Climatology of the Combined ASTER MODIS Emissivity over Land (CAMEL) Version 2
, E. Eva Borbas 1, Robert Knuteson 1, Kerry Cawse-Nicholson 2, Glynn Hulley 2 and Simon Hook 2
Round 1
Reviewer 1 Report
The climatology of emissivity data such as UWIREMIS and ASTER-GED are relevant to climate change studies. This paper comprehensively analyzed a new emissivity climatology dataset CAMEL V2.0, which will certainly benefit the study of atmospheric profile retrieval with thermal infrared data and benefit the study of surface radiation budget. This topic is interesting to general reader of Remote Sensing. The paper is technically correct and well written.
General comments:
- The time span of CAMEL V2.0 is 2000-2016, why not extend to 2018 or 2019?
- Page 1, line 33, please discriminate spectral emissivity and broadband emissivity. What the land surface model requires is broadband emissivity. Their definitions are different.
Cheng, J., Liang, S., Yao, Y., & Zhang, X. (2013). Estimating the Optimal Broadband Emissivity Spectral Range for Calculating Surface Longwave Net Radiation. IEEE Geoscience and Remote Sensing Letters, 10, 401-405
- Page 2, Second paragraph, please add GLASS BBE which has been freely released to public since 2012.
The GLASS BBE is produced from AVHRR and MODIS data. The time resolution of the BLASS BBE is 8-day, the spatial resolution is 1km for that derived from MODIS data (2000-2018) and 5km for that derived from AVHRR data (1981-2017)
Cheng, J., & Liang, S. (2014). Estimating the broadband longwave emissivity of global bare soil from the MODIS shortwave albedo product. Journal of Geophysical Research-Atmosphere, 119, 614-634
Cheng, J., Liang, S., Verhoef, W., Shi, S., & Liu, Q. (2016). Estimating the Hemispherical Broadband Longwave Emissivity of Global Vegetated Surfaces using a Radiative Transfer Model. IEEE Transactions on Geoscience and Remote Sensing, 54, 905-917
Liang, S., Cheng, J., Jia, K., Jiang, B., Liu, Q., Xiao, Z., Yao, Y., Yuan, W., Zhang, X., Zhao, X., & Zhou, J. (2020). The Global LAnd Surface Satellite (GLASS) product suite. Bulletin of the American Meteorological Society, 1-37
- As discussed by the previous studies, ASTER and MODIS emissivity products cannot characterize the vegetation abundance. I would like to know what the performance of CAMEL V2.0 over vegetation surfaces is.
Cheng, J., Liang, S., Verhoef, W., Shi, S., & Liu, Q. (2016). Estimating the Hemispherical Broadband Longwave Emissivity of Global Vegetated Surfaces using a Radiative Transfer Model. IEEE Transactions on Geoscience and Remote Sensing, 54, 905-917
Wang, W., Liang, S., & Meyer, T. (2008). Validating MODIS land surface temperature products using long-term nighttime ground measurements. Remote Sensing of Environment, 112, 623-635
Author Response
Please see the attachment.
Thanks for reviewing our paper!
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The manuscript ‘The Combined ASTER MODIS Emissivity over Land (CAMEL) Version 2 Climatology’ submitted by Michele Loveless et al. introduces a monthly global climatology based on the new version V002 of the CAMEL product, which has the same spectral, spatial and temporal resolution as the previous one, but shows more realistic seasonal changes and provides a climatology that is a more stable representation of CAMEL monthly emissivity. The manuscript outlines the changes between the two product versions and investigates the level of improvement achieved by V002 over four selected sites. CAMEL V001 and V002 climatologies are then evaluated using RTTOV calculations and IASI observations stratified by IGBP land cover class, thereby providing an assessment of the achievable improvement in practical applications, namely modelling. Finally, the manuscript presents a preliminary comparison between CAMEL V002 emissivity. Overall, CAMEL V002 is shown to be a considerable improvement over V001 and further improvements are already planned by replacing the current input MODIS product MYD11C3, which still has certain algorithmic artefacts, with MODIS MYD21 and VIIRS VNP21 products in the near future.
The manuscript is well written, well-structured and addresses a topic of interest to the wider remote sensing and modelling communities. Therefore, I recommend to accept it for publication after a minor revision.
Specific points / Suggestions:
In order to better reflect the contents of the manuscript, consider changing the title to s.th like ‘Climatology of global monthly ASTER MODIS Emissivity over Land (CAMEL) Version 2’ (thereby stressing that the main topic of the manuscript is the emissivity climatology)
Line 16: … surface emissivity and …
Line 131: … that provides emissivity estimates from space. (i.e. only radiances are measured)
Lines 136 – 137: … emissivity data are …. NASA LP DAAC and have …; please check throughout the manuscript.
Table 3.1 caption: consider writing ‘Laboratory Datasets of spectral emissivity used in CAMEL V002.’ This would make it easier for the readers to follow.
Line 165: … climatology and takes the following values: …
Line 167: … for each of the 13 …
Lines 170-171: … calendar month by averaging over each of the …
Lines 201-201: please consider using standard matrix notation
Line 290: … is based solely on ASTER data …
Line 291: … is based on a weighted mean …
Line 331: consider ‘Analyses stratified by IGBP land cover class’
Line 333: … shown for the global mean emissivities of IGBP …
Line 390: consider ‘Global Temporal Emissivity Variation’
Lines 398-400: Could you suggest reasons for the observed high variation at high latitudes (probably snow melt in April?) and in the Sahel region (seasonal vegetation cycle, desiccated & vanishing vegetation cover?).
Line 409: … are computed from IASI radiances with RTTOV v12 … (so this is a ‘partial LST retrieval’?)
Line 412: … based on the year 2007 …
Line 413: … year 2007 is a good representation …
Line 429: please explain (1-2 sentences?) how the brightness temperatures are computed from IASI footprints. Why are these brightness temperatures and not LST?
Line 453: Comparison of IASI BTs retrieved … (and see my previous question Line 429)
Line 459: … emissivities overlaid. The de-biased …. (shorter sentences are easier to follow)
Line 468: … ASTER data are …
Line 469: Reststrahlen
Line 471: ‘(bias)’ does not make sense to me – did you want to write ‘BTs’ ?
Line 482: ‘… IASI BTs: 15 cases …’ (a colon makes this more readable)
Lines 507-508: … than cases of degradation.
Author Response
Please see the attachment.
Thanks for reviewing our paper!
Author Response File: Author Response.pdf
Reviewer 3 Report
Review of “The Combined ASTER MODIS Emissivity Over Land (CAMEL) Version 2 Climatology” by Michelle Loveless , Eva Borbas, Robert Knuteson, Glynn Hulley, Simon Hook, and Kerry Cawse-Nicholson
General comments:
The authors present in this paper the CAMEL V2 climatology as an improvement of the previous version V1. The main changes between the two versions are summarized. Results are presented at four different sites, and differences between both versions are analyzed.
The paper is well written and structured, methodology and results are clearly presented, although changes should be introduced in some figures to improve readability. In section 6 the authors check the possible improvement of the new version by comparison of RTTOV calculations using both versions to IASI observations. My main concern is that the improvement (or degradation) of the new version is based on temperature difference changes mostly of the order of 0.01 K, which is well below of the usual temperature uncertainty. In this sense, I’m not sure that this new version is a real advance in terms of temperature recovery; thus, the authors should be more careful in drawing this conclusion from the presented results (that in fact are limited to only 4 days on only one site).
Some additional comments are given below to help the authors to improve the paper.
Specific comments:
Lines 201-202: equations must be numbered.
Figure 5.1.1: the monthly hinge-points and emissivities are blurred in the graphs and are not easily seen. I suggest removing them, since the standard deviation graphs give a clear idea of the variability.
Figures 5.1.3 through 5.1.6: I suggest increasing their size, since it is hard to distinguish the lines showing the different quantities. The uncertainty components (algorithm, spatial and temporal) should be removed to improve readability; in fact, these terms are almost not commented in the main text.
Section 6: this section compares the performance of both datasets (CAMEL V001 and V002) by comparison of RTTOV calculations using them to IASI observations. Most of the improvement or degradation cases obtained when using CAMEL V002 are based on temperature difference changes of the order of 0.01 K, well below the usual temperature uncertainty (1 K). Thus, this section does not show or demonstrate a real improvement or degradation of the new database with regard to the previous one. In my opinion this section does not contribute significantly to the paper and should be removed.
Figures should be numbered correlatively through the paper, not by sections. The same applies for the tables presented in the paper.
Author Response
Please see the attachment.
Thanks for reviewing our paper!
Author Response File: Author Response.pdf
