Update State of the field part according to comments

Author: hulecom

paper.bib

@@ -77,28 +77,6 @@ @article{Wieczorek_2018
   doi = {10.1029/2018GC007529},
 }
 
-@article{Rieger_2024,
-author = {Rieger, Niclas and Levang, Samuel J.},
-doi = {10.21105/joss.06060},
-journal = {Journal of Open Source Software},
-number = {93},
-pages = {6060},
-title = {{xeofs: Comprehensive EOF analysis in Python with xarray}},
-volume = {9},
-year = {2024}
-}
-
-@article{Bourgault_2023,
-author = {Bourgault, Pascal and Huard, David and Smith, Trevor James and Logan, Travis and Aoun, Abel and Lavoie, Juliette and Dupuis, Éric and Rondeau-Genesse, Gabriel and Alegre, Raquel and Barnes, Clair and Laperrière, Alexis Beaupré and Biner, Sébastien and Caron, David and Ehbrecht, Carsten and Fyke, Jeremy and Keel, Tom and Labonté, Marie-Pier and Lierhammer, Ludwig and Low, Jwen-Fai and Quinn, Jamie and Roy, Philippe and Squire, Dougie and Stephens, Ag and Tanguy, Maliko and Whelan, Christopher},
-doi = {10.21105/joss.05415},
-journal = {Journal of Open Source Software},
-number = {85},
-pages = {5415},
-title = {{xclim: xarray-based climate data analytics}},
-volume = {8},
-year = {2023}
-}
-
 @article{Dawson_2016,
   title = {Windspharm: A High-Level Library for Global Wind Field Computations Using Spherical Harmonics},
   author = {Dawson, Andrew},

paper.md

@@ -59,10 +59,7 @@ Existing Python libraries address specific needs in geophysical and climate data
 `pyshtools` [@Wieczorek_2018] and `grates` [@Kvas] offer tools for gravity spherical harmonic analysis.
 They operate on standalone arrays and lack support for `xarray`. `windspharm` [@Dawson_2016] implements `xarray` spherical harmonics analysis but without the gravity and geodetic related operations.
 `gsw-xarray` [@Caneill_2024] wraps the TEOS-10 framework for oceanographic computations within `xarray`, but does not support `Dask`.
-While `Lenapy` GSW wrapper is less complete, it proposes complementary geodetic tools for spatial and spherical harmonics operations.
-
-Other libraries built on `xarray` offer analysis capabilities that complement `Lenapy` specific focus, allowing users to apply advanced statistical or climate diagnostics to datasets.
-For example, `xeof` [@Rieger_2024] provides tools for Empirical Orthogonal Function analysis, enabling statistical decomposition and `xclim` [@Bourgault_2023] delivers a suite of climate indicators and climate processing routines.
+While `Lenapy` GSW wrapper is less complete than `gsw-xarray`, it proposes complementary geodetic tools for spatial and spherical harmonics operations.
 
 To our knowledge, no other existing Python library offers a coherent suite of oceanographic and geophysical operations (detailed below) within a unified, xarray-native framework supporting both scalability (via `Dask` [@Dask_2016]) and labeled, multidimensional arrays.
 Moreover, critical geospatial utilities (such as surface-aware averaging, weighted statistics, spherical distance computation, and climatology fitting) remain fragmented across ecosystems or require custom implementations.