|Review of manuscript “Measuring sea ice concentration in the Arctic Ocean using SMSO” by Gabarro et al. |
The manuscript introduces a new algorithm to retrieve sea ice concentration in the Arctic region based on radiometric observations from the L-band SMOS, with its multi-viewing angles. It uses the Maximum Likelihood criterion with input distributions of a couple of radiometric indices, assuming Gaussian distributions with mean and standard deviation obtained from model and observation findings.
The idea is interesting, the study is scientifically warranted and it is an appropriate continuation, with a remarkable progress, of the limited number of similar studies using SMOS in the past 8 years. I would recommend publication and certainly commend the authors on their effort. However, one should keep in mind that the challenge of estimating SIC from remote sensing data remains.
In most studies, sea ice is treated as one entity. Yet, in nature it is manifested in several types with large diversity of physical properties that may lead to consider it as different entities. Thin ice, seasonal ice, perennial ice, summer ice, etc. are different “creatures” within the realm of sea ice; let alone snow-covered ice under different metamorphosed snow conditions that lend itself to different radiative properties, even under the passive L-band radiometry. Given this concept, I would be cautious when considering SIC algorithms trying to approximate the wide range of ice properties into a single set.
With this in mind I am not comfortable with the title of the paper that groups all ice types under one phrase “sea ice in the Arctic Ocean”, but I guess nothing can be done here! But it would be more appropriate to use the word “Estimating” in the title instead of “Measuring” since we don’t really measure SIC.
The method adds to the to the tools of estimating ice concentration from microwave data. One advantage of having different methods is to be able to perform cross-checking. This is important because there is no reliable “truth” data against which we can evaluate each method. All methods suffer from errors and the only way to approach the “truth” is by cross-checking. For example, the current study performs the validation by comparing results against maps from OSI-SAF. But the latter, much like any other operational ice maps, may not be considered truth data either.
Another concern is about a sentence in the Abstract; “We find that sea ice concentration is well determined (correlations of about 0.75) when compared to estimates from other sensors such as the Special Sensor Microwave/Imager (SSM/I and SSMIS).” Retrieval of any parameter from remote sensing data is associated not only to the sensor characteristics but also to the retrieval method. I believe the method used in this study is new, so if there are other method using L-band then the authors can do comparison. To keep the above statement, the authors should qualify it; namely to say correlate well with other passive microwave – but under what condition (when and where). I think it should correlate well with other sensors over mature Arctic sea ice in winter. Other than that I don’t think the correlation would reach 0.75.
A few suggestions for corrections are listed below. It would be nice if the authors consider them while preparing the final submission.
Page 4 Line 21: correct the sentence to be “Hereafter we will use TB to refer to surface brightness temperature, for simplicity”
Page 4 Line 25: correct the sentence to be “is the ratio between reflected and incident radiation”
Page 5 Line 4: no need to mention the refractive index (n); this is for optical remote sensing but here we deal with microwave.
Page 5 line 6: the sentence “The nonlinearity is an advantageous property for remote sensing …” is not explained. How? Also it has no relevance to the text before it. The authors may remove it.
Page 5 Line 7: if Fig. 2 is for the L-band please mention that in this line or in the figure caption. Also, while the authors mentioned the seawater and sea ice parameters that are used in equation 3, they did not mention the snow parameters. Here they have to be careful because it is difficult to characterize the snow by a single temperature value as it is highly responsive to the air temperature. Even for dry snow, it can be lossy because the salinity at the snow base is usually higher than 0; it can be as high as 20 ppt or higher as shown in many studies.
Page 5 line 23: “dry snow still has an effect in (make it “on” not “in”) emissivity that changes with the angle of incidence according to Snell’s law”. Snell’s law is about the angle of refraction, nothing to do with the emissivity.
Page 6: in the set of presented equations I think one equation is missing; that is the one that determines the reflectivity from the ice surface in terms of its dielectric constant (i.e. Fresnel equation). This should be inserted before equation 5.
Page 7 line 7: close the bracket after (resulting from ….unknown physical parameters).
Page 7 line 10: something wrong in the sentence “… among conditions such as deletedwhen a phase change …”
Page 7: just wonder why didn’t you use the polarization ratio instead of the polarization difference? The former is more common and it eliminates the dependence of the brightness temperature of the physical temperature. I am not suggesting to change the present scheme but an inclusion of a sentence to explain why PD and not PR would be useful.
Page 7 Line 25 “we will use tie points as ground truth estimates of sea ice concentration”. What does that mean? Tie points are used to estimate ice concentration based on a set of algebraic equations.
Page 8 Line 7: just a comment on Figure 5, it is good to see the model confirms what we know – that Tb, not PR or PD can be used to estimate ice thickness. The latter are good for estimating ice concentration.
Page 9 Line 3: the statement “AD is the most robust index to retrieve SIC, slightly better than PD, and significantly better than TB, as TB is highly sensitive to ice thickness variations” may need some more thought. The fact that TB in the L-band is sensitive to the thickness has no relevance to its robustness in retrieving SIC of total ice (i.e. concentration regardless of ice thickness), hence the above statement may not be accurate. As mentioned in the text, the L-band has problem in estimating SIC only when the ice is thin (a few centimeter) and becomes partially transparent to the L-band. I think what can be used to comment on the high value of the propagated error in Table 3 when TB is used is the fact that the variability of TB is quite high with the thickness parameter (unlike the temperature and salinity) because of the large penetration of the L-band, and may not conform to the Gaussian assumption.
Page 12 Line 1: change the word “replacedmoenthsepochs”.
Page 12 Line 1: when talking about Fig. 10, the given information is expected, nothing new. I would prefer seeing Fig. 10 generated for data in winter months. Ice in Laptev and Kara seas remains thin during winter. The region remains a marginal ice zone throughout most of the freezing season. So, I believe that we will see the same difference during November and December as we see it during the period 2-5 November shown in Fig. 10. But it is interesting to confirm that. The authors may refer to a publication about thin ice in the Arctic titled “Interannual variability of young ice in the Arctic estimated between 2002 and 2009”.
Page 13 Line 5: Same argument applies here. The text says “… for some days in November, the month of maximum extension of thin young ice”. My argument is that this statement applies to ice extending west through the Beaufort Sea“ but not in the Laptev and Kara Seas area, where thin ice cover continues to exist in winter.
Figure 6: in the caption it should be mentioned that the values for the ice are coming from multi-year ice (as mentioned in the text).
Figure 10: I believe that the difference of SIC is presented in scale of tenth concentration. Please indicate that in the caption. The advantage of this figure is not limited to what is already described in the paragraph. It also marks the area of highly dynamic and ice reproduction, which, again not limited to November.
Finally - the phrase “tie-point regions” is confusing. Better use “regions for generating tie-points”