Climatch

Land with a climate like Sūryampālaiyam

🇮🇳Sūryampālaiyam, Tamil Nadu, India

The towns with the closest growing climate to Sūryampālaiyam are Thuraiyur, India (99% match), Attur and Dindigul. About 81,000 sq mi of land in 8 countries matches 80% or better, most of it in Tamil Nadu, India, Andhra Pradesh, India and La Guajira Department, Colombia.The towns with the closest growing climate to Sūryampālaiyam are Thuraiyur, India (99% match), Attur and Dindigul. About 209,000 km² of land in 8 countries matches 80% or better, most of it in Tamil Nadu, India, Andhra Pradesh, India and La Guajira Department, Colombia.

Your growing climate

Zone 13a · No frost · 0 chill hours · 34 in rainZone 13a · No frost · 0 chill hours · 860 mm rain

What grows in Sūryampālaiyam →

Regions with the most land like yours

  1. 1

    🇮🇳Tamil Nadu, India

    38k sq mi98k km² matching 80% or better

    For example Tammampatti (99), Kulittalai (99)

  2. 2

    🇮🇳Andhra Pradesh, India

    17k sq mi44k km² matching 80% or better

    For example Pāmūru (94), Chittoor (94)

  3. 3

    🇨🇴La Guajira Department, Colombia

    4,400 sq mi11k km² matching 80% or better

    For example Albania (89), Fonseca (87)

  4. 4

    🇨🇴Cesar Department, Colombia

    3,800 sq mi9,900 km² matching 80% or better

    For example Valledupar (88), San Diego (87)

  5. 5

    🇨🇴Magdalena Department, Colombia

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

    For example Fundación (83), Pivijay (80)

  6. 6

    🇻🇪Falcón, Venezuela

    2,100 sq mi5,300 km² matching 80% or better

    For example Dabajuro (83), Mene de Mauroa (83)

  7. 7

    🇰🇭Kampong Speu Province, Cambodia

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

    For example Phumĭ Véal Tônsay (85), Kampong Speu (84)

  8. 8

    🇰🇭Takeo, Cambodia

    1,200 sq mi3,000 km² matching 80% or better

    For example Phumĭ Yoŭl Toŭng (84), Kandoeng (83)

  9. 9

    🇰🇭Pursat, Cambodia

    1,200 sq mi3,000 km² matching 80% or better

    For example Pursat (83)

  10. 10

    🇹🇭Suphan Buri, Thailand

    1,200 sq mi3,000 km² matching 80% or better

    For example Suphan Buri (86)

  11. 11

    🇹🇭Kanchanaburi, Thailand

    900 sq mi2,300 km² matching 80% or better

    For example Tha Muang (81), Kanchanaburi (80)

  12. 12

    🇻🇪Zulia, Venezuela

    600 sq mi1,500 km² matching 80% or better

    For example Santa Cruz de Mara (80), Los Puertos de Altagracia (79)

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

    🇮🇳ThuraiyurTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 36 in rainZone 13a · No frost · 0 chill hours · 912 mm rain

    Shares 15 of your 15 great-fit crops

    99%match
  2. 2

    🇮🇳AtturTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 42 in rainZone 12b · No frost · 0 chill hours · 1,062 mm rain

    Shares 15 of your 15 great-fit crops

    99%match
  3. 3

    🇮🇳DindigulTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 37 in rainZone 13a · No frost · 0 chill hours · 941 mm rain

    Shares 15 of your 15 great-fit crops

    98%match
  4. 4

    🇮🇳DharmapuriTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 39 in rainZone 12b · No frost · 0 chill hours · 982 mm rain

    Shares 15 of your 15 great-fit crops

    98%match
  5. 5

    🇮🇳PallappattiTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 28 in rainZone 13a · No frost · 0 chill hours · 722 mm rain

    Shares 14 of your 15 great-fit crops

    97%match
  6. 6

    🇮🇳ManapparaiTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 40 in rainZone 13a · No frost · 0 chill hours · 1,004 mm rain

    Shares 15 of your 15 great-fit crops

    97%match
  7. 7

    🇮🇳PalaniTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 28 in rainZone 12b · No frost · 0 chill hours · 722 mm rain

    Shares 14 of your 15 great-fit crops · Also great there: table and raisin grapes

    96%match
  8. 8

    🇮🇳AllinagaramTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 35 in rainZone 13a · No frost · 0 chill hours · 889 mm rain

    Shares 15 of your 15 great-fit crops

    96%match
  9. 9

    🇮🇳VelloreTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 42 in rainZone 12b · No frost · 0 chill hours · 1,070 mm rain

    Shares 15 of your 15 great-fit crops

    95%match
  10. 10

    🇮🇳TuvāgudiTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 38 in rainZone 13a · No frost · 0 chill hours · 957 mm rain

    Shares 15 of your 15 great-fit crops

    95%match
  11. 11

    🇮🇳KrishnagiriTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 35 in rainZone 12b · No frost · 0 chill hours · 883 mm rain

    Shares 15 of your 15 great-fit crops

    95%match
  12. 12

    🇮🇳TiruvannamalaiTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 47 in rainZone 12b · No frost · 0 chill hours · 1,204 mm rain

    Shares 15 of your 15 great-fit crops

    94%match
  13. 13

    🇮🇳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 15 great-fit crops · Also great there: avocado

    94%match
  14. 14

    🇮🇳AmburTamil Nadu, India

    Zone 12a · No frost · 0 chill hours · 37 in rainZone 12a · No frost · 0 chill hours · 943 mm rain

    Shares 15 of your 15 great-fit crops

    94%match
  15. 15

    🇮🇳AriyalūrTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 45 in rainZone 13a · No frost · 0 chill hours · 1,152 mm rain

    Shares 15 of your 15 great-fit crops

    94%match
  16. 16

    🇮🇳KallakurichiTamil Nadu, India

    Zone 12b · No frost · 0 chill hours · 46 in rainZone 12b · No frost · 0 chill hours · 1,175 mm rain

    Shares 15 of your 15 great-fit crops

    94%match
  17. 17

    🇮🇳ĀnaiyūrTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 42 in rainZone 13a · No frost · 0 chill hours · 1,069 mm rain

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

    93%match
  18. 18

    🇮🇳MaduraiTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 42 in rainZone 13a · No frost · 0 chill hours · 1,062 mm rain

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

    93%match
  19. 19

    🇮🇳Kanigiri UAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 32 in rainZone 12b · No frost · 0 chill hours · 820 mm rain

    Shares 15 of your 15 great-fit crops

    92%match
  20. 20

    🇮🇳SūleswaranpattiTamil Nadu, India

    Zone 13a · No frost · 0 chill hours · 46 in rainZone 13a · No frost · 0 chill hours · 1,178 mm rain

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

    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 Sūryampālaiyam: 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.