Climatch

Land with a climate like Pālang

🇧🇩Pālang, Dhaka Division, Bangladesh

The towns with the closest growing climate to Pālang are Gazipur, Bangladesh (99% match), Mānikganj and Khulna. About 219,000 sq mi of land in 8 countries matches 80% or better, most of it in Assam, India, West Bengal, India and Chittagong, Bangladesh.The towns with the closest growing climate to Pālang are Gazipur, Bangladesh (99% match), Mānikganj and Khulna. About 567,000 km² of land in 8 countries matches 80% or better, most of it in Assam, India, West Bengal, India and Chittagong, Bangladesh.

Your growing climate

Zone 11a · No frost · 0 chill hours · 84 in rainZone 11a · No frost · 0 chill hours · 2,142 mm rain

What grows in Pālang →

Regions with the most land like yours

  1. 1

    🇮🇳Assam, India

    21k sq mi54k km² matching 80% or better

    For example Silchar (96), Hailākāndi (94)

  2. 2

    🇮🇳West Bengal, India

    19k sq mi49k km² matching 80% or better

    For example Tāki (97), Basirhat City (97)

  3. 3

    🇧🇩Chittagong, Bangladesh

    15k sq mi39k km² matching 80% or better

    For example Lākshām (99), Comilla (99)

  4. 4

    🇮🇳Odisha, India

    14k sq mi37k km² matching 80% or better

    For example Balasore (88), Nilagiri (88)

  5. 5

    🇲🇲Sagaing Region, Myanmar

    14k sq mi35k km² matching 80% or better

    For example Tamu (91), Tatkon (91)

  6. 6

    🇲🇲Kachin State, Myanmar

    11k sq mi30k km² matching 80% or better

    For example Myitkyina (89), Mogaung (89)

  7. 7

    🇧🇩Khulna Division, Bangladesh

    9,100 sq mi24k km² matching 80% or better

    For example Kālia (99), Khulna (99)

  8. 8

    🇧🇩Dhaka Division, Bangladesh

    7,400 sq mi19k km² matching 80% or better

    For example Tungi (99), Gazipur (99)

  9. 9

    🇹🇭Udon Thani, Thailand

    4,300 sq mi11k km² matching 80% or better

    For example Ban Dung (90), Nam Som (84)

  10. 10

    🇱🇦Savannakhet Province, Laos

    2,900 sq mi7,400 km² matching 80% or better

    For example Ban Xénô (80), Savannakhet (76)

  11. 11

    🇹🇭Sakon Nakhon, Thailand

    2,900 sq mi7,400 km² matching 80% or better

    For example Sawang Daen Din (86), Sakon Nakhon (84)

  12. 12

    🇹🇭Bueng Kan, Thailand

    2,800 sq mi7,400 km² matching 80% or better

    For example Seka (93)

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

    🇧🇩GazipurDhaka Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 84 in rainZone 11a · No frost · 0 chill hours · 2,145 mm rain

    Shares 19 of your 19 great-fit crops · Also great there: tea

    99%match
  2. 2

    🇧🇩MānikganjDhaka Division, Bangladesh

    Zone 11a · No frost · 1 chill hours · 78 in rainZone 11a · No frost · 1 chill hours · 1,982 mm rain

    Shares 18 of your 19 great-fit crops

    99%match
  3. 3

    🇧🇩KhulnaKhulna Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 74 in rainZone 11a · No frost · 0 chill hours · 1,887 mm rain

    Shares 16 of your 19 great-fit crops

    99%match
  4. 4

    🇧🇩ComillaChittagong, Bangladesh

    Zone 11a · No frost · 0 chill hours · 86 in rainZone 11a · No frost · 0 chill hours · 2,186 mm rain

    Shares 19 of your 19 great-fit crops · Also great there: macadamia, tea

    99%match
  5. 5

    🇧🇩PirojpurBarisal Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 87 in rainZone 11a · No frost · 0 chill hours · 2,221 mm rain

    Shares 18 of your 19 great-fit crops

    99%match
  6. 6

    🇧🇩PatuakhaliBarisal Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 104 in rainZone 11a · No frost · 0 chill hours · 2,641 mm rain

    Shares 17 of your 19 great-fit crops

    99%match
  7. 7

    🇧🇩JessoreKhulna Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 70 in rainZone 11a · No frost · 0 chill hours · 1,771 mm rain

    Shares 17 of your 19 great-fit crops

    99%match
  8. 8

    🇧🇩MaijdiChittagong, Bangladesh

    Zone 11b · No frost · 0 chill hours · 114 in rainZone 11b · No frost · 0 chill hours · 2,884 mm rain

    Shares 15 of your 19 great-fit crops

    99%match
  9. 9

    🇧🇩Uttar Char FassonKhulna Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 113 in rainZone 11a · No frost · 0 chill hours · 2,858 mm rain

    Shares 16 of your 19 great-fit crops

    99%match
  10. 10

    🇮🇳AgartalaTripura, India

    Zone 11a · No frost · 1 chill hours · 82 in rainZone 11a · No frost · 1 chill hours · 2,071 mm rain

    Shares 19 of your 19 great-fit crops

    99%match
  11. 11

    🇧🇩Taluker Char DoaniKhulna Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 95 in rainZone 11a · No frost · 0 chill hours · 2,424 mm rain

    Shares 18 of your 19 great-fit crops

    99%match
  12. 12

    🇧🇩KishorganjDhaka Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 92 in rainZone 11a · No frost · 0 chill hours · 2,331 mm rain

    Shares 19 of your 19 great-fit crops · Also great there: macadamia, tea

    98%match
  13. 13

    🇧🇩HabiganjSylhet Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 95 in rainZone 11a · No frost · 0 chill hours · 2,402 mm rain

    Shares 19 of your 19 great-fit crops · Also great there: macadamia, tea

    98%match
  14. 14

    🇧🇩ChattogramChittagong, Bangladesh

    Zone 11b · No frost · 0 chill hours · 110 in rainZone 11b · No frost · 0 chill hours · 2,785 mm rain

    Shares 14 of your 19 great-fit crops

    98%match
  15. 15

    🇧🇩BeraRajshahi Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 68 in rainZone 11a · No frost · 0 chill hours · 1,732 mm rain

    Shares 18 of your 19 great-fit crops

    97%match
  16. 16

    🇧🇩TangailDhaka Division, Bangladesh

    Zone 11a · No frost · 2 chill hours · 73 in rainZone 11a · No frost · 2 chill hours · 1,847 mm rain

    Shares 18 of your 19 great-fit crops

    97%match
  17. 17

    🇮🇳Basirhat CityWest Bengal, India

    Zone 11a · No frost · 0 chill hours · 67 in rainZone 11a · No frost · 0 chill hours · 1,713 mm rain

    Shares 16 of your 19 great-fit crops

    97%match
  18. 18

    🇧🇩ChhāgalnāiyaChittagong, Bangladesh

    Zone 11a · No frost · 0 chill hours · 97 in rainZone 11a · No frost · 0 chill hours · 2,458 mm rain

    Shares 19 of your 19 great-fit crops · Also great there: tea

    97%match
  19. 19

    🇧🇩KhagrachhariChittagong, Bangladesh

    Zone 11a · No frost · 0 chill hours · 89 in rainZone 11a · No frost · 0 chill hours · 2,250 mm rain

    Shares 18 of your 19 great-fit crops

    96%match
  20. 20

    🇮🇳ĀmbāsaTripura, India

    Zone 11a · No frost · 2 chill hours · 79 in rainZone 11a · No frost · 2 chill hours · 2,017 mm rain

    Shares 19 of your 19 great-fit crops · Also great there: macadamia, tea

    96%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 Pālang: 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.