Improvements in the GISTEMP uncertainty model
Open accessAbstract
We outline a new and improved uncertainty analysis for the Goddard Institute for Space Studies Surface Temperature product version 4 (GISTEMP v4). Historical spatial variations in surface temperature anomalies are derived from historical weather station data and ocean data from ships, buoys, and other sensors. Uncertainties arise from measurement uncertainty, changes in spatial coverage of the station record, and systematic biases due to technology shifts and land cover changes. Previously published uncertainty estimates for GISTEMP included only the effect of incomplete station coverage. Here, we update this term using currently available spatial distributions of source data, state‐of‐the‐art reanalyses, and incorporate independently derived estimates for ocean data processing, station homogenization, and other structural biases. The resulting 95% uncertainties are near 0.05 °C in the global annual mean for the last 50 years and increase going back further in time reaching 0.15 °C in 1880. In addition, we quantify the benefits and inherent uncertainty due to the GISTEMP interpolation and averaging method. We use the total uncertainties to estimate the probability for each record year in the GISTEMP to actually be the true record year (to that date) and conclude with 87% likelihood that 2016 was indeed the hottest year of the instrumental period (so far).
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BackgroundDetected climatic change in global distribution of tropical cyclones
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Tradowsky, J. S., Philip, S. Y., Kreienkamp, F., Kew, S., Lorenz, P. B., Arrighi, J., Bettmann, T., Caluwaerts, S., Chan, S. C., Cruz, L. D., et al. (2023) · Climatic Change · doi:10.1007/s10584-023-03502-7 · Cited by 261 · see citing works
“…of anthropogenic climate change the 4-year low-pass filtered Global Mean Surface Temperature (GMST) from the National Aeronautics and Space Administration (NASA) Goddard Institute for Space Science (GISS) surface temperature analysis (GISTEMP; Hansen et al. 2010; Lenssen et al. 2019) is used.”
MethodArtificial intelligence reconstructs missing climate information
Kadow, C., Hall, D. M., & Ulbrich, U. (2020) · Nature Geoscience · doi:10.1038/s41561-020-0582-5 · Cited by 242 · see citing works
Evaluating the Performance of Past Climate Model Projections
Hausfather, Z., Drake, H. F., Abbott, T. H., & Schmidt, G. A. (2019) · Geophysical Research Letters · doi:10.1029/2019gl085378 · Cited by 238 · see citing works
“Five different observational temperature time series were used in this analysis—National Aeronautics and Space Administration GISTEMP (Lenssen et al., 2019), National Oceanic and Atmospheric Administration GlobalTemp (Vose et al., 2012), Hadley/UEA HadCRUT4 (Morice et al., 2012), Berkeley Earth…”
MethodSelf-citationNew improved Brazilian daily weather gridded data (1961–2020)
Xavier, A. C., Scanlon, B. R., King, C. W., & Alves, A. I. (2022) · International Journal of Climatology · doi:10.1002/joc.7731 · Cited by 234 · see citing works
“3.4.2 | BR-DWGD vs. GISTEMP temporal Tmean behaviour (1961–2019) We compared our BR-DWDG Tmean behaviour for the period 1961–2019 to Tmean from the Goddard Institute for Space Studies (GISS) surface temperature analysis (GISTEMP V4, Lenssen et al. (2019)) (Figure 9).”
MethodInfluentialSimulations for CMIP6 With the AWI Climate Model AWI‐CM‐1‐1
Semmler, T., Danilov, S. D., Gierz, P., Goessling, H., Hegewald, J., Hinrichs, C., Koldunov, N., Khosravi, N., Mu, L., Rackow, T., et al. (2020) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2019ms002009 · Cited by 243 · see citing works
“The purple line indicates the observed 2 m temperature anomaly from Goddard Institute for Space Studies (GISS) Surface Temperature Analysis (GISTEMP v4) (GISS, 2019; Hansen et al., 2010; Lenssen et al., 2019).”
BackgroundInitialized Earth System prediction from subseasonal to decadal timescales
Meehl, G. A., Richter, J. H., Teng, H., Capotondi, A., Cobb, K., Doblas-Reyes, F., Donat, M. G., England, M. H., Fyfe, J. C., Han, W., et al. (2021) · Nature Reviews Earth & Environment · doi:10.1038/s43017-021-00155-x · Cited by 231 · see citing works
The Recent Emergence of Arctic Amplification
England, M., Eisenman, I., Lutsko, N. J., & Wagner, T. J. W. (2021) · Geophysical Research Letters · doi:10.1029/2021gl094086 · Cited by 245 · see citing works
“We analyze five different historical temperature estimates for our analysis of near surface air temperature (SAT) trends over the instrumental record: GISTEMPv4 (GISTEMP, 2021; Lenssen et al., 2019), HadCRUT5 (Morice et al.”
MethodVerrall, B., & Pickering, C. M. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.141344 · Cited by 217 · see citing works
Land Surface Air Temperature Variations Across the Globe Updated to 2019: The CRUTEM5 Data Set
Osborn, T. J., Jones, P. D., Lister, D., Morice, C., Simpson, I., Winn, J., Hogan, E., & Harris, I. C. (2020) · Journal of Geophysical Research Atmospheres · doi:10.1029/2019jd032352 · Cited by 231 · see citing works
“Finally, the CRUTEM error model is quite comprehensive and was the first of its type applied to a global temperature data set (Brohan et al., 2006), though other datasets have increasingly comprehensive error models (e.g., GISTEMP; Lenssen et al., 2019).”
BackgroundMethodInfluentialTibetan Plateau's Lake Level and Volume Changes From NASA's ICESat/ICESat‐2 and Landsat Missions
Zhang, G., Chen, W., & Xie, H. (2019) · Geophysical Research Letters · doi:10.1029/2019gl085032 · Cited by 214 · see citing works
“03 °C/decade) according to the NASA GISS Surface Temperature Analysis (GISTEMP) data (GISTEMP‐ Team, 2019; Lenssen et al., 2019).”
MethodInfluentialAnnual Mean Arctic Amplification 1970–2020: Observed and Simulated by CMIP6 Climate Models
Chýlek, P., Folland, C. K., Klett, J. D., Wang, M., Hengartner, N., Lesins, G. B., & Dubey, M. K. (2022) · Geophysical Research Letters · doi:10.1029/2022gl099371 · Cited by 212 · see citing works
“The NASA GISS temperature set with 1,200 km smoothing radius (Lenssen et al., 2019) provides an AA record almost identical to HadCRUT5.”
MethodKosaka, Y., Kobayashi, S., Harada, Y., KOBAYASHI, C., Naoe, H., Yoshimoto, K., HARADA, M., Goto, N., Chiba, J., Miyaoka, K., et al. (2023) · Journal of the Meteorological Society of Japan Ser II · doi:10.2151/jmsj.2024-004 · Cited by 246 · see citing works
The most at-risk regions in the world for high-impact heatwaves
Thompson, V., Mitchell, D., Hegerl, G. C., Collins, M., Leach, N. J., & Slingo, J. M. (2023) · Nature Communications · doi:10.1038/s41467-023-37554-1 · Cited by 197 · see citing works
RETRACTED ARTICLE: A 10 per cent increase in global land evapotranspiration from 2003 to 2019
Pascolini‐Campbell, M., Reager, J. T., Chandanpurkar, H. A., & Rodell, M. (2021) · Nature · doi:10.1038/s41586-021-03503-5 · Cited by 201 · see citing works
RetractedProcess Drivers, Inter-Model Spread, and the Path Forward: A Review of Amplified Arctic Warming
Taylor, P. C., Boeke, R. C., Boisvert, L. N., Feldl, N., Henry, M., Huang, Y., Langen, P. L., Liu, W., Pithan, F., Sejas, S. A., et al. (2022) · Frontiers in Earth Science · doi:10.3389/feart.2021.758361 · Cited by 182 · see citing works
Danielson, S. L., Ahkinga, O., Ashjian, C. J., Basyuk, E. O., Cooper, L. W., Eisner, L. B., Farley, E. V., Iken, K. B., Grebmeier, J. M., Juranek, L. W., et al. (2020) · Deep Sea Research Part II Topical Studies in Oceanography · doi:10.1016/j.dsr2.2020.104781 · Cited by 179 · see citing works
Leach, N. J., Jenkins, S., Nicholls, Z., Smith, C., Lynch, J., Cain, M. L., Walsh, T., Wu, B., Tsutsui, J., & Allen, M. R. (2021) · Geoscientific model development · doi:10.5194/gmd-14-3007-2021 · Cited by 202 · see citing works
2023 summer warmth unparalleled over the past 2,000 years
Esper, J., Torbenson, M. C. A., & Büntgen, U. (2024) · Nature · doi:10.1038/s41586-024-07512-y · Cited by 186 · see citing works
“These data are highly similar to other products 21,22 (Extended Data Fig.”
Paris Climate Agreement passes the cost-benefit test
Glanemann, N., Willner, S. N., & Levermann, A. (2020) · Nature Communications · doi:10.1038/s41467-019-13961-1 · Cited by 173 · see citing works
Greenhouse Gas Emissions Trends and Mitigation Measures in Australian Agriculture Sector—A Review
Panchasara, H. V., Samrat, N. H., & Islam, N. (2021) · Agriculture · doi:10.3390/agriculture11020085 · Cited by 171 · see citing works
“Monthly global mean surface temperature over 140 years [11,12].”
BackgroundTrends and variability in polar sea ice, global atmospheric circulations, and baroclinicity
Simmonds, I., & Li, M. (2021) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14673 · Cited by 172 · see citing works
CMIP6 Historical Simulations (1850–2014) With GISS‐E2.1
Miller, R. L., Schmidt, G. A., Nazarenko, L., Bauer, S. E., Kelley, M., Ruedy, R. A., Russell, G. L., Ackerman, A. S., Aleinov, I., Bauer, M., et al. (2020) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2019ms002034 · Cited by 172 · see citing works
“…4 Observations Used in Model Evaluation Variable Observation Source Citation tas GISS surface temperature analysis data.giss.nasa.gov/gistemp Lenssen et al. (2019) (GISTEMP) v.4, accessed 2020-07-29 msu tls, tmt MSU/AMSU brightness temperature Remote Sensing Systems v.4.0 Mears and Wentz…”
BackgroundMethodInfluentialSelf-citationvan Noije, T., Bergman, T., Sager, P. L., O’Donnell, D., Makkonen, R., Ageitos, M. G., Döscher, R., Fladrich, U., von Hardenberg, J., Keskinen, J., et al. (2021) · Geoscientific model development · doi:10.5194/gmd-14-5637-2021 · Cited by 184 · see citing works
Zhu, S., Delmo, E. P., Li, T., Qin, X., Tian, J., Zhang, L., & Shao, M. (2021) · Advanced Materials · doi:10.1002/adma.202005484 · Cited by 162 · see citing works
Plant-microbe interactions in the phyllosphere: facing challenges of the anthropocene
Perreault, R., & Laforest‐Lapointe, I. (2021) · The ISME Journal · doi:10.1038/s41396-021-01109-3 · Cited by 156 · see citing works
Taiwan Earth System Model Version 1: description and evaluation of mean state
Lee, W., Wang, Y., Shiu, C., Tsai, I., Tu, C., Lan, Y.-Y., Chen, J., Pan, H., & Hsu, H. (2020) · Geoscientific model development · doi:10.5194/gmd-13-3887-2020 · Cited by 155 · see citing works
Evaluation of Leading Modes of Climate Variability in the CMIP Archives
Fasullo, J., Phillips, A. S., & Deser, C. (2020) · Journal of Climate · doi:10.1175/jcli-d-19-1024.1 · Cited by 145 · see citing works
“…from the limited resolution of global models (e.g., Bojariu and Giorgi 2005) and errors in the simulated base state, particularly in the tropics (Capotondi et al. 2015) where coupled feedbacks are influenced by biases in winds and ocean structure (Vannière et al. 2013) and clouds (Li and Xie 2012).”
BackgroundImpacts and risks of “realistic” global warming projections for the 21st century
Scafetta, N. (2024) · Geoscience Frontiers · doi:10.1016/j.gsf.2023.101774 · Cited by 143 · see citing works
The ICON Earth System Model Version 1.0
Jungclaus, J. H., Lorenz, S. J., Schmidt, H., Brovkin, V. A., Brüggemann, N., Chegini, F., Crüger, T., de Vrese, P., Gayler, V., Giorgetta, M. A., et al. (2022) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2021ms002813 · Cited by 143 · see citing works
“Time series of surface temperature relative to the respective 1850– 1899 averages over (a) the globe, (b) the northern hemisphere, and (c) the southern hemisphere for (red-orange) the ICON-ESM historical ensemble, and observational compilations by (blue) the Goddard Institute for Space Studies Surface Temperature prod…”
BackgroundThe Macroeconomic Impact of Climate Change: Global vs. Local Temperature
Bilal, A., & Känzig, D. R. (2024) · National Bureau of Economic Research · doi:10.3386/w32450 · Cited by 160 · see citing works
An integrated approach to quantifying uncertainties in the remaining carbon budget
Matthews, H. D., Tokarska, K. B., Rogelj, J., Smith, C., MacDougall, A. H., Haustein, K., Mengis, N., Sippel, S., Forster, P. M. D. F., & Knutti, R. (2021) · Communications Earth & Environment · doi:10.1038/s43247-020-00064-9 · Cited by 141 · see citing works
Nordli, Ø., Wyszyński, P., Gjelten, H. M., Isaksen, K., Łupikasza, E. B., Niedźwiedź, T., & Przybylak, R. (2020) · Polar Research · doi:10.33265/polar.v39.3614 · Cited by 138 · see citing works
“This amounts to more than twice the Arctic average (0.8 °C/decade, north of 66°N (NOAA-ESRL 2019) and is about seven times the global average (0.2 °C/decade), based on the latest GISTEMP data (GISTEMP Team 2019; Lenssen et al. 2019).”
BackgroundInfluentialThe State-of-the-Art of Urban Climate Change Modeling and Observations
Hamdi, R., Kusaka, H., Doan, Q., Cai, P., He, H., Luo, G., Kuang, W., Caluwaerts, S., Duchêne, F., Schaeybroeck, B. V., et al. (2020) · Earth Systems and Environment · doi:10.1007/s41748-020-00193-3 · Cited by 137 · see citing works
“3 Change in the annual-mean surface temperature over the period 1950–2018 based on local linear trend retrieved from the GISTEMP data (Lenssen et al. 2019).”
MethodHuman influence on joint changes in temperature, rainfall and continental aridity
Bonfils, C., Santer, B. D., Fyfe, J. C., Marvel, K., Phillips, T. J., & Zimmerman, S. H. (2020) · Nature Climate Change · doi:10.1038/s41558-020-0821-1 · Cited by 136 · see citing works
Wilcox, L. J., Liu, Z., Samset, B. H., Hawkins, E., Lund, M. T., Nordling, K., Undorf, S., Bollasina, M. A., Ekman, A. M. L., Krishnan, S., et al. (2020) · Atmospheric chemistry and physics · doi:10.5194/acp-20-11955-2020 · Cited by 133 · see citing works
Huffman, G. J., Adler, R. F., Behrangi, A., Bolvin, D. T., Nelkin, E. J., Gu, G., & Ehsani, M. R. (2023) · Journal of Climate · doi:10.1175/jcli-d-23-0123.1 · Cited by 152 · see citing works
Huang, B., Menne, M. J., Boyer, T., Freeman, E., Gleason, B. E., Lawrimore, J. H., Liu, C., Rennie, J., Schreck, C. J., Sun, F., et al. (2019) · Journal of Climate · doi:10.1175/jcli-d-19-0395.1 · Cited by 134 · see citing works
Self-citationSousa, P. M., Barriopedro, D., García‐Herrera, R., Ordóñez, C., Soares, P. M. M., & Trigo, R. M. (2020) · Communications Earth & Environment · doi:10.1038/s43247-020-00048-9 · Cited by 139 · see citing works
On the curious case of the recent decade, mid-spring precipitation deficit in central Europe
Ionita-Scholz, M., Nagavciuc, V., Kumar, R., & Rakovec, O. (2020) · npj Climate and Atmospheric Science · doi:10.1038/s41612-020-00153-8 · Cited by 128 · see citing works
Equilibrium climate sensitivity above 5 °C plausible due to state-dependent cloud feedback
Bjordal, J., Storelvmo, T., Alterskjær, K., & Carlsen, T. (2020) · Nature Geoscience · doi:10.1038/s41561-020-00649-1 · Cited by 122 · see citing works
Cai, Z., You, Q., Wu, F., Chen, H. W., Chen, D., & Cohen, J. L. (2021) · Journal of Climate · doi:10.1175/jcli-d-20-0791.1 · Cited by 123 · see citing works
Anthropogenic forcing and response yield observed positive trend in Earth’s energy imbalance
Raghuraman, S. P., Paynter, D. J., & Ramaswamy, V. (2021) · Nature Communications · doi:10.1038/s41467-021-24544-4 · Cited by 129 · see citing works
Recent pronounced warming on the Mongolian Plateau boosted by internal climate variability
Cai, Q., Chen, W., Chen, S., Xie, S., Piao, J., Ma, T., & Lan, X. (2024) · Nature Geoscience · doi:10.1038/s41561-024-01377-6 · Cited by 122 · see citing works
“…the period 1840–2020 53 ; (3) the NASA Goddard Institute for Space Studies Surface Temperature, version 4 (GISTEMP v.4), over the period 1880–2020 54 ; and (4) the National Oceanic and Atmospheric Administration (NOAA) Global Surface Temperature, version 5.0 (NOAAGlobalTemp v.5), over the period…”
InfluentialEmergent constraints on future precipitation changes
Shiogama, H., Watanabe, M., Kim, H., & Hirota, N. (2022) · Nature · doi:10.1038/s41586-021-04310-8 · Cited by 114 · see citing works
Bilgili, M. S., Tümse, S., & Nar, S. (2024) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-024-09390-y · Cited by 129 · see citing works
Bilbao, R. A. F., Wild, S., Ortega, P., Navarro, J. C. A., Arsouze, T., Bretonnière, P.-A., Caron, L., Castrillo, M., Cruz-García, R., Cvijanović, I., et al. (2021) · Earth System Dynamics · doi:10.5194/esd-12-173-2021 · Cited by 110 · see citing works
Zhu, J., Otto‐Bliesner, B. L., Brady, E. C., Gettelman, A., Bacmeister, J. T., Neale, R., Poulsen, C. J., Shaw, J., McGraw, Z. S., & Kay, J. E. (2022) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2021ms002776 · Cited by 119 · see citing works
Implementing Full Spatial Coverage in NOAA’s Global Temperature Analysis
Vose, R. S., Huang, B., Yin, X., Arndt, D. S., Easterling, D. R., Lawrimore, J. H., Menne, M. J., Sánchez-Lugo, A., & Zhang, H. (2021) · Geophysical Research Letters · doi:10.1029/2020gl090873 · Cited by 115 · see citing works
“, 2013); NASA (GISTEMP; Lenssen et al., 2019); and Cowtan and Way (2014).”
BackgroundInfluentialSelf-citationIntensification of the global water cycle and evidence from ocean salinity: a synthesis review
Yu, L., Josey, S. A., Bingham, F. M., & Lee, T. (2020) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14354 · Cited by 108 · see citing works
Xing, Z., Li, Z.-L., Duan, S., Liu, X., Zheng, X., Leng, P., Gao, M., Zhang, X., & Shang, G. (2021) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2021.05.017 · Cited by 107 · see citing works
Global labor loss due to humid heat exposure underestimated for outdoor workers
Parsons, L. A., Masuda, Y. J., Kroeger, T., Shindell, D. T., Wolff, N. H., & Spector, J. T. (2021) · Environmental Research Letters · doi:10.1088/1748-9326/ac3dae · Cited by 107 · see citing works
Ades, M., Adler, R., Allan, R. J., Allan, R. P., Anderson, J., Argüez, A., Arosio, C., Augustine, J. A., Azorín-Molina, C., Barichivich, J., et al. (2020) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-20-0104.1 · Cited by 104 · see citing works
Papalexiou, S. M., Rajulapati, C. R., Clark, M., & Lehner, F. (2020) · Earth s Future · doi:10.1029/2020ef001667 · Cited by 109 · see citing works
“gov/gistemp), built by combining the NOAA GHCN v4 database for land (meteorological stations), and the ERSST v5 for ocean areas (Hansen et al., 2010; Lenssen et al., 2019); (2) Berkeley Earth Surface Temperatures (Berkeley; http://berkeleyearth.”
MethodImplications of CMIP6 Projected Drying Trends for 21st Century Amazonian Drought Risk
Parsons, L. A. (2020) · Earth s Future · doi:10.1029/2020ef001608 · Cited by 101 · see citing works
“…air temperature variability over land is also examined using Goddard Institute of Space Studies (GISS) surface temperature analysis (GISTEMP; Lenssen et al., 2019), Climate Research Unit (CRU) Air Temperature Anomalies Version 4.2.0 (CRUTEMv4; Jones et al., 2012), and UDEL temperature…”
InfluentialCompensation Between Cloud Feedback and Aerosol‐Cloud Interaction in CMIP6 Models
Wang, C., Soden, B. J., Yang, W., & Vecchi, G. A. (2021) · Geophysical Research Letters · doi:10.1029/2020gl091024 · Cited by 100 · see citing works
“The global analysis of surface temperature observations is obtained from the GISS Surface Temperature Analysis (GISTEMP v4) (Lenssen et al., 2019).”
MethodA NASA GISTEMPv4 Observational Uncertainty Ensemble
Lenssen, N., Schmidt, G. A., Hendrickson, M., Jacobs, P., Menne, M. J., & Ruedy, R. A. (2024) · Journal of Geophysical Research Atmospheres · doi:10.1029/2023jd040179 · Cited by 120 · see citing works
“However, as shown in Lenssen et al. (2019), global and large-scale GISTEMP uncertainty estimates derived from ERA5 agree with the estimates derived from the JRA-55 and MERRA2 reanalyses.”
InfluentialSelf-citationSteady global surface warming from 1973 to 2022 but increased warming rate after 1990
Samset, B. H., Zhou, C., Fuglestvedt, J. S., Lund, M. T., Marotzke, J., & Zelinka, M. D. (2023) · Communications Earth & Environment · doi:10.1038/s43247-023-01061-4 · Cited by 100 · see citing works
Reduced probability of ice-free summers for 1.5 °C compared to 2 °C warming
Jahn, A. (2018) · Nature Climate Change · doi:10.1038/s41558-018-0127-8 · Cited by 97 · see citing works
Progress in adsorption capacity of nanomaterials for carbon dioxide capture: A comparative study
Firdaus, R. M., Desforges, A., Mohamed, A. R., & Vigolo, B. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.129553 · Cited by 92 · see citing works
Persistent Ross Sea Freshening From Imbalance West Antarctic Ice Shelf Melting
Jacobs, S. S., Giulivi, C. F., & Dutrieux, P. (2022) · Journal of Geophysical Research Oceans · doi:10.1029/2021jc017808 · Cited by 92 · see citing works
Steady threefold Arctic amplification of externally forced warming masked by natural variability
Zhou, W., Leung, L.-Y. R., & Lu, J. (2024) · Nature Geoscience · doi:10.1038/s41561-024-01441-1 · Cited by 110 · see citing works
“HadCRUT5 is produced by blending data from CRUTEM5 (land) and HadSST4 (ocean); GISTEMP4 is produced by blending data from NOAA GHCN v4 (land) and ERSST v5 (ocean); the Berkeley Earth Surface Temperatures (BEST) is a merged land-ocean dataset that combines land temperature records with an interpolated version of HadSST…”
InfluentialOn the attribution of industrial-era glacier mass loss to anthropogenic climate change
Roe, G. H., Christian, J. E., & Marzeion, B. (2021) · The Cryosphere · doi:10.5194/tc-15-1889-2021 · Cited by 90 · see citing works
Climate change and extreme weather: A review focusing on the continental United States
Robinson, W. A. (2021) · Journal of the Air & Waste Management Association · doi:10.1080/10962247.2021.1942319 · Cited by 89 · see citing works
Future Climate Change Under SSP Emission Scenarios With GISS‐E2.1
Nazarenko, L. S., Tausnev, N., Russell, G. L., Rind, D., Miller, R. L., Schmidt, G. A., Bauer, S. E., Kelley, M., Ruedy, R., Ackerman, A. S., et al. (2022) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2021ms002871 · Cited by 104 · see citing works
Self-citationArctic open-water periods are projected to lengthen dramatically by 2100
Crawford, A. D., Stroeve, J. C., Smith, A., & Jahn, A. (2021) · Communications Earth & Environment · doi:10.1038/s43247-021-00183-x · Cited by 84 · see citing works
Capture of carbon dioxide using solid carbonaceous and non-carbonaceous adsorbents: a review
Sharma, H., & Dhir, A. (2020) · Environmental Chemistry Letters · doi:10.1007/s10311-020-01118-2 · Cited by 81 · see citing works
Wehrli, K., Hauser, M., & Seneviratne, S. I. (2020) · Earth System Dynamics · doi:10.5194/esd-11-855-2020 · Cited by 83 · see citing works
- Authors
- Lenssen, N. J. L., Schmidt, G. A., Hansen, J. E., Menne, M. J., Persin, A., Ruedy, R., & Zyss, D.
- Affiliations
- Goddard Institute for Space Studies (US)
- Columbia University (US)
- National Oceanic and Atmospheric Administration (US)
- Corresponding author
- Lenssen, Nathan J. L.
- Venue
- Journal of Geophysical Research: Atmospheres
- Publisher
- American Geophysical Union (AGU)
- Published
- 2019-06-24
- Volume
- 124
- Issue
- 12
- Pages
- 6307-6326
- ISSN
- 0148-0227 (ISSN-L)
- 2169-897X
- 2169-8996
- OpenAlex
- W2946160190
- Cited by
- 962
- References
- 48
- Citations by year
- 2026: 65 · 2025: 101 · 2024: 153 · 2023: 159 · 2022: 162 · 2021: 189 · 2020: 114 · 2019: 18 · 2018: 1
- FWCI
- 62.15
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Geophysical Research Atmospheres (publishedVersion)
- NOAA Institutional Repository (publishedVersion)
- Funders
- National Science Foundation (NSF DGE 16-44869)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Physical Sciences › Environmental Science › Environmental Engineering › Urban Heat Island Mitigation
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Environmental Impact
- Keywords
- surface temperature anomalies, uncertainty analysis, instrumental temperature records, station homogenization, station coverage, ocean data processing, systematic bias, land cover change
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