A Hybrid Coordinate Ocean Model （HYCOM） is used to simulate the sea surface temperature of the Tropical and North Pacific. Based on the different combinations of two air-Sea flux data sets （COADS and ECMWF） and tw...A Hybrid Coordinate Ocean Model （HYCOM） is used to simulate the sea surface temperature of the Tropical and North Pacific. Based on the different combinations of two air-Sea flux data sets （COADS and ECMWF） and two bulk parameter formulas （non-constant and constant）, four numerical experiments are carried out. The following conclusions can be deduced from the numerical results. （1） The numerical results using non-constant bulk parameter formula are much better than those using constant one. In the Pacific area from 40°N to 20°S, the annual average SST obtained from the experiment using non-constant bulk parameter formula is 0.21 ℃ higher than that from the satellite-based SST climatology （the pathfinder data）. However, the difference is 0.63 ℃ for the experiment when the using constant one. （2） HYCOM successfully simulates the monthly variation of climatological SST in tropical and north Pacific basins and monthly spatial variation of Western Pacific Warm Pool. Especially in the Pacific area from 40°N to 20°S, the difference of the seasonal averaged SST between pathfinder data and the result of experiment 2 （using COADS data set and non-constant bulk parameter formula） is only about 0.02 ℃. （3）The simulation results using different Air-Sea flux data are different and the difference is very large in some regions. In the northwest of the model region, the annual average SST obtained from experiment 2 （using COADS data set） is 1℃ higher than that obtained from experiment 4 （using ECMWF data set）. Contrarily, the result of experiment 4 is 1 ℃ larger than that of experiment 2 in the southeast of the model region. The largest difference is about 4 ℃ occurred near the area of 58°N, 140°E and the Bohai sea.展开更多
The Northern Indian Ocean （NIO） sea surface temperature （SST） warming, associated with the E1 Nifio/Southern Oscillations （ENSO） and the Indian Ocean Dipole （IOD） mode, is investigated using the International ...The Northern Indian Ocean （NIO） sea surface temperature （SST） warming, associated with the E1 Nifio/Southern Oscillations （ENSO） and the Indian Ocean Dipole （IOD） mode, is investigated using the International Comprehensive Ocean-Atmosphere Data Set （ICOADS） monthly data for the period 1979-2010. Statistical analy- ses are used to identify respective contribution from ENSO and IOD. The results indicate that the first NIO SST warming in September-November is associated with an IOD event, while the second NIO SST warming in spring-summer following the mature phase of ENSO is associated with an ENSO event. In the year that IOD co-occurred with ENSO, NIO SST warms twice, rising in the ENSO developing year and decay year. Both short- wave radiation and latent heat flux contribute to the NIO SST variation. The change in shortwave radiation is due to the change in cloudiness. A cloud-SST feedback plays an important role in NIO SST warming. The latent heat flux is related to the change in monsoonal wind. In the first NIO warming, the SST anomaly is mainly due to the change in the latent heat flux. In the second NIO warming, both factors are important.展开更多
Interannual variations in the surface and subsurface tropical Indian Ocean were studied using HadlSST and SODA datasets. Wind and heat flux datasets were used to discuss the mechanisms for these variations. Our result...Interannual variations in the surface and subsurface tropical Indian Ocean were studied using HadlSST and SODA datasets. Wind and heat flux datasets were used to discuss the mechanisms for these variations. Our results indicate that the surface and subsurface variations of the tropical Indian Ocean during Indian Ocean Dipole （IOD） events are significantly different. A prominent characteristic of the eastern pole is the SSTA rebound after a cooling process, which does not take place at the subsurface layer. In the western pole, the surface anomalies last longer than the subsurface anomalies. The subsurface anomalies are strongly correlated with ENSO, while the relationship between the surface anomalies and ENSO is much weaker. And the subsurface anomalies of the two poles are negatively correlated while they are positively correlated at the surface layer. The wind and surface heat flux analysis suggests that the thermocline depth variations are mainly determined by wind stress fields, while the heat flux effect is important on SST.展开更多
Siberia experienced intense heat waves in 2020,and this unusual warming may have caused more wildfires and losses of permafrost than normal,both of which can be devastating to ecosystems.Based on observational data,th...Siberia experienced intense heat waves in 2020,and this unusual warming may have caused more wildfires and losses of permafrost than normal,both of which can be devastating to ecosystems.Based on observational data,this paper shows that there was an intense warming trend over Siberia(60°–75°N,70°–130°E)in June during 1979–2020.The linear trend of the June surface air temperature is 0.90℃/10 yr over Siberia,which is much larger than the area with the same latitudes(60°–75°N,0°–360°,trend of 0.46℃/10 yr).The warming over Siberia extends from the surface to about 300 h Pa.Increased geopotential height in the mid-to-upper troposphere plays an important role in shaping the Siberian warming,which favors more shortwave radiation reaching the surface and further heating the overlying atmosphere via upward turbulent heat flux and longwave radiation.The Siberian warming is closely related to Arctic sea-ice decline,especially the sea ice over northern Barents Sea and Kara Sea.Numerical experiments carried out using and atmospheric general circulation model(IAP-AGCM4.1)confirmed the contribution of the Arctic sea-ice decline to the Siberian warming and the related changes in circulations and surface fluxes.展开更多
文摘A Hybrid Coordinate Ocean Model （HYCOM） is used to simulate the sea surface temperature of the Tropical and North Pacific. Based on the different combinations of two air-Sea flux data sets （COADS and ECMWF） and two bulk parameter formulas （non-constant and constant）, four numerical experiments are carried out. The following conclusions can be deduced from the numerical results. （1） The numerical results using non-constant bulk parameter formula are much better than those using constant one. In the Pacific area from 40°N to 20°S, the annual average SST obtained from the experiment using non-constant bulk parameter formula is 0.21 ℃ higher than that from the satellite-based SST climatology （the pathfinder data）. However, the difference is 0.63 ℃ for the experiment when the using constant one. （2） HYCOM successfully simulates the monthly variation of climatological SST in tropical and north Pacific basins and monthly spatial variation of Western Pacific Warm Pool. Especially in the Pacific area from 40°N to 20°S, the difference of the seasonal averaged SST between pathfinder data and the result of experiment 2 （using COADS data set and non-constant bulk parameter formula） is only about 0.02 ℃. （3）The simulation results using different Air-Sea flux data are different and the difference is very large in some regions. In the northwest of the model region, the annual average SST obtained from experiment 2 （using COADS data set） is 1℃ higher than that obtained from experiment 4 （using ECMWF data set）. Contrarily, the result of experiment 4 is 1 ℃ larger than that of experiment 2 in the southeast of the model region. The largest difference is about 4 ℃ occurred near the area of 58°N, 140°E and the Bohai sea.
基金supported by the National Basic Research Program of China(973 Program,2012CB955603 &2010 CB950302)the Knowledge Innovation Program of the Chinese Academy of Sciences(XDA05090404)the National Natural Science Foundation of China(41149908)
文摘The Northern Indian Ocean （NIO） sea surface temperature （SST） warming, associated with the E1 Nifio/Southern Oscillations （ENSO） and the Indian Ocean Dipole （IOD） mode, is investigated using the International Comprehensive Ocean-Atmosphere Data Set （ICOADS） monthly data for the period 1979-2010. Statistical analy- ses are used to identify respective contribution from ENSO and IOD. The results indicate that the first NIO SST warming in September-November is associated with an IOD event, while the second NIO SST warming in spring-summer following the mature phase of ENSO is associated with an ENSO event. In the year that IOD co-occurred with ENSO, NIO SST warms twice, rising in the ENSO developing year and decay year. Both short- wave radiation and latent heat flux contribute to the NIO SST variation. The change in shortwave radiation is due to the change in cloudiness. A cloud-SST feedback plays an important role in NIO SST warming. The latent heat flux is related to the change in monsoonal wind. In the first NIO warming, the SST anomaly is mainly due to the change in the latent heat flux. In the second NIO warming, both factors are important.
基金supported by the National Natural Science Foundation of China(Grant Nos.40876001 and40890152)the Program for New Century Excellent Talents in University(Grant No.NCET-08-0510)the State Key Development Program for National Basic Research Program of China under contract(Grant No.2007CB-411803)
文摘Interannual variations in the surface and subsurface tropical Indian Ocean were studied using HadlSST and SODA datasets. Wind and heat flux datasets were used to discuss the mechanisms for these variations. Our results indicate that the surface and subsurface variations of the tropical Indian Ocean during Indian Ocean Dipole （IOD） events are significantly different. A prominent characteristic of the eastern pole is the SSTA rebound after a cooling process, which does not take place at the subsurface layer. In the western pole, the surface anomalies last longer than the subsurface anomalies. The subsurface anomalies are strongly correlated with ENSO, while the relationship between the surface anomalies and ENSO is much weaker. And the subsurface anomalies of the two poles are negatively correlated while they are positively correlated at the surface layer. The wind and surface heat flux analysis suggests that the thermocline depth variations are mainly determined by wind stress fields, while the heat flux effect is important on SST.
基金supported by the National Key R&D Pro-gram of China[grant number 2017YFE0111800]the National Natural Science Foundation of China[grant numbers 41790472 and 41822502]。
文摘Siberia experienced intense heat waves in 2020,and this unusual warming may have caused more wildfires and losses of permafrost than normal,both of which can be devastating to ecosystems.Based on observational data,this paper shows that there was an intense warming trend over Siberia(60°–75°N,70°–130°E)in June during 1979–2020.The linear trend of the June surface air temperature is 0.90℃/10 yr over Siberia,which is much larger than the area with the same latitudes(60°–75°N,0°–360°,trend of 0.46℃/10 yr).The warming over Siberia extends from the surface to about 300 h Pa.Increased geopotential height in the mid-to-upper troposphere plays an important role in shaping the Siberian warming,which favors more shortwave radiation reaching the surface and further heating the overlying atmosphere via upward turbulent heat flux and longwave radiation.The Siberian warming is closely related to Arctic sea-ice decline,especially the sea ice over northern Barents Sea and Kara Sea.Numerical experiments carried out using and atmospheric general circulation model(IAP-AGCM4.1)confirmed the contribution of the Arctic sea-ice decline to the Siberian warming and the related changes in circulations and surface fluxes.
