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Fusion sst from Infrared and Microwave Measurement of FY-3D Meteorological Satellite

Journal of Tropical Meteorology 2024年第1期30卷 89-96页

作者：张淼徐娜陈林 National Satellite Meteorological Center/National Center for Space Weather Beijing 100081 China Innovation Center for Fengyun Meteorological Satellite(FYSIC) Beijing 100081 China Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites China Meteorological AdministrationBeijing 100081 China

Sea surface temperature(sst)is one of the important parameters of global ocean and climate research,which can be retrieved by satellite infrared and passive microwave remote sensing *** satellite infrared sst offers high spatial resolution,it is limited by cloud *** the other hand,passive microwave sst provides all-weather observation but suffers from poor spatial resolution and susceptibility to environmental factors such as rainfall,coastal effects,and high wind *** achieve high-precision,comprehensive,and high-resolution sst data,it is essential to fuse infrared and microwave sst *** this study,data from the Fengyun-3D(FY-3D)medium resolution spectral imager II(MERSI-II)sst and microwave imager(MWRI)sst were ***,the accuracy of both MERSIII sst and MWRI sst was verified,and the latter was bilinearly interpolated to match the 5km resolution grid of MERSI *** pretreatment and quality control of MERSI sst and MWRI sst,a Piece-Wise Regression method was employed to correct biases in MWRI ***,sst data were selected based on spatial resolution and accuracy within a 3-day window of the analysis ***,an optimal interpolation method was applied to fuse the FY-3D MERSI-II sst and MWRI *** results demonstrated a significant improvement in spatial coverage compared to MERSI-II sst and MWRI ***,the fusion sst retained true spatial distribution details and exhibited an accuracy of–0.12±0.74℃compared to OSTIA *** study has improved the accuracy of FY satellite fusion sst products in China.

关键词： sst data fusion FY3 infrared microwave

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sst湍流模型的激波与可压缩效应改进

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航空学报 2024年第3期45卷 91-104页

作者：汪洪波曾宇熊大鹏杨揖心孙明波国防科技大学空天科学学院、高超声速冲压发动机技术重点实验室长沙410073

由于缺乏对某些重要流动特征的考虑,针对不可压流发展的标准sst湍流模型在描述超声速流场时存在明显的局限性。为改善sst模型在吸气式高超声速推进系统内流等复杂超声速流场中的预测精度,基于流动特征结构定向开展了激波和可压缩效应改... 详细信息

由于缺乏对某些重要流动特征的考虑,针对不可压流发展的标准sst湍流模型在描述超声速流场时存在明显的局限性。为改善sst模型在吸气式高超声速推进系统内流等复杂超声速流场中的预测精度,基于流动特征结构定向开展了激波和可压缩效应改进。通过激波/湍流边界层判别函数和可压缩效应判别函数定位标准sst模型参数或建模假设失效的区域,针对性地改进湍流模型。采用超声速平板边界层流动、超声速压缩拐角分离流动、超声速隔离段复杂激波串流动以及HIFiRE-2超声速内流等算例进行了测试,结果表明改进模型具有与标准sst模型一致的边界层预测能力,但显著提高了对激波干扰流动及逆压分离流的预测精度。

关键词： sst 湍流模型激波可压缩结构特征

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两种sst湍流模型改进方法适用性分析

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航空学报 2024年

作者：曾宇汪洪波连城阅杨揖心熊大鹏孙明波刘卫东国防科技大学空天科学学院高超声速技术实验室

雷诺平均湍流模型计算效率高，在工程应用上具有重要意义。传统模式与新型数据驱动模式湍流模型改进旨在提升湍流模型预测精度。然而，新型数据驱动模式大多针对低速流动，对其在高速流动中的应用、评估以及推广较少。两种模式对比性研... 详细信息

雷诺平均湍流模型计算效率高，在工程应用上具有重要意义。传统模式与新型数据驱动模式湍流模型改进旨在提升湍流模型预测精度。然而，新型数据驱动模式大多针对低速流动，对其在高速流动中的应用、评估以及推广较少。两种模式对比性研究的缺乏也给二者的合理利用产生了困扰。在标准雷诺应力剪切输运模型（shear-stress-transport,sst）框架下，一方面采用传统模式引入可压缩效应作用于输运方程耗散项，另一方面根据新型数据驱动模式引入耗散项修正。两种模式下的改进主要作用于流场中的剪切层。超声速压缩拐角和超声速凹腔斜坡算例的测试结果表明，新型数据驱动模式可以获得不同物理特征量之间初步的、可解释的非线性关系，但需经过传统模式的调整与再优化才能应用，具有一定的推广性，在捕捉某些湍流细节方面表现出优于传统模式的性能，但精度仍有待提高。

关键词：湍流模型 sst 数据驱动技术可压缩分离流符号回归

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东南亚海域HY-1C sst数据评估与校正

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数字海洋与水下攻防 2024年第1期7卷 87-97页

作者：杨梦孙伟富姜远驰自然资源部第一海洋研究所海洋物理与遥感研究室中国石油大学(华东)海洋与空间信息学院

海洋一号C卫星（HY-1C）是服务于海洋水色水温、海岸带和海洋灾害与环境监测的业务化应用卫星，是海洋遥感数据的重要来源，对中国HY-1C卫星红外辐射计在东南亚海域的sst观测数据开展评估与校正工作具有重要意义。本研究基于多源卫星SS... 详细信息

海洋一号C卫星（HY-1C）是服务于海洋水色水温、海岸带和海洋灾害与环境监测的业务化应用卫星，是海洋遥感数据的重要来源，对中国HY-1C卫星红外辐射计在东南亚海域的sst观测数据开展评估与校正工作具有重要意义。本研究基于多源卫星sst数据和ARGO浮标测量温度数据，对中国HY-1C卫星在东南亚海域的sst数据进行了质量评估和改进工作。HY-1C sst数据的质量评估结果表明：HY-1C白天的平均偏差、标准差和均方根误差分别为–0.73℃、1.38℃和1.56℃，夜晚数据偏差分别为–0.95℃、1.57℃和1.83℃。与其他同类红外辐射计的数据质量对比发现HY-1Csst数据精度低于其他红外辐射计。采用月平均差值校正、sst分区域差值校正、sst分段校正3种校正方法对HY-1C sst数据质量进行改进，其中HY-1C sst分区域校正的质量提升最明显，标准差、均方根误差接近1℃，夜晚均方根误差比校正前降低了约0.8℃，白天和晚上均方根误差分别降低了32.52%和42.04%。

关键词： HY-1C sst 东南亚

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Mesoscale sst perturbation-induced impacts on climatological precipitation in the Kuroshio-Oyashio extension region,as revealed by the WRF simulations

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Journal of Oceanology and Limnology 2019年第2期37卷 385-397页

作者： GAO Jiaxiang ZHANG Rong-Hua WANG Hongna CAS Key Laboratory of Ocean Circulation and Waves Institute of Oceanology Chinese Academy of Sciences Qingdao 266071China University of Chinese Academy of Sciences Beijing 100049 China Laboratory for Ocean Dynamics and Climate Qingdao National Laboratory for Marine Science and Technology Qingdao 266237 China

Mesoscale coupling between perturbations of mesoscale sea surface temperature (sst) and lowlevel winds has been extensively studied using available high-resolution satellite observations. However, the climatological impacts of mesoscale sst perturbations (sst meso ) on the free atmosphere have not been fully understood. In this study, the rectified eff ect of sstmeso on local climatological precipitation in the Kuroshio- Oyashio Extension (KOE) region is investigated using the Weather Research and Forecasting (WRF) Model;two runs are performed, one forced by low-resolution sst fields (almost no mesoscale signals) and another by additional high-resolution sstmeso fields extracted from satellite observations. Climatological precipitation response to sst meso is characterized mainly by enhanced precipitation on the warmer flank of three oceanic sst fronts in this region. The results show that the positive correlation between the 10-m wind speed perturbations and sstmeso is well captured by the WRF model with a reasonable spatial pattern but relatively weak strength. The addition of sstmeso improves the climatological precipitation simulated by WRF with a better representation of fine-scale structures compared with satellite observations. A closer examination on the underlying mechanism suggests that while the pressure adjustment mechanism can explain the climatological precipitation enhancement along the fronts and the relatively high contribution of the convective precipitation, other factors such as synoptic events should also be taken into consideration to account for the seasonality of the precipitation response.

关键词： mesoscale sst perturbations and eff ects WRF model Kuroshio-Oyashio Extension climatological precipitation

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Reconstruction of incomplete satellite sst data sets based on EOF method

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Acta Oceanologica Sinica 2009年第2期28卷 36-44页

作者： DING Youzhuan WEI Zhihui MAO Zhihua WANG Xiaofei PAN Delu Department of Computer Nanjing University of Science and Technology Nanjing 210094 China State Key Laboratory of Satellite Ocean Envionment Dynamics Second Institute of Oceanography State Oceanic Administration Hangzhou 310012 China

As for the satellite remote sensing data obtained by the visible and infrared bands myers,on, the clouds coverage in the sky over the ocean often results in missing data of inversion products on a large scale, and thin clouds difficult to be detected would cause the data of the inversion products to be abnormal. Alvera et a1.（2005） proposed a method for the reconstruction of missing data based on an Empirical Orthogonal Functions （EOF） decomposition, but his method couldn＇t process these images presenting extreme cloud coverage（more than 95%）, and required a long time for recon- struction. Besides, the abnormal data in the images had a great effect on the reconstruction result. Therefore, this paper tries to improve the study result. It has reconstructed missing data sets by twice applying EOF decomposition method. Firstly, the abnormity time has been detected by analyzing the temporal modes of EOF decomposition, and the abnormal data have been eliminated. Secondly, the data sets, excluding the abnormal data, are analyzed by using EOF decomposition, and then the temporal modes undergo a filtering process so as to enhance the ability of reconstruct- ing the images which are of no or just a little data, by using EOF. At last, this method has been applied to a large data set, i.e. 43 Sea Surface Temperature （sst） satellite images of the Changjiang River （Yangtze River） estuary and its adjacent areas, and the total reconstruction root mean square error （RMSE） is 0.82℃. And it has been proved that this improved EOF reconstruction method is robust for reconstructing satellite missing data and unreliable data.

关键词： EOF sst Changjiang River estuary Missing data sets

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Impact of sst Anomaly Events over the Kuroshio-Oyashio Extension on the ＂Summer Prediction Barrier＂

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Advances in Atmospheric Sciences 2018年第4期35卷 397-409页

作者： Yujie WU Wansuo DUAN Laboratory for Climate Studies National Climate Center China Meteorological Administration Beijing 100081 China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China CMA-NJU Joint Laboratory for Climate Prediction Studies Nanjing University Nanjing 210023 China University of Chinese Academy of Sciences Beijing 100049 China

The ＂summer prediction barrier＂（SPB） of sst anomalies （sstA） over the Kuroshio--Oyashio Extension （KOE） refers to the phenomenon that prediction errors of KOE-sstA tend to increase rapidly during boreal summer, resulting in large prediction uncertainties. The fast error growth associated with the SPB occurs in the mature-to-decaying transition phase, which is usually during the August-September-October （ASO） season, of the KOE-sstA events to be predicted. Thus, the role of KOE-sstA evolutionary characteristics in the transition phase in inducing the SPB is explored by performing perfect model predictability experiments in a coupled model, indicating that the sstA events with larger mature-to-decaying transi- tion rates （Category-l） favor a greater possibility of yielding a more significant SPB than those events with smaller transition rates （Category-2）. The KOE-sstA events in Category-1 tend to have more significant anomalous Ekman pumping in their transition phase, resulting in larger prediction errors of vertical oceanic temperature advection associated with the sstA events. Consequently, Category-1 events possess faster error growth and larger prediction errors. In addition, the anomalous Ekman upwelling （downwelling） in the ASO season also causes sstA cooling （warming）, accelerating the transition rates of warm （cold） KOE-sstA events. Therefore, the sstA transition rate and error growth rate are both related with the anomalous Ekman pumping of the sstA events to be predicted in their transition phase. This may explain why the sstA events transferring more rapidly from the mature to decaying phase tend to have a greater possibility of yielding a more significant SPB.

关键词： Kuroshio-Oyashio Extension sst summer prediction barrier error growth

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Retrieving the surface axis of the Kuroshio off southern coast of Japan from sst data

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Acta Oceanologica Sinica 2007年第1期26卷 1-11页

作者： SHAO Quanqin CHEN Zhuoqi MA Weiwei Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

One thousand and forty-nine sea surface isotherm maps during 1990 - 2000 were used to detect the Kuroshio axis off the coast of Japan. The current axis on the surface cannot be identified by just one indicative isotherm as is commonly done in deep water, but still there are complicated isotherms indicatives of the Kuroshio axis. Three types of isotherms indicatives of the surface axis of the Kuroshio are identified, which are nesti indicator, warm-tongue-isotherm-indicator, and isotherm-indicator. The ocourrence frequency of NWTI-type is 72%, that of WTII-type is 19.1% and that of Ⅱ-type is 8.9%. The vector-based and raster-based methods were introduced and used to retrieve automatically the Kumshio paths from sst data. The total retrieving percentage is 74% by the three methods, 52.3% by the vector method, 56.8% by one raster method and 49.6% by another raster method. For the NWTI - type, the total retrieving percentage is 91.3% by the three methods, 64.4% by the vector method, 75. 9% by one raster method and 65% by another raster method. Using retrieving results of the Kumshio axis from sst data,the Kuroshio path detour is analyzed during 1990 - 2000.

关键词： Kuroshio axis sst nesting-warm-tongue-indicator warm-tongue-isotherm-indicator isotherm-indicator GIS

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Influence of South China Sea sst and the ENSO on Winter Rainfall over South China

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Advances in Atmospheric Sciences 2010年第4期27卷 832-844页

作者：周连童 Chi-Yung TAM 周文 Johnny C. L. CHAN Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of Sciences CityU-IAP Laboratory for Atmospheric Sciences City University of Hong Kong Guy Carpenter Asia-Pacific Climate Impact Centre School of Energy and EnvironmentCity University of Hong Kong

The present study investigates the influence of South China Sea （SCS） sst and ENSO on winter （January-February-March; JFM） rainfall over South China and its dynamic processes by using station observations for the period 1951-2003, Met Office Hadley Center sst data for the period 1900-2008, and ERA-40 reanalysis data for the period 1958-2002. It is found that JFM rainfall over South China has a sig- nificant correlation with Nio-3 and SCS sst. Analyses show that in El Nio or positive SCS sst anomaly years, southwesterly anomalies at 700 hPa dominate over the South China Sea, which in turn transports more moisture into South China and favors increased rainfall. A partial regression analysis indicates that the independent ENSO influence on winter rainfall occurs mainly over South China, whereas SCS sst has a larger independent influence on winter rainfall in northern part of South China. The temperature over South China shows an obvious decrease at 300 hPa and an increase near the surface, with the former induced by Nio-3 and the latter SCS sst anomalies. This enhances the convective instability and weakens the potential vorticity （PV）, which explains the strengthening of ascending motion and the increase of JFM rainfall over South China.

关键词： ENSO South China Sea sst rainfall convective instability potential vorticity

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An ensemble-based sst nudging method proposed for correcting the subsurface temperature field in climate model

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Acta Oceanologica Sinica 2020年第3期39卷 73-80页

作者： Xingrong Chen Hui Wang Fei Zheng Qifa Cai National Marine Environmental Forecasting Center Beijing 100081China National Meteorological Center Beijing 100081China Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China Mailbox 5111 Beijing 100094China

An ensemble-based assimilation method is proposed for correcting the subsurface temperature field when nudging the sea surface temperature(sst) observations into the Max Planck Institute(MPI) climate model,ECHAM5/MPI-OM. This method can project sst directly to subsurface according to model ensemble-based correlations between sst and subsurface temperature. Results from a 50 year(1960–2009) assimilation experiment show the method can improve the subsurface temperature field up to 300 m compared to the qualitycontrolled subsurface ocean temperature objective analyses(EN4), through reducing the biases of the thermal states, improving the thermocline structure, and reducing the root mean square(RMS) errors. Moreover, as most of the improvements concentrate over the upper 100 m, the ocean heat content in the upper 100 m(OHT100 m)is further adopted as a property to validate the performance of the ensemble-based correction method. The results show that RMS errors of the global OHT100 m convergent to one value after several times iteration,indicating this method can represent the relationship between sst and subsurface temperature fields well, and then improve the accuracy of the simulation in the subsurface temperature of the climate model.

关键词： ensemble-based nudging method ECHAM5/MPI-OM sst assimilation simulation of subsurface temperature field

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