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4 results for “Cabauw”
A two-year intercomparison of CW focusing wind lidar and tall mast wind measurements at Cabauw
<p>Dataset (.csv files) and software (python scripts) for generating figures, including data analysis, in our manuscript "A two-year intercomparison of CW focusing wind lidar and tall mast wind measurements at Cabauw", submitted to Atmos. Meas. Tech.</p>
Observations of molecular hydrogen (H2) mixing ratio and stable isotopic composition (deuterium content) at the Cabauw tall tower in the Netherlands
<p>This zip file contains the final corrected data that were used for the journal article "Observations of molecular hydrogen mixing ratio and stable isotopic composition at the Cabauw tall tower in the Netherlands" by Batenburg et al., Atmospheric Environment, 2016, doi:10.1016/j.atmosenv.2016.09.058<br> <br> Please cite the original AtmosEnv article when using these data.<br> The paper also contains more information about how these data were collected and calibrated, and on how the quality control flags were assigned.</p> <p>All samples were collected at the Cabauw tower, at the CESAR site (51.971° N, 4.927° E, http://www.cesar-observatory.nl/).<br> H2 and deltaD(H2) are calibrated using one to four laboratory reference air cylinders, depending on measurement period.<br> The H2 mixing ratio of the reference cylinders was determined by UHEI-IUP, MPI-BGC, or the IMAU isotope laboratory.<br> The deltaD(H2) of the reference cylinders is, sometimes indirectly, linked to the VSMOW scale by measurements of air mixtures containing H2 standards of known isotopic composition.<br> H2 scale: MPI2009, Jordan and Steinberg, AMT, 2011, doi:10.5194/amt-4-509-2011<br> deltaD(H2) units: permil deviation from VSMOW, Gonfiantini et al., IAEA-TECDOC-825, IAEA</p> <p>Times are UTC. </p> <p><br> The corresponding author can be reached through annekebatenburg@gmail.com for questions.</p>
Case stuides of ground-based remote sensing observations from Cabauw, NL, as obtained during the ACCEPT campaign in 2014.
<p>Datasets of Mira-35 NMRA and Mira-35 MBR4 cloud radars, PollyXT multiwavelength polarization lidar, and the corresponding Cloudnet categorization data for the case-study periods of 3 November and 7 November 2014. A detailed description of each dataset is provided below.</p> <p>1. 20141103_cesar_categorize.nc</p> <ul> <li>Categorization file produced with Cloudnet algorithm, as document on http://cloudnet.fmi.fi.</li> <li>The data were collected on November 3, 2014. They are based on Mira-35 NMRA radar, microwave radiometer, lidar ceilometer, and optical disdrometer. </li> </ul> <p>2. 20141107_cesar_categorize.nc</p> <ul> <li>Categorization file produced with Cloudnet algorithm, as document on http://cloudnet.fmi.fi.</li> <li>The data were collected on November 7, 2014. They are based on Mira-35 NMRA radar, microwave radiometer, lidar ceilometer, and optical disdrometer. </li> </ul> <p>3. 20141103_2000.pdm</p> <ul> <li>This dataset was collected on November 3, 2014, between 20:00 and 20:15 UTC, and includes four RHI scans performed using the Mira-35 MBR4 radar. It serves as the primary input for the technique used to retrieve the shape and orientation of ice particles.</li> </ul> <p>4. 20141107_0915.pdm</p> <ul> <li>This dataset was collected on November 7, 2014, between 09:15 and 09:30 UTC, and includes four RHI scans performed using the Mira-35 MBR4 radar. It serves as the primary input for the technique used to retrieve the shape and orientation of ice particles.</li> </ul> <p>5. 20141107_0945.pdm</p> <ul> <li>This dataset was collected on November 7, 2014, between 09:45 and 10:00 UTC, and includes four RHI scans performed using the Mira-35 MBR4 radar. It serves as the primary input for the technique used to retrieve the shape and orientation of ice particles.</li> </ul> <p>6. 20141107_0800.mmclx</p> <ul> <li>This dataset was collected on November 7, 2014, between 08:00 and 10:00 UTC, using the Mira-35 MBR4 radar. During this period, the radar performed eight PPI scans, with the data from each scan used to calculate wind speed and direction in 15-minute intervals. In this study, the data from the sixth and eighth scans were utilized to calculate wind speed and direction for the time intervals 09:15–09:30 UTC and 09:45–10:00 UTC, respectively.</li> </ul> <p>7. 20141103_2000.mmclx</p> <ul> <li>This dataset was collected on November 3, 2014, between 20:00 and 22:00 UTC, using the Mira-35 MBR4 radar. During this period, the radar performed eight PPI scans, with the data from each scan used to calculate wind speed and direction in 15-minute intervals. In this study, the data from the first scan were utilized to calculate wind speed and direction for the time intervals 20:00–2015 UTC.</li> </ul> <p>8. 20141103_cesar_pollyxt.nc</p> <ul> <li>This dataset was collected on November 03, 2014, between 08:00 and 10:00 UTC. Amongst others, the file provides time-height cross sections of 1064-nm attenuated backscatter coefficient and 532-nm volume depolarization ratio, which can be used to evaluate an observed cloud and aerosol scene for the occurrence of ice crystals and liquid water.</li> </ul> <p>9. 20141107_cesar_pollyxt.nc</p> <ul> <li>This dataset was collected on November 07, 2014, between 20:00 and 21:00 UTC. Amongst others, the file provides time-height cross sections of 1064-nm attenuated backscatter coefficient and 532-nm volume depolarization ratio, which can be used to evaluate an observed cloud and aerosol scene for the occurrence of ice crystals and liquid water.</li> </ul> <p> </p> <p> </p>
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