Sensitivity of East Asian Climate to the Progressive Uplift and Expansion of the Tibetan Plateau Under the Mid-Pliocene Boundary Conditions

A global atmospheric general circulation model has been used to perform eleven idealized numerical experiments, i.e., TP10, TP10, .., TP100, corresponding to different percentages of the Tibetan Plateau altitude. The aim is to explore the sensitivity of East Asian climate to the uplift and expansion of the Tibetan Plateau under the reconstructed boundary conditions for the mid-Pliocene about 3 Ma ago. When the plateau is progressively uplifted, global annual surface temperature is gradually declined and statistically significant cooling signals emerge only in the Northern Hemisphere, especially over and around the Tibetan Plateau, with larger magnitudes over land than over the oceans. On the contrary, annual surface temperature rises notably over Central Asia and most parts of Africa, as well as over northeasternmost Eurasia in the experiments TP60 to TP100. Meanwhile, the plateau uplift also leads to annual precipitation augmentation over the Tibetan Plateau but a reduction in northern Asia, the Indian Peninsula, much of Central Asia, parts of western Asia and the southern portions of northeastern Europe. Additionally, it is found that an East Asian summer monsoon system similar to that of the present initially exists in the TP60 and is gradually intensified with the continued plateau uplift. At 850 hPa the plateau uplift induces an anomalous cyclonic circulation around the Tibetan Plateau in summertime and two anomalous westerly currents respectively located to the south and north of the Tibetan Plateau in wintertime. In the mid-troposphere, similarto-modern spatial pattern of summertime western North Pacific subtropical high is only exhibited in the experiments TP60 to TP100, and the East Asian trough is steadily deepened in response to the progressive uplift and expansion of the Tibetan Plateau.

The Relationship between Melt Season Sea Ice over the Bering Sea and Summer Precipitation over Mid-Latitude East Asia

Independent datasets consistently indicate a significant correlation between the sea ice variability in the Bering Sea during melt season and the summer rainfall variability in the Lake Baikal area and Northeastern China.In this study,four sea ice datasets(HadISST1,HadISST2.2,ERA-Interim and NOAA/NSIDC)and two global precipitation datasets(CRU V4.01 and GPCP V2.3)are used to investigate co-variations between melt season(March−April−May−June,MAMJ)Bering Sea ice cover(BSIC)and summer(June−July−August,JJA)East Asian precipitation.All datasets demonstrate a significant correlation between the MAMJ BSIC and the JJA rainfall in Lake Baikal−Northeastern China(Baikal−NEC).Based on the reanalysis datasets and the numerical sensitivity experiments performed in this study using Community Atmospheric Model version 5(CAM5),a mechanism to understand how the MAMJ BSIC influences the JJA Baikal−NEC rainfall is suggested.More MAMJ BSIC triggers a wave train and causes a positive sea level pressure(SLP)anomaly over the North Atlantic during MAMJ.The high SLP anomaly,associated with an anti-cyclonic wind stress circulation anomaly,favors the appearance of sea surface temperature(SST)anomalies in a zonal dipole-pattern in the North Atlantic during summer.The dipole SST anomaly drives a zonally orientated wave train,which causes a high anomaly geopotential height at 500 hPa over the Sea of Japan.As a result,the mean East Asian trough moves westward and a low geopotential height anomaly occurs over Baikal−NEC.This prevailing regional low pressure anomaly together with enhanced moisture transport from the western North Pacific and convergence over Baikal−NEC,positively influences the increased rainfall in summer.

Eurasian Winter Cooling: Intercomparison of Reanalyses and CMIP5 Data Sets

A cooling trend in wintertime surface air temperature over continental Eurasia has been identified in reanalysis and the Coupled Model Inter-comparison Project phase 5(CMIP5)‘historical’simulations over the period 1989–2009.Here the authors have shown that this cooling trend is related to changes in Arctic sea-ice around the Barents-Kara seas.This study illustrates a consistent spatial and temporal structure of the wintertime temperature variability centered over Asia using state-of-the-art reanalyses and global climate model datasets.Our findings indicate that there is a physical basis for seasonal predictions of near-surface temperatures over continental Asia based on changes to the ice-cover in the Barents-Kara seas.

Will the summer sea ice in the Arctic reach a tipping point?

The Arctic sea-ice cover has decreased in extent,area,and thickness over the last six decades.Most global climate models project that the summer sea-ice extent(SIE)will decline to less than 1 million(mill.)km^(2) in this century,ranging from 2030 to the end of the century,indicating large uncertainty.However,some models,using the same emission scenarios as required by the Paris Agreement to keep the global temperature below 2°C,indicate that the SIE could be about 2 mill.km^(2) in 2100 but with a large uncertainty of±1.5 mill.km^(2).Here,the authors take another approach by exploring the direct relationship between the SIE and atmospheric CO_(2) concentration for the summer-fall months.The authors correlate the SIE and In(CO_(2)/CO_(2)r)during the period 1979-2022,where CO_(2)r is the reference value in 1979.Using these transient regression equations with an R2 between 0.78 and 0.87,the authors calculate the value that the CO_(2) concentration needs to reach for zero SIE.The results are that,for July,the CO_(2) concentration needs to reach 691±16.5 ppm,for August 604±16.5 ppm,for September 563±17.5 ppm,and for October 620±21 ppm.These values of CO_(2)for an ice-free Arctic are much higher than the targets of the Paris Agreement,which are 450 ppm in 2060 and 425 ppm in 2100,under the IPCC SSP1-2.6 scenario.If these targets can be reached or even almost reached,the "no tipping point"hypothesis for the summer SIE may be valid.

Population increase impacts the climate,using the sensitive Arctic as an example

The global population during the last 100 years has increased from 2 to 7.7 billion,causing an increase in greenhouse gases in the atmosphere.In order to see how population increase is directly related to physical variables of the climate,this Perspective article places observations and scenarios of climate change into context and puts forth a statistical modeling study on how the sensitive Arctic climate responds to the increasing population.The relationships between population,Arctic sea-ice extent(SIE),and surface air temperature(SAT)are very strong,with the increasing population explaining 96%of the decreasing SIE and about 80%of the increasing SAT in the Arctic.Our projection for the SIE using the population as a“proxy predictor”for a projected population of 10 billion people on the Earth in 2100,yields a SIE of 9.30 and 8.21 million km 2 for a linear and squared relationship,respectively,indicating no“tipping point”for the annual ice extent in this century.This adds another dimension to climate understanding for the public at large using population as a proxy variable,instead of the more abstract CO_(2)parameter.This also indicates that it is important to attempt to limit the ongoing increase in population,which is the main cause of the greenhouse gas emissions,in addition to reducing per capita emissions by an exponential increase in implementing renewable energy,a formidable challenge in this century.

Contrasting Vertical Structure of Recent Arctic Warming in Different Data Sets

Arctic region is experiencing strong warming and related changes in the state of sea ice, permafrost, tundra, marine environment and terrestrial ecosystems. These changes are found in any climatological data set comprising the Arctic region. This study compares the temperature trends in several surface, satellite and reanalysis data sets. We demonstrate large differences in the 1979-2002 temperature trends. Data sets disagree on the magnitude of the trends as well as on their seasonal, zonal and vertical pattern. It was found that the surface temperature trends are stronger than the trends in the tropospheric temperature for each latitude band north of 50?N for each month except for the months during the ice-melting season. These results emphasize that the conclusions of climate studies drawn on the basis of a single data set analysis should be treated with caution as they may be affected by the artificial biases in data.