A closer look at United States and global surface temperature change

Residential solid fuel use contributes to degraded indoor and ambient air quality and may affect global surface temperature. However, the potential for national-scale cookstove intervention programs to mitigate the latter issues is not yet well known, owing to the spatial heterogeneity of aerosol emissions and impacts, along with coemitted species. Here we use a combination of atmospheric modeling, remote sensing, and adjoint sensitivity analysis to individually evaluate consequences of a 20-y linear phase-out of cookstove emissions in each country with greater than 5% of the population using solid fuel for cooking. Emissions reductions in China, India, and Ethiopia contribute to the largest global surface temperature change in 2050 [combined impact of −37 mK (11 mK to −85 mK)], whereas interventions in countries less commonly targeted for cookstove mitigation such as Azerbaijan, Ukraine, and Kazakhstan have the largest per cookstove climate benefits. Abatement in China, India, and Bangladesh contributes to the largest reduction of premature deaths from ambient air pollution, preventing 198,000 (102,000–204,000) of the 260,000 (137,000–268,000) global annual avoided deaths in 2050, whereas again emissions in Ukraine and Azerbaijan have the largest per cookstove impacts, along with Romania. Global cookstove emissions abatement results in an average surface temperature cooling of −77 mK (20 mK to −278 mK) in 2050, which increases to −118 mK (−11 mK to −335 mK) by 2100 due to delayed CO2 response. Health impacts owing to changes in ambient particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) amount to ∼22.5 million premature deaths prevented between 2000 and 2100.

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Trends in Extreme Rainfall Frequency in the Contiguous United States: Attribution to Climate Change and Climate Variability Modes

Journal of Climate ◽

10.1175/jcli-d-17-0106.1 ◽

2017 ◽

Vol 31 (1) ◽

pp. 369-385 ◽

Cited By ~ 26

Author(s):

Saman Armal ◽

Naresh Devineni ◽

Reza Khanbilvardi

Keyword(s):

Climate Change ◽

United States ◽

Climate Variability ◽

Surface Temperature ◽

Multilevel Model ◽

Extreme Rainfall ◽

Temperature Anomalies ◽

Global Surface Temperature ◽

Global Surface ◽

The U.S

AbstractThis study presents a systematic analysis for identifying and attributing trends in the annual frequency of extreme rainfall events across the contiguous United States to climate change and climate variability modes. A Bayesian multilevel model is developed for 1244 rainfall stations simultaneously to test the null hypothesis of no trend and verify two alternate hypotheses: trend can be attributed to changes in global surface temperature anomalies or to a combination of well-known cyclical climate modes with varying quasiperiodicities and global surface temperature anomalies. The Bayesian multilevel model provides the opportunity to pool information across stations and reduce the parameter estimation uncertainty, hence identifying the trends better. The choice of the best alternate hypothesis is made based on the Watanabe–Akaike information criterion, a Bayesian pointwise predictive accuracy measure. Statistically significant time trends are observed in 742 of the 1244 stations. Trends in 409 of these stations can be attributed to changes in global surface temperature anomalies. These stations are predominantly found in the U.S. Southeast and Northeast climate regions. The trends in 274 of these stations can be attributed to El Niño–Southern Oscillation, the North Atlantic Oscillation, the Pacific decadal oscillation, and the Atlantic multidecadal oscillation along with changes in global surface temperature anomalies. These stations are mainly found in the U.S. Northwest, West, and Southwest climate regions.

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Reply to "Comment on 'Cosmic-ray-driven reaction and greenhouse effect of halogenated molecules: Culprits for atmospheric ozone depletion and global climate change' by Dana Nuccitelli et al."

International Journal of Modern Physics B ◽

10.1142/s0217979214820049 ◽

2014 ◽

Vol 28 (13) ◽

pp. 1482004

Author(s):

Q.-B. Lu

Keyword(s):

Surface Temperature ◽

Cosmic Ray ◽

Radiation Physics ◽

Significant Discrepancy ◽

Model Calculations ◽

Surface Temperature Change ◽

The Past ◽

Global Surface Temperature ◽

Ipcc Report ◽

Global Surface

In the Comment by Nuccitelli et al., they make many false and invalid criticisms of the CFC-warming theory in my recent paper, and claim that their anthropogenic forcings including CO2 would provide a better explanation of the observed global mean surface temperature (GMST) data over the past 50 years. First, their arguments for no significant discrepancy between modeled and observed GMST changes and for no pause in recent global warming contradict the widely accepted fact and conclusion that were reported in the recent literature extensively. Second, their criticism that the key data used in my recent paper would be "outdated" and "flawed" is untrue as these data are still used in the recent or current literature including the newest (2013) IPCC Report and there is no considerable difference between the UK Met Office HadRCUT3 and HadRCUT4 GMST datasets. The use of even more recently computer-reconstructed total solar irradiance data (whatever have large uncertainties) for the period prior to 1976 would not change any of the conclusions in my paper, where quantitative analyses were emphasized on the influences of humans and the Sun on global surface temperature after 1970 when direct measurements became available. For the latter, the solar effect has been well shown to play only a negligible role in global surface temperature change since 1970, which is identical to the conclusion made in the 2013 IPCC Report. Third, their argument that the solar effect would not play a major role in the GMST rise of 0.2°C during 1850–1970 even contradicts the data and conclusion presented in a recent paper published in their Skeptical Science by Nuccitelli himself. Fourth, their comments also indicate their lack of understandings of the basic radiation physics of the Earth system as well as of the efficacies of different greenhouse gases in affecting global surface temperature. Their listed "methodological errors" are either trivial or non-existing. Fifth, their assertion that "the climate system takes centuries to millennia to fully equilibrate" is lack of scientific basis. Finally, their model calculations including an additional fitting parameter do not reduce the discrepancy with observed GMST data even after their adjustments. Instead, their modeled results give a sharp GMST rise over the past 16 years, which obviously disagrees with the observed data.

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The Use of Insolation in Forecasting Temperatures

Bulletin of the American Meteorological Society ◽

10.1175/1520-0477-34.6.245 ◽

1953 ◽

Vol 34 (6) ◽

pp. 245-249 ◽

Cited By ~ 2

Author(s):

Thomas L. Williams

Keyword(s):

United States ◽

Solar Energy ◽

Surface Temperature ◽

Temperature Change ◽

Southwestern United States ◽

Surface Temperature Change ◽

Available Energy

Daytime temperature forecasts are made for two stations in Southwestern United States. The forecasts are based upon computed values of incident solar energy and the latest albedo values as reported by various authors. An approximation is made of the amount of energy that is used to heat the soil, and the pseudo-adiabatic chart ia used indirectly to determine the surface temperature change that will result from a given amount of available energy.

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The Assessment of Global Surface Temperature Change from 1850s: The C-LSAT2.0 Ensemble and the CMST-Interim Datasets

Advances in Atmospheric Sciences ◽

10.1007/s00376-021-1012-3 ◽

2021 ◽

Author(s):

Wenbin Sun ◽

Qingxiang Li ◽

Boyin Huang ◽

Jiayi Cheng ◽

Zhaoyang Song ◽

...

Keyword(s):

Global Warming ◽

Surface Temperature ◽

Low Frequency ◽

Warming Trend ◽

Uncertainty Assessment ◽

Surface Temperature Change ◽

Global Surface Temperature ◽

Reconstruction Methods ◽

Frequency Components ◽

Global Surface

AbstractBased on C-LSAT2.0, using high- and low-frequency components reconstruction methods, combined with observation constraint masking, a reconstructed C-LSAT2.0 with 756 ensemble members from the 1850s to 2018 has been developed. These ensemble versions have been merged with the ERSSTv5 ensemble dataset, and an upgraded version of the CMST-Interim dataset with 5° × 5° resolution has been developed. The CMST-Interim dataset has significantly improved the coverage rate of global surface temperature data. After reconstruction, the data coverage before 1950 increased from 78%–81% of the original CMST to 81%–89%. The total coverage after 1955 reached about 93%, including more than 98% in the Northern Hemisphere and 81%–89% in the Southern Hemisphere. Through the reconstruction ensemble experiments with different parameters, a good basis is provided for more systematic uncertainty assessment of C-LSAT2.0 and CMST-Interim. In comparison with the original CMST, the global mean surface temperatures are estimated to be cooler in the second half of 19th century and warmer during the 21st century, which shows that the global warming trend is further amplified. The global warming trends are updated from 0.085 ± 0.004°C (10 yr)−1 and 0.128 ± 0.006°C (10 yr)−1 to 0.089 ± 0.004°C (10 yr)−1 and 0.137 ± 0.007°C (10 yr)−1, respectively, since the start and the second half of 20th century.

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