Climatch

Land with a climate like Nāgamangala

🇮🇳Nāgamangala, Karnataka, India

The towns with the closest growing climate to Nāgamangala are Arsikere, India (99% match), Chamrajnagar and Kanakapura. About 65,000 sq mi of land in 7 countries matches 80% or better, most of it in Karnataka, India, Tamil Nadu, India and Andhra Pradesh, India.The towns with the closest growing climate to Nāgamangala are Arsikere, India (99% match), Chamrajnagar and Kanakapura. About 167,000 km² of land in 7 countries matches 80% or better, most of it in Karnataka, India, Tamil Nadu, India and Andhra Pradesh, India.

Your growing climate

Zone 12a · No frost · 0 chill hours · 26 in rainZone 12a · No frost · 0 chill hours · 670 mm rain

What grows in Nāgamangala →

Regions with the most land like yours

  1. 1

    🇮🇳Karnataka, India

    38k sq mi99k km² matching 80% or better

    For example Arsikere (99), Kadūr (99)

  2. 2

    🇮🇳Tamil Nadu, India

    4,700 sq mi12k km² matching 80% or better

    For example Mūkondapalli (98), Jūjūvādi (98)

  3. 3

    🇮🇳Andhra Pradesh, India

    4,600 sq mi12k km² matching 80% or better

    For example Punganūru (93), Hindupur (93)

  4. 4

    🇹🇭Lampang, Thailand

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

    For example Thoen (76), Lampang (73)

  5. 5

    🇲🇲Magway, Myanmar

    2,200 sq mi5,800 km² matching 80% or better

    For example Taungdwingyi (77), Magway (70)

  6. 6

    🇲🇲Mandalay Region, Myanmar

    2,000 sq mi5,100 km² matching 80% or better

    For example Kyaukpadaung (80), Pyawbwe (77)

  7. 7

    🇹🇭Lamphun, Thailand

    1,700 sq mi4,400 km² matching 80% or better

    For example Pa Sang (80), Lamphun (77)

  8. 8

    🇧🇷Piauí, Brazil

    1,500 sq mi3,800 km² matching 80% or better

    For example Inhuma (83), Valença do Piauí (79)

  9. 9

    🇹🇿Kigoma, Tanzania

    1,200 sq mi3,100 km² matching 80% or better

    For example Kigoma (79), Mwandiga (79)

  10. 10

    🇨🇩Tanganyika, Democratic Republic of the Congo

    1,200 sq mi3,100 km² matching 80% or better

    For example Kalemie (77), Kalima (58)

  11. 11

    🇹🇭Tak, Thailand

    900 sq mi2,200 km² matching 80% or better

    For example Ban Tak (65), Tak (57)

  12. 12

    🇧🇷Maranhão, Brazil

    600 sq mi1,500 km² matching 80% or better

    For example Buriti Bravo (77), São João dos Patos (77)

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

    🇮🇳ArsikereKarnataka, India

    Zone 12a · No frost · 0 chill hours · 24 in rainZone 12a · No frost · 0 chill hours · 609 mm rain

    Shares 16 of your 17 great-fit crops

    99%match
  2. 2

    🇮🇳ChamrajnagarKarnataka, India

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

    Shares 16 of your 17 great-fit crops

    99%match
  3. 3

    🇮🇳KanakapuraKarnataka, India

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

    Shares 16 of your 17 great-fit crops · Also great there: rice, sugarcane

    99%match
  4. 4

    🇮🇳BirūrKarnataka, India

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

    Shares 16 of your 17 great-fit crops

    99%match
  5. 5

    🇮🇳BangarapetKarnataka, India

    Zone 12a · No frost · 0 chill hours · 30 in rainZone 12a · No frost · 0 chill hours · 752 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: rice, barley, sugarcane

    99%match
  6. 6

    🇮🇳HosadurgaKarnataka, India

    Zone 12a · No frost · 0 chill hours · 23 in rainZone 12a · No frost · 0 chill hours · 574 mm rain

    Shares 14 of your 17 great-fit crops

    99%match
  7. 7

    🇮🇳RobertsonpetKarnataka, India

    Zone 12a · No frost · 0 chill hours · 30 in rainZone 12a · No frost · 0 chill hours · 750 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: barley, rice, sugarcane

    98%match
  8. 8

    🇮🇳MūkondapalliTamil Nadu, India

    Zone 12a · No frost · 0 chill hours · 34 in rainZone 12a · No frost · 0 chill hours · 861 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: rice, sugarcane, barley

    98%match
  9. 9

    🇮🇳BengaluruKarnataka, India

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

    Shares 17 of your 17 great-fit crops · Also great there: rice, sugarcane, barley

    97%match
  10. 10

    🇮🇳BāgepalliKarnataka, India

    Zone 12a · No frost · 0 chill hours · 27 in rainZone 12a · No frost · 0 chill hours · 683 mm rain

    Shares 15 of your 17 great-fit crops · Also great there: rice

    97%match
  11. 11

    🇮🇳ChannagiriKarnataka, India

    Zone 12a · No frost · 0 chill hours · 24 in rainZone 12a · No frost · 0 chill hours · 619 mm rain

    Shares 15 of your 17 great-fit crops

    97%match
  12. 12

    🇮🇳GauribidanurKarnataka, India

    Zone 12a · No frost · 0 chill hours · 30 in rainZone 12a · No frost · 0 chill hours · 757 mm rain

    Shares 15 of your 17 great-fit crops · Also great there: rice, sugarcane

    97%match
  13. 13

    🇮🇳HunsūrKarnataka, India

    Zone 12a · No frost · 0 chill hours · 36 in rainZone 12a · No frost · 0 chill hours · 903 mm rain

    Shares 17 of your 17 great-fit crops · Also great there: sugarcane, rice

    97%match
  14. 14

    🇮🇳SīraKarnataka, India

    Zone 12a · No frost · 0 chill hours · 22 in rainZone 12a · No frost · 0 chill hours · 569 mm rain

    Shares 14 of your 17 great-fit crops

    96%match
  15. 15

    🇮🇳ChitradurgaKarnataka, India

    Zone 12a · No frost · 0 chill hours · 24 in rainZone 12a · No frost · 0 chill hours · 614 mm rain

    Shares 14 of your 17 great-fit crops

    94%match
  16. 16

    🇮🇳DavangereKarnataka, India

    Zone 12a · No frost · 0 chill hours · 26 in rainZone 12a · No frost · 0 chill hours · 668 mm rain

    Shares 15 of your 17 great-fit crops

    94%match
  17. 17

    🇮🇳MadanapalleAndhra Pradesh, India

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

    Shares 16 of your 17 great-fit crops · Also great there: rice

    93%match
  18. 18

    🇮🇳PāvugadaKarnataka, India

    Zone 12a · No frost · 0 chill hours · 22 in rainZone 12a · No frost · 0 chill hours · 569 mm rain

    Shares 13 of your 17 great-fit crops

    91%match
  19. 19

    🇮🇳HubballiKarnataka, India

    Zone 12a · No frost · 0 chill hours · 35 in rainZone 12a · No frost · 0 chill hours · 895 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: rice, sugarcane

    91%match
  20. 20

    🇮🇳HāveriKarnataka, India

    Zone 12a · No frost · 0 chill hours · 34 in rainZone 12a · No frost · 0 chill hours · 851 mm rain

    Shares 15 of your 17 great-fit crops · Also great there: rice, sugarcane

    91%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 Nāgamangala: 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.