Cited by 962Climate variability and modelsUrban Heat Island MitigationClimate Change and Environmental Impact

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Improvements in the GISTEMP Uncertainty Model

Open access

Lenssen, Nathan J. L., Schmidt, Gavin A., Hansen, James E., Menne, Matthew J., Persin, Avraham, Ruedy, Reto, Zyss, Daniel·2019·Journal of Geophysical Research: Atmospheres

DOI 10.1029/2018jd029522

Open this paper in CoChat — free account Open PDF

Abstract

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).

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1029/2018jd029522

Cites

48 of 48 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A. M., Takacs, L. L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R. H., et al. (2017) · Journal of Climate · doi:10.1175/jcli-d-16-0758.1 · Cited by 9,261
The JRA-55 Reanalysis: General Specifications and Basic Characteristics
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi, K., Kamahori, H., Kobayashi, C., Endo, H., et al. (2015) · Journal of the Meteorological Society of Japan Ser II · doi:10.2151/jmsj.2015-001 · Cited by 4,768
Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons
Huang, B., Thorne, P., Banzon, V. F., Boyer, T., Chepurin, G. A., Lawrimore, J. H., Menne, M. J., Smith, T. M., Vose, R. S., & Zhang, H. (2017) · Journal of Climate · doi:10.1175/jcli-d-16-0836.1 · Cited by 3,245
Self-citation
Global surface temperature change
Hansen, J., Ruedy, R., Sato, M., & Lo, K. (2010) · Reviews of Geophysics · doi:10.1029/2010rg000345 · Cited by 3,081 · cited 8×
“As shown in Hansen et al. (2010), the effect of the urban adjustment on global temperature change is on the order of 0.01 ◦C.”
BackgroundMethodInfluentialSelf-citation
Processes and impacts of Arctic amplification: A research synthesis
Serreze, M. C., & Barry, R. G. (2011) · Global and Planetary Change · doi:10.1016/j.gloplacha.2011.03.004 · Cited by 2,752
Recent Arctic amplification and extreme mid-latitude weather
Cohen, J. L., Screen, J. A., Furtado, J. C., Barlow, M., Whittleston, D. P., Coumou, D., Francis, J. A., Dethloff, K., Entekhabi, D., Overland, J. E., et al. (2014) · Nature Geoscience · doi:10.1038/ngeo2234 · Cited by 2,613
Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850
Brohan, P., Kennedy, J. J., Harris, I., Tett, S. F. B., & Jones, P. D. (2006) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2005jd006548 · Cited by 2,040
Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set
Morice, C. P., Kennedy, J. J., Rayner, N. A., & Jones, P. D. (2012) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2011jd017187 · Cited by 1,657
Climate Impact of Increasing Atmospheric Carbon Dioxide
Hansen, J. E., Johnson, D., Lacis, A. A., Lebedeff, S. A., Lee, P., Rind, D. H., & Russell, G. L. (1981) · Science · doi:10.1126/science.213.4511.957 · Cited by 1,074
Self-citation

Show all 48 references

Research works printed but not linked: 2

Ishihara K., 2006, Calculation of global surface temperature anomalies with COBE‐SST, Weather Service Bulletin, 73, S19—S25
10.4172/2327-4581.1000103 · DOI · Paper page

Sorted by citations

Items 601–700 of 961

Heat-related urban mortality attributable to human-induced climate change in Europe from 2000 to 2025
Barnes, C. R., Masselot, P., Xi, D., Clarke, B., Rayner, A., Chen, X., Wang, R., Raju, E., Theokritoff, E., Mistry, M., et al. (2026) · Nature Health · doi:10.1038/s44360-026-00209-8 · Cited by 2
Current trends and future outlook in spectroscopic monitoring of the atmosphere
Chen, W., Venables, D. S., & Sigrist, M. W. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-815014-6.00010-5 · Cited by 2
Verification Data and the Skill of Decadal Predictions
Boer, G. J., Sospedra‐Alfonso, R., Martineau, P., & Kharin, V. (2022) · Frontiers in Climate · doi:10.3389/fclim.2022.836817 · Cited by 2
PROBLEMS OF ASSESSING THE TECHNICAL AND TECHNOLOGICAL SAFETY OF ECONOMIC SUBJECTS IN MODERN ECONOMIC CONDITIONS
KOROBEINKOVA, L. S., & Utochkina, L. A. (2022) · Scientific Works of the Free Economic Society of Russia · doi:10.38197/2072-2060-2022-236-4-191-209 · Cited by 2
Spatiotemporal Variation of Extreme Precipitation in the Lixia River Basin, China, between 1960 and 2019 under Global Warming, Atmospheric Circulation, and Local Effects
Ju, Y., Yang, X., Wang, D., Wang, Y., & Tao, R. (2023) · Journal of Hydrologic Engineering · doi:10.1061/jhyeff.heeng-6002 · Cited by 2
X-ray Investigation of CsPbI3:EuCl3 Infiltrated into Gig-Lox TiO2 Spongy Layers for Perovskite Solar Cells Applications
Magna, P. L., Spampinato, C., Valastro, S., Smecca, E., Arena, V., Mannino, G., Deretzis, I., Fisicaro, G., Bongiorno, C., & Alberti, A. (2023) · Nanomaterials · doi:10.3390/nano13222910 · Cited by 2
Terrestrial Temperature, Sea Levels and Ice Area Links with Solar Activity and Solar Orbital Motion
Zharkova, V. V., & Vasilieva, I. (2023) · Natural Science · doi:10.4236/ns.2023.159018 · Cited by 2
Historical global and regional spatiotemporal patterns in daily temperature
Rahim, M. A., Rohli, R. V., Mostafiz, R. B., Bushra, N., & Friedland, C. J. (2024) · Frontiers in Environmental Science · doi:10.3389/fenvs.2023.1294456 · Cited by 2
Visualizing Changes in Global Glacier Surface Mass Balances before and after 1990
Braithwaite, R. J., & Hughes, P. D. (2024) · Atmosphere · doi:10.3390/atmos15030362 · Cited by 2
Estimating freshwater flux amplification with ocean tracers via linear response theory
Basinski‐Ferris, A., & Zanna, L. (2024) · Earth System Dynamics · doi:10.5194/esd-15-323-2024 · Cited by 3
“3).”
Neural Network-Based Climate Prediction for the 21st Century Using the Finnish Multi-Millennial Tree-Ring Chronology
Kasatkina, E. A., Shumilov, O. I., & Timonen, M. (2024) · Geosciences · doi:10.3390/geosciences14080212 · Cited by 2
Study the spatiotemporal variation characteristics and driving forces differences of land surface temperature in the Chishui River Basin based on the Bayesian Structural equation model
Li, X., Cai, H. Z., Zhang, X., Zhang, L., Chen, Y., Hao, J., & Mao, Y. (2025) · Advances in Space Research · doi:10.1016/j.asr.2025.02.006 · Cited by 2
Deviations from Normality in Autocorrelation Functions and Their Implications for MA(q) Modeling
Royer‐Carenzi, M., & Hassani, H. (2025) · Stats · doi:10.3390/stats8010019 · Cited by 2
“It is interesting to see that the models generated by our procedures reveal global warming [63,64], while models SARIMA(0,0,0)(0,1,0)[12] and SARIMA(36,0,0)(0,1,0)[12] completely miss the point.”
Mapping subsea permafrost around Tuktoyaktuk Island (Northwest Territories, Canada) using electrical resistivity tomography
Erkens, E., Angelopoulos, M., Tronicke, J., Dallimore, S. R., Whalen, D., Boike, J., & Overduin, P. P. (2025) · The Cryosphere · doi:10.5194/tc-19-997-2025 · Cited by 2
“It can be regarded as the root mean square (RMS) weighted with the standard deviation (noise level) of the measurement.”
Influential
Accelerated warming of air and soil temperatures: evidence from observations in Fuyang from 1985 to 2024
Dai, Q., Wu, L., Jia, B., Wang, L., Zhang, X., Zhang, L., Xie, Z., Zhang, Q., & Zhang, S. (2025) · Theoretical and Applied Climatology · doi:10.1007/s00704-025-05545-5 · Cited by 2
Probing links between climate change and solar variability using wavelet analyses
Wang, D., & Jia, W. (2025) · Frontiers of Earth Science · doi:10.1007/s11707-025-1146-1 · Cited by 2
Early and widespread emergence of regional warming is robust to observational and model uncertainty
Shaw, J., & Lenssen, N. (2025) · Environmental Research Letters · doi:10.1088/1748-9326/ade458 · Cited by 2
Self-citation
The Representation of Surface Temperature Trends in C3S Seasonal Forecast Systems
Patterson, M., Befort, D. J., Lockwood, J. F., Slattery, J., & Weisheimer, A. (2025) · Atmospheric Science Letters · doi:10.1002/asl.1316 · Cited by 2
“JRA-55 uses COBE-SSTs, whereas ERA5, HadCRUT5, and GISTEMP use HadISST2, HadISST4, and ERSSTv5 (Huang et al. 2017), respectively.”
Influential
Analysis of the planetary thermal distribution with a simple three-zone maximum-flux model
Roca, J. M., & Pelegrí, J. L. (2020) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2020.120185 · Cited by 2
Analyse et interprétation climatologique de l'évolution des températures moyennes mondiales depuis 1880
Zeltz, E. (2021) · Physio-Géo · doi:10.4000/physio-geo.12176 · Cited by 2
Global and regional climate in 2020
Kennedy, J., Willett, K. M., Dunn, R., Morice, C., Christidis, N., & Kendon, M. (2021) · Weather · doi:10.1002/wea.4087 · Cited by 2
Local Scale Exposure and Fate of Engineered Nanomaterials
Poikkimäki, M., Quik, J. T. K., Säämänen, A. J., & Maso, M. D. (2022) · Toxics · doi:10.3390/toxics10070354 · Cited by 2
“We used a mean surface air temperature of 15 ◦C [53], a wind speed of 2.”
Method
Temporal and climatic variation in the colour forms of Adalia bipunctata and Harmonia axyridis (Coleoptera: Coccinellidae) populations in the United Kingdom
Asiri, A., & Foster, C. W. (2022) · European Journal of Entomology · doi:10.14411/eje.2022.027 · Cited by 2
“…a decrease in the proportion of melanism in the UK since 1978 (Brakefi eld & Lees, 1987), where melanic form ranges between 13 and 36%, which is consistent with an increase in global temperature (Lenssen et al., 2019) and reduction in air pollution (Murrells et al., 2010) since the 1980s.”
TO THE ISSUE OF THE STATEMENT OF THE PROBLEM OF PRACTICAL ADAPTATION TO THE CLIMATE CHANGE IN THE CONDITIONS OF RUSSIA’S PARTICIPATION IN THE GLOBAL CLIMATE AGENDA
State Duma of the Federal Assembly of the Russian Federation, & Nikolaev, N. P. (2022) · Scientific Works of the Free Economic Society of Russia · doi:10.38197/2072-2060-2022-236-4-427-446 · Cited by 2
IMPACT OF HUMAN CAPITAL ON THE INNOVATIVE ACTIVITY OF THE REGION
Олегович, П. М. (2022) · Scientific Works of the Free Economic Society of Russia · doi:10.38197/2072-2060-2022-236-4-260-278 · Cited by 2
Manifestation of the Early 20th Century Warming in the East-European Plain: Atmospheric Circulation Anomalies and Its Connection to the North Atlantic SST and Sea Ice Variability
Popova, V. V., Matveeva, T. A., & Bokuchava, D. D. (2023) · Atmosphere · doi:10.3390/atmos14030428 · Cited by 2
Climatic Challenges of Quito
Llugsi, R. (2023) · International Conference on Pattern Recognition Systems (ICPRS) · doi:10.1109/icprs58416.2023.10179029 · Cited by 2
Robust Human Influence across the Troposphere, Surface, and Ocean: A Multivariate Analysis
Blackport, R., Fyfe, J. C., & Santer, B. D. (2023) · Journal of Climate · doi:10.1175/jcli-d-23-0068.1 · Cited by 2
Housing Adaptations to Climate: Vernacular Settlements on the Kahayan Riverbank at Palangka Raya, Indonesia
Guntur, M., Kurniawan, K. R., & Sutanto, D. (2023) · International Society for the Study of Vernacular Settlements · doi:10.61275/isvsej-2023-10-08-1 · Cited by 2
The Role of Natural Fluctuations and Factors of External Forcing in Early 20th Century Warming in the Northern Hemisphere
Bokuchava, D. D., & Семенов, В. А. (2023) · Izvestiya Atmospheric and Oceanic Physics · doi:10.1134/s0001433823130030 · Cited by 2
The effect of photosynthetic gas exchange on Δ17O of atmospheric CO2
Adnew, G. A. (2020) · doi:10.33540/412 · Cited by 2
Analysis of global trends of total column water vapour from multiple years of OMI observations
Borger, C., Beirle, S., & Wagner, T. (2021) · doi:10.5194/egusphere-egu21-1170 · Cited by 2
Supplementary material to "GIR v1.0.0: a generalised impulse-response model for climate uncertainty and future scenario exploration"
Leach, N. J., Nicholls, Z., Jenkins, S., Smith, C., Lynch, J., Cain, M. L., Wu, B., Tsutsui, J., & Allen, M. R. (2020) · doi:10.5194/gmd-2019-379-supplement · Cited by 2
The contribution of agricultural methane from ruminants and plants to global warming (4588)
Devine, C. E., & Devine, S. D. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-85125-1.00118-6 · Cited by 2
Possible role of anthropogenic climate change in the record-breaking 2020 Lake Victoria levels and floodsPreprint
Pietroiusti, R., Vanderkelen, I., Otto, F. E. L., Barnes, C. R., Temple, L., Akurut, M., Bally, P., van Lipzig, N. P. M., & Thiery, W. (2023) · doi:10.5194/egusphere-2023-1827 · Cited by 2
cfr (v2023.9.14): a Python package for climate field reconstructionPreprint
Zhu, F., Emile‐Geay, J., Hakim, G. J., Guillot, D., Khider, D., Tardif, R., & Perkins, W. A. (2023) · doi:10.5194/egusphere-2023-2098 · Cited by 2
Growing cumulative activity of major tropical cyclones: Detection, attribution, and projections
Katz, Y. A., & Biem, A. (2021) · Communications in Nonlinear Science and Numerical Simulation · doi:10.1016/j.cnsns.2021.106202 · Cited by 1
Characterization of climate impacts on a semi-arid agricultural perimeter in Morocco
Boundi, A., & Yacine, Z. A. (2022) · E3S Web of Conferences · doi:10.1051/e3sconf/202233702001 · Cited by 1
Preparing for a Data-Rich World: Civic Statistics Across the Curriculum
Engel, J., Nicholson, J., & Louie, J. (2022) · Springer eBooks · doi:10.1007/978-3-031-20748-8_18 · Cited by 1
LiG Metrology, Correlated Error, and the Integrity of the Global Surface Air-Temperature Record
Frank, P. (2023) · Sensors · doi:10.3390/s23135976 · Cited by 1
Prediction of Carbon Dioxide Level Using Statistical Learning and Its Potential Correlation With Global Warming
Wang, Y., Shen, Y., & Hu, M. (2023) · SHS Web of Conferences · doi:10.1051/shsconf/202317403034 · Cited by 1
“[1] Figure 5 Scatter plot of past land-ocean temperature”
Background
Drift Correction and Sub‐Ensemble Predictive Skill Evaluation of the Decadal Prediction Large Ensemble With Application to Regional Studies
Rosa-Cánovas, J. J., Ojeda, M. G., Romero-Jiménez, E., Yeste, P., Gámiz‐Fortis, S. R., Castro‐Díez, Y., & Esteban‐Parra, M. J. (2023) · Journal of Geophysical Research Atmospheres · doi:10.1029/2023jd039709 · Cited by 1
“The Goddard Institute for Space Studies Surface Temperature Analysis version 4 (GISTEMP4; GISTEMP Team, 2023; Lenssen et al., 2019) has been chosen in the evaluation of NSTA over land.”
Method
Ground-air temperature tracking from a geothermal climate-change observatory in South India
Akkiraju, V. V., Roy, S., & Chapman, D. S. (2023) · Tectonophysics · doi:10.1016/j.tecto.2023.230154 · Cited by 1
The Effect of MOFs on Carbon Dioxide Adsorption
Wang, J. (2023) · Highlights in Science Engineering and Technology · doi:10.54097/hset.v73i.12838 · Cited by 1
“According to the report "World Energy Outlook 2021" published by the International Energy Agency [1], global energy demand increased significantly by 2.3% from 2018 to 2019, and it is projected to grow by 1.3% annually until 2040 [2].”
MethodInfluential
Dormant season warming amplifies daytime CO2 emissions from a temperate urban salt marsh
Vieillard, A. M., Girguis, P. R., & Fulweiler, R. W. (2024) · Frontiers in Environmental Science · doi:10.3389/fenvs.2024.1340416 · Cited by 1
Fingerprints of past volcanic eruptions can be detected in historical climate records using machine learning
Meuer, J., Timmreck, C., Fang, S., & Kadow, C. (2024) · Communications Earth & Environment · doi:10.1038/s43247-024-01617-y · Cited by 2
“Finally,theGISTEMP4 55,56 analysis represents an estimate of global surface temperature changes produced by the National Aeronautics and Space Administration from 1880 to the present.”
Method
On the Attribution of Weather Events to Climate Change Using Empirically Fit Extreme Value Distributions
Sherman, P. J., Huybers, P., & Tziperman, E. (2025) · Journal of Climate · doi:10.1175/jcli-d-23-0542.1 · Cited by 1
Markov analysis and the Langevin equation of the Earth surface temperature data
Lak, M., hosseinabadi, S., & Masoudi, A. A. (2025) · Scientific Reports · doi:10.1038/s41598-025-15149-8 · Cited by 1
Probabilistic Simulations and Projections of Global Temperature Based on Greenhouse Gases
Yu, H., Wang, L., & Chen, Y. (2025) · International Journal of Climatology · doi:10.1002/joc.70097 · Cited by 1
“Dataset accessed 2021-03 at https:// data. giss. nasa. gov/ giste mp/ ) provided by NASA were used for the analysis (Lenssen et al. 2019).”
Global and regional climate in 2024
Sandford, C., Dunn, R., Killick, R., Palmer, M. D., Titchner, H., Rayner, N. A., Morice, C., & Kendon, M. (2025) · Weather · doi:10.1002/wea.7776 · Cited by 1
Study on Power Frequency Breakdown and Decomposition Characteristics of SF6/N2 Gas Mixture
Wang, J., Liao, L., Xia, Y., Xu, J., Lin, X., & Geng, Z. (2025) · Energies · doi:10.3390/en18215814 · Cited by 1
Integrating Envelope Approach with Machine Learning Ranking Process for Temperature Projection in Sarawak, Malaysia
Sa’adi, Z., Shahid, S., Shiru, M. S., Ahmed, K., Alamgir, M., Houmsi, M. R., Houmsi, L. N., Kemarau, R. A., Suab, S. A., Abas, M. A., et al. (2025) · Pure and Applied Geophysics · doi:10.1007/s00024-025-03858-0 · Cited by 1
“Additionally, datasets like NASA’s Goddard Institute for Space Studies Surface Temperature Analysis (GISTEMP) (Lenssen et al., 2019) offer global coverage with a spatial resolution of approximately 1 (cid”
Striking the balance between speed and compression ratio: A fast bit-grouping algorithm and adaptive compressor selection for scientific data
Middlezong, M. (2026) · Future Generation Computer Systems · doi:10.1016/j.future.2026.108370 · Cited by 1
Reconstruction of temperature, precipitation, and identification of extreme climate events in high mountain Asia over 500 years using multi-method EnKF
Zhou, J., Chen, F., Zhu, Y., Xie, F., Qin, C., Tian, H., Shen, Y., Yang, X., Duan, Y., Afzal, M. M., et al. (2026) · Scientific Reports · doi:10.1038/s41598-026-36469-3 · Cited by 1
“…reanalyses: Berkeley Earth 42 , Hadley Centre Climatic Research Unit Temperature version 5 (HadCRUT5) 44 , Climatic Research Unit Time Series (CRU TS) 45 , Goddard Institute for Space Studies Surface Temperature Analysis (GISTEMP) 46 , and Twentieth Century Reanalysis version 3 dataset(20CRv3) 47 .”
Effect of Climate Change on Geopolitical Risk: From 1994 to 2020
Ke, H., Kong, L., & Zhang, Y. (2026) · SAGE Open · doi:10.1177/21582440251414702 · Cited by 1
Unveiling the Role of Sea‐Ice Loss in Early‐20th‐Century Arctic Warming
Li, F., Semenov, V. A., Keenlyside, N. S., Aldonina, T. A., Ha, K., Chung, E., & Yang, X. (2026) · Geophysical Research Letters · doi:10.1029/2025gl121178 · Cited by 1
A Bayesian statistical method to estimate the climatology of extreme temperature under multiple scenarios: the ANKIALE package
Robin, Y., Vrac, M., Ribes, A., Barbaux, O., & Naveau, P. (2026) · Geoscientific model development · doi:10.5194/gmd-19-2349-2026 · Cited by 2
“GISTEMP data are available at data.giss.nasa.gov/gistemp (Lenssen et al., 2019).”
Reversal of the ITCZ Shift During the Satellite Era
Shrestha, S., Soden, B. J., & He, H. (2026) · Geophysical Research Letters · doi:10.1029/2026gl123402 · Cited by 1
Paleo Data Assimilation of Coral δ 18 O Part 2: 20th‐Century Trends and Variability of the Tropical Pacific
Sanchez, S. C., Zhu, F., Saenger, C., & Thompson, D. M. (2026) · Paleoceanography and Paleoclimatology · doi:10.1029/2025pa005336 · Cited by 1
“GISTEMPv4 (Lenssen et al., 2019) with ERSSTv5 (Huang et al., 2017) is used as our surface temperature observations.”
Paleoclimate data assimilation with adaptive observation error inflation and adaptive localization
Luo, G., Zeng, Y., Zhu, F., & Zhao, J. (2026) · Geoscientific model development · doi:10.5194/gmd-19-7893-2026
Paleo Data Assimilation of Coral δ 18 O Part 1: Best Practices and Uncertainties
Sanchez, S. C., Zhu, F., Saenger, C., & Thompson, D. M. (2026) · Paleoceanography and Paleoclimatology · doi:10.1029/2025pa005335 · Cited by 2
“To isolate the influence of SSS products, we use GISTEMPv4 (Lenssen et al., 2019) data sources, methods of quality control, and how they infill missing data (Table S6 in Supporting Information S1).”
Detecção e atribuição das anomalias anuais dos índices de extremos de chuva e temperaturas máxima e mínima diárias sobre o litoral de São Paulo/Brasil
da Silva, G. A. M., Cardoso, C. D. S., Ambrizzi, T., de Souza, C. P., MENDES, D. G., & Gomes, H. B. (2021) · Revista Brasileira de Geografia Física · doi:10.26848/rbgf.v14.5.p3008-3043 · Cited by 1
An Improved Method for Defining Short-Term Climate Anomalies
Chen, X., & Li, T. (2021) · 气象学报：英文版 · doi:10.1007/s13351-021-1139-2 · Cited by 1
LOGISTICS OF INTELLECTUAL PROPERTY: DEVELOPMENT TRAJECTORY
Топоркова, Е. В., & Михайлович, К. В. (2022) · Scientific Works of the Free Economic Society of Russia · doi:10.38197/2072-2060-2022-236-4-345-354 · Cited by 1
FACTORS IN THE SUSTAINABLE DEVELOPMENT OF THE REGIONAL ECONOMY
Mantaeva, E. I., Goldenova, V., & Slobodchikova, I. (2022) · Scientific Works of the Free Economic Society of Russia · doi:10.38197/2072-2060-2022-236-4-78-97 · Cited by 1
Quantifying contributions of ozone changes to global and arctic warming during the second half of the twentieth century
Hu, Y., Wu, Q., Hu, A., & Schroeder, S. R. (2022) · Climate Dynamics · doi:10.1007/s00382-022-06621-6 · Cited by 1
Effect of geotextile cover on snow and ice melt on Triangular Glacier, the north-eastern Antarctic Peninsula
Engel, Z., Láska, K., Matějka, M., & Nedělčev, O. (2023) · Czech Polar Reports · doi:10.5817/cpr2022-2-19 · Cited by 1
Application of geoinformation systems in sounding the ecological and economic network of the urban environment in the northern territories
Мамаева, Н. Л., & Sa, P. (2023) · Oil and Gas Studies · doi:10.31660/0445-0108-2023-1-97-107 · Cited by 1
Polymer Membrane‐Based Pervaporation Process for Separating Organic Mixture by Molecular Simulation
Jiang, C., & Hou, Y. (2023) · Macromolecular Chemistry and Physics · doi:10.1002/macp.202300069 · Cited by 1
Perspectives on Climate Change Until 2030
Llugsi, R. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-32213-6_27 · Cited by 1
Can We Still Save Our Goldilocks Zone From Climate Change Catastrophes?
Aneja, K. K., & Aneja, K. K. (2023) · ACTA SCIENTIFIC MICROBIOLOGY · doi:10.31080/asmi.2023.06.1276 · Cited by 1
Global lead-lag changes between climate variability series coincide with major phase shifts in the Pacific decadal oscillation
Seip, K. L., Grøn, Ø. G., & Wang, H. (2023) · Theoretical and Applied Climatology · doi:10.1007/s00704-023-04617-8 · Cited by 1
“The data are updated every month and may change within their margin of error (Lenssen et al. (2019), Ruedy, NASA Goddard Space Flight Center, personal communication).”
Background
Can cloud images help in predicting geomagnetic storms?
Syiemlieh, R., & Saikia, E. (2024) · Journal of Atmospheric and Solar-Terrestrial Physics · doi:10.1016/j.jastp.2024.106186 · Cited by 1
Nonequilibrium Fluctuations of Global Warming
Yin, J., Porporato, A. M., & Rondoni, L. (2024) · Journal of Climate · doi:10.1175/jcli-d-23-0273.1 · Cited by 14
Impact of the Eurasian Zonal Circulation on the Interannual Variability of Winter Surface Air Temperature and Subseasonal Temperature Reversal in North China
Chen, Z., Xue, X., Liu, Y., Wu, Y., Cai, Z., Cui, Z., & Liu, R. (2024) · Journal of Geophysical Research Atmospheres · doi:10.1029/2023jd039741 · Cited by 1
“The monthly Arctic SAT from the NASA (National Aeronautics and Space Administration Goddard Institute for Space Studies) (Lenssen et al., 2019) are available at https://data.giss.nasa.gov/gistemp/.”
Method
A revised interpretation of signal-to-noise ratio paradox and its application to constrain regional climate projections
Duan, Y., & Kumar, S. (2024) · Environmental Research Climate · doi:10.1088/2752-5295/ad3a0c · Cited by 1
“To address observational uncertainty, we performed an additional analysis for a better observation period, i.e. 1950–2014, and an alternative data source from the goddard institute for space studies (GISS) surface temperature data (Lenssen et al 2019).”
Method
The Optimal Counting Number for Silicoflagellate Assemblages in the Western Arctic Ocean
Feng, X., Ren, J. X., Xu, R., Jin, H., & Chen, J. (2025) · Diversity · doi:10.3390/d17030201 · Cited by 1
Heating up, cooling off: exploring cooling behaviours at home in Aotearoa New Zealand
O’Sullivan, K. C., Dohig, R. K., Chen, Z., Jiang, T., Pierse, N., Riva, M., & Das, R. R. (2025) · Energy Research & Social Science · doi:10.1016/j.erss.2025.104128 · Cited by 1
An empirical method for the prediction of extreme low winter sea ice extent in the Barents Sea
Черенкова, Е. А., Семенов, В. А., & Титкова, Т. Б. (2020) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/611/1/012042 · Cited by 1
Assessment of Quarterly, Semiannual and Annual Models to Forecast Monthly Rainfall Anomalies: The Case of a Tropical Andean Basin
Vázquez‐Patiño, A., Peña, M., & Avilés, Á. (2022) · Atmosphere · doi:10.3390/atmos13060895 · Cited by 1
“Global Global Mean Land-Ocean Temperature (GMSST) [36].”
BackgroundInfluential
HYBRID ENERGY STORAGE: PROBLEMS AND PROSPECTS OF ENERGY STORAGE TECHNOLOGIES
Usacheva, I. V., GLADKAYA, E. A., LANDIN, S. V., & JSC, S. E. (2022) · Scientific Works of the Free Economic Society of Russia · doi:10.38197/2072-2060-2022-236-4-149-167 · Cited by 1
REGIONAL ECONOMY: CHALLENGES OF SUSTAINABLE DEVELOPMENT
Анатольевич, Б. К., & Белокрылова, О. С. (2022) · Scientific Works of the Free Economic Society of Russia · doi:10.38197/2072-2060-2022-236-4-34-54 · Cited by 1
RUSSIA AND GLOBAL CHALLENGES: TRENDS, REGULATION AND ADAPTATION OF THE NATIONAL ECONOMY
ORLOV, S. N. (2022) · Scientific Works of the Free Economic Society of Russia · doi:10.38197/2072-2060-2022-236-4-121-148 · Cited by 1
Global surface temperatures
Kent, E. C., Chan, D., Cornes, R., Nielsen‐Englyst, P., Kajtar, J. B., Merchant, C. J., Thorne, P., Wallis, E. J., & Woolway, R. I. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-21927-6.00022-2 · Cited by 1
Corrections to ocean-temperature record resolve puzzling regional differences
Hausfather, Z. (2019) · Nature · doi:10.1038/d41586-019-02147-w · Cited by 1
Adaptive Frequency Band Analysis for Functional Time SeriesPreprint
Bagchi, P., & Bruce, S. A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.01784 · Cited by 1
“For example, NASA records surface temperatures for more than 5000 locations, and these readings are used to identify yearly temperature anomalies, which are crucial in studying global warming patterns [18].”
Background
Reduce Production or Increase Efficiency? Hazardous Air Pollutants Regulation, Energy Use and the Synergistic Effect On Industrial Enterprises’ Carbon EmissionPreprint
Xu, J., Xu, H., Wang, J. X., & Hou, X. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4162311 · Cited by 1
Efficient Estimation of Climate State and Its Uncertainty Using Kalman Filtering with Application to Policy Thresholds and VolcanismPreprint
Nicklas, J., Fox‐Kemper, B., & Lawrence, C. E. (2022) · doi:10.31223/x5fh2c · Cited by 1
Comment on essd-2023-166
Forster, P. M. D. F., Smith, C., Walsh, T., et al. (2023) · Earth system science data · doi:10.5194/essd-2023-166-rc1 · Cited by 1
Reply to “Comment on ‘Advanced Testing of Low, Medium, and High ECS CMIP6 GCM Simulations Versus ERA5‐T2m’ by N. Scafetta (2022)” by Schmidt et al. (2023)
Nicola Scafetta, A. (2023) · Geophysical Research Letters · doi:10.1029/2023gl104960 · Cited by 1
Climate Change and Architecture: The Link OverlookedPreprint
Majumder, R. (2024) · Preprints.org · doi:10.20944/preprints202402.0859.v1 · Cited by 1
The influence of global warming on ENSO dynamicsPreprint
Zhang, M., Yan, L., Nayak, A., Xiong, L., & Lall, U. (2024) · Research Square · doi:10.21203/rs.3.rs-4438731/v1 · Cited by 1
The Climate Adaptation Feedback
Abajian, A., Carleton, T. A., Meng, K. C., & Deschênes, O. (2025) · National Bureau of Economic Research · doi:10.3386/w33531 · Cited by 1
Greenlandic ice archives of North Atlantic Common Era climate
Osman, M. (2019) · doi:10.1575/1912/24772
The effect of geographic sampling on extreme precipitation: from models to observations and back againPreprint
Risser, M. D., & Wehner, M. F. (2019) · arXiv (Cornell University)
Ambient intelligence in buildings : design and development of an interoperable Internet of Things platform
Ausejo, D. S. (2020) · doi:10.5821/dissertation-2117-183229
Modelling, simulation and analysis of green gas injection into the gas distribution network
Sprangers, W. (2020) · Research Repository (Delft University of Technology)
Trends of continental, zonal and seasonal land temperatures in the 20th centuryPreprint
Takalo, J., & Mursula, K. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.11410
“…(National Oceanic and Atmospheric Administration) web-site for continental data analysis (Menne et al., 2018), and NASA Goddard Space Flight Center GISTEMP (GISS Surface Temperature Analysis) data for hemispheric, zonal and seasonal land temperature analysis for 1880-2017 (Lenssen et al., 2019).”
Method
Capacitive processes for carbon capture and energy recovery from CO2 emissions : Shaping a new technology going from water to gas applications
Legrand, L. J. P. (2020) · doi:10.18174/528554
The Roles and Impacts of Greenery Club in Kolej Tuanku Canselor Universiti Teknologi Malaysia
Sia, J. S. Y., Tiong, M. F. T., Chuan, M. W., Aziz, M. A. A. A., Esa, M. F. M., Nawabjan, A., Ghani, R. A., Ahmad, A. S., & Rahim, S. K. A. (2020) · International Conference on Student and Disable Student Development (ICoSD) · doi:10.2991/assehr.k.200921.014

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.
ORCID: Lenssen, Nathan J. L.
Schmidt, Gavin A.
Hansen, James E.
Menne, Matthew J.
Ruedy, Reto
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
DOI: 10.1029/2018jd029522
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
FWCI: 62.15
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: onlinelibrary.wiley.com/termsAndConditions#am (am, 334 d)
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Improvements in the GISTEMP Uncertainty Model

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks