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Zhihua Zheng, Ramsey R. Harcourt, and Eric A. D’Asaro


Monin–Obukhov similarity theory (MOST) provides important scaling laws for flow properties in the surface layer of the atmosphere and has contributed to most of our understanding of the near-surface turbulence. The prediction of near-surface vertical mixing in most operational ocean models is largely built upon this theory. However, the validity of MOST in the upper ocean is questionable due to the demonstrated importance of surface waves in the region. Here we examine the validity of MOST in the statically unstable oceanic surface layer, using data collected from two open ocean sites with different wave conditions. The observed vertical temperature gradients are found to be about half of those predicted by MOST. We hypothesize this is attributable to either the breaking of surface waves, or Langmuir turbulence generated by the wave–current interaction. Existing turbulence closure models for surface wave breaking and for Langmuir turbulence are simplified to test these two hypotheses. Although both models predict reduced temperature gradients, the simplified Langmuir turbulence model matches observations more closely, when appropriately tuned.

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Guang-Yu Shi, Tadahiro Hayasaka, Atsumu Ohmura, Zhi-Hua Chen, Biao Wang, Jian-Qi Zhao, Hui-Zheng Che, and Li Xu


Solar radiation is one of the most important factors affecting climate and the environment. Routine measurements of irradiance are valuable for climate change research because of long time series and areal coverage. In this study, a set of quality assessment (QA) algorithms is used to test the quality of daily solar global, direct, and diffuse radiation measurements taken at 122 observatories in China during 1957–2000. The QA algorithms include a physical threshold test (QA1), a global radiation sunshine duration test (QA2), and a standard deviation test applied to time series of annually averaged solar global radiation (QA3). The results show that the percentages of global, direct, and diffuse solar radiation data that fail to pass QA1 are 3.07%, 0.01%, and 2.52%, respectively; the percentages of global solar radiation data that fail to pass the QA2 and QA3 are 0.77% and 0.49%, respectively. The method implemented by the Global Energy Balance Archive is also applied to check the data quality of solar radiation in China. Of the 84 stations with a time series longer that 20 yr, suspect data at 35 of the sites were found. Based on data that passed the QA tests, trends in ground solar radiation and the effect of the data quality assessment on the trends are analyzed. There is a decrease in ground solar global and direct radiation in China over the years under study. Although the quality assessment process has significant effects on the data from individual stations and/or time periods, it does not affect the long-term trends in the data.

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He Sun, Tandong Yao, Fengge Su, Zhihua He, Guoqiang Tang, Ning Li, Bowen Zheng, Jingheng Huang, Fanchong Meng, Tinghai Ou, and Deliang Chen


Precipitation is one of the most important atmospheric inputs to hydrological models. However, existing precipitation datasets for the Third Pole (TP) basins show large discrepancies in precipitation magnitudes and spatiotemporal patterns, which poses a great challenge to hydrological simulations in the TP basins. In this study, a gridded (10 km×10 km) daily precipitation dataset is constructed through a random forest-based machine learning algorithm (RF algorithm) correction of the ERA5 precipitation estimates based on 940 gauges in 11 upper basins of TP for 1951–2020. The data set is evaluated by gauge observations at point scale, and is inversely evaluated by the Variable Infiltration Capacity hydrological model linked with a glacier melt algorithm (VIC-Glacier). The corrected ERA5 (ERA5_cor) agrees well with gauge observations after eliminating the severe overestimation in the original ERA5 precipitation. The corrections greatly reduce the original ERA5 precipitation estimates by 10%–50% in 11 basins of the TP, and present more details on precipitation spatial variability. The inverse hydrological model evaluation demonstrates the accuracy and rationality, and we provide an updated estimate of runoff components contribution to total runoff in seven upper basins in the TP based on the VIC-Glacier model simulations with the ERA5_cor precipitation. This study provides good precipitation estimates with high spatiotemporal resolution for 11 upper basins in the TP, which are expected to facilitate the hydrological modeling and prediction studies in this high mountainous region.

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