Retrieval of ice cloud properties with a dual frequency optimal estimation algorithm for terahertz and millimeter wave cloud radar

2021 ◽  
Author(s):  
X. Ding ◽  
J. Xu ◽  
Q. Chen ◽  
C. Fu ◽  
L. Ni
Keyword(s):  
Millimeter Wave ◽  
Optimal Estimation ◽  
Estimation Algorithm ◽  
Dual Frequency ◽  
Ice Cloud ◽  
Cloud Radar ◽  
Cloud Properties

scholarly journals Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 2. Retrieval evaluation

2016 ◽  
Vol 121 (10) ◽  
pp. 5827-5845 ◽  
Author(s):  
Chenxi Wang ◽  
Steven Platnick ◽  
Zhibo Zhang ◽  
Kerry Meyer ◽  
Gala Wind ◽  
...  
Keyword(s):  
Optimal Estimation ◽  
Estimation Algorithm ◽  
Infrared Observations ◽  
Ice Cloud ◽  
Cloud Properties

scholarly journals Precipitating Snow Retrievals from Combined Airborne Cloud Radar and Millimeter-Wave Radiometer Observations

2008 ◽  
Vol 47 (6) ◽  
pp. 1634-1650 ◽  
Author(s):  
Mircea Grecu ◽  
William S. Olson
Keyword(s):  
Field Experiment ◽  
Millimeter Wave ◽  
Synthetic Data ◽  
Optimal Estimation ◽  
Physical Models ◽  
Retrieval Algorithm ◽  
The Sea Of Japan ◽  
Cloud Radar ◽  
Cloud Resolving Model ◽  
Millimeter Wave Radiometer

Abstract An algorithm for retrieving snow over oceans from combined cloud radar and millimeter-wave radiometer observations is developed. The algorithm involves the use of physical models to simulate cloud radar and millimeter-wave radiometer observations from basic atmospheric variables such as hydrometeor content, temperature, and relative humidity profiles and is based on an optimal estimation technique to retrieve these variables from actual observations. A high-resolution simulation of a lake-effect snowstorm by a cloud-resolving model is used to test the algorithm. That is, synthetic observations are generated from the output of the cloud numerical model, and the retrieval algorithm is applied to the synthetic data. The algorithm performance is assessed by comparing the retrievals with the reference variables used in synthesizing the observations. The synthetic observation experiment indicates good performance of the retrieval algorithm. The algorithm is also applied to real observations from the Wakasa Bay field experiment that took place over the Sea of Japan in January and February 2003. The application of the retrieval algorithm to data from the field experiment yields snow estimates that are consistent with both the cloud radar and radiometer observations.

scholarly journals The Characterization of Ice Cloud Properties from Doppler Radar Measurements

2007 ◽  
Vol 46 (10) ◽  
pp. 1682-1698 ◽  
Author(s):  
Julien Delanoë ◽  
A. Protat ◽  
D. Bouniol ◽  
Andrew Heymsfield ◽  
Aaron Bansemer ◽  
...  
Keyword(s):  
Water Content ◽  
Weather Prediction ◽  
Doppler Velocity ◽  
Fall Velocity ◽  
Ice Cloud ◽  
Cloud Radar ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Radar Measurements ◽  
Ice Water

Abstract The paper describes an original method that is complementary to the radar–lidar algorithm method to characterize ice cloud properties. The method makes use of two measurements from a Doppler cloud radar (35 or 95 GHz), namely, the radar reflectivity and the Doppler velocity, to recover the effective radius of crystals, the terminal fall velocity of hydrometeors, the ice water content, and the visible extinction from which the optical depth can be estimated. This radar method relies on the concept of scaling the ice particle size distribution. An error analysis using an extensive in situ airborne microphysical database shows that the expected errors on ice water content and extinction are around 30%–40% and 60%, respectively, including both a calibration error and a bias on the terminal fall velocity of the particles, which all translate into errors in the retrieval of the density–diameter and area–diameter relationships. Comparisons with the radar–lidar method in areas sampled by the two instruments also demonstrate the accuracy of this new method for retrieval of the cloud properties, with a roughly unbiased estimate of all cloud properties with respect to the radar–lidar method. This method is being systematically applied to the cloud radar measurements collected over the three-instrumented sites of the European Cloudnet project to validate the representation of ice clouds in numerical weather prediction models and to build a cloud climatology.

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.

scholarly journals Retrieval of cloud properties from spectral zenith radiances observed by sky radiometers

2019 ◽  
Vol 12 (11) ◽  
pp. 6037-6047 ◽  
Author(s):  
Pradeep Khatri ◽  
Hironobu Iwabuchi ◽  
Tadahiro Hayasaka ◽  
Hitoshi Irie ◽  
Tamio Takamura ◽  
...  
Keyword(s):  
Optimal Estimation ◽  
Estimation Algorithm ◽  
Calibration Procedure ◽  
Evaluation Study ◽  
Vapor Concentration ◽  
Observation Data ◽  
Ancillary Data ◽  
Cloud Particle ◽  
Cloud Optical Depth ◽  
Cloud Properties

Abstract. An optimal estimation algorithm to retrieve the cloud optical depth (COD) and cloud particle effective radius (CER) from spectral zenith radiances observed by narrow field-of-view (FOV) ground-based sky radiometers was developed. To further address the filter degradation problem while analyzing long-term observation data, an on-site calibration procedure is proposed, which has good accuracy compared with the standard calibration transfer method. An error evaluation study conducted by assuming errors in observed transmittances and ancillary data for water vapor concentration and surface albedo suggests that the errors in input data affect retrieved CER more than COD. Except for some narrow domains that fall within a COD of < 15, the retrieval errors are small for both COD and CER. The retrieved cloud properties reproduce the broadband radiances observed by a narrow FOV radiometer more precisely than broadband irradiances observed by a wide-FOV pyranometer, justifying the quality of the retrieved product (at least of COD) and indicating the important effect of the instrument FOV in cloud remote sensing. Furthermore, CODs (CERs) from sky radiometer and satellite observations show good (poor) agreement.

scholarly journals Research on 5G Millimeter Wave Channel Estimation Algorithm

2019 ◽  
pp. 74-77
Author(s):  
Xu Shuang
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Large Scale ◽  
Low Frequency ◽  
Estimation Algorithm ◽  
Simulation Research ◽  
Wave Technology ◽  
Wave Channel ◽  
Mimo Technology

With the explosive growth in the number of communication users and the huge demand for data from users, Limited low-frequency resources have been far from being satisfied by users. The combination of Massive MIMO technology and millimeter-wave technology has brought new hope to users. In this paper, several basic algorithms are placed under the millimeter wave large-scale antenna channel for simulation research.

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