Climatch

Land with a climate like Tamu

🇲🇲Tamu, Sagaing Region, Myanmar

The towns with the closest growing climate to Tamu are Tatkon, Myanmar (99% match), Mogaung and Mohnyin. About 281,000 sq mi of land in 8 countries matches 80% or better, most of it in West Bengal, India, Assam, India and Sagaing Region, Myanmar.The towns with the closest growing climate to Tamu are Tatkon, Myanmar (99% match), Mogaung and Mohnyin. About 728,000 km² of land in 8 countries matches 80% or better, most of it in West Bengal, India, Assam, India and Sagaing Region, Myanmar.

Your growing climate

Zone 11a · No frost · 1 chill hours · 91 in rainZone 11a · No frost · 1 chill hours · 2,322 mm rain

What grows in Tamu →

Regions with the most land like yours

  1. 1

    🇮🇳West Bengal, India

    25k sq mi64k km² matching 80% or better

    For example Bangaon (94), Gobārdānga (93)

  2. 2

    🇮🇳Assam, India

    24k sq mi61k km² matching 80% or better

    For example Lanka (96), Hojāi (96)

  3. 3

    🇲🇲Sagaing Region, Myanmar

    18k sq mi47k km² matching 80% or better

    For example Tatkon (99), Kyauktan (97)

  4. 4

    🇲🇲Kachin State, Myanmar

    18k sq mi46k km² matching 80% or better

    For example Hopin (99), Mogaung (99)

  5. 5

    🇮🇳Odisha, India

    14k sq mi37k km² matching 80% or better

    For example Nilagiri (86), Balasore (85)

  6. 6

    🇧🇩Chittagong, Bangladesh

    14k sq mi36k km² matching 80% or better

    For example Khagrachhari (96), Brāhmanbāria (95)

  7. 7

    🇧🇩Khulna Division, Bangladesh

    8,800 sq mi23k km² matching 80% or better

    For example Kushtia (96), Kālīganj (96)

  8. 8

    🇧🇩Dhaka Division, Bangladesh

    7,400 sq mi19k km² matching 80% or better

    For example Nāgarpur (97), Sakhipur (97)

  9. 9

    🇹🇭Nan, Thailand

    5,400 sq mi14k km² matching 80% or better

    For example Nan (78)

  10. 10

    🇱🇦Bokeo, Laos

    5,100 sq mi13k km² matching 80% or better

    For example Ban Khoan (89), Ban Houakhoua (86)

  11. 11

    🇹🇭Chiang Rai, Thailand

    4,500 sq mi12k km² matching 80% or better

    For example Mae Sai (89), Mae Chan (87)

  12. 12

    🇲🇲Rakhine, Myanmar

    4,200 sq mi11k km² matching 80% or better

    For example Sittwe (81), Buthidaung Town (75)

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

    🇲🇲TatkonSagaing Region, Myanmar

    Zone 11a · No frost · 1 chill hours · 80 in rainZone 11a · No frost · 1 chill hours · 2,028 mm rain

    Shares 18 of your 18 great-fit crops

    99%match
  2. 2

    🇲🇲MogaungKachin State, Myanmar

    Zone 10b · No frost · 6 chill hours · 78 in rainZone 10b · No frost · 6 chill hours · 1,992 mm rain

    Shares 17 of your 18 great-fit crops · Also great there: macadamia

    99%match
  3. 3

    🇲🇲MohnyinKachin State, Myanmar

    Zone 10b · No frost · 11 chill hours · 65 in rainZone 10b · No frost · 11 chill hours · 1,644 mm rain

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

    99%match
  4. 4

    🇲🇲HpākānKachin State, Myanmar

    Zone 10b · No frost · 12 chill hours · 98 in rainZone 10b · No frost · 12 chill hours · 2,500 mm rain

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

    98%match
  5. 5

    🇲🇲MyitkyinaKachin State, Myanmar

    Zone 11a · No frost · 2 chill hours · 72 in rainZone 11a · No frost · 2 chill hours · 1,819 mm rain

    Shares 16 of your 18 great-fit crops · Also great there: macadamia, banana, tea

    98%match
  6. 6

    🇲🇲KyauktanSagaing Region, Myanmar

    Zone 11a · No frost · 1 chill hours · 59 in rainZone 11a · No frost · 1 chill hours · 1,501 mm rain

    Shares 18 of your 18 great-fit crops

    97%match
  7. 7

    🇧🇩NāgarpurDhaka Division, Bangladesh

    Zone 11a · No frost · 2 chill hours · 73 in rainZone 11a · No frost · 2 chill hours · 1,855 mm rain

    Shares 18 of your 18 great-fit crops

    97%match
  8. 8

    🇧🇩SakhipurDhaka Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 80 in rainZone 11a · No frost · 0 chill hours · 2,034 mm rain

    Shares 18 of your 18 great-fit crops

    97%match
  9. 9

    🇧🇩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 18 great-fit crops

    96%match
  10. 10

    🇲🇲LakangKachin State, Myanmar

    Zone 10b · No frost · 12 chill hours · 62 in rainZone 10b · No frost · 12 chill hours · 1,571 mm rain

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

    96%match
  11. 11

    🇲🇲BhamoKachin State, Myanmar

    Zone 11a · No frost · 4 chill hours · 61 in rainZone 11a · No frost · 4 chill hours · 1,546 mm rain

    Shares 17 of your 18 great-fit crops

    96%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 18 great-fit crops

    96%match
  13. 13

    🇲🇲ShweguKachin State, Myanmar

    Zone 11a · No frost · 2 chill hours · 57 in rainZone 11a · No frost · 2 chill hours · 1,457 mm rain

    Shares 17 of your 18 great-fit crops · Also great there: fig

    96%match
  14. 14

    🇧🇩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 18 great-fit crops

    96%match
  15. 15

    🇮🇳AgartalaTripura, India

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

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

    96%match
  16. 16

    🇧🇩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 18 great-fit crops

    96%match
  17. 17

    🇮🇳DharmanagarTripura, India

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

    Shares 18 of your 18 great-fit crops · Also great there: banana, macadamia, tea

    96%match
  18. 18

    🇮🇳HojāiAssam, India

    Zone 10b · No frost · 5 chill hours · 58 in rainZone 10b · No frost · 5 chill hours · 1,466 mm rain

    Shares 17 of your 18 great-fit crops · Also great there: banana, fig

    96%match
  19. 19

    🇧🇩FarīdpurDhaka Division, Bangladesh

    Zone 11a · No frost · 0 chill hours · 78 in rainZone 11a · No frost · 0 chill hours · 1,988 mm rain

    Shares 18 of your 18 great-fit crops

    95%match
  20. 20

    🇧🇩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 18 great-fit crops

    95%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 Tamu: 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.