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Institution

CSIRO Marine and Atmospheric Research

FacilityCanberra, Australian Capital Territory, Australia
About: CSIRO Marine and Atmospheric Research is a facility organization based out in Canberra, Australian Capital Territory, Australia. It is known for research contribution in the topics: Climate change & Population. The organization has 891 authors who have published 2341 publications receiving 151004 citations. The organization is also known as: CMAR.


Papers
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Journal ArticleDOI
TL;DR: It is concluded that cox1 sequencing, or ‘barcoding’, can be used to identify fish species.
Abstract: GC than sharks (44.7% versus 41.0%), again largely due to higher GC in the 3rd codon position in the former (36.3% versus 26.8%). Average within-species, genus, family, order and class Kimura two parameter (K2P) distances were 0.39%, 9.93%, 15.46%, 22.18% and 23.27%, respectively. All species could be differentiated by their cox1 sequence, although single individuals of each of two species had haplotypes characteristic of a congener. Although DNA barcoding aims to develop species identification systems, some phylogenetic signal was apparent in the data. In the neighbourjoining tree for all 754 sequences, four major clusters were apparent: chimaerids, rays, sharks and teleosts. Species within genera invariably clustered, and generally so did genera within families. Three taxonomic groups—dogfishes of the genus Squalus, flatheads of the family Platycephalidae, and tunas of the genus Thunnus—were examined more closely. The clades revealed after bootstrapping generally corresponded well with expectations. Individuals from operational taxonomic units designated as Squalus species B through F formed individual clades, supporting morphological evidence for each of these being separate species. We conclude that cox1 sequencing, or ‘barcoding’, can be used to identify fish species.

3,212 citations

Journal ArticleDOI
TL;DR: Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) is a two-wavelength polarization lidar that performs global profiling of aerosols and clouds in the troposphere and lower stratosphere as discussed by the authors.
Abstract: The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) is a two-wavelength polarization lidar that performs global profiling of aerosols and clouds in the troposphere and lower stratosphere. CALIOP is the primary instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite, which has flown in formation with the NASA A-train constellation of satellites since May 2006. The global, multiyear dataset obtained from CALIOP provides a new view of the earth’s atmosphere and will lead to an improved understanding of the role of aerosols and clouds in the climate system. A suite of algorithms has been developed to identify aerosol and cloud layers and to retrieve a variety of optical and microphysical properties. CALIOP represents a significant advance over previous space lidars, and the algorithms that have been developed have many innovative aspects to take advantage of its capabilities. This paper provides a brief overview of the CALIPSO mission, the CA...

1,833 citations

Journal ArticleDOI
TL;DR: This article showed that a doubling in the occurrence of such extreme episodes is caused by increased surface warming of the eastern equatorial Pacific Ocean, which results in the atmospheric conditions required for these event to occur.
Abstract: Extreme El Nino events cause global disruption of weather patterns and affect ecosystems and agriculture through changes in rainfall. Model projections show that a doubling in the occurrence of such extreme episodes is caused by increased surface warming of the eastern equatorial Pacific Ocean, which results in the atmospheric conditions required for these event to occur.

1,672 citations

Book ChapterDOI
01 Jan 2012
TL;DR: In this article, the authors address changes in weather and climate events relevant to extreme impacts and disasters, such as hurricanes, floods, droughts, hurricanes, and floods, which can lead to extreme conditions or impacts.
Abstract: This chapter addresses changes in weather and climate events relevant to extreme impacts and disasters. An extreme (weather or climate) event is generally defined as the occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) ends (‘tails’) of the range of observed values of the variable. Some climate extremes (e.g., droughts, floods) may be the result of an accumulation of weather or climate events that are, individually, not extreme themselves (though their accumulation is extreme). As well, weather or climate events, even if not extreme in a statistical sense, can still lead to extreme conditions or impacts, either by crossing a critical threshold in a social, ecological, or physical system, or by occurring simultaneously with other events. A weather system such as a tropical cyclone can have an extreme impact, depending on where and when it approaches landfall, even if the specific cyclone is not extreme relative to other tropical cyclones. Conversely, not all extremes necessarily lead to serious impacts. [3.1] Many weather and climate extremes are the result of natural climate variability (including phenomena such as El Nino), and natural decadal or multi-decadal variations in the climate provide the backdrop for anthropogenic climate changes. Even if there were no anthropogenic changes in climate, a wide variety of natural weather and climate extremes would still occur. [3.1] A changing climate leads to changes in the frequency, intensity, spatial extent, duration, and timing of weather and climate extremes, and can result in unprecedented extremes. Changes in extremes can also be directly related to changes in mean climate, because mean future conditions in some variables are projected to lie within the tails of present-day conditions. Nevertheless, changes in extremes of a climate or weather variable are not always related in a simple way to changes in the mean of the same variable, and in some cases can be of opposite sign to a change in the mean of the variable. Changes in phenomena such as the El Nino-Southern Oscillation or monsoons could affect the frequency and intensity of extremes in several regions simultaneously.

1,501 citations

Journal ArticleDOI
TL;DR: In this paper, the authors estimate the rise in global average sea level from satellite altimeter data for 1993-2009 and from coastal and island sea-level measurements from 1880 to 2009.
Abstract: We estimate the rise in global average sea level from satellite altimeter data for 1993–2009 and from coastal and island sea-level measurements from 1880 to 2009. For 1993–2009 and after correcting for glacial isostatic adjustment, the estimated rate of rise is 3.2 ± 0.4 mm year−1 from the satellite data and 2.8 ± 0.8 mm year−1 from the in situ data. The global average sea-level rise from 1880 to 2009 is about 210 mm. The linear trend from 1900 to 2009 is 1.7 ± 0.2 mm year−1 and since 1961 is 1.9 ± 0.4 mm year−1. There is considerable variability in the rate of rise during the twentieth century but there has been a statistically significant acceleration since 1880 and 1900 of 0.009 ± 0.003 mm year−2 and 0.009 ± 0.004 mm year−2, respectively. Since the start of the altimeter record in 1993, global average sea level rose at a rate near the upper end of the sea level projections of the Intergovernmental Panel on Climate Change’s Third and Fourth Assessment Reports. However, the reconstruction indicates there was little net change in sea level from 1990 to 1993, most likely as a result of the volcanic eruption of Mount Pinatubo in 1991.

1,355 citations


Authors

Showing all 903 results

NameH-indexPapersCitations
David Smith1292184100917
Paul D. N. Hebert11153766288
Benjamin Smith10363146514
Josep G. Canadell9523154822
Aibing Yu8693034127
Peter D. Nichols8142023305
John K. Volkman7821221931
Christopher J. White7762125767
Hartmut Herrmann6928818651
Alistair J. Hobday6835118263
Anthony J. Richardson6825820639
John A. Church6819419430
Ying-Ping Wang6627617847
Mark A. Hindell6533714424
Wenju Cai6525916702
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202318
202228
20218
20207
201913
201817