Polar Studies
2021, 44(1):1-11.
DOI: 10.13878/j.cnki.dqkxxb.20201031003
Abstract:
The Arctic,Antarctic and Tibetan Plateau are respectively the northernmost,southernmost and highest plateau of the earth,referred to as the earth's "three-poles" (ETP).The ETP are the key and sensitive regions to the global climate change,and their rapid changes also play an increasingly important role in the regional and global climate system.This paper reviews the latest research results in this field,highlights the basic characteristics of interdecadal climate change in the ETP regions and their impacts on regional climate,and summarizes the potential climate linkages among them under the global warming.Finally,it discusses and looks forward to the possible challenges in the ETP climate change research in the future.
The Arctic,Antarctic and Tibetan Plateau are respectively the northernmost,southernmost and highest plateau of the earth,referred to as the earth's "three-poles" (ETP).The ETP are the key and sensitive regions to the global climate change,and their rapid changes also play an increasingly important role in the regional and global climate system.This paper reviews the latest research results in this field,highlights the basic characteristics of interdecadal climate change in the ETP regions and their impacts on regional climate,and summarizes the potential climate linkages among them under the global warming.Finally,it discusses and looks forward to the possible challenges in the ETP climate change research in the future.
LIU Jiping
,
LEI Ruibo
,
SONG Mirong
,
XU Shiming
,
JI Shunying
,
SU Jie
,
LI Zhijun
,
WANG Xiaochun
,
ZHU Zhu
,
YANG Chaoyuan
2021, 44(1):12-25.
DOI: 10.13878/j.cnki.dqkxxb.20201203003
Abstract:
Polar sea ice is an important component of the earth's climate system,and also an indicator and amplifier of climate and environmental changes.The complex multi-scale physical processes of polar sea ice and the lack of polar observations have brought huge challenges to research and development of sea ice models.In the past half-century,the mathematical descriptions of complex interactions of atmosphere-sea ice-ocean and sea ice internal physical processes in sea ice models have made significant progresses,but there are still problems to describe some important physical processes realistically,especially the rapid changes of polar sea ice and its physical properties in recent years have greatly increased the uncertainty of physical parameterization schemes and simulation results of sea ice models.Therefore,it is urgent to have a high-resolution sea ice model that has complete physical processes and adapts to rapid multi-scale changes of polar sea ice,and the model is applied to the research and prediction of global climate change and the development and utilization of polar regions.This paper elaborates and discusses the development history and status of sea ice models,the challenges brought by rapid changes of polar sea ice,and the research directions of improvement and development of sea ice model that adapts to rapid polar sea ice changes.
Polar sea ice is an important component of the earth's climate system,and also an indicator and amplifier of climate and environmental changes.The complex multi-scale physical processes of polar sea ice and the lack of polar observations have brought huge challenges to research and development of sea ice models.In the past half-century,the mathematical descriptions of complex interactions of atmosphere-sea ice-ocean and sea ice internal physical processes in sea ice models have made significant progresses,but there are still problems to describe some important physical processes realistically,especially the rapid changes of polar sea ice and its physical properties in recent years have greatly increased the uncertainty of physical parameterization schemes and simulation results of sea ice models.Therefore,it is urgent to have a high-resolution sea ice model that has complete physical processes and adapts to rapid multi-scale changes of polar sea ice,and the model is applied to the research and prediction of global climate change and the development and utilization of polar regions.This paper elaborates and discusses the development history and status of sea ice models,the challenges brought by rapid changes of polar sea ice,and the research directions of improvement and development of sea ice model that adapts to rapid polar sea ice changes.
2021, 44(1):26-38.
DOI: 10.13878/j.cnki.dqkxxb.20201125001
Abstract:
After two "Artificial Intelligence winters",machine learning has become a subject of intense of media hype and come up in countless articles,showing a promising future.Machine learning has gained a big success in image recognition and speech recognition systems.Refining key message and dominant features from the train datasets and making accurate prediction on the never-seen-before datasets are the major task and the ultimate goal of machine learning,respectively.From this perspective,it's feasible to integrate machine learning into climate prediction.Beginning with a simple example on finding the weights of a linear fitting,this study shows how machine learning updates weights through gradient descent algorithm and eventually obtains the linear fitting line.Next,this study illustrates the architecture of neural network and uses neural network algorithm to learn the true curve fitting a non-linear function.In the end,this study elaborates the architecture of deep learning such as convolutional neural network,and uses convolutional neural network model to hindcast winter monthly surface air temperature anomalies in East Asia.The results by deep learning are further compared with the hindcast by dynamical model-CanCM4i.This study will help to understand the fundamental of machine learning and provides insights how to integrate machine learning into climate prediction.
After two "Artificial Intelligence winters",machine learning has become a subject of intense of media hype and come up in countless articles,showing a promising future.Machine learning has gained a big success in image recognition and speech recognition systems.Refining key message and dominant features from the train datasets and making accurate prediction on the never-seen-before datasets are the major task and the ultimate goal of machine learning,respectively.From this perspective,it's feasible to integrate machine learning into climate prediction.Beginning with a simple example on finding the weights of a linear fitting,this study shows how machine learning updates weights through gradient descent algorithm and eventually obtains the linear fitting line.Next,this study illustrates the architecture of neural network and uses neural network algorithm to learn the true curve fitting a non-linear function.In the end,this study elaborates the architecture of deep learning such as convolutional neural network,and uses convolutional neural network model to hindcast winter monthly surface air temperature anomalies in East Asia.The results by deep learning are further compared with the hindcast by dynamical model-CanCM4i.This study will help to understand the fundamental of machine learning and provides insights how to integrate machine learning into climate prediction.
2021, 44(1):39-49.
DOI: 10.13878/j.cnki.dqkxxb.20201113007
Abstract:
The Arctic climate,an important component of the global climate system,has moved into a new state over the past 20 years.Scientific questions and possible consequences related to these changes are now front in the midst of many important issues that the world needs to deal with in the future.These changes,including prominent atmospheric and oceanic warming and sea ice melting have been largely attributed to a combined effect of anthropogenic forcing and internal variability of the climate system.This review highlights some findings from a number of studies conducted by my research group in the past few years.The studies collectively suggest that the high latitude atmospheric circulation that is sensitive to tropical SST forcing related to the interdecadal Pacific oscillation (IPO) plays a vital role in driving the interannual and interdecadal variability of Arctic sea ice by affecting the atmospheric temperature,moisture,clouds and radiative fluxes over sea ice.In particular,the teleconnection excited by a SST cooling over the tropical Pacific is suggested to cause an enhanced melting from 2007 to 2012.In addition,it suggests that a similar internal process may also play a role to cause strong sea ice melting in summer 2020.Furthermore,the model evaluation focusing on CMIP5 models finds that most climate models have a limitation to replicate this IPO-related teleconnection,raising awareness on an urgent need to investigate the cause of this bias in models.Thus,this review is meant to offer priorities for future Arctic research so that more efforts are targeted on critical scientific questions raised in this study.
The Arctic climate,an important component of the global climate system,has moved into a new state over the past 20 years.Scientific questions and possible consequences related to these changes are now front in the midst of many important issues that the world needs to deal with in the future.These changes,including prominent atmospheric and oceanic warming and sea ice melting have been largely attributed to a combined effect of anthropogenic forcing and internal variability of the climate system.This review highlights some findings from a number of studies conducted by my research group in the past few years.The studies collectively suggest that the high latitude atmospheric circulation that is sensitive to tropical SST forcing related to the interdecadal Pacific oscillation (IPO) plays a vital role in driving the interannual and interdecadal variability of Arctic sea ice by affecting the atmospheric temperature,moisture,clouds and radiative fluxes over sea ice.In particular,the teleconnection excited by a SST cooling over the tropical Pacific is suggested to cause an enhanced melting from 2007 to 2012.In addition,it suggests that a similar internal process may also play a role to cause strong sea ice melting in summer 2020.Furthermore,the model evaluation focusing on CMIP5 models finds that most climate models have a limitation to replicate this IPO-related teleconnection,raising awareness on an urgent need to investigate the cause of this bias in models.Thus,this review is meant to offer priorities for future Arctic research so that more efforts are targeted on critical scientific questions raised in this study.
2021, 44(1):50-60.
DOI: 10.13878/j.cnki.dqkxxb.20201030001
Abstract:
The Arctic Oscillation (AO) is the dominant mode of atmospheric circulation in the extratropical Northern Hemisphere,which exerts widespread influences on the Northern Hemispheric and regional temperature changes.AO can be generated via wave-mean flow interactions without the presence of atmospheric external forcing.Hence,it is considered to be an essential component of the internal variability of the global climate system.Investigating the interdecadal variation of the AO and its impacts on climate helps to deepen the physical understanding of the observed climate change and variability in the Northern Hemisphere.Meanwhile,it also provides a scientific basis for the near-term projection of climate change and its uncertainty on the interdecadal scale.This paper briefly reviews and summarizes the recent research on the temporal and spatial variations of wintertime AO on the interdecadal scale and their impacts on the climate in the Northern Hemisphere.Three aspects are reviewed,including the physical mechanism of influences of the AO on interdecadal variations of the East Asian winter monsoon,the contribution of the AO to long-term trend of wintertime air temperature in the Northern Hemisphere,and the uncertainty of interdecadal influence of the AO.The possible issues that deserve future research are also discussed.
The Arctic Oscillation (AO) is the dominant mode of atmospheric circulation in the extratropical Northern Hemisphere,which exerts widespread influences on the Northern Hemispheric and regional temperature changes.AO can be generated via wave-mean flow interactions without the presence of atmospheric external forcing.Hence,it is considered to be an essential component of the internal variability of the global climate system.Investigating the interdecadal variation of the AO and its impacts on climate helps to deepen the physical understanding of the observed climate change and variability in the Northern Hemisphere.Meanwhile,it also provides a scientific basis for the near-term projection of climate change and its uncertainty on the interdecadal scale.This paper briefly reviews and summarizes the recent research on the temporal and spatial variations of wintertime AO on the interdecadal scale and their impacts on the climate in the Northern Hemisphere.Three aspects are reviewed,including the physical mechanism of influences of the AO on interdecadal variations of the East Asian winter monsoon,the contribution of the AO to long-term trend of wintertime air temperature in the Northern Hemisphere,and the uncertainty of interdecadal influence of the AO.The possible issues that deserve future research are also discussed.
2021, 44(1):61-74.
DOI: 10.13878/j.cnki.dqkxxb.20201103002
Abstract:
The Los Alamos Sea Ice Model 5.0 (CICE5.0) was introduced to the Beijing Climate Center Climate System Model (BCC_CSM) as a new alternative to the Sea Ice Simulator (SIS).The new coupled model performance on the Arctic sea ice and polar climate simulations has been satisfactorily improved.On this basis,this paper evaluates the simulation performance of the new coupled model for East Asia winter climate from 1985 to 2014,and tests the impact of the improved Arctic sea ice simulation performance on the East Asian winter climate simulation performance.Results show that the new coupled model can well simulate the winter sea level pressure,850 hPa wind vector and radiation flux in East Asian,which can improve the simulation effect of climatological distributions of temperature and precipitation in East Asian.Further analysis indicates that,compared with the original coupled model,the new coupled model can better capture the response of East Asia winter sea level pressure,total precipitation and temperature anomalies to the sea ice concentration anomaly in Barents and Kara seas in the same period,thus improving the simulation ability of the model to temperature and precipitation variability in the mid-high latitudes of East Asia in winter.
The Los Alamos Sea Ice Model 5.0 (CICE5.0) was introduced to the Beijing Climate Center Climate System Model (BCC_CSM) as a new alternative to the Sea Ice Simulator (SIS).The new coupled model performance on the Arctic sea ice and polar climate simulations has been satisfactorily improved.On this basis,this paper evaluates the simulation performance of the new coupled model for East Asia winter climate from 1985 to 2014,and tests the impact of the improved Arctic sea ice simulation performance on the East Asian winter climate simulation performance.Results show that the new coupled model can well simulate the winter sea level pressure,850 hPa wind vector and radiation flux in East Asian,which can improve the simulation effect of climatological distributions of temperature and precipitation in East Asian.Further analysis indicates that,compared with the original coupled model,the new coupled model can better capture the response of East Asia winter sea level pressure,total precipitation and temperature anomalies to the sea ice concentration anomaly in Barents and Kara seas in the same period,thus improving the simulation ability of the model to temperature and precipitation variability in the mid-high latitudes of East Asia in winter.
2021, 44(1):75-88.
DOI: 10.13878/j.cnki.dqkxxb.20201030012
Abstract:
Analyses and forecasts of extreme weather and anomalous climate require a precise reference state.The temporal climatology is a reference state coupling from the atmosphere and the surface when the Earth revolves both round the sun oriented radiation with the diurnal cycle of 24 hours and the annual cycle of 365 days.This paper depicts into three parts:1) it first examines synoptic and climatic anomalies including intra-seasonal anomaly,inter-annual anomaly,and different long-term trends (or inter-decadal anomalies) based on the daily-mean climatic state;2) it evaluates the meridional four-cell model,horizontal planetary-scale and regional-scale circulation systems from annual and intra-seasonal timescales within the climatic state;and 3) it recapitulates the asymmetrical distribution of anomalous climatic patterns linked with the long-term trends of the atmospheric circulation in the two hemispheres.
Analyses and forecasts of extreme weather and anomalous climate require a precise reference state.The temporal climatology is a reference state coupling from the atmosphere and the surface when the Earth revolves both round the sun oriented radiation with the diurnal cycle of 24 hours and the annual cycle of 365 days.This paper depicts into three parts:1) it first examines synoptic and climatic anomalies including intra-seasonal anomaly,inter-annual anomaly,and different long-term trends (or inter-decadal anomalies) based on the daily-mean climatic state;2) it evaluates the meridional four-cell model,horizontal planetary-scale and regional-scale circulation systems from annual and intra-seasonal timescales within the climatic state;and 3) it recapitulates the asymmetrical distribution of anomalous climatic patterns linked with the long-term trends of the atmospheric circulation in the two hemispheres.
2021, 44(1):89-103.
DOI: 10.13878/j.cnki.dqkxxb.20201013001
Abstract:
Based on the NCEP/NCAR reanalysis datasets,the ERA-Interim reanalysis datasets,and the observational data sets,this study investigates the relationship between the sea ice anomaly over the Barents Sea in March and the mode of "warm south-cold north"(WSCN) pattern in eastern China in August.The results indicate that the positive(negative) inconsistency of the Barents Sea ice in March corresponds to the mode of the "WSCN"("cold south-warm north",CSWN) pattern in eastern China in August.Further analyses suggested that the "WSCN"("CSWN") patterned was categorized by the atypical cyclone(anticyclone) and the ascending(sinking) motion over northeastern China as well as the uncharacteristic anticyclone(cyclone) and the sinking(ascending) motion over southern China.Besides,the surface net heat flux was mentioned as the "positive south-negative north"("negative south-positive north") pattern.Further analyses revealed that the "Silk Road" teleconnection pattern is closely related to the inconsistent atmospheric circulation in eastern China,which acts as a bridge to link the Barents Sea ice in March and the dipole temperature pattern in eastern China.Besides,the positive(negative) anomaly of the Barents Sea ice in March last until August,which accelerate the southward wave train over the Kara Sea,strength the negative phase(positive phase) of the "Silk Road" teleconnection,and further regulate the inconsistent atmospheric circulations in eastern China.On the other hand,the positive(negative) variance of the Barents Sea ice in spring results in lower(higher) temperature in northern Eurasia,which result in "positive western-negative eastern"("positive eastern-negative western") snow cover and "wet western-dry eastern"("dry western-wet eastern") soil moisture in northern Eurasia.The spatial pattern of soil moisture may last until August,which leads to the enhancement of the "Silk Road" teleconnection wave train,affecting the circulation anomaly in eastern China,and resulting in the dipole distribution of air temperature in eastern China in August.
Based on the NCEP/NCAR reanalysis datasets,the ERA-Interim reanalysis datasets,and the observational data sets,this study investigates the relationship between the sea ice anomaly over the Barents Sea in March and the mode of "warm south-cold north"(WSCN) pattern in eastern China in August.The results indicate that the positive(negative) inconsistency of the Barents Sea ice in March corresponds to the mode of the "WSCN"("cold south-warm north",CSWN) pattern in eastern China in August.Further analyses suggested that the "WSCN"("CSWN") patterned was categorized by the atypical cyclone(anticyclone) and the ascending(sinking) motion over northeastern China as well as the uncharacteristic anticyclone(cyclone) and the sinking(ascending) motion over southern China.Besides,the surface net heat flux was mentioned as the "positive south-negative north"("negative south-positive north") pattern.Further analyses revealed that the "Silk Road" teleconnection pattern is closely related to the inconsistent atmospheric circulation in eastern China,which acts as a bridge to link the Barents Sea ice in March and the dipole temperature pattern in eastern China.Besides,the positive(negative) anomaly of the Barents Sea ice in March last until August,which accelerate the southward wave train over the Kara Sea,strength the negative phase(positive phase) of the "Silk Road" teleconnection,and further regulate the inconsistent atmospheric circulations in eastern China.On the other hand,the positive(negative) variance of the Barents Sea ice in spring results in lower(higher) temperature in northern Eurasia,which result in "positive western-negative eastern"("positive eastern-negative western") snow cover and "wet western-dry eastern"("dry western-wet eastern") soil moisture in northern Eurasia.The spatial pattern of soil moisture may last until August,which leads to the enhancement of the "Silk Road" teleconnection wave train,affecting the circulation anomaly in eastern China,and resulting in the dipole distribution of air temperature in eastern China in August.
2021, 44(1):104-117.
DOI: 10.13878/j.cnki.dqkxxb.20201103001
Abstract:
Multi-physics ensemble simulation experiments of regional climate in China by CWRF (Climate-Weather Research and Forecasting model) for the period 1979-2016 were applied to analyze and evaluate the simulation of temperature and precipitation over the Tibetan Plateau and its sensitivity to horizontal resolution and parameterization scheme of physical processes.The results show that:1) Compared with global models,CWRF downscaling improves the simulation of temperature and precipitation over the plateau,reduces the root mean square error(RMSE) of the annual temperature cycle by nearly 1℃,and decreases the RMSE of the annual cycle of precipitation by 10-40 mm.At the same time,it significantly improves the correlation coefficient between simulated and measured interannual variability,with the highest increase of 0.6;2) Model's resolution has a significant impact on precipitation simulation.The difference of simulated precipitation by models with the different resolution is as high as 60 mm (54%),and the simulation deviation first decreases and then increases with the increased resolution,and the turning point is about 30 km;3) Physical process parameterization scheme has a significant impact on temperature and precipitation simulation.The difference in monthly average temperature between different schematais 1-4℃,and the difference in monthly precipitation in summer is 20-100 mm.Among them,the radiation scheme has the highest impact on temperature simulation,and the cumulus scheme has the utmost impact on precipitation.This paper provides a basis for the selection of physical parameterization and horizontal resolution for CWRF local optimization.
Multi-physics ensemble simulation experiments of regional climate in China by CWRF (Climate-Weather Research and Forecasting model) for the period 1979-2016 were applied to analyze and evaluate the simulation of temperature and precipitation over the Tibetan Plateau and its sensitivity to horizontal resolution and parameterization scheme of physical processes.The results show that:1) Compared with global models,CWRF downscaling improves the simulation of temperature and precipitation over the plateau,reduces the root mean square error(RMSE) of the annual temperature cycle by nearly 1℃,and decreases the RMSE of the annual cycle of precipitation by 10-40 mm.At the same time,it significantly improves the correlation coefficient between simulated and measured interannual variability,with the highest increase of 0.6;2) Model's resolution has a significant impact on precipitation simulation.The difference of simulated precipitation by models with the different resolution is as high as 60 mm (54%),and the simulation deviation first decreases and then increases with the increased resolution,and the turning point is about 30 km;3) Physical process parameterization scheme has a significant impact on temperature and precipitation simulation.The difference in monthly average temperature between different schematais 1-4℃,and the difference in monthly precipitation in summer is 20-100 mm.Among them,the radiation scheme has the highest impact on temperature simulation,and the cumulus scheme has the utmost impact on precipitation.This paper provides a basis for the selection of physical parameterization and horizontal resolution for CWRF local optimization.
2021, 44(1):118-127.
DOI: 10.13878/j.cnki.dqkxxb.20201031002
Abstract:
The initiation and advancement of surface waves(sea and swell) within the Arctic Ocean have been regulating by the wind forcing and the sea ice extent,which was clearly distinctive from the tropical and subtropical oceans.We present the current research advances of Arctic Ocean surface waves beneath distinctive ice coverage based on the perceptions of buoys,moorings,and ship-based measurements,as well as the studies based on satellite remote sensing and numerical simulations.The propagation mechanisms of waves in sea ice covered regions were evaluated too.The average significant wave height in the open water of the Arctic Ocean in summer can reach 3 m,and amid storms,the significant wave height can reach 5 m in the Beaufort Sea.Excluding the Atlantic division,the wave activity in the most range of the Arctic Ocean during summer has expanded within the past few decades,and the significant wave height on the Beaufort-Chukchi Sea has an expanding drift of approximately 1-3 cm/a.This trend is basically triggered by the collective impact of an increase in fetch due to the sea ice retreat,and the frequency and intensity of storms.The projection based on the CMIP5 multi-model simulations appears that compared with the historical period (1979-2005),the significant wave height over the Arctic Ocean at the end of this century (2081-2100) will increase by 3 cm/a,of which the highest increment happens within the eastern part of the central Arctic Ocean.Expanded wave movement advances the removal of through the wave-ice positive feedback mechanism during the melting period.In coastal zones,enhanced wave movement will quicken coastal erosion and promote the disintegration of coastal permafrost.Extreme waves can also pose a threat to shipping security.Future research needs to be conducted based on more and extensive field observations to deepen the understanding of the generation,development,propagation,and attenuation mechanisms of waves under the influence of changes in the sea ice extent and thickness,to progress the capacity to mimic and project waves in ice areas.
The initiation and advancement of surface waves(sea and swell) within the Arctic Ocean have been regulating by the wind forcing and the sea ice extent,which was clearly distinctive from the tropical and subtropical oceans.We present the current research advances of Arctic Ocean surface waves beneath distinctive ice coverage based on the perceptions of buoys,moorings,and ship-based measurements,as well as the studies based on satellite remote sensing and numerical simulations.The propagation mechanisms of waves in sea ice covered regions were evaluated too.The average significant wave height in the open water of the Arctic Ocean in summer can reach 3 m,and amid storms,the significant wave height can reach 5 m in the Beaufort Sea.Excluding the Atlantic division,the wave activity in the most range of the Arctic Ocean during summer has expanded within the past few decades,and the significant wave height on the Beaufort-Chukchi Sea has an expanding drift of approximately 1-3 cm/a.This trend is basically triggered by the collective impact of an increase in fetch due to the sea ice retreat,and the frequency and intensity of storms.The projection based on the CMIP5 multi-model simulations appears that compared with the historical period (1979-2005),the significant wave height over the Arctic Ocean at the end of this century (2081-2100) will increase by 3 cm/a,of which the highest increment happens within the eastern part of the central Arctic Ocean.Expanded wave movement advances the removal of through the wave-ice positive feedback mechanism during the melting period.In coastal zones,enhanced wave movement will quicken coastal erosion and promote the disintegration of coastal permafrost.Extreme waves can also pose a threat to shipping security.Future research needs to be conducted based on more and extensive field observations to deepen the understanding of the generation,development,propagation,and attenuation mechanisms of waves under the influence of changes in the sea ice extent and thickness,to progress the capacity to mimic and project waves in ice areas.
2021, 44(1):128-139.
DOI: 10.13878/j.cnki.dqkxxb.20200928001
Abstract:
Based on the International Bathymetric Chart of the Southern Ocean Version 1.0 (IBCSO V1),we rebuilt an improved high resolution digital bathymetric model for the bathymetry of Prydz Bay and the surrounding region by compiling the water depths from in situ hydrography observations.After removing the reduplicated data from multiple data sets,we compared the water depths from the in situ hydrography observations with the seafloor depths from the IBCSO V1 on the original IBCSO grid with a 500 m×500 m spatial resolution.In the revised bathymetry,the data including multi-beam and single-beam echo soundings,digitized depths from nautical charts in IBCSO complete preserved,and only the interpolated bathymetry in IBCSO revise,using the water depths from in situ hydrography observations with a specific gridding technique.Our bathymetry revision is mostly benefited from the remarks by equipped seals,especially in the coastal regions from south of Davis Station to 82°E,west of Amery Ice shelf front and the neighborhood of West Ice Shelf front,where benthic observations existed and the ocean bottom is extremely deepened compared to the current datasets.The improved digital bathymetric model provides insights into new topographical features in these regions.Besides,,by revealing an accurate seafloor around the continental shelf region of Prydz Bay,it can favor our understanding of the dynamic influences of bathymetry on the circulations of the ocean and the sea ice and the basal mass balance of the Amery Ice Shelf.
Based on the International Bathymetric Chart of the Southern Ocean Version 1.0 (IBCSO V1),we rebuilt an improved high resolution digital bathymetric model for the bathymetry of Prydz Bay and the surrounding region by compiling the water depths from in situ hydrography observations.After removing the reduplicated data from multiple data sets,we compared the water depths from the in situ hydrography observations with the seafloor depths from the IBCSO V1 on the original IBCSO grid with a 500 m×500 m spatial resolution.In the revised bathymetry,the data including multi-beam and single-beam echo soundings,digitized depths from nautical charts in IBCSO complete preserved,and only the interpolated bathymetry in IBCSO revise,using the water depths from in situ hydrography observations with a specific gridding technique.Our bathymetry revision is mostly benefited from the remarks by equipped seals,especially in the coastal regions from south of Davis Station to 82°E,west of Amery Ice shelf front and the neighborhood of West Ice Shelf front,where benthic observations existed and the ocean bottom is extremely deepened compared to the current datasets.The improved digital bathymetric model provides insights into new topographical features in these regions.Besides,,by revealing an accurate seafloor around the continental shelf region of Prydz Bay,it can favor our understanding of the dynamic influences of bathymetry on the circulations of the ocean and the sea ice and the basal mass balance of the Amery Ice Shelf.
2021, 44(1):140-150.
DOI: 10.13878/j.cnki.dqkxxb.20201027001
Abstract:
Using the monthly data of sea ice concentration,precipitation,sea surface temperature,500 hPa geopotential height,and 850 hPa wind field under RCP8.5 scenario of MPI-ESM-LR model,a comparative analysis of the difference of relationship between spring Arctic sea ice and East Asian summer precipitation before and after Arctic sea ice abrupt change and explore its possible causes.The results show that 1)The abrupt change of Arctic sea ice has caused changes in the Arctic Sea Ice Concentration (SIC) and ENSO's influence on East Asian summer precipitation.Before the abrupt change,SIC and ENSO jointly affect the interannual variation of precipitation;after the abrupt change,ENSO dominates the EOF's first mode of precipitation,and SIC dominates the EOF's second mode of precipitation;2)Before the abrupt change of Arctic sea ice,ENSO and SIC affected the 850 hPa wind field in the whole east Asia through the 500 hPa meridional wave train,and eventually leading to a tripole-type precipitation mode.After the sudden change,ENSO affects the 850 hPa wind field in South China through the 500 hPa meridional wave train,leading to the dipole spatial mode of rainfall,which dominates the EOF's first mode of precipitation;Meanwhile,SIC influences the wind field of 850 hPa in the north through the 500 hPa zonal wave train in east Asia and finally dominates the EOF's second mode of precipitation.3)Rapid change in Arctic sea ice,the regional differences of East Asia observed from the effects of ENSO and SIC on summer precipitation.Before the abrupt change of Arctic sea ice,ENSO and SIC jointly affected rainfall in North and South China;after the abrupt change of Arctic sea ice,SIC mainly affected precipitation in North China,and ENSO mainly affected rainfall in South China.
Using the monthly data of sea ice concentration,precipitation,sea surface temperature,500 hPa geopotential height,and 850 hPa wind field under RCP8.5 scenario of MPI-ESM-LR model,a comparative analysis of the difference of relationship between spring Arctic sea ice and East Asian summer precipitation before and after Arctic sea ice abrupt change and explore its possible causes.The results show that 1)The abrupt change of Arctic sea ice has caused changes in the Arctic Sea Ice Concentration (SIC) and ENSO's influence on East Asian summer precipitation.Before the abrupt change,SIC and ENSO jointly affect the interannual variation of precipitation;after the abrupt change,ENSO dominates the EOF's first mode of precipitation,and SIC dominates the EOF's second mode of precipitation;2)Before the abrupt change of Arctic sea ice,ENSO and SIC affected the 850 hPa wind field in the whole east Asia through the 500 hPa meridional wave train,and eventually leading to a tripole-type precipitation mode.After the sudden change,ENSO affects the 850 hPa wind field in South China through the 500 hPa meridional wave train,leading to the dipole spatial mode of rainfall,which dominates the EOF's first mode of precipitation;Meanwhile,SIC influences the wind field of 850 hPa in the north through the 500 hPa zonal wave train in east Asia and finally dominates the EOF's second mode of precipitation.3)Rapid change in Arctic sea ice,the regional differences of East Asia observed from the effects of ENSO and SIC on summer precipitation.Before the abrupt change of Arctic sea ice,ENSO and SIC jointly affected rainfall in North and South China;after the abrupt change of Arctic sea ice,SIC mainly affected precipitation in North China,and ENSO mainly affected rainfall in South China.
2021, 44(1):151-164.
DOI: 10.13878/j.cnki.dqkxxb.20180424001
Abstract:
This study analyzed the ERA-Interim data from the European Centre for Medium-Range Weather Forecasts and NECP reanalysis data from the National Oceanic and Atmospheric Administration Earth System Research Laboratory in the Antarctic region to compare with the radiosonde data derived from the Antarctic 18 stations, assessed the applicability of these two reanalysis data sets in the upper atmosphere.The results demonstrated that the reanalysis data sequentially drift away from the radiosonde data steadily in four meteorological elements with the increase in height over the Antarctic.The biases in geopotential height and temperature in the two reanalysis data are relatively small,but the differences of wind direction between the sounding data and the two sets of reanalysis data are quite huge.The differences in wind speed between the sounding data and the two sets of reanalysis data are quite large at 300 hPa.In the seasonal distributions of these biases,the differences of the geopotential height and temperature between the sounding data and the two sets of reanalysis data are huge in the austral spring but are relatively small in autumn,summer,and winter.The difference in the wind speed between the sounding data and the two sets of reanalysis data is relatively small in summer.The difference of the wind direction between the sounding data and the two sets of reanalysis data is relatively large but has no significant seasonal dependency.Nevertheless,both reanalysis data sets have large biases,ERA-Interim performs better than NCEP as a whole.The results suggest that using the data from these two reanalysis data sets as initial and boundary conditions to drive regional atmospheric models can lead to large model biases.Thus,more intensive radiosonde observations are necessitated for improving the qualities of reanalysis data,along with further improvements in the data assimilation and model system.
This study analyzed the ERA-Interim data from the European Centre for Medium-Range Weather Forecasts and NECP reanalysis data from the National Oceanic and Atmospheric Administration Earth System Research Laboratory in the Antarctic region to compare with the radiosonde data derived from the Antarctic 18 stations, assessed the applicability of these two reanalysis data sets in the upper atmosphere.The results demonstrated that the reanalysis data sequentially drift away from the radiosonde data steadily in four meteorological elements with the increase in height over the Antarctic.The biases in geopotential height and temperature in the two reanalysis data are relatively small,but the differences of wind direction between the sounding data and the two sets of reanalysis data are quite huge.The differences in wind speed between the sounding data and the two sets of reanalysis data are quite large at 300 hPa.In the seasonal distributions of these biases,the differences of the geopotential height and temperature between the sounding data and the two sets of reanalysis data are huge in the austral spring but are relatively small in autumn,summer,and winter.The difference in the wind speed between the sounding data and the two sets of reanalysis data is relatively small in summer.The difference of the wind direction between the sounding data and the two sets of reanalysis data is relatively large but has no significant seasonal dependency.Nevertheless,both reanalysis data sets have large biases,ERA-Interim performs better than NCEP as a whole.The results suggest that using the data from these two reanalysis data sets as initial and boundary conditions to drive regional atmospheric models can lead to large model biases.Thus,more intensive radiosonde observations are necessitated for improving the qualities of reanalysis data,along with further improvements in the data assimilation and model system.
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