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: 79b9c6153f21ea721f6b45590ad0bf09 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 ['2025-10-30 22:44:21']

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 ['2025-10-30 22:44:22']

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 10:10:37']

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: 858952a523ad6d3b8653d5d5755b8fce 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 ['2025-10-30 22:44:25']

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 ['2025-10-30 22:44:26']

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 10:10:24']

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: 46105affacb80afd3ab90caad744867b 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 ['2025-10-30 22:44:30']

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 10:10:47']

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: a5b13ffdc7bf894ddad42a26d39dc07a Copy
Format: BADC CSV format

Berkeley Earth

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 ['Land_and_Ocean_complete.txt'] downloaded from ['https://berkeley-earth-temperature.s3.us-west-1.amazonaws.com/Global/Land_and_Ocean_complete.txt'] at ['2025-10-31 10:50:00']
• 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).
• 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 2025.

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 ['2025-10-30 22:43:14']
• 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 2025.

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 2025-10-31 11:39:57)

Acknowledgement: Contains using Copernicus Climate Change Service information [2025]. 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_202509_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] downloaded from ['https://climate.copernicus.eu/sites/default/files/2025-10/C3S_Bulletin_temp_202509_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] at ['2025-10-31 11:39:57']
• 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 2025.

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 2025-10-14 10:43:17 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 ['2025-10-14 10:43:17']
• 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 2025.

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 2025-10-30 22:43:15 and are © British Crown Copyright, Met Office 2025, 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.5.0.2.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.0.2.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] at ['2025-10-30 22:43:15', '2025-10-30 22:43:15']
• 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 2025.

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 2025-10-14 09:48:00.

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 ['2025-10-14 09:48:00']
• 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).
• 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 2025.

NOAAGlobalTemp v6

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 2025-09-29 21:48:30.

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

• Data set created from file ['aravg.mon.land_ocean.90S.90N.v6.0.0.202508.asc', 'aravg.ann.land_ocean.90S.90N.*.asc'] downloaded from ['https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6/access/timeseries/aravg.mon.land_ocean.90S.90N.v6.0.0.202508.asc', 'https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6/access/timeseries/aravg.ann.land_ocean.90S.90N.*.asc'] at ['2025-09-29 21:48:30']
• 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 2025.

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: 9c6293d7cd6f4298ba4fc654cd427aef Copy
Format: BADC CSV format

Berkeley Earth

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 ['Land_and_Ocean_complete.txt'] downloaded from ['https://berkeley-earth-temperature.s3.us-west-1.amazonaws.com/Global/Land_and_Ocean_complete.txt'] at ['2025-10-31 10:50:00']
• 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).
• 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 2025.

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 ['2025-10-30 22:43:14']
• 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 2025.

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 2025-10-31 11:39:57)

Acknowledgement: Contains using Copernicus Climate Change Service information [2025]. 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_202509_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] downloaded from ['https://climate.copernicus.eu/sites/default/files/2025-10/C3S_Bulletin_temp_202509_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] at ['2025-10-31 11:39:57']
• 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 2025.

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 2025-10-14 10:43:17 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 ['2025-10-14 10:43:17']
• 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 2025.

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 2025-10-30 22:43:15 and are © British Crown Copyright, Met Office 2025, 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.5.0.2.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.0.2.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] at ['2025-10-30 22:43:15', '2025-10-30 22:43:15']
• 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 2025.

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 2025-10-14 09:48:00.

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 ['2025-10-14 09:48:00']
• 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).
• 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 2025.

NOAAGlobalTemp v6

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 2025-09-29 21:48:30.

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

• Data set created from file ['aravg.mon.land_ocean.90S.90N.v6.0.0.202508.asc', 'aravg.ann.land_ocean.90S.90N.*.asc'] downloaded from ['https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6/access/timeseries/aravg.mon.land_ocean.90S.90N.v6.0.0.202508.asc', 'https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6/access/timeseries/aravg.ann.land_ocean.90S.90N.*.asc'] at ['2025-09-29 21:48:30']
• 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 2025.

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: c0185f4b6de1c794f6a629f02ae1e6fa 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 ['2025-10-30 22:43:14']
• 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 2025-10-31 11:39:57)

Acknowledgement: Contains using Copernicus Climate Change Service information [2025]. 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_202509_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] downloaded from ['https://climate.copernicus.eu/sites/default/files/2025-10/C3S_Bulletin_temp_202509_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] at ['2025-10-31 11:39:57']
• 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 2025-10-14 10:43:17 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 ['2025-10-14 10:43:17']
• 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 2025-10-30 22:43:15 and are © British Crown Copyright, Met Office 2025, 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.5.0.2.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.0.2.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] at ['2025-10-30 22:43:15', '2025-10-30 22:43:15']
• 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 2025-10-14 09:48:00.

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 ['2025-10-14 09:48:00']
• 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).

NOAAGlobalTemp v6

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 2025-09-29 21:48:30.

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

• Data set created from file ['aravg.mon.land_ocean.90S.90N.v6.0.0.202508.asc', 'aravg.ann.land_ocean.90S.90N.*.asc'] downloaded from ['https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6/access/timeseries/aravg.mon.land_ocean.90S.90N.v6.0.0.202508.asc', 'https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6/access/timeseries/aravg.ann.land_ocean.90S.90N.*.asc'] at ['2025-09-29 21:48:30']
• 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).

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: 19c63c85f1a3feedbafe799fbe1c2855 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 ['2025-10-30 22:43:14']
• 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 2025-10-31 11:39:57)

Acknowledgement: Contains using Copernicus Climate Change Service information [2025]. 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_202509_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] downloaded from ['https://climate.copernicus.eu/sites/default/files/2025-10/C3S_Bulletin_temp_202509_Fig1b_timeseries_anomalies_ref1991-2020_global_allmonths_DATA.csv'] at ['2025-10-31 11:39:57']
• 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 2025-10-14 10:43:17 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 ['2025-10-14 10:43:17']
• 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 2025-10-30 22:43:15 and are © British Crown Copyright, Met Office 2025, 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.5.0.2.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.monthly.csv', 'https://www.metoffice.gov.uk/hadobs/hadcrut5/data/HadCRUT.5.0.2.0/analysis/diagnostics/HadCRUT.5.1.0.0.analysis.summary_series.global.annual.csv'] at ['2025-10-30 22:43:15', '2025-10-30 22:43:15']
• 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 2025-10-14 09:48:00.

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 ['2025-10-14 09:48:00']
• 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).

NOAAGlobalTemp v6

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 2025-09-29 21:48:30.

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

• Data set created from file ['aravg.mon.land_ocean.90S.90N.v6.0.0.202508.asc', 'aravg.ann.land_ocean.90S.90N.*.asc'] downloaded from ['https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6/access/timeseries/aravg.mon.land_ocean.90S.90N.v6.0.0.202508.asc', 'https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6/access/timeseries/aravg.ann.land_ocean.90S.90N.*.asc'] at ['2025-09-29 21:48:30']
• 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).

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: 2f9e449fa460e5ea528b5d3c5fbffc47 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 17:02:42']
• 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 2025.

DCENT

Original data file (external link)

Citation:

• Chan, Duo; Gebbie, Geoffrey; Huybers, Peter; Kent, Elizabeth, 2024, DCENT: Dynamically Consistent ENsemble of Temperature at the earth surface, Scientific Data (2024)..

Data citation: Chan, Duo; Gebbie, Geoffrey; Huybers, Peter; Kent, Elizabeth, 2024, DCENT: Dynamically Consistent ENsemble of Temperature at the earth surface, https://doi.org/10.7910/DVN/NU4UGW, Harvard Dataverse, V1

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

• Gridded dataset created from file ['DCENT_ensemble_1850_2023_ensemble_mean.nc', 'DCENT_monthly_climatology_1982_2014.nc'] downloaded from ['']
• Data set created from file ['DCENT_ensemble_1850_2023_ensemble_mean.nc', 'DCENT_monthly_climatology_1982_2014.nc'] downloaded from [''] at ['2024-07-31 11:55:51', '2024-07-31 11:55:49']
• 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).
• Selected years within the range 2010 to 2025.

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 [2025-10-10 13:43:16].

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

• Data set created from file ['aravg.mon.ocean.90S.90N.v6.0.0.2025MMMM.asc', 'aravg.ann.ocean.90S.90N.v6.0.0.2025MMMM.asc'] downloaded from ['https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6/access/timeseries/aravg.mon.ocean.90S.90N.v6.0.0.2025MMMM.asc', 'https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v6/access/timeseries/aravg.ann.ocean.90S.90N.v6.0.0.2025MMMM.asc'] at ['2025-10-10 13:43:16']
• 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).
• Selected years within the range 2010 to 2025.

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 2025-10-30 22:43:18 and are © British Crown Copyright, Met Office 2025, 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 ['2025-10-30 22:43:18', '2025-10-30 22:43:18']
• 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 2025.

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 09/2025

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 06/2025 to 08/2025
• 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 10/2024 to 09/2025
• 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 09/2025

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 06/2025 to 08/2025
• 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 10/2024 to 09/2025
• 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: e70e095766b8f45a8949fdd681997c11 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 ['2025-10-30 22:44:16']
• 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 10:47:52']
• 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 ['2025-10-30 22:44:18']
• 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: 9ec9dee921c330f46d99232e37aa14ad 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 ['2025-10-30 22:43:28']
• Selected years within the range 1993 to 2025.

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: bb26f4a3a7ee644ae6dd6a9dd1d62343 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 ['2025-10-30 22:41:29']
• 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

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. [2025-07-30 07:38:10].

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. [2025-07-30 07:38:10].

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

• Data set created from file ['N_01_extent_v3.0.csv', 'N_02_extent_v3.0.csv', 'N_03_extent_v3.0.csv', 'N_04_extent_v3.0.csv', 'N_05_extent_v3.0.csv', 'N_06_extent_v3.0.csv', 'N_07_extent_v3.0.csv', 'N_08_extent_v3.0.csv', 'N_09_extent_v3.0.csv', 'N_10_extent_v3.0.csv', 'N_11_extent_v3.0.csv', 'N_12_extent_v3.0.csv'] downloaded from ['ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_01_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_02_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_03_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_04_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_05_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_06_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_07_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_08_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_09_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_10_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_11_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/N_12_extent_v3.0.csv'] at ['2025-07-30 07:38:10', '2025-07-30 07:38:11', '2025-07-30 07:38:12', '2025-07-30 07:38:14', '2025-07-30 07:38:15', '2025-07-30 07:38:16', '2025-07-30 07:38:17', '2025-07-30 07:38:18', '2025-07-30 07:38:19', '2025-07-30 07:38:20', '2025-07-30 07:38:21', '2025-07-30 07:38:22']
• 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. [2025-10-30 22:43:39].

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. [2025-10-30 22:43:39].

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 ['2025-10-30 22:43:39', '2025-10-30 22:43:40', '2025-10-30 22:43:41', '2025-10-30 22:43:42', '2025-10-30 22:43:43', '2025-10-30 22:43:44', '2025-10-30 22:43:46', '2025-10-30 22:43:47', '2025-10-30 22:43:48', '2025-10-30 22:43:49', '2025-10-30 22:43:50', '2025-10-30 22:43:51']
• 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 v2.2

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 (v2.2, 2023), OSI-420, Data extracted from OSI SAF FTP server: 1979-present, Northern Hemisphere, accessed 2025-10-30 22:43:51

Acknowledgement: The OSI SAF Sea Ice Index v2.2 is made available at https://osisaf-hl.met.no/v2p2-sea-ice-index. The OSI SAF Sea Ice Index v2p1 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 ['osisaf_nh_sie_monthly.txt'] downloaded from ['ftp://osisaf.met.no/prod_test/ice/index/v2p2/nh/osisaf_nh_sie_monthly.txt'] at ['2025-10-30 22:43:51']
• 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 v2.3

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 (v2.2, 2023), OSI-420, Data extracted from OSI SAF FTP server: 1979-present, Northern Hemisphere, accessed 2025-10-27 18:58:23

Acknowledgement: The OSI SAF Sea Ice Index v2.2 is made available at https://osisaf-hl.met.no/v2p2-sea-ice-index. The OSI SAF Sea Ice Index v2p1 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 ['osisaf_nh_sie_monthly.txt'] downloaded from ['ftp://osisaf.met.no/prod_test/ice/index/v2p3/nh/osisaf_nh_sie_monthly.txt'] at ['2025-10-27 18:58:23']
• 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: 05f31449f65d783e62a802863eec0a54 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 ['2025-10-30 22:42:00']
• 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

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. [2025-07-30 07:38:24].

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. [2025-07-30 07:38:24].

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

• Data set created from file ['S_01_extent_v3.0.csv', 'S_02_extent_v3.0.csv', 'S_03_extent_v3.0.csv', 'S_04_extent_v3.0.csv', 'S_05_extent_v3.0.csv', 'S_06_extent_v3.0.csv', 'S_07_extent_v3.0.csv', 'S_08_extent_v3.0.csv', 'S_09_extent_v3.0.csv', 'S_10_extent_v3.0.csv', 'S_11_extent_v3.0.csv', 'S_12_extent_v3.0.csv'] downloaded from ['ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_01_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_02_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_03_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_04_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_05_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_06_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_07_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_08_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_09_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_10_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_11_extent_v3.0.csv', 'ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/S_12_extent_v3.0.csv'] at ['2025-07-30 07:38:24', '2025-07-30 07:38:25', '2025-07-30 07:38:26', '2025-07-30 07:38:27', '2025-07-30 07:38:28', '2025-07-30 07:38:29', '2025-07-30 07:38:30', '2025-07-30 07:38:31', '2025-07-30 07:38:32', '2025-07-30 07:38:33', '2025-07-30 07:38:34', '2025-07-30 07:38:36']
• 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. [2025-10-30 22:43:52].

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. [2025-10-30 22:43:52].

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 ['2025-10-30 22:43:52', '2025-10-30 22:43:54', '2025-10-30 22:43:55', '2025-10-30 22:43:56', '2025-10-30 22:43:57', '2025-10-30 22:43:58', '2025-10-30 22:43:59', '2025-10-30 22:44:00', '2025-10-30 22:44:01', '2025-10-30 22:44:02', '2025-10-30 22:44:03', '2025-10-30 22:44:04']
• 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 v2.2

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 (v2.1, 2020), OSI-420, Data extracted from OSI SAF FTP server: 1979-present, Northern Hemisphere, accessed 2025-10-30 22:44:05

Acknowledgement: The OSI SAF Sea Ice Index v2.1 is made available at https://osisaf-hl.met.no/v2p1-sea-ice-index. The OSI SAF Sea Ice Index v2p1 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 ['osisaf_sh_sie_monthly.txt'] downloaded from ['ftp://osisaf.met.no/prod_test/ice/index/v2p2/sh/osisaf_sh_sie_monthly.txt'] at ['2025-10-30 22:44:05']
• 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 v2.3

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 (v2.1, 2020), OSI-420, Data extracted from OSI SAF FTP server: 1979-present, Northern Hemisphere, accessed 2025-10-27 18:58:39

Acknowledgement: The OSI SAF Sea Ice Index v2.1 is made available at https://osisaf-hl.met.no/v2p1-sea-ice-index. The OSI SAF Sea Ice Index v2p1 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 ['osisaf_sh_sie_monthly.txt'] downloaded from ['ftp://osisaf.met.no/prod_test/ice/index/v2p3/sh/osisaf_sh_sie_monthly.txt'] at ['2025-10-27 18:58:39']
• 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: 3e233565ed4cc758b45f27385103ca6f 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 ['2025-10-30 22:41:29']

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: b912a6dfba382fb7f5962a3dd25e04a5 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 ['2025-10-30 22:42:00']

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: 398bb7c2d772aff253cb685900f54e74 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 [2025-09-08 23:32:00] 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_2025MMMM.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_2025MMMM.txt'] at ['2025-09-08 23:32:00']
• Zeroed series on July 2005 by subtracting the value for that month from all data values (see next entry)
• Added offset of 615.85 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 14:40:20']
• 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 ['2025-10-30 22:44:06']
• Zeroed series on July 2005 by subtracting the value for that month from all data values (see next entry)
• Added offset of 1453.376009 to all data values.
• Manually changed baseline to 2005-2005. Note that data values remain unchanged.

Velicogna et al.

Original data file (external link)

Citations:

• Geruo, A., Wahr, J., & Zhong, S. (2013). Computations of the viscoelastic response of a 3-D compressible Earth to surface loading: An application to Glacial Isostatic Adjustment in Antarctica and Canada. Geophysical Journal International, 192(2), 557–572.
• Ivins, E. R., T. S. James, J. Wahr, E. J. O Schrama, F. W. Landerer, and K. M. Simon (2013), Antarctic contribution to sea level rise observed by GRACE with improved GIA correction, J. Geophys. Res. Solid Earth, 118, 3126–3141, doi:10.1002/jgrb.50208.
• Loomis, B. D., Rachlin, K. E., & Luthcke, S. B. (2019). Improved Earth oblateness rate reveals increased ice sheet losses and mass-driven sea level rise. Geophysical Research Letters, 46, 6910–6917. https://doi.org/10.1029/2019GL082929.
• Peltier, W., Argus, D., & Drummond, R. (2015). Space geodesy constrains ice age terminal deglaciation: The global ICE-6G_C (VM5a) model. Journal of Geophysical Research: Solid Earth, 120, 450–487. https://doi.org/10.1002/2014JB011176.
• Simpson, M. J., Milne, G. A., Huybrechts, P., & Long, A. J. (2009). Calibrating a glaciological model of the Greenland ice sheet from the Last Glacial Maximum to present-day using field observations of relative sea level and ice extent. Quaternary Science Reviews, 28(17), 1631–1657.
• Sutterley, T. C., & Velicogna, I. (2019). Improved estimates of geocenter variability from time-variable gravity and ocean model outputs. Remote Sensing, 11(18), 2108.
• Velicogna I., Mohajerani Y., A G., Landerer F., Mouginot J., Noel B., Rignot E., Sutterley T., van den Broeke M., van Wessem J., Wiese D. (2020). Continuity of ice sheet mass loss in Greenland and Antarctica from the GRACE and GRACE Follow-On missions, Geophys. Res. Lett. 47, e2020GL087291.

Notes: Gravimetric (GRACE) ice mass time series for the Greenland and Antarctic Ice Sheets are calculated using spherical harmonics from JPL RL06v1, following Velicogna et al (2020). The degree-1 geocentre terms are calculated using Sutterley and Velicogna (2019), using Loomis et al (2020) C2.0 and C3.0 coefficients. The GRACE/GRACE-FO data are corrected for the long-term trend of glacial isostatic adjustment (GIA) from the solid earth using the regional IJ05 R2 GIA model (Ivins et al., 2013) over Antarctica and the regional Simpson et al. (2009) GIA model over Greenland. These regional GIA models do not include realistic GIA signal outside the ice sheets. For this reason, outside of Greenland and Antarctica, GIA corrections are based on Geruou et al. (2013) with the ICE6G ice history (Peltier et al., 2015).

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

• Data set created from file ['out_ts_filled_4_261_GIS.txt'] downloaded from [''] at ['2024-02-28 15:05:54']
• Zeroed series on July 2005 by subtracting the value for that month from all data values (see next entry)
• Added offset of -1982.552 to all data values.
• Manually changed baseline to 2005-2005. Note that data values remain unchanged.

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: 72498752ecc09c31c822a671d729f28a Copy
Format: BADC CSV format

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 ['2025-10-30 22:44:10']
• Calculated monthly average from values using arithmetic mean of all dates that fall within each month
• Selected years within the range 1990 to 2025.

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: 59484ab5ef81c9a8d24b0fb99930be20 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 ['2025-10-30 22:44:11']
• Selected years within the range 1950 to 2025.

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: 40d97e7bef8d89d7ff3bd29a713d5829 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 ['2025-10-30 22:44:09']
• Selected years within the range 1950 to 2025.

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: ffaf07d6c861991e5af4348b616aacd1 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 ['2025-10-30 22:44:11']
• 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 2025.

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 10:47:43']
• 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 2025.

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: a03490f1a1885de521f2d62d0a7579f8 Copy
Format: BADC CSV format

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 ['2025-10-30 22:44:12']
• Selected years within the range 1950 to 2025.

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: 7ed77217ed63854d020215d8144c63fe 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 ['2025-10-30 22:44:08']
• Selected years within the range 1950 to 2025.

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: f74e50cd013747e03cb9246662e50316 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 ['2025-10-30 22:44:07']
• Selected years within the range 2010 to 2025.

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: ce3a9080c09d14458ea064c865127edf 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 ['2025-10-30 22:44:07']
• Selected years within the range 2010 to 2025.