When climate change predictions are right for the wrong reasons

Broecker, W. S.

doi:10.1007/s10584-017-1927-y

Cited by 11 publications

(8 citation statements)

References 12 publications

(8 reference statements)

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“…We find no evidence that the climate models evaluated in this paper have systematically overestimated or 10.1029/2019GL085378 underestimated warming over their projection period. The projection skill of the 1970s models is particularly impressive given the observational evidence of warming at the time, as the world was thought to have been cooling for the past few decades (e.g., Broecker, 1975;Broecker, 2017).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Evaluating the Performance of Past Climate Model Projections

Hausfather

Drake

Abbott

et al. 2020

Geophysical Research Letters

125

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Retrospectively comparing future model projections to observations provides a robust and independent test of model skill. Here we analyze the performance of climate models published between 1970 and 2007 in projecting future global mean surface temperature (GMST) changes. Models are compared to observations based on both the change in GMST over time and the change in GMST over the change in external forcing. The latter approach accounts for mismatches in model forcings, a potential source of error in model projections independent of the accuracy of model physics. We find that climate models published over the past five decades were skillful in predicting subsequent GMST changes, with most models examined showing warming consistent with observations, particularly when mismatches between model‐projected and observationally estimated forcings were taken into account.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Evaluating the Performance of Past Climate Model Projections

Hausfather

Drake

Abbott

et al. 2020

Geophysical Research Letters

125

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“…The obtained values of the spatial correlation of temperature and precipitation explained the synchronous course of temperature variation in all climatic zones, and the regional precipitation regime in all climatic zones of southern Russia (Figure 2. ) Various estimates of the change in global surface air temperature have been given [1][2][3][4][5]46,47]. From the second half of the 20th century, and in the first decade of the 21st century, the rate of temperature growth on average has varied in the range 0.17 ± 0.01 °C.…”

Section: Analysis and Discussionmentioning

confidence: 99%

“…The global climate on our planet is changing rapidly. In this regard, an increasing number of studies are being devoted to this problem [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. The Russia territory is more sensitive to the effects of climate than the Northern Hemisphere and the rest of the globe.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Climate Change in the Caucasus Region: End of the 20th–Beginning of the 21st Century

Tashilova

Ashabokov

Kesheva

et al. 2019

Climate

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The study of climate, in such a diverse climatic region as the Caucasus, is necessary in order to evaluate the influence of local factors on the formation of temperature and precipitation regimes in its various climatic zones. This study is based on the instrumental data (temperatures and precipitation) from 20 weather stations, located on the territory of the Caucasian region during 1961–2011. Mathematical statistics, trend analysis, and rescaled range Methods were used. It was found that the warming trend prevailed in all climatic zones, it intensified since the beginning of global warming (since 1976), while the changes in precipitation were not so unidirectional. The maximum warming was observed in the summer (on average by 0.3 °C/10 years) in all climatic zones. Persistence trends were investigated using the Hurst exponent H (range of variation 0–1), which showed a higher trend persistence of annual mean temperature changes (H = 0.8) compared to annual sum precipitations (H = 0.64). Spatial-correlation analysis performed for precipitations and temperatures showed a rapid decrease in the correlation between precipitations at various weather stations from R = 1 to R = 0.5, on a distance scale from 0 to 200 km. In contrast to precipitation, a high correlation (R = 1.0–0.7) was observed between regional weather stations temperatures at a distance scale from 0 to 1000 km, which indicates synchronous temperature changes in all climatic zones (unlike precipitation).

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“…Prior researchers predicted the connections between increase in atm. CO 2 and global temperature, not surface temperature in particular, and the term "climate change" itself was first used by JM Mitchell in 1961(Broecker 2017.…”

Section: Climate Changementioning

confidence: 99%

Climate Change, Climate Informatics, and AI: Information Analysis

Ababneh¹

2021

Handbook of Climate Change Management

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I assess and discuss relevant literature on the potential positive and negative contributions of AI to climate change as it relates to climate sciences and its interdisciplinary branches of paleoclimatology, paleoecology, and archaeology. To the moment of writing this essay, there is an information gap on the applications of AI in the three interdisciplinary branches. I conclude, AI is an essential tool for scientific advancement and interdisciplinary and cross-boundary collaboration; however, there is a technological gap between developed and developing countries that hinders AI applications in climate change and mitigations as envisioned under the Paris Agreement, while Advancements in AI applications in climate change are limited by priority agenda and trained personal.

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When climate change predictions are right for the wrong reasons

Cited by 11 publications

References 12 publications

Evaluating the Performance of Past Climate Model Projections

Evaluating the Performance of Past Climate Model Projections

Analysis of Climate Change in the Caucasus Region: End of the 20th–Beginning of the 21st Century

Climate Change, Climate Informatics, and AI: Information Analysis

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