Data source:
 
1) Bottom pressure derived from the spherical harmonic transform
   of the output Max-Planck-Institute for Meteorology Ocean Model 
   (MPIOM07, Shihora et al., 2023), release RL07, truncated at 
   degree/order 180. The coefficients of the MPIOM07 model 
   spherical harmonics transform are provided by the 
   GeoForschingZentrum (GFZ) and can be downloaded from 
   ftp://isdcftp.gfz-potsdam.de/grace/Level-1B/GFZ/AOD/RL07/

   MPIOM (Jungclaus, 2013) is a free surface general circulation 
   model that solves the primitive equations under the Boussinesq 
   approximation. The MPIOM model used 1.0 deg tri-polar 
   Arakawa-C grid with 40 vertical layers and nominal internal 
   model time-step of 20 minutes. The model contains a dedicated 
   sea-ice module. The full feedback of self-attraction and
   loading has been implemented and the spatial domain has been 
   extended to also include cavities underneath the Antarctic 
   shelf-ice.

   The original output of the MPIOM07 model contains signals of 
   the atmospheric tides and its oceanic response to them. 
   The harmonic variations at 18 frequencies, including diurnal, 
   semi-diurnal, ter-diurnal, 4-diurnal frequencies as well as 
   the mean bottom pressure computed over 43 year time series of 
   MPIOM07 bottom pressure over 1980-2023 were estimated by least 
   squares and removed. The bottom pressure dataset used fir loading 
   computation has not harmonic signal at these frequencies.

   Here are the frequencies for which harmonic signal from bottom
   pressure has been removed:

   7.232384890619D-05  rad/s   ( PI1 )
   7.252294578148D-05  rad/s   ( P1  )
   7.272206167609D-05  rad/s   ( S1  )
   7.292115855138D-05  rad/s   ( K1  )
   7.312025542667D-05  rad/s   ( PSI1)
   1.450459105823D-04  rad/s   ( 2T2 )
   1.452450074576D-04  rad/s   ( T2  )
   1.454441043329D-04  rad/s   ( S2  )
   1.456432012082D-04  rad/s   ( R2  )
   1.458423171028D-04  rad/s   ( K2  )
   2.177679627494D-04  rad/s   ( U3  )
   2.179670596247D-04  rad/s   ( T3  )
   2.181661850283D-04  rad/s   ( S3  )
   2.183652533752D-04  rad/s   ( R3  )
   2.185643502505D-04  rad/s   ( K3  )
   2.904900529562D-04  rad/s   ( U4  )
   2.906891498303D-04  rad/s   ( T4  )
   2.908882467044D-04  rad/s   ( S4  )

   The spherical harmonic transform was underwent the procedure
   of its conditioning in order to mitigate corruption of the bottom
   pressure due leakage due to spherical harmonics truncation.

   The procedure of conditioning has nine  steps:

   1) inverse harmonic transform of degree/order 180.

   2) re-gridding to the equi-angular longitude/latitude grid 10800x5400.

   3) applying fine land/sea mask at 10800x5400 grid, i.e. masking out
      points that are land.

   4) smoothing by convolving the bottom pressure with a kernel
      that exponentially decays with distance. The decay parameter is
      -PI/(2.0*T), where T is the degree/order of truncation of the 
      original harmonic transform (180).     

   5) Subtraction of harmonic signal at 18 frequencies from each
      cell of bottom pressure.

   6) direct harmonic transform of the grid with degree/order 2699.

   7) replacements of spherical harmonics with degree/order < 181
      with original harmonic transform from the MPIOM07 model

   8) inverse harmonic transform of degree/order 2699.

   9) smoothing by convolving the bottom pressure with a kernel
      that exponentially decays with distance.

   Credit:

   The MPIOM model was originally developed by M. Thomas and his colleagues.

   The main document that describes the input dataset is available here:

   ftp://isdcftp.gfz-potsdam.de/grace/DOCUMENTS/Level-1/GRACE_AOD1B_Product_Description_Document_for_RL07.pdf

   The main peer-reviewed paper that describes the input dataset
   is Shihora et al. (2023).

References:

   Linus Shihora, Kyriakos Balidakis, Robert Dill, Christoph Dahle,
     Khosro Ghobadi-Far, Jennifer Bonin, and Henryk Dobslaw, "Non-Tidal 
     Background Modeling for Satellite Gravimetry Based on Operational 
     ECWMF and ERA5 Reanalysis Data: AOD1B RL07", (2023). 
     Journal of Geophysical Research, Solid Earth, 127, e2022JB024360. 
     DOI: https://doi.org/10.1029/2022JB024360

   Dobslaw, H., Bergmann-Wolf, I., Dill, R., Poropat, L., Thomas, M., Dahle, 
     C., Esselborn, S., Koenig R. & Flechtner, F. (2017). 
     A New High-Resolution Model of Non-Tidal Atmosphere and Ocean
     Mass Variability for De-Aliasing of Satellite Gravity Observations: 
     AOD1B RL06, Geophys. J. Int., 211, 263269, DOI: 10.1093/gji/ggx302. 10

   Dobslaw, H., Flechtner, F., Bergmann-Wolf, I., Dahle, C., Dill, R., 
     Esselborn, S., Sasgen, I., Thomas, M. (2013). 
     Simulating high-frequency atmosphere-ocean mass variability for 
     dealiasing of satellite gravity observations: AOD1B RL05. J.
     Geophys. Res., 118(7), 3704--3711. DOI: 10.1002/jgrc.20271. 

   Dobslaw, H., Thomas, M., Simulation and observation of global ocean mass 
     anomalies, (2007). JGR, 112, C05040, 

   Jungclaus, J. H., Fischer, N., Haak, H., Lohmann, K., Marotzke, J., 
     Matei, D., Mikolajewicz, U., Notz, D. & von Storch, J. S. (2013). 
     Characteristics of the ocean simulations in the Max Planck
     Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth 
     system model, Journal of Advances in Modeling Earth Systems, 5, 
     422--446, DOI: 10.1002/jame.20023. 7, 23

   Petrov, L., The International Mass Loading Service, 
     Proceedings of the Reference Frames for Applications in 
     Geosciences Symposium, held in Luxembourg in October 2014, (2015). 
     DOI: 10.1007/1345_2015_218, http://arxiv.org/abs/1503.00191

   Petrov L., J.-P. Boy, "Study of the atmospheric
     pressure loading signal in VLBI observations", (2004).
     Journal of Geophysical Research, vol. 109, No. B03405
     DOI: 10.1029/2003JB002500, 

