the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 22 Sep 2022
Simulation and sensitivity analysis for cloud and precipitation measurements via spaceborne millimeter wave radar
Abstract. This study presents a simulation framework for cloud and precipitation measurements via spaceborne millimeter wave radar composed of nine sub modules. To demonstrate the influence of the assumed physical parameters and optimizing the microphysical modeling of the hydrometeors, we first conducted a sensitivity analysis. The results indicated that the radar reflectivity was highly sensitive to the particle size distribution (PSD) parameter of the median volume diameter and particle density parameter, which can cause reflectivity variations of several to more than 10 dB. The variation in the prefactor of the mass-power relations that related to riming degree may result in an uncertainty of approximately 30–45 %. The particle shape and orientation also had a significant impact on the radar reflectivity. The spherical assumption may result in an average overestimation of the reflectivity by approximately 4–8 %, dependent on the particle shape and orientation modeling. Typical weather cases were simulated using optimal physical modeling accounting for the particle shapes, typical PSD parameters corresponding to the cloud precipitation types, mass-power relations for snow and graupel, and melting modeling. We present and validate the simulation results for a cold front stratiform cloud and a deep convective process with observations from W-band cloud profiling radar (CPR) on the CloudSat satellite. The simulated brightness band features, echo structure, and intensity showed good agreement with the CloudSat observations; the average relative error in the vertical profile was within 20 %. Our results quantify the uncertainty in the millimeter wave radar echo simulation that may be caused by the physical model parameters and provide a scientific basis for optimal forward modeling. They also provide suggestions for prior physical parameter constraints for the retrieval of the microphysical properties of clouds and precipitation.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(2952 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- BibTeX
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-886', Anonymous Referee #1, 03 Nov 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-886/egusphere-2022-886-RC1-supplement.pdf
- AC1: 'Reply on RC1', Leilei Kou, 13 Dec 2022
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RC2: 'Comment on egusphere-2022-886', Anonymous Referee #2, 03 Nov 2022
Please see the attached PDF for my detailed overall comments and line-specific comments.
Note that for some reason, the preview of my revies is indicating I'm not willing to review the revised manuscript. This is incorrect, I *am* willing to review the revised manuscript.
This is a review of Kou et al., "Simulation and sensitivity analysis for cloud
and precipitation measurements via spaceborne millimeter wave radar". The
authors evaluate the sensitivity of a forward model for radar reflectivity to
its microphysical input variables. The forward model includes cloud ice and
water, melting mixed-phase precipitation, snow, graupel and rain. They then
perform comparisons of reflectivities that are forward modeled for two WRF
simulations (one stratiform and one convective event) against CloudSat
observations of the same events. They find in particular that including radar
attenuation in the forward model gives improved results over a forward model
without attenuation.Overall, this seems to be a concise and well-executed study. The conclusion
that including attenuation in the forward model is necessary for reproducing
W-band reflectivities in precipitation that includes melting and liquid phases is
not surprising. Perhaps more surprising is that such good agreement was
achieved in the comparisons of reflectivities between the WRF simulations and
the CloudSat observations. It appears that the model fields were selected
from the exact groundtrack and the exact time of the CloudSat overpass. It's
unusual, I think, for model features, particularly precipitation, to be so
well-located with the observations.I think the study is a useful contribution to the precipitation retrieval
literature. My overall comments relate to how the sensitivity perturbations
were defined and how the WRF simulations were configured. Most significant is
whether the assessment of uncertainties due to particle shape and orientation
is sufficient. I'd like to see this addressed in revision. My specific
comments are more extensive and touch mainly on unclear language and missing
details. Because they are extensive, I am calling the necessary revisions
"major".I think that with revision, the paper can be acceptable for publication. For
this current revision, the scientific significance is good, the scientific
quality is fair but this is difficult to judge due to the presentation. The
presentation quality is fair.- AC2: 'Reply on RC2', Leilei Kou, 13 Dec 2022
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-886', Anonymous Referee #1, 03 Nov 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-886/egusphere-2022-886-RC1-supplement.pdf
- AC1: 'Reply on RC1', Leilei Kou, 13 Dec 2022
-
RC2: 'Comment on egusphere-2022-886', Anonymous Referee #2, 03 Nov 2022
Please see the attached PDF for my detailed overall comments and line-specific comments.
Note that for some reason, the preview of my revies is indicating I'm not willing to review the revised manuscript. This is incorrect, I *am* willing to review the revised manuscript.
This is a review of Kou et al., "Simulation and sensitivity analysis for cloud
and precipitation measurements via spaceborne millimeter wave radar". The
authors evaluate the sensitivity of a forward model for radar reflectivity to
its microphysical input variables. The forward model includes cloud ice and
water, melting mixed-phase precipitation, snow, graupel and rain. They then
perform comparisons of reflectivities that are forward modeled for two WRF
simulations (one stratiform and one convective event) against CloudSat
observations of the same events. They find in particular that including radar
attenuation in the forward model gives improved results over a forward model
without attenuation.Overall, this seems to be a concise and well-executed study. The conclusion
that including attenuation in the forward model is necessary for reproducing
W-band reflectivities in precipitation that includes melting and liquid phases is
not surprising. Perhaps more surprising is that such good agreement was
achieved in the comparisons of reflectivities between the WRF simulations and
the CloudSat observations. It appears that the model fields were selected
from the exact groundtrack and the exact time of the CloudSat overpass. It's
unusual, I think, for model features, particularly precipitation, to be so
well-located with the observations.I think the study is a useful contribution to the precipitation retrieval
literature. My overall comments relate to how the sensitivity perturbations
were defined and how the WRF simulations were configured. Most significant is
whether the assessment of uncertainties due to particle shape and orientation
is sufficient. I'd like to see this addressed in revision. My specific
comments are more extensive and touch mainly on unclear language and missing
details. Because they are extensive, I am calling the necessary revisions
"major".I think that with revision, the paper can be acceptable for publication. For
this current revision, the scientific significance is good, the scientific
quality is fair but this is difficult to judge due to the presentation. The
presentation quality is fair.- AC2: 'Reply on RC2', Leilei Kou, 13 Dec 2022
Peer review completion
Journal article(s) based on this preprint
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Leilei Kou
Zhengjian Lin
Haiyang Gao
Shujun Liao
Piman Ding
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2952 KB) - Metadata XML