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197 results for “era5-land”

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zenodo44/100

ERA5-Land selected indicators daily aggregates for the Latin America region, 2021

<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2021.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>

opencc-by-4.0Oct 2023View details →
zenodo44/100

ERA5-Land selected indicators daily aggregates for the Latin America region, 2020

<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2020.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>

opencc-by-4.0Oct 2023View details →
zenodo44/100

ERA5-Land selected indicators daily aggregates for the Latin America region, 2018

<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2018.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>

opencc-by-4.0Oct 2023View details →
zenodo44/100

ERA5-Land selected indicators daily aggregates for the Latin America region, 2019

<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2019.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>

opencc-by-4.0Oct 2023View details →
zenodo40/100

ERA5-Land selected indicators daily aggregates for the Latin America region, 2023

<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 2023.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>

opencc-by-4.0Mar 2024View details →
zenodo40/100

ERA5-Land selected indicators daily aggregates for Africa, 1991

<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa for 1991.</p> <p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p> <p>For 2m dewpoint pressure, 10m u-component of wind, 10m v-component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean, and minimum were used for aggregation.</p> <p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>

opencc-by-4.0May 2024View details →
zenodo40/100

C3S SM COMBINED all versions (until v202212) with ERA5-Land vs ISMN FRMs 0-10 cm

QA4SM validation: C3S SM combined v202212 vs C3S SM combined v202012 vs C3S SM combined v201912 vs C3S SM combined v201812 vs ERA5-Land v20190904 vs ISMN 20230110 global. URL: https://qa4sm.eu/ui/validation-result/2f865302-5e35-4c28-8549-1cc7e86f38cd. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroJun 2023View details →
zenodo36/100

Exemplary validation of SMOS Level 3 version 339 Descending vs ERA5-Land v20190904 vs ISMN 20230110 global for EGU24

Exemplary QA4SM validation using FRMs for EGU24: SMOS Level 3 version 339 Descending vs ERA5-Land v20190904 vs ISMN 20230110 global. URL: https://qa4sm.eu/ui/validation-result/7f27889e-95e4-4e67-9a85-2e472cbb935c. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroApr 2024View details →
zenodo36/100

Validation of C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904

QA4SM validation: C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904. URL: https://qa4sm.eu/ui/validation-result/ab9a564e-8c55-4ba2-828a-9577e9948803. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroMay 2024View details →
zenodo36/100

Validation of C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904

QA4SM validation: C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904. URL: https://qa4sm.eu/ui/validation-result/9241fbf2-995f-4ece-be64-2302efaae280. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroMay 2024View details →
zenodo36/100

Validation of C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global

QA4SM validation: C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global. URL: https://qa4sm.eu/ui/validation-result/b61ec3bb-0eb9-4803-bd70-2dd052c5bcfb. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroMay 2024View details →
zenodo36/100

Validation of C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global

QA4SM validation: C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global. URL: https://qa4sm.eu/ui/validation-result/ceed8392-014f-48e6-a7f7-eb00d0b4ddd9. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroMay 2024View details →
zenodo36/100

Validation of C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global

QA4SM validation: C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global. URL: https://qa4sm.eu/ui/validation-result/24418dc9-98ae-4b96-a272-87c4c6583df3. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroMay 2024View details →
zenodo36/100

Validation of C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global

QA4SM validation: C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global. URL: https://qa4sm.eu/ui/validation-result/ed647646-8513-4bca-8d0a-1db534c145fd. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroMay 2024View details →
zenodo36/100

Validation of C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global

QA4SM validation: C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global. URL: https://qa4sm.eu/ui/validation-result/62c2f4f1-572a-4932-b4c9-cf0d29da156b. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroMay 2024View details →
zenodo36/100

Validation of C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global

QA4SM validation: C3S SM combined v201912 vs C3S SM combined v202012 vs C3S SM combined v202212 vs C3S SM combined v202312 vs ERA5-Land v20190904 vs ISMN 20240314 global. URL: https://qa4sm.eu/ui/validation-result/d6936b1a-e01c-4908-8f71-ea4be275c4fd. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroMay 2024View details →
zenodo36/100

Data: Soil moisture modeling with ERA5-Land retrievals, topographic indices, and in situ measurements and its use for predicting ruts

<p>Data for:&nbsp;<br><br>Soil moisture modeling with ERA5-Land retrievals, topographic indices, and in situ measurements and its use for predicting ruts</p> <p>Marian Sch&ouml;nauer<sup>1</sup>, Anneli M. &Aring;gren<sup>2</sup>, Klaus Katzensteiner<sup>3</sup>, Florian Hartsch<sup>1</sup>, Paul Arp<sup>4</sup>, Simon Drollinger<sup>5</sup>, Dirk Jaeger<sup>1</sup></p> <p><sup>1</sup>Department of Forest Work Science and Engineering, University of G&ouml;ttingen, G&ouml;ttingen, Germany</p> <p><sup>2</sup>Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Ume&aring;, Sweden</p> <p><sup>3</sup>Institute of Forest Ecology, University of Natural Resources and Life Sciences, Vienna, Vienna, Austria</p> <p><sup>4</sup>Forestry and Environmental Management, University of New Brunswick, New Brunswick, Canada</p> <p><sup>5</sup>Department of Physical Geography, University of G&ouml;ttingen, G&ouml;ttingen, Germany</p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

Validation of C3S SM combined v202212 vs C3S SM combined v202012 vs ERA5-Land v20190904

QA4SM validation: C3S SM combined v202212 vs C3S SM combined v202012 vs ERA5-Land v20190904. URL: https://qa4sm.eu/ui/validation-result/80beb102-f5f4-4b1a-94f4-57008df9e322. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroJul 2023View details →
zenodo36/100

Validation of C3S SM combined v202212 vs C3S SM combined v202012 vs ERA5-Land v20190904

QA4SM validation: C3S SM combined v202212 vs C3S SM combined v202012 vs ERA5-Land v20190904. URL: https://qa4sm.eu/ui/validation-result/aaf66b58-ce30-4754-9349-8c48dcf81595. Produced on QA4SM (https://qa4sm.eu)

opencc-zeroJul 2023View details →
zenodo32/100

ERA5-Land monthly averaged dataset for Galaxy Panoply training

<p><strong>ERA5-Land monthly averaged data January 2019</strong></p> <p>Dataset has been retrieved on the Copernicus Climate data Store (<a href="https://cds.climate.copernicus.eu/#!/home">https://cds.climate.copernicus.eu/#!/home</a>) and is meant to be used for teaching purposes only. This dataset is used in the Galaxy training on &quot;Visualize Climate data with Panoply in Galaxy&quot;.</p> <p>See&nbsp;<a href="https://training.galaxyproject.org/">https://training.galaxyproject.org/</a>&nbsp;(topic: climate) for more information.</p> <p><strong>Product type:&nbsp;</strong>Monthly averaged reanalysis</p> <p><strong>Variable:</strong></p> <p>10m u-component of wind, 10m v-component of wind, 2m temperature, Leaf area index, high vegetation, Leaf area index, low vegetation, Snow cover, Snow depth</p> <p><strong>Year:</strong></p> <p>2019</p> <p><strong>Month:</strong></p> <p>January</p> <p><strong>Time:</strong></p> <p>00:00</p> <p><strong>Format:</strong></p> <p>NetCDF (experimental)</p>

opencc-by-4.0Mar 2020View details →

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