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Title: Assessing State-of-the-Art Capabilities for Probing the Atmospheric Boundary Layer: The XPIA Field Campaign

Abstract

The synthesis of new measurement technologies with advances in high performance computing provides an unprecedented opportunity to advance our understanding of the atmosphere, particularly with regard to the complex flows in the atmospheric boundary layer. To assess current measurement capabilities for quantifying features of atmospheric flow within wind farms, the U.S. Dept. of Energy sponsored the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign at the Boulder Atmospheric Observatory (BAO) in spring 2015. Herein, we summarize the XPIA field experiment design, highlight novel approaches to boundary-layer measurements, and quantify measurement uncertainties associated with these experimental methods. Line-of-sight velocities measured by scanning lidars and radars exhibit close agreement with tower measurements, despite differences in measurement volumes. Virtual towers of wind measurements, from multiple lidars or dual radars, also agree well with tower and profiling lidar measurements. Estimates of winds over volumes,conducted with rapid lidar scans, agree with those from scanning radars, enabling assessment of spatial variability. Microwave radiometers provide temperature profiles within and above the boundary layer with approximately the same uncertainty as operational remote sensing measurements. Using a motion platform, we assess motion-compensation algorithms for lidars to be mounted on offshore platforms. Finally, we highlight cases that could be usefulmore » for validation of large-eddy simulations or mesoscale numerical weather prediction, providing information on accessing the archived dataset. We conclude that modern remote Lundquist et al. XPIA BAMS Page 4 of 81 sensing systems provide a generational improvement in observational capabilities, enabling resolution of refined processes critical to understanding 61 inhomogeneous boundary-layer flows such as those found in wind farms.« less

Authors:
 [1];  [2];  [3];  [4];  [2];  [2];  [5];  [3];  [6];  [7];  [8];  [3];  [3];  [7];  [9];  [6];  [6];  [6];  [7];  [2] more »;  [10];  [11];  [9];  [7];  [2];  [8];  [10];  [6];  [7];  [6];  [6];  [7];  [7];  [2];  [4];  [7] « less
  1. Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, and National Renewable Energy Laboratory, Golden, Colorado
  2. National Oceanic and Atmospheric Administration/Earth System Research Laboratory, Boulder, Colorado
  3. The University of Texas at Dallas, Dallas, Texas
  4. Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado
  5. National Renewable Energy Laboratory, Golden, Colorado
  6. University of Maryland, Baltimore County, Baltimore, Maryland
  7. Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado
  8. Texas Tech University, Lubbock, Texas
  9. National Center for Atmospheric Research, Boulder, Colorado
  10. Pacific Northwest National Laboratory, Richland, Washington
  11. College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, Oregon
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1347869
Report Number(s):
PNNL-SA-115298
Journal ID: ISSN 0003-0007; WW0600000
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Bulletin of the American Meteorological Society; Journal Volume: 98; Journal Issue: 2
Country of Publication:
United States
Language:
English

Citation Formats

Lundquist, Julie K., Wilczak, James M., Ashton, Ryan, Bianco, Laura, Brewer, W. Alan, Choukulkar, Aditya, Clifton, Andrew, Debnath, Mithu, Delgado, Ruben, Friedrich, Katja, Gunter, Scott, Hamidi, Armita, Iungo, Giacomo Valerio, Kaushik, Aleya, Kosović, Branko, Langan, Patrick, Lass, Adam, Lavin, Evan, Lee, Joseph C. -Y., McCaffrey, Katherine L., Newsom, Rob K., Noone, David C., Oncley, Steven P., Quelet, Paul T., Sandberg, Scott P., Schroeder, John L., Shaw, William J., Sparling, Lynn, Martin, Clara St., Pe, Alexandra St., Strobach, Edward, Tay, Ken, Vanderwende, Brian J., Weickmann, Ann, Wolfe, Daniel, and Worsnop, Rochelle. Assessing State-of-the-Art Capabilities for Probing the Atmospheric Boundary Layer: The XPIA Field Campaign. United States: N. p., 2017. Web. doi:10.1175/BAMS-D-15-00151.1.
Lundquist, Julie K., Wilczak, James M., Ashton, Ryan, Bianco, Laura, Brewer, W. Alan, Choukulkar, Aditya, Clifton, Andrew, Debnath, Mithu, Delgado, Ruben, Friedrich, Katja, Gunter, Scott, Hamidi, Armita, Iungo, Giacomo Valerio, Kaushik, Aleya, Kosović, Branko, Langan, Patrick, Lass, Adam, Lavin, Evan, Lee, Joseph C. -Y., McCaffrey, Katherine L., Newsom, Rob K., Noone, David C., Oncley, Steven P., Quelet, Paul T., Sandberg, Scott P., Schroeder, John L., Shaw, William J., Sparling, Lynn, Martin, Clara St., Pe, Alexandra St., Strobach, Edward, Tay, Ken, Vanderwende, Brian J., Weickmann, Ann, Wolfe, Daniel, & Worsnop, Rochelle. Assessing State-of-the-Art Capabilities for Probing the Atmospheric Boundary Layer: The XPIA Field Campaign. United States. doi:10.1175/BAMS-D-15-00151.1.
Lundquist, Julie K., Wilczak, James M., Ashton, Ryan, Bianco, Laura, Brewer, W. Alan, Choukulkar, Aditya, Clifton, Andrew, Debnath, Mithu, Delgado, Ruben, Friedrich, Katja, Gunter, Scott, Hamidi, Armita, Iungo, Giacomo Valerio, Kaushik, Aleya, Kosović, Branko, Langan, Patrick, Lass, Adam, Lavin, Evan, Lee, Joseph C. -Y., McCaffrey, Katherine L., Newsom, Rob K., Noone, David C., Oncley, Steven P., Quelet, Paul T., Sandberg, Scott P., Schroeder, John L., Shaw, William J., Sparling, Lynn, Martin, Clara St., Pe, Alexandra St., Strobach, Edward, Tay, Ken, Vanderwende, Brian J., Weickmann, Ann, Wolfe, Daniel, and Worsnop, Rochelle. Wed . "Assessing State-of-the-Art Capabilities for Probing the Atmospheric Boundary Layer: The XPIA Field Campaign". United States. doi:10.1175/BAMS-D-15-00151.1.
@article{osti_1347869,
title = {Assessing State-of-the-Art Capabilities for Probing the Atmospheric Boundary Layer: The XPIA Field Campaign},
author = {Lundquist, Julie K. and Wilczak, James M. and Ashton, Ryan and Bianco, Laura and Brewer, W. Alan and Choukulkar, Aditya and Clifton, Andrew and Debnath, Mithu and Delgado, Ruben and Friedrich, Katja and Gunter, Scott and Hamidi, Armita and Iungo, Giacomo Valerio and Kaushik, Aleya and Kosović, Branko and Langan, Patrick and Lass, Adam and Lavin, Evan and Lee, Joseph C. -Y. and McCaffrey, Katherine L. and Newsom, Rob K. and Noone, David C. and Oncley, Steven P. and Quelet, Paul T. and Sandberg, Scott P. and Schroeder, John L. and Shaw, William J. and Sparling, Lynn and Martin, Clara St. and Pe, Alexandra St. and Strobach, Edward and Tay, Ken and Vanderwende, Brian J. and Weickmann, Ann and Wolfe, Daniel and Worsnop, Rochelle},
abstractNote = {The synthesis of new measurement technologies with advances in high performance computing provides an unprecedented opportunity to advance our understanding of the atmosphere, particularly with regard to the complex flows in the atmospheric boundary layer. To assess current measurement capabilities for quantifying features of atmospheric flow within wind farms, the U.S. Dept. of Energy sponsored the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign at the Boulder Atmospheric Observatory (BAO) in spring 2015. Herein, we summarize the XPIA field experiment design, highlight novel approaches to boundary-layer measurements, and quantify measurement uncertainties associated with these experimental methods. Line-of-sight velocities measured by scanning lidars and radars exhibit close agreement with tower measurements, despite differences in measurement volumes. Virtual towers of wind measurements, from multiple lidars or dual radars, also agree well with tower and profiling lidar measurements. Estimates of winds over volumes,conducted with rapid lidar scans, agree with those from scanning radars, enabling assessment of spatial variability. Microwave radiometers provide temperature profiles within and above the boundary layer with approximately the same uncertainty as operational remote sensing measurements. Using a motion platform, we assess motion-compensation algorithms for lidars to be mounted on offshore platforms. Finally, we highlight cases that could be useful for validation of large-eddy simulations or mesoscale numerical weather prediction, providing information on accessing the archived dataset. We conclude that modern remote Lundquist et al. XPIA BAMS Page 4 of 81 sensing systems provide a generational improvement in observational capabilities, enabling resolution of refined processes critical to understanding 61 inhomogeneous boundary-layer flows such as those found in wind farms.},
doi = {10.1175/BAMS-D-15-00151.1},
journal = {Bulletin of the American Meteorological Society},
number = 2,
volume = 98,
place = {United States},
year = {Wed Feb 01 00:00:00 EST 2017},
month = {Wed Feb 01 00:00:00 EST 2017}
}
  • To assess current capabilities for measuring flow within the atmospheric boundary layer, including within wind farms, the U.S. Dept. of Energy sponsored the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign at the Boulder Atmospheric Observatory (BAO) in spring 2015. Herein, we summarize the XPIA field experiment, highlight novel measurement approaches, and quantify uncertainties associated with these measurement methods. Line-of-sight velocities measured by scanning lidars and radars exhibit close agreement with tower measurements, despite differences in measurement volumes. Virtual towers of wind measurements, from multiple lidars or radars, also agree well with tower and profiling lidar measurements. Estimates of windsmore » over volumes from scanning lidars and radars are in close agreement, enabling assessment of spatial variability. Strengths of the radar systems used here include high scan rates, large domain coverage, and availability during most precipitation events, but they struggle at times to provide data during periods with limited atmospheric scatterers. In contrast, for the deployment geometry tested here, the lidars have slower scan rates and less range, but provide more data during non-precipitating atmospheric conditions. Microwave radiometers provide temperature profiles with approximately the same uncertainty as Radio-Acoustic Sounding Systems (RASS). Using a motion platform, we assess motion-compensation algorithms for lidars to be mounted on offshore platforms. As a result, we highlight cases for validation of mesoscale or large-eddy simulations, providing information on accessing the archived dataset. We conclude that modern remote sensing systems provide a generational improvement in observational capabilities, enabling resolution of fine-scale processes critical to understanding inhomogeneous boundary-layer flows.« less
  • Accurate three-dimensional information of wind flow fields can be an important tool in not only visualizing complex flow but also understanding the underlying physical processes and improving flow modeling. However, a thorough analysis of the measurement uncertainties is required to properly interpret results. The XPIA (eXperimental Planetary boundary layer Instrumentation Assessment) field campaign conducted at the Boulder Atmospheric Observatory (BAO) in Erie, CO, from 2 March to 31 May 2015 brought together a large suite of in situ and remote sensing measurement platforms to evaluate complex flow measurement strategies. In this paper, measurement uncertainties for different single and multi-Doppler strategies using simple scanmore » geometries (conical, vertical plane and staring) are investigated. The tradeoffs (such as time–space resolution vs. spatial coverage) among the different measurement techniques are evaluated using co-located measurements made near the BAO tower. Sensitivity of the single-/multi-Doppler measurement uncertainties to averaging period are investigated using the sonic anemometers installed on the BAO tower as the standard reference. Finally, the radiometer measurements are used to partition the measurement periods as a function of atmospheric stability to determine their effect on measurement uncertainty. It was found that with an increase in spatial coverage and measurement complexity, the uncertainty in the wind measurement also increased. For multi-Doppler techniques, the increase in uncertainty for temporally uncoordinated measurements is possibly due to requiring additional assumptions of stationarity along with horizontal homogeneity and less representative line-of-sight velocity statistics. Lastly, it was also found that wind speed measurement uncertainty was lower during stable conditions compared to unstable conditions.« less
    Cited by 1
  • Accurate three-dimensional information of wind flow fields can be an important tool in not only visualizing complex flow but also understanding the underlying physical processes and improving flow modeling. However, a thorough analysis of the measurement uncertainties is required to properly interpret results. The XPIA (eXperimental Planetary boundary layer Instrumentation Assessment) field campaign conducted at the Boulder Atmospheric Observatory (BAO) in Erie, CO, from 2 March to 31 May 2015 brought together a large suite of in situ and remote sensing measurement platforms to evaluate complex flow measurement strategies. In this paper, measurement uncertainties for different single and multi-Doppler strategies using simple scanmore » geometries (conical, vertical plane and staring) are investigated. The tradeoffs (such as time–space resolution vs. spatial coverage) among the different measurement techniques are evaluated using co-located measurements made near the BAO tower. Sensitivity of the single-/multi-Doppler measurement uncertainties to averaging period are investigated using the sonic anemometers installed on the BAO tower as the standard reference. Finally, the radiometer measurements are used to partition the measurement periods as a function of atmospheric stability to determine their effect on measurement uncertainty. It was found that with an increase in spatial coverage and measurement complexity, the uncertainty in the wind measurement also increased. For multi-Doppler techniques, the increase in uncertainty for temporally uncoordinated measurements is possibly due to requiring additional assumptions of stationarity along with horizontal homogeneity and less representative line-of-sight velocity statistics. Lastly, it was also found that wind speed measurement uncertainty was lower during stable conditions compared to unstable conditions.« less
  • In March and April of 2015, the ARM Doppler lidar that was formerly operated at the Tropical Western Pacific site in Darwin, Australia (S/N 0710-08) was deployed to the Boulder Atmospheric Observatory (BAO) for the eXperimental Planetary boundary-layer Instrument Assessment (XPIA) field campaign. The goal of the XPIA field campaign was to investigate methods of using multiple Doppler lidars to obtain high-resolution three-dimensional measurements of winds and turbulence in the atmospheric boundary layer, and to characterize the uncertainties in these measurements. The ARM Doppler lidar was one of many Doppler lidar systems that participated in this study. During XPIA themore » 300-m tower at the BAO site was instrumented with well-calibrated sonic anemometers at six levels. These sonic anemometers provided highly accurate reference measurements against which the lidars could be compared. Thus, the deployment of the ARM Doppler lidar during XPIA offered a rare opportunity for the ARM program to characterize the uncertainties in their lidar wind measurements. Results of the lidar-tower comparison indicate that the lidar wind speed measurements are essentially unbiased (~1cm s-1), with a random error of approximately 50 cm s-1. Two methods of uncertainty estimation were tested. The first method was found to produce uncertainties that were too low. The second method produced estimates that were more accurate and better indicators of data quality. As of December 2015, the first method is being used by the ARM Doppler lidar wind value-added product (VAP). One outcome of this work will be to update this VAP to use the second method for uncertainty estimation.« less
  • The recent ship-based MAGIC (Marine ARM GCSS Pacific Cross-Section Intercomparison (GPCI) Investigation of Clouds) field campaign with the marine-capable Second ARM Mobile Facility (AMF2) deployed on the Horizon Lines cargo container M/V Spirit provided nearly 200 days of intraseasonal high-resolution observations of clouds, precipitation, and marine boundary layer (MBL) structure on multiple legs between Los Angeles, California, and Honolulu, Hawaii. During the deployment, MBL clouds exhibited a much higher frequency of occurrence than other cloud types and occurred more often in the warm season than in the cold season. MBL clouds demonstrated a propensity to produce precipitation, which often evaporatedmore » before reaching the ocean surface. The formation of stratocumulus is strongly correlated to a shallow MBL with a strong inversion and a weak transition, while cumulus formation is associated with a much weaker inversion and stronger transition. The estimated inversion strength is shown to depend seasonally on the potential temperature at 700 hPa. The location of the commencement of systematic MBL decoupling always occurred eastward of the locations of cloud breakup, and the systematic decoupling showed a strong moisture stratification. The entrainment of the dry warm air above the inversion appears to be the dominant factor triggering the systematic decoupling, while surface latent heat flux, precipitation, and diurnal circulation did not play major roles. MBL clouds broke up over a short spatial region due to the changes in the synoptic conditions, implying that in real atmospheric conditions the MBL clouds do not have enough time to evolve as in the idealized models. (auth)« less