Telangana, India weather forecasts
184 cities and towns of 1,000 people or more, each with its own forecast page.
- Achampet 20,721
- Ādilābād 118,526
- Ālampur 14,060
- Allipur 11,276
- Amīnpur 36,452
- Āmūr 64,023
- Andol 24,645
- Anwaram 6,840
- Asifābād 23,059
- Atmākūr 12,297
- Bādepalli 32,598
- Bālāpur 8,280
- Bandlaguda 12,734
- Bānswāda 28,384
- Bāspalli 27,563
- Bellampalli 66,660
- Bhadrāchalam 50,087
- Bhaisa 49,764
- Bhānūr 9,203
- Bhīmavaram 13,841
- Bhongīr 53,339
- Bhupalpally 42,387
- Bībīnagar 8,320
- Bodhan 77,573
- Bodupāl 43,692
- Bolārum 34,667
- Bontapalli 6,608
- Boyāpalli 9,247
- Chandūr 11,220
- Chandūr 10,880
- Chātakonda 2,816
- Chautāpal 19,092
- Chegunta 5,747
- Chinnachintakunta 5,637
- Chinnūr 23,579
- Chitkul 5,596
- Chityāl 13,752
- Chunchupally 19,944
- Dasnapur 22,216
- Devāpur 9,683
- Devarkonda 29,731
- Dharmaram 11,537
- Dornakal 15,350
- Dundigal 13,465
- Farrukhnagar 45,675
- Gaddi Annaram 53,622
- Gadwāl 63,177
- Gajwel 24,961
- Garimellapadu 6,296
- Ghanpur 12,721
- Ghatkesar 19,763
- Gopālur 3,324
- Gorrakunta 13,159
- Gūdūr 5,647
- Gunpuram 5,182
- Guntur 13,183
- Hyderabad 6,993,262
- Ibrāhīmpatan 12,349
- Ichora 12,358
- Isnapuram 8,276
- Jadcherla 17,958
- Jagtiāl 103,930
- Jallaram 9,329
- Jām 6,426
- Jangaon 52,394
- Jawaharnagar 44,562
- Jilādiguda 27,461
- Jogipet 18,494
- Kadipikonda 8,685
- Kagaznāgār 57,583
- Kalwākurti 28,060
- Kamalāpuram 11,493
- Kāmāreddi 80,315
- Karīmnagar 289,821
- Kasipet 5,133
- Khammam 196,283
- Khanapuram Haveli 53,442
- Kiādgira 6,711
- Kismatpur 7,288
- Kodār 64,234
- Kompalli 15,575
- Kondamallapally 9,683
- Konta 7,038
- Koratla 66,504
- Kothakota 19,042
- Kothāpet 4,266
- Kottagūdem 79,819
- Kottapalli 9,899
- Kottapeta 12,740
- Kotūr 10,519
- Kukatpally 341,709
- Kyathampalle 42,275
- Lakshettipet 11,322
- Lal Bahadur Nagar 261,987
- Laxmidevipally 13,442
- Madhira 22,716
- Mahbūbābād 42,851
- Mahbūbnagar 190,400
- Mailāram 11,759
- Malkajgiri 150,000
- Mamnūr 6,319
- Mancherial 89,935
- Mandamarri 66,176
- Manthani 15,661
- Manuguru 32,539
- Medak 46,880
- Medchal 35,611
- Medpalli 10,787
- Meerpet 32,013
- Metpalle 50,902
- Miryalaguda 104,918
- Mulugu 297,671
- Muttargi 8,777
- Nāgar Karnūl 29,439
- Nāgāvaram 30,502
- Nakrekal 29,126
- Nalgonda 154,326
- Nārāyankher 15,610
- Nārāyanpet 41,752
- Narsampet 30,963
- Narsāpuram 6,647
- Nārsingi 9,449
- Nārsingi 6,445
- Nāspur 31,244
- Nirmal 88,433
- Nizāmābād 311,152
- Osmania University 6,762
- Palakurthy 7,380
- Pāloncha 75,224
- Palwancha 80,199
- Patancheru 46,821
- Peddapalli 41,171
- Pīrzādagūda 32,586
- Pochampalli 12,972
- Potreddipalli 11,514
- Quthbullapur 225,816
- Raghunāthpuram 4,008
- Rāmachandrapuran 15,381
- Ramagundam 242,979
- Rāmanapeta 10,202
- Rāmgundam 452,261
- Ratnāpuram 3,154
- Rekurti 7,626
- Sadasivpet 47,920
- Sādpalli 31,857
- Saknepalli 32,385
- Sangāreddi 72,344
- Sarapāka 22,149
- Sathupalli 40,000
- Secunderabad 204,182
- Serilingampalle 150,525
- Shahmīrpet 0
- Shamshabad 32,583
- Shankrampet 6,227
- Siddipet 66,737
- Singānuram 20,061
- Singāpur 24,457
- Sirpur 10,116
- Sirsilla 83,186
- Sivunipalli 6,242
- Soanpeta 6,820
- Srīrāmnagar 19,550
- Suriāpet 111,729
- Tandur 65,115
- Tangapur 7,704
- Tarlapalli 9,656
- Teegalpahad 12,656
- Timmāpur 13,485
- Torūr 19,100
- Umarkhāngūda 5,349
- Uppal Kalan 118,259
- Utnūr 16,005
- Vativellupalli 4,544
- Vemalwāda 33,706
- Vijayapuri North 15,887
- Vikārābād 53,143
- Wanparti 60,949
- Warangal 704,570
- Yadagirigutta 15,232
- Yamjāl 15,689
- Yellandu 43,787
- Yellāreddi 14,923
- Yenugonda 10,611
- Zahirābād 71,166
What is here
- Seven days
- The high, the low, the chance and amount of rain and snow, the wind and the forecaster’s words for each day and night, from the National Weather Service grid for the exact cell your town sits in.
- Hour by hour
- Temperature, what it feels like, dew point, humidity, chance and amount of precipitation, wind and gusts, sky cover, the chance of thunder, pressure, visibility and ceiling, as a chart and as a table, with nights shaded.
- Everything else on the grid
- The office edits about sixty fields for every cell. The ones the mainstream forecast pages leave out are here as a daily table: HeatRisk, wet bulb globe temperature, lightning activity, mixing height, transport wind, the fire weather indices, and at the coast the waves and swell.
- The discussion
- The Area Forecast Discussion the forecaster wrote to explain the forecast, in their own words, with the specialist annexes folded away. Also the office’s hazardous weather outlook.
- Beyond the week
- The Storm Prediction Center’s severe weather category for each of the next eight days, the Weather Prediction Center’s rainfall forecast to day seven and its winter storm severity, and the Climate Prediction Center’s odds for days six to fourteen, all read at your coordinate.
- Against the record
- Each forecast day beside the same date at the nearest long-record station: the thirty-year normal and the record high and low with their years, so a forecast high that would break a record says so.
- The next 90 days
- The forecast as far as the grid, the National Blend and the global models reach, and the calendar after that: the normal and the record for every date, with the Climate Prediction Center’s lean for the weeks, the month and the season drawn over them. No made-up highs for a date three months out.
Common questions
Where does this forecast come from?
From the National Weather Service forecast grid published at api.weather.gov, the same grid the local forecast office edits through the day and the source of every forecast on weather.gov. The written periods, the hourly digest and the forecaster’s discussion are the NWS’s own products, shown as issued. Nothing here is a blend a website made.
How far ahead does it go?
The grid runs seven days ahead, hour by hour for the first days and in three to six hour steps after that. The National Blend of Models carries the days to eleven and the global models to sixteen. Beyond that the page carries the national centers’ outlooks, severe weather to day eight, rainfall to day seven, and the Climate Prediction Center’s odds for the coming weeks, month and season, over a ninety-day calendar of the normal and the record for each date. No forecast has skill day by day past about two weeks, and this page does not print one.
Why is this different from the app on my phone?
Most forecast apps show a blend of models chosen by the company that makes the app. This page shows the forecast the local National Weather Service office issues, edited by the forecasters who will also issue the warnings, and it shows all of it rather than the six numbers that fit on a phone. The discussion explains the reasoning, which no app carries.
What is a place’s address here?
Every town has its own page, such as /forecast/us/oklahoma/oklahoma-city/, and every day at a town has one too. A ZIP code typed into the search goes to the town it belongs to. Any coordinate at all can be looked up, and the page names the nearest town.
What the weather actually was · Open the live radar · Where the data comes from