In addition to processing error, correct interpretation of GRACE, & GRACE-FO, data must also consider issue such as atmospheric river events, local ice discharge events (such as from the Thwaites Ice Tongue), and isostatic round (see the linked references):

I have checked to see if the GRACE-FO data has been recalibrated - the answer is no.

The GRACE-FO raw data is processed as follows.......

http://gravis.gfz-potsdam.de/corrections**Corrections and Auxiliary Products**

A number of corrections and reductions are applied to the Level-2 spherical harmonics to generate Level-3 products that represent variations of the Earth's surface masses as accurately as possible. These post-processed Level-2 coefficients, denoted as Level-2B products, are provided as an additional data set for users who wish to undertake surface mass inversion starting from spherical harmonic coefficients by themselves.

The Level-2B products as well as individual data sets and models used during the post-processing steps mentioned below are available here.

**Mean Field**

GRACE/GRACE-FO Level-3 products represent mass anomalies, i.e., positive or negative variations about a long-term mean gravity field of the Earth. Essentially, the choice of this mean field is arbitrary, since using a different mean field only introduces a constant bias to the time series of mass anomalies. However, when comparing these Level-3 products to other data or models, all time series should refer to the same reference epoch.

All Level-2B/Level-3 products currently available at GravIS refer to a long-term mean field calculated as unweighted average of the 156 available GFZ RL06 GSM products in the period from 2002/04 up to and including 2016/08.

**Anisotropic Filtering**

In order to optimally separate signal and noise in the GRACE/GRACE-FO Level-2 data, filtering is necessary. Due to the observation geometry with its pure along-track ranging on polar orbits GRACE and GRACE-FO gravity fields reveal highly anisotropic error characteristics. An adequate filter technique to account for this is the decorrelation method by Kusche et al. (2009), named DDK, which is deduced from a regularization approach using signal and error information in terms of variance and covariance matrices. The filtering is applied in the spectral domain by multiplying the filter matrix to the unfiltered spherical harmonic (SH) coefficients (residual with respect to a mean field). This method has been adapted by Horvath et al. (2018) taking into account the temporal variations of the error variances and covariances, namely VDK filtering.

Hence, our Level-2B products are optionally decorrelated and smoothed with an adaptive filter that explicitly takes into account the error covariance information of the corresponding Level-2 product. We provide the following variants of Level-2B products: filtered with VDK2, VDK3, and VDK5 as well as unfiltered (NFIL) solutions. These variants are distinguishable by respective strings in the product file names.

**C20 Time Series**

The spherical harmonic coefficient of degree 2 and order 0 (C20) is related to the flattening of the Earth. Since it is known that monthly GRACE estimates of C20 are affected by spurious systematic effects (e.g. Cheng & Ries, 2017), the C20 coefficients and their formal errors are replaced by estimates derived from satellite laser ranging (SLR) observations that are regarded to be more reliable.

Here, we use a C20 time series processed at GFZ (König et al., 2019) that is based on the six geodetic satellites LAGEOS-1 and -2, AJISAI, Stella, Starlette, and LARES (starting from March 2012) and uses the same background models and standards as applied during GFZ GRACE/GRACE-FO processing, including the Atmosphere and Ocean De-aliasing model AOD1B.

**GIA Correction**

Glacial Isostatic Adjustment (GIA) denotes the surface deformation of the solid Earth (lithosphere and mantle) caused by ice-mass redistribution over the last 100,000 years, dominated by the termination of the last glacial cycle. Due to the Earth's viscoelastic response to mass redistribution between the ice sheets and the ocean, the Earth's gravity field is affected by long term secular trends mainly in previously glaciated regions such as North America, Fennoscandia and Antarctica. Moreover, also coefficients of low degrees and orders are affected.

The Level-2B/Level-3 products provided here are corrected using a GIA model based on ICE-5G ice load history (Peltier, 2004) as applied to the 3D-Viscoelastic Lithosphere and Mantle Model VILMA (Martinec, 2000; Klemann et al., 2008).

I downloaded the PNAS AIS & GIS papers from Rignot et al, together with the spreadsheets included, last year. Fascinating stuff. What I found fascinating was that the Net Antarctic Mass Loss is the relatively small difference between SMB addition (snowfall) and ice mass loss.

(see graph attached).

The spreadsheet also showed that annual SMB addition averaged circa 2,100 GT per annum over the 39 years analysed, but during that time increased by at least 200 GT per annum.

The SMB simulated by MARv3.10 looks like annual SMB increase is now circa 2,500 GT per annum. (see 2nd graph attached)

This means that for the NET MASS BALANCE of the AIS to reduce at an accelerated rate (as it has), Ice Mass Loss has had to increase at an even greater rate.

I was hoping to compare basin data from GRACE-FO with PNAS basin data (which has area in KM")- BUT

- GRACE-FO uses 25 basins,

-PNAS uses 27 basins.

The match is close but not exact (sea map attached)

*ps: The same problem applies to the GIS*

So all I can do is use what I've got - i.e. GRACE-FO monthly data and SMB graphs from

http://climato.be/cms/index.php?climato=the-2020-melt-season-over-antarctica-as-simulated-by-marv3-10