Influence of Qinghai-Xizang Plateau snow cover on interannual variability of Western North Pacific tropical cyclone tracks

Track density function(TDF)was computed for all Western North Pacific tropical cyclones(WNP TCs)tracks from 1950 to 2018,and the TDFs were further investigated using principal component analysis(PCA)to analyze their inter-annual spatial and temporal variability.Then,the relationships between each empirical orthogonal function(EOF)mode and the typhoon count,typhoon landfall count,track pattern,and the Qinghai-Xizang Plateau snow cover(QXPSC)were examined,and the possible physical mechanisms implied by the statistical relationship were explored.The results show the QXPSC significantly affected the surface-atmosphere heat exchange through snow cover(SC)level,then changed the East Asian summer monsoon regional circulation pattern,influenced the subtropical high-pressure system strength and location,and ultimately affected the WNP TCs track patterns and thus changed their landfall locations.

伊洛河上游流域退耕还林/还草对蓝水绿水分配的影响

土地利用变化对区域水循环具有重要影响,土地利用决策就是水资源决策,这一命题已经被诸多研究证实并被研究者和决策者所认识。本文以黄河流域中游的伊洛河上游流域为研究区域,应用分布式流域农业生态水文模型SWAT(Soil and Water Assessment Tool),在我国退耕还林还草的生态恢复和重建的重大背景下,分别设置了6种不同的土地利用变化情景,基于蓝水和绿水的视角,研究土地利用/覆被对流域水循环的影响。本文对SWAT模型输出的月径流结果进行了率定和验证,证明该模型对研究流域水文循环的模拟达到了可接受水平的准确性与合理性。采用单因素方差分析和多重比较,分析基于不同水文年型下土地利用变化对各水文要素变化的影响。结果表明:1)2010 2015年多年平均降水资源总量为34.94亿m^3,多年平均蓝水绿水资源总量为34.09亿m^3,蓝水资源量占多年蓝水绿水资源总量的33.73%,绿水资源量占多年蓝水绿水资源总量的66.27%。2)不同情景退耕还林或还草,蓝水资源量均减少,绿水流均增加,绿水库均减少。在丰水年和平水年,退耕还林还草对蓝水资源量中地表径流分量影响较明显。该结论对于加深认识伊洛河上游流域土地利用/覆被和水资源的相互关系具有一定意义,为该区域高效合理利用水土资源提供了科学依据。

Study on Oil Film Model of Electronic Fuel Injection Motorcycle Engine Cylinder

Based on the principles of heat transfer,an oil film model in the engine cylinder was established.Under the condition of cold state,the influence of factors such as engine fuel injection,fuel drop point,cylinder inner wall temperature,and inlet fluid on the oil film is comprehensively considered to establish an oil film quality prediction model.Based on the measurement of the compensation oil quantity in the transition conditions,the variation of the oil film during the transition is analyzed.The experimental results show that the velocity of the air-flow in the intake port and the temperature and pressure on the wall of the intake port are the main factors affecting the oil film in the cylinder.Based on the abovementioned experimental and theoretical studies,an oil film distribution model for each cycle of the transition condition was established based on the engine inlet oil film model.The experimental measurement curve and model prediction curve for the fuel compensation per cycle in the transition condition from 10%load to 30%load.The model established can be in good agreement with the experimental results and meet the fuel compensation trend in the transition condition.While realizing the fuel compensation for the transient conditions,this work is definitely helpful to achieve accurate control of the air-fuel ratio.

2D magnetotelluric inversion based on ResNet

In this study,a deep learning algorithm was applied to two-dimensional magnetotelluric(MT)data inversion.Compared with the traditional linear iterative inversion methods,the MT inversion method based on convolutional neural networks(CNN)does not rely on the selection of the initial model parameters and does not fall into the local optima.Although the CNN inversion models can provide a clear electrical interface division,their inversion results may remain prone to abrupt electrical interfaces as opposed to the actual underground electrical situation.To solve this issue,a neural network with a residual network architecture(ResNet-50)was constructed in this study.With the apparent resistivity and phase pseudo-section data as the inputs and with the resistivity parameters of the geoelectric model as the training labels,the modified ResNet-50 model was trained end-to-end for producing samples according to the corresponding production strategy of the study area.Through experiments,the training of the ResNet-50 with the dice loss function effectively solved the issue of over-segmentation of the electrical interface by the cross-entropy function,avoided its abrupt inversion,and overcame the computational inefficiency of the traditional iterative methods.The proposed algorithm was validated against MT data measured from a geothermal field prospect in Huanggang,Hubei Province,which showed that the deep learning method has opened up broad prospects in the field of MT data inversion.

SIMULATION OF OCEAN RESPONSES TO AN IDEALIZED LANDFALLING TROPICAL CYCLONE USING A COUPLED ATMOSPHERE-WAVE-OCEAN MODELING SYSTEM

Oceanic responses to a hypothetical landfalling tropical cyclone(TC) are studied by using a coupled atmosphere-wave-ocean modeling system(CAWOMS). A set of experiments are conducted to compare the effects of atmosphere-wave-ocean interaction on ocean responses in coastal and deep waters. The results show that in a three-way coupled atmosphere-wave-ocean system, the resonse to a tropical cyclone is considerably different in coastal water and deep water. In a three-way coupled system, air-sea interactions tend to increase coastal storm surge, inundation, significant wave heights and ocean currents in shallow coastal areas as a result of waveenhanced air-sea heat and moisture fluxes. But the change is little in sea surface temperature and mixed-layer structure due to the well-mixed nature in the coastal zone. In contrast, in a three-way coupled system, air-sea interactions enhance sea surface cooling, increase mixed layer depth in deep waters largely due to the tendency of a wave-enhanced TC to induce strong mixing and entrainment in the upper ocean. A stronger TC also strengthens the surface currents and significant wave height in the offshore waters. The inclusion of waves in air-sea interactions fundamentally changes the dynamic and thermodynamic coupling between tropical cyclone and the underlying ocean. In the absence of TC-wave consideration, a negative feedback between the TC and the upper ocean mixed layer results in a weakening of the TC system and a cooling in the offshore upper ocean and therefore reduces coastal storm surge, flooding areas, significant wave height and ocean currents. Only in a TC-waveocean three-way coupled system, air-sea interaction may correspond to a stronger TC due to wave-induced airsea heat and moisture fluxes which compensate the effect of negative feedback between the TC and the upper ocean. In coastal waters, the negative feedback between the TC and the ocean mixed layer is fairly weak. Airsea interaction is dominated by the positive TC-wave feedback. As a result, air-sea interaction increases coastal storm surge, inundation, currents and significant wave height.

MODELING TROPICAL CYCLONE INDUCED STREAM FLOW IN TAR PAMLICO RIVER OF NORTH CAROLINA

In order to better understand and simulate large coastal watershed hydrology and hydro-meteorological processes associated with tropical cyclone(TC) induced inland flooding, the Annualized Agricultural Nonpoint Source Pollution Model(Ann AGNPS) with Muskingum channel routing has been applied to the Tar-Pamlico river basin in North Carolina, USA. The study focuses on three major hydro-meteorological processes: 1) largescale atmospheric environment, 2) watershed hydrological processes and 3) groundwater response. The modeling results indicate that although the Ann AGNPS model can perform well in predicting the total amount of watershed runoff, channel routing is needed to improve the hydrographs of flow discharge during hurricane events. Sensitivity analysis of soil saturated hydrological conductivity(K_s) indicates that both base flow and event total runoff are sensitive to K_s. Base flow increases as K_s increases when 0 < K_s ≤ 15 m/day, but decreases slightly when K_s > 15 m/day. Peak runoff exponentially decreases as K_s increases. The results also show that without the preceding Hurricane Dennis, the outlet discharge as a result of Hurricane Floyd would have been as much as 37% lower than that caused by the combined Dennis-Floyd effect.