Climatch

Land with a climate like Kyaukpyu

🇲🇲Kyaukpyu, Rakhine, Myanmar

The towns with the closest growing climate to Kyaukpyu are Gwa, Myanmar (97% match), Pathein and Taungup. About 95,000 sq mi of land in 10 countries matches 80% or better, most of it in Rakhine, Myanmar, Ayeyarwady, Myanmar and Bago Region, Myanmar.The towns with the closest growing climate to Kyaukpyu are Gwa, Myanmar (97% match), Pathein and Taungup. About 247,000 km² of land in 10 countries matches 80% or better, most of it in Rakhine, Myanmar, Ayeyarwady, Myanmar and Bago Region, Myanmar.

Your growing climate

Zone 12a · No frost · 0 chill hours · 120 in rainZone 12a · No frost · 0 chill hours · 3,057 mm rain

What grows in Kyaukpyu →

Regions with the most land like yours

  1. 1

    🇲🇲Rakhine, Myanmar

    19k sq mi50k km² matching 80% or better

    For example Gwa (97), Taungup (96)

  2. 2

    🇲🇲Ayeyarwady, Myanmar

    16k sq mi42k km² matching 80% or better

    For example Pathein (96), Myaungmya (95)

  3. 3

    🇲🇲Bago Region, Myanmar

    9,400 sq mi24k km² matching 80% or better

    For example Thanatpin (90), Letpandan (90)

  4. 4

    🇮🇳Karnataka, India

    6,700 sq mi17k km² matching 80% or better

    For example Karwar (91), Gokarna (91)

  5. 5

    🇧🇩Chittagong, Bangladesh

    5,600 sq mi14k km² matching 80% or better

    For example Teknāf (95), Cox’s Bāzār (88)

  6. 6

    🇰🇭Ratanakiri, Cambodia

    3,200 sq mi8,300 km² matching 80% or better

    For example Banlung (81), Lumphat (79)

  7. 7

    🇵🇭Ilocos, Philippines

    2,000 sq mi5,200 km² matching 80% or better

    For example Bantay (89), Vigan (88)

  8. 8

    🇮🇳Maharashtra, India

    1,700 sq mi4,500 km² matching 80% or better

    For example Sāvantvādi (81), Ratnagiri (80)

  9. 9

    🇮🇳Goa, India

    1,400 sq mi3,700 km² matching 80% or better

    For example Madgaon (87), Cuncolim (83)

  10. 10

    🇸🇱Western Area, Sierra Leone

    1,200 sq mi3,100 km² matching 80% or better

    For example Freetown (84), Waterloo (79)

  11. 11

    🇮🇩East Nusa Tenggara, Indonesia

    900 sq mi2,300 km² matching 80% or better

    For example Kupang (84), Waingapu (72)

  12. 12

    🇮🇩West Nusa Tenggara, Indonesia

    600 sq mi1,500 km² matching 80% or better

    For example Sumbawa Besar (75), Bima (70)

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

    🇲🇲GwaRakhine, Myanmar

    Zone 12a · No frost · 0 chill hours · 150 in rainZone 12a · No frost · 0 chill hours · 3,802 mm rain

    Shares 10 of your 14 great-fit crops

    97%match
  2. 2

    🇲🇲PatheinAyeyarwady, Myanmar

    Zone 12b · No frost · 0 chill hours · 121 in rainZone 12b · No frost · 0 chill hours · 3,067 mm rain

    Shares 13 of your 14 great-fit crops

    96%match
  3. 3

    🇲🇲TaungupRakhine, Myanmar

    Zone 11b · No frost · 0 chill hours · 192 in rainZone 11b · No frost · 0 chill hours · 4,869 mm rain

    Shares 11 of your 14 great-fit crops

    96%match
  4. 4

    🇲🇲KyeintaliRakhine, Myanmar

    Zone 12a · No frost · 0 chill hours · 171 in rainZone 12a · No frost · 0 chill hours · 4,341 mm rain

    Shares 10 of your 14 great-fit crops

    96%match
  5. 5

    🇲🇲ThandweRakhine, Myanmar

    Zone 11b · No frost · 0 chill hours · 205 in rainZone 11b · No frost · 0 chill hours · 5,213 mm rain

    Shares 11 of your 14 great-fit crops

    95%match
  6. 6

    🇲🇲Mrauk URakhine, Myanmar

    Zone 11b · No frost · 0 chill hours · 164 in rainZone 11b · No frost · 0 chill hours · 4,171 mm rain

    Shares 11 of your 14 great-fit crops · Also great there: wheat

    94%match
  7. 7

    🇲🇲SittweRakhine, Myanmar

    Zone 11b · No frost · 0 chill hours · 155 in rainZone 11b · No frost · 0 chill hours · 3,930 mm rain

    Shares 10 of your 14 great-fit crops · Also great there: wheat

    93%match
  8. 8

    🇲🇲WakemaAyeyarwady, Myanmar

    Zone 12b · No frost · 0 chill hours · 99 in rainZone 12b · No frost · 0 chill hours · 2,509 mm rain

    Shares 13 of your 14 great-fit crops · Also great there: citrus

    93%match
  9. 9

    🇲🇲Buthidaung TownRakhine, Myanmar

    Zone 11b · No frost · 0 chill hours · 186 in rainZone 11b · No frost · 0 chill hours · 4,733 mm rain

    Shares 10 of your 14 great-fit crops · Also great there: wheat

    92%match
  10. 10

    🇲🇲LabuttaAyeyarwady, Myanmar

    Zone 12b · No frost · 0 chill hours · 122 in rainZone 12b · No frost · 0 chill hours · 3,099 mm rain

    Shares 13 of your 14 great-fit crops

    92%match
  11. 11

    🇲🇲DawbonAyeyarwady, Myanmar

    Zone 12b · No frost · 0 chill hours · 92 in rainZone 12b · No frost · 0 chill hours · 2,349 mm rain

    Shares 13 of your 14 great-fit crops · Also great there: citrus

    92%match
  12. 12

    🇮🇳KarwarKarnataka, India

    Zone 13a · No frost · 0 chill hours · 133 in rainZone 13a · No frost · 0 chill hours · 3,377 mm rain

    Shares 12 of your 14 great-fit crops

    91%match
  13. 13

    🇲🇲HinthadaAyeyarwady, Myanmar

    Zone 12a · No frost · 0 chill hours · 89 in rainZone 12a · No frost · 0 chill hours · 2,250 mm rain

    Shares 13 of your 14 great-fit crops · Also great there: citrus

    91%match
  14. 14

    🇮🇳KumtaKarnataka, India

    Zone 13a · No frost · 0 chill hours · 149 in rainZone 13a · No frost · 0 chill hours · 3,774 mm rain

    Shares 10 of your 14 great-fit crops

    90%match
  15. 15

    🇲🇲BagoBago Region, Myanmar

    Zone 12a · No frost · 0 chill hours · 136 in rainZone 12a · No frost · 0 chill hours · 3,447 mm rain

    Shares 12 of your 14 great-fit crops

    90%match
  16. 16

    🇲🇲KyonpyawAyeyarwady, Myanmar

    Zone 12a · No frost · 0 chill hours · 99 in rainZone 12a · No frost · 0 chill hours · 2,524 mm rain

    Shares 13 of your 14 great-fit crops · Also great there: citrus

    90%match
  17. 17

    🇧🇩Cox’s BāzārChittagong, Bangladesh

    Zone 11b · No frost · 0 chill hours · 141 in rainZone 11b · No frost · 0 chill hours · 3,590 mm rain

    Shares 12 of your 14 great-fit crops · Also great there: wheat

    88%match
  18. 18

    🇮🇳BhatkalKarnataka, India

    Zone 13a · No frost · 0 chill hours · 172 in rainZone 13a · No frost · 0 chill hours · 4,366 mm rain

    Shares 9 of your 14 great-fit crops

    88%match
  19. 19

    🇵🇭ViganIlocos, Philippines

    Zone 13a · No frost · 0 chill hours · 97 in rainZone 13a · No frost · 0 chill hours · 2,472 mm rain

    Shares 13 of your 14 great-fit crops · Also great there: citrus, avocado

    88%match
  20. 20

    🇲🇲San ChaungYangon, Myanmar

    Zone 12a · No frost · 0 chill hours · 105 in rainZone 12a · No frost · 0 chill hours · 2,671 mm rain

    Shares 13 of your 14 great-fit crops · Also great there: citrus

    88%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 Kyaukpyu: 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.