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639 results for “eastern China”
Figures 9–11 in Cyana shirakawai, a new species from south-eastern Xizang, China (Lepidoptera: Erebidae: Arctiinae: Lithosiini)
Figures 9–11. Cyana spp.: male genitalia. Depositories of the specimens dissected: 9 in WIGJ; 10 and 11 in MWM/ZSM.
Linked collectors and determiners for: Ranunculus huainingensis and R. lujiangensis (Ranunculaceae), described from Anhui in China, are both synonymous with R. ternatus, a polymorphic eastern Asian species.
Natural history specimen data linked to collectors and determiners held within, "Ranunculus huainingensis and R. lujiangensis (Ranunculaceae), described from Anhui in China, are both synonymous with R. ternatus, a polymorphic eastern Asian species". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/9273b87e-eab4-4fcb-bce5-1201044cb994">https://bionomia.net/dataset/9273b87e-eab4-4fcb-bce5-1201044cb994</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/9273b87e-eab4-4fcb-bce5-1201044cb994">https://gbif.org/dataset/9273b87e-eab4-4fcb-bce5-1201044cb994</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Cabardites, a new genus for the " Adites " maculata (Poujade, 1886) species-group with descriptions of five new species from northern Indochina and eastern China (Lepidoptera: Erebidae: Arctiinae: Lithosiini).
Natural history specimen data linked to collectors and determiners held within, "Cabardites, a new genus for the " Adites " maculata (Poujade, 1886) species-group with descriptions of five new species from northern Indochina and eastern China (Lepidoptera: Erebidae: Arctiinae: Lithosiini)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/1d51f348-b3b2-46ff-a370-636249acbdc3">https://bionomia.net/dataset/1d51f348-b3b2-46ff-a370-636249acbdc3</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/1d51f348-b3b2-46ff-a370-636249acbdc3">https://gbif.org/dataset/1d51f348-b3b2-46ff-a370-636249acbdc3</a>. Formatted as a Frictionless Data package.
AOD and FMF dataset retrieved from NNAero in eastern and northern China from 2010 to 2020
<p>In this work, the development of an artificial Neural Network for AEROsol retrieval (NNAero) is presented. NNAero uses data from the NASA MODerate resolution Imaging Spectroradiometer (MODIS) flying on the NASA Terra and Aqua satellites. The MODIS-derived spectral reflectances of solar radiation at the top of the atmosphere (TOA) and at the surface were used together with ground-based Aerosol Robotic Network (AERONET) measurements of Aerosol Optical Depth (AOD) and FMF to train a Convolutional Neural Network (CNN) for the joint retrieval of FMF and AOD. The NNAero results over northern and eastern China were validated against an independent reference AERONET dataset (i.e. not used in training the CNN). The results show that 68% of the NNAero AOD values are within the MODIS expected error (EE) envelope over land of ± (0.05 + 15%), which is similar to the results from the MODIS Deep Blue (DB) algorithm (63% within EE), and both are better than the Dark Target (DT) algorithm (31% within EE). The validation of the NNAero FMF vs AERONET data shows a significant improvement with respect to the DT FMF, with Root Mean Squared Prediction Errors (RMSE) of 0.1567 (NNAero) and 0.34 (DT). The NNAero method shows the potential of improved retrieval of the FMF.</p> <p>If you use this dataset for related scientific research,please cite the below-listed corredponding references first(Chen X et al. ,RSE, 2020 )</p> <p>Chen, X., de Leeuw, G., Arola, A., Liu, S., Liu, Y., Li, Z., &amp; Zhang, K. (2020). Joint retrieval of the aerosol fine mode fraction and optical depth using MODIS spectral reflectance over northern and eastern China: Artificial neural network method. Remote Sensing of Environment, 249, 112006.<a href="https://doi.org/10.1016/j.rse.2020.112006">https://doi.org/10.1016/j.rse.2020.112006</a></p>
Simulation results from WRF-CMAQ with enabling aerosol-radiation interactions in eastern China for January-April 2017
<p>Simulation results from WRF-CMAQ with enabling aerosol-radiation interactions in eastern China for January-April 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for January-April 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_CCTM_ACONC.zip:</p><p>Air quality file including CCTM_ACONC_v3852_YYYYMMDD.nc on each day for January-April 2017, which contains these variables:</p><p>ASO4I, ANO3I, ANH4I, ANAI, ACLI, AECI, ALVPO1I, ASVPO1I, ASVPO2I, ALVOO1I, ALVOO2I, ASVOO1I, ASVOO2I, AOTHRI, ASO4J, ANO3J, ANH4J, ANAJ, ACLJ, AECJ, AOTHRJ, AFEJ, ASIJ, ATIJ, ACAJ, AMGJ, AMNJ, AALJ, AKJ, ALVPO1J, ASVPO1J, ASVPO2J, AXYL1J, AXYL2J, AXYL3J, ATOL1J, ATOL2J, AXYL2J, AXYL3J, ATOL1J, ABNZ3J, AISO1J, AISO2J, AISO3J, ATRP1J, ATRP2J, ASQTJ, AALK1J, AALK2J, APAH1J, APAH2J, APAH3J, AORGCJ, AOLGBJ, AOLGAJ, ALVOO1J, ALVOO2J, ASVOO1J, ASVOO2J, ASVOO3J, APCSOJ, ASOIL, ACORS, ACLK, ASO4K, ANO3K, ANH4K, O3, SO2, NO2, CO, and NH3.</p><p>YYYYMM_CCTM_APMDIAG.zip:</p><p>Air quality file including CCTM_APMDIAG_v3852_YYYYMMDD.nc on each day for January-April 2017, which contains these variables:</p><p>PM25AT, PM25AC and PM25CO.</p><p>YYYYMM_CCTM_PHOTDIAG1.zip:</p><p>Air quality file including CCTM_PHOTDIAG1_v3852_YYYYMMDD.nc on each day for January-April 2017, which contains these variables:</p><p>OZONE_COLUMN, NO2_COLUMN, CO_COLUMN, SO2_COLUMN, HCHO_COLUMN, TROPO_O3_COLUMN and AOD_W550_ANGST.</p>
Data of "High concentration of atmospheric sub-3 nm particles in polluted environment of eastern China: new particle formation and traffic emission"
<p>The attached data is the measurement data at SORPES station in Yangtze Rive Delta of China. The data is for analysis and figures in the study of "High concentration of atmospheric sub-3 nm particles in polluted environment of eastern China: new particle formation and traffic emission". Currently the manuscript is submitted to JGR-A.</p>
The daily gridded precipitation observations (0.5° × 0.5°) in central and eastern China (1961-2021)
<p>The daily observed gridded precipitation data were obtained from the China Meteorological Data Service Center (<a href="http://www.nmic.cn/en">http://www.nmic.cn/en</a>) on 04-08-2021 but are currently not available at this website. These data have 128 columns and 72 rows with longitude and latitude starting from 72°E and 18°N, respectively. Spatial resolution is 0.5°×0.5°.</p> <p>Here, we provide these data during 1961-2021 in two study regions: central China (111°-116°E, 32°-37°N) and eastern China (118°-123°E, 28°-34°N). To make it easier for everyone to reuse the data, we select these data with adding two degrees in each direction of two regions. The selected data have 19 columns and 19 rows (21 columns and 19 rows) in central (eastern) China with the grid center's longitude and latitude ranging from (109°-118°E, 30°-39°N) to (116°-125°E, 26°-36°N). </p>
Figure 3. – A in First record of Odontobutis haifengensis (Gobioidei, Odontobutidae) from the Rongjiang River, Eastern Guangdong, China
Figure 3. – A: Regularly arranged occipital scales of O. haifengensis; B: Cephalic lateral line system of O. haifengensis. Solid arrows = sensory canal; dotted arrows = sensory rows of papilla.
Figure 1. – A in First record of Odontobutis haifengensis (Gobioidei, Odontobutidae) from the Rongjiang River, Eastern Guangdong, China
Figure 1. – A: Geographic distribution of Odontobutis species in China, based on the literature. ▲ = O. haifengensis; C = O. potamophila; ● = O. sinensis; ■ = O. yaluensis. B: Geographical distribution of known captures of O. haifengensis. ▲ = records by Chen and Zheng (1985), Wu (1991) and Wu and Zhong (2009); Δ = new records from the present study. Numbers indicate different river drainages separated by mountains.
Figure 2 in First record of Odontobutis haifengensis (Gobioidei, Odontobutidae) from the Rongjiang River, Eastern Guangdong, China
Figure 2. – Two specimens of O. haifengensis captured in Rongjiang River. The first specimen was caught on 8 August 2016 (A), the second specimen was caught on 17 October 2016, 64.7 mm SL (B).
Middle Eocene terrestrial paleoweathering and climate evolution in the midlatitude Bohai Bay Basin of Eastern China
<p>The middle Eocene is a key time period for understanding Cenozoic cooling of the global climate. In eastern Asia, this time period was marked by deposition of extensive mudstones, shales and interbedded siltstones, especially in the midlatitude Bohai Bay Basin. Still, midlatitude terrestrial records of climate evolution during the middle Eocene are rare. Here, we analyze a continuous, high-resolution record of this period using samples of the shales in the fourth submember of the third member from the mid-Eocene Shahejie Formation (MES shales) in the Bohai Bay Basin using major-element and wavelet analysis. We use this information to derive insights into terrestrial paleoweathering and paleoclimatic evolution during the mid-Eocene in this midlatitude region. As a result of element mobility during continental weathering, the MES shales are more enriched in Ca and depleted in Na compared to average upper continental crust (UCC). The MES shales experienced moderate paleoweathering with limited K-metasomatism under a subtropical monsoon paleoclimate with mean annual temperature (MAT) of 8.3-12.9 °C and mean annual precipitation (MAP) of 685-1100 <span>mm</span>/<span>yr</span>. The MES shales record a mixed provenance involving intermediate igneous rocks, and low compositional maturity. The nutrient-rich environment led to enrichment in organic matter in the MES shales. We divide the depositional process of the MES shales into two stages that represent distinct climates. In stage I, the paleolake was high in nutrients, and the MES shales experienced high chemical weathering due to a relatively warmer and more humid climate. In contrast, the climate in stage II was relatively cold and dry, and the maturity of the MES shales was relatively high during this stage, suggesting a relatively stable tectonic background.</p>
Data for assessment of rainfall forecasts over eastern China with the GRIST
<p>This datasets provides the data and codes for JGR-A(2024JD042811).</p>
Figures 19–20 in Two new species of Eryciini (Diptera: Tachinidae) from the Eastern edge of the Qinghai-Tibetan Plateau, China
Figures 19–20. Lydella gannanensis sp. nov., male terminalia. 19. Lateral view. 20. Caudal view.
Figures 9–10 in Two new species of Eryciini (Diptera: Tachinidae) from the Eastern edge of the Qinghai-Tibetan Plateau, China
Figures 9–10. Drino latifrons sp. nov., male terminalia. 9. Lateral view. 10. Caudal view.
Object-based evaluation of precipitation systems in convection-permitting regional climate simulation over eastern China
<p>Data used in the manuscript "<strong>Object-based evaluation of precipitation systems in convection-permitting regional climate simulation over eastern China</strong>" which was submitted to Journal of Geophysical Research: Atmospheres. </p>
Fig. 1 in Waterbird Distribution Patterns And Environmentally Impacted Factors In Reclaimed Coastal Wetlands Of The Eastern End Of Nanhui County, Shanghai, China
Fig. 1. LocationofstudysitesinNanhuiCounty, Shanghai.
Fig. 1 in Antireicheia chinensis sp. nov. of the subtribe Reicheiina (Coleoptera: Carabidae: Scaritinae) from the south-eastern China
Fig. 1. Antireicheia chinensis sp. nov., habitus of male holotype (body length 2.15 mm).
Projection of hourly extreme precipitation over Eastern China
<p>Data used in the manuscript "<strong>Projection of hourly extreme precipitation over Eastern China</strong>" which will be submitted to Journal of Geophysical Research: Atmospheres.</p>
Air mass exposure to chlorophyll a (AEC) over the eastern China seas during 2009 to 2020
<p>This dataset contains (1) air mass exposure to chlorophyll <em>a</em> (AEC) values, (2) air mass retention ratio over the land (<em>R<sub>L</sub></em>), (3) marine air mss retention ratio within the boundary layer (<em>R<sub>MBL</sub></em>), and (4) harmonic means of boundary layer height along the air mass trajectory (BLH_traj) over the eastern China seas spanning from 2009 to 2020. The domain (23−37° N, 117−130° E) includes the south Yellow Sea (YS), the East China Sea (ECS), and part of Northwest Pacific, which is divided into 145 grids with a spatial resolution of 1° × 1°. The time period is 1 January 2009 − 31 December 2020, and the time resolution is 6 hours. The tracking time of initial trajectory is 72 hours.</p> <p>The Matlab scripts for calculating the abovementioned indices are also given. The main code includes "AEC_Cal_Multi.m", "AirmasstoChla.m", and "BLH_traj_multi.m".</p>
Aerosol measurements over the eastern China seas during 2017 to 2020
<p>This dataset contains the concentrations of trace elements and water-soluble ions in total suspended particles (TSP) over the eastern China seas on four cruises during (1) 27 March – 14 April 2017 (spring), (2) 27 June – 19 July 2018 (summer), (3) 28 December 2019 – 17 January 2020 (winter), and (4) 12 – 29 October 2020 (autumn). The air mass exposure to chlorophyll <em>a</em> (AEC), air mass retention ratio over the land (<em>R<sub>L</sub></em>), marine air mss retention ratio within the boundary layer (<em>R<sub>MBL</sub></em>), and harmonic means of boundary layer height along the air mass trajectory (BLH_traj) corresponding to each TSP sample are also presented. The calculation code for these indices is available at https://doi.org/10.5281/zenodo.7056981.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.