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Mengnan Zhao, Rui M. Ponte, Ou Wang, and Rick Lumpkin

Abstract

Properly fitting ocean models to observations is crucial for improving model performance and understanding ocean dynamics. Near-surface velocity measurements from the Global Drifter Program (GDP) contain valuable information about upper-ocean circulation and air–sea fluxes on various space and time scales. This study explores whether GDP measurements can be used for usefully constraining the surface circulation from coarse-resolution ocean models, using global solutions produced by the consortium for Estimating the Circulation and Climate of the Ocean (ECCO) as an example. To address this problem, a careful examination of velocity data errors is required. Comparisons between an ECCO model simulation, performed without any data constraints, and GDP and Ocean Surface Current Analyses Real-Time (OSCAR) velocity data, over the period 1992–2017, reveal considerable differences in magnitude and pattern. These comparisons are used to estimate GDP data errors in the context of the time-mean and time-variable surface circulations. Both instrumental errors and errors associated with limitations in model physics and resolution (representation errors) are considered. Given the estimated model–data differences, errors, and signal-to-noise ratios, our results indicate that constraining ocean-state estimates to GDP can have a substantial impact on the ECCO large-scale time-mean surface circulation over extensive areas. Impact of GDP data constraints on the ECCO time-variable circulation would be weaker and mainly limited to low latitudes. Representation errors contribute substantially to degrading the data impacts.

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Rui Wang, Xin Yan, Zhenguo Niu, and Wei Chen

Abstract

Water surface temperature is a direct indication of climate change. However, it is not clear how China’s inland waters have responded to climate change in the past using a consistent method on a national scale. In this study, we used Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2000 to 2015 to study the temporal and spatial variation characteristics of water surface temperature in China using the wavelet transform method. The results showed the following: 1) the freezing date of China inland water has shown a significant delaying trend during the past 16 years with an average rate of −1.5 days yr−1; 2) the shift of the 0°C isotherm position of surface water across China has clear seasonal changes, which first moved eastward about 25° and northward about 15°, and then gradually moved back after the year 2009; 3) during the past 16 years, the 0°C isotherm of China’s surface water has gradually moved north by about 0.09° in the latitude direction and east by about 1° in the longitude direction; and 4) the interannual variation of water surface temperature in 17 lakes of China showed a similar fluctuation trend that increased before 2010, and then decreased. The El Niño and La Niña around 2010 could have impacts on the turning point of the annual variation of water surface temperature. This study validated the response of China’s inland surface water to global climate change and improved the understanding of the wetland environment’s response to climate change.

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Guihua Wang, Rui Xin Huang, Jilan Su, and Dake Chen

Abstract

The dynamic influence of thermohaline circulation on wind-driven circulation in the South China Sea (SCS) is studied using a simple reduced gravity model, in which the upwelling driven by mixing in the abyssal ocean is treated in terms of an upward pumping distributed at the base of the upper layer.

Because of the strong upwelling of deep water, the cyclonic gyre in the northern SCS is weakened, but the anticyclonic gyre in the southern SCS is intensified in summer, while cyclonic gyres in both the southern and northern SCS are weakened in winter. For all seasons, the dynamic influence of thermohaline circulation on wind-driven circulation is larger in the northern SCS than in the southern SCS. Analysis suggests that the upwelling associated with the thermohaline circulation in the deep ocean plays a crucial role in regulating the wind-driven circulation in the upper ocean.

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Lei Wang, Zhi-Jun Yao, Li-Guang Jiang, Rui Wang, Shan-Shan Wu, and Zhao-Fei Liu

Abstract

The spatiotemporal changes in 21 indices of extreme temperature and precipitation for the Mongolian Plateau from 1951 to 2012 were investigated on the basis of daily temperature and precipitation data from 70 meteorological stations. Changes in catastrophic events, such as droughts, floods, and snowstorms, were also investigated for the same period. The correlations between catastrophic events and the extreme indices were examined. The results show that the Mongolian Plateau experienced an asymmetric warming trend. Both the cold extremes and warm extremes showed greater warming at night than in the daytime. The spatial changes in significant trends showed a good homogeneity and consistency in Inner Mongolia. Changes in the precipitation extremes were not as obvious as those in the temperature extremes. The spatial distributions in changes of precipitation extremes were complex. A decreasing trend was shown for total precipitation from west to east as based on the spatial distribution of decadal trends. Drought was the most serious extreme disaster, and prolonged drought for longer than 3 yr occurred about every 7–11 yr. An increasing trend in the disaster area was apparent for flood events from 1951 to 2012. A decreasing trend was observed for the maximum depth of snowfall from 1951 to 2012, with a decreased average maximum depth of 10 mm from the 1990s.

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Xuejin Wang, Baoqing Zhang, Feng Li, Xiang Li, Xuliang Li, Yibo Wang, Rui Shao, Jie Tian, and Chansheng He

Abstract

From 1998 to the present, the Chinese government has implemented numerous large-scale ecological programs to restore ecosystems and improve environmental protection in the agro-pastoral ecotone of northern China (APENC). However, it remains unclear how vegetation restoration modulates intraregional moisture cycles and changes regional water balance. To fill this gap, we first investigated the variation in precipitation (P) from the China Meteorological Forcing Dataset and evapotranspiration (ET) estimated using the Priestley–Taylor Jet Propulsion Laboratory model under two scenarios: dynamic vegetation (DV) and no dynamic vegetation (no-DV). We then used the dynamic recycling model to analyze the changes in precipitation recycling ratio (PRR). Finally, we examined how vegetation restoration modulates intraregional moisture recycling to change the regional water cycle in APENC. Results indicate P increased at an average rate of 4.42 mm yr−2 from 1995 to 2015. ET with DV exhibited a significant increase at a rate of 1.57, 3.58, 1.53, and 1.84 mm yr−2 in the four subregions, respectively, compared with no-DV, and the annual mean PRR values were 10.15%, 9.30%, 11.01%, and 12.76% in the four subregions, and significant increasing trends were found in the APENC during 1995–2015. Further analysis of regional moisture recycling shows that vegetation restoration does not increase local P directly, but has an indirect effect by enhancing moisture recycling process to produce more P by increasing PRR. Our findings show that large-scale ecological restoration programs have a positive effect on local moisture cycle and precipitation.

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Xing Chen, Mukesh Kumar, Rui Wang, Adam Winstral, and Danny Marks

Abstract

Previous studies have shown that gauge-observed daily streamflow peak times (DPTs) during spring snowmelt can exhibit distinct temporal shifts through the season. These shifts have been attributed to three processes: 1) melt flux translation through the snowpack or percolation, 2) surface and subsurface flow of melt from the base of snowpacks to streams, and 3) translation of water flux in the streams to stream gauging stations. The goal of this study is to evaluate and quantify how these processes affect observed DPTs variations at the Reynolds Mountain East (RME) research catchment in southwest Idaho, United States. To accomplish this goal, DPTs were simulated for the RME catchment over a period of 25 water years using a modified snowmelt model, iSnobal, and a hydrology model, the Penn State Integrated Hydrologic Model (PIHM). The influence of each controlling process was then evaluated by simulating the DPT with and without the process under consideration. Both intra- and interseasonal variability in DPTs were evaluated. Results indicate that the magnitude of DPTs is dominantly influenced by subsurface flow, whereas the temporal shifts within a season are primarily controlled by percolation through snow. In addition to the three processes previously identified in the literature, processes governing the snowpack ripening time are identified as additionally influencing DPT variability. Results also indicate that the relative dominance of each control varies through the melt season and between wet and dry years. The results could be used for supporting DPTs prediction efforts and for prioritization of observables for DPT determination.

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Rui Mao, Dao-Yi Gong, Tianbao Zhao, Wenshan Wang, and Jing Yang

Abstract

High relative humidity (HRH) is defined as a relative humidity of at least 80%, which is often associated with the occurrence of cloud layers. Thus, the frequency of HRH and its changes in the troposphere may be related to the occurrence frequency of cloud layers and their changes. In this study, trends in the frequency of HRH (defined as days with relative humidity ≥80%) over China from the surface to the midtroposphere (≥400 hPa) from 1979 to 2012 were analyzed using a homogenized humidity dataset for spring (March–May), summer (June–August), autumn (September–November), and winter (December–February). The results for the ground level indicate decreasing trends at most stations in southeastern China in spring and in northern China in summer. In the lower troposphere (850 and 700 hPa), most stations over China exhibit positive trends in summer, autumn, and winter. For the midtroposphere (500–400 hPa), increasing trends dominate over China in spring, summer, and autumn. Finally, six reanalysis datasets, the NCEP–NCAR, NCEP–DOE, CFSR, ERA-Interim, MERRA, and JRA-55 datasets, were compared with the observed increasing trends in HRH frequency in the low-to-middle troposphere. Similar increasing trends in HRH frequency in the reanalysis datasets and the homogenized humidity data are observed in certain seasons and for certain regions. These results are consistent with the increasing low-to-middle cloud amounts in recent decades.

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Xiaowei Wang, Shiqiu Peng, Zhiyu Liu, Rui Xin Huang, Yu-Kun Qian, and Yineng Li

Abstract

By taking into account the contributions of both locally and remotely generated internal tides, the tidal mixing in the Luzon Strait (LS) and the South China Sea (SCS) is investigated through internal-tide simulation and energetics analysis. A three-dimensional nonhydrostatic high-resolution model driven by four primary tidal constituents (M2, S2, K1, and O1) is used for the internal-tide simulation. The baroclinic energy budget analysis reveals that the internal tides radiated from the LS are the dominant energy source for the tidal dissipation in the SCS. In the LS, the estimated depth-integrated turbulent kinetic energy dissipation exceeds O(1) W m−2 atop the two subsurface ridges, with a dissipation rate of >O(10−7) W kg−1 and diapycnal diffusivity of ~O(10−2) m2 s−1. In the SCS, the most intense turbulence occurs in the deep-water basin with a dissipation rate of O(10−8–10−6) W kg−1 and diapycnal diffusivity of O(10−3–10−1) m2 s−1 within the ~2000-m water column above the seafloor as well as in the shelfbreak region with a dissipation rate of O(10−7–10−6) W kg−1 and diapycnal diffusivity of O(10−4–10−3) m2 s−1. These estimated values are consistent with observations reported in previous studies and are at least one order of magnitude larger than those based solely on locally generated internal tides.

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Jiamin Wang, Xiaodan Guan, Yuping Guan, Kaiwei Zhu, Rui Shi, Xiangning Kong, and Shuyang Guo

Abstract

Due to global warming, the lengths of the four seasons, which are always taken as constant values, have experienced significant variations with rising temperature. Such changes play different roles on regional climate change, with the most significant effect on drylands. To guarantee local crop yields and preserve ecosystems, the identification of the changes of the four seasons in drylands is important. Our results show that, relative to humid lands, changing trends in lengths of spring, summer and autumn were particularly enhanced in drylands of the Northern Hemisphere mid-latitudes during 1951-2020. In this period, summer length has increased by 0.51 day per year, while spring and autumn lengths have contracted by 0.14 and 0.14 day per year, respectively. However, the enhanced changes in drylands did not appear in winter length. Such changes of spring, summer and autumn in drylands are dominated by internal variability over the entire study period, with a stronger external forcing effect on drylands than on humid lands. In drylands, the external forcing contributed to the changes in lengths of spring, summer and autumn by 30.1%, 42.2% and 29.4%, respectively. The external forcing has become an increasingly important component since 1990, with the ability to dominate all seasons in drylands after 2010. Nevertheless, only one out of the 16 Coupled Model Intercomparison Project Phase 6 (CMIP6) models used in this study can capture the enhanced changes in the lengths of spring, summer and autumn in drylands. Further investigation on the local effects of changes in seasons on agriculture and ecosystem would be needed, especially for the fragile regions.

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Kang Xu, Rui Xin Huang, Weiqiang Wang, Congwen Zhu, and Riyu Lu

Abstract

The interannual fluctuations of the equatorial thermocline are usually associated with El Niño activity, but the linkage between the thermocline modes and El Niño is still under debate. In the present study, a mode function decomposition method is applied to the equatorial Pacific thermocline, and the results show that the first two dominant modes (M1 and M2) identify two distinct characteristics of the equatorial Pacific thermocline. The M1 reflects a basinwide zonally tilted thermocline related to the eastern Pacific (EP) El Niño, with shoaling (deepening) in the western (eastern) equatorial Pacific. The M2 represents the central Pacific (CP) El Niño, characterized by a V-shaped equatorial Pacific thermocline (i.e., deep in the central equatorial Pacific and shallow on both the western and eastern boundaries). Furthermore, both modes are stable and significant on the interannual time scale, and manifest as the major feature of the thermocline fluctuations associated with the two types of El Niño events. As good proxies of EP and CP El Niño events, thermocline-based indices clearly reveal the inherent characteristics of subsurface ocean responses during the evolution of El Niño events, which are characterized by the remarkable zonal eastward propagation of equatorial subsurface ocean temperature anomalies, particularly during the CP El Niño. Further analysis of the mixed layer heat budget suggests that the air–sea interactions determine the establishment and development stages of the CP El Niño, while the thermocline feedback is vital for its further development. These results highlight the key influence of equatorial Pacific thermocline fluctuations in conjunction with the air–sea interactions, on the CP El Niño.

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