{ "cells": [ { "cell_type": "markdown", "id": "a74c9d90", "metadata": { "papermill": { "duration": 0.009536, "end_time": "2024-07-01T13:29:50.727880", "exception": false, "start_time": "2024-07-01T13:29:50.718344", "status": "completed" }, "tags": [] }, "source": [ "# Metadata table" ] }, { "cell_type": "code", "execution_count": 1, "id": "23d0dba9", "metadata": { "execution": { "iopub.execute_input": "2024-07-01T13:29:50.743111Z", "iopub.status.busy": "2024-07-01T13:29:50.742346Z", "iopub.status.idle": "2024-07-01T13:29:50.758122Z", "shell.execute_reply": "2024-07-01T13:29:50.757084Z" }, "papermill": { "duration": 0.026714, "end_time": "2024-07-01T13:29:50.761677", "exception": false, "start_time": "2024-07-01T13:29:50.734963", "status": "completed" }, "tags": [ "remove-input" ] }, "outputs": [], "source": [ "# NO CODE\n", "from json2html import json2html\n", "import json, re\n", "from IPython.display import HTML" ] }, { "cell_type": "code", "execution_count": 2, "id": "3edfadad", "metadata": { "execution": { "iopub.execute_input": "2024-07-01T13:29:50.776878Z", "iopub.status.busy": "2024-07-01T13:29:50.776375Z", "iopub.status.idle": "2024-07-01T13:29:50.783114Z", "shell.execute_reply": "2024-07-01T13:29:50.781726Z" }, "papermill": { "duration": 0.016371, "end_time": "2024-07-01T13:29:50.785600", "exception": false, "start_time": "2024-07-01T13:29:50.769229", "status": "completed" }, "tags": [ "parameters", "remove-input" ] }, "outputs": [], "source": [ "# NO CODE\n", "# PARAMETERS\n", "path = './meta/environment/meteocat_xema'" ] }, { "cell_type": "code", "execution_count": 3, "id": "5ae975a0", "metadata": { "execution": { "iopub.execute_input": "2024-07-01T13:29:50.800621Z", "iopub.status.busy": "2024-07-01T13:29:50.800020Z", "iopub.status.idle": "2024-07-01T13:29:50.806882Z", "shell.execute_reply": "2024-07-01T13:29:50.805973Z" }, "papermill": { "duration": 0.016324, "end_time": "2024-07-01T13:29:50.808747", "exception": false, "start_time": "2024-07-01T13:29:50.792423", "status": "completed" }, "tags": [ "injected-parameters" ] }, "outputs": [], "source": [ "# Parameters\n", "path = \"./meta/environment/ncep\"\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "ff44bc1e", "metadata": { "execution": { "iopub.execute_input": "2024-07-01T13:29:50.829456Z", "iopub.status.busy": "2024-07-01T13:29:50.828778Z", "iopub.status.idle": "2024-07-01T13:29:50.850034Z", "shell.execute_reply": "2024-07-01T13:29:50.848189Z" }, "papermill": { "duration": 0.034078, "end_time": "2024-07-01T13:29:50.853620", "exception": false, "start_time": "2024-07-01T13:29:50.819542", "status": "completed" }, "tags": [ "remove-input", "full-width" ] }, "outputs": [ { "data": { "text/html": [ "
$schema../schema.json
@context
@vocabhttps://schema.org/
qudthttp://qudt.org/schema/qudt/
xsdhttp://www.w3.org/2001/XMLSchema#
@typeDataset
namencep
conditionsOfAccessPrivate
descriptionNCEP-GFS hourly worldwide weather 5-days forecast on 0.25 degree grid, updated every 6 hours. Temporal resolution is of 1 hour out to 120 hours, then 3 hours for days 5-16, has 57 vertical standard pressure levels, and is cycled 4x/day. This dataset is not intended for general public access since the original row dataset is freely distributed by NOAA-NCEP.
licensehttps://www.weather.gov/disclaimer
citation
  • National Centers For Environmental Prediction/National Weather Service/NOAA/U.S. Department Of Commerce, “NCEP GFS 0.25 Degree Global Forecast Grids Historical Archive.” UCAR/NCAR - Research Data Archive, 2015, doi: 10.5065/D65D8PWK.
temporalCoverage0 to 5 day forecast
spatialCoverage
@typePlace
nameWorldwide
sameAshttps://www.wikidata.org/wiki/Q13780930
distribution
  • @typeDataDownload
    namecluster_ceab
    descriptionDistribution by CSIC-CEAB cluster
    encodingFormatnetCDF
    workExample./notebooks/ncep.py
    contentUrl
    • sftp://{USER}@cluster-ceab:/leov1/ncep/daily_chunks/{YEAR-MONTH-DAY}/masked_{VARIABLE_NAME}_t_{YEAR-MONTH-DAY}.nc
    contentSize10MB
variableMeasured
  • @typePropertyValue
    name2m_temperature
    description2 m above ground air temperature
    unitTextDegree Kelvin
    qudt:dataTypexsd:int
  • @typePropertyValue
    name2m_dewpoint_temperature
    description2 m above ground dew point temperature
    unitTextDegree Kelvin
    qudt:dataTypexsd:int
  • @typePropertyValue
    name10m_u_component_of_wind
    description10 m above ground wind velocity component u
    unitTextm s^-1
    qudt:dataTypexsd:int
  • @typePropertyValue
    name10m_v_component_of_wind
    description10m above ground wind velocity component v
    unitTextm s^-1
    qudt:dataTypexsd:int
  • @typePropertyValue
    nametotal_precipitation
    descriptionAccumulated total precipitation during 1 hour
    unitTextmm h^-1
    qudt:dataTypexsd:int
measurementTechnique
  • Global Forecast System (GFS) is a global numerical weather prediction system containing a global computer model and variational analysis run by the U.S. National Weather Service (NWS)
creator
  • @typeOrganization
    @idNWS
    nameNational Weather Service (NWS)
    contactPoint
    @typeContactPoint
    emailsdm@noaa.gov
    urlhttps://www.weather.gov/about/
  • @typePerson
    @idZJ
    nameJužnič Zonta, Živko
    identifierhttps://orcid.org/0000-0002-2362-9771
    contactPoint
    @typeContactPoint
    roleNamedata engineer
    emailjzivko@gmail.com
    urlhttps://es.linkedin.com/in/zivko
" ], "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# NO CODE\n", "# FULL WIDTH\n", "with open(f'{path}.json') as f:\n", " data = json.load(f)\n", "\n", "table = json2html.convert(json=data, clubbing=False)\n", "table_sub = re.sub('', '', table)\n", "\n", "HTML(table_sub)\n", "\n", "# Run the following in the command line to build a html table\n", "# $ jupyter nbconvert --to html --no-input --no-prompt build_tables.ipynb\n" ] }, { "cell_type": "code", "execution_count": null, "id": "c418c7b5", "metadata": { "papermill": { "duration": 0.007125, "end_time": "2024-07-01T13:29:50.871034", "exception": false, "start_time": "2024-07-01T13:29:50.863909", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "interpreter": { "hash": "524d3359b179f3b444361f48db8ae048bd8c237924fac1cd48a4c6f8144f6452" }, "kernelspec": { "display_name": "Python 3.7.10 64-bit ('scidb': conda)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.4" }, "metadata": { "interpreter": { "hash": "e3961729dbf4ff77740ff872c9a3eef08621b5b434e3d8d81026af4505918c74" } }, "papermill": { "default_parameters": {}, "duration": 1.61659, "end_time": "2024-07-01T13:29:51.203057", "environment_variables": {}, "exception": null, "input_path": "build_info.ipynb", "output_path": "./meta_ipynb/ncep.ipynb", "parameters": { "path": "./meta/environment/ncep" }, "start_time": "2024-07-01T13:29:49.586467", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }