Temporal gravity field solutions from the Gravity Recovery and Climate Experiment Follow-on (GRACE-FO) mission are inherently constrained by aliasing effects stemming from imperfect background models. Recent advancements in ocean tide modeling (e.g., FES2022) and nontidal dealiasing products (e.g., Atmosphere and Ocean De-Aliasing Level-1B (AOD1B) RL07) have the potential to enhance signal retrieval; however, their combined impact on gravity field estimation from the K-band Ranging System (KBR) and the more precise Laser Ranging Interferometer (LRI) remains insufficiently quantified. In this study, we assess the influence of these updated background models using eight sets of monthly GRACE-FO gravity field solutions spanning June 2018 to December 2022. Our analysis demonstrates that LRI-based solutions achieve lower noise levels than KBR-based ones while maintaining consistent temporal signal characteristics. The adoption of FES2022 and AOD1B RL07 effectively reduces noise levels across both oceanic and desert regions and enhances the temporal consistency of mass variation signals. Moreover, LRI-based solutions exhibit more pronounced noise reduction than KBR-based ones, with decreases of 5.3% and 8.7% over oceans after applying P4M6 decorrelation filtering, suggesting the LRI's superior measurement sensitivity. Overall, this study provides quantitative evidence that refining background models is crucial for realizing the potential of LRI observations to improve monthly gravity field solutions. This advancement is expected to hold more significant implications for the design of future satellite gravimetry missions.