text:
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Number-of-Cited-References = {{70}},
Times-Cited = {{13}},
Usage-Count-Last-180-days = {{5}},
Usage-Count-Since-2013 = {{22}},
Journal-ISO = {{J. Clim.}},
Doc-Delivery-Number = {{HB0FM}},
Unique-ID = {{ISI:000450688200007}},
OA = {{Bronze}},
DA = {{2020-08-06}},
}

@article{ ISI:000439401800059,
Author = {Fang, Wei and Huang, Shengzhi and Huang, Qiang and Huang, Guohe and
   Meng, Erhao and Luan, Jinkai},
Title = {{Reference evapotranspiration forecasting based on local meteorological
   and global climate information screened by partial mutual information}},
Journal = {{JOURNAL OF HYDROLOGY}},
Year = {{2018}},
Volume = {{561}},
Pages = {{764-779}},
Month = {{JUN}},
Abstract = {{In this study, reference evapotranspiration (ETo) forecasting models are
   developed for the least economically developed regions subject to
   meteorological data scarcity. Firstly, the partial mutual information
   (PMI) capable of capturing the linear and nonlinear dependence is
   investigated regarding its utility to identify relevant predictors and
   exclude those that are redundant through the comparison with partial
   linear correlation. An efficient input selection technique is crucial
   for decreasing model data requirements. Then, the interconnection
   between global climate indices and regional ETo is identified. Relevant
   climatic indices are introduced as additional predictors to comprise
   information regarding ETo, which ought to be provided by meteorological
   data unavailable. The case study in the Jing River and Beiluo River
   basins, China, reveals that PMI outperforms the partial linear
   correlation in excluding the redundant information, favouring the yield
   of smaller predictor sets. The teleconnection analysis identifies the
   correlation between Nino 1 + 2 and regional ETo, indicating influences
   of ENSO events on the evapotranspiration process in the study area.
   Furthermore, introducing Nino 1 + 2 as predictors helps to yield more
   accurate ET forecasts. A model performance comparison also shows that
   nonlinear stochastic models (SVR or RF with input selection through PMI)
   do not always outperform linear models (MLR with inputs screen by linear
   correlation). However, the former can offer quite comparable performance
   depending on smaller predictor sets. Therefore, efforts such as
   screening model inputs through PMI and incorporating global climatic
   indices interconnected with ETo can benefit the development of ETo,
   forecasting models suitable for data-scarce regions.}},
Publisher = {{ELSEVIER}},
Address = {{RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Huang, SZ (Corresponding Author), Xian Univ Technol, State Key Lab Ecohydraul Northwest Arid Reg China, Xian 710048, Shaanxi, Peoples R China.
   Fang, Wei; Huang, Shengzhi; Huang, Qiang; Meng, Erhao; Luan, Jinkai, Xian Univ Technol, State Key Lab Ecohydraul Northwest Arid Reg China, Xian 710048, Shaanxi, Peoples R China.
   Huang, Guohe, Univ Regina, Inst Energy Environm \& Sustainable Communities, Regina, SK S4S 0A2, Canada.}},
DOI = {{10.1016/j.jhydrol.2018.04.038}},
ISSN = {{0022-1694}},
EISSN = {{1879-2707}},
Keywords = {{Evapotranspiration; Partial mutual information; Climatic indices;
   Teleconnection}},
Keywords-Plus = {{ARTIFICIAL NEURAL-NETWORKS; SOLAR-RADIATION; VARIABLE SELECTION;
   RIVER-BASIN; MODELS; ENSO; RAINFALL; PRECIPITATION; ASSOCIATION;
   VARIABILITY}},
Research-Areas = {{Engineering; Geology; Water Resources}},
Web-of-Science-Categories  = {{Engineering, Civil; Geosciences, Multidisciplinary; Water Resources}},
Author-Email = {{huangshengzhi@xaut.edu.cn}},
ResearcherID-Numbers = {{Huang, Guohe/AAA-7305-2019
   Huang, Guohe/H-5306-2011
   }},
ORCID-Numbers = {{Huang, Guohe/0000-0003-4974-3019
   Fang, Wei/0000-0001-5616-1645}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}51709221]; Planning project of science and
   technology of water resources of Shaanxi {[}2017s1kj-19]; National
   Department Public Benefit Research Foundation of Ministry of Water
   Resources {[}201501058]; China Scholarship CouncilChina Scholarship
   Council {[}201608610170]; Xi'an University of Technology
   {[}310-252071712]; School of Water Resources and Hydropower of Xi'an
   University of Technology {[}2016ZZKT-15]}},
Funding-Text = {{This study was joint funded by the National Natural Science Foundation
   of China (grant number 51709221), the Planning project of science and
   technology of water resources of Shaanxi (grant number 2017s1kj-19), the
   National Department Public Benefit Research Foundation of Ministry of
   Water Resources (grant number 201501058), China Scholarship Council
   (grant number 201608610170), the doctorate innovation funding of Xi'an
   University of Technology (grant number 310-252071712) and the project of
   School of Water Resources and Hydropower of Xi'an University of
   Technology (grant number 2016ZZKT-15). Interested readers can access the
   data used in this study by contacting the first author.}},
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Number-of-Cited-References = {{63}},
Times-Cited = {{14}},
Usage-Count-Last-180-days = {{5}},
Usage-Count-Since-2013 = {{28}},
Journal-ISO = {{J. Hydrol.}},
Doc-Delivery-Number = {{GN8HZ}},
Unique-ID = {{ISI:000439401800059}},
DA = {{2020-08-06}},
}

@article{ ISI:000437892300008,
Author = {Neumann, Jessica and Arnal, Louise and Magnusson, Linus and Cloke,
   Hannah},
Title = {{The 2013/14 Thames Basin Floods: Do Improved Meteorological Forecasts
   Lead to More Skillful Hydrological Forecasts at Seasonal Time Scales?}},
Journal = {{JOURNAL OF HYDROMETEOROLOGY}},
Year = {{2018}},
Volume = {{19}},
Number = {{6}},
Pages = {{1059-1075}},
Month = {{JUN}},
Abstract = {{The Thames basin experienced 12 major Atlantic depressions in winter
   2013/14, leading to extensive and prolonged fluvial and groundwater
   flooding. This exceptional weather coincided with highly anomalous
   meteorological conditions across the globe. Atmospheric relaxation
   experiments, whereby conditions within specified regions are relaxed
   toward a reanalysis, have been used to investigate teleconnection
   patterns. However, no studies have examined whether improvements to
   seasonal meteorological forecasts translate into more skillful seasonal
   hydrological forecasts. This study applied relaxation experiments to
   reforecast the 2013/14 floods for three Thames basin catchments with
   different hydrogeological characteristics. The tropics played an
   important role in the development of extreme conditions over the Thames
   basin. The greatest hydrological forecasting skill was associated with
   the tropical Atlantic and less with the tropical Pacific, although both
   captured seasonal meteorological flow anomalies. Relaxation applied over
   the northeastern Atlantic produced confident ensemble forecasts, but
   hydrological extremes were underpredicted; this was unexpected with
   relaxation applied so close to the United Kingdom. Streamflow was most
   skillfully forecast for the catchment representing a large drainage area
   with high peak flow. Permeable lithology and antecedent conditions were
   important for skillfully forecasting groundwater levels. Atmospheric
   relaxation experiments can improve our understanding of extratropical
   anomalies and the potential predictability of extreme events such as the
   Thames 2013/14 floods. Seasonal hydrological forecasts differed from
   what was expected from the meteorology alone, and thus knowledge is
   gained by considering both components. In the densely populated Thames
   basin, considering the local hydrogeological context can provide an
   effective early alert of potential high-impact events, allowing for
   better preparedness.}},
Publisher = {{AMER METEOROLOGICAL SOC}},
Address = {{45 BEACON ST, BOSTON, MA 02108-3693 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Neumann, J (Corresponding Author), Univ Reading, Dept Geog \& Environm Sci, Reading, Berks, England.
   Neumann, Jessica; Arnal, Louise; Cloke, Hannah, Univ Reading, Dept Geog \& Environm Sci, Reading, Berks, England.
   Arnal, Louise; Magnusson, Linus, European Ctr Medium Range Weather Forecasts, Reading, Berks, England.
   Cloke, Hannah, Univ Reading, Dept Meteorol, Reading, Berks, England.}},
DOI = {{10.1175/JHM-D-17-0182.1}},
ISSN = {{1525-755X}},
EISSN = {{1525-7541}},
Keywords = {{Europe; Extratropics; Hydrometeorology; Seasonal forecasting; Anomalies;
   Flood events}},
Keywords-Plus = {{NORTHERN-HEMISPHERE WINTER; ALERT SYSTEM; RIVER FLOWS; UK; PREDICTION;
   STREAMFLOW; ELASTICITY; RAINFALL; EUROPE; RECORD}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{j.l.neumann@reading.ac.uk}},
ORCID-Numbers = {{Magnusson, Linus/0000-0003-4707-2231}},
Funding-Acknowledgement = {{EU Horizon 2020 IMPREX project {[}641811]}},
Funding-Text = {{This work was supported and funded by the EU Horizon 2020 IMPREX project
   (http://www.imprex.eu/) (641811). Borehole groundwater level data and
   flood alert exceedance thresholds were made available by the Environment
   Agency, and we thank Simon Lewis and Stuart Hyslop at the Environment
   Agency for useful discussions on seasonal forecasting in theThames
   basin. The authors have no conflicts of interest to declare.}},
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   Wood AW, 2016, J HYDROMETEOROL, V17, P651, DOI 10.1175/JHM-D-14-0213.1.
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   Yossef NC, 2013, WATER RESOUR RES, V49, P4687, DOI 10.1002/wrcr.20350.}},
Number-of-Cited-References = {{59}},
Times-Cited = {{2}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{J. Hydrometeorol.}},
Doc-Delivery-Number = {{GM2DV}},
Unique-ID = {{ISI:000437892300008}},
OA = {{Other Gold, Green Accepted}},
DA = {{2020-08-06}},
}

@article{ ISI:000434132900004,
Author = {Tukker, Arnold and Giljum, Stefan and Wood, Richard},
Title = {{Recent Progress in Assessment of Resource Efficiency and Environmental
   Impacts Embodied in Trade: An Introduction to this Special Issue}},
Journal = {{JOURNAL OF INDUSTRIAL ECOLOGY}},
Year = {{2018}},
Volume = {{22}},
Number = {{3, SI}},
Pages = {{489-501}},
Month = {{JUN}},
Abstract = {{This paper serves as an introduction to this special issue on the use of
   multiregional input-output modeling in assessments of natural resource
   use and resource use efficiency. Due to globalization, growth in trade
   has outpaced growth in global gross domestic product (GDP). As a
   consequence, impacts of consumption of a country increasingly take place
   abroad. Various methods have been developed to perform so-called
   footprint analyses. We argue that global multiregional input-output
   (GMRIO) analysis has the largest potential to provide a consistent
   accounting framework to calculate a variety of different footprint
   indicators. The state of the art in GMRIO has, however, various
   shortcomings, such as limited sector and regional detail and incomplete
   extensions. The work presented in this special issue addresses a number
   of such problems and how to possibly overcome them, focusing on the
   construction of a new GMRIO database (EXIOBASE V3). This database
   includes long time series in both current and constant prices, a high
   level of product and sector detail, a physical representation of the
   world economy, and allows analyzing which footprints out of the many
   possible indicators provide most information for policy making. Various
   options for empirical analyses are presented in this special issue.
   Finally, we analyze how GMRIOs can be further standardized and gradually
   moved from the scientific to the official statistical domain.}},
Publisher = {{WILEY}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Tukker, A (Corresponding Author), Leiden Univ, Inst Environm Sci CML, POB 9518, NL-2300 RA Leiden, Netherlands.
   Tukker, Arnold, Leiden Univ, Inst Environm Sci CML, POB 9518, NL-2300 RA Leiden, Netherlands.
   Tukker, Arnold, Netherlands Org Appl Sci Res TNO, Delft, Netherlands.
   Giljum, Stefan, Vienna Univ Econ \& Business WU, Inst Ecol Econ, Vienna, Austria.
   Wood, Richard, Norwegian Univ Sci \& Technol, Trondheim, Norway.}},
DOI = {{10.1111/jiec.12736}},
ISSN = {{1088-1980}},
EISSN = {{1530-9290}},
Keywords = {{embodied impacts; embodiments in trade; impact assessment; industrial
   ecology; input-output analysis (IOA); robustness}},
Keywords-Plus = {{INPUT-OUTPUT-ANALYSIS; STRUCTURAL DECOMPOSITION ANALYSIS; RAW-MATERIAL
   CONSUMPTION; CARBON FOOTPRINT; INTERNATIONAL-TRADE; WATER FOOTPRINTS;
   EUROPEAN-UNION; TIME-SERIES; INDICATORS; EMISSIONS}},
Research-Areas = {{Science \& Technology - Other Topics; Engineering; Environmental
   Sciences \& Ecology}},
Web-of-Science-Categories  = {{Green \& Sustainable Science \& Technology; Engineering, Environmental;
   Environmental Sciences}},
Author-Email = {{tukker@cml.leidenuniv.nl}},
ResearcherID-Numbers = {{Tukker, Arnold/M-4596-2013
   Wood, Richard/E-4111-2015
   Giljum, Stefan/M-3162-2015}},
ORCID-Numbers = {{Tukker, Arnold/0000-0002-8229-2929
   Wood, Richard/0000-0002-7906-3324
   Giljum, Stefan/0000-0002-4719-5867}},
Funding-Acknowledgement = {{European UnionEuropean Union (EU) {[}308552]}},
Funding-Text = {{This paper has been written in the context of the Development of a
   System of Indicators for a Resource Efficient Europe (DESIRE), a
   Collaborative project under the Seventh Framework Program of the
   European Union, Grant agreement no: 308552.}},
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Number-of-Cited-References = {{76}},
Times-Cited = {{21}},
Usage-Count-Last-180-days = {{3}},
Usage-Count-Since-2013 = {{50}},
Journal-ISO = {{J. Ind. Ecol.}},
Doc-Delivery-Number = {{GI1LV}},
Unique-ID = {{ISI:000434132900004}},
OA = {{Green Published, Other Gold, Green Accepted}},
DA = {{2020-08-06}},
}

@article{ ISI:000434132900010,
Author = {Steinmann, Zoran J. N. and Schipper, Aafke M. and Stadler, Konstantin
   and Wood, Richard and de Koning, Arjan and Tukker, Arnold and
   Huijbregts, Mark A. J.},
Title = {{Headline Environmental Indicators Revisited with the Global
   Multi-Regional Input-Output Database EXIOBASE}},
Journal = {{JOURNAL OF INDUSTRIAL ECOLOGY}},
Year = {{2018}},
Volume = {{22}},
Number = {{3, SI}},
Pages = {{565-573}},
Month = {{JUN}},
Abstract = {{Environmentally extended multiregion input-output (EEMRIO) databases are
   used to quantify numerous environmental pressures and impacts from a
   consumption perspective. However, for targeted communication with
   decision makers, large sets of impact indicators are unfavorable. Small
   sets of headline indicators have been proposed to guide environmental
   policy, but these may not cover all relevant aspects of environmental
   impact. The aim of our study was to evaluate the extent to which a set
   of four headline indicators (material, land, water, and carbon) is
   representative of the total environmental impact embedded in an EEMRIO
   database. We also used principal component analysis combined with linear
   regression to investigate which environmental indicators are good
   candidates to supplement this headline indicator set, using 119
   environmental indicators linked to the EEMRIO database, EXIOBASE. We
   found that the four headline indicators covered 59.9\% of the variance
   in product-region rankings among environmental indicators, with carbon
   and land already explaining 57.4\%. Five additional environmental
   indicators (marine eco-toxicity, terrestrial eco-toxicity, photochemical
   oxidation, terrestrial acidification, and eutrophication) were needed to
   cover 95\% of the variance. In comparison, a statistically optimal set
   of seven indicators explained 95\% of the variance as well. Our findings
   imply that there is (1) a significant statistical redundancy in the four
   headline indicators, and (2) a considerable share of the variance is
   caused by other environmental impacts not covered by the headline
   indicators. The results of our study can be used to further optimize the
   set of headline indicators for environmental policy.}},
Publisher = {{WILEY}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Steinmann, ZJ (Corresponding Author), Radboud Univ Nijmegen, Dept Environm Sci, POB 9010,Box 89, NL-6500 GL Nijmegen, Netherlands.
   Steinmann, Zoran J. N.; Huijbregts, Mark A. J., Radboud Univ Nijmegen, Dept Environm Sci, POB 9010,Box 89, NL-6500 GL Nijmegen, Netherlands.
   Schipper, Aafke M., Planbureau Leefomgeving, Den Hagg, Netherlands.
   Stadler, Konstantin; Wood, Richard, NTNU, Trondheim, Norway.
   de Koning, Arjan; Tukker, Arnold, Leiden Univ, CML, Leiden, Netherlands.
   Tukker, Arnold, TNO, Delft, Netherlands.}},
DOI = {{10.1111/jiec.12694}},
ISSN = {{1088-1980}},
EISSN = {{1530-9290}},
Keywords = {{EEMRIO; environmental indicator; EXIOBASE; industrial ecology;
   input-output analysis (IOA); principal component analysis (PCA)}},
Keywords-Plus = {{PRINCIPAL COMPONENT ANALYSIS; CYCLE IMPACT ASSESSMENT; CARBON FOOTPRINT
   SERVE; MULTIOBJECTIVE OPTIMIZATION; INTERNATIONAL-TRADE; WATER
   FOOTPRINT; CONSUMPTION; CONSTRUCTION; DESIGN; BURDEN}},
Research-Areas = {{Science \& Technology - Other Topics; Engineering; Environmental
   Sciences \& Ecology}},
Web-of-Science-Categories  = {{Green \& Sustainable Science \& Technology; Engineering, Environmental;
   Environmental Sciences}},
Author-Email = {{z.steinmann@science.ru.nl}},
ResearcherID-Numbers = {{Tukker, Arnold/M-4596-2013
   Schipper, Aafke M/C-2758-2011
   Stadler, Konstantin/H-7541-2019
   Huijbregts, Mark A.J./B-8971-2011
   Wood, Richard/E-4111-2015
   }},
ORCID-Numbers = {{Tukker, Arnold/0000-0002-8229-2929
   Stadler, Konstantin/0000-0002-1548-201X
   Huijbregts, Mark A.J./0000-0002-7037-680X
   Wood, Richard/0000-0002-7906-3324
   Steinmann, Zoran/0000-0001-8606-917X}},
Funding-Acknowledgement = {{European CommissionEuropean Commission Joint Research Centre {[}308552]}},
Funding-Text = {{This work was funded by the European Commission Seventh Framework
   Programme 308552.}},
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Number-of-Cited-References = {{38}},
Times-Cited = {{9}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{14}},
Journal-ISO = {{J. Ind. Ecol.}},
Doc-Delivery-Number = {{GI1LV}},
Unique-ID = {{ISI:000434132900010}},
OA = {{Other Gold, Green Published}},
DA = {{2020-08-06}},
}

@article{ ISI:000434132900012,
Author = {Tukker, Arnold and de Koning, Arjan and Owen, Anne and Lutter, Stephan
   and Bruckner, Martin and Giljum, Stefan and Stadler, Konstantin and
   Wood, Richard and Hoekstra, Rutger},
Title = {{Towards Robust, Authoritative Assessments of Environmental Impacts
   Embodied in Trade: Current State and Recommendations}},
Journal = {{JOURNAL OF INDUSTRIAL ECOLOGY}},
Year = {{2018}},
Volume = {{22}},
Number = {{3, SI}},
Pages = {{585-598}},
Month = {{JUN}},
Abstract = {{Global multiregional input-output databases (GMRIOs) became the standard
   tool for tracking environmental impacts through global supply chains. To
   date, several GMRIOs are available, but the numerical results differ.
   This paper considers how GMRIOs can be made more robust and
   authoritative. We show that GMRIOs need detail in environmentally
   relevant sectors. On the basis of a review of earlier work, we conclude
   that the highest uncertainty in footprint analyses is caused by the
   environmental data used in a GMRIO, followed by the size of country
   measured in gross domestic product (GDP) as fraction of the global
   total, the structure of the national table, and only at the end the
   structure of trade. We suggest the following to enhance robustness of
   results. In the short term, we recommend using the Single country
   National Accounts Consistent footprint approach, that uses official data
   for extensions and the national table for the country in question,
   combined with embodiments in imports calculated using a GMRIO. In a time
   period of 2 to 3 years, we propose work on harmonized environmental data
   for water, carbon, materials, and land, and use the aggregated
   Organization for Economic Cooperation and Development (OECD)
   Inter-Country Input-Output GMRIO as default in combination with
   detailing procedures developed in, for example, the EXIOBASE and Eora
   projects. In the long term, solutions should be coordinated by the
   international organizations such as the United Nations (UN) Statistical
   Division, OECD, and Eurostat. This could ensure that when input-output
   tables and trade data of individual countries are combined, that the
   global totals are consistent and that bilateral trade asymmetries are
   resolved.}},
Publisher = {{WILEY}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Tukker, A (Corresponding Author), Leiden Univ, Inst Environm Sci CML, POB 9518, NL-2300 RA Leiden, Netherlands.
   Tukker, Arnold; de Koning, Arjan, Leiden Univ, Inst Environm Sci CML, POB 9518, NL-2300 RA Leiden, Netherlands.
   Tukker, Arnold, Netherlands Org Appl Sci Res TNO, Delft, Netherlands.
   Owen, Anne, Univ Leeds, Sustainabil Res Inst, Sch Earth \& Environm, Leeds, W Yorkshire, England.
   Lutter, Stephan; Bruckner, Martin; Giljum, Stefan, Vienna Univ Econ \& Business WU, Vienna, Austria.
   Stadler, Konstantin; Wood, Richard, Norwegian Univ Sci \& Technol, Trondheim, Norway.
   Hoekstra, Rutger, Stat Netherlands, The Hague, Netherlands.}},
DOI = {{10.1111/jiec.12716}},
ISSN = {{1088-1980}},
EISSN = {{1530-9290}},
Keywords = {{embodiments in trade; footprints; impact assessment; industrial ecology;
   input-output analysis (IOA); statistical offices}},
Keywords-Plus = {{INPUT-OUTPUT TABLES; INTERNATIONAL-TRADE; MRIO DATABASES; CONSUMPTION;
   CARBON; FOOTPRINT; CONSTRUCTION; EXIOBASE; DECOMPOSITION; AGGREGATION}},
Research-Areas = {{Science \& Technology - Other Topics; Engineering; Environmental
   Sciences \& Ecology}},
Web-of-Science-Categories  = {{Green \& Sustainable Science \& Technology; Engineering, Environmental;
   Environmental Sciences}},
Author-Email = {{tukker@cml.leidenuniv.nl}},
ResearcherID-Numbers = {{Stadler, Konstantin/H-7541-2019
   Bruckner, Martin/O-7443-2016
   Wood, Richard/E-4111-2015
   Giljum, Stefan/M-3162-2015
   Lutter, Stephan/AAD-1881-2019
   Tukker, Arnold/M-4596-2013
   }},
ORCID-Numbers = {{Stadler, Konstantin/0000-0002-1548-201X
   Bruckner, Martin/0000-0002-1405-7951
   Wood, Richard/0000-0002-7906-3324
   Giljum, Stefan/0000-0002-4719-5867
   Tukker, Arnold/0000-0002-8229-2929
   Hoekstra, Rutger/0000-0001-6531-9782
   Lutter, Stephan/0000-0003-0097-7535}},
Funding-Acknowledgement = {{European Commission under project DESIRE (Developing a System of
   Indicators for a Resource Efficient Europe) {[}308552]}},
Funding-Text = {{The research presented in this article was funded by the European
   Commission under the FP7 project DESIRE (Developing a System of
   Indicators for a Resource Efficient Europe) under Grant agreement no:
   308552.}},
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Number-of-Cited-References = {{49}},
Times-Cited = {{33}},
Usage-Count-Last-180-days = {{4}},
Usage-Count-Since-2013 = {{26}},
Journal-ISO = {{J. Ind. Ecol.}},
Doc-Delivery-Number = {{GI1LV}},
Unique-ID = {{ISI:000434132900012}},
OA = {{Green Accepted, Other Gold, Green Published}},
DA = {{2020-08-06}},
}

@article{ ISI:000438139000004,
Author = {Yan, Xin and Ren, Juzhang and Ju, Jianhua and Yang, Song},
Title = {{Influence of Springtime Atlantic SST on ENSO: Role of the Madden-Julian
   Oscillation}},
Journal = {{JOURNAL OF METEOROLOGICAL RESEARCH}},
Year = {{2018}},
Volume = {{32}},
Number = {{3}},
Pages = {{380-393}},
Month = {{JUN}},
Abstract = {{Increased evidence has shown the important role of Atlantic sea surface
   temperature (SST) in modulating the El Nio-Southern Oscillation (ENSO).
   Persistent anomalies of summer Madden-Julian Oscillation (MJO) act to
   link the Atlantic SST anomalies (SSTAs) to ENSO. The Atlantic SSTAs are
   strongly correlated with the persistent anomalies of summer MJO, and
   possibly affect MJO in two major ways. One is that an anomalous cyclonic
   (anticyclonic) circulation appears over the tropical Atlantic Ocean
   associated with positive (negative) SSTA in spring, and it intensifies
   (weakens) the Walker circulation. Equatorial updraft anomaly then
   appears over the Indian Ocean and the eastern Pacific Ocean,
   intensifying MJO activity over these regions. The other involves a high
   pressure (low pressure) anomaly associated with the North Atlantic SSTA
   tripole pattern that is transmitted to the mid- and low-latitudes by a
   circumglobal teleconnection pattern, leading to strong (weak) convective
   activity of MJO over the Indian Ocean. The above results offer new
   viewpoints about the process from springtime Atlantic SSTA signals to
   summertime atmospheric oscillation, and then to the MJO of tropical
   atmosphere affecting wintertime Pacific ENSO events, which connects
   different oceans.}},
Publisher = {{SPRINGER HEIDELBERG}},
Address = {{TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ju, JH (Corresponding Author), Yunnan Prov Meteorol Bur, Kunming 650034, Yunnan, Peoples R China.
   Yan, Xin; Yang, Song, Sun Yat Sen Univ, Sch Atmospher Sci, Guangzhou 510275, Guangdong, Peoples R China.
   Yan, Xin; Yang, Song, Sun Yat Sen Univ, Guangdong Prov Key Lab Climate Change \& Nat Disas, Guangzhou 510275, Guangdong, Peoples R China.
   Ren, Juzhang, Yunnan Res Inst Meteorol, Kunming 650034, Yunnan, Peoples R China.
   Ju, Jianhua, Yunnan Prov Meteorol Bur, Kunming 650034, Yunnan, Peoples R China.}},
DOI = {{10.1007/s13351-018-7046-5}},
ISSN = {{2095-6037}},
EISSN = {{2198-0934}},
Keywords = {{Madden-Julian Oscillation (MJO); Atlantic; sea surface temperature
   anomaly (SSTA); Walker circulation; teleconnection; El Nino-Southern
   Oscillation (ENSO)}},
Keywords-Plus = {{SEA-SURFACE TEMPERATURE; NORTH TROPICAL ATLANTIC; EL-NINO; INTERANNUAL
   VARIABILITY; ATMOSPHERIC VARIABILITY; PACIFIC; MJO; OCEAN;
   TELECONNECTIONS; CIRCULATION}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{jujh@cma.gov.cn}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}41375059, 41690123, 41690120, 41661144019,
   41375081]; China Meteorological Administration (CMA) Special Public
   Welfare Research Fund {[}GYHY201306022]; State Key Laboratory for Severe
   Weather Special Fund {[}2016LASW-B01]; Research Fund of CMA Guangzhou
   Institute of Tropical and Marine Meteorology/Guangdong Provincial Key
   Laboratory of Regional Numerical Weather Prediction}},
Funding-Text = {{Supported by the National Natural Science Foundation of China (41375059,
   41690123, 41690120, 41661144019, and 41375081), China Meteorological
   Administration (CMA) Special Public Welfare Research Fund
   (GYHY201306022), State Key Laboratory for Severe Weather Special Fund
   (2016LASW-B01), and Research Fund of CMA Guangzhou Institute of Tropical
   and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional
   Numerical Weather Prediction.}},
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Number-of-Cited-References = {{74}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{11}},
Journal-ISO = {{J. Meteorol. Res.}},
Doc-Delivery-Number = {{GM5AN}},
Unique-ID = {{ISI:000438139000004}},
OA = {{Other Gold}},
DA = {{2020-08-06}},
}

@article{ ISI:000452824700014,
Author = {Liu, Wei and Xie, Shang-Ping},
Title = {{An Ocean View of the Global Surface Warming Hiatus}},
Journal = {{OCEANOGRAPHY}},
Year = {{2018}},
Volume = {{31}},
Number = {{2, SI}},
Pages = {{72-79}},
Month = {{JUN}},
Abstract = {{The rate of global mean surface temperature increase slowed during
   1998-2012. We review oceanic changes during this global warming hiatus
   from different but related perspectives. In one perspective, we explore
   the physical mechanisms for sea surface temperature patterns and
   highlight the role of natural variability, particularly the Interdecadal
   Pacific Oscillation (IPO) and the Atlantic Multidecadal Oscillation
   (AMO) that both have chaotic/random phases. In the other perspective, we
   investigate how the hiatus relates to changes in energy fluxes at the
   top of the atmosphere and to the three-dimensional distribution of ocean
   heat content change on decadal timescales. We find that the recent
   surface warming hiatus is associated with a transition of the IPO from a
   positive to negative phase and with heat redistribution between the
   tropical Pacific and Indian Oceans. The AMO has shifted to a positive
   phase since the late 1990s, inducing a La Nina-type response over the
   tropical Pacific via a tropic-wide teleconnection, contributing to the
   global warming hiatus.}},
Publisher = {{OCEANOGRAPHY SOC}},
Address = {{P.O. BOX 1931, ROCKVILLE, MD USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Liu, W (Corresponding Author), Univ Calif Riverside, Dept Earth Sci, Riverside, CA 92521 USA.
   Liu, Wei, Univ Calif Riverside, Dept Earth Sci, Riverside, CA 92521 USA.
   Xie, Shang-Ping, Univ Calif San Diego, Scripps Inst Oceanog, Roger Revelle Chair Environm Sci, La Jolla, CA 92093 USA.}},
DOI = {{10.5670/oceanog.2018.217}},
ISSN = {{1042-8275}},
Keywords-Plus = {{HEAT-CONTENT; NORTH-ATLANTIC; TEMPERATURE ANALYSIS; DECADAL MODULATION;
   TROPICAL PACIFIC; CLIMATE; VARIABILITY; CIRCULATION; SLOWDOWN; UPGRADES}},
Research-Areas = {{Oceanography}},
Web-of-Science-Categories  = {{Oceanography}},
Author-Email = {{wei.liu@ucr.edu}},
ResearcherID-Numbers = {{Xie, Shang-Ping/C-1254-2009}},
ORCID-Numbers = {{Xie, Shang-Ping/0000-0002-3676-1325}},
Funding-Acknowledgement = {{National Science FoundationNational Science Foundation (NSF)
   {[}OPP-1741841, AGS-1637450]; Department of Earth Sciences, University
   of California, Riverside}},
Funding-Text = {{WL is supported by the National Science Foundation (OPP-1741841) and
   startup funds from the Department of Earth Sciences, University of
   California, Riverside, and SPX by the National Science Foundation
   (AGS-1637450).}},
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Number-of-Cited-References = {{68}},
Times-Cited = {{6}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Oceanography}},
Doc-Delivery-Number = {{HD8QV}},
Unique-ID = {{ISI:000452824700014}},
OA = {{DOAJ Gold}},
DA = {{2020-08-06}},
}

@article{ ISI:000429753900037,
Author = {Shigetomi, Yosuke and Nansai, Keisuke and Kagawa, Shigemi and Tohno,
   Susumu},
Title = {{Fertility-rate recovery and double-income policies require solving the
   carbon gap under the Paris Agreement}},
Journal = {{RESOURCES CONSERVATION AND RECYCLING}},
Year = {{2018}},
Volume = {{133}},
Pages = {{385-394}},
Month = {{JUN}},
Abstract = {{In 2015, in response to the Paris Agreement for mitigating an increase
   in global temperatures, the Japanese government committed itself to
   reducing greenhouse gas (GHG) emissions by 26\% below 2013 levels by
   2030. In the same year, the government also committed itself to
   overcoming the barriers to economic growth imposed by an aging society
   with a low birthrate by implementing socio-economic policies referred to
   as ``A Society in Which All Citizens are Dynamically Engaged{''}.
   Regarding achievement of these two national targets, this study examines
   the extent to which increases in the total fertility rate and the number
   of double-income households would impact the domestic carbon footprint
   (CF) associated with household consumption in 2030. The findings show
   that the total household CF in 2030 would range from 683 to 815
   Mt-CO(2)eq/y, depending on the consumer preferences resulting from
   implementation of the socio-economic policies. This implies that,
   compared with a business-as-usual scenario, the GHG emissions associated
   with household consumption would need to be reduced by more 7.8-29\% in
   order to meet the CF target that can be set using the CF for 2009 and
   the reduction target proposed in the Paris Agreement. Furthermore, the
   household CF for non-energy commodities would need to be reduced by
   17-28\% in order to satisfy the trade-off between the socio-economic
   policies and the emissions mitigation target for 2030, even if the
   current CO2 emissions targets for household energy use and private car
   use are achieved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Shigetomi, Y (Corresponding Author), Nagasaki Univ, Grad Sch Fisheries \& Environm Sci, 1-14 Bunkyo Machi, Nagasaka, Yamanashi 8528521, Japan.
   Shigetomi, Yosuke, Nagasaki Univ, Grad Sch Fisheries \& Environm Sci, 1-14 Bunkyo Machi, Nagasaka, Yamanashi 8528521, Japan.
   Nansai, Keisuke, Natl Inst Environm Studies, Ctr Mat Cycles \& Waste Management Res, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan.
   Kagawa, Shigemi, Kyushu Univ, Fac Econ, Higashi Ku, 6-19-1 Hakozaki, Fukuoka 8128581, Japan.
   Tohno, Susumu, Kyoto Univ, Grad Sch Energy Sci, Sakyo Ku, Kyoto 6068501, Japan.}},
DOI = {{10.1016/j.resconrec.2017.11.017}},
ISSN = {{0921-3449}},
EISSN = {{1879-0658}},
Keywords = {{Carbon footprint; Double-income household; Environmentally extended
   input-output analysis; Paris agreement; Total fertility rate}},
Keywords-Plus = {{ENVIRONMENTAL IMPACTS; SUSTAINABLE CONSUMPTION; HOUSEHOLD CONSUMPTION;
   JAPANESE HOUSEHOLDS; FOOTPRINT; EMISSIONS; UNIVERSITY; ENERGY}},
Research-Areas = {{Engineering; Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Engineering, Environmental; Environmental Sciences}},
Author-Email = {{y-shigetomi@nagasaki-u.ac

path: /data/wos_io/savedrecs (3).bib

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filename: savedrecs (3).bib