A multifunctional alternative lawn where warm-season grass and cold-season flowers coexist

The acquisition of real-time temperature and relative humidity (RH) profiles in the Arctic is of great significance for the study of the Arctic’s climate and Arctic scientific research. However, the operational algorithm of Fengyun-3D only takes into account areas within 60°N, the innovation of this work is that a new technique based on Neural Network (NN) algorithm was proposed, which can retrieve these parameters in real time from the Fengyun-3D Hyperspectral Infrared Radiation Atmospheric Sounding (HIRAS) observations in the Arctic region. Considering the difficulty of obtaining a large amount of actual observation (such as radiosonde) in the Arctic region, collocated ERA5 data from European Centre for Medium-Range Weather Forecasts (ECMWF) and HIRAS observations were used to train the neural networks (NNs). Brightness temperature and training targets were classified using two variables: season (warm season and cold season) and surface type (ocean and land). NNs-based retrievals were compared with ERA5 data and radiosonde observations (RAOBs) independent of the NN training sets. Results showed that (1) the NNs retrievals accuracy is generally higher on warm season and ocean; (2) the root-mean-square error (RMSE) of retrieved profiles is generally slightly higher in the RAOB comparisons than in the ERA5 comparisons, but the variation trend of errors with height is consistent; (3) the retrieved profiles by the NN method are closer to ERA5, comparing with the AIRS products. All the results demonstrated the potential value in time and space of NN algorithm in retrieving temperature and relative humidity profiles of the Arctic region from HIRAS observations under clear-sky conditions. As such, the proposed NN algorithm provides a valuable pathway for retrieving reliably temperature and RH profiles from HIRAS observations in the Arctic region, providing information of practical value in a wide spectrum of practical applications and research investigations alike.All in all, our work has important implications in broadening Fengyun-3D’s operational implementation range from within 60°N to the Arctic region.

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Late Dorset architecture on Little Cornwallis Island, Nunavut

Études/Inuit/Studies ◽

10.7202/010804ar ◽

2005 ◽

Vol 27 (1-2) ◽

pp. 255-280 ◽

Cited By ~ 7

Author(s):

Genevieve LeMoine ◽

James Helmer ◽

Bjarne Grønnow

Keyword(s):

Warm Season ◽

Cold Season ◽

Nuclear Families ◽

Construction Techniques ◽

Architectural Features ◽

Size Number ◽

Cornwallis Island

Abstract Late Dorset dwellings from two sites on Little Cornwallis Island (Nunavut) illustrate the diversity of architectural forms from this period. Ten architectural features are described. They include five tent rings, ascribed to warm season occupations, and five rectangular semi-subterranean houses with axial features, including one exceptionally well-preserved example, ascribed to cold season occupations. Variations in size, number of hearths, and construction techniques are examined and the use of both types of structures to house multiple nuclear families is suggested.

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Protozooplankton characterization of two contrasting sites in a tropical coastal ecosystem (Guanabara Bay, RJ)

Brazilian Journal of Oceanography ◽

10.1590/s1679-87592007000100004 ◽

2007 ◽

Vol 55 (1) ◽

pp. 29-38 ◽

Cited By ~ 8

Author(s):

Eli Ana Traversim Gomes ◽

Viviane Severiano dos Santos ◽

Denise Rivera Tenenbaum ◽

Maria Célia Villac

Keyword(s):

Water Quality ◽

Surface Water ◽

Food Web ◽

Warm Season ◽

Descriptive Study ◽

Cold Season ◽

Guanabara Bay ◽

Trophic Conditions ◽

Plankton Dynamics

Much time and resources have been invested in understanding plankton dynamics in Guanabara Bay (Brazil), but no attention has been devoted to the protozooplankton. To fulfill this lacuna, abundance and composition of protozooplankton were investigated from January to December - 2000 in fortnightly surface water samplings at two distinct water quality sites (Urca - closer to the bay entrance, more saline and cleaner waters; Ramos - inner reaches, hypereutrophic waters). The density at Urca (10³ - 10(5) cell.l-1) was one to three orders of magnitude lower than at Ramos (10(4) - 10(5) cell.l-1). A seasonal trend for nanoplankton and protozooplankton was more evident at Urca, but both sites had lower densities during the colder period. Small heterotrophic dinoflagellates (20-30 mm) were dominant in over 50% of the samples. The protozooplankton abundance and composition reflected the distinct trophic conditions states found at the bay. During the wet-warm season, non-oligotrich ciliates were representative of Ramos site with Gymnodiniaceae dinoflagellates, while tintinnids and heterotrophic dinoflagellates were predominantly found at Urca mainly during the dry-cold season. This first descriptive study towards the understanding of the intricate relationships among the microbial food web components reveals that protozooplankton can be a good indicator of water quality conditions at the bay.

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Diet composition and feeding habits of the eyespot skate, Atlantoraja cyclophora (Elasmobranchii: Arhynchobatidae), off Uruguay and northern Argentina

Neotropical Ichthyology ◽

10.1590/1982-0224-20160032 ◽

2016 ◽

Vol 14 (3) ◽

Cited By ~ 5

Author(s):

Santiago A. Barbini ◽

Luis O. Lucifora

Keyword(s):

Body Size ◽

Diet Composition ◽

Prey Size ◽

Prey Availability ◽

Feeding Habits ◽

Warm Season ◽

Cold Season ◽

The North ◽

Multiple Hypothesis ◽

Modelling Approach

ABSTRACT The eyespot skate, Atlantoraja cyclophora, is an endemic species from the southwestern Atlantic, occurring from Rio de Janeiro, Brazil, to northern Patagonia, Argentina. The feeding habits of this species, from off Uruguay and north Argentina, were evaluated using a multiple hypothesis modelling approach. In general, the diet was composed mainly of decapod crustaceans, followed by teleost fishes. Molluscs, mysidaceans, amphipods, isopods, lancelets and elasmobranchs were consumed in lower proportion. The consumption of shrimps drecreased with increasing body size of A. cyclophora. On the other hand, the consumption of teleosts increased with body size. Mature individuals preyed more heavily on crabs than immature individuals. Teleosts were consumed more in the south region (34º - 38ºS) and crabs in the north region (38º - 41ºS). Shrimps were eaten more in the warm season than in the cold season. Prey size increased with increasing body size of A. cyclophora , but large individuals also consumed small teleosts and crabs. Atlantoraja cyclophora has demersal-benthic feeding habits, shifts its diet with increasing body size and in response to seasonal and regional changes in prey availability and distribution.

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Annual cycles of organochlorine pesticide enantiomers in Arctic air suggest changing sources and pathways

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-1411-2015 ◽

2015 ◽

Vol 15 (3) ◽

pp. 1411-1420 ◽

Cited By ~ 15

Author(s):

T. F. Bidleman ◽

L. M. Jantunen ◽

H. Hung ◽

J. Ma ◽

G. A. Stern ◽

...

Keyword(s):

Warm Season ◽

Open Water ◽

Cold Season ◽

Secondary Emission ◽

Air Monitoring ◽

The Arctic ◽

Gas Chromatography Mass Spectrometry ◽

Annual Cycles ◽

Digital Filtration ◽

Peak Areas

Abstract. Air samples collected during 1994–2000 at the Canadian Arctic air monitoring station Alert (82°30' N, 62°20' W) were analysed by enantiospecific gas chromatography–mass spectrometry for α-hexachlorocyclohexane (α-HCH), trans-chlordane (TC) and cis-chlordane (CC). Results were expressed as enantiomer fractions (EF = peak areas of (+)/[(+) + (−)] enantiomers), where EFs = 0.5, < 0.5 and > 0.5 indicate racemic composition, and preferential depletion of (+) and (−) enantiomers, respectively. Long-term average EFs were close to racemic values for α -HCH (0.504 ± 0.004, n = 197) and CC (0.505 ± 0.004, n = 162), and deviated farther from racemic for TC (0.470 ± 0.013, n = 165). Digital filtration analysis revealed annual cycles of lower α-HCH EFs in summer–fall and higher EFs in winter–spring. These cycles suggest volatilization of partially degraded α-HCH with EF < 0.5 from open water and advection to Alert during the warm season, and background transport of α-HCH with EF > 0.5 during the cold season. The contribution of sea-volatilized α-HCH was only 11% at Alert, vs. 32% at Resolute Bay (74.68° N, 94.90° W) in 1999. EFs of TC also followed annual cycles of lower and higher values in the warm and cold seasons. These were in phase with low and high cycles of the TC/CC ratio (expressed as FTC = TC/(TC+CC)), which suggests greater contribution of microbially "weathered" TC in summer–fall versus winter–spring. CC was closer to racemic than TC and displayed seasonal cycles only in 1997–1998. EF profiles are likely to change with rising contribution of secondary emission sources, weathering of residues in the environment, and loss of ice cover in the Arctic. Enantiomer-specific analysis could provide added forensic capability to air monitoring programs.

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Investigation of post-depositional processing of nitrate in East Antarctic snow: isotopic constraints on photolytic loss, re-oxidation, and source inputs

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-9435-2015 ◽

2015 ◽

Vol 15 (16) ◽

pp. 9435-9453 ◽

Cited By ~ 21

Author(s):

G. Shi ◽

A. M. Buffen ◽

M. G. Hastings ◽

C. Li ◽

H. Ma ◽

...

Keyword(s):

Isotopic Composition ◽

Mass Fraction ◽

Stratospheric Ozone ◽

Warm Season ◽

Cold Season ◽

Depth Interval ◽

Depositional Processes ◽

Antarctic Snow ◽

Exponential Change ◽

The Impact

Abstract. Snowpits along a traverse from coastal East Antarctica to the summit of the ice sheet (Dome Argus) are used to investigate the post-depositional processing of nitrate (NO3−) in snow. Seven snowpits from sites with accumulation rates between 24 and 172 kg m−2 a−1 were sampled to depths of 150 to 300 cm. At sites from the continental interior (low accumulation, < 55 kg m−2 a−1), nitrate mass fraction is generally > 200 ng g−1 in surface snow and decreases quickly with depth to < 50 ng g−1. Considerably increasing values of δ15N of nitrate are also observed (16–461 ‰ vs. air N2), particularly in the top 20 cm, which is consistent with predicted fractionation constants for the photolysis of nitrate. The δ18O of nitrate (17–84 ‰ vs. VSMOW (Vienna Standard Mean Ocean Water)), on the other hand, decreases with increasing δ15N, suggestive of secondary formation of nitrate in situ (following photolysis) with a low δ18O source. Previous studies have suggested that δ15N and δ18O of nitrate at deeper snow depths should be predictable based upon an exponential change derived near the surface. At deeper depths sampled in this study, however, the relationship between nitrate mass fraction and δ18O changes, with increasing δ18O of nitrate observed between 100 and 200 cm. Predicting the impact of post-depositional loss, and therefore changes in the isotopes with depth, is highly sensitive to the depth interval over which an exponential change is assumed. In the snowpits collected closer to the coast (accumulation > 91 kg m−2 a−1), there are no obvious trends detected with depth and instead seasonality in nitrate mass fraction and isotopic composition is found. In comparison to the interior sites, the coastal pits are lower in δ15N (−15–71 ‰ vs. air N2) and higher in δ18O of nitrate (53–111 ‰ vs. VSMOW). The relationships found amongst mass fraction, δ15N, δ18O and Δ17O (Δ17O = δ17O–0.52 × δ18O) of nitrate cannot be explained by local post-depositional processes alone, and are instead interpreted in the context of a primary atmospheric signal. Consistent with other Antarctic observational and modeling studies, the isotopic results are suggestive of an important influence of stratospheric ozone chemistry on nitrate formation during the cold season and a mix of tropospheric sources and chemistry during the warm season. Overall, the findings in this study speak to the sensitivity of nitrate isotopic composition to post-depositional processing and highlight the strength of combined use of the nitrogen and oxygen isotopes for a mechanistic understanding of this processing.

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