Climatch

Land with a climate like Savar

🇧🇩Savar, Dhaka Division, Bangladesh

The towns with the closest growing climate to Savar are Madaripur, Bangladesh (99% match), Comilla and Agartala. About 243,000 sq mi of land in 7 countries matches 80% or better, most of it in Assam, India, West Bengal, India and Sagaing Region, Myanmar.The towns with the closest growing climate to Savar are Madaripur, Bangladesh (99% match), Comilla and Agartala. About 628,000 km² of land in 7 countries matches 80% or better, most of it in Assam, India, West Bengal, India and Sagaing Region, Myanmar.

Your growing climate

Zone 11a · No frost · 0 chill hours · 83 in rainZone 11a · No frost · 0 chill hours · 2,112 mm rain

What grows in Savar →

Regions with the most land like yours

  1. 1

    🇮🇳Assam, India

    23k sq mi59k km² matching 80% or better

    For example Silchar (98), Hailākāndi (97)

  2. 2

    🇮🇳West Bengal, India

    23k sq mi59k km² matching 80% or better

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

  3. 3

    🇲🇲Sagaing Region, Myanmar

    17k sq mi44k km² matching 80% or better

    For example Tamu (95), Tatkon (94)

  4. 4

    🇧🇩Chittagong, Bangladesh

    15k sq mi38k km² matching 80% or better

    For example Brāhmanbāria (99), Ashuganj City (99)

  5. 5

    🇮🇳Odisha, India

    13k sq mi35k km² matching 80% or better

    For example Nilagiri (88), Balasore (88)

  6. 6

    🇲🇲Kachin State, Myanmar

    13k sq mi34k km² matching 80% or better

    For example Mogaung (93), Mohnyin (93)

  7. 7

    🇧🇩Khulna Division, Bangladesh

    9,100 sq mi24k km² matching 80% or better

    For example Kālia (99), Narail (99)

  8. 8

    🇧🇩Dhaka Division, Bangladesh

    7,400 sq mi19k km² matching 80% or better

    For example Madaripur (99), Bājitpur (99)

  9. 9

    🇹🇭Udon Thani, Thailand

    4,300 sq mi11k km² matching 80% or better

    For example Ban Dung (89), Nam Som (84)

  10. 10

    🇱🇦Bokeo, Laos

    3,600 sq mi9,500 km² matching 80% or better

    For example Ban Khoan (87), Ban Houakhoua (85)

  11. 11

    🇹🇭Loei, Thailand

    3,400 sq mi8,900 km² matching 80% or better

    For example Loei (85), Wang Saphung (84)

  12. 12

    🇹🇭Phrae, Thailand

    3,400 sq mi8,800 km² matching 80% or better

    For example Den Chai (84), Phrae (82)

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

    🇧🇩MadaripurDhaka Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 83 in rainZone 11a · No frost · 0 chill hours · 2,120 mm rain

    Shares 19 of your 19 great-fit crops

    99%match
  2. 2

    🇧🇩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
  3. 3

    🇮🇳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
  4. 4

    🇧🇩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

    99%match
  5. 5

    🇧🇩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

    99%match
  6. 6

    🇧🇩ChāndpurChittagong, Bangladesh

    Zone 11b · No frost · 0 chill hours · 84 in rainZone 11b · No frost · 0 chill hours · 2,135 mm rain

    Shares 17 of your 19 great-fit crops · Also great there: macadamia, tea

    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

    🇧🇩BarishalBarisal Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 89 in rainZone 11a · No frost · 0 chill hours · 2,269 mm rain

    Shares 18 of your 19 great-fit crops

    99%match
  9. 9

    🇧🇩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
  10. 10

    🇧🇩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
  11. 11

    🇮🇳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

    99%match
  12. 12

    🇧🇩PābnaRajshahi Division, Bangladesh

    Zone 10b · No frost · 2 chill hours · 67 in rainZone 10b · No frost · 2 chill hours · 1,700 mm rain

    Shares 18 of your 19 great-fit crops

    99%match
  13. 13

    🇮🇳DharmanagarTripura, India

    Zone 11a · No frost · 0 chill hours · 91 in rainZone 11a · No frost · 0 chill hours · 2,318 mm rain

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

    98%match
  14. 14

    🇧🇩SirajganjRajshahi Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 70 in rainZone 11a · No frost · 0 chill hours · 1,784 mm rain

    Shares 18 of your 19 great-fit crops

    98%match
  15. 15

    🇧🇩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

    98%match
  16. 16

    🇧🇩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

    98%match
  17. 17

    🇧🇩MymensinghMymensingh Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 89 in rainZone 11a · No frost · 0 chill hours · 2,252 mm rain

    Shares 18 of your 19 great-fit crops · Also great there: macadamia

    98%match
  18. 18

    🇮🇳SilcharAssam, India

    Zone 11a · No frost · 0 chill hours · 92 in rainZone 11a · No frost · 0 chill hours · 2,336 mm rain

    Shares 19 of your 19 great-fit crops

    98%match
  19. 19

    🇧🇩ShibganjRajshahi Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 77 in rainZone 11a · No frost · 0 chill hours · 1,966 mm rain

    Shares 18 of your 19 great-fit crops

    98%match
  20. 20

    🇧🇩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

    98%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 Savar: 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.