scholarly journals Adaptation in an Uncertain World—Detection and Attribution of Climate Change Trends and Extreme Possibilities

2019 ◽  
Author(s):  
Xiyue Li ◽  
Gary Yohe
Keyword(s):  
Climate Change ◽  
Historical Data ◽  
Affirmative Answer ◽  
Anthropogenic Sources ◽  
Data Series ◽  
High Confidence ◽  
Simulation Exercise ◽  
Detection And Attribution ◽  
Uncertain Future ◽  
Insight Into

This chapter offers results from an artificial simulation exercise that was designed to answer three fundamental questions that lie at the heart of anticipatory adaptation. First, how can confidence in projected vulnerabilities and impacts be greater than the confidence in attributing what has heretofore been observed? Second, are there characteristics of recent historical data series that do or do not portend our achieving high confidence in attribution to climate change in support of framing adaptation decisions in an uncertain future? And finally, what can analysis of confidence in attribution tell us about ranges of “not-implausible” extreme futures vis-à-vis projections based at least implicitly on an assumption that the climate system is static? An extension of the IPCC method of assessing our confidence in attribution to anthropogenic sources of detected warming presents an answer to the first question. It is also possible to identify characteristics that support an affirmative answer to the second. Finally, this chapter offer some insight into the significance of our attribution methodology in informing attempts to frame considerations of potential extremes and how to respond.

scholarly journals Tropical Cyclones and Climate Change Assessment: Part I: Detection and Attribution

2019 ◽  
Vol 100 (10) ◽  
pp. 1987-2007 ◽  
Author(s):  
Thomas Knutson ◽  
Suzana J. Camargo ◽  
Johnny C. L. Chan ◽  
Kerry Emanuel ◽  
Chang-Hoi Ho ◽  
...  
Keyword(s):  
Climate Change ◽  
Historical Data ◽  
False Alarms ◽  
Type I ◽  
Anthropogenic Influence ◽  
Type Ii ◽  
Type I Errors ◽  
Detection And Attribution ◽  
Climate Change Assessment ◽  
Type Ii Errors

AbstractAn assessment was made of whether detectable changes in tropical cyclone (TC) activity are identifiable in observations and whether any changes can be attributed to anthropogenic climate change. Overall, historical data suggest detectable TC activity changes in some regions associated with TC track changes, while data quality and quantity issues create greater challenges for analyses based on TC intensity and frequency. A number of specific published conclusions (case studies) about possible detectable anthropogenic influence on TCs were assessed using the conventional approach of preferentially avoiding type I errors (i.e., overstating anthropogenic influence or detection). We conclude there is at least low to medium confidence that the observed poleward migration of the latitude of maximum intensity in the western North Pacific is detectable, or highly unusual compared to expected natural variability. Opinion on the author team was divided on whether any observed TC changes demonstrate discernible anthropogenic influence, or whether any other observed changes represent detectable changes. The issue was then reframed by assessing evidence for detectable anthropogenic influence while seeking to reduce the chance of type II errors (i.e., missing or understating anthropogenic influence or detection). For this purpose, we used a much weaker “balance of evidence” criterion for assessment. This leads to a number of more speculative TC detection and/or attribution statements, which we recognize have substantial potential for being false alarms (i.e., overstating anthropogenic influence or detection) but which may be useful for risk assessment. Several examples of these alternative statements, derived using this approach, are presented in the report.

scholarly journals Czech Building Stock: Renovation Wave Scenarios and Potential for CO2 Savings until 2050

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2455
Author(s):  
Antonín Lupíšek ◽  
Tomáš Trubačík ◽  
Petr Holub
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Climate Change Mitigation ◽  
Emission Factors ◽  
Anthropogenic Sources ◽  
Building Stock ◽  
National Debate ◽  
Energy Consumptions ◽  
Change Mitigation

One of the major anthropogenic sources of greenhouse gases is the operation of building stock. Improving its energy efficiency has the potential to significantly contribute to achieving climate change mitigation targets. The purpose of this study was to roughly estimate such potential for the operation of the national building stock of Czechia to steer the national debate on the development of related national plans. The estimation is based on a simplified energy model of the Czech building stock that consists of sub-models of residential and nonresidential building stocks, for which their future energy consumptions, shares of energy carriers and sources, and emission factors were modeled in four scenarios. Uncertainties from the approximation of the emission factors were investigated in a sensitivity analysis. The results showed that the operation of the Czech building stock in 2016 totaled 36.9 Mt CO2, which represented 34.6% of the total national carbon dioxide emissions. The four building stock scenarios could produce reductions in the carbon dioxide emissions of between 28% and 93% by 2050, when also considering on-side production from photovoltaics. The implementation of the most ambitious scenario would represent a drop in national CO2 yearly emissions by 43.2% by 2050 (compared to 2016).

scholarly journals Detecting bursty terms in computer science research

2019 ◽  
Vol 122 (1) ◽  
pp. 681-699 ◽  
Author(s):  
E. Tattershall ◽  
G. Nenadic ◽  
R. D. Stevens
Keyword(s):  
Computer Science ◽  
Historical Data ◽  
Science Research ◽  
Detection Algorithm ◽  
Trend Detection ◽  
Free Text ◽  
Research Topics ◽  
Computer Science Research ◽  
Insight Into ◽  
Over Time

AbstractResearch topics rise and fall in popularity over time, some more swiftly than others. The fastest rising topics are typically called bursts; for example “deep learning”, “internet of things” and “big data”. Being able to automatically detect and track bursty terms in the literature could give insight into how scientific thought evolves over time. In this paper, we take a trend detection algorithm from stock market analysis and apply it to over 30 years of computer science research abstracts, treating the prevalence of each term in the dataset like the price of a stock. Unlike previous work in this domain, we use the free text of abstracts and titles, resulting in a finer-grained analysis. We report a list of bursty terms, and then use historical data to build a classifier to predict whether they will rise or fall in popularity in the future, obtaining accuracy in the region of 80%. The proposed methodology can be applied to any time-ordered collection of text to yield past and present bursty terms and predict their probable fate.

scholarly journals How Does the Arctic Council Support Conservation of Arctic Biodiversity?

2020 ◽  
Vol 12 (12) ◽  
pp. 5042
Author(s):  
Tom Barry ◽  
Brynhildur Daviðsdóttir ◽  
Níels Einarsson ◽  
Oran R. Young
Keyword(s):  
Climate Change ◽  
Sustainable Development ◽  
Environmental Protection ◽  
Indigenous Communities ◽  
The Arctic ◽  
Arctic Council ◽  
National Interests ◽  
Conflicting Demands ◽  
Agent Of Change ◽  
Insight Into

The Arctic Council is an intergovernmental forum promoting cooperation, coordination and interaction among Arctic states, indigenous communities, and peoples on issues of common importance. The rising geo-political importance of the Arctic and the onset of climate change has resulted in the Council becoming a focus of increasing interest from both inside and beyond the Arctic. This has resulted in new demands placed on the Council, attracting an increasing number of participants, and instigating a period of transformation as Arctic states work to find a way to balance conflicting demands to improve the Council’s effectiveness and take care of national interests. This paper considers whether, during this time of change, the Council is having an impact on the issues it was formed to address, i.e., environmental protection and sustainable development. To provide answers, it looks at how the Council reports on and evaluates progress towards the implementation of recommendations it makes regarding biodiversity, how it identifies where activities have had impacts and uncovers the mechanisms through which they were successful, to provide an insight into how the Arctic Council can be an agent of change.

scholarly journals A Bayesian Climate Change Detection and Attribution Assessment

2005 ◽  
Vol 18 (13) ◽  
pp. 2429-2440 ◽  
Author(s):  
Terry C. K. Lee ◽  
Francis W. Zwiers ◽  
Gabriele C. Hegerl ◽  
Xuebin Zhang ◽  
Min Tsao
Keyword(s):  
Climate Change ◽  
Strong Evidence ◽  
Climate Model ◽  
Consistency Test ◽  
Change Question ◽  
Detection And Attribution ◽  
Complex Process ◽  
Detection Approach ◽  
Limited Length ◽  
Observational Record

Abstract A Bayesian analysis of the evidence for human-induced climate change in global surface temperature observations is described. The analysis uses the standard optimal detection approach and explicitly incorporates prior knowledge about uncertainty and the influence of humans on the climate. This knowledge is expressed through prior distributions that are noncommittal on the climate change question. Evidence for detection and attribution is assessed probabilistically using clearly defined criteria. Detection requires that there is high likelihood that a given climate-model-simulated response to historical changes in greenhouse gas concentration and sulphate aerosol loading has been identified in observations. Attribution entails a more complex process that involves both the elimination of other plausible explanations of change and an assessment of the likelihood that the climate-model-simulated response to historical forcing changes is correct. The Bayesian formalism used in this study deals with this latter aspect of attribution in a more satisfactory way than the standard attribution consistency test. Very strong evidence is found to support the detection of an anthropogenic influence on the climate of the twentieth century. However, the evidence from the Bayesian attribution assessment is not as strong, possibly due to the limited length of the available observational record or sources of external forcing on the climate system that have not been accounted for in this study. It is estimated that strong evidence from a Bayesian attribution assessment using a relatively stringent attribution criterion may be available by 2020.

scholarly journals Natural and anthropogenic sources of salinity in the Awash River and Lake Beseka (Ethiopia): Modelling impacts of climate change and lake-river interactions

2021 ◽  
Vol 36 ◽  
pp. 100865
Author(s):  
Li Jin ◽  
Paul G. Whitehead ◽  
Gianbattista Bussi ◽  
Feyera Hirpa ◽  
Meron Teferi Taye ◽  
...  
Keyword(s):  
Climate Change ◽  
Anthropogenic Sources ◽  
Impacts Of Climate Change

Large Surface Effect Ship Size Limits

2013 ◽  
Vol 29 (02) ◽  
pp. 84-91
Author(s):  
Stefanos Koullias ◽  
Santiago Balestrini Robinson ◽  
Dimitri N. Mavris
Keyword(s):  
Historical Data ◽  
Surface Effect ◽  
Advanced Materials ◽  
Complex Structures ◽  
First Principle ◽  
Simplified Models ◽  
Surface Effect Ship ◽  
Size Limits ◽  
Technology Level ◽  
Insight Into

The purpose of this study is to obtain insight into surface effect ship (SES) endurance without reliance on historical data as a function of geometry, displacement, and technology level. First-principle models of the resistance, structures, and propulsion system are developed and integrated to predict large SES endurance and to suggest the directions that future large SESs will take. It is found that large SESs are dominated by structural weight, which indicates the need for advanced materials and complex structures, and that advanced propulsion cycles can increase endurance by up to 33%. SES endurance is shown to be a nonlinear discontinuous function of geometry, displacement, and technology level that cannot be predicted by simplified models or assumptions.

scholarly journals Pan-spectral observing system simulation experiments of shortwave reflectance and long-wave radiance for climate model evaluation

2015 ◽  
Vol 8 (7) ◽  
pp. 1943-1954 ◽  
Author(s):  
D. R. Feldman ◽  
W. D. Collins ◽  
J. L. Paige
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Coupled Model ◽  
Climate System ◽  
Spectral Measurements ◽  
Intergovernmental Panel ◽  
Climate System Model ◽  
Detection And Attribution ◽  
Long Wave ◽  
Hadley Centre

Abstract. Top-of-atmosphere (TOA) spectrally resolved shortwave reflectances and long-wave radiances describe the response of the Earth's surface and atmosphere to feedback processes and human-induced forcings. In order to evaluate proposed long-duration spectral measurements, we have projected 21st Century changes from the Community Climate System Model (CCSM3.0) conducted for the Intergovernmental Panel on Climate Change (IPCC) A2 Emissions Scenario onto shortwave reflectance spectra from 300 to 2500 nm and long-wave radiance spectra from 2000 to 200 cm−1 at 8 nm and 1 cm−1 resolution, respectively. The radiative transfer calculations have been rigorously validated against published standards and produce complementary signals describing the climate system forcings and feedbacks. Additional demonstration experiments were performed with the Model for Interdisciplinary Research on Climate (MIROC5) and Hadley Centre Global Environment Model version 2 Earth System (HadGEM2-ES) models for the Representative Concentration Pathway 8.5 (RCP8.5) scenario. The calculations contain readily distinguishable signatures of low clouds, snow/ice, aerosols, temperature gradients, and water vapour distributions. The goal of this effort is to understand both how climate change alters reflected solar and emitted infrared spectra of the Earth and determine whether spectral measurements enhance our detection and attribution of climate change. This effort also presents a path forward to understand the characteristics of hyperspectral observational records needed to confront models and inline instrument simulation. Such simulation will enable a diverse set of comparisons between model results from coupled model intercomparisons and existing and proposed satellite instrument measurement systems.

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