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16 results for “niñas”
MOM6-COBALT2 model results for asymmetrical Ocean Carbon Responses to La Niña and El Niño in the Tropical Pacific Ocean
<p>1. MOM6 COBALT2 model results</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_fco2_decomposition_1990_2021.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_fco2_decomposition_1990_2021.nc</a></p> <p>(air-sea carbon flux decomposition)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_dic_stf_gas_1980_2023_detrend_deseason_matlab_tp.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_dic_stf_gas_1980_2023_detrend_deseason_matlab_tp.nc</a></p> <p> (detrended and deseasonalized air-sea CO2 flux, positive to ocean)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_sfc_chl_1980_2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_sfc_chl_1980_2023.nc</a></p> <p> (sea surface chlorophyll)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_SSH_1990_2021_detrend_deseason_matlab.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_SSH_1990_2021_detrend_deseason_matlab.nc</a></p> <p> (detrended and deseasonalized sea surface height)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_sfc_no3_1980_2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_sfc_no3_1980_2023.nc</a></p> <p>(sea surface nitrate, NO3)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_SST_1980-2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_SST_1980-2023.nc</a></p> <p> (sea surface temperature)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_sfc_po4_1980_2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_sfc_po4_1980_2023.nc</a></p> <p> (sea surface phosphate, PO4)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_SSS_1980-2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_SSS_1980-2023.nc</a></p> <p> (sea surface salinity)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_SSS_1990-2023_detrend_deseason_matlab.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_SSS_1990-2023_detrend_deseason_matlab.nc</a></p> <p>(detrended and deseasonalized sea surface salinity)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_SST_1990-2023_detrend_deseason_matlab.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_SST_1990-2023_detrend_deseason_matlab.nc</a></p> <p>(detrended and deseasonalized sea surface temperature)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_u_1990-2021_detrend_deseason_matlab.nc.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_u_1990-2021_detrend_deseason_matlab.nc.nc</a></p> <p>(detrended and deseasonalized sea surface zonal velocity)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_MLD_003_1980-2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_MLD_003_1980-2023.nc</a></p> <p>(Mixing layer depth with a density criterial of 0.03 kg/m3)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_v_1990-2021_detrend_deseason_matlab.nc.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_v_1990-2021_detrend_deseason_matlab.nc.nc</a></p> <p>(detrended and deseasonalized sea surface meridional velocity)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_pco2surf_1980_2023_detrend_deseason_matlab_tp.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_pco2surf_1980_2023_detrend_deseason_matlab_tp.nc</a></p> <p> (detrended and deseasonalized ocean pCO2 in the ocean surface)</p> <p><a href="../api/records/13325632/draft/files/hist_gcb_simA_ocean_static.nc/content" target="_blank" rel="noopener noreferrer">hist_gcb_simA_ocean_static.nc</a></p> <p>(grid of model)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_budget_mld001_pco2surf_1990_2021_detrend_deseason_matlab.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_budget_mld001_pco2surf_1990_2021_detrend_deseason_matlab.nc</a></p> <p> (budget terms used for ocean pCO2 budget analysis, vertical mean in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)<br>pco2_hadv_hdif: horizontal transport term, H_circ;<br>dpco2_vadv_vdif: vertical transport term,V_circ;<br>dpco2_bio: biological term<br>dpco2_rain: surface freshwater term<br>dpco2_sst: thermal term<br>dpco2_dt: pco2 response term<br>dpco2_flux: CO2 flux response term</p> <p>2. dataset</p> <p><a href="../api/records/13325632/draft/files/co2_products_Rodenbeck_v2022_monthly_all_detrend_deseason_by_filter.nc/content" target="_blank" rel="noopener noreferrer">co2_products_Rodenbeck_v2022_monthly_all_detrend_deseason_by_filter.nc</a></p> <p>(CO2 based MLS: detrended and deseasonalized ocean pCO2 and air-sea carbon flux in the ocean surface)</p> <p><a href="../api/records/13325632/draft/files/co2_products_Rodenbeck_v2022_monthly_area.nc/content" target="_blank" rel="noopener noreferrer">co2_products_Rodenbeck_v2022_monthly_area.nc</a></p> <div>(the grid of MLS)</div> <p><a href="../api/records/13325632/draft/files/co2_products_Landschutzer_v2022_MPI_SOM_FFN_2022_NCEI_OCADS_detrend_deseason_matlab.nc/content" target="_blank" rel="noopener noreferrer">co2_products_Landschutzer_v2022_MPI_SOM_FFN_2022_NCEI_OCADS_detrend_deseason_matlab.nc</a></p> <p>(CO2 based SOM-FFN: detrended and deseasonalized ocean pCO2 and air-sea carbon flux in the ocean surface)</p> <p><a href="../api/records/13325632/draft/files/co2_products_Landschutzer_v2022_MPI_SOM_FFN_2022_NCEI_OCADS_area.nc/content" target="_blank" rel="noopener noreferrer">co2_products_Landschutzer_v2022_MPI_SOM_FFN_2022_NCEI_OCADS_area.nc</a></p> <p>(the grid of SOM-FFN)</p> <p><a href="../api/records/13325632/draft/files/precipitation_JRA55-do-v1.5merge_res_all_monthly_prra.JRA.1.5.monthly_detrend_deseason.nc/content" target="_blank" rel="noopener noreferrer">precipitation_JRA55-do-v1.5merge_res_all_monthly_prra.JRA.1.5.monthly_detrend_deseason.nc</a></p> <p>(JRA: detrended and deseasonalized precipitation)</p> <p><a href="../api/records/13325632/draft/files/phosphate_all_woa18_all_p_monthly.nc/content" target="_blank" rel="noopener noreferrer">phosphate_all_woa18_all_p_monthly.nc</a></p> <p>(WOA: sea surface phosphate, PO4)</p> <p><a href="../api/records/13325632/draft/files/ssh_AVISO_all_sla_tp_twosat_phy_l4_vDT2018_monthly_1994_2020_03_01_detrend_deseason.nc/content" target="_blank" rel="noopener noreferrer">ssh_AVISO_all_sla_tp_twosat_phy_l4_vDT2018_monthly_1994_2020_03_01_detrend_deseason.nc</a></p> <p>(AVISO: detrended and deseasonalized sea surface height)</p> <p><a href="../api/records/13325632/draft/files/sss_satellite_all_oisss_v1_sss_201109-202203_monthly.nc/content" target="_blank" rel="noopener noreferrer">sss_satellite_all_oisss_v1_sss_201109-202203_monthly.nc</a></p> <p>(OISSS: sea surface salinity)</p> <p><a href="../api/records/13325632/draft/files/sss_satellite_all_oisss_v1_sss_201109-202203_monthly_detrend_deseason.nc/content" target="_blank" rel="noopener noreferrer">sss_satellite_all_oisss_v1_sss_201109-202203_monthly_detrend_deseason.nc</a></p> <div>(OISSS: detrended and deseasonalized sea surface salinity)</div> <p><a href="../api/records/13325632/draft/files/co2_SOCAT_SOCATv2022_tracks_gridded_monthly.nc/content" target="_blank" rel="noopener noreferrer">co2_SOCAT_SOCATv2022_tracks_gridded_monthly.nc</a></p> <p>(SOCAT: ocean pCO2)</p> <p><a href="../api/records/13325632/draft/files/mld_obs_mld_DR003_c1m_reg2.0_rewrite_nanvalue.nc/content" target="_blank" rel="noopener noreferrer">mld_obs_mld_DR003_c1m_reg2.0_rewrite_nanvalue.nc</a></p> <p>(Mixing layer depth with a density criterial of 0.03 kg/m3)</p> <p><a href="../api/records/13325632/draft/files/nitrate_all_woa18_all_n_monthly.nc/content" target="_blank" rel="noopener noreferrer">nitrate_all_woa18_all_n_monthly.nc</a></p> <p>(WOA: sea surface nitrate, NO3)</p> <p><a href="../api/records/13325632/draft/files/sst_OISST_allsst.avhrr-only-v2.1_1990_2021_monthly.nc/content" target="_blank" rel="noopener noreferrer">sst_OISST_allsst.avhrr-only-v2.1_1990_2021_monthly.nc</a></p> <p> (OISST: sea surface temperature)</p> <p><a href="../api/records/13325632/draft/files/sst_OISST_allsst.avhrr-only-v2.1_1990_2021_monthly_detrend_deseason.nc/content" target="_blank" rel="noopener noreferrer">sst_OISST_allsst.avhrr-only-v2.1_1990_2021_monthly_detrend_deseason.nc</a></p> <p>(OISST: detrended and deseasonalized sea surface temperature)</p> <p><a href="../api/records/13325632/draft/files/chl_OC_CCI_all_OC_CCI_momthly_chlor_a_4km_fv5.0_199709_202112_clim.nc/content" target="_blank" rel="noopener noreferrer">chl_OC_CCI_all_OC_CCI_momthly_chlor_a_4km_fv5.0_199709_202112_clim.nc</a></p> <p>(GlobColour: sea surface chlorophyll)</p> <p><a href="../api/records/13325632/draft/files/uwind_JRA55-do-v1.5merge_res_all_monthly_uas.JRA.1.5.monthly_detrend_deseason.nc/content" target="_blank" rel="noopener noreferrer">uwind_JRA55-do-v1.5merge_res_all_monthly_uas.JRA.1.5.monthly_detrend_deseason.nc</a></p> <p>(JAR: detrended and deseasonalized zonal wind velocity)</p> <p><a href="../api/records/13325632/draft/files/TAO_CO2_tao_pco2_13stations_monthly_deseason_1997_2017.nc/content" target="_blank" rel="noopener noreferrer">TAO_CO2_tao_pco2_13stations_monthly_deseason_1997_2017.nc</a></p> <p>(TAO: sea surface temperature, sea surface salinity, and ocean pco2)</p> <p>3. Figure</p> <p>Figure1-4, FigureS1-S11 are data analysis files used python</p> <p> </p>
Homo neanderthalensis (niña de Teshik-Tash)
**Especie:** *Homo neanderthalensis* Cambell, 1963 **Nombre común**: niña de Teshik-Tash **Edad biológica:** niña de 7´5 años **Capacidad craneal:** 1550 cc. **Edad fósil:** 0,07 M.a (Pleistoceno Superior) **Localidad hallazgo:** cueva Teshik-Tash, cordillera Bajsuntau (Uzbekistan) **Clasificación:** família Hominidae, género Homo **Material:** réplica en resina, **Técnica:** ** fotogrametría, **Procesado:** Photoscan, **Cámara:** Sony DSC HX60V **Autor:** Andreu Vilaplana **nº registro / Colección:** MGUV 36476 / "Evolución Humana" del Museo de la Universitat de València de Historia Natural **Referencia bibliográfica:** Climent, A. V., Herraiz, J. L., Villena, J. A., Máñez, T. S., Boisset-Castells, E., Conejero, N., García-Forner, A. & Pérez, C. M. (2019). La holografía como herramienta para la divulgación del patrimonio paleontológico: La colección de paleontología humana del museu de la universitat de valència de historia natural. Zubía, (31), 275-280. Source: Objaverse 1.0 / Sketchfab
Comparación de la conciencia fonológica en niños y niñas de 5 años de la IE 84 del Callao
<p>La matriz de datos contiene las siguientes variables: Grupo, Sexo, Pre_segmentación silábica, Pre_supresión silábica, Pre_detección de rimas, Pre_adiciones silábicas, Pre_aislar fonemas, Pre_unión de fonemas, Pre_contar fonemas, Total, Estadios, Silábica, Intrasilábica, Fonemas, Post_segmentación silábica, Post_supresión silábica, Post_detección de rimas, Post_adiciones silábicas, Post_aislar fonemas, Post_unión de fonemas, Post_contar fonemas, Total_post, Silábicas, Intrasilábicas, Fonemass.</p>
niñas sin miedo
Niñas sin Miedo es una Fundación Legalmente constituida desde el 2016, que tiene como misión prevenir violencia sexual en niñas y adolescentes. YO APOYO A LAS NIÑAS. Source: Objaverse 1.0 / Sketchfab
CESM experiments for intraseasonal oscillation intensity changes in El Niño and La Niña developing summers
<p> Experiments are conducted using version 5.2 of Community Atmospheric Model (CAM-5.2; https://www.cesm.ucar.edu/models/cesm1.1/cam/). CAM is the atmosphere component of Community Earth System Model (CESM) developed by the National Center for Atmospheric Research (NCAR). The model resolution used in this study is f19_g16, with f19 finite volume grid (1.9º latitude by 2.5º longitude) for the atmosphere and land components combined with the gx1v6 displaced pole grid (approximately 1º) for the ocean and ice components.</p> <p> Four sets of numerical experiments are performed in this study:</p> <ol> <li>Full SST forcing simulation (full-SST run): The CAM is forced by global monthly OI SST and integrated from January 1982 to December 2020.</li> <li>Climatological SST forcing simulation (CLM-SST run): The CAM is integrated for 30 years forced by global climatological mean monthly SST obtained from OI SST data for the period of January 1982 to December 2020.</li> <li>Tropical central-eastern Pacific SST forcing simulation (CEP-SST run): The SST forcing field is composed of two parts: total monthly SST in the domain of 15°S-15°N and 160°E-80°W and climatological mean monthly SST in the other regions. The CAM is integrated from January 1982 to December 2020.</li> <li>Sensitivity experiments of tropical central-eastern Pacific SST anomalies during ENSO events: Composite SST anomalies in El Niño and La Niña events in the region of 15°S-15°N and 160°E-80°W and the above SST anomaly fields multiplied by -1 are added to climatological mean monthly SST from May to December. Climatological mean monthly SST is used in the other regions and months. The CAM is integrated for 30 years in these experiments. These experiments are referred to as EPEL, EPLA, EPEL-reverse and EPLA-reverse, respectively.</li> </ol>
Numerical experiments for La Niña, north Atlantic, and the LA_NA
<p>The data named "FCAM_cntrl*" are the outputs of the control run.</p> <p>The data named "FCAM_nina_2022*" are the outputs of for the La Niña run.</p> <p>The data named "FCAM_NA_2022_Feb*" are the outputs of for the north Atlantic run.</p> <p>The data named "FCAM_nina_NA*" are the outputs of for the LA_NA run.</p> <p> </p> <p> </p>
Habilidades sociales en niños y niñas de cinco años de instituciones educativas de la red N° 4 del distrito Callao
<p>La matriz de datos contiene 75 variables y 109 casos.</p>
Habilidades sociales en niños y niñas de cinco años de instituciones educativas de la red N° 4 del distrito Callao
<p>La matriz de datos contiene 75 variables y 109 casos.</p>
Tropical and Subtropical Pacific Sources of the Asymmetric El Niño La Niña Decay and their Future Changes
<p>The model data output supporting the figures shown in the manuscript.</p> <p>For further details, please see</p> <p>Jiepeng Chen, Jin-Yi Yu, Sheng Chen, Xin Wang, Ziniu Xiao, Shih-Wei Fang (2022). Tropical and Subtropical Pacific Sources of the Asymmetric El Niño La Niña Decay and their Future Changes. Accepted at Geophysical Research Letters.</p>
Record low Arctic sea ice extent in 2012 linked to two-year La Niña-driven sea surface temperature pattern
<p class="Abstract"><span>Arctic summer sea ice decline accelerated from the mid-2000s to 2012, with the 2012 record low remaining unbroken. While frequent La Niña events during this period have been suggested as a driver of this trend acceleration, no convincing evidence has been presented. Here, using a climate model nudged to observed pan-tropical sea surface temperatures (SST), we show that the back-to-back La Niña events during 2010–2011, followed by a North Pacific cooling and a marginal El Niño, were a key contribution to the 2012 record low. Specifically, the La Niña events in 2010–2011 warmed the Arctic Pacific sector, whereas tropical SST anomalies in 2012 strengthened the Greenland high pressure, leading to an Arctic dipole-like pressure pattern and strengthening of transpolar ice drift. These Arctic temperature and circulation anomalies led to the record low sea ice extent in 2012, highlighting the strong influence of tropical SSTs on Arctic climate.</span></p>
The Enhanced Teleconnection of Maritime Continent Deforestation on North Pacific Climate During La Niña Conditions
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Triple-dip La Niña contributes to Pakistan flooding and southern China drought in summer 2022
<p><span>In the summer of 2022, a long-lasting La Niña entered its third year. In Asia, southern China was in the grip of a historic drought while heavy rainfall ravaged Pakistan. Using a climate model forced by observed sea surface temperatures (SST) over the equatorial Pacific, we show that the back-to-back La Niña events from 2020 to 2022 are a key contributor to the global SST pattern in 2022 including the negative phase of Pacific decadal oscillation and exceptionally strong negative Indian Ocean dipole. The model reproduces the observed precipitation pattern over South and East Asia, including enhanced rainfall over Pakistan–northwest India and reduced rainfall over southern China. Additional model simulations indicate that the negative Indian Ocean dipole combined with La Niña can decrease southern China rainfall by causing anomalous subsidence and anticyclonic flows. </span><span>These results highlight the dominant role of long-lasting La Niña in modulating rainfall over heavily populated monsoon Asia.</span></p>
Data from: impacts of El Niño and La Niña on interannual snow accumulation in the Andes: results from a high-resolution 31 year reanalysis
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Record low Arctic sea ice extent in 2012 linked to two-year La Niña-driven sea surface temperature pattern
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Triple-dip La Niña contributes to Pakistan flooding and southern China drought in summer 2022
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Rendering Scripts and Source Data for Figures in "Why East Asian Monsoon Anomalies Are More Robust in Post El Niño than in Post La Niña Summers"
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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.