Data Quality and need of Regional Algorithm

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antu
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Data Quality and need of Regional Algorithm

by antu » Mon Mar 02, 2020 9:53 pm America/New_York

We have been investigating the annual/seasonal variability of chlorophyll-a concentration and its relationship with sea-surface temperature and river discharge in coastal shelf region of northern Bay of Bengal (Norther Indian Ocean) and validate MODIA Aqua chl-a data with in-situ measurement. We used 16 years’ level- 3 MODIS aqua chl-a (OCI algorithm) data for our study. But, we are facing several questions related to data from scientific community while publishing paper. The question was quoted below …

“In general, MODIS chlorophyll concentration products provided by NASA were directly used in the paper, without regional correction or regional algorithm inversion, which would lead to the unreliability of the results:
1)    The credibility of MODIS chlorophyll concentration products in offshore turbid water bodies is poor and significantly overestimated. The last figure (validation result graph of MODIS data with in-situ measurement) in the paper also proves this problem. Therefore, it is usually necessary to remove these turbid water bodies which are greatly affected by terrestrial sources. However, the analysis in this paper does not seem to exclude the region of turbid water, which will lead to unreliable results.
2)    Since the inshore MODIS inversion chlorophyll concentration value is significantly higher than that of the offshore sea, the regional mean value change more reflects the inshore water changes. However, the remote sensing data error of chlorophyll concentration in coastal water is very large. In fact, the chlorophyll concentration inversion in this region is more about the concentration of terrestrial suspended particulates than the real chlorophyll concentration. Therefore, the annual average, seasonal average and long-term variation trends all reflect the distribution and change of suspended matter concentration in water, rather than the distribution and change of chlorophyll concentration.
It is suggested to carry out regional correction of MODIS or regional algorithm inversion”


How can we clarify this query?
As we worked with level-3 data, there are no way to use regional algorithm. Level-3 chl-a data has a build-in algorithm called OCI (OCx and CI combined). Moreover, there need huge work load (time and funding) to form up a regional algorithm, which was not the scope of our study. Developing regional algorithm can be handy to get more accurate results. But without it, can’t we use level-3 data for our study area in scientific study?

I need some really strong and plausible statements regarding this query? We are rigorously questioned about quality of MODIS aqua data.

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OB WebDev - norman
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Data Quality and need of Regional Algorithm

by OB WebDev - norman » Tue Mar 03, 2020 10:13 am America/New_York

In addition to heavy suspended sediment load in the Bay of Bengal,
the region also suffers from perennially bad air quality.  This negatively
affects the accuracy of the MODIS atmospheric correction.

I am afraid your reviewers are correct.  Ocean color remote sensing
is difficult even over clear skies and Case 1 waters, so your region
comes with significant additional difficulties.

Norman

antu
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Data Quality and need of Regional Algorithm

by antu » Tue Mar 03, 2020 11:38 am America/New_York

Thank you very much for your reply.
Yes, the reviewer was right. We understand his point. But how can we provide some statement that support our work? We have no option to do regional correction.

Antu

gnwiii
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Data Quality and need of Regional Algorithm

by gnwiii » Tue Mar 03, 2020 12:08 pm America/New_York

I agree with Norman, but there may be some things you can do to better understand the NASA global products.   Some examples of things to consider are wind patterns (onshore winds may provide clear "maritime" air near coasts), effects of current patterns on river outflow plumes, and seasonal changes in the volumes of river outflows.    You will likely need to reference other data sources for winds, atmospheric conditions, and currents (perhaps you can find numerical model results).  If your in situ observations include turbidity measures you may be able to develop some understanding of the conditions where chlor_a dominates OCI, those where sediment dominates, and those where both are strong contributers.  You may find it helpful to consider patterns in "missing data", e.g., failures in atmospheric correction due to air pollution and offshore winds.   You should not be too worried about  reprocessing the full time series -- it may be enough to demonstrate the ability to quantify limitations of OCI using select areas and times.

OB.DAAC - SeanBailey
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Data Quality and need of Regional Algorithm

by OB.DAAC - SeanBailey » Wed Mar 04, 2020 8:45 am America/New_York

Following on George's suggestions, you may want to look at the L3 Rrs_667 product as a proxy for turbidity.  It may provide a means to identify where the chlorophyll retrievals are more uncertain.
Below is an example for January 2019.

Sean

antu
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Data Quality and need of Regional Algorithm

by antu » Mon Mar 09, 2020 1:54 am America/New_York

Thanks a lot; Mr. Sean, Mr. George and again Mr. Norman for your valuable and helpful suggestions. As you all suggested considering L3 Rrs_667, current pattern, wind pattern or atmospheric condition for regional correction, we like to take those considerations and some more for our next interest of study.
But now we want to know, whether MODIS level-3 chl-a data, itself has any procedures for atmospheric correction, cloud masking, etc for minimizing such type of errors. If it has, is there any documents regarding processing level-3 data or information about the atmospheric correction for MODIS aqua chl-a data.
Thanks in advance.
Antu

OB.DAAC - SeanBailey
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Data Quality and need of Regional Algorithm

by OB.DAAC - SeanBailey » Mon Mar 09, 2020 8:49 am America/New_York

Antu,
The Level-3 ocean color products (including chlorophyll) have a number of masking criteria applied to ensure only the best possible data are included.
However, these do not necessarily address the concerns of your reviewers, as there are conditions for which the flagging criteria cannot address or capture.

Specifics on the atmospheric correction can be found in the NASA Technical Memorandum "Atmospheric Correction for Satellite Ocean Color Radiometry"

Sean

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