scholarly journals Assessing the accuracy of microwave radiometers and radio acoustic sounding systems for wind energy applications

Author(s):  
Laura Bianco ◽  
Katja Friedrich ◽  
James Wilczak ◽  
Duane Hazen ◽  
Daniel Wolfe ◽  
...  

Abstract. To assess current remote-sensing capabilities for wind energy applications, a remote-sensing system evaluation study, called XPIA (eXperimental Planetary boundary layer Instrument Assessment), was held in the spring of 2015 at NOAA’s Boulder Atmospheric Observatory (BAO) facility. Several remote-sensing platforms were evaluated to determine their suitability for the verification and validation processes used to test the accuracy of numerical weather prediction models. The evaluation of these platforms was performed with respect to well-defined reference systems: the BAO’s 300-m tower equipped at 6 levels (50, 100, 150, 200, 250, and 300 m) with 12 sonic anemometers and 6 temperature and relative humidity sensors; and approximately 60 radiosonde launches. In this study we first employ these reference measurements to validate temperature profiles retrieved by two co-located microwave radiometers, as well as virtual temperature measured by co-located wind profiling radars equipped with radio acoustic sounding systems. Results indicate a mean absolute error in the temperature retrieved by the microwave radiometers below 1.5 °C in the lowest 5 km of the atmosphere, and a mean absolute error in the virtual temperature measured by the radio acoustic sounding systems below 0.8 °C in the layer of the atmosphere covered by these measurements (up to approximately 1.6–2 km). We also investigated the benefit of the vertical velocity applied to the speed of sound before computing the virtual temperature by the radio acoustic sounding systems. We find that using this correction frequently increases the RASS error, and that it should not be routinely applied to all data. Water vapor density profiles measured by the MWRs were also compared with similar measurements from the soundings, showing the capability of MWRs to follow the vertical profile measured by the sounding, and finding a mean absolute error below 0.5 g m−3 in the lowest 5 km of the atmosphere. However, the relative humidity profiles measured by the microwave radiometer lack the high-resolution details available from radiosonde profiles. An encouraging and significant finding of this study was that the coefficient of determination between the lapse rate measured by the microwave radiometer and the tower measurements over the tower levels between 50 and 300 m ranged from 0.76 to 0.91, proving that these remote-sensing instruments can provide accurate information on atmospheric stability conditions in the lower boundary layer.

2017 ◽  
Vol 10 (5) ◽  
pp. 1707-1721 ◽  
Author(s):  
Laura Bianco ◽  
Katja Friedrich ◽  
James M. Wilczak ◽  
Duane Hazen ◽  
Daniel Wolfe ◽  
...  

Abstract. To assess current remote-sensing capabilities for wind energy applications, a remote-sensing system evaluation study, called XPIA (eXperimental Planetary boundary layer Instrument Assessment), was held in the spring of 2015 at NOAA's Boulder Atmospheric Observatory (BAO) facility. Several remote-sensing platforms were evaluated to determine their suitability for the verification and validation processes used to test the accuracy of numerical weather prediction models.The evaluation of these platforms was performed with respect to well-defined reference systems: the BAO's 300 m tower equipped at six levels (50, 100, 150, 200, 250, and 300 m) with 12 sonic anemometers and six temperature (T) and relative humidity (RH) sensors; and approximately 60 radiosonde launches.In this study we first employ these reference measurements to validate temperature profiles retrieved by two co-located microwave radiometers (MWRs) as well as virtual temperature (Tv) measured by co-located wind profiling radars equipped with radio acoustic sounding systems (RASSs). Results indicate a mean absolute error (MAE) in the temperature retrieved by the microwave radiometers below 1.5 K in the lowest 5 km of the atmosphere and a mean absolute error in the virtual temperature measured by the radio acoustic sounding systems below 0.8 K in the layer of the atmosphere covered by these measurements (up to approximately 1.6–2 km). We also investigated the benefit of the vertical velocity correction applied to the speed of sound before computing the virtual temperature by the radio acoustic sounding systems. We find that using this correction frequently increases the RASS error, and that it should not be routinely applied to all data.Water vapor density (WVD) profiles measured by the MWRs were also compared with similar measurements from the soundings, showing the capability of MWRs to follow the vertical profile measured by the sounding and finding a mean absolute error below 0.5 g m−3 in the lowest 5 km of the atmosphere. However, the relative humidity profiles measured by the microwave radiometer lack the high-resolution details available from radiosonde profiles. An encouraging and significant finding of this study was that the coefficient of determination between the lapse rate measured by the microwave radiometer and the tower measurements over the tower levels between 50 and 300 m ranged from 0.76 to 0.91, proving that these remote-sensing instruments can provide accurate information on atmospheric stability conditions in the lower boundary layer.


2018 ◽  
Vol 18 (10) ◽  
pp. 7001-7017 ◽  
Author(s):  
Andrés Esteban Bedoya-Velásquez ◽  
Francisco Navas-Guzmán ◽  
María José Granados-Muñoz ◽  
Gloria Titos ◽  
Roberto Román ◽  
...  

Abstract. This study focuses on the analysis of aerosol hygroscopic growth during the Sierra Nevada Lidar AerOsol Profiling Experiment (SLOPE I) campaign by using the synergy of active and passive remote sensors at the ACTRIS Granada station and in situ instrumentation at a mountain station (Sierra Nevada, SNS). To this end, a methodology based on simultaneous measurements of aerosol profiles from an EARLINET multi-wavelength Raman lidar (RL) and relative humidity (RH) profiles obtained from a multi-instrumental approach is used. This approach is based on the combination of calibrated water vapor mixing ratio (r) profiles from RL and continuous temperature profiles from a microwave radiometer (MWR) for obtaining RH profiles with a reasonable vertical and temporal resolution. This methodology is validated against the traditional one that uses RH from co-located radiosounding (RS) measurements, obtaining differences in the hygroscopic growth parameter (γ) lower than 5 % between the methodology based on RS and the one presented here. Additionally, during the SLOPE I campaign the remote sensing methodology used for aerosol hygroscopic growth studies has been checked against Mie calculations of aerosol hygroscopic growth using in situ measurements of particle number size distribution and submicron chemical composition measured at SNS. The hygroscopic case observed during SLOPE I showed an increase in the particle backscatter coefficient at 355 and 532 nm with relative humidity (RH ranged between 78 and 98 %), but also a decrease in the backscatter-related Ångström exponent (AE) and particle linear depolarization ratio (PLDR), indicating that the particles became larger and more spherical due to hygroscopic processes. Vertical and horizontal wind analysis is performed by means of a co-located Doppler lidar system, in order to evaluate the horizontal and vertical dynamics of the air masses. Finally, the Hänel parameterization is applied to experimental data for both stations, and we found good agreement on γ measured with remote sensing (γ532=0.48±0.01 and γ355=0.40±0.01) with respect to the values calculated using Mie theory (γ532=0.53±0.02 and γ355=0.45±0.02), with relative differences between measurements and simulations lower than 9 % at 532 nm and 11 % at 355 nm.


2018 ◽  
Vol 176 ◽  
pp. 06010
Author(s):  
Gregori de A. Moreira ◽  
Juan L. Guerrero-Rascado ◽  
Jose A. Benavent-Oltra ◽  
Pablo Ortiz-Amezcua ◽  
Roberto Róman ◽  
...  

The Planetary Boundary Layer (PBL) is the lowermost part of the troposphere. In this work, we analysed some high order moments and PBL height detected continuously by three remote sensing systems: an elastic lidar, a Doppler lidar and a passive Microwave Radiometer, during the SLOPE-2016 campaign, which was held in Granada from May to August 2016. This study confirms the feasibility of these systems for the characterization of the PBL, helping us to justify and understand its behaviour along the day.


2011 ◽  
Vol 139 (8) ◽  
pp. 2309-2326 ◽  
Author(s):  
Jason A. Otkin ◽  
Daniel C. Hartung ◽  
David D. Turner ◽  
Ralph A. Petersen ◽  
Wayne F. Feltz ◽  
...  

AbstractIn this study, an Observing System Simulation Experiment was used to examine how the assimilation of temperature, water vapor, and wind profiles from a potential array of ground-based remote sensing boundary layer profiling instruments impacts the accuracy of atmospheric analyses when using an ensemble Kalman filter data assimilation system. Remote sensing systems evaluated during this study include the Doppler wind lidar (DWL), Raman lidar (RAM), microwave radiometer (MWR), and the Atmospheric Emitted Radiance Interferometer (AERI). The case study tracked the evolution of several extratropical weather systems that occurred across the contiguous United States during 7–8 January 2008. Overall, the results demonstrate that using networks of high-quality temperature, wind, and moisture profile observations of the lower troposphere has the potential to improve the accuracy of wintertime atmospheric analyses over land. The impact of each profiling system was greatest in the lower and middle troposphere on the variables observed or retrieved by that instrument; however, some minor improvements also occurred in the unobserved variables and in the upper troposphere, particularly when RAM observations were assimilated. The best analysis overall was achieved when DWL wind profiles and temperature and moisture observations from the RAM, AERI, or MWR were assimilated simultaneously, which illustrates that both mass and momentum observations are necessary to improve the analysis accuracy.


2021 ◽  
Author(s):  
Etienne Cheynet ◽  
Martin Flügge ◽  
Joachim Reuder ◽  
Jasna B. Jakobsen ◽  
Yngve Heggelund ◽  
...  

Abstract. The paper presents the measurement strategy and dataset collected during the COTUR (COherence of TURbulence with lidars) campaign. This field experiment took place from February 2019 to April 2020 on the southwestern coast of Norway. The coherence quantifies the spatial correlation of eddies and is little known in the marine atmospheric boundary layer. The study was motivated by the need to better characterize the lateral coherence, which partly governs the dynamic wind load on multi-megawatt offshore wind turbines. During the COTUR campaign, the coherence was studied using land-based remote sensing technology. The instrument setup consisted of three long-range scanning Doppler wind lidars, one Doppler wind lidar profiler and one passive microwave radiometer. Both the WindScanner software and Lidar Planner software were used jointly to simultaneously orient the three scanner heads into the mean wind direction, which was provided by the lidar wind profiler. The radiometer instrument complemented these measurements by providing temperature and humidity profiles in the atmospheric boundary layer. The preliminary results show an undocumented variation of the lateral coherence with the distance from the coast. The scanning beams were pointed slightly upwards to record turbulence characteristics both within and above the surface layer, providing further insight on the applicability of surface-layer scaling to model the turbulent wind load on offshore wind turbines.


2011 ◽  
Vol 139 (8) ◽  
pp. 2327-2346 ◽  
Author(s):  
Daniel C. Hartung ◽  
Jason A. Otkin ◽  
Ralph A. Petersen ◽  
David D. Turner ◽  
Wayne F. Feltz

AbstractIn this study, atmospheric analyses obtained through assimilation of temperature, water vapor, and wind profiles from a potential network of ground-based remote sensing boundary layer profiling instruments were used to generate short-range ensemble forecasts for each assimilation experiment performed in Part I. Remote sensing systems evaluated during this study include the Doppler wind lidar (DWL), Raman lidar (RAM), microwave radiometer (MWR), and the Atmospheric Emitted Radiance Interferometer (AERI). Overall, the results show that the most accurate forecasts were achieved when mass (temperature and humidity profiles from the RAM, MWR, and/or AERI) and momentum (wind profiles from the DWL) observations were assimilated simultaneously, which is consistent with the main conclusion from Part I. For instance, the improved wind and moisture analyses obtained through assimilation of these observations contributed to more accurate forecasts of moisture flux convergence and the intensity and location of accumulated precipitation (ACPC) due to improved dynamical forcing and mesoscale boundary layer thermodynamic structure. An object-based verification tool was also used to assess the skill of the ACPC forecasts. Overall, total interest values for ACPC matched objects, along with traditional forecast skill statistics like the equitable threat score and critical success index, were most improved in the multisensor assimilation cases.


2020 ◽  
Author(s):  
Nikita Rusakov ◽  
Evgeny Poplavsky ◽  
Olga Ermakova ◽  
Yuliya Troitskaya ◽  
Daniil Sergeev ◽  
...  

<p>Active microwave sensing using satellite instruments has great advantages, since in this range the absorption by clouds and atmospheric gases is noticeably reduced, it allows for round-the-clock and all-weather monitoring of the ocean. One of the main problems is concerned with obtaining the dependency between the RCS of radar signal scattered by the wavy water surface and the parameters of the atmospheric boundary layer in hurricane conditions. To obtain this dependence, we used field measurements of wind speed in a hurricane from falling NOAA GPS-sondes and SAR images from the Sentinel-1 satellite. However, there is the problem of correct collocation of remote sensing data with field measurements of the atmospheric boundary layer parameters, since they are separated in time and space. In this regard, the amount of data suitable for analysis is very limited, which forces us to look for new data sources for processing. A six-channel SFMR radiometer is also installed on board of NOAA research aircraft that measures the emissivity of the ocean surface beneath the aircraft. Thus, it becomes possible to relate the radiometric measurements of SFMR with the parameters of the atmospheric boundary layer in a tropical cyclone obtained from wind velocity profiles, since they are carried out as close as possible in time and space. Using this relation, the SFMR data and the hurricane radar images were analyzed together and an alternative method was found for constructing the dependence of the RCS on the parameters of the boundary layer.</p><p>This work was supported by the RFBR projects No. 19-05-00249, 19-05-00366, 18-35-20068 (remote sensing data analysis) and RSF No. 19-17-00209 (GPS-sondes data assimilation and processing).</p><p> </p>


Author(s):  
Y L Pichugina ◽  
R M Banta ◽  
N D Kelley ◽  
W A Brewer ◽  
S P Sandberg ◽  
...  

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