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28 results for “Deep convection”

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zenodo32/100

A Deep Learning Approach to Afternoon Convection Prediction Using Heterogeneous Weather Data: Taking the Important Areas in Taiwan as an Example

<p>The following partial dataset&nbsp;is provided&nbsp;by the authors for&nbsp;the Afternoon Convection Prediction&nbsp; method presented in the paper.</p> <p>afternoon_rainfall_label is labeled as&nbsp;afternoon convection&nbsp;data</p> <p>weather_image is weather images</p>

opencc-by-4.0Dec 2022View details →
zenodo28/100

Buoyancy in Deep Convection Simulations

The dataset contains some of the data from numerical simulations investigating deep convection dynamics, the impact of in-cloud supersaturations on convective updraft strength in particular. It includes simple fortran codes to read the data and write some of them into a data files (standard write from fortran), the data files, and a README file that explains how the data was written and how to read it.

opencc-by-4.0Dec 2020View details →
nasa28/100

MODIS Terra L2 deep-convective cloud classification

MODIS Terra L2 deep-convective cloud classification (DC) are part of our global MODIS Terra data from the 2017 MEaSUREs project, A Comprehensive Data Record of Marine Low-level and Deep Convective Cloud Systems Using an Object-Oriented Approach.

restrictednotspecifiedApr 2025View details →
nasa28/100

MODIS Aqua L2 deep-convective cloud classification

MODIS Aqua L2 deep-convective cloud classification (DC) are part of our global MODIS Aqua data from the 2017 MEaSUREs project, A Comprehensive Data Record of Marine Low-level and Deep Convective Cloud Systems Using an Object-Oriented Approach.

restrictednotspecifiedApr 2025View details →
zenodo24/100

Air parcels extracted from LES simulations of a deep convective cloud observed during DC3 field campaign

<p>The dataset consists of 500 files describing air parcels retrieved from the simulation of the deep convective cloud event observed on May 29, 2012, during the DC3 field campaign. Values for coordinate (X, Y, Z), velocity components (U, V, W), potential temperature (PTIL), total water content (QT), water vapor (QV), condensate density (QC), precipitation density (QR), net precipitation change (QR_FLUX), relative humidity (RH), buoyancy (BUOY), temperature (T), pressure (P), resolved TKE (KRES), SGS TKE (SGS_TKE), turbulent diffusion (TDIFF) are provided for each parcel at every time step of the simulation.</p>

opencc-by-4.0Jan 2020View details →
zenodo24/100

Linking deep and shallow convection in CAM5_CLUBB

<p>Model outputs from CAM5_CLUBB that applies a revised ZM deep convection scheme, in which the mass flux of deep convection is linked to that of shallow convection determined by CLUBB.</p>

opencc-by-4.0Sep 2020View details →
zenodo20/100

On the deep carbon cycle in numerical modelling of mantle convection: Implications for the long-term climate evolution

Open the record for dataset details and reuse information.

openNov 2024View details →
zenodo8/100

The trajectories of deep convective cloud air parcels over Manaus, Brazil simulated by MIMICA LES / CRM

<p>The dataset contains trajectories of the deep convective clouds&nbsp;simulated with MIMICA code based on&nbsp;soundings retrieved on April 8, 2020, April 23, 2020, and April 27, 2020, over Manaus,&nbsp;Brazil.</p> <p><br> OUTPUT folder contains all 500 air parcel trajectories retrieved from MIMICA.<br> OUTPUT_MEAN folder contains all the bin averaged parcels</p> <p>Parcel data contains values for coordinate (X, Y, Z), velocity components (U, V, W), potential temperature (PTIL), total water content (QT), water vapor (QV), condensate density (QC), precipitation density (QR), net precipitation change (QR_FLUX), relative humidity (RH), buoyancy (BUOY), temperature (T), pressure (P), resolved TKE (KRES), SGS TKE (SGS_TKE), turbulent diffusion (TDIFF) are provided for each parcel at every time step of the simulation.</p>

restrictedJul 2021View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record