Datasets:
City
stringlengths 3
21
| Country
stringlengths 3
20
| Continent
stringclasses 7
values | Avg Temp Start (1996)
float64 -3.94
28.3
| Avg Temp End (2025)
float64 -3.27
29.2
| Total Warming (C)
float64 -1.91
5.41
| Warming Rate (C/Decade)
float64 -0.85
2.37
| Prediction 2026 (C)
float64 -3.11
29.4
|
|---|---|---|---|---|---|---|---|
Leh
|
India
|
Asia
| -1.29
| 4.12
| 5.41
| 2.367
| 4.4
|
Dushanbe
|
Tajikistan
|
Asia
| 12.28
| 15.84
| 3.56
| 1.621
| 16.16
|
Marrakech
|
Morocco
|
Africa
| 18.12
| 21.06
| 2.94
| 1.449
| 21.48
|
Sweimeh
|
Jordan
|
Asia
| 23.36
| 26.42
| 3.06
| 1.425
| 26.82
|
Yerevan
|
Armenia
|
Asia
| 10.79
| 13.66
| 2.86
| 1.331
| 13.95
|
Almaty
|
Kazakhstan
|
Asia
| 7.83
| 10.53
| 2.7
| 1.214
| 10.78
|
Interlaken
|
Switzerland
|
Europe
| 8.63
| 11.14
| 2.51
| 1.187
| 11.41
|
Innsbruck
|
Austria
|
Europe
| 8.58
| 11
| 2.42
| 1.158
| 11.4
|
Eilat
|
Israel
|
Asia
| 22.88
| 25.26
| 2.38
| 1.126
| 25.67
|
Queenstown
|
New Zealand
|
Pacific
| 8.2
| 10.73
| 2.53
| 1.099
| 10.86
|
Samarkand
|
Uzbekistan
|
Asia
| 13.22
| 15.54
| 2.32
| 1.067
| 15.77
|
Hallstatt
|
Austria
|
Europe
| 8.6
| 10.62
| 2.02
| 1.026
| 11.1
|
AlUla
|
Saudi Arabia
|
Asia
| 22.9
| 25.12
| 2.21
| 1.02
| 25.39
|
Podgorica
|
Montenegro
|
Europe
| 14.03
| 15.99
| 1.97
| 0.999
| 16.51
|
Luxor
|
Egypt
|
Africa
| 24.42
| 26.49
| 2.07
| 0.969
| 26.8
|
Krakow
|
Poland
|
Europe
| 8.33
| 10.25
| 1.92
| 0.963
| 10.72
|
Salzburg
|
Austria
|
Europe
| 8.61
| 10.51
| 1.91
| 0.959
| 10.94
|
Vienna
|
Austria
|
Europe
| 10.17
| 12.04
| 1.87
| 0.951
| 12.54
|
Sharm El Sheikh
|
Egypt
|
Africa
| 24.96
| 27
| 2.04
| 0.945
| 27.24
|
Tbilisi
|
Georgia
|
Asia
| 10.96
| 13.01
| 2.04
| 0.929
| 13.43
|
Annecy
|
France
|
Europe
| 10.06
| 11.94
| 1.87
| 0.923
| 12.28
|
Tromsø
|
Norway
|
Europe
| 0.96
| 2.83
| 1.87
| 0.898
| 3.21
|
Bishkek
|
Kyrgyzstan
|
Asia
| 9.36
| 11.31
| 1.95
| 0.895
| 11.6
|
Budapest
|
Hungary
|
Europe
| 10.71
| 12.46
| 1.75
| 0.891
| 13.04
|
Chamonix
|
France
|
Europe
| 6.77
| 8.66
| 1.89
| 0.888
| 8.96
|
Izmir
|
Turkey
|
Europe
| 17.33
| 19.18
| 1.85
| 0.888
| 19.55
|
Siena
|
Italy
|
Europe
| 13.1
| 14.92
| 1.82
| 0.883
| 15.18
|
Sofia
|
Bulgaria
|
Europe
| 10.38
| 12.07
| 1.69
| 0.865
| 12.51
|
Cairo
|
Egypt
|
Africa
| 21.8
| 23.59
| 1.79
| 0.864
| 23.92
|
Bodrum
|
Turkey
|
Europe
| 18.15
| 19.93
| 1.78
| 0.861
| 20.28
|
Bratislava
|
Slovakia
|
Europe
| 10.28
| 11.97
| 1.69
| 0.86
| 12.47
|
Corfu
|
Greece
|
Europe
| 16.97
| 18.66
| 1.69
| 0.855
| 19
|
Cannes
|
France
|
Europe
| 14.87
| 16.64
| 1.77
| 0.852
| 16.86
|
Takayama
|
Japan
|
Asia
| 10.3
| 12.13
| 1.83
| 0.849
| 12.39
|
Nikko
|
Japan
|
Asia
| 11.25
| 13.05
| 1.8
| 0.845
| 13.28
|
Mexico City
|
Mexico
|
Americas
| 15.83
| 17.51
| 1.68
| 0.834
| 17.74
|
Fethiye
|
Turkey
|
Europe
| 17.75
| 19.45
| 1.7
| 0.833
| 19.76
|
Stuttgart
|
Germany
|
Europe
| 10.06
| 11.69
| 1.63
| 0.825
| 12.04
|
Prague
|
Czech Republic
|
Europe
| 9.31
| 10.91
| 1.59
| 0.821
| 11.31
|
Antalya
|
Turkey
|
Europe
| 17.93
| 19.65
| 1.72
| 0.816
| 19.88
|
Kanazawa
|
Japan
|
Asia
| 13.01
| 14.68
| 1.67
| 0.801
| 14.89
|
Riyadh
|
Saudi Arabia
|
Asia
| 25.25
| 26.89
| 1.64
| 0.797
| 27.15
|
Hoedspruit
|
South Africa
|
Africa
| 21.04
| 22.77
| 1.74
| 0.794
| 23.04
|
Muscat
|
Oman
|
Asia
| 27.47
| 29.19
| 1.72
| 0.793
| 29.36
|
Split
|
Croatia
|
Europe
| 15.03
| 16.57
| 1.54
| 0.784
| 16.92
|
Palm Springs
|
United States
|
Americas
| 22.03
| 23.79
| 1.76
| 0.783
| 23.89
|
Warsaw
|
Poland
|
Europe
| 8.53
| 10.06
| 1.53
| 0.783
| 10.4
|
Fes
|
Morocco
|
Africa
| 18
| 19.67
| 1.66
| 0.777
| 19.91
|
Malaga
|
Spain
|
Europe
| 17.95
| 19.57
| 1.62
| 0.775
| 19.79
|
Tashkent
|
Uzbekistan
|
Asia
| 13.76
| 15.35
| 1.58
| 0.762
| 15.63
|
Granada
|
Spain
|
Europe
| 15.55
| 17.12
| 1.57
| 0.758
| 17.42
|
Munich
|
Germany
|
Europe
| 8.68
| 10.16
| 1.48
| 0.757
| 10.5
|
Scottsdale
|
United States
|
Americas
| 22.11
| 23.79
| 1.68
| 0.757
| 23.96
|
Ras Al Khaimah
|
UAE
|
Asia
| 26.89
| 28.46
| 1.57
| 0.74
| 28.62
|
Malmö
|
Sweden
|
Europe
| 8.38
| 9.95
| 1.57
| 0.737
| 10.22
|
Mendoza
|
Argentina
|
Americas
| 15.4
| 16.96
| 1.55
| 0.736
| 17.38
|
Wrocław
|
Poland
|
Europe
| 9.28
| 10.73
| 1.45
| 0.734
| 11.09
|
Santorini
|
Greece
|
Europe
| 17.82
| 19.28
| 1.46
| 0.726
| 19.6
|
Berlin
|
Germany
|
Europe
| 9.56
| 10.96
| 1.39
| 0.711
| 11.28
|
Tirana
|
Albania
|
Europe
| 15.04
| 16.42
| 1.38
| 0.709
| 16.77
|
Taipei
|
Taiwan
|
Asia
| 21.79
| 23.31
| 1.52
| 0.708
| 23.42
|
Florence
|
Italy
|
Europe
| 14.15
| 15.57
| 1.41
| 0.706
| 15.82
|
Tucumán
|
Argentina
|
Americas
| 18.35
| 19.77
| 1.42
| 0.702
| 20.12
|
Madrid
|
Spain
|
Europe
| 14.18
| 15.57
| 1.38
| 0.7
| 15.8
|
Strasbourg
|
France
|
Europe
| 10.6
| 11.97
| 1.37
| 0.699
| 12.3
|
Hydra
|
Greece
|
Europe
| 18.08
| 19.49
| 1.4
| 0.698
| 19.81
|
Johannesburg
|
South Africa
|
Africa
| 15.03
| 16.52
| 1.49
| 0.696
| 16.81
|
Kaunas
|
Lithuania
|
Europe
| 7.51
| 8.88
| 1.37
| 0.693
| 9.19
|
Mykonos
|
Greece
|
Europe
| 17.64
| 19.01
| 1.37
| 0.68
| 19.33
|
Symi
|
Greece
|
Europe
| 18.64
| 20.01
| 1.36
| 0.676
| 20.31
|
Santiago
|
Chile
|
Americas
| 15.49
| 16.89
| 1.41
| 0.674
| 17.07
|
Istanbul
|
Turkey
|
Europe
| 14.46
| 15.77
| 1.31
| 0.673
| 16.18
|
Lyon
|
France
|
Europe
| 12.12
| 13.47
| 1.35
| 0.673
| 13.7
|
Helsinki
|
Finland
|
Europe
| 5.45
| 6.73
| 1.28
| 0.664
| 7.16
|
Budva
|
Montenegro
|
Europe
| 15.97
| 17.23
| 1.27
| 0.663
| 17.57
|
Ljubljana
|
Slovenia
|
Europe
| 10.08
| 11.34
| 1.25
| 0.663
| 11.74
|
Naxos
|
Greece
|
Europe
| 17.89
| 19.19
| 1.31
| 0.659
| 19.51
|
Zadar
|
Croatia
|
Europe
| 14.44
| 15.68
| 1.24
| 0.656
| 16.03
|
Gdańsk
|
Poland
|
Europe
| 8.49
| 9.83
| 1.34
| 0.652
| 10.12
|
Rome
|
Italy
|
Europe
| 15.44
| 16.7
| 1.27
| 0.652
| 16.97
|
Denver
|
United States
|
Americas
| 9.02
| 10.44
| 1.42
| 0.647
| 10.61
|
Matera
|
Italy
|
Europe
| 14.71
| 15.91
| 1.2
| 0.646
| 16.25
|
Sapporo
|
Japan
|
Asia
| 6.94
| 8.18
| 1.24
| 0.643
| 8.63
|
Kalambaka
|
Greece
|
Europe
| 14.53
| 15.81
| 1.27
| 0.636
| 16.18
|
Nagoya
|
Japan
|
Asia
| 14.8
| 16.09
| 1.29
| 0.634
| 16.28
|
Rhodes
|
Greece
|
Europe
| 18.94
| 20.2
| 1.26
| 0.634
| 20.5
|
Verona
|
Italy
|
Europe
| 13.34
| 14.59
| 1.25
| 0.63
| 14.85
|
Kuşadası
|
Turkey
|
Europe
| 17.98
| 19.28
| 1.29
| 0.629
| 19.61
|
Lucerne
|
Switzerland
|
Europe
| 9.89
| 11.15
| 1.25
| 0.629
| 11.37
|
Hamburg
|
Germany
|
Europe
| 9.36
| 10.65
| 1.29
| 0.627
| 10.95
|
Jerusalem
|
Israel
|
Asia
| 17.35
| 18.67
| 1.32
| 0.627
| 18.91
|
Quepos
|
Costa Rica
|
Americas
| 24.7
| 26.07
| 1.37
| 0.619
| 26.17
|
Zakynthos
|
Greece
|
Europe
| 18.38
| 19.54
| 1.16
| 0.618
| 19.86
|
Chongqing
|
China
|
Asia
| 17.47
| 18.75
| 1.29
| 0.617
| 19.03
|
Nafplio
|
Greece
|
Europe
| 17.79
| 19.01
| 1.22
| 0.615
| 19.34
|
Copenhagen
|
Denmark
|
Europe
| 8.6
| 9.83
| 1.23
| 0.614
| 10.1
|
Düsseldorf
|
Germany
|
Europe
| 10.44
| 11.72
| 1.27
| 0.613
| 11.94
|
Paris
|
France
|
Europe
| 11.53
| 12.69
| 1.16
| 0.61
| 12.91
|
Athens
|
Greece
|
Europe
| 17.44
| 18.61
| 1.16
| 0.608
| 18.94
|
Las Vegas
|
United States
|
Americas
| 19.71
| 21.02
| 1.31
| 0.608
| 21.14
|
End of preview. Expand
in Data Studio
Global Warming Prediction 2026: The Accelerating Heat of Our Cities
Dataset Summary
This dataset provides a quantitative analysis of warming trends across 473 major global urban centers and tourist destinations. It contains processed historical weather data spanning 30 years (1996–2025), used to predict temperature baselines for 2026.
The data was generated by the 30YearWeather research team using raw input from the NASA POWER Project and Open-Meteo (ERA5 Reanalysis).
- Full Research Report: Global Warming Prediction 2026: City-by-City Analysis
- Methodology: Ordinary Least Squares (OLS) linear regression on annual mean temperatures.
- Maintainer: 30YearWeather
Supported Tasks and Leaderboards
- Time Series Forecasting: Predicting future urban temperatures based on 30-year historical trends.
- Climatology Analysis: Analyzing the rate of warming (degrees per decade) across different continents and latitudes.
Data Structure
The dataset contains 473 rows with the following columns:
City: Name of the city (e.g., "Paris", "Tokyo").Country: Country of the destination.Continent: Geographical region.Avg Temp Start (1996): Baseline average temperature (°C) at the start of the analysis period.Avg Temp End (2025): Current average temperature (°C).Warming Rate (C/Decade): The calculated rate of warming per 10 years (slope * 10).Prediction 2026 (C): Projected annual mean temperature for 2026.
Citation
If you use this dataset, please cite the original research:
@article{30yearweather2026global,
title={Global Warming Prediction 2026: The Accelerating Heat of Our Cities},
author={Vesecký, Michal and 30YearWeather Research Team},
journal={30YearWeather Research},
year={2026},
url={[https://30yearweather.com/research/global-warming-prediction-2026](https://30yearweather.com/research/global-warming-prediction-2026)},
doi={10.5281/zenodo.18144475}
}
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