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#netcdf

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EOMasters

𝗖𝗙 𝗠𝗲𝘁𝗮𝗱𝗮𝘁𝗮 𝗖𝗼𝗻𝘃𝗲𝗻𝘁𝗶𝗼𝗻𝘀 support #OpenScience by automating processes via metadata in #NetCDF and #Zarr files. They establish a unified language for the #weather, #climate, #ocean, and #EO community. buff.ly/rGPuoku
#remotesensing #EarthObs

ZenodoSupporting Open Science with the CF Metadata Conventions for NetCDFSlides for the presentation given on 11 December 2024 at the AGU Annual Meeting to the session for the AGU Open Science Recognition Prize. Abstact:The CF (Climate and Forecast) Conventions are a community-developed standard that promotes the sharing and automated processing of Earth systems science data in the netCDF data format (and in Zarr/GeoZarr). The CF conventions define metadata that can be used to describe the coordinate systems, data structure, and geophysical meaning and units of each variable. This enables users of data from different sources to decide which quantities are comparable and facilitates building applications with powerful extraction, analysis, and display capabilities. There is a mature and growing ecosystem of FOSS (Free and Open Source Software) and commercial software tools which work with CF. The CF standard has been essential to the success of high-profile internationally-coordinated modeling activities (e.g, the Coupled Model Intercomparison Project, which hosts more than 30 million files and more than 15 petabytes of data, all compliant with CF). CF is widely used by weather, climate, ocean and Earth observation scientists, and is gaining traction among others, such as the biogeochemistry and atmospheric chemistry communities.
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💧🌏 Greg Cocks

Using Mesh Data In QGIS [including accessing NetCDF data]
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courses.gisopencourseware.org/ <-- shared tutorial
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youtu.be/OBi4wuxLiAE?si=_5DCAc <-- tutorial as a video
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“Mesh data represents an unstructured grid that can include temporal and other components. It consists of vertices, edges, and faces that form a spatial structure in 2D or 3D space. Each vertex can store multiple datasets, which can also have a temporal dimension, making mesh data highly versatile for various applications such as meteorology, hydrodynamics, and environmental modeling…
This course is designed to equip you with the knowledge and skills needed to effectively work with mesh data within the QGIS environment…"
#QGIS #GIS #mesh #datavisualisation #NetCDF #climate #animation #openaccess #onlinelearning #learning #spatial #mapping #tutorial

maps and charts - tutorial output - precipitation and temperature at IHE Delft on Feb 21st 2022
screen shoot - QGIS - making the plot from the mesh data
Public
💧🌏 Greg Cocks

A Gentle Introduction to GDAL Part 8 - Reading Scientific Data Formats
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medium.com/@robsimmon/a-gentle <-- shared technical article / tutorial
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“Among its many well-known capabilities, GDAL has a hidden superpower — the ability to read scientific data formats like Hierarchical Data Format (HDF), Network Common Data Form (NetCDF), and Gridded Binary (GRIB). Many essential climate and satellite datasets created by the likes of NASA, NOAA, the World Meteorological Organization (WMO), and the European Space Agency (ESA) are stored and distributed in one of these formats. They contain records of everything from global temperatures to land cover to ocean salinity. Unfortunately, many people who’d be interested in using these data don’t even know they exist…”
#GIS #spatial #mapping #remotesensing #earth #global #gdal #opensource #opendata #tutorial #learning #onlinelearning #introduction #scientificdata #HDF #NetCDF #GRIB #NASA #NOAA #WMO #ESA

graphic - GDAL logo
maps made via GDAL - Maps of monthly long-term climatology net flux data from CERES. In general, the Earth accumulates heat energy near the equator (red), and loses heat near the poles (blue). The latitudes receiving the most energy shift as the sun moves north and south with the seasons. The effect of thick clouds, which reflect solar energy, can be seen near the equator and during the summer off the west coasts of North America, South America, and Africa.
maps made via GDAL - Temperature forecast for the contiguous United States valid for July 29, 2024, at 2:00 pm PDT. The coolest areas (mostly along the West Coast or in mountain ranges) were predicted to be about 10˚C (light yellow), while the hottest (in the desert Southwest) were over 40˚ C (dark red). Contours complement the color palette and highlight small (1˚ C) variations in temperature.
maps made via GDAL - maps of the global biosphere combine ocean color, vegetation, and land cover classification data from the Visible Infrared Imaging Radiometer Suite (VIIRS) with bathymetry and elevation data from GEBCO.
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