Dominant patterns of winter surface air temperature over Central Asia and their connection with atmospheric circulation

The dominant patterns of the winter(December-February)surface air temperature anomalies(SATAs)over Central Asia(CA)are investigated in this study.The first two leading modes revealed by empirical orthogonal function(EOF)analysis represent the patterns by explaining 74%of the total variance.The positive phase of EOF1 is characterized by a monopole pattern,corresponding to cold SATAs over CA,while the positive phase of EOF2 shows a meridional dipole pattern with warm and cold SATAs over northern and southern CA.EOF1 is mainly modulated by the negative phase of the Arctic Oscillation(AO)in the troposphere,and the negative AO phase may be caused by the downward propagation of the precursory anomalies of the stratospheric polar vortex.EOF2 is mainly influenced by the Ural blocking pattern and the winter North Atlantic Oscillation(NAO).The SATAs associated with EOF2 can be attributed to a dipole-like pattern of geopotential height anomalies over CA.The dipole-like pattern is mainly caused by the Ural blocking pattern,and the NAO can also contribute to the northern part of the dipole.

Global Annual Mean Surface Air Temperature Anomalies and Their Link with Indian Summer Monsoon Failures

Analysis of the global mean annual temperature anomalies based on land and marine data for the last 88 years (1901-1988) of this century has been carried out with a view to find any relationship with failures in Indian summer monsoon rainfall. On the climatological scale (i.e. 30 years) it has been noticed that there is an abnormal increase in the frequency of drought years during epochs of global warming and cooling, while it is considerably less when global temperatures are near normal. Results are unchanged even when the data are filtered out for ENSO (El-Nino Southern Oscillation) effect.It has also been noticed that during warm and cold epochs in global temperatures the amount of summer monsoon rainfall decreases as compared to the rainfall during a normal temperature epoch.

Multidecadal Trends in Large-Scale Annual Mean SATa Based on CMIP5 Historical Simulations and Future Projections

Based on observations and Coupled Model lntercomparison Project Phase 5 （CMIP5） results, multidecadal variations and trends in annual mean surface air temperature anomalies （SATa） at global, hemispheric, and hemispheric land and ocean scales in the past and under the future scenarios of two representative concentration pathways （RCPs） are analyzed. Fifteen models are selected based on their performances in capturing the temporal variability, long-term trend, multidecadal variations, and trends in global annual mean SATa. Observational data analysis shows that the multidecadal variations in annual mean SATa of the land and ocean in the northern hemisphere （NH） and of the ocean in the southern hemisphere （SH） are similar to those of the global mean, showing an increase during the 1900-1944 and 1971-2000 periods, and flattening or even cooling during the 1945-1970 and 2001-2013 periods. These observed characteristics are basically reproduced by the models. However, SATa over SH land show an increase during the 1945-1970 period, which differs from the other hemispheric scales, and this feature is not captured well by the models. For the recent hiatus period （2001-2013）, the projected trends of BCC-CSM1-1-m, CMCC-CM, GFDL-ESM2M, and NorESM1-ME at the global and hemispheric scales are closest to the observations based on RCP4.5 and RCP8.5 scenarios, suggesting that these four models have better projection capability in SATa. Because these four models are better at simulating and projecting the multidecadal trends of SATa, they are selected to analyze future SATa variations at the global and hemispheric scales during the 2006-2099 period. The selected multi-model ensemble （MME） projected trends in annual mean SATa for the globe, NH, and SH under RCP4.5 （RCP8.5） are 0.17 （0.29） ℃, 0.22 （0.36） ℃, and 0.11 （0.23） ℃-decade-1 in the 21st century, respectively. These values are significantly lower than the projections of CMIP5 MME without model selection.

Causes of seasonal sea level anomalies in the coastal region of the East China Sea

Based on the analysis of sea level, air temperature, sea surface temperature（SST）, air pressure and wind data during 1980-2013, the causes of seasonal sea level anomalies in the coastal region of the East China Sea（ECS） are investigated. The research results show：（1） sea level along the coastal region of the ECS takes on strong seasonal variation. The annual range is 30-45 cm, larger in the north than in the south. From north to south, the phase of sea level changes from 140° to 231°, with a difference of nearly 3 months.（2） Monthly mean sea level（MSL）anomalies often occur from August to next February along the coast region of the ECS. The number of sea level anomalies is at most from January to February and from August to October, showing a growing trend in recent years.（3） Anomalous wind field is an important factor to affect the sea level variation in the coastal region of the ECS. Monthly MSL anomaly is closely related to wind field anomaly and air pressure field anomaly. Wind-driven current is essentially consistent with sea surface height. In August 2012, the sea surface heights at the coastal stations driven by wind field have contributed 50%-80% of MSL anomalies.（4） The annual variations for sea level,SST and air temperature along the coastal region of the ECS are mainly caused by solar radiation with a period of12 months. But the correlation coefficients of sea level anomalies with SST anomalies and air temperature anomalies are all less than 0.1.（5） Seasonal sea level variations contain the long-term trends and all kinds of periodic changes. Sea level oscillations vary in different seasons in the coastal region of the ECS. In winter and spring, the oscillation of 4-7 a related to El Ni？o is stronger and its amplitude exceeds 2 cm. In summer and autumn, the oscillations of 2-3 a and quasi 9 a are most significant, and their amplitudes also exceed 2 cm. The height of sea level is lifted up when the different oscillations superposed. On the other hand, the height of sea level is fallen down.