Climatch

Land with a climate like Sālūr

🇮🇳Sālūr, Andhra Pradesh, India

The towns with the closest growing climate to Sālūr are Gunupur, India (99% match), Rāyagada and Narsīpatnam. About 348,000 sq mi of land in 14 countries matches 80% or better, most of it in Odisha, India, Andhra Pradesh, India and West Bengal, India.The towns with the closest growing climate to Sālūr are Gunupur, India (99% match), Rāyagada and Narsīpatnam. About 900,000 km² of land in 14 countries matches 80% or better, most of it in Odisha, India, Andhra Pradesh, India and West Bengal, India.

Your growing climate

Zone 12a · No frost · 0 chill hours · 55 in rainZone 12a · No frost · 0 chill hours · 1,393 mm rain

What grows in Sālūr →

Regions with the most land like yours

  1. 1

    🇮🇳Odisha, India

    38k sq mi97k km² matching 80% or better

    For example Gunupur (99), Rāyagada (99)

  2. 2

    🇮🇳Andhra Pradesh, India

    28k sq mi72k km² matching 80% or better

    For example Chodavaram (99), Narsīpatnam (99)

  3. 3

    🇮🇳West Bengal, India

    20k sq mi53k km² matching 80% or better

    For example Kharagpur (90), Howrah (88)

  4. 4

    🇹🇭Nakhon Ratchasima, Thailand

    6,900 sq mi18k km² matching 80% or better

    For example Nakhon Ratchasima (90), Chok Chai (89)

  5. 5

    🇹🇭Kanchanaburi, Thailand

    5,800 sq mi15k km² matching 80% or better

    For example Nong Prue (84), Bo Phloi (81)

  6. 6

    🇱🇦Savannakhet Province, Laos

    5,400 sq mi14k km² matching 80% or better

    For example Ban Xénô (83), Savannakhet (83)

  7. 7

    🇰🇭Kampong Thom, Cambodia

    5,200 sq mi14k km² matching 80% or better

    For example Phumĭ Tnaôt (85), Kampong Thom (82)

  8. 8

    🇰🇭Stung Treng, Cambodia

    4,900 sq mi13k km² matching 80% or better

    For example Stung Treng (85)

  9. 9

    🇰🇭Kratie, Cambodia

    4,700 sq mi12k km² matching 80% or better

    For example Kratié (83), Preaek Prasab (82)

  10. 10

    🇹🇭Udon Thani, Thailand

    4,600 sq mi12k km² matching 80% or better

    For example Nam Som (86), Kut Chap (85)

  11. 11

    🇹🇿Morogoro, Tanzania

    4,400 sq mi11k km² matching 80% or better

    For example Ifakara (82), Kidodi (81)

  12. 12

    🇲🇲Sagaing Region, Myanmar

    4,400 sq mi11k km² matching 80% or better

    For example Kalemyo (84), Kanbalu (81)

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

    🇮🇳GunupurOdisha, India

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

    Shares 16 of your 17 great-fit crops

    99%match
  2. 2

    🇮🇳RāyagadaOdisha, India

    Zone 11b · No frost · 0 chill hours · 62 in rainZone 11b · No frost · 0 chill hours · 1,574 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: canola (rapeseed), barley

    99%match
  3. 3

    🇮🇳NarsīpatnamAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 56 in rainZone 12a · No frost · 0 chill hours · 1,420 mm rain

    Shares 16 of your 17 great-fit crops

    99%match
  4. 4

    🇮🇳ParalakhemundiOdisha, India

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

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

    99%match
  5. 5

    🇮🇳BālugaonOdisha, India

    Zone 11b · No frost · 0 chill hours · 61 in rainZone 11b · No frost · 0 chill hours · 1,548 mm rain

    Shares 16 of your 17 great-fit crops

    98%match
  6. 6

    🇮🇳RampachodavaramAndhra Pradesh, India

    Zone 12a · No frost · 0 chill hours · 58 in rainZone 12a · No frost · 0 chill hours · 1,472 mm rain

    Shares 17 of your 17 great-fit crops

    98%match
  7. 7

    🇮🇳HinjilicutOdisha, India

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

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

    97%match
  8. 8

    🇮🇳CuttackOdisha, India

    Zone 11b · No frost · 0 chill hours · 70 in rainZone 11b · No frost · 0 chill hours · 1,775 mm rain

    Shares 16 of your 17 great-fit crops

    97%match
  9. 9

    🇮🇳BhubaneswarOdisha, India

    Zone 11b · No frost · 0 chill hours · 69 in rainZone 11b · No frost · 0 chill hours · 1,752 mm rain

    Shares 16 of your 17 great-fit crops

    97%match
  10. 10

    🇮🇳BānapurOdisha, India

    Zone 11b · No frost · 0 chill hours · 63 in rainZone 11b · No frost · 0 chill hours · 1,594 mm rain

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

    96%match
  11. 11

    🇮🇳KendrāparhaOdisha, India

    Zone 11b · No frost · 0 chill hours · 68 in rainZone 11b · No frost · 0 chill hours · 1,725 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: canola (rapeseed)

    95%match
  12. 12

    🇮🇳BhubanOdisha, India

    Zone 11b · No frost · 0 chill hours · 64 in rainZone 11b · No frost · 0 chill hours · 1,631 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: canola (rapeseed)

    94%match
  13. 13

    🇮🇳ByasanagarOdisha, India

    Zone 11b · No frost · 0 chill hours · 67 in rainZone 11b · No frost · 0 chill hours · 1,701 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: canola (rapeseed)

    94%match
  14. 14

    🇮🇳BhadrakOdisha, India

    Zone 11b · No frost · 0 chill hours · 69 in rainZone 11b · No frost · 0 chill hours · 1,756 mm rain

    Shares 16 of your 17 great-fit crops · Also great there: canola (rapeseed)

    94%match
  15. 15

    🇮🇳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 17 great-fit crops

    93%match
  16. 16

    🇮🇳MalakanagiriOdisha, India

    Zone 11b · No frost · 0 chill hours · 71 in rainZone 11b · No frost · 0 chill hours · 1,813 mm rain

    Shares 15 of your 17 great-fit crops

    93%match
  17. 17

    🇮🇳NidadavoleAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 49 in rainZone 12b · No frost · 0 chill hours · 1,249 mm rain

    Shares 16 of your 17 great-fit crops

    92%match
  18. 18

    🇹🇭TakThailand

    Zone 12a · No frost · 0 chill hours · 49 in rainZone 12a · No frost · 0 chill hours · 1,243 mm rain

    Shares 15 of your 17 great-fit crops

    92%match
  19. 19

    🇮🇳RajamahendravaramAndhra Pradesh, India

    Zone 12b · No frost · 0 chill hours · 50 in rainZone 12b · No frost · 0 chill hours · 1,280 mm rain

    Shares 16 of your 17 great-fit crops

    92%match
  20. 20

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

    92%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 Sālūr: 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.