Colored dissolved organic matter(CDOM)is a crucial constituent that affects the optical absorption properties of seawater.Owing to the relatively limited measured data on the spatial distribution characteristics of CD...Colored dissolved organic matter(CDOM)is a crucial constituent that affects the optical absorption properties of seawater.Owing to the relatively limited measured data on the spatial distribution characteristics of CDOM in the tropical eastern Indian Ocean,this study analyzes the optical absorption characteristics of CDOM in the southeast Indian Ocean using the data collected during four seasons from 2013 to 2017.This work also systematically describes the seasonal horizontal and vertical distribution characteristics of CDOM in this area and conducts a preliminary analysis of the relevant factors affecting CDOM absorption characteristics in this region.Results indicate that the CDOM ag(440)during summer was remarkably lower than that in the coastal waters of Europe and coastal waters of China but slightly higher than that in the western and southeast Pacific.The spatial distribution of surface CDOM shows remarkable seasonal differences,and the spatial distribution characteristics of CDOM in the 5°S,92°E region differ between spring/summer and autumn/winter.The values of ag(400)and ag(440)are weak/strong at a surface/subsurface level of 100 m,with differences found between summer and winter.The correlation of CDOM with temperature,salinity,and chlorophyll-a concentration is relatively low,indicating that CDOM is an independent driving mechanism influenced by phytoplankton degradation,photobleaching,and water mixing.展开更多
Offshore waters provide resources for human beings,while on the other hand,threaten them because of marine disasters.Ocean stations are part of offshore observation networks,and the quality of their data is of great s...Offshore waters provide resources for human beings,while on the other hand,threaten them because of marine disasters.Ocean stations are part of offshore observation networks,and the quality of their data is of great significance for exploiting and protecting the ocean.We used hourly mean wave height,temperature,and pressure real-time observation data taken in the Xiaomaidao station(in Qingdao,China)from June 1,2017,to May 31,2018,to explore the data quality using eight quality control methods,and to discriminate the most effective method for Xiaomaidao station.After using the eight quality control methods,the percentages of the mean wave height,temperature,and pressure data that passed the tests were 89.6%,88.3%,and 98.6%,respectively.With the marine disaster(wave alarm report)data,the values failed in the test mainly due to the influence of aging observation equipment and missing data transmissions.The mean wave height is often affected by dynamic marine disasters,so the continuity test method is not effective.The correlation test with other related parameters would be more useful for the mean wave height.展开更多
The wind-sea and swell climates in the China Seas are investigated by using the 27-yr Integrated Ocean Waves for Geophysical and other Applications(IOWAGA)hindcast data.A comparison is made between the significant wav...The wind-sea and swell climates in the China Seas are investigated by using the 27-yr Integrated Ocean Waves for Geophysical and other Applications(IOWAGA)hindcast data.A comparison is made between the significant wave height from the IOWAGA hindcasts and that from a jointly calibrated altimetry dataset,showing the good performance of the IOWAGA hindcasts in the China Seas.A simple but practical method of diagnosing whether the sea state is wind-sea-dominant or swell-dominant is proposed based on spectral partitioning.Different from the characteristics of wind-seas and swells in the open ocean,the wave fields in the enclosed seas such as the China Seas are predominated by wind-sea events in respect of both frequencies of occurrences and energy weights,due to the island sheltering and limited fetches.The energy weights of wind-seas in a given location is usually more significant than the occurrence probability of wind-sea-dominated events,as the wave energy is higher in the wind-sea events than in the swell events on average and extreme wave heights are mostly related to wind-seas.The most energetic swells in the China Seas(and other enclosed seas)are‘local swells’,having just propagated out of their generation areas.However,the swells coming from the West Pacific also play an important role in the wave climate of the China Seas,which can only be revealed by partitioning different swell systems in the wave spectra as the energy of them is significantly less than the‘local swells’.展开更多
In this study, the temporal and spatial variations of observed global oceanic precipitation during 1979–2010 are investigated. It is found that the global trend in precipitation during this period varies at a rate of...In this study, the temporal and spatial variations of observed global oceanic precipitation during 1979–2010 are investigated. It is found that the global trend in precipitation during this period varies at a rate of 1.5%/K of surface warming while the rate is 6.6%/K during 2006–2010. The precipitation is highly correlated with Sea Surface Temperature(SST) in both the temporal and the spatial patterns since the strong 1997–98 El Nino event. Considering the distributions of precipitation and SST, seven oceanic regions are classified and presented using the observed Global Precipitation Climatology Project(GPCP) data and Extended Reconstructed Sea Surface Temperatures, version 3(ERSST.v3) data. Further examining the mechanisms of the classified oceanic precipitation regions is conducted using the Tropical Rainfall Measuring Mission(TRMM) satellite, GFDL-ESM-2G model precipitation and SST data and Hadley Center sea ice and SST version 1(Had ISST1) data. More than 85% of global oceanic precipitations are controlled by either one or both of the warmer-get-wetter mechanism and wet-get-wetter mechanism. It is estimated that a 0.5 SST signal-to-noise ratio, representing the trend of SST time series to the standard deviation, is a criterion to distinguish the mechanism of a region. When the SST ratio is larger than 0.5, the precipitation of this region is controlled by the warmer-get-wetter mechanism. SST, rather than the humidity, is the pivotal factor. On the other hand, when the SST ratio is less than 0.5, the precipitation is controlled by the wet-get-wetter mechanism. The SST variability is a significant factor contributing to the precipitation variation.展开更多
基金The study has received support from the National Natural Science Foundation of China(No.41906182)the National Program on Global Change and Air-Sea Interactions(No.GASI-01-WIND-STwin)the Program of Shandong Key Laboratory of Marine Ecological Environment and Disaster Prevention and Mitigation(Nos.202102,202209 and 201901).
文摘Colored dissolved organic matter(CDOM)is a crucial constituent that affects the optical absorption properties of seawater.Owing to the relatively limited measured data on the spatial distribution characteristics of CDOM in the tropical eastern Indian Ocean,this study analyzes the optical absorption characteristics of CDOM in the southeast Indian Ocean using the data collected during four seasons from 2013 to 2017.This work also systematically describes the seasonal horizontal and vertical distribution characteristics of CDOM in this area and conducts a preliminary analysis of the relevant factors affecting CDOM absorption characteristics in this region.Results indicate that the CDOM ag(440)during summer was remarkably lower than that in the coastal waters of Europe and coastal waters of China but slightly higher than that in the western and southeast Pacific.The spatial distribution of surface CDOM shows remarkable seasonal differences,and the spatial distribution characteristics of CDOM in the 5°S,92°E region differ between spring/summer and autumn/winter.The values of ag(400)and ag(440)are weak/strong at a surface/subsurface level of 100 m,with differences found between summer and winter.The correlation of CDOM with temperature,salinity,and chlorophyll-a concentration is relatively low,indicating that CDOM is an independent driving mechanism influenced by phytoplankton degradation,photobleaching,and water mixing.
基金Supported by the National Key Research and Development Program of China(Nos.2016YFC1402000,2018YFC1407003,2017YFC1405300)
文摘Offshore waters provide resources for human beings,while on the other hand,threaten them because of marine disasters.Ocean stations are part of offshore observation networks,and the quality of their data is of great significance for exploiting and protecting the ocean.We used hourly mean wave height,temperature,and pressure real-time observation data taken in the Xiaomaidao station(in Qingdao,China)from June 1,2017,to May 31,2018,to explore the data quality using eight quality control methods,and to discriminate the most effective method for Xiaomaidao station.After using the eight quality control methods,the percentages of the mean wave height,temperature,and pressure data that passed the tests were 89.6%,88.3%,and 98.6%,respectively.With the marine disaster(wave alarm report)data,the values failed in the test mainly due to the influence of aging observation equipment and missing data transmissions.The mean wave height is often affected by dynamic marine disasters,so the continuity test method is not effective.The correlation test with other related parameters would be more useful for the mean wave height.
基金supported by the National Key R&D Program of China (No. 2017YFC1404700) the National Natural Science Foundation of China (No. 41806010)+2 种基金 Laboratory for Regional Oceanography and Numerical Modeling,Qingdao National Laboratory for Marine Science and Technology (No. 2019A03) the Discipline Layout Project for Basic Research of Shenzhen Science and Technology Innovation Committee (No. 20170418) the Guangdong Special Fund Program for Marine Economy Development (No. GDME-2018E001)
文摘The wind-sea and swell climates in the China Seas are investigated by using the 27-yr Integrated Ocean Waves for Geophysical and other Applications(IOWAGA)hindcast data.A comparison is made between the significant wave height from the IOWAGA hindcasts and that from a jointly calibrated altimetry dataset,showing the good performance of the IOWAGA hindcasts in the China Seas.A simple but practical method of diagnosing whether the sea state is wind-sea-dominant or swell-dominant is proposed based on spectral partitioning.Different from the characteristics of wind-seas and swells in the open ocean,the wave fields in the enclosed seas such as the China Seas are predominated by wind-sea events in respect of both frequencies of occurrences and energy weights,due to the island sheltering and limited fetches.The energy weights of wind-seas in a given location is usually more significant than the occurrence probability of wind-sea-dominated events,as the wave energy is higher in the wind-sea events than in the swell events on average and extreme wave heights are mostly related to wind-seas.The most energetic swells in the China Seas(and other enclosed seas)are‘local swells’,having just propagated out of their generation areas.However,the swells coming from the West Pacific also play an important role in the wave climate of the China Seas,which can only be revealed by partitioning different swell systems in the wave spectra as the energy of them is significantly less than the‘local swells’.
基金supported by the National Basic Research Program of China (2012CB955603)the Natural Science Foundation of China (41076115)Basic Scientific Research Operating Expenses of Ocean University of China
文摘In this study, the temporal and spatial variations of observed global oceanic precipitation during 1979–2010 are investigated. It is found that the global trend in precipitation during this period varies at a rate of 1.5%/K of surface warming while the rate is 6.6%/K during 2006–2010. The precipitation is highly correlated with Sea Surface Temperature(SST) in both the temporal and the spatial patterns since the strong 1997–98 El Nino event. Considering the distributions of precipitation and SST, seven oceanic regions are classified and presented using the observed Global Precipitation Climatology Project(GPCP) data and Extended Reconstructed Sea Surface Temperatures, version 3(ERSST.v3) data. Further examining the mechanisms of the classified oceanic precipitation regions is conducted using the Tropical Rainfall Measuring Mission(TRMM) satellite, GFDL-ESM-2G model precipitation and SST data and Hadley Center sea ice and SST version 1(Had ISST1) data. More than 85% of global oceanic precipitations are controlled by either one or both of the warmer-get-wetter mechanism and wet-get-wetter mechanism. It is estimated that a 0.5 SST signal-to-noise ratio, representing the trend of SST time series to the standard deviation, is a criterion to distinguish the mechanism of a region. When the SST ratio is larger than 0.5, the precipitation of this region is controlled by the warmer-get-wetter mechanism. SST, rather than the humidity, is the pivotal factor. On the other hand, when the SST ratio is less than 0.5, the precipitation is controlled by the wet-get-wetter mechanism. The SST variability is a significant factor contributing to the precipitation variation.
