the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Far-Infrared Radiation Mobile Observation System for spectral characterisation of the atmospheric emission
- 1National Institute of Optics, National Research Council, Florence, Italy
- 2Institute of Applied Physics "Nello Carrara", National Research Council, Florence, Italy
- 3Karlsruhe Institute of Technology (KIT), IMK-IFU, Garmisch-Partenkirchen, Germany
- 4Forschungszentrum Jülich, IEK-7, Jülich, Germany
- 1National Institute of Optics, National Research Council, Florence, Italy
- 2Institute of Applied Physics "Nello Carrara", National Research Council, Florence, Italy
- 3Karlsruhe Institute of Technology (KIT), IMK-IFU, Garmisch-Partenkirchen, Germany
- 4Forschungszentrum Jülich, IEK-7, Jülich, Germany
Abstract. The Far-Infrared Radiation Mobile Observation System (FIRMOS) is a Fourier transform spectroradiometer developed to support the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) satellite mission by validating measurement methods and instrument design concepts, both in the laboratory and in field campaigns. FIRMOS is capable of measuring the downwelling spectral radiance emitted by the atmosphere in the spectral band from 100 to 1000 cm-1 (10–100 µm in wavelength), with a maximum spectral resolution of 0.25 cm-1. We describe the instrument design and its characterisation and discuss the geophysical products obtained by inverting the atmospheric spectral radiance measured during a campaign from the high-altitude location of Mount Zugspitze in Germany, beside the Extended-range Atmospheric Emitted Radiance Interferometer (E-AERI), which is permanently installed at the site. Following the selection of clear-sky scenes, using a specific algorithm, the water vapour and temperature profiles were retrieved from the FIRMOS spectra by applying the Kyoto protocol and Informed Management of the Adaptation (KLIMA) code. The profiles were found in very good agreement with those provided by radiosondes and by the Raman lidar operating from the Zugspitze Schneefernerhaus station. In addition, the retrieval products were validated by comparing the retrieved Integrated Water Vapour values with those obtained from the E-AERI spectra. Finally, we found that the trends for the temperature, and the water vapour profiles over time were in good agreement with those provided by ERA5 reanalysis.
Claudio Belotti et al.
Status: open (extended)
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RC1: 'Comment on egusphere-2022-1327', Anonymous Referee #1, 22 Jan 2023
reply
This paper describes a new portable infrared spectrometer that has is able to provide spectral radiance observations from 100 to 1000 cm-1. This spectrometer (FIRMOS) is the successor of the REFIR-PAD system, and is serving as a technology demonstrator for the future FORUM instrument. It was deployed to a dry, high-altitude site at Mount Zugspitze in Germany, where there are other instruments which were used to help evaluate this instrument.
In general, the paper was well written, especially the first half of the paper that discuss the technical details of the FIRMOS instrument. The latter part of the paper compares temperature and humidity retrievals from the FIRMOS against radiosondes, Raman lidar, E-AERI, and ERA5 reanalysis. Due to the relatively few observations that were available, this latter section is somewhat weak. However, there are always data limitations, so this isn’t necessarily crippling to this paper.
This paper would greatly benefit from having a comparison with both the E-AERI in radiance space. Due to the differences in the spectral resolutions, I would recommend the authors use the “double difference technique” outlined in Tobin et al. JGR. 2006. As the two instruments are essentially collocated (although vertically offset by 4 m), the spectral differences between 405 and 600 cm-1 should be within the instrument noise (if both systems are well calibrated).
Line 253: did you assume any cross-level covariance in your a-priori? Were there any cross-correlations between temperature and humidity? There should certainly be cross-level correlations in temperature due to the atmospheric lapse rate, and a long analysis of radiosonde data from the region (or ERA5 data) should indicate if there should be other correlations in the a-priori. If you assume the a-priori is a diagonal matrix, that will essentially increase the information content (DFS) of the retrievals.
Line 260: It is important to note that the gradient in a cloud-free measurement is zero only because it is so dry at the Zugspitze location. If you were in a tropical location, there would be a negative slope. This needs to be stated.
Line 279: In the selection of the 625 cases, did the Raman lidar (or the backscatter lidar, which was briefly mentioned later in the paper) confirm that these were cloud-free?
Line 288: it was not clear if the uncertainty used in the retrievals was the NESR or the sum of the NESR and the CalErr. Please clarify this in the text. If the latter, then the chi-squared term being less than 1 could be due to the very conservative estimate of the thermistor error in the blackbodies (stated on line 230).
Line 293: the mean residual also will contain any bias error in the forward model (not only instrument calibration error).
For the two comparisons in Fig 15: it would be nice to include the integrated water vapor (IWV) amount for the two cases. Also, for line 309, the authors suggest that the DOF depends on the surface water vapor content, but it is really dependent on IWV? Turner and Löhnert (JAMC, 2014) showed that the DOF in the water vapor retrieval using AERI observations in the 538-588 cm-1 region depends on IWV.
Figure 20: please replot using a skew-T approach, so that differences of a few degrees can be more easily identified and quantified.
Fig 23 and resulting analysis: this is pretty unsatisfying. I realize the purpose is to show that the FIRMOS is capturing the evolution of the event well, but the very coarse resolution of the ERA5 data in a mountainous region is totally inadequate to the task. I highly recommend that the comparison be made against higher-resolution NWP output, such as the (order)2-km resolution ICON data from the DWD. And that the figure include a subpanel showing the bias and RMS difference between the NWP model and the FIRMOS.
Question: Why did the authors not perform KLIMA retrievals using the E-AERI spectra, and then compare the retrievals from the E-AERI with the FIRMOS? This seems like it would be a relatively simple comparison and include a lot more data (e.g., there seems to be hundreds of points in Fig 22), and open up an interesting discussion because their spectral differences between the two instruments.
Claudio Belotti et al.
Data sets
FIRMOS - Technical Assistance for a Far-Infrared Radiation Mobile Observation System (EE9 Forum) Luca Palchetti, Marco Barucci, Claudio Belotti, Giovanni Bianchini, Bertrand Cluzet, Francesco D'Amato, Samuele Del Bianco, Gianluca Di Natale, Marco Gai, Dina Khordakova, Alessio Montori, Hilke Oetjen, Markus Rettinger, Christian Rolf, Dirk Schuettemeyer, Ralf Sussmann, Silvia Viciani, Hannes Vogelmann, Frank Gunther Wienhold https://doi.org/10.5270/ESA-38034ee
Claudio Belotti et al.
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