Where are the two sample SWOT data files ? THANKS!

[Mingzhi-Sun]

Thank you for your sharing. This is a great tool for frocessing SWOT data, but where are the two sample SWOT data files (SWOT_L2_LR_SSH_Expert_474_013_20230329T081622_20230329T090516_PIB0_01.nc and SWOT_L2_LR_SSH_Expert_474_026_20230329T191926_20230329T201032_PIB0_01.nc)?

[sgille]

Apologies. The file turns out to be too big for github. It's available through PODAAC ( https://podaac.jpl.nasa.gov/SWOT?tab=datasets-information&sections=about%2Bdata) or AVISO ( https://www.aviso.altimetry.fr/en/data/products/sea-surface-height-products/global/swot-karin-low-rate-ocean-products.html). If neither of those works, let me know, and I'll see what other options are available. For the software that I posted, the only function of the data file is to provide latitude and longitude coordinates.

Best,

Sarah Gille

On Tue, Jul 9, 2024 at 10:36 PM Mingzhi @.***> wrote:

Thank you for your sharing. This is a great tool for frocessing SWOT data, but where are the two sample SWOT data files (SWOT_L2_LR_SSH_Expert_474_013_20230329T081622_20230329T090516_PIB0_01.nc and SWOT_L2_LR_SSH_Expert_474_026_20230329T191926_20230329T201032_PIB0_01.nc)?

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[Mingzhi-Sun]

That is great! Thank you for your help. I have downloaded these two files.

[Mingzhi-Sun]

Hello,

I am a PhD student conducting applied research on SWOT mission data, primarily focused on geodesy. My goal is to obtain accurate SSHA data to determine geoid heights, which I can then use to derive marine gravity anomalies on the sea surface. I recently read your article, "SWOT Data Assimilation with Correlated Error Reduction: Fitting Model 1 and Error Together," and was able to successfully run your code. However, the process still seems quite complex, and I’m uncertain about how to use this code to correct SWOT KaRin data specifically.

Ideally, I am looking to modify the input data path in the code and directly generate corrected .nc data files. I tried adapting your code for this purpose but haven’t succeeded. I would greatly appreciate your guidance. For example, my research area is in the Philippine Sea. Could you advise on the specific auxiliary data I would need to prepare and which parts of the code are relevant to implement the method described in your paper for achieving more precise SSHA?

Thank you very much for your assistance.

[sgille]

Good question! We wrote the code as a proof of concept, using synthetic data with a known prior error covariance. In our own group, we have not yet tested it with SWOT data, though our longterm goal is to incorporate this into data assimilation. To apply the method to real data, the biggest change would be to set the error covariance to match the covariance of the SWOT errors. I did this for SWOT simulator data in the updated version of the code, developed for the manuscript revisions. In general, I'd suggest making a first pass at fitting the correlated error and using the fitting procedure (or extract the correlated error estimates from the L3 product to set the a priori permitted magnitude of the parameters). If the P matrix is defined correctly, then the other details should follow.

In passing, I'll note that to my knowledge my Scripps colleagues who are working on the geoid have been using the L3 correlated error corrections, without adding an additional correction. The value of the correlated error strategy in our code comes in fitting two separate models at the same time.

Best,

Sarah

On Wed, Oct 30, 2024 at 12:00 AM Mingzhi @.***> wrote:

Hello,

I am a PhD student conducting applied research on SWOT mission data, primarily focused on geodesy. My goal is to obtain accurate SSHA data to determine geoid heights, which I can then use to derive marine gravity anomalies on the sea surface. I recently read your article, "SWOT Data Assimilation with Correlated Error Reduction: Fitting Model 1 and Error Together," and was able to successfully run your code. However, the process still seems quite complex, and I’m uncertain about how to use this code to correct SWOT KaRin data specifically.

Ideally, I am looking to modify the input data path in the code and directly generate corrected .nc data files. I tried adapting your code for this purpose but haven’t succeeded. I would greatly appreciate your guidance. For example, my research area is in the Philippine Sea. Could you advise on the specific auxiliary data I would need to prepare and which parts of the code are relevant to implement the method described in your paper for achieving more precise SSHA?

Thank you very much for your assistance.

— Reply to this email directly, view it on GitHub https://urldefense.com/v3/__https://github.com/sgille/swot_correlated_error/issues/1*issuecomment-2446014428__;Iw!!Mih3wA!DQCKggGRiQflsDNgStfCJYRhWIqigRfJKEAGzjW1fUhP8ZJSBmo6KKbbLOh-NKvq8oHjxSMN1FOzIHliJmhoR58$, or unsubscribe https://urldefense.com/v3/__https://github.com/notifications/unsubscribe-auth/AEJJIT5D7DWKLYS5IZ2CZ53Z6B7ZTAVCNFSM6AAAAABKUEVFBWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDINBWGAYTINBSHA__;!!Mih3wA!DQCKggGRiQflsDNgStfCJYRhWIqigRfJKEAGzjW1fUhP8ZJSBmo6KKbbLOh-NKvq8oHjxSMN1FOzIHlimf8jZVA$ . You are receiving this because you commented.Message ID: @.***>

-- Sarah Gille @.*** (she/her/hers) phone:858-822-4425 Professor Scripps Institution of Oceanography University of California San Diego, La Jolla, CA 92093-0230