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
In this study, the predictability of the El Nino-South Oscillation(ENSO) in an operational prediction model from the perspective of initial errors is diagnosed using the seasonal hindcasts of the Beijing Climate Cente...In this study, the predictability of the El Nino-South Oscillation(ENSO) in an operational prediction model from the perspective of initial errors is diagnosed using the seasonal hindcasts of the Beijing Climate Center System Model,BCC;SM1.1(m). Forecast skills during the different ENSO phases are analyzed and it is shown that the ENSO forecasts appear to be more challenging during the developing phase, compared to the decay phase. During ENSO development, the SST prediction errors are significantly negative and cover a large area in the central and eastern tropical Pacific, thus limiting the model skill in predicting the intensity of El Nino. The large-scale SST errors, at their early stage, are generated gradually in terms of negative anomalies in the subsurface ocean temperature over the central-western equatorial Pacific,featuring an error evolutionary process similar to that of El Nino decay and the transition to the La Nina growth phase.Meanwhile, for short lead-time ENSO predictions, the initial wind errors begin to play an increasing role, particularly in linking with the subsurface heat content errors in the central-western Pacific. By comparing the multiple samples of initial fields in the model, it is clearly found that poor SST predictions of the Nino-3.4 region are largely due to contributions of the initial errors in certain specific locations in the tropical Pacific. This demonstrates that those sensitive areas for initial fields in ENSO prediction are fairly consistent in both previous ideal experiments and our operational predictions,indicating the need for targeted observations to further improve operational forecasts of ENSO.展开更多
The authors examine the Indian Ocean sea surface temperature(SST) biases simulated by a Flexible Regional Ocean Atmosphere Land System(FROALS) model.The regional coupled model exhibits pronounced cold SST biases in a ...The authors examine the Indian Ocean sea surface temperature(SST) biases simulated by a Flexible Regional Ocean Atmosphere Land System(FROALS) model.The regional coupled model exhibits pronounced cold SST biases in a large portion of the Indian Ocean warm pool.Negative biases in the net surface heat fluxes are evident in the model,leading to the cold biases of the SST.Further analysis indicates that the negative biases in the net surface heat fluxes are mainly contributed by the biases of sensible heat and latent heat flux.Near-surface meteorological variables that could contribute to the SST biases are also examined.It is found that the biases of sensible heat and latent heat flux are caused by the colder and dryer near-surface air in the model.展开更多
This study used National Center for Environmental Prediction (NCEP) reanalysis data to confirm that the variance of sea surface temperature (SST) in the South China Sea (SCS) has pronounced intraseasonal oscillations ...This study used National Center for Environmental Prediction (NCEP) reanalysis data to confirm that the variance of sea surface temperature (SST) in the South China Sea (SCS) has pronounced intraseasonal oscillations characterized by quasi standing waves; and was aimed to document how intraseasonal time scale SST formed and developed in the SCS. The results derived from the composite analysis indicated the existence of a local low level atmospheric dynamic forcing system over the SCS. The main formation mechanism of SST intraseasonal oscillation is the low level rotational atmospheric circulation forcing over the SCS on intraseasonal time scales and the solar radiation variations caused by cloud amount changes.展开更多
By utilizing multiple datasets from various sources available for the last 100 years, the existence for the interdecadal change of the winter sea surface temperature（SST） variability in the Kuroshio Extension（KE） ...By utilizing multiple datasets from various sources available for the last 100 years, the existence for the interdecadal change of the winter sea surface temperature（SST） variability in the Kuroshio Extension（KE） region is investigated. And its linkage with the Aleutian Low（AL） activity changes is also discussed. The results find that the KE SST variability exhibits the significant ~6 a and ~10 a oscillations with obvious interdecadal change. The ~6 a oscillation is mainly detected during 1930–1950, which is largely impacted by the anomalous surface heat flux forcing and Ekman heat transport associated with the AL intensity variation. The ~10 a oscillation is most evident after the 1980s, which is predominantly triggered by the AL north-south shift through the bridge of oceanic Rossby waves.展开更多
Tropical cyclone(TC)activities in the North Indian Ocean(NIO)peak in May during the pre-monsoon period,but the TC frequency shows obvious inter-annual variations.By conducting statistical analysis and dynamic diagnosi...Tropical cyclone(TC)activities in the North Indian Ocean(NIO)peak in May during the pre-monsoon period,but the TC frequency shows obvious inter-annual variations.By conducting statistical analysis and dynamic diagnosis of long-term data from 1948 to 2016,the relationship between the inter-annual variations of Indian Ocean SST and NIO TC genesis frequency in May is analyzed in this paper.Furthermore,the potential mechanism concerning the effect of SST anomaly on TC frequency is also investigated.The findings are as follows:1)there is a broadly consistent negative correlation between NIO TC frequency in May and SST in the Indian Ocean from March to May,with the key influencing area located in the southwestern Indian Ocean(SWIO);2)the anomalies of SST in SWIO(SWIO-SST)are closely related to a teleconnection pattern surrounding the Indian Ocean,which can significantly modulate the high-level divergence,mid-level vertical motion and other related environmental factors and ultimately influence the formation of TCs over the NIO;3)the increasing trend of SWIO-SST may play an essential role in the downward trend of NIO TC frequency over the past 69 years.展开更多
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.
基金jointly supported by the National Key Research and Development Program on Monitoring,Early WarningPrevention of Major Natural Disaster(Grant No.2018YFC1506000)the China National Science(Grant Nos.41606019,41975094,and 41706016)。
文摘In this study, the predictability of the El Nino-South Oscillation(ENSO) in an operational prediction model from the perspective of initial errors is diagnosed using the seasonal hindcasts of the Beijing Climate Center System Model,BCC;SM1.1(m). Forecast skills during the different ENSO phases are analyzed and it is shown that the ENSO forecasts appear to be more challenging during the developing phase, compared to the decay phase. During ENSO development, the SST prediction errors are significantly negative and cover a large area in the central and eastern tropical Pacific, thus limiting the model skill in predicting the intensity of El Nino. The large-scale SST errors, at their early stage, are generated gradually in terms of negative anomalies in the subsurface ocean temperature over the central-western equatorial Pacific,featuring an error evolutionary process similar to that of El Nino decay and the transition to the La Nina growth phase.Meanwhile, for short lead-time ENSO predictions, the initial wind errors begin to play an increasing role, particularly in linking with the subsurface heat content errors in the central-western Pacific. By comparing the multiple samples of initial fields in the model, it is clearly found that poor SST predictions of the Nino-3.4 region are largely due to contributions of the initial errors in certain specific locations in the tropical Pacific. This demonstrates that those sensitive areas for initial fields in ENSO prediction are fairly consistent in both previous ideal experiments and our operational predictions,indicating the need for targeted observations to further improve operational forecasts of ENSO.
基金supported by the National High Technology Research and Development Program of China (863 Program,Grant No.2010AA012304)
文摘The authors examine the Indian Ocean sea surface temperature(SST) biases simulated by a Flexible Regional Ocean Atmosphere Land System(FROALS) model.The regional coupled model exhibits pronounced cold SST biases in a large portion of the Indian Ocean warm pool.Negative biases in the net surface heat fluxes are evident in the model,leading to the cold biases of the SST.Further analysis indicates that the negative biases in the net surface heat fluxes are mainly contributed by the biases of sensible heat and latent heat flux.Near-surface meteorological variables that could contribute to the SST biases are also examined.It is found that the biases of sensible heat and latent heat flux are caused by the colder and dryer near-surface air in the model.
文摘This study used National Center for Environmental Prediction (NCEP) reanalysis data to confirm that the variance of sea surface temperature (SST) in the South China Sea (SCS) has pronounced intraseasonal oscillations characterized by quasi standing waves; and was aimed to document how intraseasonal time scale SST formed and developed in the SCS. The results derived from the composite analysis indicated the existence of a local low level atmospheric dynamic forcing system over the SCS. The main formation mechanism of SST intraseasonal oscillation is the low level rotational atmospheric circulation forcing over the SCS on intraseasonal time scales and the solar radiation variations caused by cloud amount changes.
基金The National Basic Research Program(973 program)of China under contract No.2013CB956203the National Natural Science Foundation of China under contract No.41375063
文摘By utilizing multiple datasets from various sources available for the last 100 years, the existence for the interdecadal change of the winter sea surface temperature（SST） variability in the Kuroshio Extension（KE） region is investigated. And its linkage with the Aleutian Low（AL） activity changes is also discussed. The results find that the KE SST variability exhibits the significant ~6 a and ~10 a oscillations with obvious interdecadal change. The ~6 a oscillation is mainly detected during 1930–1950, which is largely impacted by the anomalous surface heat flux forcing and Ekman heat transport associated with the AL intensity variation. The ~10 a oscillation is most evident after the 1980s, which is predominantly triggered by the AL north-south shift through the bridge of oceanic Rossby waves.
基金National Natural Science Foundation of China(41965005,41790471,42075013)Key R&D Plan of Yunnan Province Science and Technology Department(202203AC100006)National Natural Science Foundation of Yunnan Province(202201AS070069)。
文摘Tropical cyclone(TC)activities in the North Indian Ocean(NIO)peak in May during the pre-monsoon period,but the TC frequency shows obvious inter-annual variations.By conducting statistical analysis and dynamic diagnosis of long-term data from 1948 to 2016,the relationship between the inter-annual variations of Indian Ocean SST and NIO TC genesis frequency in May is analyzed in this paper.Furthermore,the potential mechanism concerning the effect of SST anomaly on TC frequency is also investigated.The findings are as follows:1)there is a broadly consistent negative correlation between NIO TC frequency in May and SST in the Indian Ocean from March to May,with the key influencing area located in the southwestern Indian Ocean(SWIO);2)the anomalies of SST in SWIO(SWIO-SST)are closely related to a teleconnection pattern surrounding the Indian Ocean,which can significantly modulate the high-level divergence,mid-level vertical motion and other related environmental factors and ultimately influence the formation of TCs over the NIO;3)the increasing trend of SWIO-SST may play an essential role in the downward trend of NIO TC frequency over the past 69 years.
