This paper studies the data preprocessing and analysis methods of the key microwave ranging system for the low-low satellite-to-satellite tracking gravity mission, and achieve the efficient suppression of the key carrier frequency noise, as well as the elimination and correction of the related interference and deviation. According to the theoretical analysis results, relevant processing and analysis procedures are developed. The residual between the dual one-way ranging data product completed by this research and the official product of GRACE Follow-On is much smaller than the design requirement of the payload, which meets the accuracy requirements of gravity field inversion. Evaluation and analysis methods for electronic noise, system noise and other noise in the final data product are discussed. In this paper, by introducing the frequency-domain analysis method of the spatial inhomogeneity of the ionospheric free electron content, and using the inter-satellite microwave ranging data, the ability to analyse the variation behaviour of free electron content at different spatial scales and its global distribution characteristics is realized, providing data support for the in-depth study of the ionosphere. This research can provide relevant technical accumulation and reference for the data preprocessing and analysis of the microwave ranging system for low-low satellite-to-satellite tracking missions of China.

As a complement to the conventional monthly global solutions by Gravity Recovery and Climate Experiment series of gravimetric satellites, this study proposes an alternative method for estimating daily regional gravity field by utilizing the orbital Line‐of‐Sight Gravity Difference. The method is based on Slepian and B‐spline basis functions for spatial and temporal parameterizations, respectively. Such parameterization of regional gravity field can be used to estimate total water storage change in a way compatible with surface mass estimation previously designed in the framework of global gravity field determination. The formal uncertainty of daily mass changes recovery is ∼5 Gt, equivalent to ∼3 cm of equivalent water height over 400² km². In the evaluation part, the method is applied to the 2020 Bangladesh flood and the 2021 Australian flood. Our approach demonstrates strong agreement with the previous mascon‐based studies, yielding Nash‐Sutcliffe Efficiency values exceeding 0.81, and capturing the onset and recession of the flooding events. Additionally, we investigate the impact of data gaps, occasionally occur in the space‐borne missions employing intersatellite laser ranging system. Our findings indicate that the B‐spline parameterization effectively determines surface mass changes even with missing data rates up to 20% or with gap lengths no longer than 2 days, highlighting its reliability for continuous monitoring in challenging observational scenarios. By providing a new methodological framework for daily‐scale monitoring from satellite gravimetry, this work advances our understanding of the rapid evolution of climate extremes, which will ultimately facilitate future disaster monitoring and adaption efforts.

Abstract Landfalling hurricanes pose significant hydrological risks, yet monitoring their terrestrial water storage (TWS) dynamics remains challenging. Here we employed a new technique that estimates daily regional gravity changes from orbital perturbation measurements of the Gravity Recovery and Climate Experiment and its follow-on mission to characterize TWS variations during Hurricanes Katrina (2005) and Laura (2020). Our spatiotemporal water storage maps reveal ∼40 Gt of accumulation by Katrina and a coastally localized ∼15 Gt by Laura, with coastal regions retaining up to 80% of precipitation but draining several days faster than inland areas. Despite differing magnitudes, both storms exhibited similar precipitation-to-TWS conversion patterns, implying consistent scaling of hydrological responses across intensities. Our observations also indicate that current land surface models, lacking surface inundation modeling, result in underestimations of flood recession rates. This work highlights satellite gravimetry’s potential for continuous hurricane-induced flood monitoring, offering a new tool to alleviate current observational difficulties.