil, Pernambuco, Brazil and Kilimanjaro, Tanzania.The towns with the closest growing climate to Merelani are Taveta, Kenya (99% match), Same and Hedaru. About 201,000 km² of land in 4 countries matches 80% or better, most of it in Bahia, Brazil, Pernambuco, Brazil and Kilimanjaro, Tanzania.

Your growing climate

Zone 12a · No frost · 0 chill hours · 25 in rainZone 12a · No frost · 0 chill hours · 626 mm rain

What grows in Merelani →

Regions with the most land like yours

  1. 1

    🇧🇷Bahia, Brazil

    15k sq mi39k km² matching 80% or better

    For example Uauá (86), Umburanas (86)

  2. 2

    🇧🇷Pernambuco, Brazil

    12k sq mi30k km² matching 80% or better

    For example Exu (83), Trindade (83)

  3. 3

    🇹🇿Kilimanjaro, Tanzania

    8,700 sq mi22k km² matching 80% or better

    For example Same (98), Hedaru (94)

  4. 4

    🇹🇿Morogoro, Tanzania

    7,700 sq mi20k km² matching 80% or better

    For example Kilosa (90), Msowero (88)

  5. 5

    🇹🇿Arusha, Tanzania

    4,500 sq mi12k km² matching 80% or better

    For example Mto wa Mbu (87), Makuyuni (86)

  6. 6

    🇰🇪Makueni County, Kenya

    4,200 sq mi11k km² matching 80% or better

    For example Emali (88), Wote (84)

  7. 7

    🇰🇪Taita Taveta, Kenya

    3,900 sq mi10k km² matching 80% or better

    For example Taveta (99), Voi (85)

  8. 8

    🇰🇪Kajiado County, Kenya

    3,600 sq mi9,300 km² matching 80% or better

    For example Kitengela (84), Kajiado (77)

  9. 9

    🇧🇷Ceará, Brazil

    1,800 sq mi4,600 km² matching 80% or better

    For example Santana do Cariri (83), Porteiras (80)

  10. 10

    🇩🇴San Juan Province, Dominican Republic

    600 sq mi1,500 km² matching 80% or better

    For example San Juan de la Maguana (80), Las Matas de Farfán (74)

  11. 11

    🇩🇴Baoruco Province, Dominican Republic

    300 sq mi700 km² matching 80% or better

    For example Neiba (54)

  12. 12

    🇩🇴Azua Province, Dominican Republic

    300 sq mi700 km² matching 80% or better

    For example Azua (58)

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

    🇰🇪TavetaTaita Taveta, Kenya

    Zone 12a · No frost · 0 chill hours · 23 in rainZone 12a · No frost · 0 chill hours · 596 mm rain

    Shares 17 of your 17 great-fit crops

    99%match
  2. 2

    🇹🇿SameKilimanjaro, Tanzania

    Zone 12a · No frost · 0 chill hours · 30 in rainZone 12a · No frost · 0 chill hours · 752 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: cassava, sugarcane

    98%match
  3. 3

    🇹🇿HedaruKilimanjaro, Tanzania

    Zone 11b · No frost · 0 chill hours · 24 in rainZone 11b · No frost · 0 chill hours · 613 mm rain

    Shares 17 of your 17 great-fit crops

    94%match
  4. 4

    🇹🇿KilosaMorogoro, Tanzania

    Zone 12a · No frost · 0 chill hours · 34 in rainZone 12a · No frost · 0 chill hours · 870 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: cassava, rice, sugarcane

    90%match
  5. 5

    🇹🇿MaguguManyara, Tanzania

    Zone 12a · No frost · 0 chill hours · 23 in rainZone 12a · No frost · 0 chill hours · 574 mm rain

    Shares 16 of your 17 great-fit crops

    89%match
  6. 6

    🇹🇿MazindeTanga, Tanzania

    Zone 12a · No frost · 0 chill hours · 25 in rainZone 12a · No frost · 0 chill hours · 623 mm rain

    Shares 17 of your 17 great-fit crops

    88%match
  7. 7

    🇧🇷UauáBahia, Brazil

    Zone 12a · No frost · 0 chill hours · 17 in rainZone 12a · No frost · 0 chill hours · 438 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: rice, banana, cassava

    86%match
  8. 8

    🇹🇿MakuyuniArusha, Tanzania

    Zone 11b · No frost · 0 chill hours · 21 in rainZone 11b · No frost · 0 chill hours · 535 mm rain

    Shares 16 of your 17 great-fit crops

    86%match
  9. 9

    🇧🇷UmburanasBahia, Brazil

    Zone 11b · No frost · 0 chill hours · 19 in rainZone 11b · No frost · 0 chill hours · 472 mm rain

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

    86%match
  10. 10

    🇧🇷TanhaçuBahia, Brazil

    Zone 12a · No frost · 0 chill hours · 23 in rainZone 12a · No frost · 0 chill hours · 580 mm rain

    Shares 14 of your 17 great-fit crops

    86%match
  11. 11

    🇹🇿DumilaMorogoro, Tanzania

    Zone 12a · No frost · 0 chill hours · 32 in rainZone 12a · No frost · 0 chill hours · 821 mm rain

    Shares 15 of your 17 great-fit crops · Also great there: cassava, rice, sugarcane

    85%match
  12. 12

    🇰🇪WanguruKirinyaga County, Kenya

    Zone 12a · No frost · 0 chill hours · 35 in rainZone 12a · No frost · 0 chill hours · 892 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: cassava, wine grapes, sugarcane

    85%match
  13. 13

    🇹🇿MorogoroTanzania

    Zone 12a · No frost · 0 chill hours · 34 in rainZone 12a · No frost · 0 chill hours · 863 mm rain

    Shares 15 of your 17 great-fit crops · Also great there: cassava, sugarcane, rice

    85%match
  14. 14

    🇰🇪VoiTaita Taveta, Kenya

    Zone 12a · No frost · 0 chill hours · 30 in rainZone 12a · No frost · 0 chill hours · 756 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: cassava, sugarcane

    85%match
  15. 15

    🇧🇷CafarnaumBahia, Brazil

    Zone 11b · No frost · 0 chill hours · 22 in rainZone 11b · No frost · 0 chill hours · 563 mm rain

    Shares 14 of your 17 great-fit crops

    84%match
  16. 16

    🇹🇿BariadiSimiyu, Tanzania

    Zone 12a · No frost · 0 chill hours · 25 in rainZone 12a · No frost · 0 chill hours · 644 mm rain

    Shares 16 of your 17 great-fit crops

    84%match
  17. 17

    🇧🇷OuricuriPernambuco, Brazil

    Zone 12a · No frost · 0 chill hours · 21 in rainZone 12a · No frost · 0 chill hours · 522 mm rain

    Shares 13 of your 17 great-fit crops

    83%match
  18. 18

    🇧🇷BodocóPernambuco, Brazil

    Zone 12a · No frost · 0 chill hours · 22 in rainZone 12a · No frost · 0 chill hours · 554 mm rain

    Shares 13 of your 17 great-fit crops

    83%match
  19. 19

    🇧🇷SalgueiroPernambuco, Brazil

    Zone 12a · No frost · 0 chill hours · 20 in rainZone 12a · No frost · 0 chill hours · 517 mm rain

    Shares 14 of your 17 great-fit crops

    82%match
  20. 20

    🇧🇷São José do BelmontePernambuco, Brazil

    Zone 12a · No frost · 0 chill hours · 25 in rainZone 12a · No frost · 0 chill hours · 629 mm rain

    Shares 15 of your 17 great-fit crops · Also great there: rice

    82%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 Merelani: 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.