Mon Oct 13, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Zhang, Lin, Shen, Yunzhong, Sneeuw, Nico, Ji, Kunpu, and Ju, Xiaolei, 2025. One-step estimation of non-seasonal terrestrial water storage variation in Southeastern China. Environmental Research Letters, 20(8):084071, doi:10.1088/1748-9326/adeff4.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025ERL....20h4071Z,
author = {{Zhang}, Lin and {Shen}, Yunzhong and {Sneeuw}, Nico and {Ji}, Kunpu and {Ju}, Xiaolei},
title = "{One-step estimation of non-seasonal terrestrial water storage variation in Southeastern China}",
journal = {Environmental Research Letters},
keywords = {non-seasonal signals, GRACE, extreme drought and wetness, climate indices, Southeastern China},
year = 2025,
month = aug,
volume = {20},
number = {8},
eid = {084071},
pages = {084071},
abstract = "{Accurate estimation of non-seasonal signals (NSSs) of Terrestrial Water
Storage Anomaly (TWSA) from Gravity Recovery and Climate
Experiment monthly gravity field models is essential for
identifying and understanding extreme hydrological phenomena.
However, significant north-south striped noise in the models
necessitates spectral filtering before estimating NSSs,
resulting in signal attenuation and leakage. In this paper, we
propose a one-step approach (OSA) that iteratively filters noise
and estimates NSSs alongside trends and seasonal signals
starting from unfiltered regional TWSA signals, where the
covariance matrices of NSSs are populated using distance-based
exponential functions. The non-seasonal TWSA signals in
Southeastern China, estimated by OSA from April 2002 to December
2024, effectively preserves signal integrity with reduced
spatial leakage and enhanced signal strength, aligning closely
with those of the RL06 mascon products from CSR (Center for
Space Research) and JPL (Jet Propulsion Laboratory), achieving
Nash-Sutcliffe Efficiency (NSE) of 0.91 and 0.90. Moreover, we
introduce a Standardized NSS (SNSS) index from OSA, which
enhances the consistency with the standardized streamflow index,
identifying the extreme wetness in pearl river basin (PRB) and
Southeastern River Basin (SERB) from August 2015 to June 2016,
and the extreme drought in Middle and Lower Yangtze River Basin
(MLYRB) from July 2022 to April 2023. SNSS also exhibits
enhanced correlations with nine key climate indices, especially
for ENSO (El Ni{\~n}o-Southern Oscillation) and TIOS (Tropical
Indian Ocean Sea Surface Temperature Anomaly), with cross-
correlations of 0.99 and 0.96 for PRB, 0.97 and 0.94 for SERB
during extreme wetness, and 0.96 and 0.90 for MLYRB during
extreme drought.}",
doi = {10.1088/1748-9326/adeff4},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025ERL....20h4071Z},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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