Climatch

Land with a climate like Parepare

🇮🇩Parepare, South Sulawesi, Indonesia

The towns with the closest growing climate to Parepare are Majene, Indonesia (99% match), Weleri and Semarang. About 1.7 million sq mi of land in 51 countries matches 80% or better, most of it in Amazonas, Brazil, Pará, Brazil and Bolívar, Venezuela.The towns with the closest growing climate to Parepare are Majene, Indonesia (99% match), Weleri and Semarang. About 4.3 million km² of land in 51 countries matches 80% or better, most of it in Amazonas, Brazil, Pará, Brazil and Bolívar, Venezuela.

Your growing climate

Zone 13b · No frost · 0 chill hours · 80 in rainZone 13b · No frost · 0 chill hours · 2,023 mm rain

What grows in Parepare →

Regions with the most land like yours

  1. 1

    🇧🇷Amazonas, Brazil

    73k sq mi188k km² matching 80% or better

    For example Novo Airão (87), Careiro da Várzea (87)

  2. 2

    🇧🇷Pará, Brazil

    65k sq mi168k km² matching 80% or better

    For example Itaituba (88), Acará (87)

  3. 3

    🇻🇪Bolívar, Venezuela

    28k sq mi72k km² matching 80% or better

    For example La Paragua (92), El Dorado (91)

  4. 4

    🇵🇭Mimaropa, Philippines

    28k sq mi71k km² matching 80% or better

    For example Narra (92), Puerto Princesa (91)

  5. 5

    🇮🇩Central Kalimantan, Indonesia

    27k sq mi70k km² matching 80% or better

    For example Kualakapuas (97), Palangkaraya (94)

  6. 6

    🇮🇩South Sumatra, Indonesia

    20k sq mi51k km² matching 80% or better

    For example Baturaja (94), Indralaya (94)

  7. 7

    🇮🇩Jambi, Indonesia

    19k sq mi50k km² matching 80% or better

    For example Simpang (87), Jambi City (87)

  8. 8

    🇨🇴Antioquia, Colombia

    17k sq mi45k km² matching 80% or better

    For example San Pedro de Urabá (98), Turbo (97)

  9. 9

    🇵🇭Autonomous Region in Muslim Mindanao, Philippines

    15k sq mi39k km² matching 80% or better

    For example Al-Barka (91), City of Isabela (90)

  10. 10

    🇨🇩Mongala, Democratic Republic of the Congo

    13k sq mi34k km² matching 80% or better

    For example Bumba (84), Lisala (81)

  11. 11

    🇵🇭Zamboanga Peninsula, Philippines

    12k sq mi30k km² matching 80% or better

    For example Siocon (92), Ipil (92)

  12. 12

    🇨🇮Bas-Sassandra District, Ivory Coast

    11k sq mi29k km² matching 80% or better

    For example Watté (92), Gagny (91)

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

    🇮🇩MajeneWest Sulawesi, Indonesia

    Zone 13b · No frost · 0 chill hours · 72 in rainZone 13b · No frost · 0 chill hours · 1,819 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  2. 2

    🇮🇩WeleriCentral Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 88 in rainZone 13a · No frost · 0 chill hours · 2,241 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  3. 3

    🇮🇩SemarangCentral Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 86 in rainZone 13b · No frost · 0 chill hours · 2,188 mm rain

    Shares 17 of your 18 great-fit crops

    99%match
  4. 4

    🇮🇩PurwodadiCentral Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 82 in rainZone 13a · No frost · 0 chill hours · 2,071 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  5. 5

    🇮🇩JuwanaCentral Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 74 in rainZone 13b · No frost · 0 chill hours · 1,871 mm rain

    Shares 17 of your 18 great-fit crops

    99%match
  6. 6

    🇮🇩SubangWest Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 97 in rainZone 13a · No frost · 0 chill hours · 2,460 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  7. 7

    🇮🇩SerangBanten, Indonesia

    Zone 13b · No frost · 0 chill hours · 71 in rainZone 13b · No frost · 0 chill hours · 1,812 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  8. 8

    🇮🇩MetroLampung, Indonesia

    Zone 13b · No frost · 0 chill hours · 87 in rainZone 13b · No frost · 0 chill hours · 2,219 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  9. 9

    🇮🇩PekalonganCentral Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 97 in rainZone 13a · No frost · 0 chill hours · 2,454 mm rain

    Shares 18 of your 18 great-fit crops

    98%match
  10. 10

    🇮🇩BangkalanEast Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 69 in rainZone 13a · No frost · 0 chill hours · 1,740 mm rain

    Shares 18 of your 18 great-fit crops

    98%match
  11. 11

    🇮🇩CileungsirWest Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 97 in rainZone 13b · No frost · 0 chill hours · 2,458 mm rain

    Shares 18 of your 18 great-fit crops

    98%match
  12. 12

    🇮🇩TegalCentral Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 76 in rainZone 13a · No frost · 0 chill hours · 1,943 mm rain

    Shares 18 of your 18 great-fit crops

    98%match
  13. 13

    🇮🇩BekasiWest Java, Indonesia

    Zone 13b · No frost · 0 chill hours · 79 in rainZone 13b · No frost · 0 chill hours · 2,015 mm rain

    Shares 17 of your 18 great-fit crops

    98%match
  14. 14

    🇨🇴San Pedro de Urabá↻Seasons flipped. Antioquia, Colombia

    Zone 13b · No frost · 0 chill hours · 74 in rainZone 13b · No frost · 0 chill hours · 1,876 mm rain

    Shares 18 of your 18 great-fit crops

    98%match
  15. 15

    🇹🇭Krabi↻Seasons flipped. Thailand

    Zone 13b · No frost · 0 chill hours · 83 in rainZone 13b · No frost · 0 chill hours · 2,120 mm rain

    Shares 17 of your 18 great-fit crops

    97%match
  16. 16

    🇮🇩KualakapuasCentral Kalimantan, Indonesia

    Zone 13b · No frost · 0 chill hours · 96 in rainZone 13b · No frost · 0 chill hours · 2,435 mm rain

    Shares 17 of your 18 great-fit crops

    97%match
  17. 17

    🇮🇩KutoarjoCentral Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 91 in rainZone 13a · No frost · 0 chill hours · 2,304 mm rain

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

    97%match
  18. 18

    🇮🇩KotabumiLampung, Indonesia

    Zone 13b · No frost · 0 chill hours · 93 in rainZone 13b · No frost · 0 chill hours · 2,361 mm rain

    Shares 18 of your 18 great-fit crops

    97%match
  19. 19

    🇮🇩JakartaIndonesia

    Zone 13b · No frost · 0 chill hours · 81 in rainZone 13b · No frost · 0 chill hours · 2,049 mm rain

    Shares 17 of your 18 great-fit crops

    97%match
  20. 20

    🇹🇭Lang Suan↻Seasons flipped. Chumphon, Thailand

    Zone 13a · No frost · 0 chill hours · 76 in rainZone 13a · No frost · 0 chill hours · 1,923 mm rain

    Shares 17 of your 18 great-fit crops

    97%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 Parepare: 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.