Hi! I’m a climate scientist trying to visualize the signal from a lot of noise. My research interests coincide with disentangling patterns of climate change from climate variability using data-driven methods, especially in the Arctic. I also spend a lot of time thinking about improving science communication and accessibility through storytelling with engaging visualizations.
Global average surface temperature anomalies for centered running 60-month periods. Monthly anomalies are calculated relative to pre-industrial levels (1850-1900 – outlined in the IPCC Special Report on Global Warming of 1.5°C). Data is from Berkeley Earth Surface Temperatures (BEST; http://berkeleyearth.org/data/). Graphic updated using data through January 2024.Monthly global average surface temperature anomalies, which are calculated relative to pre-industrial levels (1850-1900 – outlined in the IPCC Special Report on Global Warming of 1.5°C). Data is from Berkeley Earth Surface Temperatures (BEST; http://berkeleyearth.org/data/). Graphic updated using data through January 2024. Monthly temperature anomalies are now consistently at least 1°C above pre-industrial levels, which is why the annotation color is turned from blue to red.Carbon dioxide levels over the last 800,000 years, which are merged from ice cores (https://www.nature.com/articles/nature06949 & https://data.csiro.au/collection/csiro:37077) and recent Mauna Loa observations (starting in 1958). Updated 12/15/2023.Graphic showing CO2-equivalent (CO2-e) atmospheric abundance (left) and radiative forcing (right) from 1979 to 2022 using data from https://gml.noaa.gov/aggi/aggi.html. CO2-e is the amount of carbon dioxide that would be needed to be equivalent to the average radiative forcing from all of the greenhouse gases combined. The direct radiative forcing is calculated for nearly all greenhouse gases relative to a 1750 baseline period. Radiative forcing is a measure of the perturbation (warming) to the climate system from greenhouse gases (i.e., Earth’s energy imbalance in the atmosphere). For more information, see https://gml.noaa.gov/ccgg/ghgpower/.Decadal trends in annual mean surface air temperatures over land areas from 1900 to 2023, 1940 to 2023, 1980 to 2023, and 2000 to 2023. Data are from NASA GISS Surface Temperature Analysis (GISTEMPv4; https://data.giss.nasa.gov/gistemp/). Graphic was updated on 1/12/2024.Global average surface temperature anomalies for centered running 60-month periods (white line) compared to global average surface temperature anomalies over only land areas for centered running 60-month periods (red line). Monthly anomalies are calculated relative to pre-industrial levels (1850-1900 – outlined in the IPCC Special Report on Global Warming of 1.5°C). Data is from Berkeley Earth Surface Temperatures (BEST; http://berkeleyearth.org/data/). Graphic updated using data through January 2024.Global average surface temperature anomalies for centered running 60-month periods (white line) compared to global average surface temperature anomalies over only land areas for centered running 60-month periods (red line) and global average surface temperature anomalies over only ocean areas for centered running 60-month periods (blue line). Monthly anomalies are calculated relative to pre-industrial levels (1850-1900 – outlined in the IPCC Special Report on Global Warming of 1.5°C). Data is from Berkeley Earth Surface Temperatures (BEST; http://berkeleyearth.org/data/). Graphic updated using data through January 2024.Monthly average surface temperature anomalies for only extratropical land areas (67°S to 67°N), which are calculated relative to pre-industrial levels (1850-1900 – outlined in the IPCC Special Report on Global Warming of 1.5°C). Data is from Berkeley Earth Surface Temperatures (BEST; http://berkeleyearth.org/data/). Graphic updated using data through January 2024.Average surface temperature anomalies for extratropical land areas (67°S to 67°N) centered running 60-month periods (white line) compared to average surface temperature anomalies over only Northern Hemisphere land areas for centered running 60-month periods (orange line) and average surface temperature anomalies over only Southern Hemisphere land areas for centered running 60-month periods (purple line). Monthly anomalies are calculated relative to pre-industrial levels (1850-1900 – outlined in the IPCC Special Report on Global Warming of 1.5°C). Data is from Berkeley Earth Surface Temperatures (BEST; http://berkeleyearth.org/data/). Graphic updated using data through January 2024.This graphic shows monthly data from January 1984 through January 2024/April 2024. The first graph is a 12-month running mean of global mean surface temperature anomalies using ERA5 data. Anomalies are computed relative to a 1991-2020. The other three graphs show carbon dioxide abundance, global methane abundance, and global nitrous oxide abundance (https://gml.noaa.gov/ccgg/trends/). Graphic updated 5/7/2024.Graph showing the annual mean growth rate in atmospheric carbon dioxide at Mauna Loa Observatory from 1959 through 2023. The uncertainty in the annual growth rate is approximately 0.11 ppm per year. A linear trend line (dashed) is also shown over the entire period. Data from https://gml.noaa.gov/ccgg/trends/gr.html. Graphic updated on 3/18/2024.Annual carbon dioxide levels from a merged ice-core record (Scripps CO2 program; https://scrippsco2.ucsd.edu/data/atmospheric_co2/icecore_merged_products.html) over the period of years 1600 to 2021.Globally averaged near-surface (2-m) air temperature for each year from 1940 to 2023. Data is from ERA5 reanalysis. The actual global temperature in 2023 was approximately 15.0°C (59.0°F). Updated 1/21/2024.Globally averaged near-surface (2-m) air temperature anomalies for each month from January 1979 to April 2024. Data is from ERA5 reanalysis using a 1981-2010 reference period and smoothed with a 12-month running mean. Updated 5/7/2024.Change in annual mean global ocean heat content (vertical integral between 0-2000 m) since 1955. Data is updated through 2023. The current rate of change is approximately 6.18 × 10²² joules per decade. Data are from https://www.data.jma.go.jp/gmd/kaiyou/english/ohc/ohc_global_en.html. Graphic was produced on 2/25/2024.Global mean sea level anomalies from 1993 to 2024 using satellite altimetry data from TOPEX/Poseidon, Jason-1, OSTM/Jason-2, Jason-3, and Sentinel-6. See more information from https://climate.nasa.gov/vital-signs/sea-level/. The baseline is 1996-2016. The current rate of change is approximately 3.24 mm per year. Data available through 16 January 2024. Graphic was produced on 5/3/2024.Change in annual mean upper global ocean heat content (vertical integral between 0-700 m) since 1955. Data is updated through 2023. The current rate of change is approximately 6.18 × 10²² joules per decade in the 0-2000 m layer. Data are from https://www.data.jma.go.jp/gmd/kaiyou/english/ohc/ohc_global_en.html. Graphic was produced on 2/25/2024.Decadal trends in annual mean surface air temperatures over land areas from 1990 to 2023. Data are from NASA GISS Surface Temperature Analysis (GISTEMPv4; https://data.giss.nasa.gov/gistemp/). Graphic was updated on 1/12/2024.Decadal trends in annual mean precipitation rate over land areas from 1990 to 2023. Data are from the Global Precipitation Climatology Project Monthly Analysis Product (GPCP; https://psl.noaa.gov/data/gridded/data.gpcp.html).Decadal trends (linear) in annual mean sea surface temperatures from 1982 to 2023. Data are from OISSTv2.1 (https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html). Graphic was produced on 1/20/2024.Cumulative change in the mass balance of reference glaciers around the world through 2023. Change is measured relative to 1970 levels. More information on the details and methods can be found at https://wgms.ch/global-glacier-state/. The units are equivalent to tonnes per square meter (1,000 kg/m²). Graphic updated 2/16/2024.Change in land ice mass since 2002 (Right: Greenland, Left: Antarctica). Data is measured by NASA’s Gravity Recovery and Climate Experiment (GRACE/GRACE-FO) satellites with observations through February 2024. Additional information can be found at https://climate.nasa.gov/vital-signs/land-ice/. Graphic was updated on 5/3/2024.Zonal-mean vertical cross-section (latitude vs. height) of decadal trends in annual mean temperature (90°S-90°N). Trends are calculated using ERA5 reanalysis over the 1979 to 2022 period.Zonal-mean vertical cross-section (latitude vs. height) of decadal trends in seasonal mean temperature (90°S-90°N) (DJF; December-February, MAM; March-May, JJA; June-August, SON; September-November). Trends are calculated using ERA5 reanalysis over the 1979 to 2022 period.Annual mean surface air temperature anomalies for the Arctic (67-90°N; white line), the global average over land areas (90°S-90°N; red line), and the global average over ocean areas (90°S-90°N; blue line) from 1900 to 2023. Linear trend lines (dashed) are also shown over the 1990 to 2023 period. GISS Surface Temperature Analysis (GISTEMPv4) is available from 1880 to 2023 at https://data.giss.nasa.gov/gistemp/. Tools including the NOAA/ESRL Physical Sciences Division Web-based Reanalysis Intercomparison Tool: Monthly/Seasonal Time Series (WRIT) have been used for the construction of this plot. Analysis will updated as annual data becomes available. Graphic was updated on 1/13/2024.Monthly zonal mean (averaged over longitude) surface air temperature anomalies from 1880 through 2023. The y-axis is latitude, and the x-axis is time. The data are smoothed using a 12-month running mean from NASA GISS Surface Temperature Analysis (GISTEMPv4; https://data.giss.nasa.gov/gistemp/) with a reference period of 1951-1980. Graphic was updated on 1/12/2024.Zonal-mean (averaged over longitude) temperature anomalies for each year from 1900 to 2023. The x-axis is latitude (not scaled by distance), and the y-axis is the temperature anomaly. Data is from Berkeley Earth Surface Temperatures (BEST; http://berkeleyearth.org/data/) using a reference period of 1951-1980. Graphic was updated on 1/19/2024.Animation of surface air temperature anomalies over only land areas for each year from 1924 to 2023. Data are from NASA GISS Surface Temperature Analysis (GISTEMPv4; https://data.giss.nasa.gov/gistemp/) with a reference period of 1951-1980. Graphic was updated on 1/12/2024.Annual mean surface air temperature anomalies for the entire globe from 1880 through 2023. A 5-year lowess smoothing line is also shown for this time series. See more on this temperature variability in Labe and Barnes (2022) (https://doi.org/10.1029/2022GL098173). GISS Surface Temperature Analysis (GISTEMPv4) is available from 1880 to 2023 at https://data.giss.nasa.gov/gistemp/. Analysis will updated with each year.Reconstructed late-summer (August) Arctic sea ice extent during the last 1450 years. Sea ice extent data have been smoothed using a 40-year running mean (light blue). The shading shows the 95% confidence interval (dark blue). Smoothed observational data are compared using a dashed line (red). This figure is reproduced from Figure 3a in Kinnard et al. 2011 (Nature: https://www.nature.com/articles/nature10581).Annual mean surface air temperature anomalies over the Arctic during the satellite-era. Data is from Berkeley Earth Surface Temperatures (BEST; http://berkeleyearth.org/data/) using a reference period of 1951-1980. Graphic updated from 1979 through 2023 on 1/19/2024.Change in annual mean precipitation rate anomalies from 1979 through 2023 for the global average. Anomalies in each year are calculated to a 1981-2010 climatological reference period. Data are from GPCP (https://psl.noaa.gov/data/gridded/data.gpcp.html), ERA5 (https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means?tab=overview), and JRA-55 (https://jra.kishou.go.jp/JRA-55/index_en.html). Graphic was updated on 1/18/2024.Change in annual mean precipitable water anomalies from 1940 through 2023 for the global average. Anomalies in each year are calculated to a 1981-2010 climatological reference period. The linear least squares trend line is also displayed over this period. Data are from https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means?tab=overview. Graphic was updated on 1/18/2024.Change in annual mean specific humidity (2-m height) anomalies from 1979 through 2019 for the global average (green dashed line), global average over land areas (thick red line), and global average over ocean areas (blue thin line). Data are from https://www.metoffice.gov.uk/hadobs/hadisdh/. Anomalies in each year are calculated to a 1981-2010 climatological reference period. Linear least squares trend lines are also displayed for each global average.Zonal-mean vertical cross-section (latitude vs. height) of decadal trends in annual mean geopotential heights (90°S-90°N). Trends are calculated using ERA5 reanalysis over the 1979 to 2022 period.Zonal-mean vertical cross-section (latitude vs. height) of decadal trends in seasonal mean geopotential heights (90°S-90°N) (DJF; December-February, MAM; March-May, JJA; June-August, SON; September-November). Trends are calculated using ERA5 reanalysis over the 1979 to 2022 period.Zonal-mean vertical cross-section (latitude vs. height) of decadal trends in annual zonal wind (90°S-90°N). Trends are calculated using ERA5 reanalysis over the 1979 to 2022 period. The climatological zonal-mean zonal wind is shown with gray contours.Zonal-mean vertical cross-section (latitude vs. height) of decadal trends in seasonal zonal wind (90°S-90°N) (DJF; December-February, MAM; March-May, JJA; June-August, SON; September-November). Trends are calculated using ERA5 reanalysis over the 1979 to 2022 period. The climatological zonal-mean zonal wind is shown with gray contours.
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[19] Eischeid, J.K., M.P. Hoerling, X.-W. Quan, A. Kumar, J. Barsugli, Z.M. Labe, K.E. Kunkel, C.J. Schreck III, D.R. Easterling, T. Zhang, J. Uehling, and X. Zhang (2023). Why has the summertime central U.S. warming hole not disappeared? Journal of Climate, DOI:10.1175/JCLI-D-22-0716.1 [HTML][BibTeX] [Fox 32 Chicago][NOAA CPO][NOAA Climate(dot)gov][Wired]
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[5] Thoman, R.L., U. Bhatt, P. Bieniek, B. Brettschneider, M. Brubaker, S. Danielson, Z.M. Labe, R. Lader, W. Meier, G. Sheffield, and J. Walsh (2019): The record low Bering Sea ice extent in 2018: Context, impacts and an assessment of the role of anthropogenic climate change [in “Explaining Extreme Events of 2018 from a Climate Perspective”]. Bull. Amer. Meteor. Soc, DOI:10.1175/BAMS-D-19-0175.1 [HTML][BibTeX] [Press Release]
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[3]Labe, Z.M., Y. Peings, and G. Magnusdottir (2018), Contributions of ice thickness to the atmospheric response from projected Arctic sea ice loss, Geophysical Research Letters, DOI:10.1029/2018GL078158 [HTML][BibTeX] [Plain Language Summary][Arctic Today]
[2]Labe, Z.M., G. Magnusdottir, and H.S. Stern (2018), Variability of Arctic sea ice thickness using PIOMAS and the CESM Large Ensemble, Journal of Climate, DOI:10.1175/JCLI-D-17-0436.1 [HTML][BibTeX] [Plain Language Summary]
The views presented here only reflect my own. These figures may be freely distributed (with credit). Information about the data can be found on my references page and methods page.
