The dominant annual cycle of sea surface temperature(SST)in the tropical Pacific exhibits an antisymmetric mode,which explains 83.4%total variance,and serves as a background of El Niño-Southern Oscillation(ENSO)....The dominant annual cycle of sea surface temperature(SST)in the tropical Pacific exhibits an antisymmetric mode,which explains 83.4%total variance,and serves as a background of El Niño-Southern Oscillation(ENSO).However,there is no consensus yet on its anomalous impacts on the phase and amplitude of ENSO.Based on data during 1982-2022,results show that anomalies of the antisymmetric mode can affect the evolution of ENSO on the interannual scale via Bjerknes feedback,in which the positive(negative)phase of the antisymmetric mode can strengthen El Niño(La Niña)in boreal winter via an earlier(delayed)seasonal cycle transition and larger(smaller)annual mean.The magnitude of the SST anomalies in the equatorial eastern Pacific can reach more than±0.3◦C,regulated by the changes in the antisymmetric mode based on random sensitivity analysis.Results reveal the spatial pattern of the annual cycle associated with the seasonal phase-locking of ENSO evolution and provide new insight into the impact of the annual cycle of background SST on ENSO,which possibly carries important implications for forecasting ENSO.展开更多
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 instruments.While satellite infrare...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 instruments.While satellite infrared SST offers high spatial resolution,it is limited by cloud cover.On 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 speeds.To achieve high-precision,comprehensive,and high-resolution SST data,it is essential to fuse infrared and microwave SST measurements.In this study,data from the Fengyun-3D(FY-3D)medium resolution spectral imager II(MERSI-II)SST and microwave imager(MWRI)SST were fused.Firstly,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 SST.After pretreatment and quality control of MERSI SST and MWRI SST,a Piece-Wise Regression method was employed to correct biases in MWRI SST.Subsequently,SST data were selected based on spatial resolution and accuracy within a 3-day window of the analysis date.Finally,an optimal interpolation method was applied to fuse the FY-3D MERSI-II SST and MWRI SST.The results demonstrated a significant improvement in spatial coverage compared to MERSI-II SST and MWRI SST.Furthermore,the fusion SST retained true spatial distribution details and exhibited an accuracy of–0.12±0.74℃compared to OSTIA SST.This study has improved the accuracy of FY satellite fusion SST products in China.展开更多
The Yangtze River basin(YRB)experienced a record-breaking mei-yu season in June‒July 2020.This unique long-lasting extreme event and its origin have attracted considerable attention.Previous studies have suggested tha...The Yangtze River basin(YRB)experienced a record-breaking mei-yu season in June‒July 2020.This unique long-lasting extreme event and its origin have attracted considerable attention.Previous studies have suggested that the Indian Ocean(IO)SST forcing and soil moisture anomaly over the Indochina Peninsula(ICP)were responsible for this unexpected event.However,the relative contributions of IO SST and ICP soil moisture to the 2020 mei-yu rainfall event,especially their linkage with atmospheric circulation changes,remain unclear.By using observations and numerical simulations,this study examines the synergistic impacts of IO SST and ICP soil moisture on the extreme mei-yu in 2020.Results show that the prolonged dry soil moisture led to a warmer surface over the ICP in May under strong IO SST backgrounds.The intensification of the warm condition further magnified the land thermal effects,which in turn facilitated the westward extension of the western North Pacific subtropical high(WNPSH)in June‒July.The intensified WNPSH amplified the water vapor convergence and ascending motion over the YRB,thereby contributing to the 2020 mei-yu.In contrast,the land thermal anomalies diminish during normal IO SST backgrounds due to the limited persistence of soil moisture.The roles of IO SST and ICP soil moisture are verified and quantified using the Community Earth System Model.Their synergistic impacts yield a notable 32%increase in YRB precipitation.Our findings provide evidence for the combined influences of IO SST forcing and ICP soil moisture variability on the occurrence of the 2020 super mei-yu.展开更多
尝试利用卫星遥感高分辨率海表温度资料GHRSST(Group for High Resolution Sea Surface Temperature)与海表温度(sea surface temperature,SST)数值预报产品之间的误差,建立一种南海SST模式预报订正方法。首先,利用南海的Argo浮标上层...尝试利用卫星遥感高分辨率海表温度资料GHRSST(Group for High Resolution Sea Surface Temperature)与海表温度(sea surface temperature,SST)数值预报产品之间的误差,建立一种南海SST模式预报订正方法。首先,利用南海的Argo浮标上层海温数据对GHRSST海温数据进行验证,结果表明两者之间均方根误差约为0.3℃,相关系数为0.98,GHRSST海温数据可用于南海业务化数值预报SST的订正。预报订正后的SST与Argo浮标海温数据相比,24h、48h和72h的均方根误差均由0.8℃左右下降到0.5℃以内。与GHRSST海温数据相比,南海北部海域(110°E—121°E,13°N—23°N)订正后的24h、48h和72h的SST预报空间误差均显著减小,在冷空气影响南海期间或中尺度涡存在的过程中,SST预报订正效果也较为显著。因此,该方法可考虑在南海业务化SST数值预报系统中应用。展开更多
热带海表温度(SST)模拟偏差是困扰海气耦合模式发展的经典问题之一,其原因仍不完全清晰。针对海气耦合模式CESM1(Community Earth System Model version 1)模拟的热带印度洋SST偏差,我设计了单独大气-陆面模式、单独海洋-海冰模式以及...热带海表温度(SST)模拟偏差是困扰海气耦合模式发展的经典问题之一,其原因仍不完全清晰。针对海气耦合模式CESM1(Community Earth System Model version 1)模拟的热带印度洋SST偏差,我设计了单独大气-陆面模式、单独海洋-海冰模式以及海气耦合模式等一系列数值实验。在此基础上,采用大气-陆面模式和海洋-海冰模式隐式(implicit)SST偏差的分析方法,诊断了CESM1模拟的热带印度洋SST偏差的来源,并分析了大气模式和海洋模式中影响热带印度洋上层海温模拟的主要因素。通过分析热带印度洋不同地区SST的模拟偏差来源,发现耦合模式CESM1中孟加拉湾SST模拟偏冷主要是由海洋-海冰模式中过强的垂直混合、平流作用等海洋动力偏差引起的。在阿拉伯海和赤道西印度洋,过多的潜热释放导致SST降低,大气-陆面模式模拟误差是这两个海域SST冷偏差的主要来源。对于赤道中印度洋,潜热通量偏差和垂直混合、平流作用等模拟误差共同影响上层海水温度,潜热释放偏少、海水垂直混合偏弱以及经向平流向南输送过多暖水使耦合模式模拟的赤道中印度洋SST出现暖偏差,而在赤道东印度洋,模拟的SST偏冷是由大气-陆面模式中短波辐射偏少和海洋-海冰模式中海水垂直混合过强引起的,潜热通量偏差影响较小。分析表明,耦合模式中海气相互作用只影响SST模拟偏差的大小,但不是引起SST偏差的根本原因。展开更多
基金jointly supported by the National Natural Science Foundation of China [grant numbers U2242205 and 41830969]the S&T Development Fund of CAMS [grant number 2023KJ036]the Basic Scientific Research and Operation Foundation of CAMS [grant number 2023Z018]。
文摘The dominant annual cycle of sea surface temperature(SST)in the tropical Pacific exhibits an antisymmetric mode,which explains 83.4%total variance,and serves as a background of El Niño-Southern Oscillation(ENSO).However,there is no consensus yet on its anomalous impacts on the phase and amplitude of ENSO.Based on data during 1982-2022,results show that anomalies of the antisymmetric mode can affect the evolution of ENSO on the interannual scale via Bjerknes feedback,in which the positive(negative)phase of the antisymmetric mode can strengthen El Niño(La Niña)in boreal winter via an earlier(delayed)seasonal cycle transition and larger(smaller)annual mean.The magnitude of the SST anomalies in the equatorial eastern Pacific can reach more than±0.3◦C,regulated by the changes in the antisymmetric mode based on random sensitivity analysis.Results reveal the spatial pattern of the annual cycle associated with the seasonal phase-locking of ENSO evolution and provide new insight into the impact of the annual cycle of background SST on ENSO,which possibly carries important implications for forecasting ENSO.
文摘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 instruments.While satellite infrared SST offers high spatial resolution,it is limited by cloud cover.On 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 speeds.To achieve high-precision,comprehensive,and high-resolution SST data,it is essential to fuse infrared and microwave SST measurements.In this study,data from the Fengyun-3D(FY-3D)medium resolution spectral imager II(MERSI-II)SST and microwave imager(MWRI)SST were fused.Firstly,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 SST.After pretreatment and quality control of MERSI SST and MWRI SST,a Piece-Wise Regression method was employed to correct biases in MWRI SST.Subsequently,SST data were selected based on spatial resolution and accuracy within a 3-day window of the analysis date.Finally,an optimal interpolation method was applied to fuse the FY-3D MERSI-II SST and MWRI SST.The results demonstrated a significant improvement in spatial coverage compared to MERSI-II SST and MWRI SST.Furthermore,the fusion SST retained true spatial distribution details and exhibited an accuracy of–0.12±0.74℃compared to OSTIA SST.This study has improved the accuracy of FY satellite fusion SST products in China.
基金supported by the National Key R&D Program of China(Grant No.2022YFF0801603).
文摘The Yangtze River basin(YRB)experienced a record-breaking mei-yu season in June‒July 2020.This unique long-lasting extreme event and its origin have attracted considerable attention.Previous studies have suggested that the Indian Ocean(IO)SST forcing and soil moisture anomaly over the Indochina Peninsula(ICP)were responsible for this unexpected event.However,the relative contributions of IO SST and ICP soil moisture to the 2020 mei-yu rainfall event,especially their linkage with atmospheric circulation changes,remain unclear.By using observations and numerical simulations,this study examines the synergistic impacts of IO SST and ICP soil moisture on the extreme mei-yu in 2020.Results show that the prolonged dry soil moisture led to a warmer surface over the ICP in May under strong IO SST backgrounds.The intensification of the warm condition further magnified the land thermal effects,which in turn facilitated the westward extension of the western North Pacific subtropical high(WNPSH)in June‒July.The intensified WNPSH amplified the water vapor convergence and ascending motion over the YRB,thereby contributing to the 2020 mei-yu.In contrast,the land thermal anomalies diminish during normal IO SST backgrounds due to the limited persistence of soil moisture.The roles of IO SST and ICP soil moisture are verified and quantified using the Community Earth System Model.Their synergistic impacts yield a notable 32%increase in YRB precipitation.Our findings provide evidence for the combined influences of IO SST forcing and ICP soil moisture variability on the occurrence of the 2020 super mei-yu.
文摘尝试利用卫星遥感高分辨率海表温度资料GHRSST(Group for High Resolution Sea Surface Temperature)与海表温度(sea surface temperature,SST)数值预报产品之间的误差,建立一种南海SST模式预报订正方法。首先,利用南海的Argo浮标上层海温数据对GHRSST海温数据进行验证,结果表明两者之间均方根误差约为0.3℃,相关系数为0.98,GHRSST海温数据可用于南海业务化数值预报SST的订正。预报订正后的SST与Argo浮标海温数据相比,24h、48h和72h的均方根误差均由0.8℃左右下降到0.5℃以内。与GHRSST海温数据相比,南海北部海域(110°E—121°E,13°N—23°N)订正后的24h、48h和72h的SST预报空间误差均显著减小,在冷空气影响南海期间或中尺度涡存在的过程中,SST预报订正效果也较为显著。因此,该方法可考虑在南海业务化SST数值预报系统中应用。
文摘热带海表温度(SST)模拟偏差是困扰海气耦合模式发展的经典问题之一,其原因仍不完全清晰。针对海气耦合模式CESM1(Community Earth System Model version 1)模拟的热带印度洋SST偏差,我设计了单独大气-陆面模式、单独海洋-海冰模式以及海气耦合模式等一系列数值实验。在此基础上,采用大气-陆面模式和海洋-海冰模式隐式(implicit)SST偏差的分析方法,诊断了CESM1模拟的热带印度洋SST偏差的来源,并分析了大气模式和海洋模式中影响热带印度洋上层海温模拟的主要因素。通过分析热带印度洋不同地区SST的模拟偏差来源,发现耦合模式CESM1中孟加拉湾SST模拟偏冷主要是由海洋-海冰模式中过强的垂直混合、平流作用等海洋动力偏差引起的。在阿拉伯海和赤道西印度洋,过多的潜热释放导致SST降低,大气-陆面模式模拟误差是这两个海域SST冷偏差的主要来源。对于赤道中印度洋,潜热通量偏差和垂直混合、平流作用等模拟误差共同影响上层海水温度,潜热释放偏少、海水垂直混合偏弱以及经向平流向南输送过多暖水使耦合模式模拟的赤道中印度洋SST出现暖偏差,而在赤道东印度洋,模拟的SST偏冷是由大气-陆面模式中短波辐射偏少和海洋-海冰模式中海水垂直混合过强引起的,潜热通量偏差影响较小。分析表明,耦合模式中海气相互作用只影响SST模拟偏差的大小,但不是引起SST偏差的根本原因。
