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Microwave Radiometer CU Radiometrics MWR, Condon Raw Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
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Microwave Radiometer CU Radiometrics MWR, Condon Reviewed Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
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Microwave Radiometer ESRL Radiometrics MWR, Troutdale Raw Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
0 Stars
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Microwave Radiometer ESRL Radiometrics MWR, Troutdale Reviewed Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
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Microwave Radiometer ESRL Radiometrics MWR, Wasco Airport Raw Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
0 Stars
Publicly accessible

Microwave Radiometer ESRL Radiometrics MWR, Wasco Airport Reviewed Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
0 Stars
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Microwave Radiometer UND Radiometrics MWR, Rufus Raw Data

**Overview** These data monitor real-time profiles of temperature (K), water vapor (gm-3), relative humidity (%), and liquid water (gm-3) up to 10 km. **Data Details** All output files are named automatically using the following format: yyyy-mm-dd_hh-mm-ss_xxx.csv, where yyyy...

Bianco, L. Wind Energy Technologies Office (WETO)

Nov 18, 2015
1 Resources
0 Stars
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Site B PNNL Surface Met Station / Raw Data

**Overview** Low-speed weather information and high-speed sonic anemometer data at AWAKEN Site B

Goldberger, L. Wind Energy Technologies Office (WETO)

Nov 23, 2021
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Site G PNNL Surface Met Station / Raw Data

**Overview** Low-speed weather information and high-speed sonic anemometer data at AWAKEN Site G

Goldberger, L. Wind Energy Technologies Office (WETO)

Nov 23, 2021
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Site A2 PNNL Surface Met Station / Raw Data

**Overview** Low-speed weather information and high-speed sonic anemometer data at AWAKEN Site A2

Goldberger, L. Wind Energy Technologies Office (WETO)

Dec 13, 2021
1 Resources
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Site A4 PNNL Surface Met Station / Raw Data

**Overview** Low-speed weather information and high-speed sonic anemometer data at AWAKEN Site A4

Goldberger, L. Wind Energy Technologies Office (WETO)

Nov 23, 2021
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Site A5 PNNL Surface Met Station / Raw Data

**Overview** Low-speed weather information and high-speed sonic anemometer data at AWAKEN Site A5

Goldberger, L. Wind Energy Technologies Office (WETO)

Jan 10, 2022
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Site A7 PNNL Surface Met Station / Raw Data

**Overview** Low-speed weather information and high-speed sonic anemometer data at AWAKEN Site A7.

Goldberger, L. Wind Energy Technologies Office (WETO)

Oct 29, 2021
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Site C1 PNNL Surface Met Station / Raw Data

**Overview** Low-speed weather information and high-speed sonic anemometer data at American WAKE experimeNt (AWAKEN) Site C1

Goldberger, L. Wind Energy Technologies Office (WETO)

Dec 13, 2021
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Site A4 PNNL Surface Met Station / Reviewed Data

**Overview** Low-speed weather information and high-speed sonic anemometer data at AWAKEN Site A4

Goldberger, L. Wind Energy Technologies Office (WETO)

Nov 23, 2021
1 Resources
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Lidar UT-Dallas WindCube 200S Doppler Lidar Derived Data

**Overview** fixed scan against southeast sonic of 50m, 100m and 150m and supersite at 60m height **Data Quality** unfiltered data **Uncertainty** raw data **Constraints**

Iungo, G. Wind Energy Technologies Office (WETO)

Mar 05, 2015
1 Resources
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Lidar UT-Dallas WindCube 200S Doppler Lidar Processed Data

**Overview** fixed scan against southeast sonic of 50m, 100m and 150m and supersite at 60m height **Data Quality** unfiltered data **Uncertainty** raw data **Constraints**

Iungo, G. Wind Energy Technologies Office (WETO)

Mar 18, 2015
1 Resources
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Lidar UT-Dallas WindCube 200S Doppler Lidar Raw Data

**Overview** fixed scan against southeast sonic of 50m, 100m and 150m and supersite at 60m height **Data Quality** unfiltered data **Uncertainty** raw data **Constraints**

Iungo, G. Wind Energy Technologies Office (WETO)

Mar 06, 2015
1 Resources
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UAE6 Wind Tunnel Tests Data UAE6 Sequence P Raw Data

**Overview** Sequence P: Wake Flow Visualization, Upwind (P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 15 m/s. Yaw angles of 0° to –60° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM. ...

Fingersh, L. Wind Energy Technologies Office (WETO)

Nov 28, 2018
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OC6 Phase Ia Nonlinear hydrodynamic loading validation dataset

**Overview** Two validation campaigns were examined within the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) Phase 1 project to examine the modeling tools' underprediction of loads and motion of a floating wind semisubmersible (semi) at...

Robertson, A. Wind Energy Technologies Office (WETO)

Aug 08, 2021
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Lidar DTU SpinnerLidar Reviewed Data

**Overview** Scaled Wind Farm Technology (SWiFT) Facility meteorological tower (MET), turbine, and Technical University of Denmark (DTU) SpinnerLidar data acquired on 20161216 UTC during a neutral atmospheric boundary layer inflow at a single focus distance of 2.5 D (D=27 m). **...

Kelley, C. and Naughton, B. Wind Energy Technologies Office (WETO)

Dec 15, 2016
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Wind Turbine SWiFT southeast WTGa1 Reviewed Data

**Overview** Scaled Wind Farm Technology (SWiFT) Facility meteorological tower (MET), turbine, and Technical University of Denmark (DTU) SpinnerLidar data acquired on 20161216 UTC during a neutral atmospheric boundary layer inflow at a single focus distance of 2.5 D (D=27 m). **...

Kelley, C. and Naughton, B. Wind Energy Technologies Office (WETO)

Dec 15, 2016
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wfip2.model/realtime.hrrr_esrl.graphics.01

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...

Macduff, M. Wind Energy Technologies Office (WETO)

Dec 14, 2015
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wfip2.model/realtime.hrrr_esrl.icbc.01

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...

Macduff, M. Wind Energy Technologies Office (WETO)

Dec 01, 2015
1 Resources
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wfip2.model/realtime.hrrr_wfip2.graphics.02

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...

Macduff, M. Wind Energy Technologies Office (WETO)

Dec 16, 2015
1 Resources
0 Stars
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