Scanning ARM Cloud Radars. Part II: Data Quality Control and Processing

2014 ◽  
Vol 31 (3) ◽  
pp. 583-598 ◽  
Author(s):  
Pavlos Kollias ◽  
Ieng Jo ◽  
Paloma Borque ◽  
Aleksandra Tatarevic ◽  
Katia Lamer ◽  
...  
Keyword(s):  
Data Quality ◽  
Wind Profile ◽  
Pulse Repetition Frequency ◽  
Dimensional Structure ◽  
Horizontal Wind ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
Wind Measurements ◽  
Atmospheric Radiation Measurement ◽  
High Pulse

Abstract The scanning Atmospheric Radiation Measurement (ARM) Program cloud radars (SACRs) are the primary instruments for documenting the four-dimensional structure and evolution of clouds within a 20–30-km radius of the ARM fixed and mobile sites. Here, the postprocessing of the calibrated SACR measurements is discussed. First, a feature mask algorithm that objectively determines the presence of significant radar returns is described. The feature mask algorithm is based on the statistical properties of radar receiver noise. It accounts for atmospheric emission and is applicable even for SACR profiles with few or no signal-free range gates. Using the nearest-in-time atmospheric sounding, the SACR radar reflectivities are corrected for gaseous attenuation (water vapor and oxygen) using a line-by-line absorption model. Despite having a high pulse repetition frequency, the SACR has a narrow Nyquist velocity limit and thus Doppler velocity folding is commonly observed. An unfolding algorithm that makes use of a first guess for the true Doppler velocity using horizontal wind measurements from the nearest sounding is described. The retrieval of the horizontal wind profile from the hemispherical sky range–height indicator SACR scan observations and/or nearest sounding is described. The retrieved horizontal wind profile can be used to adaptively configure SACR scan strategies that depend on wind direction. Several remaining challenges are discussed, including the removal of insect and second-trip echoes. The described algorithms significantly enhance SACR data quality and constitute an important step toward the utilization of SACR measurements for cloud research.

scholarly journals Doppler wind lidar activities at Cabauw

2021 ◽  
Author(s):  
Steven Knoop ◽  
Fred Bosveld ◽  
Marijn de Haij ◽  
Arnoud Apituley
Keyword(s):  
Wind Speed ◽  
Wind Profile ◽  
Continuous Wave ◽  
Wind Farms ◽  
Data Availability ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Low Clouds ◽  
Wind Measurements ◽  
Wind Lidar

<p>Atmospheric motion and turbulence are essential parameters for weather and topics related to air quality. Therefore, wind profile measurements play an important role in atmospheric research and meteorology. One source of wind profile data are Doppler wind lidars, which are laser-based remote sensing instruments that measure wind speed and wind direction up to a few hundred meters or even a few kilometers. Commercial wind lidars use the laser wavelength of 1.5 µm and therefore backscatter is mainly from aerosols while clear air backscatter is minimal, limiting the range to the boundary layer typically.</p><p>We have carried out a two-year intercomparison of the ZephIR 300M (ZX Lidars) short-range wind lidar and tall mast wind measurements at Cabauw [1]. We have focused on the (height-dependent) data availability of the wind lidar under various meteorological conditions and the data quality through a comparison with in situ wind measurements at several levels in the 213m tall meteorological mast. We have found an overall availability of quality-controlled wind lidar data of 97% to 98 %, where the missing part is mainly due to precipitation events exceeding 1 mm/h or fog or low clouds below 100 m. The mean bias in the horizontal wind speed is within 0.1 m/s with a high correlation between the mast and wind lidar measurements, although under some specific conditions (very high wind speed, fog or low clouds) larger deviations are observed. This instrument is being deployed within North Sea wind farms.</p><p>Recently, a scanning long-range wind lidar Windcube 200S (Leosphere/Vaisala) has been installed at Cabauw, as part of the Ruisdael Observatory program [2]. The scanning Doppler wind lidars will provide detailed measurements of the wind field, aerosols and clouds around the Cabauw site, in coordination with other instruments, such as the cloud radar.</p><p>[1] Knoop, S., Bosveld, F. C., de Haij, M. J., and Apituley, A.: A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw, Atmos. Meas. Tech., 14, 2219–2235, 2021</p><p>[2] https://ruisdael-observatory.nl/</p>

scholarly journals Algorithms for Doppler Spectral Density Data Quality Control and Merging for the Ka-Band Solid-State Transmitter Cloud Radar

2019 ◽  
Vol 11 (2) ◽  
pp. 209 ◽  
Author(s):  
Liping Liu ◽  
Jiafeng Zheng
Keyword(s):  
Spectral Density ◽  
Data Quality ◽  
Pulse Compression ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
Density Data ◽  
Cloud Radar ◽  
Coherent Integration ◽  
Reflectivity Spectra ◽  
The Individual

The Chinese Ka-band solid-state transmitter cloud radar (CR) can operate in three different work modes with different pulse widths and coherent integration and non-coherent integration numbers to meet the requirement for long-term cloud measurements. The CR was used to observe cloud and precipitation data in southern China in 2016. In order to resolve the data quality problems caused by coherent integration and pulse compression, which are used to detect weak cloud in the cloud radar, this study focuses on analyzing the consistencies of reflectivity spectra using the three modes and the influence of coherent integration and pulse compression, developing an algorithm for Doppler spectral density data quality control (QC) and merging based on multiple-mode observation data. After dealiasing Doppler velocity and artefact removal, the three types of Doppler spectral density data were merged. Then, Doppler moments such as reflectivity, radial velocity, and spectral width were recalculated from the merged reflectivity spectra. Performance of the merging algorithm was evaluated. Three conclusions were drawn. Firstly, four rounds of coherent integration with a pulse repetition frequency (PRF) of 8333 Hz underestimated the reflectivity spectra for Doppler velocities exceeding 2 m·s−1, causing a large negative bias in the reflectivity and radial velocity when large drops were present. In contrast, two rounds of coherent integration affected the reflectivity spectra to a lesser extent. The reflectivity spectra were underestimated for low signal-to-noise ratios in the low-sensitivity mode. Secondly, pulse compression improved the radar sensitivity and air vertical speed observation, whereas the precipitation mode and coherent integration led to an underestimation of the number concentration of big raindrops and an overestimation of the number concentration of small drops. Thirdly, a comparison of the individual spectra with the merged reflectivity spectra showed that the Doppler moments filled in the gaps in the individual spectra during weak cloud periods, reduced the effects of coherent integration and pulse compression in liquid precipitation, mitigated the aliasing of Doppler velocity, and removed the artefacts, yielding a comprehensive and accurate depiction of most of the clouds and precipitation in the vertical column above the radar. The recalculated moments of the Doppler spectra had better quality than those merged from raw data.

scholarly journals Intercomparison of middle-atmospheric wind in observations and models

2018 ◽  
Vol 11 (4) ◽  
pp. 1971-1987 ◽  
Author(s):  
Rolf Rüfenacht ◽  
Gerd Baumgarten ◽  
Jens Hildebrand ◽  
Franziska Schranz ◽  
Vivien Matthias ◽  
...  
Keyword(s):  
Wind Profile ◽  
Microwave Radiometer ◽  
Horizontal Wind ◽  
Random Errors ◽  
Good Correspondence ◽  
Mesopause Region ◽  
Wind Speeds ◽  
Wind Measurements ◽  
Remote Sensing Techniques

Abstract. Wind profile information throughout the entire upper stratosphere and lower mesosphere (USLM) is important for the understanding of atmospheric dynamics but became available only recently, thanks to developments in remote sensing techniques and modelling approaches. However, as wind measurements from these altitudes are rare, such products have generally not yet been validated with (other) observations. This paper presents the first long-term intercomparison of wind observations in the USLM by co-located microwave radiometer and lidar instruments at Andenes, Norway (69.3∘ N, 16.0∘ E). Good correspondence has been found at all altitudes for both horizontal wind components for nighttime as well as daylight conditions. Biases are mostly within the random errors and do not exceed 5–10 m s−1, which is less than 10 % of the typically encountered wind speeds. Moreover, comparisons of the observations with the major reanalyses and models covering this altitude range are shown, in particular with the recently released ERA5, ECMWF's first reanalysis to cover the whole USLM region. The agreement between models and observations is very good in general, but temporally limited occurrences of pronounced discrepancies (up to 40 m s−1) exist. In the article's Appendix the possibility of obtaining nighttime wind information about the mesopause region by means of microwave radiometry is investigated.

scholarly journals Evaluation of gridded scanning ARM cloud radar reflectivity observations and vertical doppler velocity retrievals

2014 ◽  
Vol 7 (4) ◽  
pp. 1089-1103 ◽  
Author(s):  
K. Lamer ◽  
A. Tatarevic ◽  
I. Jo ◽  
P. Kollias
Keyword(s):  
Great Plains ◽  
Spatial Scales ◽  
Domain Size ◽  
Horizontal Wind ◽  
Cape Cod ◽  
Doppler Velocity ◽  
Cloud Radar ◽  
Stratiform Clouds ◽  
Atmospheric Observations ◽  
Atmospheric Radiation Measurement

Abstract. The scanning Atmospheric Radiation Measurement (ARM) cloud radars (SACRs) provide continuous atmospheric observations aspiring to capture the 3-D cloud-scale structure. Sampling clouds in 3-D is challenging due to their temporal–spatial scales, the need to sample the sky at high elevations and cloud radar limitations. Thus, a suggested scan strategy is to repetitively slice the atmosphere from horizon to horizon as clouds advect over the radar (Cross-Wind Range-Height Indicator – CW-RHI). Here, the processing and gridding of the SACR CW-RHI scans are presented. First, the SACR sample observations from the ARM Southern Great Plains and Cape Cod sites are post-processed (detection mask, gaseous attenuation correction, insect filtering and velocity de-aliasing). The resulting radial Doppler moment fields are then mapped to Cartesian coordinates with time as one of the dimensions. Next the Cartesian-gridded Doppler velocity fields are decomposed into the horizontal wind velocity contribution and the vertical Doppler velocity component. For validation purposes, all gridded and retrieved fields are compared to collocated zenith-pointing ARM cloud radar measurements. We consider that the SACR sensitivity loss with range, the cloud type observed and the research purpose should be considered in determining the gridded domain size. Our results also demonstrate that the gridded SACR observations resolve the main features of low and high stratiform clouds. It is established that the CW-RHI observations complemented with processing techniques could lead to robust 3-D cloud dynamical representations up to 25–30 degrees off zenith. The proposed gridded products are expected to advance our understanding of 3-D cloud morphology, dynamics and anisotropy and lead to more realistic 3-D radiative transfer calculations.

scholarly journals Improved Doppler Velocity Dealiasing for Radar Data Assimilation and Storm-Scale Vortex Detection

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Qin Xu ◽  
Kang Nai ◽  
Shun Liu ◽  
Chris Karstens ◽  
Travis Smith ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Data Quality ◽  
Radar Data ◽  
Quality Standard ◽  
Second Step ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
High Data ◽  
Data Coverage ◽  
Radar Data Assimilation

The Doppler velocity dealiasing technique based on alias-robust VAD and variational (AR-Var) analyses developed at the National Severe Storms Laboratory for radar data quality control and assimilation is further improved in its two-step procedures: the reference check in the first step and the continuity check in the second step. In the first step, the alias-robust variational analysis is modified adaptively and used in place of the alias-robust velocity-azimuth display (VAD) analysis for all scan modes (rather than solely the WSR-88D volume coverage pattern 31 with the Nyquist velocityvNreduced below 12 m s−1and the TDWR Mod80 withvNreduced below 15 m s−1), so more raw data can pass the stringent threshold conditions used by the reference check in the first step. This improves the dealiased data coverage without false dealiasing to better satisfy the high data quality standard required by radar data assimilation. In the second step, new procedures are designed and added to the continuity check to increase the dealiased data coverage over storm-scale areas threatened by intense mesocyclones and their generated tornados. The performances of the improved dealiasing technique versus the existing techniques are exemplified by the results obtained for tornadic storms scanned by the operational KTLX radar in Oklahoma.

scholarly journals Validation of middle-atmospheric wind in observations and models

2017 ◽  
Author(s):  
Rolf Rüfenacht ◽  
Gerd Baumgarten ◽  
Jens Hildebrand ◽  
Franziska Schranz ◽  
Vivien Matthias ◽  
...  
Keyword(s):  
Wind Profile ◽  
Microwave Radiometer ◽  
Horizontal Wind ◽  
Random Errors ◽  
Good Correspondence ◽  
Mesopause Region ◽  
Wind Speeds ◽  
Wind Measurements ◽  
Remote Sensing Techniques

Abstract. Wind profile information throughout the upper stratosphere and lower mesosphere (USLM) is important for the understanding of atmospheric dynamics but became available only recently, thanks to developments in remote sensing techniques and modelling approaches. However, as wind measurements from these altitudes are still very rare, such products have generally not yet been validated with (other) observations. This paper presents the first long-term intercomparison of wind observations in the USLM by opposing co-located microwave radiometer and lidar instruments at Andenes (69.3° N, 16.0° E). Good correspondence has been found at all altitudes for both horizontal wind components for nighttime as well as daylight conditions. Biases are mostly within the random errors and do not exceed 5–10 m/s which is less than 10 % of the typically encountered wind speeds. Moreover, comparisons of the observations with the major re-analyses and models covering this altitude range are shown, especially also with the freshly released ERA5, ECMWF's first re-analysis to cover the whole USLM region. The agreement between models and observations is very good in general, but temporally limited occurrences of pronounced discrepancies (up to 40 m/s) exist. In the article's appendix the possibility of obtaining nighttime wind information about the mesopause region by means of microwave radiometry is investigated.

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