Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Abstract. Pre-launch simulated data to be obtained from new sensors on a satellite is useful to develop retrieval algorithms and aid the rapid release of retrieval products after launch. Here we introduce Japanese Aerospace Exploration Agencies (JAXA) EarthCARE synthetic data based on simulations using a 3.5 km horizontal-mesh global storm-resolving model. Global aerosol transport simulation results are added for aerosol retrieval developers. Synthetic data were produced for four types of EarthCARE sensor: a 94 GHz cloud-profiling radar (CPR), a 355 nm atmospheric lidar (ATLID), a seven-channel multispectral imager (MSI), and a broadband radiometer (BBR). JAXA EarthCARE synthetic data include a standard product with data for two orbits and a research product with shorter frames and more detailed instrument settings. In the research products, random errors in the CPR are considered based on the observation window, and noise in ATLID signals are added using a noise simulator. We consider the spectral misalignment effect of the visible and near-infrared MSI channels based on response functions depending on the angle from nadir. We discuss plans for updating JAXA EarthCARE synthetic data using a large eddy simulation and implementation of a three-dimensional radiation model.
Woosub Roh et al.
Status: open (until 24 Mar 2023)
- RC1: 'Comment on amt-2023-18', Anonymous Referee #1, 22 Feb 2023 reply
- RC2: 'Comment on amt-2023-18', Anonymous Referee #2, 24 Mar 2023 reply
Woosub Roh et al.
Woosub Roh et al.
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Review of “Introduction to EarthCARE synthetic data using a global storm-resolving simulation” by Roh et al., submitted to Atmospheric Measurement Techniques (AMT)
This report contains general, major, and specific comments from this reviewer on the manuscript.
A summary of the manuscript and general assessment:
Recommendation: Major revision
This manuscript introduces synthetic level-1 (L1) data products of the EarthCARE space-borne instruments, which will be launched in a few years. The purpose of producing the data is to support the development of retrieval algorithms to create higher-level data products before the satellite observations start and the operational product release. The synthetic data was produced by simulating the satellite orbits and observations in the geophysical fields of global storm-resolving model simulation with a 3.5 km horizontal mesh. In addition, the distribution of aerosol concentrations, which was not included in the storm-resolving model simulation, was considered by implementing additional global aerosol transport simulation with a coarser horizontal mesh. The data products include standard one with two full orbits around the earth and research-mode one with a part of the orbits adding corrections in the satellite simulations, which imitate the observation products by the actual instruments more realistically.
The scope of the manuscript is within the main subject areas of AMT, specifically theoretical calculations of measurement simulations with detailed error analysis, including instrument simulations.
I suggest a major revision. I have no deep expertise in the measurements using each remote-sensing instrument. However, from such a perspective, the current manuscript needs to be improved for better readability and clearer points. In addition, the present descriptions of the data availability could be better because this manuscript aims to introduce and advance the use of the EarthCARE synthetic data by other engineers and researchers for retrieval algorithm development. I list major problems in the following section.
The abstract needs to be rewritten to meet the objectives of the manuscript. At least, related to the data availability, the information about how to get the data sets is necessary for the abstract.
The quality of the figures in the current discussion preprint could be better, although it might be degraded in the preprint production. Some specific comments for each figure can be found in the specific comments section.
The differences between the standard and research(-mode) products need to be presented in a more explicit format. Adding a table summarizing the differences may be helpful to show what is in or not in each product. The authors present some examples of the synthetic data products in the manuscript. However, which type of product is used to produce the examples and what are the differences in the case which type is used to make the examples need to be clarified.
Similar to algorithm development in other previous works, the original geophysical fields in the atmospheric simulations are expected to work as the true value in the validation of the result in applying the retrieval algorithm to the L1 data to get the L2 data. However, in this study, as long as I understand the process, the NICAM simulation with a 3.5 km horizontal mesh itself does not have aerosol direct effects on the atmospheric radiation in the simulated geophysical fields, and the NICAM-SPRINTARS simulation alternatively provides the spatial distribution of aerosol loading only in the process of creating the L1 data. This inconsistency could be an error in the L2 validation in the retrieval algorithms for the L1 data, specifically BBR. The NICAM simulation has no aerosol direct effects, so there is no true value.
The data sharing needs to be improved, given the scope and objectives of the manuscript. Although the traditional “upon request” may be acceptable in most research articles, this is not the case. AMT suggests the following data policy for handling data sets:
the deposit of research data (i.e. the material necessary to validate the research findings) that correspond to manuscripts, preprints, or journal articles in reliable FAIR-aligned data repositories that assign persistent identifiers (preferably digital object identifiers (DOIs)). Suitable repositories can be found at https://www.re3data.org/;
the proper citation of data sets in the text and the reference list including the persistent identifier. For data sets hosted on GitHub, authors are kindly asked to issue a DOI through Zenodo and include this DOI in the reference list;
the inclusion of a statement on how their underlying research data can be accessed. This must be placed in the section "Data availability" at the end of the manuscript before the acknowledgements. If the data are not publicly accessible, a detailed explanation of why this is the case is required (e.g. applicable laws, university and research institution policies, funder terms, privacy, intellectual property and licensing agreements, and the ethical context of the research);
the provision of unrestricted access to all data and materials underlying reported findings for which ethical or legal constraints do not apply.
The authors should follow the guidelines carefully. In addition, detailed information about the data sets, such as data size, data format, etc., should be included in the section or other parts of the manuscript.
Line 19: “discuss” should be “introduce”.
Line 71: I need clarification on the relationship between the NICAM simulation (Line 64) and the NICAM-SPRINTERS simulation. Was the NICAM-SPRINTERS simulation run separately from the NICAM simulation? The aerosol distribution simulated in the NICAM-SPRINTERS simulation was used for the JAXA L1 data only, and it was not used in the NICAM simulation with ~3.5 km grid spacing for calculating the atmospheric radiation (aerosol direct effects) and the aerosol-cloud interaction. Correct?
Line 75: Related to the comment above, if calculating aerosol particle radiative properties needs information on the ambient atmosphere, such as relative humidity, which simulation provides the information?
Figure 1: Is the color transition of the line consistent with the color bar on the right side of the figure? Purple is not included in the color bar.
Figure 2: Does the 3.5 km NICAM simulation also provide terrain heights and land/ocean/ice surface states, or is this information from other data sources?
Figure 3: This figure quality is very poor. It should have a higher dpi to be read. I cannot see which side of the color bars is negative. And which is the upward or downward direction positive vertically?
Figure 7: The figure quality is very poor again.
Line 229 and Figure 10: Which is the base? I mean, which is subtracted from the other?
Line 279: What this section does is not discussion. It should be renamed “future plans”, “future improvement”, or something.
Line 34: Remove “global”.
Line 178: “The attenuation of water clouds” => “The attenuation by water clouds”
Line 227: “1.67” => “1.65”