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| 1 | Weather induced subtidal flows through multiple inlets of an arctic microtidal lagoon显示文摘Estuarine processes in the arctic lagoons are among the least studied but important subjects, especially considering the rapid warming of arctic water which may change the length of ice-free period in the summer. In this paper, wind-driven exchange flows in the micro-tidal Elson Lagoon of northern Alaska with multiple inlets of contrasting widths and depths are studied with in situ observations, statistical analysis, numerical experiments, a regression model on the basis of dynamics, and remote sensing data. Water velocity profiles were obtained from a bottom deployed acoustic Doppler current profiler(ADCP) in the northwestern Eluitkak Pass connecting the Beaufort Sea to the Elson Lagoon during a 4.9 day ice-free period in the summer of 2013. The subtidal flow is found correlated with wind(R^2 value ~96%). Frequently occurring east, northeast and north winds from the arctic atmospheric high-and low-pressure systems push water from the Beaufort Sea into the lagoon through the wide inlets on the eastern side of the lagoon, resulting in an outward flow against the wind at the narrow northwestern inlet. The counter-wind flow is a result of an uneven wind forcing acting through the asymmetric inlets and depth,an effect of 'torque' or vorticity. Under northwest wind, the exchange flow at the northwestern inlet reverses its direction, with inward flows through the upwind northwestern inlet and outward flows through the downwind eastern inlets. A regression model is established based on the momentum equations and Taylor series expansions. The model is used to predict flows in July and August of 2015 and July of 2017, supported by available Landsat satellite images. About 73%–80% of the time the flows at Eluitkak Pass are out of Elson Lagoon for the summer of 2015 and 2017. Numerical experiments are conducted to corroborate the findings and illustrate the effects under various wind conditions. A quasi-steady state balance between wind force and surface pressure gradient is confirmed. | Chunyan Li Kevin M.Boswell Nazanin Chaichitehrani Wei Huang Renhao Wu | 2019 | Acta Oceanologica Sinica2019，38，3： | 1 |
| 2 | The Arctic Sea Ice Thickness Change in CMIP6’s Historical Simulations显示文摘This study assesses sea ice thickness(SIT)from the historical run of the Coupled Model Inter-comparison Project Phase 6(CMIP6).The SIT reanalysis from the Pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS)product is chosen as the validation reference data.Results show that most models can adequately reproduce the climatological mean,seasonal cycle,and long-term trend of Arctic Ocean SIT during 1979-2014,but significant inter-model spread exists.Differences in simulated SIT patterns among the CMIP6 models may be related to model resolution and sea ice model components.By comparing the climatological mean and trend for SIT among all models,the Arctic SIT change in different seas during 1979-2014 is evaluated.Under the scenario of historical radiative forcing,the Arctic SIT will probably exponentially decay at-18%(10 yr)-1 and plausibly reach its minimum(equilibrium)of 0.47 m since the 2070s. | Lanying CHEN Renhao WU Qi SHU Chao MIN Qinghua YANG Bo HAN | 2023 | Advances in Atmospheric Sciences2023，40，12： | 0 |
| 3 | GmYSL7 controls iron uptake,allocation,and cellular response of nodules in soybean显示文摘Iron(Fe)is essential for DNA synthesis,photosynthesis and respiration of plants.The demand for Fe substantially increases during legumesrhizobia symbiotic nitrogen fixation because of the synthesis of leghemoglobin in the host and Fecontaining proteins in bacteroids.However,the mechanism by which plant controls iron transport to nodules remains largely unknown.Here we demonstrate that GmYSL7 serves as a key regulator controlling Fe uptake from root to nodule and distribution in soybean nodules.GmYSL7 is Fe responsive and GmYSL7 transports iron across the membrane and into the infected cells of nodules.Alterations of GmYSL7 substantially affect iron distribution between root and nodule,resulting in defective growth of nodules and reduced nitrogenase activity.GmYSL7 knockout increases the expression of GmbHLH300,a transcription factor required for Fe response of nodules.Overexpression of GmbHLH300 decreases nodule number,nitrogenase activity and Fe content in nodules.Remarkably,GmbHLH300 directly binds to the promoters of ENOD93 and GmLbs,which regulate nodule number and nitrogenase activity,and represses their transcription.Our data reveal a new role of GmYSL7 in controlling Fe transport from host root to nodule and Fe distribution in nodule cells,and uncover a molecular mechanism by which Fe affects nodule number and nitrogenase activity. | Xinying Wu Yongliang Wang Qiaohan Ni Haizhen Li Xuesong Wu Zhanxin Yuan Renhao Xiao Ziyin Ren Jingjing Lu Jinxia Yun Zhijuan Wang Xia Li | 2023 | Journal of Integrative Plant Biology2023，65，1： | 0 |
| 4 | A general spatial-temporal framework for short-term building temperature forecasting at arbitrary locations with crowdsourcing weather data显示文摘Weather forecasting has been a critical component to predict and control building energy consumption for better building energy management.Without accessibility to other data sources,the onsite observed temperatures or the airport temperatures are used in forecast models.In this paper,we present a novel approach by utilizing the crowdsourcing weather data from neighboring personal weather stations(PWS)to improve the weather forecast accuracy around buildings using a general spatial-temporal modeling framework.The final forecast is based on the ensemble of local forecasts for the target location using neighboring PWSs.Our approach is distinguished from existing literature in various aspects.First,we leverage the crowdsourcing weather data from PWS in addition to public data sources.In this way,the data is at much finer time resolution(e.g.,at 5-minute frequency)and spatial resolution(e.g.,arbitrary location vs grid).Second,our proposed model incorporates spatial-temporal correlation information of weather variables between the target building and a set of neighboring PWSs so that underlying correlations can be effectively captured to improve forecasting performance.We demonstrate the performance of the proposed framework by comparing to the benchmark models on temperature forecasting for a building located at an arbitrary location at San Antonio,Texas,USA.In general,the proposed model framework equipped with machine learning technique such as Random Forest can improve forecasting by 50%compares with persistent model and has 90%chance to outperform airport forecast in short-term forecasting.In a real-time setting,the proposed model framework can provide more accurate temperature forecasting results compared with using airport temperature forecast for most forecast horizon.Moreover,we analyze the sensitivity of model parameters to gain insights on how crowdsourcing data from the neighboring personal weather stations impacts forecasting performance.Finally,we implement our model in other cities such as Syracuse and Chicago to test the model’s performance in different landforms and climate types. | Reisa F.Widjaja Wenbo Wu Zhi Zhou Renhao Sun Hannah C.Fontenot Bing Dong | 2023 | Building Simulation2023，16，6： | 0 |
| 5 | Wave hindcast under tropical cyclone conditions in the South China Sea:sensitivity to wind fields显示文摘Reliable wave information is critical for marine engineering.Numerical wave models are useful tools to obtain wave information with continuous spatiotemporal distributions.However,the accuracy of model results highly depends on the quality of wind forcing.In this study,we utilize observations from five buoys deployed in the northern South China Sea from August to September 2017.Notably,these buoys successfully recorded wind field and wave information during the passage of five tropical cyclones of different intensities without sustaining any damage.Based on these unique observations,we evaluated the quality of four widely used wind products,namely CFSv2,ERA5,CCMP,and ERAI.Our analysis showed that in the northern South China Sea,ERA5 performed best compared to buoy observations,especially in terms of maximum wind speed values at 10 m height(U10),extreme U10 occurrence time,and overall statistical indicators.CFSv2 tended to overestimate non-extreme U10 values.CCMP showed favorable statistical performance at only three of the five buoys,but underestimated extreme U10 values at all buoys.ERAI had the worst performance under both normal and tropical cyclone conditions.In terms of wave hindcast accuracy,ERA5 outperformed the other reanalysis products,with CFSv2 and CCMP following closely.ERAI showed poor performance especially in the upper significant wave heights.Furthermore,we found that the wave hindcasts did not improve with increasing spatiotemporal resolution,with spatial resolution up to 0.5°.These findings would help in improving wave hindcasts under extreme conditions. | Liqun Jia Shimei Wu Bo Han Shuqun Cai Renhao Wu | 2023 | Acta Oceanologica Sinica2023，42，10： | 0 |
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