Perception of climate change Hansen, James; Sato, Makiko; Ruedy, Reto
Proceedings of the National Academy of Sciences - PNAS,
09/2012, Volume:
109, Issue:
37
Journal Article
Peer reviewed
Open access
“Climate dice,” describing the chance of unusually warm or cool seasons, have become more and more “loaded” in the past 30 y, coincident with rapid global warming. The distribution of seasonal mean ...temperature anomalies has shifted toward higher temperatures and the range of anomalies has increased. An important change is the emergence of a category of summertime extremely hot outliers, more than three standard deviations (3σ) warmer than the climatology of the 1951–1980 base period. This hot extreme, which covered much less than 1% of Earth’s surface during the base period, now typically covers about 10% of the land area. It follows that we can state, with a high degree of confidence, that extreme anomalies such as those in Texas and Oklahoma in 2011 and Moscow in 2010 were a consequence of global warming because their likelihood in the absence of global warming was exceedingly small. We discuss practical implications of this substantial, growing, climate change.
Climate sensitivity, sea level and atmospheric carbon dioxide Hansen, James; Sato, Makiko; Russell, Gary ...
Philosophical transactions - Royal Society. Mathematical, Physical and engineering sciences/Philosophical transactions - Royal Society. Mathematical, physical and engineering sciences,
10/2013, Volume:
371, Issue:
2001
Journal Article
Peer reviewed
Open access
Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the ...initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 31C for a 4Wm2 CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 34C for a 4Wm2 CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.
In the aftermath of the March 2011 accident at Japan’s Fukushima Daiichi nuclear power plant, the future contribution of nuclear power to the global energy supply has become somewhat uncertain. ...Because nuclear power is an abundant, low-carbon source of base-load power, it could make a large contribution to mitigation of global climate change and air pollution. Using historical production data, we calculate that global nuclear power has prevented an average of 1.84 million air pollution-related deaths and 64 gigatonnes of CO2-equivalent (GtCO2-eq) greenhouse gas (GHG) emissions that would have resulted from fossil fuel burning. On the basis of global projection data that take into account the effects of the Fukushima accident, we find that nuclear power could additionally prevent an average of 420 000–7.04 million deaths and 80–240 GtCO2-eq emissions due to fossil fuels by midcentury, depending on which fuel it replaces. By contrast, we assess that large-scale expansion of unconstrained natural gas use would not mitigate the climate problem and would cause far more deaths than expansion of nuclear power.
Global warming over the past several decades is now large enough that regional climate change is emerging above the noise of natural variability, especially in the summer at middle latitudes and ...year-round at low latitudes. Despite the small magnitude of warming relative to weather fluctuations, effects of the warming already have notable social and economic impacts. Global warming of 2 °C relative to preindustrial would shift the 'bell curve' defining temperature anomalies a factor of three larger than observed changes since the middle of the 20th century, with highly deleterious consequences. There is striking incongruity between the global distribution of nations principally responsible for fossil fuel CO2 emissions, known to be the main cause of climate change, and the regions suffering the greatest consequences from the warming, a fact with substantial implications for global energy and climate policies.
Financial fraud can have serious ramifications for the long-term sustainability of an organization, as well as adverse effects on its employees and investors, and on the economy as a whole. Several ...of the largest bankruptcies in U.S. history involved firms that engaged in major fraud. Accordingly, there has been considerable emphasis on the development of automated approaches for detecting financial fraud. However, most methods have yielded performance results that are less than ideal. In consequence, financial fraud detection continues as an important challenge for business intelligence technologies. In light of the need for more robust identification methods, we use a design science approach to develop MetaFraud, a novel meta-learning framework for enhanced financial fraud detection. To evaluate the proposed framework, a series of experiments are conducted on a test bed encompassing thousands of legitimate and fraudulent firms. The results reveal that each component of the framework significantly contributes to its overall effectiveness. Additional experiments demonstrate the effectiveness of the meta-learning framework over state-of-the-art financial fraud detection methods. Moreover, the MetaFraud framework generates confidence scores associated with each prediction that can facilitate unprecedented financial fraud detection performance and serve as a useful decision-making aid. The results have important implications for several stakeholder groups, including compliance officers, investors, audit firms, and regulators.
Improvements in the GISTEMP Uncertainty Model Lenssen, Nathan J. L.; Schmidt, Gavin A.; Hansen, James E. ...
Journal of geophysical research. Atmospheres,
27 June 2019, Volume:
124, Issue:
12
Journal Article
Peer reviewed
Open access
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 86% likelihood that 2016 was indeed the hottest year of the instrumental period (so far).
Key Points
A total uncertainty analysis for GISTEMP is presented for the first time
Uncertainty in global mean surface temperature is roughly 0.05 degrees Celsius in recent decades increasing to 0.15 degrees Celsius in the nineteenth century
Annual mean uncertainties are small relative to the long‐term trend
Human activities and their relation with land, through agriculture and forestry, are significantly impacting Earth system functioning. Specifically, agriculture has increasingly become a key sector ...for adaptation and mitigation initiatives that address climate change and help ensure food security for a growing global population. Climate change and agricultural outcomes influence our ability to reach targets for at least seven of the 17 Sustainable Development Goals. By 2015, 103 nations had committed themselves to reduce greenhouse gas emissions from agriculture, while 102 countries had prioritized agriculture in their adaptation agenda. Adaptation and mitigation actions within agriculture still receive insufficient support across scales, from local to international level. This paper reviews a series of climate change adaptation and mitigation options that can support increased production, production efficiency and greater food security for 9 billion people by 2050. Climate-smart agriculture can help foster synergies between productivity, adaptation, and mitigation, although trade-offs may be equally apparent. This study highlights the importance of identifying and exploiting those synergies in the context of Nationally Determined Contributions. Finally, the paper points out that keeping global warming to 2 °C above pre-industrial levels by 2100 requires going beyond the agriculture sector and exploring possibilities with respect to reduced emissions from deforestation, food loss, and waste, as well as from rethinking human diets.
We assess climate impacts of global warming using ongoing observations and paleoclimate data. We use Earth's measured energy imbalance, paleoclimate data, and simple representations of the global ...carbon cycle and temperature to define emission reductions needed to stabilize climate and avoid potentially disastrous impacts on today's young people, future generations, and nature. A cumulative industrial-era limit of ∼500 GtC fossil fuel emissions and 100 GtC storage in the biosphere and soil would keep climate close to the Holocene range to which humanity and other species are adapted. Cumulative emissions of ∼1000 GtC, sometimes associated with 2°C global warming, would spur "slow" feedbacks and eventual warming of 3-4°C with disastrous consequences. Rapid emissions reduction is required to restore Earth's energy balance and avoid ocean heat uptake that would practically guarantee irreversible effects. Continuation of high fossil fuel emissions, given current knowledge of the consequences, would be an act of extraordinary witting intergenerational injustice. Responsible policymaking requires a rising price on carbon emissions that would preclude emissions from most remaining coal and unconventional fossil fuels and phase down emissions from conventional fossil fuels.
Purpose
This paper aims to investigate inferences consumers make about organic and all-natural labeled products in both food and non-food contexts using the health halo effect as a theoretical ...foundation.
Design/methodology/approach
This paper uses three experiments to test the effects of organic and all-natural labeling across three product types, food, personal hygiene and household cleaning, while controlling for environmental attitudes.
Findings
The results of the experiments in the context of food, personal hygiene and household cleaning products suggest that both organic and all-natural labeling produce halo effects. Distinct findings are presented across the three product types.
Research limitations/implications
Findings indicate that consumers may make unwarranted inferences about both organic and all-natural labeled products and demonstrates that the health halo effect is a potentially robust phenomenon, pervasive across a diverse array of products. This research used a crowdsourcing platform for sample recruitment. Future research should validate the results of these experiments with other sample types.
Practical implications
This research suggests that consumers may make similar unwarranted inferences for diverse products bearing organic and all-natural labels. These inferences are particularly intriguing given the differing regulatory requirements for the labels
Originality/value
Organic and all-natural labels are ubiquitous in both food and non-food products. However, research on either label primarily exists in a food context and has not directly compared the labels. Understanding the inferences consumers make based on the labels across product types is imperative for both marketing and public policy.
To improve the prediction of crop yields at an aggregate scale, we developed a data assimilation-crop modeling framework that incorporates remotely sensed soil moisture and leaf area index (LAI) into ...a crop model using sequential data assimilation. The core of the framework is an Ensemble Kalman Filter (EnKF) used to control crop model runs, assimilate remote sensing (RS) data and update model state variables. We modified the Decision Support System for Agro-technology Transfer – Cropping System Model (DSSAT-CSM)-Maize model (Jones et al., 2003) to be able to stop and start simulations at any given time in the growing season, such that the EnKF can update model state variables as RS data become available. The data assimilation-crop modeling framework was evaluated against 2003–2009 maize yields in Story County, Iowa, USA, assimilating AMSR-E soil moisture and MODIS-LAI data independently and simultaneously. Assimilating LAI or soil moisture independently slightly improved the correlation of observed and simulated yields (R=0.51 and 0.50) compared to no data assimilation (open-loop; R=0.47) but prediction errors improved with reductions in MBE and RMSE by 0.5 and 0.5Mgha−1 respectively for LAI assimilation while these were reduced by 1.8 and 1.1Mgha−1 for soil moisture assimilation. Yield correlation improved more when both soil moisture and LAI were assimilated (R=0.65) suggesting a cause–effect interaction between soil moisture and LAI, prediction errors (MBE and RMSE) were also reduced by 1.7 and 1.8Mgha−1 with respect to open-loop simulations. Results suggest that assimilation of LAI independently might be preferable when conditions are extremely wet while assimilation of soil moisture+LAI might be more suitable when conditions are more nominal. AMSR-E soil moisture tends to be more biased under the presence of high vegetation (i.e., when crops are fully developed) and that updating rootzone soil moisture by near-surface soil moisture assimilation under very wet conditions could increase the modeled percolation causing excessive nitrogen (N) leaching hence reducing crop yields even with water stress reduced at a minimum due to soil moisture assimilation. However, applying the data assimilation-crop modeling framework strategically by considering a-priori information on climate condition expected during the growing season may improve yield prediction performance substantially, in our case with higher correlation (R=0.80) and more reductions in MBE and RMSE (2.5 and 3.3Mgha−1) compared to when there is no data assimilation. Scaling AMSR-E soil moisture to the climatology of the model did not improve our data assimilation results because the model is also biased. Better soil moisture products e.g., from Soil Moisture Active Passive (SMAP) mission, may solve the soil moisture data issue in the near future.
•Assimilation of RS soil moisture and LAI with crop model to predict crop yields at aggregate scale.•Assimilating LAI or soil moisture slightly improved yield prediction.•Yield prediction performance improved more when both soil moisture and LAI were assimilated.•Applying the method strategically improved yield prediction performance substantially.
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