scholarly journals The NCAR airborne 94-GHz cloud radar: calibration and data processing

2021 ◽  
Author(s):  
Ulrike Romatschke ◽  
Michael Dixon ◽  
Peisang Tsai ◽  
Eric Loew ◽  
Jothiram Vivekanandan ◽  
...  
Keyword(s):  
Data Processing ◽  
Cloud Radar ◽  
Radar Calibration

scholarly journals Absolute calibration method for frequency-modulated continuous wave (FMCW) cloud radars based on corner reflectors

2020 ◽  
Vol 13 (12) ◽  
pp. 6853-6875
Author(s):  
Felipe Toledo ◽  
Julien Delanoë ◽  
Martial Haeffelin ◽  
Jean-Charles Dupont ◽  
Susana Jorquera ◽  
...  
Keyword(s):  
Field Experiments ◽  
Continuous Wave ◽  
Intermediate Frequency ◽  
Absolute Calibration ◽  
Experimental Setup ◽  
Cloud Radar ◽  
Calibration Uncertainty ◽  
Radar Calibration ◽  
The Impact ◽  
Uncertainty Source

Abstract. This article presents a new cloud radar calibration methodology using solid reference reflectors mounted on masts, developed during two field experiments held in 2018 and 2019 at the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA) atmospheric observatory, located in Palaiseau, France, in the framework of the Aerosol Clouds Trace gases Research InfraStructure version 2 (ACTRIS-2) research and innovation program. The experimental setup includes 10 and 20 cm triangular trihedral targets installed at the top of 10 and 20 m masts, respectively. The 10 cm target is mounted on a pan-tilt motor at the top of the 10 m mast to precisely align its boresight with the radar beam. Sources of calibration bias and uncertainty are identified and quantified. Specifically, this work assesses the impact of receiver compression, temperature variations inside the radar, frequency-dependent losses in the receiver's intermediate frequency (IF), clutter and experimental setup misalignment. Setup misalignment is a source of bias, previously undocumented in the literature, that can have an impact of the order of tenths of a decibel in calibration retrievals of W-band radars. A detailed analysis enabled the quantification of the importance of each uncertainty source to the final cloud radar calibration uncertainty. The dominant uncertainty source comes from the uncharacterized reference target which reached 2 dB. Additionally, the analysis revealed that our 20 m mast setup with an approximate alignment approach is preferred to the 10 m mast setup with the motor-driven alignment system. The calibration uncertainty associated with signal-to-clutter ratio of the former is 10 times smaller than for the latter. Following the proposed methodology, it is possible to reduce the added contribution from all uncertainty terms, excluding the target characterization, down to 0.4 dB. Therefore, this procedure should enable the achievement of calibration uncertainties under 1 dB when characterized reflectors are available. Cloud radar calibration results are found to be repeatable when comparing results from a total of 18 independent tests. Once calibrated, the cloud radar provides valid reflectivity values when sampling midtropospheric clouds. Thus, we conclude that the method is repeatable and robust, and that the uncertainties are precisely characterized. The method can be implemented under different configurations as long as the proposed principles are respected. It could be extended to reference reflectors held by other lifting devices such as tethered balloons or unmanned aerial vehicles.

scholarly journals Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration?

2019 ◽  
Vol 12 (6) ◽  
pp. 3151-3171 ◽  
Author(s):  
Maximilian Maahn ◽  
Fabian Hoffmann ◽  
Matthew D. Shupe ◽  
Gijs de Boer ◽  
Sergey Y. Matrosov ◽  
...  
Keyword(s):  
Radar Data ◽  
Reference Points ◽  
Radar Reflectivity ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Liquid Water Path ◽  
Cloud Radar ◽  
Microphysical Processes ◽  
Radar Calibration ◽  
Sudden Decrease

Abstract. Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Thus far, no single robust method exists for assessing the calibration of past cloud radar data sets. Here, we investigate whether observations of microphysical processes in liquid clouds such as the transition of cloud droplets to drizzle drops can be used to calibrate cloud radars. Specifically, we study the relationships between the radar reflectivity factor and three variables not affected by absolute radar calibration: the skewness of the radar Doppler spectrum (γ), the radar mean Doppler velocity (W), and the liquid water path (LWP). For each relation, we evaluate the potential for radar calibration. For γ and W, we use box model simulations to determine typical radar reflectivity values for reference points. We apply the new methods to observations at the Atmospheric Radiation Measurement (ARM) sites North Slope of Alaska (NSA) and Oliktok Point (OLI) in 2016 using two 35 GHz Ka-band ARM Zenith Radars (KAZR). For periods with a sufficient number of liquid cloud observations, we find that liquid cloud processes are robust enough for cloud radar calibration, with the LWP-based method performing best. We estimate that, in 2016, the radar reflectivity at NSA was about 1±1 dB too low but stable. For OLI, we identify serious problems with maintaining an accurate calibration including a sudden decrease of 5 to 7 dB in June 2016.

scholarly journals The NCAR Airborne 94-GHz Cloud Radar: Calibration and Data Processing

Data ◽  
2021 ◽  
Vol 6 (6) ◽  
pp. 66
Author(s):  
Ulrike Romatschke ◽  
Michael Dixon ◽  
Peisang Tsai ◽  
Eric Loew ◽  
Jothiram Vivekanandan ◽  
...  
Keyword(s):  
Radar Data ◽  
Reanalysis Data ◽  
Time Range ◽  
Cloud Radar ◽  
Elevation Data ◽  
Radar Echo ◽  
Western Caribbean ◽  
Radar Calibration ◽  
Terrain Elevation ◽  
Gain Errors

The 94-GHz airborne HIAPER Cloud Radar (HCR) has been deployed in three major field campaigns, sampling clouds over the Pacific between California and Hawaii (2015), over the cold waters of the Southern Ocean (2018), and characterizing tropical convection in the Western Caribbean and Pacific waters off Panama and Costa Rica (2019). An extensive set of quality assurance and quality control procedures were developed and applied to all collected data. Engineering measurements yielded calibration characteristics for the antenna, reflector, and radome, which were applied during flight, to produce the radar moments in real-time. Temperature changes in the instrument during flight affect the receiver gains, leading to some bias. Post project, we estimate the temperature-induced gain errors and apply gain corrections to improve the quality of the data. The reflectivity calibration is monitored by comparing sea surface cross-section measurements against theoretically calculated model values. These comparisons indicate that the HCR is calibrated to within 1–2 dB of the theory. A radar echo classification algorithm was developed to identify “cloud echo” and distinguish it from artifacts. Model reanalysis data and digital terrain elevation data were interpolated to the time-range grid of the radar data, to provide an environmental reference.

scholarly journals Absolute Calibration method for FMCW Cloud Radars

2020 ◽  
Author(s):  
Felipe Toledo ◽  
Julien Delanoë ◽  
Martial Haeffelin ◽  
Jean-Charles Dupont
Keyword(s):  
Field Experiments ◽  
Calibration Method ◽  
Absolute Calibration ◽  
Experimental Setup ◽  
Cloud Radar ◽  
Research And Innovation ◽  
W Band ◽  
Calibration Uncertainty ◽  
Radar Calibration ◽  
The Impact

Abstract. This article presents a new Cloud Radar calibration methodology using solid reference reflectors mounted on masts, developed during two field experiments held in 2018 and 2019 at the SIRTA atmospheric observatory, located in Palaiseau, France, in the framework of the ACTRIS-2 research and innovation program. The experimental setup includes 10 cm and 20 cm triangular trihedral targets installed at the top of 10 m and 20 m masts, respectively. The 10 cm target is mounted on a pan-tilt motor at the top of the 10 m mast to precisely align its boresight with the radar beam. Sources of calibration bias and uncertainty are identified and quantified. Specifically, this work assesses the impact of receiver compression, incomplete antenna overlap, temperature variations inside the radar, clutter and experimental setup misalignment. Setup misalignment is a source of bias previously undocumented in the literature, that can have an impact on the order of tenths of dB in calibration retrievals of W band Radars. A detailed analysis enabled the design of a calibration methodology which can reach a cloud radar calibration uncertainty of 0.3 dB based on the equipment used in the experiment. Among different sources of uncertainty, the two largest terms are due to signal-to-clutter ratio and radar-to-target alignment. The analysis revealed that our 20 m mast setup with an approximate alignment approach is preferred to the 10 m mast setup with the motor-driven alignment system. The calibration uncertainty associated with signal-to-clutter ratio of the former is ten times smaller than for the latter. Cloud radar calibration results are found to be repeatable when comparing results from a total of 18 independent tests. Once calibrated the cloud radar provides valid reflectivity values when sampling mid-tropospheric clouds. Thus we conclude that the method is repeatable and robust, and that the uncertainties are precisely characterized. The method can be implemented under different configurations as long as the proposed principles are respected. It could be extended to reference reflectors held by other lifting devices such as tethered balloons or unmanned aerial vehicles.

scholarly journals Can liquid cloud microphysical processes be used for vertically-pointing cloud radar calibration?

2019 ◽  
Author(s):  
Maximilian Maahn ◽  
Fabian Hoffmann ◽  
Matthew D. Shupe ◽  
Gijs de Boer ◽  
Sergey Y. Matrosov ◽  
...  
Keyword(s):  
Radar Data ◽  
Reference Points ◽  
Radar Reflectivity ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Liquid Water Path ◽  
Cloud Radar ◽  
Microphysical Processes ◽  
Radar Calibration ◽  
Sudden Decrease

Abstract. Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Thus far, no single, robust method exists for assessing calibration of past cloud radar data sets. Here, we investigate whether observations of microphysical processes of liquid clouds such as the transition of cloud droplets to drizzle drops can be used to calibrate cloud radars. Specifically, we study the relationships between the radar reflectivity factor and three variables not affected by absolute radar calibration: the skewness of the radar Doppler spectrum (γ), the radar mean Doppler velocity (W), and the liquid water path (LWP). We identify reference points of these relationships and evaluate their potential for radar calibration. For γ and W, we use box model simulations to determine typical radar reflectivity values for these reference points. We apply the new methods to observations at the Atmospheric Radiation Measurement (ARM) sites North Slope of Alaska (NSA) and Oliktok Point (OLI) in 2016 using two 35 GHz Ka-band ARM Zenith Radars (KAZR). For periods with a sufficient number of liquid cloud observations, we find that the methods are robust enough for cloud radar calibration, with the LWP-based method performing best. We estimate that in 2016, the radar reflectivity at NSA was about 1 ± 1 dB too low, but stable. For OLI, we identify serious problems with maintaining an accurate calibration including a sudden decrease of 5 to 7 dB in June 2016.

scholarly journals Assessment of Cloudsat Reflectivity Measurements and Ice Cloud Properties Using Ground-Based and Airborne Cloud Radar Observations

2009 ◽  
Vol 26 (9) ◽  
pp. 1717-1741 ◽  
Author(s):  
A. Protat ◽  
D. Bouniol ◽  
J. Delanoë ◽  
E. O’Connor ◽  
P. T. May ◽  
...  
Keyword(s):  
Multiple Scattering ◽  
Field Experiments ◽  
Weighted Mean Difference ◽  
Time Lag ◽  
Supercooled Liquid ◽  
Cloud Base ◽  
Ice Cloud ◽  
Cloud Radar ◽  
Cloud Properties ◽  
Radar Calibration

Abstract A quantitative assessment of Cloudsat reflectivities and basic ice cloud properties (cloud base, top, and thickness) is conducted in the present study from both airborne and ground-based observations. Airborne observations allow direct comparisons on a limited number of ocean backscatter and cloud samples, whereas the ground-based observations allow statistical comparisons on much longer time series but with some additional assumptions. Direct comparisons of the ocean backscatter and ice cloud reflectivities measured by an airborne cloud radar and Cloudsat during two field experiments indicate that, on average, Cloudsat measures ocean backscatter 0.4 dB higher and ice cloud reflectivities 1 dB higher than the airborne cloud radar. Five ground-based sites have also been used for a statistical evaluation of the Cloudsat reflectivities and basic cloud properties. From these comparisons, it is found that the weighted-mean difference ZCloudsat − ZGround ranges from −0.4 to +0.3 dB when a ±1-h time lag around the Cloudsat overpass is considered. Given the fact that the airborne and ground-based radar calibration accuracy is about 1 dB, it is concluded that the reflectivities of the spaceborne, airborne, and ground-based radars agree within the expected calibration uncertainties of the airborne and ground-based radars. This result shows that the Cloudsat radar does achieve the claimed sensitivity of around −29 dBZ. Finally, an evaluation of the tropical “convective ice” profiles measured by Cloudsat has been carried out over the tropical site in Darwin, Australia. It is shown that these profiles can be used statistically down to approximately 9-km height (or 4 km above the melting layer) without attenuation and multiple scattering corrections over Darwin. It is difficult to estimate if this result is applicable to all types of deep convective storms in the tropics. However, this first study suggests that the Cloudsat profiles in convective ice need to be corrected for attenuation by supercooled liquid water and ice aggregates/graupel particles and multiple scattering prior to their quantitative use.

The Karolinska Hospital Information System

1974 ◽  
Vol 13 (03) ◽  
pp. 125-140 ◽  
Author(s):  
Ch. Mellner ◽  
H. Selajstder ◽  
J. Wolodakski
Keyword(s):  
Information System ◽  
Data Processing ◽  
Data Base ◽  
Hospital Information System ◽  
Care Delivery ◽  
Traditional Approach ◽  
Processing System ◽  
Systems Design ◽  
Data Processing System ◽  
Karolinska Hospital

The paper gives a report on the Karolinska Hospital Information System in three parts.In part I, the information problems in health care delivery are discussed and the approach to systems design at the Karolinska Hospital is reported, contrasted, with the traditional approach.In part II, the data base and the data processing system, named T1—J 5, are described.In part III, the applications of the data base and the data processing system are illustrated by a broad description of the contents and rise of the patient data base at the Karolinska Hospital.

Data Screening Methods – Application to Differential Diagnosis in Pancreatic Pathology from Radiological Signs

1978 ◽  
Vol 17 (01) ◽  
pp. 36-40 ◽  
Author(s):  
J.-P. Durbec ◽  
Jaqueline Cornée ◽  
P. Berthezene
Keyword(s):  
Differential Diagnosis ◽  
Mutual Information ◽  
Data Processing ◽  
Screening Methods ◽  
Automatic Data ◽  
Chronic Calcifying Pancreatitis ◽  
Number Of Patients ◽  
Calcifying Pancreatitis ◽  
Pancreatic Pathology ◽  
Data Screening

The practice of systematic examinations in hospitals and the increasing development of automatic data processing permits the storing of a great deal of information about a large number of patients belonging to different diagnosis groups.To predict or to characterize these diagnosis groups some descriptors are particularly useful, others carry no information. Data screening based on the properties of mutual information and on the log cross products ratios in contingency tables is developed. The most useful descriptors are selected. For each one the characterized groups are specified.This approach has been performed on a set of binary (presence—absence) radiological variables. Four diagnoses groups are concerned: cancer of pancreas, chronic calcifying pancreatitis, non-calcifying pancreatitis and probable pancreatitis. Only twenty of the three hundred and forty initial radiological variables are selected. The presence of each corresponding sign is associated with one or more diagnosis groups.

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