No abstract

No abstract

A three dimensional coupled biophysical model was used to examine the supply of oceanic nutrients to the shelf of the East China Sea (ECS) and its role in primary production over the shelf. The model consisted of two modules: the hydrodynamic module was based on a nested model with a horizontal resolution of 1/18 degree, whereas the biological module was a low trophic level ecosystem model including two types of phytoplankton, three elements of nutrients, and biogenic organic material. Model results suggested that seasonal variation in chlorophyll-<i>a</i> had a strong regional dependence over the shelf of the ECS. The area with high chlorophyll-<i>a</i> appears firstly at the outer shelf in winter, and gradually migrates toward the inner shelf (offshore region of Changjiang estuary) from spring to summer. Vertically, chlorophyll-<i>a</i> was generally homogenous from the coastal zone to the inner shelf. In the middle and outer shelves, high chlorophyll-<i>a</i> appeared in the surface in spring but moved to the subsurface from summer to early autumn. The annual averaged onshore flux across the shelf break was estimated to be 1.53 Sv for volume, 9.4 kmol s⁻¹ for DIN, 0.7 kmol s⁻¹ for DIP, and 18.2 kmol s⁻¹ for silicate, which are supplied mainly from the northeast of Taiwan and southwest of Kyushu. From calculations that artificially increased the concentration of nutrients in the Kuroshio water, the additional oceanic nutrients were distributed in the bottom layer from the shelf break to the region offshore of Changjiang estuary from spring to summer, and appeared in the surface layer from autumn to winter. The contribution of oceanic nutrients to primary production over the shelf was found not only in the surface layer (mainly at the outer shelf and shelf break in winter and in the region offshore of Changjiang estuary in summer) but also in the subsurface layer over the shelf from spring to autumn

Abstract:Understanding the spatial variation in annual actual evapotranspiration (AET) and its influencing factors is crucial for a better understanding of hydrological processes and water resources management. By synthesizing ecosystem-level observations of eddy-covariance flux sites in China (a total of 61 sites), we constructed the most complete AET dataset in China up to now. Based on this dataset, we quantified the statistic characteristics of AET and water budgets (defined as the ratio of AET to annual mean precipitation (MAP), AET/MAP) of terrestrial ecosystems in China. Results showed that AET differed significantly among both different vegetation types and climate types in China, with overall mean AET of 534.7±232.8 mm yr -1 . AET/MAP also differed significantly among different climate types, but there were no distinct differences in AET/MAP values across vegetation types, with mean AET/MAP of 0.82±0.28 for non-irrigated ecosystems. We further investigated how the main climatic factors and vegetation attributes control the spatial variation in AET. Our findings revealed that the spatial variation of AET in China was closely correlated with the geographical patterns of climate and vegetation, in which the effects of total annual net radiation (R n ), MAP and mean annual air temperature (MAT) were dominant. Thus, we proposed an empirical equation to describe the spatial patterns of AET in China, which could explain about 84% of the spatial variation in AET of terrestrial ecosystems in China. Based on the constructed dataset, we also evaluated the uncertainties of five published global evapotranspiration products in simulating 1392 Journal of Geographical Sciences site-specific AET in China. Results showed that large biases in site-specific AET values existed for all five global evapotranspiration products, which indicated that it is necessary to involve more observation data of China in their parameterization or validation, while our AET dataset would provide a data source for it.

Using high-frequency tide gauge observations from 1980 to 2017, we analyzed changes in extreme sea levels (ESLs) along the Chinese coast to examine whether extreme sea-level rise acceleration could be observed. The results indicated that the ESL has risen with fluctuations along the Chinese coast. The ESL also featured significant decadal variabilities. The ESL rise was accelerated at most tide gauges throughout the whole study period, especially after the 1980s, while the acceleration patterns varied with station location. The mean sea level (MSL) change was confirmed as the major driver of the ESL change according to the analysis. However, the skew surge may also have affected the extremes at many of the tide gauges, which was observed after detrending. The extreme/MSL had a significant positive correlation with the Atlantic Multidecadal Oscillation, which is supposed to affect the MSL through a combination of variation in sea surface temperature, pressure system, and wind. That sea level oscillation is dominated by Atlantic Multidecadal Oscillation should be taken into consideration when studying accelerations in the rate of ESLs and of MSLs along the Chinese coast.Other studies revealed that the long-term trend of MSL is nonlinear and that the MSL rise has accelerated in recent years