To research the relationship between coral growth rate and sea surface temperature ( Tss), 5 cores of living Porites lutea were collected from the Xisha Islands and the southern Hainan Island waters and measured. The ...To research the relationship between coral growth rate and sea surface temperature ( Tss), 5 cores of living Porites lutea were collected from the Xisha Islands and the southern Hainan Island waters and measured. The results of the study show that there is an obviously positive correlation between the coral growth rates and the Tss records from the northern part of South China Sea. The annual growth rates of the five samples of Porites lutea during the past 100 a are in the range of 7-15 mm/a, and their mean value is 11 mm/a. The correlation coefficients between the coral growth rates and the Tss records from the waters during 1961-1993 are in the range of 0. 77-0.89. As a result, a thermometer of the coral growth rate is established. A hindcasting Tss in the waters from 1993 to 1961 has been obtained with an error of about 0.12-0.17℃ . Based upon the calculated result, the rising rate of Tss in the northern part of South China Sea during the past 100 a is 0. 20℃ , which is higher than that of the air temperature in China (0.09℃/100 a), but lower than that of the global temperature and that of Tss in the tropical western Pacific Ocean.展开更多
Wave parameters, such as wave height and wave period, are important for human activities, such as navigation, ocean engineering and sediment transport, etc. In this study, wave data from six buoys around Chinese water...Wave parameters, such as wave height and wave period, are important for human activities, such as navigation, ocean engineering and sediment transport, etc. In this study, wave data from six buoys around Chinese waters, are used to assess the quality of wave height and wave period in the ERA5 reanalysis of the European Centre for Medium-Range Weather Forecasts. Annual hourly data with temporal resolution are used. The difference between the significant wave height(SWH) of ERA 5 and that of the buoy varies from-0.35 m to 0.30 m for the three shallow locations;for the three deep locations, the variation ranges from-0.09 m to 0.09 m. The ERA5 SWH data show positive biases, indicating an overall overestimation for all locations, except for E2 and S1 where underestimation is observed. During the tropical cyclone period, a large(about 32%) underestimation of the maximum SWH in the ERA5 data is observed. Hence, the ERA5 SWH data cannot be used for design applications without site-specific validation. The difference between the annual wave period from ERA5 and the mean wave period from the buoys varies from-1.31 s to 0.4 s. Inter-comparisons suggest that the ERA5 dataset is consistent with the annual mean SWH. However, for the average period, the performance is not good, and half of the correlation coefficients in the four points are less 50%. Overall, the deep water area simulation effect is better than that in the shallow water.展开更多
Using the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） version g1.11, a group of seasonal hindcasting experiments were carried out. In order to investigate the potential predictability of sea surface ...Using the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） version g1.11, a group of seasonal hindcasting experiments were carried out. In order to investigate the potential predictability of sea surface temperature （SST）, singular value decomposition （SVD） analyses were applied to extract dominant coupled modes between observed and predicated SST from the hindcasting experiments in this study. The fields discussed are sea surface temperature anomalies over the tropical Pacific basin （20~0S-20~0N, 120~0E- 80~0W）, respectively starting in four seasons from 1982 to 2005. On the basis of SVD analysis, the simulated pattern was replaced with the corresponding observed pattern to reconstruct SST anomaly fields to improve the ability of the simulation. The predictive skill, anomaly correlation coefficients （ACC）, after systematic error correction using the first five modes was regarded as potential predictability. Results showed that： 1） the statistical postprocessing approach was effective for systematic error correction; 2） model error sources mainly arose from mode 2 extracted from the SVD analysis-that is, during the transition phase of ENSO, the model encountered the spring predictability barrier; and 3） potential predictability （upper limits of predictability） could be high over most of the tropical Pacific basin, including the tropical western Pacific and an extra 10-degrees region of the mid and eastern Pacific.展开更多
The 22-year(1998-2019)surface seawater dimethylsulfi de(DMS)concentrations in the Yellow Sea(YS)were hindcasted based on satellite sea surface temperature(SST)and chlorophyll-a(Chl-a)data using a generalized additive ...The 22-year(1998-2019)surface seawater dimethylsulfi de(DMS)concentrations in the Yellow Sea(YS)were hindcasted based on satellite sea surface temperature(SST)and chlorophyll-a(Chl-a)data using a generalized additive mixed model(GAMM).A continuous monthly dataset of DMS concentration in the YS was obtained after using the data interpolation empirical orthogonal function(DINEOF)to reconstruct missing information in the dataset.Then,the interannual DMS variability in the YS was analyzed.The results indicated that the monthly climatological DMS concentration in the YS was 3.61 nmol/L.DMS concentrations in the spring and summer were signifi cantly higher than those in the autumn and winter.DMS concentrations were highest in coastal YS waters and lowest primarily in off shore YS waters.Interannual DMS variability between 1998 and 2019 was subdivided into two inverse phases:with the exception of the central YS,DMS increased before the turning point and decreased after.The turning point in interannual DMS variation was earlier in the inshore YS as compared to the central YS.Spectrum analysis identifi ed some signifi cant patterns of interannual variation in the DMS anomaly in the YS.Chl a appeared to be the main factor infl uencing interannual trends in DMS in the YS.Interannual DMS variability was under the joint control of Chl a and SST.However,short-term interannual DMS variation(2-3 years)was primarily related to SST,while longer term interannual DMS variation(6-8 years)was signifi cantly correlated with Chl a and SST.展开更多
The risk of wind waves in a bay is often overlooked,owing to the belief that peninsulas and islands will inhibit high waves.However,during the passage of a tropical cyclone,a semi-enclosed bay is exposed to twodirecti...The risk of wind waves in a bay is often overlooked,owing to the belief that peninsulas and islands will inhibit high waves.However,during the passage of a tropical cyclone,a semi-enclosed bay is exposed to twodirectional waves:one generated inside the bay and the other propagated from the outer sea.Typhoon Faxai in 2019 resulted in the worst coastal disaster in Tokyo Bay in the last few decades.The authors conducted a post-disaster survey immediately after this typhoon.Numerical modeling was also performed to reveal the mechanisms of unusual high waves.No significant high-wave damage occurred on coasts facing the Pacific Ocean.By contrast,Fukuura-Yokohama,which faces Tokyo Bay,suffered overtopping waves that collapsed seawalls.To precisely reproduce multi-directional waves,the authors developed an extended parametric typhoon model,which was embedded in the JMA mesoscale meteorological model(JMA-MSM).The peak wave height was estimated to be 3.4 m off the coast of Fukuura,in which the contribution of the outer-sea waves was as low as 10%–20%.A fetchlimited wave developed over a short distance in the bay is considered the primary mechanism of the high wave.The maximum wave occurred on the left-hand side of the typhoon track in the bay,which appears to be contrary to the common understanding that it is safer within the semicircle of a storm than on the opposite side.Typhoon Faxai was a small typhoon;however,if the radius was tripled,it is estimated that the wave height would exceed 3 m over the entire bay and surpass 4 m off the coasts of Yokohama and Chiba.展开更多
Using the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM) under the Chinese Academy of Sciences, 30-year extraseasonal short-term ensemble hincast of win...Using the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM) under the Chinese Academy of Sciences, 30-year extraseasonal short-term ensemble hincast of winter climate is performed, with integrations starting from annual autumn during 1969—1998. Winter climate predictability over China is then evaluated for the first time. It follows that the predictability is higher in tropics than in extratropics. Also, it is higher over ocean compared with land, especially for surface air temperature. With height increasing in troposphere, the predictability of geopotential height slightly changes zonally, but for weakening of band-ship distribution and dropping near the date line. Of all analyzed variables, the prediction skill of air temperature and geopotential height (precipitation) is the highest (smallest). In addition, the predictability of winter climate over China and even East Asia enhances obviously during ENSO cycle, especially during La Nia phase. Simulation comparison against verifying analysis for surface temperature anomaly exhibits the model抯 skill in predicting surface temperature抯 interannual variation trend in winter.展开更多
基金Project supported by the National Natural Science Foundation of China and the Multidesciplinary Oceanographic Expedition Team of Chinese Academy of Sciences to the Nansha Islands
文摘To research the relationship between coral growth rate and sea surface temperature ( Tss), 5 cores of living Porites lutea were collected from the Xisha Islands and the southern Hainan Island waters and measured. The results of the study show that there is an obviously positive correlation between the coral growth rates and the Tss records from the northern part of South China Sea. The annual growth rates of the five samples of Porites lutea during the past 100 a are in the range of 7-15 mm/a, and their mean value is 11 mm/a. The correlation coefficients between the coral growth rates and the Tss records from the waters during 1961-1993 are in the range of 0. 77-0.89. As a result, a thermometer of the coral growth rate is established. A hindcasting Tss in the waters from 1993 to 1961 has been obtained with an error of about 0.12-0.17℃ . Based upon the calculated result, the rising rate of Tss in the northern part of South China Sea during the past 100 a is 0. 20℃ , which is higher than that of the air temperature in China (0.09℃/100 a), but lower than that of the global temperature and that of Tss in the tropical western Pacific Ocean.
基金supported by National Key R&D Program of China(No.2018YFB1501901)the National Natural Science Foundation of China(No.51909114)+2 种基金the Major Research Grant(Nos.U1806227 and U1906231)from the Natural Science Foundation of China and the Provincial Natural Science Foundation of Shandongthe Open Research Fund of the Key Laboratory of Ocean Circulation and Waves,Chinese Academy of Sciences(No.KLOCW1901)the Open Research Fund of State Key Laboratory of Tropical Oceanography,South China Sea Institute of Oceanology,Chinese Academy of Sciences(No.LTO1905).
文摘Wave parameters, such as wave height and wave period, are important for human activities, such as navigation, ocean engineering and sediment transport, etc. In this study, wave data from six buoys around Chinese waters, are used to assess the quality of wave height and wave period in the ERA5 reanalysis of the European Centre for Medium-Range Weather Forecasts. Annual hourly data with temporal resolution are used. The difference between the significant wave height(SWH) of ERA 5 and that of the buoy varies from-0.35 m to 0.30 m for the three shallow locations;for the three deep locations, the variation ranges from-0.09 m to 0.09 m. The ERA5 SWH data show positive biases, indicating an overall overestimation for all locations, except for E2 and S1 where underestimation is observed. During the tropical cyclone period, a large(about 32%) underestimation of the maximum SWH in the ERA5 data is observed. Hence, the ERA5 SWH data cannot be used for design applications without site-specific validation. The difference between the annual wave period from ERA5 and the mean wave period from the buoys varies from-1.31 s to 0.4 s. Inter-comparisons suggest that the ERA5 dataset is consistent with the annual mean SWH. However, for the average period, the performance is not good, and half of the correlation coefficients in the four points are less 50%. Overall, the deep water area simulation effect is better than that in the shallow water.
基金supported by the National Natural Science Foundation of China (NSFC) (Grant Nos. 40975065 and 40821092)the National Basic Research Program (NBRP) "Ocean–atmosphere interaction over the joining area of Asia and the Indian-Pacific Ocean (AIPO) and its impact on the short-term climate variation in China" project(2006CB403605)
文摘Using the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） version g1.11, a group of seasonal hindcasting experiments were carried out. In order to investigate the potential predictability of sea surface temperature （SST）, singular value decomposition （SVD） analyses were applied to extract dominant coupled modes between observed and predicated SST from the hindcasting experiments in this study. The fields discussed are sea surface temperature anomalies over the tropical Pacific basin （20~0S-20~0N, 120~0E- 80~0W）, respectively starting in four seasons from 1982 to 2005. On the basis of SVD analysis, the simulated pattern was replaced with the corresponding observed pattern to reconstruct SST anomaly fields to improve the ability of the simulation. The predictive skill, anomaly correlation coefficients （ACC）, after systematic error correction using the first five modes was regarded as potential predictability. Results showed that： 1） the statistical postprocessing approach was effective for systematic error correction; 2） model error sources mainly arose from mode 2 extracted from the SVD analysis-that is, during the transition phase of ENSO, the model encountered the spring predictability barrier; and 3） potential predictability （upper limits of predictability） could be high over most of the tropical Pacific basin, including the tropical western Pacific and an extra 10-degrees region of the mid and eastern Pacific.
基金Supported by the National Key Research and Development Program of China(No.2016YFA0601301)the National Natural Science Foundation of China(No.41876018)the Tianjin Natural Science Foundation(No.19JCZDJC40600)。
文摘The 22-year(1998-2019)surface seawater dimethylsulfi de(DMS)concentrations in the Yellow Sea(YS)were hindcasted based on satellite sea surface temperature(SST)and chlorophyll-a(Chl-a)data using a generalized additive mixed model(GAMM).A continuous monthly dataset of DMS concentration in the YS was obtained after using the data interpolation empirical orthogonal function(DINEOF)to reconstruct missing information in the dataset.Then,the interannual DMS variability in the YS was analyzed.The results indicated that the monthly climatological DMS concentration in the YS was 3.61 nmol/L.DMS concentrations in the spring and summer were signifi cantly higher than those in the autumn and winter.DMS concentrations were highest in coastal YS waters and lowest primarily in off shore YS waters.Interannual DMS variability between 1998 and 2019 was subdivided into two inverse phases:with the exception of the central YS,DMS increased before the turning point and decreased after.The turning point in interannual DMS variation was earlier in the inshore YS as compared to the central YS.Spectrum analysis identifi ed some signifi cant patterns of interannual variation in the DMS anomaly in the YS.Chl a appeared to be the main factor infl uencing interannual trends in DMS in the YS.Interannual DMS variability was under the joint control of Chl a and SST.However,short-term interannual DMS variation(2-3 years)was primarily related to SST,while longer term interannual DMS variation(6-8 years)was signifi cantly correlated with Chl a and SST.
基金funded by grants awarded to Tokyo Institute of Technology(Japan Society for the Promotion of Science,Nos.16KK0121,19K04964 and 19K24677).
文摘The risk of wind waves in a bay is often overlooked,owing to the belief that peninsulas and islands will inhibit high waves.However,during the passage of a tropical cyclone,a semi-enclosed bay is exposed to twodirectional waves:one generated inside the bay and the other propagated from the outer sea.Typhoon Faxai in 2019 resulted in the worst coastal disaster in Tokyo Bay in the last few decades.The authors conducted a post-disaster survey immediately after this typhoon.Numerical modeling was also performed to reveal the mechanisms of unusual high waves.No significant high-wave damage occurred on coasts facing the Pacific Ocean.By contrast,Fukuura-Yokohama,which faces Tokyo Bay,suffered overtopping waves that collapsed seawalls.To precisely reproduce multi-directional waves,the authors developed an extended parametric typhoon model,which was embedded in the JMA mesoscale meteorological model(JMA-MSM).The peak wave height was estimated to be 3.4 m off the coast of Fukuura,in which the contribution of the outer-sea waves was as low as 10%–20%.A fetchlimited wave developed over a short distance in the bay is considered the primary mechanism of the high wave.The maximum wave occurred on the left-hand side of the typhoon track in the bay,which appears to be contrary to the common understanding that it is safer within the semicircle of a storm than on the opposite side.Typhoon Faxai was a small typhoon;however,if the radius was tripled,it is estimated that the wave height would exceed 3 m over the entire bay and surpass 4 m off the coasts of Yokohama and Chiba.
基金This work was jointly supported by the National Natural Science Foundation of China(Grant No.40125014)the Chinese Academy of Sciences(Grant No.KZCX2-203).
文摘Using the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM) under the Chinese Academy of Sciences, 30-year extraseasonal short-term ensemble hincast of winter climate is performed, with integrations starting from annual autumn during 1969—1998. Winter climate predictability over China is then evaluated for the first time. It follows that the predictability is higher in tropics than in extratropics. Also, it is higher over ocean compared with land, especially for surface air temperature. With height increasing in troposphere, the predictability of geopotential height slightly changes zonally, but for weakening of band-ship distribution and dropping near the date line. Of all analyzed variables, the prediction skill of air temperature and geopotential height (precipitation) is the highest (smallest). In addition, the predictability of winter climate over China and even East Asia enhances obviously during ENSO cycle, especially during La Nia phase. Simulation comparison against verifying analysis for surface temperature anomaly exhibits the model抯 skill in predicting surface temperature抯 interannual variation trend in winter.
