Climatch

Land with a climate like Rāmachandrapuram

🇮🇳Rāmachandrapuram, Andhra Pradesh, India

The towns with the closest growing climate to Rāmachandrapuram are Tuni, India (99% match), Machilīpatnam and Eluru. About 123,000 sq mi of land in 7 countries matches 80% or better, most of it in Andhra Pradesh, India, Telangana, India and Odisha, India.The towns with the closest growing climate to Rāmachandrapuram are Tuni, India (99% match), Machilīpatnam and Eluru. About 320,000 km² of land in 7 countries matches 80% or better, most of it in Andhra Pradesh, India, Telangana, India and Odisha, India.

Your growing climate

Zone 12b · No frost · 0 chill hours · 48 in rainZone 12b · No frost · 0 chill hours · 1,231 mm rain

What grows in Rāmachandrapuram →

Regions with the most land like yours

  1. 1

    🇮🇳Andhra Pradesh, India

    36k sq mi94k km² matching 80% or better

    For example Tuni (99), Payakaraopeta (99)

  2. 2

    🇮🇳Telangana, India

    5,700 sq mi15k km² matching 80% or better

    For example Sathupalli (91), Sādpalli (91)

  3. 3

    🇮🇳Odisha, India

    4,800 sq mi12k km² matching 80% or better

    For example Paralakhemundi (92), Gunupur (85)

  4. 4

    🇮🇩East Nusa Tenggara, Indonesia

    3,500 sq mi9,200 km² matching 80% or better

    For example Waingapu (84), Lewoleba (83)

  5. 5

    🇰🇭Siem Reap, Cambodia

    3,500 sq mi9,000 km² matching 80% or better

    For example Siem Reap (86), Yeang (83)

  6. 6

    🇰🇭Preah Vihear, Cambodia

    2,900 sq mi7,500 km² matching 80% or better

    For example Tbeng Meanchey (81)

  7. 7

    🇹🇿Lindi, Tanzania

    2,400 sq mi6,100 km² matching 80% or better

    For example Kilwa Masoko (83), Lindi (78)

  8. 8

    🇰🇭Kampong Thom, Cambodia

    2,300 sq mi6,000 km² matching 80% or better

    For example Phumĭ Tnaôt (80), Kampong Thom (74)

  9. 9

    🇦🇺Northern Territory, Australia

    1,800 sq mi4,500 km² matching 80% or better

    For example Darwin (71), Palmerston (67)

  10. 10

    🇹🇿Pwani, Tanzania

    900 sq mi2,300 km² matching 80% or better

    For example Ikwiriri (74), Kibiti (59)

  11. 11

    🇹🇿Morogoro, Tanzania

    900 sq mi2,300 km² matching 80% or better

    For example Ifakara (73), Kidodi (59)

  12. 12

    🇹🇭Nakhon Pathom, Thailand

    300 sq mi800 km² matching 80% or better

    For example Bang Len (80), Sam Phran (78)

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

    🇮🇳TuniAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 48 in rainZone 12b · No frost · 0 chill hours · 1,217 mm rain

    Shares 15 of your 16 great-fit crops

    99%match
  2. 2

    🇮🇳MachilīpatnamAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 45 in rainZone 12b · No frost · 0 chill hours · 1,137 mm rain

    Shares 14 of your 16 great-fit crops

    99%match
  3. 3

    🇮🇳EluruAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 46 in rainZone 12b · No frost · 0 chill hours · 1,166 mm rain

    Shares 16 of your 16 great-fit crops

    98%match
  4. 4

    🇮🇳ThenaliAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 41 in rainZone 12b · No frost · 0 chill hours · 1,046 mm rain

    Shares 15 of your 16 great-fit crops

    98%match
  5. 5

    🇮🇳SrikakulamAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 46 in rainZone 12a · No frost · 0 chill hours · 1,179 mm rain

    Shares 15 of your 16 great-fit crops

    97%match
  6. 6

    🇮🇳VizianagaramAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 50 in rainZone 12a · No frost · 0 chill hours · 1,271 mm rain

    Shares 16 of your 16 great-fit crops

    96%match
  7. 7

    🇮🇳RasapūdipalemAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 46 in rainZone 12b · No frost · 0 chill hours · 1,171 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: avocado

    96%match
  8. 8

    🇮🇳PhirangipuramAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 40 in rainZone 12b · No frost · 0 chill hours · 1,009 mm rain

    Shares 15 of your 16 great-fit crops

    95%match
  9. 9

    🇮🇳KondapalleAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 39 in rainZone 12b · No frost · 0 chill hours · 998 mm rain

    Shares 15 of your 16 great-fit crops

    94%match
  10. 10

    🇮🇳NarasaraopetAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 38 in rainZone 12a · No frost · 0 chill hours · 967 mm rain

    Shares 15 of your 16 great-fit crops

    92%match
  11. 11

    🇮🇳ParalakhemundiOdisha, India

    Zone 12a · No frost · 0 chill hours · 61 in rainZone 12a · No frost · 0 chill hours · 1,556 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: avocado, wheat

    92%match
  12. 12

    🇮🇳SathupalliTelangana, India

    Zone 12a · No frost · 0 chill hours · 49 in rainZone 12a · No frost · 0 chill hours · 1,244 mm rain

    Shares 16 of your 16 great-fit crops

    91%match
  13. 13

    🇮🇳BobbiliAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 56 in rainZone 12a · No frost · 0 chill hours · 1,417 mm rain

    Shares 16 of your 16 great-fit crops · Also great there: wheat

    90%match
  14. 14

    🇮🇳DarsiAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 33 in rainZone 12b · No frost · 0 chill hours · 841 mm rain

    Shares 15 of your 16 great-fit crops

    89%match
  15. 15

    🇮🇳OngoleAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 37 in rainZone 12b · No frost · 0 chill hours · 950 mm rain

    Shares 15 of your 16 great-fit crops

    88%match
  16. 16

    🇰🇭Siem ReapCambodia

    Zone 12b · No frost · 0 chill hours · 53 in rainZone 12b · No frost · 0 chill hours · 1,342 mm rain

    Shares 14 of your 16 great-fit crops

    86%match
  17. 17

    🇮🇳GunupurOdisha, India

    Zone 11b · No frost · 0 chill hours · 64 in rainZone 11b · No frost · 0 chill hours · 1,637 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: wheat

    85%match
  18. 18

    🇮🇳HinjilicutOdisha, India

    Zone 11b · No frost · 0 chill hours · 62 in rainZone 11b · No frost · 0 chill hours · 1,584 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: avocado, wheat

    85%match
  19. 19

    🇮🇳BrahmapurOdisha, India

    Zone 12a · No frost · 0 chill hours · 60 in rainZone 12a · No frost · 0 chill hours · 1,520 mm rain

    Shares 15 of your 16 great-fit crops · Also great there: avocado, wheat

    84%match
  20. 20

    🇮🇳PalwanchaTelangana, India

    Zone 12a · No frost · 0 chill hours · 47 in rainZone 12a · No frost · 0 chill hours · 1,201 mm rain

    Shares 16 of your 16 great-fit crops

    84%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 Rāmachandrapuram: 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.