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Poyang Lake is a dynamic floodplain lake system that exhibits complex water level fluctuations and experiences significant regime changes over space and time, which remains to be further explored. This study used the variational mode decomposition (VMD) model to decompose the Poyang Lake's water levels from 1960 to 2022 at four key stations into six intrinsic mode functions (IMFs), namely IMF1–IMF6, representing variations on different time scales. The results present significant spatiotemporal heterogeneity. The multi‐year variation (IMF1) accounts for 5.6%–12.4% of the total variation and displays a northward decreasing trend, reflecting the lake's river‐like characteristics. The spectrum of IFM1 also reveals a significant 3.6‐year fluctuation mainly attributed to the tributary inflow, especially the Ganjiang River. The IMF1 differences between stations show abrupt decreases since the 2000s, indicating the impact of concentrated sand mining activities on the northern and central regions. The annual variation (IMF2) is the most prominent, contributing 76.1%–88.4% of the total variation, and shows a southward attenuation trend, likely due to the weakening influence of the Yangtze River flow. The intra‐annual scale (IMF3–IMF6) represents 6.0%–11.5% of the total variation and exhibits less spatial difference compared to the multi‐year and annual variations. The VMD model effectively separates the water level signals into different frequency bands, providing insights into the complex interactions between the lake, tributaries, and Yangtze River, as well as the impacts of human activities like sand mining, enhancing understanding of floodplain lake dynamics. The results also imply the importance of coping with the water level decline of Poyang Lake. [ABSTRACT FROM AUTHOR]

Air–sea heat flux is one of the most important factors that affects ocean circulation, weather, and climate. Satellite remote sensing could serve as an important supplement to the sparse in situ observations for heat flux estimations. In this study, we analyze the uncertainty of the turbulent heat fluxes derived from wind speed measured by the Cyclone Global Navigation Satellite System (CYGNSS) over the global tropical oceans at different time scales. In terms of spatial distribution, there is large uncertainty (approximately 50 to 85 W·m−2 in the RMSE) near the equator in the western Pacific Ocean, the Arabian Sea, the Bay of Bengal, and near the Gulf of Guinea. The turbulent heat fluxes are in agreement with the buoys in representing the intraseasonal and seasonal variability, but more specific regional validations are needed for revealing the synoptic and sub-synoptic phenomena and the diurnal cycle. The uncertainty of the CYGNSS wind speed contributes approximately 50–57% to the uncertainty of the estimation of turbulent heat fluxes at the frequency band with a typical period of 3–7 days. In addition, the input sea surface temperature, rather than the wind speed, results in differences in the estimation of the monthly mean turbulent heat fluxes in the tropical Atlantic Ocean based on the COARE 3.5 algorithm. In conclusion, although the CYGNSS-derived turbulent heat fluxes are basically in good agreement with the in situ observations, our analysis highlights the importance of considering the limitations of these datasets, particularly in high wind speed conditions and for higher-frequency variations, including at synoptic, sub-synoptic, and diurnal time scales. [ABSTRACT FROM AUTHOR]

The accurate estimation of ocean tide loading displacements is essential and necessary for geodesy, oceanic and geophysical studies. It is common knowledge that K1 and K2 tidal constituents estimated from Global Positioning System (GPS) observations are unsatisfactory because their tidal periods are nearly same to the revisit cycle or orbital period of GPS constellation. To date, this troublesome problem is not fully solved. In this paper, we revisit this important issue and develop a novel method based on the unique characteristic of tidal waves to separate GPS-system errors from astronomical K1/K2 tides. The well-known credo of smoothness indicates that tidal admittances of astronomical constituents in a narrow band can be expressed as smooth functions of tidal frequencies, while the interference of GPS-system errors seriously damages the smooth nature of observed tidal admittances. Via quadratic fitting, smooth functions of tidal frequencies for tidal admittances can be determined, thus, astronomical K1 and K2 tides can be interpolated using fitted quadratic functions. Three GPS stations are selected to demonstrate our method because of their typicality in terms of poor estimates of K1/K2 tidal parameters related to GPS-system errors. After removing GPS-systematical contributions based on our method, corrected K1/K2 tides at three GPS stations are much closer to the modeled K1/K2 tides from FES2014, which is one of the most accurate tide models. Furthermore, the proposed method can be easily applied to other areas to correct GPS-system errors because their smooth nature is valid for global tidal signals. [ABSTRACT FROM AUTHOR]