Climatch

Land with a climate like Kuppam

🇮🇳Kuppam, Andhra Pradesh, India

The towns with the closest growing climate to Kuppam are Madanapalle, India (99% match), Kanakapura and Pennāgaram. About 166,000 sq mi of land in 13 countries matches 80% or better, most of it in Karnataka, India, Maranhão, Brazil and Tamil Nadu, India.The towns with the closest growing climate to Kuppam are Madanapalle, India (99% match), Kanakapura and Pennāgaram. About 431,000 km² of land in 13 countries matches 80% or better, most of it in Karnataka, India, Maranhão, Brazil and Tamil Nadu, India.

Your growing climate

Zone 12a · No frost · 0 chill hours · 32 in rainZone 12a · No frost · 0 chill hours · 801 mm rain

What grows in Kuppam →

Regions with the most land like yours

  1. 1

    🇮🇳Karnataka, India

    28k sq mi74k km² matching 80% or better

    For example Kanakapura (99), Kollegāl (98)

  2. 2

    🇧🇷Maranhão, Brazil

    23k sq mi60k km² matching 80% or better

    For example Buriti Bravo (88), Estreito (88)

  3. 3

    🇮🇳Tamil Nadu, India

    18k sq mi47k km² matching 80% or better

    For example Pennāgaram (98), Pallippatti (94)

  4. 4

    🇧🇷Piauí, Brazil

    16k sq mi42k km² matching 80% or better

    For example Água Branca (86), Regeneração (86)

  5. 5

    🇮🇳Andhra Pradesh, India

    16k sq mi41k km² matching 80% or better

    For example Madanapalle (99), Pīleru (97)

  6. 6

    🇲🇲Mandalay Region, Myanmar

    9,500 sq mi25k km² matching 80% or better

    For example Yamethin (88), Kyaukse (87)

  7. 7

    🇲🇲Magway, Myanmar

    7,000 sq mi18k km² matching 80% or better

    For example Taungdwingyi (85), Magway (80)

  8. 8

    🇹🇭Lampang, Thailand

    4,800 sq mi13k km² matching 80% or better

    For example Thoen (89), Lampang (88)

  9. 9

    🇹🇭Phayao, Thailand

    3,100 sq mi8,000 km² matching 80% or better

    For example Phayao (86), Dok Kham Tai (84)

  10. 10

    🇹🇭Tak, Thailand

    2,600 sq mi6,700 km² matching 80% or better

    For example Ban Tak (83), Tak (78)

  11. 11

    🇲🇲Sagaing Region, Myanmar

    2,500 sq mi6,400 km² matching 80% or better

    For example Sagaing (82), Ye-u (79)

  12. 12

    🇹🇿Lindi, Tanzania

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

    For example Nachingwea (84), Nyangao (84)

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

    🇮🇳MadanapalleAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 27 in rainZone 12a · No frost · 0 chill hours · 692 mm rain

    Shares 17 of your 18 great-fit crops

    99%match
  2. 2

    🇮🇳KanakapuraKarnataka, India

    Zone 12a · No frost · 0 chill hours · 33 in rainZone 12a · No frost · 0 chill hours · 832 mm rain

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

    99%match
  3. 3

    🇮🇳PennāgaramTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 38 in rainZone 12b · No frost · 0 chill hours · 964 mm rain

    Shares 15 of your 18 great-fit crops

    98%match
  4. 4

    🇮🇳PīleruAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 30 in rainZone 12a · No frost · 0 chill hours · 768 mm rain

    Shares 16 of your 18 great-fit crops

    97%match
  5. 5

    🇮🇳NanjangūdKarnataka, India

    Zone 12a · No frost · 0 chill hours · 31 in rainZone 12a · No frost · 0 chill hours · 794 mm rain

    Shares 16 of your 18 great-fit crops · Also great there: avocado

    96%match
  6. 6

    🇮🇳ChintamaniKarnataka, India

    Zone 11b · No frost · 0 chill hours · 28 in rainZone 11b · No frost · 0 chill hours · 711 mm rain

    Shares 17 of your 18 great-fit crops · Also great there: barley, avocado

    96%match
  7. 7

    🇮🇳BengaluruKarnataka, India

    Zone 12a · No frost · 0 chill hours · 36 in rainZone 12a · No frost · 0 chill hours · 914 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: avocado, barley

    96%match
  8. 8

    🇮🇳ChamrajnagarKarnataka, India

    Zone 12a · No frost · 0 chill hours · 28 in rainZone 12a · No frost · 0 chill hours · 717 mm rain

    Shares 15 of your 18 great-fit crops · Also great there: avocado

    95%match
  9. 9

    🇮🇳MysuruKarnataka, India

    Zone 12b · No frost · 0 chill hours · 31 in rainZone 12b · No frost · 0 chill hours · 781 mm rain

    Shares 16 of your 18 great-fit crops · Also great there: avocado

    94%match
  10. 10

    🇮🇳PallippattiTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 40 in rainZone 12b · No frost · 0 chill hours · 1,015 mm rain

    Shares 15 of your 18 great-fit crops

    94%match
  11. 11

    🇮🇳GorantlaAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 26 in rainZone 12a · No frost · 0 chill hours · 669 mm rain

    Shares 16 of your 18 great-fit crops

    94%match
  12. 12

    🇮🇳HindupurAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 27 in rainZone 12a · No frost · 0 chill hours · 687 mm rain

    Shares 15 of your 18 great-fit crops

    94%match
  13. 13

    🇮🇳TirumalaAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 42 in rainZone 12a · No frost · 0 chill hours · 1,074 mm rain

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

    94%match
  14. 14

    🇮🇳KadiriAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 27 in rainZone 12a · No frost · 0 chill hours · 684 mm rain

    Shares 14 of your 18 great-fit crops

    93%match
  15. 15

    🇮🇳KoratagereKarnataka, India

    Zone 12a · No frost · 0 chill hours · 29 in rainZone 12a · No frost · 0 chill hours · 740 mm rain

    Shares 17 of your 18 great-fit crops

    92%match
  16. 16

    🇮🇳CoimbatoreTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 39 in rainZone 12b · No frost · 0 chill hours · 995 mm rain

    Shares 15 of your 18 great-fit crops · Also great there: avocado

    91%match
  17. 17

    🇮🇳MāgadiKarnataka, India

    Zone 12a · No frost · 0 chill hours · 33 in rainZone 12a · No frost · 0 chill hours · 831 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: avocado, barley

    90%match
  18. 18

    🇮🇳ChittoorAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 40 in rainZone 12a · No frost · 0 chill hours · 1,015 mm rain

    Shares 15 of your 18 great-fit crops

    90%match
  19. 19

    🇮🇳UdumalaippettaiTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 33 in rainZone 12b · No frost · 0 chill hours · 837 mm rain

    Shares 16 of your 18 great-fit crops

    90%match
  20. 20

    🇮🇳TumkūrKarnataka, India

    Zone 12a · No frost · 0 chill hours · 31 in rainZone 12a · No frost · 0 chill hours · 786 mm rain

    Shares 18 of your 18 great-fit crops · Also great there: avocado, barley

    89%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 Kuppam: 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.