the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Jan 2024
ZJU-AERO V0.5: An Accurate and Efficient Radar Operator Designed for CMA-GFS/MESO with Capability of Simulating Non-spherical Hydrometeors
Abstract. In this study, we present a new forward polarimetric radar operator called the Accurate and Efficient Radar Operator designed by ZheJiang University (ZJU-AERO). This operator was designed to interface with the numerical weather prediction (NWP) model of the global forecast system/regional mesoscale model of the China Meteorology Administration (CMA-GFS/MESO). The main objective of developing this observation operator was to assimilate observations from the Precipitation Measurement Radar (PMR) and ground-based radar’s polarimetric radar variables, excluding the Doppler variables. To calculate the hydrometeor optical properties of ZJU-AERO, we utilized the invariant-imbedding T-matrix (IITM) method, which can handle non-spherical and inhomogeneous hydrometeor particles in the atmosphere. The optical database of ZJU-AERO was designed with a multi-layered architecture to ensure the flexibility in hydrometeor morphology and orientation specifications, while maintaining operational efficiency. In this work, we elaborate on the design concepts, physical basis, and hydrometeor specifications of ZJU-AERO. Additionally, we present a case study demonstrating the application of ZJU-AERO in simulating radar observations of Typhoon Haishen.
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RC1: 'Comment on gmd-2023-225', Anonymous Referee #1, 01 Feb 2024
Review comments on “ZJU-AERO V0.5: An Accurate and Efficient Radar Operator Designed for CMA-GFS / MESO with Capability of Simulating Non-spherical Hydrometeors” by Xie et al., (2024)
Summary:
Radar forward operators transform the model’s prognostic variables to the observed radar variables and are crucial tools in a number of applications including model evaluation, retrieval development, and data assimilation. The manuscript presents a newly developed radar forward operator based on the T-matrix method for calculating scattering amplitudes. The radar forward operator uses a non-spheroid hydrometeor model, namely the Chebyshev-shaped model to characterize the raindrops. The difference between the Chebyshev-shaped model and the spheroid model for calculating raindrop radar variables was compared in different single-moment (SM) schemes. However, the effect of the Chebyshev-shaped model on radar variables may only be notable in the presence of extremely large raindrops.
Overall, the topic of the manuscript is scientifically interesting and relevant. The presentation of the paper is reasonably good. The writing quality is fine and clear. I do have several comments below which I think translate into a recommendation for major revisions. I do not think there is anything fundamentally wrong with the manuscript, but considerable clarification on some points is needed as well as an expansion of the case results on polarimetric radar variables.
Major comments:
- 1. In the ABSTRACT and INTRODUCTION, the authors claimed the main purpose of developing this radar forward operator is to assimilate the polarimetric radar variables. However, it is not clarified in what follows that the operator has the potential to be able to be used for assimilating polarimetric radar. For the data assimilation purpose, the simplicity and efficiency of the radar forward operator are necessary. How computationally efficient is this radar forward operator? The variational method requires the tangent linear (TL) and adjoint (AD) operators, so whether this complex forward operator can be easily linearized. If the goal is to use it for data assimilation, then the manuscript needs to include sufficient discussion about the relevant aspects (advantages, limitations, and alternatives) of the radar forward operator.
- In section 3.4, six SM microphysics schemes are used to explore the effects of different PSD schemes on the simulation of radar variables. It is not clear why the authors chose these six SM microphysics schemes. The shortcomings of the SM microphysics scheme are obvious in reproducing polarimetric features observed in convective storms and stratiform events. Although the SM microphysics scheme has been used for years and will continue to be used, the authors should clarify this point. Also, it is not clear that there are six schemes in Figure 11, while there are only five schemes in Figure 12 and three schemes in Figure 13. Based on the statistics in Figure 16, it seems that the Thompson or ThompsonTuned scheme has the best simulation results, and of course, the authors present only the results of the ThompsonTuned scheme in Figures 14 and 15. This is also clearly demonstrated in Figure 11. Therefore, is it necessary to evaluate other SM microphysics schemes?
- The authors describe a forward operator that can simulate ground-based and space-borne polarimetric radar observations, but only show the observation and simulation of the Ku-band radar reflectivity in the case study. This is clearly insufficient for proving the reliability of the forward operator. Simulated polarimetric radar variables (such as differential reflectivity, specific differential phase, and Co-polar correlation coefficient) should also be shown.
- There are some concerns about the value of introducing the Chebyshev-shaped model for raindrops. In Figure 13, it is shown that the ZDR simulated by the Chebyshev-shaped model and the spherical model in the Thompson scheme only show a pronounced difference when the liquid water content is larger, and the differences in the other radar variables are very small. Figure 16 shows that the Chebyshev-shaped model and the spherical model have the same simulation distributions on radar reflectivity. It’s not clear if ZDR would have a different result. This goes back to the previous comment. In addition, whether there would be a difference between the Chebyshev-shaped model and the spherical model if the statistics were performed at different locations of the typhoon.
Minor comment:
- Title: I suggest that the name of the operator would be used the words that more objectively, characterized the operator, instead of some subjective adjectives like “accurate and efficient”.
- L17: which the Doppler variables are meant here?
- L125: Qh (hail) is included in Figure 2, but not here. Please be consistent.
- L195: “…undergone sufficient discussions in other works concerning radar operators, and we just inherited those settings and options from them”, pleas add specific references.
- L229: Z and K are very critical variables, and their specific definitions should be given.
- (5): It is suggested that Zh and Zv be separated into two formulas. The plus and minus signs are very confusing here.
- L398: “…incident radar beam and OZL This alignment sets the azimuthal…” should be “…incident radar beam and OZL. This alignment sets the azimuthal…”
- L411: How to determine if a particle is axial symmetry in the program.
- L456: “It is apprarent” should be “It is apparent”?
- L564: Why use a constant air density instead of diagnostic air density. Air density decreases with increasing altitude, it also changes with variations in pressure, temperature, and humidity.
- L684: Why does not it show the temperature profile? There is no temperature profile how to determine the altitude of freezing level.
- L686: It is difficult to see the features of the melting layer in Figure 15a and b.
- L690-692: This may be due to the operator not considering melting or mixed-phased particles, and the shortcoming of the microphysics scheme.
- Figure 15: It is suggested to add temperature profile.
- The SUMMARY is not sufficient.
Citation: https://doi.org/10.5194/gmd-2023-225-RC1 - AC1: 'Reply on RC1', Lei Bi, 17 Mar 2024
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RC2: 'Comment on gmd-2023-225', Anonymous Referee #2, 14 Feb 2024
he paper presents the radar forward operator ZJU-AERO that is capable of simulating radar observables for both ground-based and air-/spaceborne sensors and of considering effects of non-spherical, non-homogeneous hydrometeors incuding polarimetry, designed particularly for use along with the Chinese Meteorology Administration’s numerical weather prediction models. A larger fraction of the paper deals with evaluation of the Chebyshev shape model for rain suggested by Chuang and Beard (1990) compared to more classical spheroid models.
In general, this topic is suitable for publication in GMD. However, the paper “oscillates” between some very basic, textbook-like descriptions entangled with some quite specific, not always relevant details, but lacking clear direction and clarity and detail at places where it would start to be really interesting. I suggest publication to be considered after major revisions.
Please find my detailed review report attached.
- AC2: 'Reply on RC2', Lei Bi, 17 Mar 2024
Data sets
Example Case Data of Forward Radar Operator ZJU-AERO Release V0.5.0 Hejun Xie, Lei Bi, and Wei Han https://doi.org/10.5281/zenodo.10058324
Model code and software
An Accurate and Efficient Radar Operator Designed for CMA-GFS / MESO with Capability of Simulating Non-spherical Hydrometeors Hejun Xie, Lei Bi, and Wei Han https://doi.org/10.5281/zenodo.10058181
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