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This dataset contains vertical profiling lidar data from AWAKEN site A1. This is the ZephIR300 #773 lidar system. The .csv files are monthly data files with 10-min average data. The .zip files are daily high frequency data and zipped by month.
This dataset contains processed NREL thermodynamic profiler (Assist II-12) data from the WFIP3 CACO site.
This dataset contains raw NREL Thermodynamic profiler (Assist II-12) data from the WFIP3 CACO site.
This dataset contains wind profiles retrieved from 6-beam Velocity Azimuth Display (VAD) scans done by a Streamline XR Doppler Lidar operated by Lawrence Livermore National Laboratory and deployed at the Tree Tops site (1.5 km South-West of MLBS site). The wind components (expressed as zonal, meridional and vertical) are retrieved through the algorithm of Paschke et al. (2015). The quality control of the radial wind speed is performed following the algorithm of Foken et al. (2004).
This dataset contains wind profiles retrieved from 6-beam Velocity Azimuth Display (VAD) scans done by a Streamline XR Doppler Lidar operated by the University of Virginia and deployed at the MLBS site. The wind components (expressed as zonal, meridional and vertical) are retrieved through the algorithm of Paschke et al. (2015). The quality control of the radial wind speed is performed following the algorithm of Foken et al. (2004).
This dataset contains wind profiles retrieved from 6-beam Velocity Azimuth Display (VAD) scans done by the UC Davis scanning Lidar. The wind components (expressed as zonal, meridional and vertical) are retrieved through the algorithm of Paschke et al. (2015). The quality control of the radial wind speed is performed following the algorithm of Goring & Nikora (2002).
A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and combined to derive the horizontal wind field over the radar. These data are typically sampled and averaged hourly or sub-hourly (15-min) and usually have 60-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz system. Both a high-resolution, lower height coverage mode and a low-resolution, higher height coverage mode are used to collect the data.
A radar wind profiler measures the Doppler shift of electromagnetic energy scattered back from atmospheric turbulence and hydrometeors along 3-5 vertical and off-vertical point beam directions. Back-scattered signal strength and radial-component velocities are remotely sensed along all beam directions and combined to derive the horizontal wind field over the radar. These data are typically sampled and averaged hourly or sub-hourly (15-min) and usually have 60-m and/or 100-m vertical resolutions up to 4 km for the 915 MHz system. Both a high-resolution, lower height coverage mode and a low-resolution, higher height coverage mode are used to collect the data.
This dataset contains standardized data from the WFIP3 Wind Profiler located at the Rhode Island WFIP3 site.
This dataset contains standardized data from the WFIP3 Wind Profiler with Radio Acoustic Sounding System (RASS).
The field profiling lidar #ZX300-773 was deployed on the ground in an open field 880 m south of the Wind River NEON tower in summer 2025. It was co-located with LLNL's Halo XR+ scanning lidar (z05) and Argonne's Waggle Node to capture mountain-valley flows during the warm summer season. The zip files contain high frequency data. The excel files are 10-min averages.
This dataset contains 10-minute averaged data from DOE Buoy 130 during WFIP-3. This includes wind speed and corrected wind direction profiles from a ZX 300 M lidar as well as surface meteorology from the ZX and from the WXT sensors.
This dataset contains high-frequency wind profiles from ground-based NLR Halo XR+ 235 performing six-beam scans.
This dataset contains high-frequency data from the ground-based NLR profiling lidar (Windcube v2.1) deployed at FC Site 4.0.
The dataset contains raw data from the ground-based NLR profiling lidar (Windcube v2.1) at FC Site 4.0. Two data types are included here: 1) STA files, which have 10-minute average data, and 2) RTD files, which have real-time data, at about 1 Hz resolution.
The goal of the experiment was to demonstrate that the optimized multiplexed multi-PTM profiling workflow can comprehensively and quantitatively capture dynamic changes in protein abundance, cysteine oxidation, phosphorylation, and acetylation in cytokine-induced inflammatory stress in mouse pancreatic ß-cells. Global proteomic, redox proteomic, phosphoproteomic, and acetylomic were data collected from mouse Beta-TC-6 pancreatic Beta-cells, untreated (mock) and cytokine-treated Beta-cells at 4, 8, and 24 hours with 4 biological replicates. Samples were digested with trypsin and Lys-C, then analyzed by LC-MS/MS. Data were searched with MS-GF+, MASIC, and MaxQuant using PNNL's DMS processing pipeline.
PerCon SFA project mass spectrometry data analysis of SoDA-PAL photoaffinity probe labeled proteins and global proteome profiling of microbial isolate A. pittii SO1 sorgoleone interactome grown under three different culture conditions using acetate and sorgoleone.
The economy of biorefineries is influenced not only by biofuel production from carbohydrates but also by the production of valuable compounds from largely underutilized industrial residues. Currently, the demand for many chemicals that could be made in a biorefinery, such as succinic acid (SA), medium-chain fatty acids (MCFAs), and lactic acid (LA), is fulfilled using petroleum, palm oil, or pure carbohydrates as raw materials, respectively. Thin stillage (TS), the residual liquid material following distillation of ethanol, is an underutilized coproduct from the starch biofuel industry. This carbon-rich material has the potential for chemical upgrading by microorganisms. Here, we explored the formation of different fermentation products by microbial communities grown on TS using different bioreactor conditions. At the baseline operational condition (6-day retention time, pH 5.5, 35°C), we observed a mixture of MCFAs as the principal fermentation products. Operation of a bioreactor with a 1-day retention time induced an increase in SA production, and a temperature increase to 55°C resulted in the accumulation of lactic and propionic acids. In addition, a reactor operated with a 1-day retention time at 55°C conditions resulted in LA accumulation as the main fermentation product. The prominent members of the microbial community in each reactor were assessed by 16S rRNA gene amplicon sequencing and phylogenetic analysis. Under all operating conditions, members of the Lactobacillaceae family within Firmicutes and the Acetobacteraceae family within Proteobacteria were ubiquitous. Members of the Prevotellaceae family within Bacteroidetes and Lachnospiraceae family within the Clostridiales order of Firmicutes were mostly abundant at 35°C and not abundant in the microbial communities of the TS reactors incubated at 55°C. The ability to adjust bioreactor operating conditions to select for microbial communities with different fermentation product profiles offers new strategies to explore and compare potentially valuable fermentation products from TS and allows industries the flexibility to adapt and switch chemical production based on market prices and demands.