Introduction

Global climate indicators (for an overview see Trewin et al. 2021) provide a broad view of climate change at the largest scale, encompassing the composition of the atmosphere, energy changes, and the responses of the land, ocean, and ice. These indicators are closely related to one another. For example, the rise in CO₂ and other greenhouse gases in the atmosphere leads to an imbalance of energy and thus warming of the atmosphere and ocean. Warming of the ocean in turn leads to rising sea levels, to which is added the melting of ice on land in response to increasing atmospheric temperatures.

The global indicators draw on a wide range of data sets, which are listed at the bottom of the page. Differences between data sets for the same indicator indicate the degree of uncertainty in the indicator. Figures are updated monthly, with some data sets being updated more or less frequently.

Under each of the figures, you will find links to the images in multiple file formats (png, pdf and svg), as well as a set of data as shown in the figure in a common comma-separated values (csv) format. The "Read more" link will take you to a wider range of linked indicators.

Key messages

Dataset and processing details

Carbon dioxide

Carbon dioxide (CO₂) is one of the most important greenhouse gases. The concentration of CO₂ in the atmosphere is measured at stations around the world which are combined to provide a globally representative value.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Carbon_dioxide_data_files.zip
Checksum: 3bed378c3f537bc156f1337765cc8ab5 Copy
Format: BADC CSV format

Kennaook/Cape Grim

Original data file (external link)

Data citation: https://www.csiro.au/greenhouse-gases/

Acknowledgement: https://www.csiro.au/greenhouse-gases/ Data measured at the Kennaook / Cape Grim Baseline Air Pollution Station (KCGBAPS), located near the north-west tip of Tasmania, Australia. KCGBAPS is funded and managed by the Australian Bureau of Meteorology, and the scientific program is jointly supervised with CSIRO Oceans & Atmosphere

To produce the plot, the following processing steps were performed:

• Data set created from file ['CapeGrim_CO2_data_download.csv'] downloaded from ['https://capegrim.csiro.au/GreenhouseGas/data/CapeGrim_CO2_data_download.csv'] at ['2026-09-10 22:42:02']

Mauna Loa

Original data file (external link)

Citation:

• Keeling, C. D., Bacastow, R. B., Bainbridge, A. E., Ekdahl, C. A., Guenther, P. R., Waterman, L. S. and Chin, J. F. (1976), Atmospheric carbon dioxide variations at Mauna Loa Observatory, Hawaii. Tellus, 28: 538-551. doi:10.1111/j.2153-3490.1976.tb00701.x.

Acknowledgement: Dr. Pieter Tans, NOAA/ESRL (www.esrl.noaa.gov/gmd/ccgg/trends/) and Dr. Ralph Keeling, Scripps Institution of Oceanography (scrippsco2.ucsd.edu/).

To produce the plot, the following processing steps were performed:

• Data set created from file ['co2_mm_mlo.txt'] downloaded from ['ftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_mm_mlo.txt'] at ['2026-09-10 22:42:04']

WDCGG

Original data file (external link)

Citation:

• WMO Greenhouse Gas Bulletin, No.18, 2022. 26 October 2022 ISSN 2078-0796.

To produce the plot, the following processing steps were performed:

• Data set created from file ['co2_monthly_20251016.csv'] downloaded from ['https://gaw.kishou.go.jp/static/publications/global_mean_mole_fractions/2025/co2_monthly_20251016.csv'] at ['2025-10-17 10:10:38']

Methane

Methane (CH₄) is an important greenhouse gas. The concentration of CH₄ in the atmosphere is measured at stations around the world which are combined to provide a globally representative value.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Methane_data_files.zip
Checksum: 8b13e541f9bc93a720fa95d26fe9842e Copy
Format: BADC CSV format

Kennaook/Cape Grim

Original data file (external link)

Data citation: https://www.csiro.au/greenhouse-gases/

Acknowledgement: https://www.csiro.au/greenhouse-gases/ Data measured at the Kennaook / Cape Grim Baseline Air Pollution Station (KCGBAPS), located near the north-west tip of Tasmania, Australia. KCGBAPS is funded and managed by the Australian Bureau of Meteorology, and the scientific program is jointly supervised with CSIRO Oceans & Atmosphere

To produce the plot, the following processing steps were performed:

• Data set created from file ['CapeGrim_CH4_data_download.csv'] downloaded from ['https://capegrim.csiro.au/GreenhouseGas/data/CapeGrim_CH4_data_download.csv'] at ['2026-09-10 22:42:09']

NOAA

Original data file (external link)

Citation:

• Dlugokencky, E. J., L. P. Steele, P. M. Lang, and K. A. Masarie (1994), The growth rate and distribution of atmospheric methane, J. Geophys. Res., 99, 17,021– 17,043, doi:10.1029/94JD01245..

Data citation: Ed Dlugokencky, NOAA/ESRL (www.esrl.noaa.gov/gmd/ccgg/trends_ch4/)

Acknowledgement: Ed Dlugokencky, NOAA/ESRL (www.esrl.noaa.gov/gmd/ccgg/trends_ch4/)

To produce the plot, the following processing steps were performed:

• Data set created from file ['ch4_mm_gl.txt'] downloaded from ['ftp://aftp.cmdl.noaa.gov/products/trends/ch4/ch4_mm_gl.txt'] at ['2026-09-10 22:42:10']

WDCGG

Original data file (external link)

Citation:

• WMO Greenhouse Gas Bulletin, No.18, 2022. 26 October 2022 ISSN 2078-0796.

To produce the plot, the following processing steps were performed:

• Data set created from file ['ch4_monthly_20251016.csv'] downloaded from ['https://gaw.kishou.go.jp/static/publications/global_mean_mole_fractions/2025/ch4_monthly_20251016.csv'] at ['2025-10-17 10:10:26']

Nitrous Oxide

Nitrous oxide (N₂O) is an important greenhouse gas. The concentration of N₂O in the atmosphere is measured at stations around the world which are combined to provide a globally representative value.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Nitrous_Oxide_data_files.zip
Checksum: 36a17ba66ec77c4aeeaa093c7e04ee79 Copy
Format: BADC CSV format

Kennaook/Cape Grim

Original data file (external link)

Data citation: https://www.csiro.au/greenhouse-gases/

Acknowledgement: https://www.csiro.au/greenhouse-gases/ Data measured at the Kennaook / Cape Grim Baseline Air Pollution Station (KCGBAPS), located near the north-west tip of Tasmania, Australia. KCGBAPS is funded and managed by the Australian Bureau of Meteorology, and the scientific program is jointly supervised with CSIRO Oceans & Atmosphere

To produce the plot, the following processing steps were performed:

• Data set created from file ['CapeGrim_N2O_data_download.csv'] downloaded from ['https://capegrim.csiro.au/GreenhouseGas/data/CapeGrim_N2O_data_download.csv'] at ['2026-09-10 22:42:13']

WDCGG

Original data file (external link)

Citation:

• WMO Greenhouse Gas Bulletin, No.18, 2022. 26 October 2022 ISSN 2078-0796.

To produce the plot, the following processing steps were performed:

• Data set created from file ['n2o_monthly_20251016.csv'] downloaded from ['https://gaw.kishou.go.jp/static/publications/global_mean_mole_fractions/2025/n2o_monthly_20251016.csv'] at ['2025-10-17 10:10:48']

Daily global mean temperature

Global mean temperature is based on measurements made at weather stations over land and by ships and buoys over the ocean. Temperatures are typically expressed as anomalies which are temperature differences from the average for a standard period. Here, 1850-1900 is used for the global mean. Instrumental temperature records are some of the longest climate records available, with some series extending back to the 17th century.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Daily_global_mean_temperature_data_files.zip
Checksum: 34c08717cc3614191c9602d687f78e20 Copy
Format: BADC CSV format

ERA5

Original data file (external link) Original data file (external link)

Citation:

• Hersbach H, Bell B, Berrisford P et al. 2020. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146: 1999-2049. https://doi.org/10.1002/qj.3803.

Data citation: Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 (Accessed on 2026-09-11 11:49:37)

Acknowledgement: Contains using Copernicus Climate Change Service information [2026]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

To produce the plot, the following processing steps were performed:

• Data set created from file ['era5_daily_series_2t_global.csv', 'era5_daily_sfc_temp_global_anomalies_with_preindustrial_1940-2023.csv'] downloaded from ['https://sites.ecmwf.int/data/climatepulse/data/series/era5_daily_series_2t_global.csv', 'https://sites.ecmwf.int/data/c3sci/era5-daily/data/era5_daily_sfc_temp_global_anomalies_with_preindustrial_1940-2023.csv'] at ['2026-09-11 11:49:37']
• Time series expanded with NaN to include all days between 1940 and 2026

Monthly global temperature

Global mean temperature is based on measurements made at weather stations over land and by ships and buoys over the ocean. Temperatures are typically expressed as anomalies which are temperature differences from the average for a standard period. Here, 1850-1900 is used for the global mean. Instrumental temperature records are some of the longest climate records available, with some series extending back to the 17th century.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Monthly_global_temperature_data_files.zip
Checksum: 183c30455a45ec3e8461338bd5be437e Copy
Format: BADC CSV format

Berkeley Earth Hires

Original data file (external link)

Citation:

• Rohde, R. A. and Hausfather, Z.: The Berkeley Earth Land/Ocean Temperature Record, Earth Syst. Sci. Data, 12, 3469-3479, https://doi.org/10.5194/essd-12-3469-2020, 2020.

To produce the plot, the following processing steps were performed:

• Data set created from file ['Global_TAVG_monthly.txt'] downloaded from ['https://storage.googleapis.com/berkeley-earth-temperature-hr/global/Global_TAVG_monthly.txt'] at ['2026-09-10 22:39:16']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 2010 to 2026.

CMA-GMST

Citation:

• Chen, L., Xu, W., Zhou, Z. et al. A new global land–ocean merged surface temperature dataset since the 1850s: the CMA-GMST dataset. Clim Dyn 63, 187 (2025). https://doi.org/10.1007/s00382-025-07614-x.

Data citation: https://data.cma.cn/en/#/Visualization/Visualization-detail?id=16

To produce the plot, the following processing steps were performed:

• Data set created from file ['CMA-GMST_Global_Month_Temp_1981_2010.csv'] downloaded from [] at ['2026-09-11 14:39:28']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 2010 to 2026.

CMST

Original data file (external link)

Citation:

• Sun, W., Yang, Y., Chao, L., Dong, W., Huang, B., Jones, P., and Li, Q.: Description of the China global Merged Surface Temperature version 2.0, Earth Syst. Sci. Data, 14, 1677–1693, https://doi.org/10.5194/essd-14-1677-2022, 2022.

To produce the plot, the following processing steps were performed:

• Data set created from file ['CMST_monthly_2026.csv'] downloaded from ['http://www.gwpu.net/en/h-nd-166.html'] at ['2026-09-08 10:58:44']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 2010 to 2026.

COBE3

Original data file (external link)

Citation:

• ISHII, M., A. NISHIMURA, S. YASUI, S. HIRAHARA, Historical High-Resolution Daily SST Analysis (COBE-SST3) with Consistency to Monthly Land Surface Air Temperature, Journal of the Meteorological Society of Japan. Ser. II, 2025, Volume 103, Issue 1, Pages 17-44, https://doi.org/10.2151/jmsj.2025-002.

To produce the plot, the following processing steps were performed:

• Data set created from file ['gm_cobe-stemp3'] downloaded from ['https://climate.mri-jma.go.jp/pub/archives/Ishii-et-al_COBE-SST3/gm/gm_cobe-stemp3'] at ['2026-05-30 16:32:30']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 2010 to 2026.

DCENT-I

Original data file (external link)

Citations:

• Chan, D., Gebbie, G., Huybers, P. & Kent, E. C. DCENT: Dynamically Consistent ENsemble of Temperature at the Earth Surface. https://doi.org/10.7910/DVN/NU4UGW (2024)..
• Chan, D., Chan, S. C., Siddons, J. T., Cable, A., Cornes, R. C., Kent, E. C., Gebbie, G., & Huybers, P. DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset. https://doi.org/10.7910/DVN/ZY0WM8 (2025)..
• Chan D., Chan, S. C., Siddons, J. T., Cable, A., Cornes, R. C., Kent, E. C., Gebbie, G., & Huybers, P. (2025). DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset. Geoscience Data Journal..

To produce the plot, the following processing steps were performed:

• Data set created from file ['DCENT_DCENT_I_GMST_monthly_statistics_live.txt'] downloaded from ['https://dcent-i.github.io/'] at ['2026-08-13 14:01:27']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 2010 to 2026.

ERA5

Original data file (external link)

Citation:

• Hersbach H, Bell B, Berrisford P et al. 2020. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146: 1999-2049. https://doi.org/10.1002/qj.3803.

Data citation: Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 (Accessed on 2026-09-10 22:39:24)

Acknowledgement: Contains using Copernicus Climate Change Service information [2026]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

To produce the plot, the following processing steps were performed:

• Data set created from file ['C3S_Bulletin_temp_202608_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] downloaded from ['https://climate.copernicus.eu/sites/default/files/2026-MMMM/C3S_Bulletin_temp_YLYLMLML_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] at ['2026-09-10 22:39:24']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 2010 to 2026.

GISTEMP

Original data file (external link)

Citation:

• Lenssen, N., G. Schmidt, J. Hansen, M. Menne, A. Persin, R. Ruedy, and D. Zyss, 2019: Improvements in the GISTEMP uncertainty model. J. Geophys. Res. Atmos., 124, no. 12, 6307-6326, doi:10.1029/2018JD029522.

Data citation: GISTEMP Team, 2022: GISS Surface Temperature Analysis (GISTEMP), version 4. NASA Goddard Institute for Space Studies. Dataset accessed 2026-09-10 22:37:11 at data.giss.nasa.gov/gistemp/.

To produce the plot, the following processing steps were performed:

• Data set created from file ['GLB.Ts+dSST.csv'] downloaded from ['https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.csv'] at ['2026-09-10 22:37:11']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 2010 to 2026.

HadCRUT5

Original data file (external link) Original data file (external link)

Citation:

• Morice, C. P., Kennedy, J. J., Rayner, N. A., Winn, J. P., Hogan, E., Killick, R. E., et al. (2021). An updated assessment of near-surface temperature change from 1850: the HadCRUT5 data set. Journal of Geophysical Research: Atmospheres, 126, e2019JD032361. https://doi.org/10.1029/2019JD032361.

Acknowledgement: HadCRUT.5.1.0.0 data were obtained from http://www.metoffice.gov.uk/hadobs/hadcrut5 on 2026-09-10 22:39:29 and are © British Crown Copyright, Met Office 2026, provided under an Open Government License, http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

To produce the plot, the following processing steps were performed:

• Data set created from file ['HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] downloaded from ['https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.1.0.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.1.0.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] at ['2026-09-10 22:39:29', '2026-09-10 22:39:29']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 2010 to 2026.

JRA-3Q

Original data file (external link)

Citation:

• Kosaka, Y.; Kobayashi, S.; Harada, Y.; Kobayashi, C.; Naoe, H.; Yoshimoto, K.; Harada, M.; Goto, N.; Chiba, J.; Miyaoka, K.; Sekiguchi, R.; Deushi, M.; Kamahori, H.; Nakaegawa, T.; Tanaka, T. Y.; Tokuhiro, T.; Sato, Y.; Matsushita, Y.; Onogi, K. The JRA-3Q Reanalysis. J. Meteorol. Soc. Jpn. Ser II 2024, 102 (1), 49–109. https://doi.org/10.2151/jmsj.2024-004.

Data citation: Japan Meteorological Agency. 2023, updated monthly. Japanese Reanalysis for Three Quarters of a Century (JRA-3Q). Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/AVTZ-1H78. Accessed 2026-08-14 11:44:49.

To produce the plot, the following processing steps were performed:

• Data set created from file ['JRA-3Q_tmp2m_global_ts_125_Clim9120.txt'] downloaded from [''] at ['2026-08-14 11:44:49']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 2010 to 2026.

NOAAGlobalTemp v6.1

Original data file (external link) Original data file (external link)

Citation:

• Yin, X., and Coauthors, 2024: NOAAGlobalTemp Version 6: An AI-Based Global Surface Temperature Dataset. Bull. Amer. Meteor. Soc., 105, E2184–E2193, https://doi.org/10.1175/BAMS-D-24-0012.1..

Data citation: Huang, Boyin; Yin, Xungang; Menne, Matthew J.; Vose, Russell S.; and Zhang, Huai-Min. 2024. NOAA Global Surface Temperature Dataset (NOAAGlobalTemp), Version 6.0.. NOAA National Centers for Environmental Information. https://doi.org/10.25921/rzxg-p717. Accessed 2026-09-11 17:00:20.

To produce the plot, the following processing steps were performed:

• Data set created from file ['aravg.mon.land_ocean.90S.90N.v6.1.0.202608.asc', 'aravg.ann.land_ocean.90S.90N.*.asc'] downloaded from ['https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.mon.land_ocean.90S.90N.v6.1.0.202608.asc', 'https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.ann.land_ocean.90S.90N.*.asc'] at ['2026-09-11 17:00:20']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 2010 to 2026.

Global 12-month temperature

Global mean temperature is based on measurements made at weather stations over land and by ships and buoys over the ocean. Temperatures are typically expressed as anomalies which are temperature differences from the average for a standard period. Here, 1850-1900 is used for the global mean. Instrumental temperature records are some of the longest climate records available, with some series extending back to the 17th century.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Global_12-month_temperature_data_files.zip
Checksum: 567e2a2eaa0ce8fc54ecaf9907515085 Copy
Format: BADC CSV format

Berkeley Earth Hires

Original data file (external link)

Citation:

• Rohde, R. A. and Hausfather, Z.: The Berkeley Earth Land/Ocean Temperature Record, Earth Syst. Sci. Data, 12, 3469-3479, https://doi.org/10.5194/essd-12-3469-2020, 2020.

To produce the plot, the following processing steps were performed:

• Data set created from file ['Global_TAVG_monthly.txt'] downloaded from ['https://storage.googleapis.com/berkeley-earth-temperature-hr/global/Global_TAVG_monthly.txt'] at ['2026-09-10 22:39:16']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Calculated 12-month trailing moving average
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 1970 to 2026.

CMA-GMST

Citation:

• Chen, L., Xu, W., Zhou, Z. et al. A new global land–ocean merged surface temperature dataset since the 1850s: the CMA-GMST dataset. Clim Dyn 63, 187 (2025). https://doi.org/10.1007/s00382-025-07614-x.

Data citation: https://data.cma.cn/en/#/Visualization/Visualization-detail?id=16

To produce the plot, the following processing steps were performed:

• Data set created from file ['CMA-GMST_Global_Month_Temp_1981_2010.csv'] downloaded from [] at ['2026-09-11 14:39:28']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Calculated 12-month trailing moving average
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 1970 to 2026.

CMST

Original data file (external link)

Citation:

• Sun, W., Yang, Y., Chao, L., Dong, W., Huang, B., Jones, P., and Li, Q.: Description of the China global Merged Surface Temperature version 2.0, Earth Syst. Sci. Data, 14, 1677–1693, https://doi.org/10.5194/essd-14-1677-2022, 2022.

To produce the plot, the following processing steps were performed:

• Data set created from file ['CMST_monthly_2026.csv'] downloaded from ['http://www.gwpu.net/en/h-nd-166.html'] at ['2026-09-08 10:58:44']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Calculated 12-month trailing moving average
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 1970 to 2026.

COBE3

Original data file (external link)

Citation:

• ISHII, M., A. NISHIMURA, S. YASUI, S. HIRAHARA, Historical High-Resolution Daily SST Analysis (COBE-SST3) with Consistency to Monthly Land Surface Air Temperature, Journal of the Meteorological Society of Japan. Ser. II, 2025, Volume 103, Issue 1, Pages 17-44, https://doi.org/10.2151/jmsj.2025-002.

To produce the plot, the following processing steps were performed:

• Data set created from file ['gm_cobe-stemp3'] downloaded from ['https://climate.mri-jma.go.jp/pub/archives/Ishii-et-al_COBE-SST3/gm/gm_cobe-stemp3'] at ['2026-05-30 16:32:30']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Calculated 12-month trailing moving average
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 1970 to 2026.

DCENT-I

Original data file (external link)

Citations:

• Chan, D., Gebbie, G., Huybers, P. & Kent, E. C. DCENT: Dynamically Consistent ENsemble of Temperature at the Earth Surface. https://doi.org/10.7910/DVN/NU4UGW (2024)..
• Chan, D., Chan, S. C., Siddons, J. T., Cable, A., Cornes, R. C., Kent, E. C., Gebbie, G., & Huybers, P. DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset. https://doi.org/10.7910/DVN/ZY0WM8 (2025)..
• Chan D., Chan, S. C., Siddons, J. T., Cable, A., Cornes, R. C., Kent, E. C., Gebbie, G., & Huybers, P. (2025). DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset. Geoscience Data Journal..

To produce the plot, the following processing steps were performed:

• Data set created from file ['DCENT_DCENT_I_GMST_monthly_statistics_live.txt'] downloaded from ['https://dcent-i.github.io/'] at ['2026-08-13 14:01:27']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Calculated 12-month trailing moving average
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 1970 to 2026.

ERA5

Original data file (external link)

Citation:

• Hersbach H, Bell B, Berrisford P et al. 2020. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146: 1999-2049. https://doi.org/10.1002/qj.3803.

Data citation: Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 (Accessed on 2026-09-10 22:39:24)

Acknowledgement: Contains using Copernicus Climate Change Service information [2026]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

To produce the plot, the following processing steps were performed:

• Data set created from file ['C3S_Bulletin_temp_202608_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] downloaded from ['https://climate.copernicus.eu/sites/default/files/2026-MMMM/C3S_Bulletin_temp_YLYLMLML_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] at ['2026-09-10 22:39:24']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Calculated 12-month trailing moving average
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 1970 to 2026.

GISTEMP

Original data file (external link)

Citation:

• Lenssen, N., G. Schmidt, J. Hansen, M. Menne, A. Persin, R. Ruedy, and D. Zyss, 2019: Improvements in the GISTEMP uncertainty model. J. Geophys. Res. Atmos., 124, no. 12, 6307-6326, doi:10.1029/2018JD029522.

Data citation: GISTEMP Team, 2022: GISS Surface Temperature Analysis (GISTEMP), version 4. NASA Goddard Institute for Space Studies. Dataset accessed 2026-09-10 22:37:11 at data.giss.nasa.gov/gistemp/.

To produce the plot, the following processing steps were performed:

• Data set created from file ['GLB.Ts+dSST.csv'] downloaded from ['https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.csv'] at ['2026-09-10 22:37:11']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Calculated 12-month trailing moving average
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 1970 to 2026.

HadCRUT5

Original data file (external link) Original data file (external link)

Citation:

• Morice, C. P., Kennedy, J. J., Rayner, N. A., Winn, J. P., Hogan, E., Killick, R. E., et al. (2021). An updated assessment of near-surface temperature change from 1850: the HadCRUT5 data set. Journal of Geophysical Research: Atmospheres, 126, e2019JD032361. https://doi.org/10.1029/2019JD032361.

Acknowledgement: HadCRUT.5.1.0.0 data were obtained from http://www.metoffice.gov.uk/hadobs/hadcrut5 on 2026-09-10 22:39:29 and are © British Crown Copyright, Met Office 2026, provided under an Open Government License, http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

To produce the plot, the following processing steps were performed:

• Data set created from file ['HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] downloaded from ['https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.1.0.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.1.0.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] at ['2026-09-10 22:39:29', '2026-09-10 22:39:29']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Calculated 12-month trailing moving average
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 1970 to 2026.

JRA-3Q

Original data file (external link)

Citation:

• Kosaka, Y.; Kobayashi, S.; Harada, Y.; Kobayashi, C.; Naoe, H.; Yoshimoto, K.; Harada, M.; Goto, N.; Chiba, J.; Miyaoka, K.; Sekiguchi, R.; Deushi, M.; Kamahori, H.; Nakaegawa, T.; Tanaka, T. Y.; Tokuhiro, T.; Sato, Y.; Matsushita, Y.; Onogi, K. The JRA-3Q Reanalysis. J. Meteorol. Soc. Jpn. Ser II 2024, 102 (1), 49–109. https://doi.org/10.2151/jmsj.2024-004.

Data citation: Japan Meteorological Agency. 2023, updated monthly. Japanese Reanalysis for Three Quarters of a Century (JRA-3Q). Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/AVTZ-1H78. Accessed 2026-08-14 11:44:49.

To produce the plot, the following processing steps were performed:

• Data set created from file ['JRA-3Q_tmp2m_global_ts_125_Clim9120.txt'] downloaded from [''] at ['2026-08-14 11:44:49']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Calculated 12-month trailing moving average
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 1970 to 2026.

NOAAGlobalTemp v6.1

Original data file (external link) Original data file (external link)

Citation:

• Yin, X., and Coauthors, 2024: NOAAGlobalTemp Version 6: An AI-Based Global Surface Temperature Dataset. Bull. Amer. Meteor. Soc., 105, E2184–E2193, https://doi.org/10.1175/BAMS-D-24-0012.1..

Data citation: Huang, Boyin; Yin, Xungang; Menne, Matthew J.; Vose, Russell S.; and Zhang, Huai-Min. 2024. NOAA Global Surface Temperature Dataset (NOAAGlobalTemp), Version 6.0.. NOAA National Centers for Environmental Information. https://doi.org/10.25921/rzxg-p717. Accessed 2026-09-11 17:00:20.

To produce the plot, the following processing steps were performed:

• Data set created from file ['aravg.mon.land_ocean.90S.90N.v6.1.0.202608.asc', 'aravg.ann.land_ocean.90S.90N.*.asc'] downloaded from ['https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.mon.land_ocean.90S.90N.v6.1.0.202608.asc', 'https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.ann.land_ocean.90S.90N.*.asc'] at ['2026-09-11 17:00:20']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Calculated 12-month trailing moving average
• Added offset of 0.69 to all data values.
• Manually changed baseline to 1850-1900. Note that data values remain unchanged.
• Selected years within the range 1970 to 2026.

Global temperature average year-to-date

Global mean temperature is based on measurements made at weather stations over land and by ships and buoys over the ocean. Temperatures are typically expressed as anomalies which are temperature differences from the average for a standard period. Here, 1850-1900 is used for the global mean. Instrumental temperature records are some of the longest climate records available, with some series extending back to the 17th century.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Global_temperature_average_year-to-date_data_files.zip
Checksum: 37191449a6764b5de91481b8e3277cca Copy
Format: BADC CSV format

Berkeley Earth Hires

Original data file (external link)

Citation:

• Rohde, R. A. and Hausfather, Z.: The Berkeley Earth Land/Ocean Temperature Record, Earth Syst. Sci. Data, 12, 3469-3479, https://doi.org/10.5194/essd-12-3469-2020, 2020.

To produce the plot, the following processing steps were performed:

• Data set created from file ['Global_TAVG_monthly.txt'] downloaded from ['https://storage.googleapis.com/berkeley-earth-temperature-hr/global/Global_TAVG_monthly.txt'] at ['2026-09-10 22:39:16']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

CMA-GMST

Citation:

• Chen, L., Xu, W., Zhou, Z. et al. A new global land–ocean merged surface temperature dataset since the 1850s: the CMA-GMST dataset. Clim Dyn 63, 187 (2025). https://doi.org/10.1007/s00382-025-07614-x.

Data citation: https://data.cma.cn/en/#/Visualization/Visualization-detail?id=16

To produce the plot, the following processing steps were performed:

• Data set created from file ['CMA-GMST_Global_Month_Temp_1981_2010.csv'] downloaded from [] at ['2026-09-11 14:39:28']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

CMST

Original data file (external link)

Citation:

• Sun, W., Yang, Y., Chao, L., Dong, W., Huang, B., Jones, P., and Li, Q.: Description of the China global Merged Surface Temperature version 2.0, Earth Syst. Sci. Data, 14, 1677–1693, https://doi.org/10.5194/essd-14-1677-2022, 2022.

To produce the plot, the following processing steps were performed:

• Data set created from file ['CMST_monthly_2026.csv'] downloaded from ['http://www.gwpu.net/en/h-nd-166.html'] at ['2026-09-08 10:58:44']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

COBE3

Original data file (external link)

Citation:

• ISHII, M., A. NISHIMURA, S. YASUI, S. HIRAHARA, Historical High-Resolution Daily SST Analysis (COBE-SST3) with Consistency to Monthly Land Surface Air Temperature, Journal of the Meteorological Society of Japan. Ser. II, 2025, Volume 103, Issue 1, Pages 17-44, https://doi.org/10.2151/jmsj.2025-002.

To produce the plot, the following processing steps were performed:

• Data set created from file ['gm_cobe-stemp3'] downloaded from ['https://climate.mri-jma.go.jp/pub/archives/Ishii-et-al_COBE-SST3/gm/gm_cobe-stemp3'] at ['2026-05-30 16:32:30']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

DCENT-I

Original data file (external link)

Citations:

• Chan, D., Gebbie, G., Huybers, P. & Kent, E. C. DCENT: Dynamically Consistent ENsemble of Temperature at the Earth Surface. https://doi.org/10.7910/DVN/NU4UGW (2024)..
• Chan, D., Chan, S. C., Siddons, J. T., Cable, A., Cornes, R. C., Kent, E. C., Gebbie, G., & Huybers, P. DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset. https://doi.org/10.7910/DVN/ZY0WM8 (2025)..
• Chan D., Chan, S. C., Siddons, J. T., Cable, A., Cornes, R. C., Kent, E. C., Gebbie, G., & Huybers, P. (2025). DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset. Geoscience Data Journal..

To produce the plot, the following processing steps were performed:

• Data set created from file ['DCENT_DCENT_I_GMST_monthly_statistics_live.txt'] downloaded from ['https://dcent-i.github.io/'] at ['2026-08-13 14:01:27']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

ERA5

Original data file (external link)

Citation:

• Hersbach H, Bell B, Berrisford P et al. 2020. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146: 1999-2049. https://doi.org/10.1002/qj.3803.

Data citation: Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 (Accessed on 2026-09-10 22:39:24)

Acknowledgement: Contains using Copernicus Climate Change Service information [2026]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

To produce the plot, the following processing steps were performed:

• Data set created from file ['C3S_Bulletin_temp_202608_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] downloaded from ['https://climate.copernicus.eu/sites/default/files/2026-MMMM/C3S_Bulletin_temp_YLYLMLML_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] at ['2026-09-10 22:39:24']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

GISTEMP

Original data file (external link)

Citation:

• Lenssen, N., G. Schmidt, J. Hansen, M. Menne, A. Persin, R. Ruedy, and D. Zyss, 2019: Improvements in the GISTEMP uncertainty model. J. Geophys. Res. Atmos., 124, no. 12, 6307-6326, doi:10.1029/2018JD029522.

Data citation: GISTEMP Team, 2022: GISS Surface Temperature Analysis (GISTEMP), version 4. NASA Goddard Institute for Space Studies. Dataset accessed 2026-09-10 22:37:11 at data.giss.nasa.gov/gistemp/.

To produce the plot, the following processing steps were performed:

• Data set created from file ['GLB.Ts+dSST.csv'] downloaded from ['https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.csv'] at ['2026-09-10 22:37:11']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

HadCRUT5

Original data file (external link) Original data file (external link)

Citation:

• Morice, C. P., Kennedy, J. J., Rayner, N. A., Winn, J. P., Hogan, E., Killick, R. E., et al. (2021). An updated assessment of near-surface temperature change from 1850: the HadCRUT5 data set. Journal of Geophysical Research: Atmospheres, 126, e2019JD032361. https://doi.org/10.1029/2019JD032361.

Acknowledgement: HadCRUT.5.1.0.0 data were obtained from http://www.metoffice.gov.uk/hadobs/hadcrut5 on 2026-09-10 22:39:29 and are © British Crown Copyright, Met Office 2026, provided under an Open Government License, http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

To produce the plot, the following processing steps were performed:

• Data set created from file ['HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] downloaded from ['https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.1.0.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.1.0.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] at ['2026-09-10 22:39:29', '2026-09-10 22:39:29']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

JRA-3Q

Original data file (external link)

Citation:

• Kosaka, Y.; Kobayashi, S.; Harada, Y.; Kobayashi, C.; Naoe, H.; Yoshimoto, K.; Harada, M.; Goto, N.; Chiba, J.; Miyaoka, K.; Sekiguchi, R.; Deushi, M.; Kamahori, H.; Nakaegawa, T.; Tanaka, T. Y.; Tokuhiro, T.; Sato, Y.; Matsushita, Y.; Onogi, K. The JRA-3Q Reanalysis. J. Meteorol. Soc. Jpn. Ser II 2024, 102 (1), 49–109. https://doi.org/10.2151/jmsj.2024-004.

Data citation: Japan Meteorological Agency. 2023, updated monthly. Japanese Reanalysis for Three Quarters of a Century (JRA-3Q). Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/AVTZ-1H78. Accessed 2026-08-14 11:44:49.

To produce the plot, the following processing steps were performed:

• Data set created from file ['JRA-3Q_tmp2m_global_ts_125_Clim9120.txt'] downloaded from [''] at ['2026-08-14 11:44:49']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

NOAAGlobalTemp v6.1

Original data file (external link) Original data file (external link)

Citation:

• Yin, X., and Coauthors, 2024: NOAAGlobalTemp Version 6: An AI-Based Global Surface Temperature Dataset. Bull. Amer. Meteor. Soc., 105, E2184–E2193, https://doi.org/10.1175/BAMS-D-24-0012.1..

Data citation: Huang, Boyin; Yin, Xungang; Menne, Matthew J.; Vose, Russell S.; and Zhang, Huai-Min. 2024. NOAA Global Surface Temperature Dataset (NOAAGlobalTemp), Version 6.0.. NOAA National Centers for Environmental Information. https://doi.org/10.25921/rzxg-p717. Accessed 2026-09-11 17:00:20.

To produce the plot, the following processing steps were performed:

• Data set created from file ['aravg.mon.land_ocean.90S.90N.v6.1.0.202608.asc', 'aravg.ann.land_ocean.90S.90N.*.asc'] downloaded from ['https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.mon.land_ocean.90S.90N.v6.1.0.202608.asc', 'https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.ann.land_ocean.90S.90N.*.asc'] at ['2026-09-11 17:00:20']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

Global temperature year by year comparison

Global mean temperature is based on measurements made at weather stations over land and by ships and buoys over the ocean. Temperatures are typically expressed as anomalies which are temperature differences from the average for a standard period. Here, 1850-1900 is used for the global mean. Instrumental temperature records are some of the longest climate records available, with some series extending back to the 17th century.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Global_temperature_year_by_year_comparison_data_files.zip
Checksum: 21e8052a61b8762519750a10ae1bcfbc Copy
Format: BADC CSV format

Berkeley Earth Hires

Original data file (external link)

Citation:

• Rohde, R. A. and Hausfather, Z.: The Berkeley Earth Land/Ocean Temperature Record, Earth Syst. Sci. Data, 12, 3469-3479, https://doi.org/10.5194/essd-12-3469-2020, 2020.

To produce the plot, the following processing steps were performed:

• Data set created from file ['Global_TAVG_monthly.txt'] downloaded from ['https://storage.googleapis.com/berkeley-earth-temperature-hr/global/Global_TAVG_monthly.txt'] at ['2026-09-10 22:39:16']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

CMA-GMST

Citation:

• Chen, L., Xu, W., Zhou, Z. et al. A new global land–ocean merged surface temperature dataset since the 1850s: the CMA-GMST dataset. Clim Dyn 63, 187 (2025). https://doi.org/10.1007/s00382-025-07614-x.

Data citation: https://data.cma.cn/en/#/Visualization/Visualization-detail?id=16

To produce the plot, the following processing steps were performed:

• Data set created from file ['CMA-GMST_Global_Month_Temp_1981_2010.csv'] downloaded from [] at ['2026-09-11 14:39:28']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

CMST

Original data file (external link)

Citation:

• Sun, W., Yang, Y., Chao, L., Dong, W., Huang, B., Jones, P., and Li, Q.: Description of the China global Merged Surface Temperature version 2.0, Earth Syst. Sci. Data, 14, 1677–1693, https://doi.org/10.5194/essd-14-1677-2022, 2022.

To produce the plot, the following processing steps were performed:

• Data set created from file ['CMST_monthly_2026.csv'] downloaded from ['http://www.gwpu.net/en/h-nd-166.html'] at ['2026-09-08 10:58:44']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

COBE3

Original data file (external link)

Citation:

• ISHII, M., A. NISHIMURA, S. YASUI, S. HIRAHARA, Historical High-Resolution Daily SST Analysis (COBE-SST3) with Consistency to Monthly Land Surface Air Temperature, Journal of the Meteorological Society of Japan. Ser. II, 2025, Volume 103, Issue 1, Pages 17-44, https://doi.org/10.2151/jmsj.2025-002.

To produce the plot, the following processing steps were performed:

• Data set created from file ['gm_cobe-stemp3'] downloaded from ['https://climate.mri-jma.go.jp/pub/archives/Ishii-et-al_COBE-SST3/gm/gm_cobe-stemp3'] at ['2026-05-30 16:32:30']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

DCENT-I

Original data file (external link)

Citations:

• Chan, D., Gebbie, G., Huybers, P. & Kent, E. C. DCENT: Dynamically Consistent ENsemble of Temperature at the Earth Surface. https://doi.org/10.7910/DVN/NU4UGW (2024)..
• Chan, D., Chan, S. C., Siddons, J. T., Cable, A., Cornes, R. C., Kent, E. C., Gebbie, G., & Huybers, P. DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset. https://doi.org/10.7910/DVN/ZY0WM8 (2025)..
• Chan D., Chan, S. C., Siddons, J. T., Cable, A., Cornes, R. C., Kent, E. C., Gebbie, G., & Huybers, P. (2025). DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset. Geoscience Data Journal..

To produce the plot, the following processing steps were performed:

• Data set created from file ['DCENT_DCENT_I_GMST_monthly_statistics_live.txt'] downloaded from ['https://dcent-i.github.io/'] at ['2026-08-13 14:01:27']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

ERA5

Original data file (external link)

Citation:

• Hersbach H, Bell B, Berrisford P et al. 2020. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146: 1999-2049. https://doi.org/10.1002/qj.3803.

Data citation: Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 (Accessed on 2026-09-10 22:39:24)

Acknowledgement: Contains using Copernicus Climate Change Service information [2026]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

To produce the plot, the following processing steps were performed:

• Data set created from file ['C3S_Bulletin_temp_202608_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] downloaded from ['https://climate.copernicus.eu/sites/default/files/2026-MMMM/C3S_Bulletin_temp_YLYLMLML_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] at ['2026-09-10 22:39:24']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

GISTEMP

Original data file (external link)

Citation:

• Lenssen, N., G. Schmidt, J. Hansen, M. Menne, A. Persin, R. Ruedy, and D. Zyss, 2019: Improvements in the GISTEMP uncertainty model. J. Geophys. Res. Atmos., 124, no. 12, 6307-6326, doi:10.1029/2018JD029522.

Data citation: GISTEMP Team, 2022: GISS Surface Temperature Analysis (GISTEMP), version 4. NASA Goddard Institute for Space Studies. Dataset accessed 2026-09-10 22:37:11 at data.giss.nasa.gov/gistemp/.

To produce the plot, the following processing steps were performed:

• Data set created from file ['GLB.Ts+dSST.csv'] downloaded from ['https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.csv'] at ['2026-09-10 22:37:11']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

HadCRUT5

Original data file (external link) Original data file (external link)

Citation:

• Morice, C. P., Kennedy, J. J., Rayner, N. A., Winn, J. P., Hogan, E., Killick, R. E., et al. (2021). An updated assessment of near-surface temperature change from 1850: the HadCRUT5 data set. Journal of Geophysical Research: Atmospheres, 126, e2019JD032361. https://doi.org/10.1029/2019JD032361.

Acknowledgement: HadCRUT.5.1.0.0 data were obtained from http://www.metoffice.gov.uk/hadobs/hadcrut5 on 2026-09-10 22:39:29 and are © British Crown Copyright, Met Office 2026, provided under an Open Government License, http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

To produce the plot, the following processing steps were performed:

• Data set created from file ['HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] downloaded from ['https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.1.0.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.1.0.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] at ['2026-09-10 22:39:29', '2026-09-10 22:39:29']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

JRA-3Q

Original data file (external link)

Citation:

• Kosaka, Y.; Kobayashi, S.; Harada, Y.; Kobayashi, C.; Naoe, H.; Yoshimoto, K.; Harada, M.; Goto, N.; Chiba, J.; Miyaoka, K.; Sekiguchi, R.; Deushi, M.; Kamahori, H.; Nakaegawa, T.; Tanaka, T. Y.; Tokuhiro, T.; Sato, Y.; Matsushita, Y.; Onogi, K. The JRA-3Q Reanalysis. J. Meteorol. Soc. Jpn. Ser II 2024, 102 (1), 49–109. https://doi.org/10.2151/jmsj.2024-004.

Data citation: Japan Meteorological Agency. 2023, updated monthly. Japanese Reanalysis for Three Quarters of a Century (JRA-3Q). Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/AVTZ-1H78. Accessed 2026-08-14 11:44:49.

To produce the plot, the following processing steps were performed:

• Data set created from file ['JRA-3Q_tmp2m_global_ts_125_Clim9120.txt'] downloaded from [''] at ['2026-08-14 11:44:49']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

NOAAGlobalTemp v6.1

Original data file (external link) Original data file (external link)

Citation:

• Yin, X., and Coauthors, 2024: NOAAGlobalTemp Version 6: An AI-Based Global Surface Temperature Dataset. Bull. Amer. Meteor. Soc., 105, E2184–E2193, https://doi.org/10.1175/BAMS-D-24-0012.1..

Data citation: Huang, Boyin; Yin, Xungang; Menne, Matthew J.; Vose, Russell S.; and Zhang, Huai-Min. 2024. NOAA Global Surface Temperature Dataset (NOAAGlobalTemp), Version 6.0.. NOAA National Centers for Environmental Information. https://doi.org/10.25921/rzxg-p717. Accessed 2026-09-11 17:00:20.

To produce the plot, the following processing steps were performed:

• Data set created from file ['aravg.mon.land_ocean.90S.90N.v6.1.0.202608.asc', 'aravg.ann.land_ocean.90S.90N.*.asc'] downloaded from ['https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.mon.land_ocean.90S.90N.v6.1.0.202608.asc', 'https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.ann.land_ocean.90S.90N.*.asc'] at ['2026-09-11 17:00:20']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

Monthly global sea-surface temperature

Sea-surface temperature (SST) is the temperature of the surface ocean, typically measured in the upper metre, or metres of the ocean, by ships, buoys and satellites.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Monthly_global_sea-surface_temperature_data_files.zip
Checksum: 60c5774de4aaa53910a280e559549de9 Copy
Format: BADC CSV format

COBE SST 3

Original data file (external link)

Citation:

• ISHII, M., A. NISHIMURA, S. YASUI, S. HIRAHARA, Historical High-Resolution Daily SST Analysis (COBE-SST3) with Consistency to Monthly Land Surface Air Temperature, Journal of the Meteorological Society of Japan. Ser. II, 2025, Volume 103, Issue 1, Pages 17-44, https://doi.org/10.2151/jmsj.2025-002.

To produce the plot, the following processing steps were performed:

• Data set created from file ['gm_cobe-sst3'] downloaded from ['https://climate.mri-jma.go.jp/pub/archives/Ishii-et-al_COBE-SST3/gm/gm_cobe-sst3'] at ['2025-06-20 17:02:44']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Selected years within the range 2010 to 2026.

DCENT-I

Original data file (external link)

Citations:

• Chan, D., Gebbie, G., Huybers, P. & Kent, E. C. DCENT: Dynamically Consistent ENsemble of Temperature at the Earth Surface. https://doi.org/10.7910/DVN/NU4UGW (2024)..
• Chan, D., Chan, S. C., Siddons, J. T., Cable, A., Cornes, R. C., Kent, E. C., Gebbie, G., & Huybers, P. DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset. https://doi.org/10.7910/DVN/ZY0WM8 (2025)..
• Chan D., Chan, S. C., Siddons, J. T., Cable, A., Cornes, R. C., Kent, E. C., Gebbie, G., & Huybers, P. (2025). DCENT-I: A Globally Infilled Extension of the Dynamically Consistent ENsemble of Temperature Dataset. Geoscience Data Journal..

To produce the plot, the following processing steps were performed:

• Data set created from file ['DCENT_DCENT_I_OST_monthly_statistics_live.txt'] downloaded from ['https://dcent-i.github.io/'] at ['2026-08-13 14:10:46']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Selected years within the range 2010 to 2026.

ERSST

Original data file (external link) Original data file (external link)

Citation:

• Huang, B., Peter W. Thorne, et. al, 2017: Extended Reconstructed Sea Surface Temperature version 5 (ERSSTv5), Upgrades, validations, and intercomparisons. J. Climate, doi: 10.1175/JCLI-D-16-0836.1.

Data citation: Boyin Huang, Peter W. Thorne, Viva F. Banzon, Tim Boyer, Gennady Chepurin, Jay H. Lawrimore, Matthew J. Menne, Thomas M. Smith, Russell S. Vose, and Huai-Min Zhang (2017): NOAA Extended Reconstructed Sea Surface Temperature (ERSST), Version 5. [indicate subset used]. NOAA National Centers for Environmental Information. doi:10.7289/V5T72FNM [2026-09-10 22:40:41].

To produce the plot, the following processing steps were performed:

• Data set created from file ['aravg.mon.ocean.90S.90N.v6.1.0.2026MMMM.asc', 'aravg.ann.ocean.90S.90N.v6.1.0.2026MMMM.asc'] downloaded from ['https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.mon.ocean.90S.90N.v6.1.0.2026MMMM.asc', 'https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6.1/access/timeseries/aravg.ann.ocean.90S.90N.v6.1.0.2026MMMM.asc'] at ['2026-09-10 22:40:41']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Selected years within the range 2010 to 2026.

HadSST4

Original data file (external link) Original data file (external link)

Citation:

• Kennedy, J. J., Rayner, N. A., Atkinson, C. P., and Killick, R. E. (2019). An ensemble data set of sea-surface temperature change from 1850: the Met Office Hadley Centre HadSST.4.0.0.0 data set. Journal of Geophysical Research: Atmospheres, 124. https://doi.org/10.1029/2018JD029867.

Acknowledgement: HadSST.4.2.0.0 data were obtained from http://www.metoffice.gov.uk/hadobs/hadsst4 on 2026-09-10 22:41:00 and are © British Crown Copyright, Met Office 2026, provided under an Open Government License, http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/

To produce the plot, the following processing steps were performed:

• Data set created from file ['HadSST.4.2.0.0_monthly_GLOBE.csv', 'HadSST.4.2.0.0_annual_GLOBE.csv'] downloaded from ['https://www.metoffice.gov.uk/hadobs/hadsst4/data/data/HadSST.4.2.0.0_monthly_GLOBE.csv', 'https://www.metoffice.gov.uk/hadobs/hadsst4/data/data/HadSST.4.2.0.0_annual_GLOBE.csv'] at ['2026-09-10 22:41:00', '2026-09-10 22:41:00']
• Rebaselined to 1981-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Selected years within the range 2010 to 2026.

Temperature Anomalies

Global mean temperature is based on measurements made at weather stations over land and by ships and buoys over the ocean. Temperatures are typically expressed as anomalies which are temperature differences from the average for a standard period. Here, 1850-1900 is used for the global mean. Instrumental temperature records are some of the longest climate records available, with some series extending back to the 17th century.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Temperature_Anomalies_data_files.zip
Checksum: 76cdb2bad9582d23c1f6f4d868218d6c Copy
Format: BADC CSV format

ERA5

Original data file (external link)

Citation:

• Hersbach H, Bell B, Berrisford P et al. 2020. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146: 1999-2049. https://doi.org/10.1002/qj.3803.

Data citation: Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 (Accessed on AAAA)

Acknowledgement: Contains using Copernicus Climate Change Service information [YYYY]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

To produce the plot, the following processing steps were performed:

• Gridded dataset created from file ['era5_2m_tas_YYYY.nc'] downloaded from ['']
• Rebaselined to 1991-2020
• Selected single month 08/2026

Seasonal Temperature Anomalies

Global mean temperature is based on measurements made at weather stations over land and by ships and buoys over the ocean. Temperatures are typically expressed as anomalies which are temperature differences from the average for a standard period. Here, 1850-1900 is used for the global mean. Instrumental temperature records are some of the longest climate records available, with some series extending back to the 17th century.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Seasonal_Temperature_Anomalies_data_files.zip
Checksum: 76cdb2bad9582d23c1f6f4d868218d6c Copy
Format: BADC CSV format

ERA5

Original data file (external link)

Citation:

• Hersbach H, Bell B, Berrisford P et al. 2020. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146: 1999-2049. https://doi.org/10.1002/qj.3803.

Data citation: Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 (Accessed on AAAA)

Acknowledgement: Contains using Copernicus Climate Change Service information [YYYY]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

To produce the plot, the following processing steps were performed:

• Gridded dataset created from file ['era5_2m_tas_YYYY.nc'] downloaded from ['']
• Rebaselined to 1991-2020
• Selected period from 06/2026 to 08/2026
• Calculated time mean

Annual Temperature Anomalies

Global mean temperature is based on measurements made at weather stations over land and by ships and buoys over the ocean. Temperatures are typically expressed as anomalies which are temperature differences from the average for a standard period. Here, 1850-1900 is used for the global mean. Instrumental temperature records are some of the longest climate records available, with some series extending back to the 17th century.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Annual_Temperature_Anomalies_data_files.zip
Checksum: 76cdb2bad9582d23c1f6f4d868218d6c Copy
Format: BADC CSV format

ERA5

Original data file (external link)

Citation:

• Hersbach H, Bell B, Berrisford P et al. 2020. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146: 1999-2049. https://doi.org/10.1002/qj.3803.

Data citation: Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023): ERA5 monthly averaged data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), DOI: 10.24381/cds.f17050d7 (Accessed on AAAA)

Acknowledgement: Contains using Copernicus Climate Change Service information [YYYY]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

To produce the plot, the following processing steps were performed:

• Gridded dataset created from file ['era5_2m_tas_YYYY.nc'] downloaded from ['']
• Rebaselined to 1991-2020
• Selected period from 09/2025 to 08/2026
• Calculated time mean

Precipitation

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Precipitation_data_files.zip
Checksum: 76cdb2bad9582d23c1f6f4d868218d6c Copy
Format: BADC CSV format

GPCC

Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link)

To produce the plot, the following processing steps were performed:

• Gridded dataset created from file ['monitoring_v2022_10_YYYY_MMMM.nc.gz', 'first_guess_monthly_YYYY_MMMM.nc.gz', 'normals_1981_2010_v2022_10.nc.gz', 'normals_1991_2020_v2022_10.nc.gz'] downloaded from ['https://opendata.dwd.de/climate_environment/GPCC/monitoring_v2022/YYYY/monitoring_v2022_10_YYYY_MMMM.nc.gz', 'https://opendata.dwd.de/climate_environment/GPCC/first_guess/YYYY/first_guess_monthly_YYYY_MMMM.nc.gz', 'https://opendata.dwd.de/climate_environment/GPCC/gpcc_normals_v2022/normals_1981_2010_v2022_10.nc.gz', 'https://opendata.dwd.de/climate_environment/GPCC/gpcc_normals_v2022/normals_1991_2020_v2022_10.nc.gz']
• Rebaselined to 1991-2020
• Selected single month 08/2026

Seasonal precipitation anomalies

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Seasonal_precipitation_anomalies_data_files.zip
Checksum: 76cdb2bad9582d23c1f6f4d868218d6c Copy
Format: BADC CSV format

GPCC

Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link)

To produce the plot, the following processing steps were performed:

• Gridded dataset created from file ['monitoring_v2022_10_YYYY_MMMM.nc.gz', 'first_guess_monthly_YYYY_MMMM.nc.gz', 'normals_1981_2010_v2022_10.nc.gz', 'normals_1991_2020_v2022_10.nc.gz'] downloaded from ['https://opendata.dwd.de/climate_environment/GPCC/monitoring_v2022/YYYY/monitoring_v2022_10_YYYY_MMMM.nc.gz', 'https://opendata.dwd.de/climate_environment/GPCC/first_guess/YYYY/first_guess_monthly_YYYY_MMMM.nc.gz', 'https://opendata.dwd.de/climate_environment/GPCC/gpcc_normals_v2022/normals_1981_2010_v2022_10.nc.gz', 'https://opendata.dwd.de/climate_environment/GPCC/gpcc_normals_v2022/normals_1991_2020_v2022_10.nc.gz']
• Rebaselined to 1991-2020
• Selected period from 06/2026 to 08/2026
• Calculated time mean

Annual precipitation anomalies

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Annual_precipitation_anomalies_data_files.zip
Checksum: 76cdb2bad9582d23c1f6f4d868218d6c Copy
Format: BADC CSV format

GPCC

Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link)

To produce the plot, the following processing steps were performed:

• Gridded dataset created from file ['monitoring_v2022_10_YYYY_MMMM.nc.gz', 'first_guess_monthly_YYYY_MMMM.nc.gz', 'normals_1981_2010_v2022_10.nc.gz', 'normals_1991_2020_v2022_10.nc.gz'] downloaded from ['https://opendata.dwd.de/climate_environment/GPCC/monitoring_v2022/YYYY/monitoring_v2022_10_YYYY_MMMM.nc.gz', 'https://opendata.dwd.de/climate_environment/GPCC/first_guess/YYYY/first_guess_monthly_YYYY_MMMM.nc.gz', 'https://opendata.dwd.de/climate_environment/GPCC/gpcc_normals_v2022/normals_1981_2010_v2022_10.nc.gz', 'https://opendata.dwd.de/climate_environment/GPCC/gpcc_normals_v2022/normals_1991_2020_v2022_10.nc.gz']
• Rebaselined to 1991-2020
• Selected period from 09/2025 to 08/2026
• Calculated time mean

Lower Troposhere Temperature

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Lower_Troposhere_Temperature_data_files.zip
Checksum: 7bfec82bad8780388552b26c7bf517f2 Copy
Format: BADC CSV format

RSS

Original data file (external link)

Citation:

• Mears, C. A., and F. J. Wentz, 2009: Construction of the Remote Sensing Systems V3.2 Atmospheric Temperature Records from the MSU and AMSU Microwave Sounders. J. Atmos. Oceanic Technol., 26, 1040–1056, https://doi.org/10.1175/2008JTECHA1176.1..

To produce the plot, the following processing steps were performed:

• Data set created from file ['RSS_Monthly_MSU_AMSU_Channel_TLT_Anomalies_Land_and_Ocean_v04_0.txt'] downloaded from ['http://data.remss.com/msu/monthly_time_series/RSS_Monthly_MSU_AMSU_Channel_TLT_Anomalies_Land_and_Ocean_v04_0.txt'] at ['2026-09-10 22:41:54']
• Rebaselined to 1991-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

NOAA STAR

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['NESDIS-STAR_TCDR_TLT_Combined_With_TMT_TUT_TLS_Monthly_S198101-E202507_V5.0_Regional_Means_Anomaly.txt'] downloaded from ['https://www.star.nesdis.noaa.gov/data/mscat/MSU_AMSU_v5.0/Monthly_Atmospheric_Layer_Mean_Temperature/Global_Mean_Anomaly_Time_Series/NESDIS-STAR_TCDR_TLT_Combined_With_TMT_TUT_TLS_Monthly_S198101-E202507_V5.0_Regional_Means_Anomaly.txt'] at ['2025-10-14 10:47:54']
• Rebaselined to 1991-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

UAH

Original data file (external link)

Citation:

• Spencer, R.W., Christy, J.R. & Braswell, W.D. UAH Version 6 global satellite temperature products: Methodology and results. Asia-Pacific J Atmos Sci 53, 121–130 (2017). https://doi.org/10.1007/s13143-017-0010-y.

To produce the plot, the following processing steps were performed:

• Data set created from file ['uahncdc_lt_6.1.txt'] downloaded from ['https://www.nsstc.uah.edu/data/msu/v6.1/tlt/uahncdc_lt_6.1.txt'] at ['2026-09-10 22:41:56']
• Rebaselined to 1991-2010 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

Sea level

Global mean sea level is a measured by satellites using radar altimeters that record the time taken for a radar signal to reach the sea-surface and return to the satellite. Longer records of sea level (not shown here) exist based on tide gauge measurements made along coastlines around the world since the late 19th century.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Sea_level_data_files.zip
Checksum: 0b27ab3a8b86515cf0c67b730504bbbb Copy
Format: BADC CSV format

AVISO CNES

Original data file (external link)

Citation:

• Legeais, J.-F., Ablain, M., Zawadzki, L., Zuo, H., Johannessen, J. A., Scharffenberg, M. G., Fenoglio-Marc, L., Fernandes, M. J., Andersen, O. B., Rudenko, S., Cipollini, P., Quartly, G. D., Passaro, M., Cazenave, A., and Benveniste, J. (2018). An improved and homogeneous altimeter sea level record from the ESA Climate Change Initiative. Earth System Science Data, 10, 281-301. DOI: 10.5194/essd-10-281-2018.

Acknowledgement: Generated using AVISO+ Products

To produce the plot, the following processing steps were performed:

• Data set created from file ['MSL_Serie_MERGED_Global_AVISO_GIA_Adjust_Filter2m_NRT.nc'] downloaded from ['ftp://ftp.aviso.altimetry.fr/pub/oceano/AVISO/indicators/msl/MSL_Serie_MERGED_Global_AVISO_GIA_Adjust_Filter2m_NRT.nc'] at ['2026-09-10 22:41:22']
• Filtered with a 9-point Savgol filter of order 1
• Calculated monthly average from values using arithmetic mean of all dates that fall within each month
• Selected years within the range 1993 to 2026.
• Rebaselined to 1999-2025 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

CMEMS

Original data file (external link)

Data citation: https://doi.org/10.48670/moi-00237

Acknowledgement: Generated using E.U. Copernicus Marine Service Information

To produce the plot, the following processing steps were performed:

• Data set created from file ['omi_climate_sl_global_area_averaged_anomalies_19990220_P20260615.nc'] downloaded from ['https://jimmywarting.github.io/StreamSaver.js/data.marine.copernicus.eu/238524/omi_climate_sl_global_area_averaged_anomalies_19990220_P20260615.nc'] at ['2026-07-14 17:07:25']
• Calculated monthly average from values using arithmetic mean of all dates that fall within each month
• Selected years within the range 1993 to 2026.
• Rebaselined to 1999-2025 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

Colorado

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Selected years within the range 1993 to 2026.
• Rebaselined to 1999-2025 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

NASA

Original data file (external link)

Citation:

• Beckley, B. D., Callahan, P. S., Hancock, D. W., Mitchum, G. T., & Ray, R. D. (2017). On the 'cal-mode' correction to TOPEX satellite altimetry and its effect on the global mean sea level time series. Journal of Geophysical Research: Oceans, 122. https://doi.org/10.1002/2017JC013090.

Data citation: GSFC. 2021. Global Mean Sea Level Trend from Integrated Multi-Mission Ocean Altimeters TOPEX/Poseidon, Jason-1, OSTM/Jason-2, and Jason-3 Version 5.1. Ver. 5.1 PO.DAAC, CA, USA. Dataset accessed [YYYY-MM-DD] at https://doi.org/10.5067/GMSLM-TJ151.

To produce the plot, the following processing steps were performed:

• Selected years within the range 1993 to 2026.
• Rebaselined to 1999-2025 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

Arctic sea ice

Sea-ice concentrations are estimated from microwave radiances measured from satellites (from 1979). Sea-ice extent is calculated as the area of ocean grid cells where the sea-ice concentration exceeds 15%. Although there are relatively large differences in the absolute extent between data sets, they agree well on the year-to-year changes and the trends.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Arctic_sea_ice_data_files.zip
Checksum: 9e3170c801c268b556faa518ff7376fb Copy
Format: BADC CSV format

JAXA

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['JASMES_CLIMATE_SIE_5DAVG_PS_NHM.txt'] downloaded from ['ftp://apollo.eorc.jaxa.jp/pub/JASMES/Polar_XXkm/sie/'] at ['2026-09-11 11:50:05']
• Calculated monthly average from values using arithmetic mean of all dates that fall within each month
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

NSIDC v4

Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link)

Data citation: Fetterer, F., K. Knowles, W. N. Meier, M. Savoie, and A. K. Windnagel. 2017, updated daily. Sea Ice Index, Version 3. 1979-present. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: https://doi.org/10.7265/N5K072F8. [2026-09-10 22:38:40].

Acknowledgement: Fetterer, F., K. Knowles, W. N. Meier, M. Savoie, and A. K. Windnagel. 2017, updated daily. Sea Ice Index, Version 3. 1979-present. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: https://doi.org/10.7265/N5K072F8. [2026-09-10 22:38:40].

To produce the plot, the following processing steps were performed:

• Data set created from file ['N_01_extent_v4.0.csv', 'N_02_extent_v4.0.csv', 'N_03_extent_v4.0.csv', 'N_04_extent_v4.0.csv', 'N_05_extent_v4.0.csv', 'N_06_extent_v4.0.csv', 'N_07_extent_v4.0.csv', 'N_08_extent_v4.0.csv', 'N_09_extent_v4.0.csv', 'N_10_extent_v4.0.csv', 'N_11_extent_v4.0.csv', 'N_12_extent_v4.0.csv'] downloaded from ['ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_01_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_02_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_03_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_04_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_05_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_06_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_07_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_08_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_09_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_10_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_11_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_12_extent_v4.0.csv'] at ['2026-09-10 22:38:40', '2026-09-10 22:38:42', '2026-09-10 22:38:43', '2026-09-10 22:38:45', '2026-09-10 22:38:46', '2026-09-10 22:38:48', '2026-09-10 22:38:49', '2026-09-10 22:38:51', '2026-09-10 22:38:53', '2026-09-10 22:38:54', '2026-09-10 22:38:56', '2026-09-10 22:38:57']
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

OSI SAF v3.0

Original data file (external link)

Citation:

• Lavergne, T., Sorensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjar, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49-78, doi:10.5194/tc-13-49-2019, 2019..

Data citation: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Sea ice index 1979-onwards (v3.0, 2023), OSI-420, Data extracted from OSI SAF FTP server: 1979-present, Northern Hemisphere, accessed 2026-09-10 22:38:58

Acknowledgement: The OSI SAF Sea Ice Index v3.0 is made available at https://osisaf-hl.met.no/v3p0-sea-ice-index. The OSI SAF Sea Ice Index v3p0 is prepared using EUMETSAT OSI SAF Sea Ice Concentration data, with R&D input from the ESA Climate Change Initiative (ESA CCI) (Lavergne et al. 2019)

To produce the plot, the following processing steps were performed:

• Data set created from file ['ice_extent_nh_sii-v3p0_monthly.txt'] downloaded from ['ftp://osisaf.met.no/prod/ice/index/v3p0/timeseries/nh/ice_extent_nh_sii-v3p0_monthly.txt'] at ['2026-09-10 22:38:58']
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

Antarctic sea ice

Sea-ice concentrations are estimated from microwave radiances measured from satellites (from 1979). Sea-ice extent is calculated as the area of ocean grid cells where the sea-ice concentration exceeds 15%. Although there are relatively large differences in the absolute extent between data sets, they agree well on the year-to-year changes and the trends.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Antarctic_sea_ice_data_files.zip
Checksum: a4f14f764a24f39150daae1c5ccc5791 Copy
Format: BADC CSV format

JAXA

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['JASMES_CLIMATE_SIE_5DAVG_PS_SHM.txt'] downloaded from ['ftp://apollo.eorc.jaxa.jp/pub/JASMES/Polar_XXkm/sie/'] at ['2026-09-11 11:50:36']
• Calculated monthly average from values using arithmetic mean of all dates that fall within each month
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

NSIDC v4

Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link) Original data file (external link)

Data citation: Fetterer, F., K. Knowles, W. N. Meier, M. Savoie, and A. K. Windnagel. 2017, updated daily. Sea Ice Index, Version 3. 1979-present. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: https://doi.org/10.7265/N5K072F8. [2026-09-10 22:38:59].

Acknowledgement: Fetterer, F., K. Knowles, W. N. Meier, M. Savoie, and A. K. Windnagel. 2017, updated daily. Sea Ice Index, Version 3. 1979-present. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: https://doi.org/10.7265/N5K072F8. [2026-09-10 22:38:59].

To produce the plot, the following processing steps were performed:

• Data set created from file ['S_01_extent_v4.0.csv', 'S_02_extent_v4.0.csv', 'S_03_extent_v4.0.csv', 'S_04_extent_v4.0.csv', 'S_05_extent_v4.0.csv', 'S_06_extent_v4.0.csv', 'S_07_extent_v4.0.csv', 'S_08_extent_v4.0.csv', 'S_09_extent_v4.0.csv', 'S_10_extent_v4.0.csv', 'S_11_extent_v4.0.csv', 'S_12_extent_v4.0.csv'] downloaded from ['ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_01_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_02_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_03_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_04_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_05_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_06_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_07_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_08_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_09_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_10_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_11_extent_v4.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_12_extent_v4.0.csv'] at ['2026-09-10 22:38:59', '2026-09-10 22:39:01', '2026-09-10 22:39:02', '2026-09-10 22:39:04', '2026-09-10 22:39:05', '2026-09-10 22:39:07', '2026-09-10 22:39:08', '2026-09-10 22:39:09', '2026-09-10 22:39:10', '2026-09-10 22:39:12', '2026-09-10 22:39:13', '2026-09-10 22:39:14']
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

OSI SAF v3.0

Original data file (external link)

Citation:

• Lavergne, T., Sorensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjar, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49-78, doi:10.5194/tc-13-49-2019, 2019..

Data citation: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Sea ice index 1979-onwards (v3.0, 2020), OSI-420, Data extracted from OSI SAF FTP server: 1979-present, Northern Hemisphere, accessed 2026-09-10 22:39:15

Acknowledgement: The OSI SAF Sea Ice Index v3.0 is made available at https://osisaf-hl.met.no/v3p0-sea-ice-index. The OSI SAF Sea Ice Index v3p0 is prepared using EUMETSAT OSI SAF Sea Ice Concentration data, with R&D input from the ESA Climate Change Initiative (ESA CCI) (Lavergne et al. 2019)

To produce the plot, the following processing steps were performed:

• Data set created from file ['ice_extent_sh_sii-v3p0_monthly.txt'] downloaded from ['ftp://osisaf.met.no/prod/ice/index/v3p0/timeseries/sh/ice_extent_sh_sii-v3p0_monthly.txt'] at ['2026-09-10 22:39:15']
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).

Arctic daily sea ice

Sea-ice concentrations are estimated from microwave radiances measured from satellites (from 1979). Sea-ice extent is calculated as the area of ocean grid cells where the sea-ice concentration exceeds 15%. Although there are relatively large differences in the absolute extent between data sets, they agree well on the year-to-year changes and the trends.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Arctic_daily_sea_ice_data_files.zip
Checksum: ff63549490c7cc4d75e7c5bf34568408 Copy
Format: BADC CSV format

OSI SAF v3.0

Original data file (external link)

Citation:

• Lavergne, T., Sorensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjar, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49-78, doi:10.5194/tc-13-49-2019, 2019..

Data citation: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Sea ice index 1979-onwards (v3.0, 2023), OSI-420, Data extracted from OSI SAF FTP server: 1979-present, Northern Hemisphere, accessed 2026-09-11 11:50:08

Acknowledgement: The OSI SAF Sea Ice Index v3.0 is made available at https://osisaf-hl.met.no/v3p0-sea-ice-index. The OSI SAF Sea Ice Index v3p0 is prepared using EUMETSAT OSI SAF Sea Ice Concentration data, with R&D input from the ESA Climate Change Initiative (ESA CCI) (Lavergne et al. 2019)

To produce the plot, the following processing steps were performed:

• Data set created from file ['ice_extent_nh_sii-v3p0_daily.nc'] downloaded from ['https://thredds.met.no/thredds/fileServer/osisaf/met.no/ice/index/sii_v3p0/nh/ice_extent_nh_sii-v3p0_daily.nc'] at ['2026-09-11 11:50:08']
• Time series expanded with NaN to include all days between 1978 and 2026

Antarctic daily sea ice

Sea-ice concentrations are estimated from microwave radiances measured from satellites (from 1979). Sea-ice extent is calculated as the area of ocean grid cells where the sea-ice concentration exceeds 15%. Although there are relatively large differences in the absolute extent between data sets, they agree well on the year-to-year changes and the trends.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Antarctic_daily_sea_ice_data_files.zip
Checksum: e10894708c98c708bfef523ea1e1e4b3 Copy
Format: BADC CSV format

OSI SAF v3.0

Original data file (external link)

Citation:

• Lavergne, T., Sorensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjar, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49-78, doi:10.5194/tc-13-49-2019, 2019..

Data citation: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Sea ice index 1979-onwards (v3.0, 2020), OSI-420, Data extracted from OSI SAF FTP server: 1979-present, Northern Hemisphere, accessed 2026-09-11 11:50:39

Acknowledgement: The OSI SAF Sea Ice Index v3.0 is made available at https://osisaf-hl.met.no/v3p0-sea-ice-index. The OSI SAF Sea Ice Index v3p0 is prepared using EUMETSAT OSI SAF Sea Ice Concentration data, with R&D input from the ESA Climate Change Initiative (ESA CCI) (Lavergne et al. 2019)

To produce the plot, the following processing steps were performed:

• Data set created from file ['ice_extent_sh_sii-v3p0_daily.nc'] downloaded from ['https://thredds.met.no/thredds/fileServer/osisaf/met.no/ice/index/sii_v3p0/sh/ice_extent_sh_sii-v3p0_daily.nc'] at ['2026-09-11 11:50:39']
• Time series expanded with NaN to include all days between 1978 and 2026

Greenland ice sheet

The Greenland ice sheet mass balance measures the change in ice mass of the Greenland ice sheet. The change in mass is estimated in three principle ways: gravimetric measurements, altimetric measurements and the input-output method. Gravimetric measurements infer mass changes from variations in the Earth's gravitational field as measured by the GRACE and GRACE-FO (Gravity Recovery and Climate Experiment - Follow On) satellites. Altimetric measurements, measured the height of the ice sheet surface, using radar and laser altimeters. Input-output methods, use weather conditions from a numerical weather prediction model, to estimate changes in mass balance at the surface of the ice sheet. These are combined with estimates of mass loss from glaciers around the edge of Greenland and melting on the underside of the glaciers. The IMBIE data set combines over 25 different estimates of Greenland mass balance to get a comprehensive view of the long-term changes.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Greenland_ice_sheet_data_files.zip
Checksum: 20fe64898cc5f854a4890b8f27d5f455 Copy
Format: BADC CSV format

NASA GRACE

Original data file (external link)

Citation:

• Watkins, M. M., D. N. Wiese, D. -N. Yuan, C. Boening, and F. W. Landerer (2015), Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons, J. Geophys. Res. Solid Earth, 120, 2648_2671, doi: 10.1002/2014JB011547..

Data citation: Wiese, D. N., D.-N. Yuan, C. Boening, F. W. Landerer, and M. M. Watkins (2019) JPL GRACE and GRACE-FO Mascon Ocean, Ice, and Hydrology Equivalent Water Height RL06M CRI Filtered Version 2.0, Ver. 2.0, PO.DAAC, CA, USA. Dataset accessed [2026-05-07 16:21:32] at http://dx.doi.org/10.5067/TEMSC-3MJ62.

Notes: Data from the GRACE and GRACE-FO JPL RL06Mv2 Mascon Solution

To produce the plot, the following processing steps were performed:

• Data set created from file ['greenland_mass_200204_2026MMMM.txt'] downloaded from ['https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/GREENLAND_MASS_TELLUS_MASCON_CRI_TIME_SERIES_RL06.3_V4/greenland_mass_200204_2026MMMM.txt'] at ['2026-05-07 16:21:32']
• Zeroed series on July 2005 by subtracting the value for that month from all data values (see next entry)
• Added offset of 616.91 to all data values.
• Manually changed baseline to 2005-2005. Note that data values remain unchanged.

IMBIE 2021

Original data file (external link)

Citation:

• Shepherd, A., Ivins, E., Rignot, E., Smith, B., van den Broeke, M., Velicogna, I., Whitehouse, P., Briggs, K., Joughin, I., Krinner, G., Nowicki, S., Payne, A., Scambos, T., Schlegel, N., A, G., Agosta, C., Ahlstrøm, A., Babonis, G., Barletta, V., … Wuite, J. (2021). Antarctic and Greenland Ice Sheet mass balance 1992-2020 for IPCC AR6 (Version 1.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/77B64C55-7166-4A06-9DEF-2E400398E452.

Data citation: Shepherd, A., Ivins, E., Rignot, E., Smith, B., van den Broeke, M., Velicogna, I., Whitehouse, P., Briggs, K., Joughin, I., Krinner, G., Nowicki, S., Payne, A., Scambos, T., Schlegel, N., A, G., Agosta, C., Ahlstrøm, A., Babonis, G., Barletta, V., … Wuite, J. (2021). Antarctic and Greenland Ice Sheet mass balance 1992-2020 for IPCC AR6 (Version 1.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/77B64C55-7166-4A06-9DEF-2E400398E452

To produce the plot, the following processing steps were performed:

• Data set created from file ['imbie_greenland_2021_Gt.csv'] downloaded from ['https://ramadda.data.bas.ac.uk/repository/entry/get/imbie_greenland_2021_Gt.csv?entryid=synth%3A77b64c55-7166-4a06-9def-2e400398e452%3AL2ltYmllX2dyZWVubGFuZF8yMDIxX0d0LmNzdg%3D%3D'] at ['2023-08-07 14:40:22']
• Zeroed series on July 2005 by subtracting the value for that month from all data values (see next entry)
• Added offset of 1000.3866 to all data values.
• Manually changed baseline to 2005-2005. Note that data values remain unchanged.

Mankoff et al. 2021

Original data file (external link)

Citation:

• Mankoff, K. D., Fettweis, X., Langen, P. L., Stendel, M., Kjeldsen, K. K., Karlsson, N. B., Noël, B., van den Broeke, M. R., Solgaard, A., Colgan, W., Box, J. E., Simonsen, S. B., King, M. D., Ahlstrøm, A. P., Andersen, S. B., and Fausto, R. S.: Greenland ice sheet mass balance from 1840 through next week, Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, 2021. doi: 10.5194/essd-13-5001-2021.

Data citation: https://doi.org/10.22008/FK2/OHI23Z

Notes: Filename should be MB_SMB_D_BMB.csv

To produce the plot, the following processing steps were performed:

• Data set created from file ['MB_SMB_D_BMB.csv'] downloaded from ['https://thredds.geus.dk/thredds/fileServer/MassBalance/MB_SMB_D_BMB.csv'] at ['2026-09-10 22:41:38']
• Zeroed series on July 2005 by subtracting the value for that month from all data values (see next entry)
• Added offset of 1549.1470230000007 to all data values.
• Manually changed baseline to 2005-2005. Note that data values remain unchanged.

Antarctic ice sheet

The Antarctic ice sheet mass balance measures the change in ice mass of the Antarctic ice sheet. The change in mass is estimated in three principle ways: gravimetric measurements, altimetric measurements and the input-output method. Gravimetric measurements infer mass changes from variations in the Earth's gravitational field as measured by the GRACE and GRACE-FO (Gravity Recovery and Climate Experiment - Follow On) satellites. Altimetric measurements, measured the height of the ice sheet surface, using radar and laser altimeters. Input-output methods, use weather conditions from a numerical weather prediction model, to estimate changes in mass balance at the surface of the ice sheet. These are combined with estimates of mass loss from glaciers around the edge of the continent and melting on the underside of the glaciers. The IMBIE data set combines many estimates of Antarctic mass balance to get a comprehensive view of the long-term changes.

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Antarctic_ice_sheet_data_files.zip
Checksum: b178fc610a909c2adaae211d4883ef5a Copy
Format: BADC CSV format

NASA GRACE

Original data file (external link)

Citation:

• Watkins, M. M., D. N. Wiese, D. -N. Yuan, C. Boening, and F. W. Landerer (2015), Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons, J. Geophys. Res. Solid Earth, 120, 2648_2671, doi: 10.1002/2014JB011547..

Data citation: Wiese, D. N., D.-N. Yuan, C. Boening, F. W. Landerer, and M. M. Watkins (2019) JPL GRACE and GRACE-FO Mascon Ocean, Ice, and Hydrology Equivalent Water Height RL06M CRI Filtered Version 2.0, Ver. 2.0, PO.DAAC, CA, USA. Dataset accessed [2026-05-07 16:21:01] at http://dx.doi.org/10.5067/TEMSC-3MJ62.

Notes: Data from the GRACE and GRACE-FO JPL RL06Mv2 Mascon Solution

To produce the plot, the following processing steps were performed:

• Data set created from file ['antarctica_mass_200204_2026MMMM.txt'] downloaded from ['https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/ANTARCTICA_MASS_TELLUS_MASCON_CRI_TIME_SERIES_RL06.3_V4/antarctica_mass_200204_2026MMMM.txt'] at ['2026-05-07 16:21:01']
• Zeroed series on June 2005 by subtracting the value for that month from all data values (see next entry)
• Added offset of 161.03 to all data values.
• Manually changed baseline to 2005-2005. Note that data values remain unchanged.

IMBIE 2021

Original data file (external link)

Citation:

• Shepherd, A., Ivins, E., Rignot, E., Smith, B., van den Broeke, M., Velicogna, I., Whitehouse, P., Briggs, K., Joughin, I., Krinner, G., Nowicki, S., Payne, A., Scambos, T., Schlegel, N., A, G., Agosta, C., Ahlstrøm, A., Babonis, G., Barletta, V., … Wuite, J. (2021). Antarctic and Greenland Ice Sheet mass balance 1992-2020 for IPCC AR6 (Version 1.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/77B64C55-7166-4A06-9DEF-2E400398E452.

Data citation: Shepherd, A., Ivins, E., Rignot, E., Smith, B., van den Broeke, M., Velicogna, I., Whitehouse, P., Briggs, K., Joughin, I., Krinner, G., Nowicki, S., Payne, A., Scambos, T., Schlegel, N., A, G., Agosta, C., Ahlstrøm, A., Babonis, G., Barletta, V., … Wuite, J. (2021). Antarctic and Greenland Ice Sheet mass balance 1992-2020 for IPCC AR6 (Version 1.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/77B64C55-7166-4A06-9DEF-2E400398E452

To produce the plot, the following processing steps were performed:

• Data set created from file ['imbie_antarctica_2021_Gt.csv'] downloaded from ['https://ramadda.data.bas.ac.uk/repository/entry/get/imbie_antarctica_2021_Gt.csv?entryid=synth%3A77b64c55-7166-4a06-9def-2e400398e452%3AL2ltYmllX2FudGFyY3RpY2FfMjAyMV9HdC5jc3Y%3D'] at ['2023-08-07 14:40:20']
• Zeroed series on June 2005 by subtracting the value for that month from all data values (see next entry)
• Added offset of 646.1411 to all data values.
• Manually changed baseline to 2005-2005. Note that data values remain unchanged.

ONI

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: ONI_data_files.zip
Checksum: 67089ee2675ce4f3cfb23c0f9ad7bbf4 Copy
Format: BADC CSV format

CPC ONI

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['oni.data'] downloaded from ['https://psl.noaa.gov/data/correlation/oni.data'] at ['2026-09-10 22:41:48']
• Selected years within the range 1950 to 2026.

Relative ONI

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Relative_ONI_data_files.zip
Checksum: 02e56c8324017dc4609b77662eb12005 Copy
Format: BADC CSV format

Bureau of Meteorology

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['rnino_3.4.txt'] downloaded from ['https://www.bom.gov.au/clim_data/IDCK000072/rnino_3.4.txt'] at ['2026-09-10 22:41:40']
• Calculated monthly average from values using arithmetic mean of all dates that fall within each month
• Selected years within the range 1950 to 2026.

NOAA CPC

Original data file (external link)

Citation:

• https://www.ncei.noaa.gov/access/monitoring/ao/.

To produce the plot, the following processing steps were performed:

• Data set created from file ['RONI.ascii.txt'] downloaded from ['https://www.cpc.ncep.noaa.gov/data/indices/RONI.ascii.txt'] at ['2026-09-10 22:41:44']
• Selected years within the range 1950 to 2026.

University of Miami

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['RONI_NINO34_v6.txt'] downloaded from ['https://bmcnoldy.earth.miami.edu/tropics/roni/RONI_NINO34_v6.txt'] at ['2026-09-09 09:25:13']
• Selected years within the range 1950 to 2026.

ENSO

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: ENSO_data_files.zip
Checksum: 83b4fa3af4b1c89ee5a84ebcf82ff721 Copy
Format: BADC CSV format

ERSSTv5

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['nina34.data'] downloaded from ['https://psl.noaa.gov/data/correlation/nina34.data'] at ['2026-09-10 22:41:48']
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Selected years within the range 1950 to 2026.

HadISST

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['nino34.long.data'] downloaded from ['https://psl.noaa.gov/gcos_wgsp/Timeseries/Data/nino34.long.data'] at ['2024-11-27 10:47:44']
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Selected years within the range 1950 to 2026.

SOI

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: SOI_data_files.zip
Checksum: 2b72b5e45bfc90049f4e38d645ed5a4f Copy
Format: BADC CSV format

Bureau of Meteorology

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['soi_monthly.txt'] downloaded from ['https://www.bom.gov.au/clim_data/IDCKGSH000/soi_monthly.txt'] at ['2026-09-10 22:41:40']
• Selected years within the range 1950 to 2026.

CPC SOI

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['soi.data'] downloaded from ['https://psl.noaa.gov/data/correlation/soi.data'] at ['2026-09-10 22:41:49']
• Selected years within the range 1950 to 2026.

Indian Ocean Dipole

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Indian_Ocean_Dipole_data_files.zip
Checksum: 1eaa8c528d24d8f3f802e758d88ad8fd Copy
Format: BADC CSV format

Bureau of Meteorology

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['iod_1.txt'] downloaded from ['https://reg.bom.gov.au/clim_data/IDCK000072/iod_1.txt'] at ['2026-09-10 22:41:39']
• Calculated monthly average from values using arithmetic mean of all dates that fall within each month
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Selected years within the range 2000 to 2026.

NOAA OSMC

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['dmi.nc'] downloaded from ['https://stateoftheocean.osmc.noaa.gov/sur/data/dmi.nc'] at ['2026-09-10 22:41:45']
• Calculated monthly average from values using arithmetic mean of all dates that fall within each month
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Selected years within the range 2000 to 2026.

JMA

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['3rmean'] downloaded from ['https://ds.data.jma.go.jp/tcc/tcc/products/elnino/index/sstindex/base_period_9120/DMI/3rmean'] at ['2026-09-10 22:41:46']
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Selected years within the range 2000 to 2026.

NOAA NCEP

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['mnth.ersstv5.clim19912020.dmi_current.txt'] downloaded from ['https://www.cpc.ncep.noaa.gov/products/international/ocean_monitoring/IODMI/mnth.ersstv5.clim19912020.dmi_current.txt'] at ['2026-09-10 22:41:47']
• Rebaselined to 1991-2020 for each month separately by calculating the arithmetic mean of the data over the baseline period and subtracting the mean from all data values. This is done for each month separately (Januarys, Februarys etc).
• Selected years within the range 2000 to 2026.

Pacific Decadal Oscillation

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Pacific_Decadal_Oscillation_data_files.zip
Checksum: f4e590cf7eb3894c6f1a2dcb27d6280b Copy
Format: BADC CSV format

NOAA CPC

Original data file (external link)

Citation:

• https://www.ncei.noaa.gov/access/monitoring/pdo/.

To produce the plot, the following processing steps were performed:

• Data set created from file ['ersst.v5.pdo.dat'] downloaded from ['https://www.ncei.noaa.gov/pub/data/cmb/ersst/v5/index/ersst.v5.pdo.dat'] at ['2026-09-10 22:41:43']
• Selected years within the range 1950 to 2026.

Arctic Oscillation

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Arctic_Oscillation_data_files.zip
Checksum: 71d50cb526d7b91bbe24d35e18fa1469 Copy
Format: BADC CSV format

NOAA CPC

Original data file (external link)

Citation:

• https://www.ncei.noaa.gov/access/monitoring/ao/.

To produce the plot, the following processing steps were performed:

• Data set created from file ['monthly.ao.index.b50.current.ascii.table'] downloaded from ['https://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/monthly.ao.index.b50.current.ascii.table'] at ['2026-09-10 22:41:42']
• Selected years within the range 2010 to 2026.

Antarctic Oscillation

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: Antarctic_Oscillation_data_files.zip
Checksum: bfc2c412e1a98046df20f302480e1a99 Copy
Format: BADC CSV format

NOAA CPC

Original data file (external link)

Citation:

• https://www.ncei.noaa.gov/access/monitoring/ao/.

To produce the plot, the following processing steps were performed:

• Data set created from file ['monthly.aao.index.b79.current.ascii.table'] downloaded from ['https://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/aao/monthly.aao.index.b79.current.ascii.table'] at ['2026-09-10 22:41:41']
• Selected years within the range 2010 to 2026.

RONI year by year comparison

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: RONI_year_by_year_comparison_data_files.zip
Checksum: 3eac3cfe01bc5c5ffac4604f153e16b2 Copy
Format: BADC CSV format

NOAA CPC

Original data file (external link)

Citation:

• https://www.ncei.noaa.gov/access/monitoring/ao/.

To produce the plot, the following processing steps were performed:

• Data set created from file ['RONI.ascii.txt'] downloaded from ['https://www.cpc.ncep.noaa.gov/data/indices/RONI.ascii.txt'] at ['2026-09-10 22:41:44']
• Selected years within the range 1950 to 2026.

ONI year by year comparison

The data in the above plot are available in a zip file containing a csv file for each data set.

Data file: ONI_year_by_year_comparison_data_files.zip
Checksum: e0777eb2c61282671efdd58e29db6f33 Copy
Format: BADC CSV format

CPC ONI

Original data file (external link)

To produce the plot, the following processing steps were performed:

• Data set created from file ['oni.data'] downloaded from ['https://psl.noaa.gov/data/correlation/oni.data'] at ['2026-09-10 22:41:48']
• Selected years within the range 1950 to 2026.