Climatch

Land with a climate like Rangkasbitung

🇮🇩Rangkasbitung, Banten, Indonesia

The towns with the closest growing climate to Rangkasbitung are Cileungsir, Indonesia (99% match), Baturaja and Prabumulih. About 2.7 million sq mi of land in 61 countries matches 80% or better, most of it in Amazonas, Brazil, Pará, Brazil and Sabah, Malaysia.The towns with the closest growing climate to Rangkasbitung are Cileungsir, Indonesia (99% match), Baturaja and Prabumulih. About 6.9 million km² of land in 61 countries matches 80% or better, most of it in Amazonas, Brazil, Pará, Brazil and Sabah, Malaysia.

Your growing climate

Zone 13b · No frost · 0 chill hours · 92 in rainZone 13b · No frost · 0 chill hours · 2,325 mm rain

What grows in Rangkasbitung →

Regions with the most land like yours

  1. 1

    🇧🇷Amazonas, Brazil

    149k sq mi385k km² matching 80% or better

    For example Novo Airão (92), Maués (90)

  2. 2

    🇧🇷Pará, Brazil

    51k sq mi132k km² matching 80% or better

    For example Belém (91), Ananindeua (90)

  3. 3

    🇲🇾Sabah, Malaysia

    28k sq mi72k km² matching 80% or better

    For example Donggongon (96), Kinarut (96)

  4. 4

    🇮🇩Central Kalimantan, Indonesia

    27k sq mi71k km² matching 80% or better

    For example Kualakapuas (99), Palangkaraya (97)

  5. 5

    🇻🇪Bolívar, Venezuela

    23k sq mi59k km² matching 80% or better

    For example El Dorado (90), Tumeremo (88)

  6. 6

    🇮🇩Jambi, Indonesia

    23k sq mi59k km² matching 80% or better

    For example Simpang (96), Jambi City (96)

  7. 7

    🇮🇩Central Sulawesi, Indonesia

    22k sq mi57k km² matching 80% or better

    For example Poso (96), Toli-Toli (92)

  8. 8

    🇨🇴Antioquia, Colombia

    18k sq mi47k km² matching 80% or better

    For example San Pedro de Urabá (95), Carepa (94)

  9. 9

    🇵🇭Mimaropa, Philippines

    18k sq mi46k km² matching 80% or better

    For example Mapun (88), Romblon (87)

  10. 10

    🇵🇪Loreto, Peru

    17k sq mi43k km² matching 80% or better

    For example Yurimaguas (86), Contamana (84)

  11. 11

    🇨🇩Tshopo, Democratic Republic of the Congo

    16k sq mi41k km² matching 80% or better

    For example Basoko (89), Kisangani (84)

  12. 12

    🇧🇷Roraima, Brazil

    16k sq mi40k km² matching 80% or better

    For example Alto Alegre (85), Rorainópolis (80)

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

    🇮🇩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 19 great-fit crops

    99%match
  2. 2

    🇮🇩BaturajaSouth Sumatra, Indonesia

    Zone 13b · No frost · 0 chill hours · 108 in rainZone 13b · No frost · 0 chill hours · 2,735 mm rain

    Shares 17 of your 19 great-fit crops

    99%match
  3. 3

    🇮🇩PrabumulihSouth Sumatra, Indonesia

    Zone 13b · No frost · 0 chill hours · 113 in rainZone 13b · No frost · 0 chill hours · 2,882 mm rain

    Shares 15 of your 19 great-fit crops

    99%match
  4. 4

    🇮🇩Terbanggi BesarLampung, Indonesia

    Zone 13b · No frost · 0 chill hours · 93 in rainZone 13b · No frost · 0 chill hours · 2,372 mm rain

    Shares 18 of your 19 great-fit crops

    99%match
  5. 5

    🇮🇩Bandar LampungLampung, Indonesia

    Zone 13b · No frost · 0 chill hours · 84 in rainZone 13b · No frost · 0 chill hours · 2,134 mm rain

    Shares 18 of your 19 great-fit crops

    99%match
  6. 6

    🇮🇩LahatSouth Sumatra, Indonesia

    Zone 13b · No frost · 0 chill hours · 126 in rainZone 13b · No frost · 0 chill hours · 3,194 mm rain

    Shares 14 of your 19 great-fit crops

    99%match
  7. 7

    🇮🇩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 19 great-fit crops

    99%match
  8. 8

    🇮🇩PolewaliWest Sulawesi, Indonesia

    Zone 13b · No frost · 0 chill hours · 80 in rainZone 13b · No frost · 0 chill hours · 2,041 mm rain

    Shares 18 of your 19 great-fit crops

    99%match
  9. 9

    🇮🇩PalembangSouth Sumatra, Indonesia

    Zone 13b · No frost · 0 chill hours · 104 in rainZone 13b · No frost · 0 chill hours · 2,651 mm rain

    Shares 16 of your 19 great-fit crops

    98%match
  10. 10

    🇮🇩LubuklinggauSouth Sumatra, Indonesia

    Zone 13a · No frost · 0 chill hours · 116 in rainZone 13a · No frost · 0 chill hours · 2,957 mm rain

    Shares 17 of your 19 great-fit crops

    98%match
  11. 11

    🇮🇩LebaksiuCentral Java, Indonesia

    Zone 13a · No frost · 0 chill hours · 120 in rainZone 13a · No frost · 0 chill hours · 3,046 mm rain

    Shares 17 of your 19 great-fit crops

    98%match
  12. 12

    🇮🇩ManggarBangka–Belitung Islands, Indonesia

    Zone 13b · No frost · 0 chill hours · 99 in rainZone 13b · No frost · 0 chill hours · 2,516 mm rain

    Shares 18 of your 19 great-fit crops

    98%match
  13. 13

    🇮🇩ManismataWest Kalimantan, Indonesia

    Zone 13b · No frost · 0 chill hours · 113 in rainZone 13b · No frost · 0 chill hours · 2,874 mm rain

    Shares 15 of your 19 great-fit crops

    98%match
  14. 14

    🇮🇩PalangkarayaCentral Kalimantan, Indonesia

    Zone 13b · No frost · 0 chill hours · 99 in rainZone 13b · No frost · 0 chill hours · 2,527 mm rain

    Shares 17 of your 19 great-fit crops

    97%match
  15. 15

    🇮🇩SampitCentral Kalimantan, Indonesia

    Zone 13b · No frost · 0 chill hours · 107 in rainZone 13b · No frost · 0 chill hours · 2,727 mm rain

    Shares 16 of your 19 great-fit crops

    97%match
  16. 16

    🇮🇩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 19 great-fit crops

    97%match
  17. 17

    🇮🇩ParepareSouth Sulawesi, Indonesia

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

    Shares 18 of your 19 great-fit crops

    97%match
  18. 18

    🇮🇩PangkalpinangBangka–Belitung Islands, Indonesia

    Zone 13b · No frost · 0 chill hours · 114 in rainZone 13b · No frost · 0 chill hours · 2,894 mm rain

    Shares 15 of your 19 great-fit crops

    97%match
  19. 19

    🇮🇩BanjarmasinSouth Kalimantan, Indonesia

    Zone 13b · No frost · 0 chill hours · 104 in rainZone 13b · No frost · 0 chill hours · 2,646 mm rain

    Shares 16 of your 19 great-fit crops

    97%match
  20. 20

    🇮🇩MuntokBangka–Belitung Islands, Indonesia

    Zone 13b · No frost · 0 chill hours · 109 in rainZone 13b · No frost · 0 chill hours · 2,767 mm rain

    Shares 16 of your 19 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 Rangkasbitung: 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.