the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
COSP-RTTOV-1.0: Flexible radiation diagnostics to enable new science applications in model evaluation, climate change detection, and satellite mission design
Abstract. Infrared spectral radiation fields observed by satellites make up an information-rich, multi-decade record with continuous coverage of the entire planet. As direct observations, spectral radiation fields are also largely free from uncertainties that accumulate during geophysical retrieval and data assimilation processes. Comparing these direct observations with earth system models (ESMs), however, is hindered by definitional differences between the radiation fields satellites observe and those generated by models. Here, we present a flexible, computationally efficient tool called COSP-RTTOV for simulating satellite-like radiation fields within ESMs. Outputs from COSP-RTTOV are consistent with instrument spectral response functions and orbit sampling, as well as the physics of the host model. After validating COSP-RTTOV's performance, we demonstrate new constraints on model performance enabled by COSP-RTTOV. We show additional applications in climate change detection using the NASA AIRS instrument, and observing system simulation experiments using the NASA PREFIRE mission. In summary, COSP-RTTOV is a convenient tool for directly comparing satellite radiation observations with ESMs. It enables a wide range of scientific applications, especially when users desire to avoid the assumptions and uncertainties inherent in satellite-based retrievals of geophysical variables or in atmospheric reanalysis.
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Status: open (until 14 Apr 2025)
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RC1: 'Comment on egusphere-2025-169', Anonymous Referee #1, 19 Mar 2025
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Review of “COSP-RTTOV-1.0: Flexible radiation diagnostics to enable new science applications in model evaluation, climate change detection, and satellite mission design” by J. K. Shaw et al.
This paper describes the development integration of the RTTOV radiative transfer code within COSP2, and presents a range of potential applications by using CESM2 as host model. The paper is well written and the content is adequate for publication in GMD. It provides a very valuable description of the new capabilities, including the satellite-like sampling patterns made available to all simulators within COSP. I particularly like Section 3, which covers a wide range of potential applications at the right level of detail for a paper documenting the new capabilities. Overall, I find the paper gives the reader an excellent overview of the potential of COSP-RTTOV for evaluation and climate studies without making the paper too long. I believe this paper is a useful addition to the scientific literature and deserves publication with only minor changes. Please see my specific comments below.
SPECIFIC COMMENTS
-L14-20. The first paragraph of the introduction would benefit from some references, for instance to the IPCC AR6.-L45-47. I suggest adding references to previous work documenting uncertainties and limitations of simulators, e.g. https://doi.org/10.1175/JCLI-D-11-00267.1 and https://doi.org/10.1175/2010JCLI3517.1.
-Figure 4. I recommend adding coast lines to the figures to facilitate the interpretation of the maps.-Figure 7. I suggest deleting the monthly means from the bottom row of plots (or moving them to a 3rd row of plots). This will allow the use of a better y-axis scale for the long-term averages.
-Figure 8. I believe the main point of this figure could be better made by plotting the average seasonal cycle, rather than the whole time series of monthly means.
Citation: https://doi.org/10.5194/egusphere-2025-169-RC1 -
RC2: 'Comment on egusphere-2025-169', Anonymous Referee #2, 28 Mar 2025
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COSP-RTTOV-1.0: Flexible radiation diagnostics to enable new science applications in model evaluation, climate change detection, and satellite mission design by Shaw et al
Implementation of RRTOV in the COSP is described along with tests to verify that it works correctly, mostly using single column model simulations for a range of cases. In addition to describing the implementation, the broader utility of RTTOV thermal radiances are shown using global climate model simulations with CAM. This includes the application of the RRTOV radiances for model evaluation, OSSEs and showing the effect of sampling. The paper is well organized and provides sufficient information about the RTTOV implementation in COSP and relevant applications.
Comments
Line 28 and 29: “only measure spectrally-resolved radiation field”, true for passive instruments but there are active instruments that measure returns from a known source signal.
Line 43: Just a point that instruments on satellites do not directly observe fields like radiances, e.g., the L0 data needs to be processed into a L1 quantity like radiances which have uncertainties.
Line 119: The CESM simulation using pre-industrial boundary conditions is 199 years long?
Line 125: Is SARTA faster than RTTOV? While RTTOV offers flexibility, if one was interested in evaluation relative to AIRS there could be value in using SARTA instead of RTTOV given the computational cost (Table 3).
Line 139: Are there options in RTTOV to use different cloud optics over cloud vertical overlap? While it might not be possible to match exactly what is used in the host model, there would be value if assumptions could be similar as possible. E.g., using the same cloud vertical overlap assumption.
Section 3.1.1: As noted in this section, different AIRS channels provide different information about the simulation. With respect to the computational time, the end user may decide to only simulate particular channels. Is this easily configured in COSP-RTTOV?
Citation: https://doi.org/10.5194/egusphere-2025-169-RC2
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