Structure and large‐scale organization of extreme cold wave events over the Chinese mainland during the boreal cold season

Author(s):  
L. Zhang ◽  
Z. Xie ◽  
Y. Deng ◽  
W. Huang
2019 ◽  
Vol 32 (4) ◽  
pp. 1203-1216 ◽  
Author(s):  
Shuangmei Ma ◽  
Congwen Zhu

It is argued that anthropogenic global warming may decrease the global occurrence of cold waves. However, a historical record-extreme cold wave, popularly called the “boss level” cold wave, attacked East Asia in January 2016, which gives rise to the discussion of why this boss-level cold wave occurred during the winter with the warmest recorded global mean surface air temperature (SAT). To explore the impacts of human-induced global warming and natural internal atmosphere variability, we investigated the cold-wave-related circulation regime (i.e., the large-scale atmospheric circulation pattern) and compared the observation with the large ensemble simulations of the MIROC5 model. Our results showed that this East Asian extreme cold-wave-related atmospheric circulation regime mainly exhibited an extremely strong anomaly of the Ural blocking high (UBH) and a record-breaking anomaly of the surface Siberian high (SH), and it largely originated from the natural internal atmosphere variability. However, because of the dynamic effect of Arctic amplification, anthropogenic global warming may increase the likelihood of extreme cold waves through shifting the responsible natural atmospheric circulation regime toward a stronger amplitude. The probability of occurrence of extreme anomalies of UBH, SH, and the East Asia area mean SAT have been increased by 58%, 57%, and 32%, respectively, as a consequence of anthropogenic global warming. Therefore, extreme cold waves in East Asia, such as the one in January 2016, may be an enhanced response to the larger internal atmospheric variability modulated by human-induced global warming.


2021 ◽  
Vol 38 (10) ◽  
pp. 1791-1802
Author(s):  
Peiyan Chen ◽  
Hui Yu ◽  
Kevin K. W. Cheung ◽  
Jiajie Xin ◽  
Yi Lu

AbstractA dataset entitled “A potential risk index dataset for landfalling tropical cyclones over the Chinese mainland” (PRITC dataset V1.0) is described in this paper, as are some basic statistical analyses. Estimating the severity of the impacts of tropical cyclones (TCs) that make landfall on the Chinese mainland based on observations from 1401 meteorological stations was proposed in a previous study, including an index combining TC-induced precipitation and wind (IPWT) and further information, such as the corresponding category level (CAT_IPWT), an index of TC-induced wind (IWT), and an index of TC-induced precipitation (IPT). The current version of the dataset includes TCs that made landfall from 1949–2018; the dataset will be extended each year. Long-term trend analyses demonstrate that the severity of the TC impacts on the Chinese mainland have increased, as embodied by the annual mean IPWT values, and increases in TCinduced precipitation are the main contributor to this increase. TC Winnie (1997) and TC Bilis (2006) were the two TCs with the highest IPWT and IPT values, respectively. The PRITC V1.0 dataset was developed based on the China Meteorological Administration’s tropical cyclone database and can serve as a bridge between TC hazards and their social and economic impacts.


2021 ◽  
Vol 13 (11) ◽  
pp. 2067
Author(s):  
Haoyu Liu ◽  
Xianwen He ◽  
Yanbing Bai ◽  
Xing Liu ◽  
Yilin Wu ◽  
...  

The official method of collecting county-level GDP values in the Chinese Mainland relies mainly on administrative reporting data and suffers from high costs of time, money, and human labor. To date, a series of studies have been conducted to generate fine-grained maps of socioeconomic indicators from the easily accessed remote sensing data and achieved satisfactory results. This paper proposes a transfer learning framework that regards nightlight intensities as a proxy of economic activity degrees to estimate county-level GDP around the Chinese Mainland. In the framework, paired daytime satellite images and nightlight intensity levels were applied to train a VGG-16 architecture, and the output features at a specific layer, after dimensional reduction and statistics calculation, were fed into a simple regressor to estimate county-level GDP. We trained the model with data of 2017 and utilized it to predict county-level GDP of 2018, achieving an R-squared of 0.71. Furthermore, the results of gradient visualization confirmed the validity of the proposed framework qualitatively. To the best of our knowledge, this is the first time that county-level GDP values around the Chinese Mainland have been estimated from both daytime and nighttime remote sensing data relying on attention-augmented CNN. We believe that our work will shed light on both the evolution of fine-grained socioeconomic surveys and the application of remote sensing data in economic research.


2013 ◽  
Vol 26 (21) ◽  
pp. 8378-8391 ◽  
Author(s):  
Yi Zhang ◽  
Rucong Yu ◽  
Jian Li ◽  
Weihua Yuan ◽  
Minghua Zhang

Abstract Given the large discrepancies that exist in climate models for shortwave cloud forcing over eastern China (EC), the dynamic (vertical motion and horizontal circulation) and thermodynamic (stability) relations of stratus clouds and the associated cloud radiative forcing in the cold season are examined. Unlike the stratus clouds over the southeastern Pacific Ocean (as a representative of marine boundary stratus), where thermodynamic forcing plays a primary role, the stratus clouds over EC are affected by both dynamic and thermodynamic factors. The Tibetan Plateau (TP)-forced low-level large-scale lifting and high stability over EC favor the accumulation of abundant saturated moist air, which contributes to the formation of stratus clouds. The TP slows down the westerly overflow through a frictional effect, resulting in midlevel divergence, and forces the low-level surrounding flows, resulting in convergence. Both midlevel divergence and low-level convergence sustain a rising motion and vertical water vapor transport over EC. The surface cold air is advected from the Siberian high by the surrounding northerly flow, causing low-level cooling. The cooling effect is enhanced by the blocking of the YunGui Plateau. The southwesterly wind carrying warm, moist air from the east Bay of Bengal is uplifted by the HengDuan Mountains via topographical forcing; the midtropospheric westerly flow further advects the warm air downstream of the TP, moistening and warming the middle troposphere on the lee side of the TP. The low-level cooling and midlevel warming together increase the stability. The favorable dynamic and thermodynamic large-scale environment allows for the formation of stratus clouds over EC during the cold season.


2006 ◽  
Vol 17 (1) ◽  
pp. 34-45
Author(s):  
Haili Yu ◽  
Houhun Li

Fourteen species of Phaecasiophora Grote from the Chinese Mainland are treated, including five new species (P. supparallelica sp. n., P. levis sp. n., P. curvicosta sp. n., P. lushina sp. n., and P. similithaiensis sp. n.) and three new species records for China. Phaecasiophora leechi is transferred from subgenus Megasyca to subgenus Phaecasiophora, and a new synonym of it, viz. P. obligata Kawabe, is proposed. Photographs of the adults, genitalia of the new species, and the species with new synonyms are provided. A key to the species from the Chinese Mainland based on genitalia is given.


Sign in / Sign up

Export Citation Format

Share Document