scholarly journals Synergistic Modulations of Large-Scale Synoptic Patterns and Local-Scale Urbanization Effects on Summer Rainfall in South China

2021 ◽  
Vol 3 ◽  
Author(s):  
Minxuan Zhang ◽  
Wanju Li ◽  
Xueyan Bi ◽  
Lian Zong ◽  
Yanhao Zhang ◽  
...  
Keyword(s):  
South China ◽  
Rural Areas ◽  
Large Scale ◽  
Summer Precipitation ◽  
Guangdong Province ◽  
Northwestern Pacific ◽  
Observation Data ◽  
Rapid Urbanization ◽  
Weather Types ◽  
Frequency Changes

Using the ERA5 (the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts) data and the T-PCA (Principal Component Analysis in T-mode) objective classification method to classify the 850-hPa geopotential height, we summarize four conceptual models of large-scale synoptic weather types over East Asia. By combining this with the daily precipitation observation data of 36 meteorological stations in Guangdong, South China, during summer (June to August) of 2014–2018, we found that summer precipitation in Guangdong Province is closely related to the position of the northwestern Pacific subtropical high and the strong upward motion of the warm airflow over the Pearl River Delta. It is further revealed the regulation effect of different weather patterns on summer precipitation in Guangdong Province and their urban–rural differences. More specifically, both urban and rural areas have a decreasing proportion of light rainfall and an increasing proportion of heavy and torrential rainfall, which are mainly regulated by the trend of frequency changes of four different weather types: Type 1 (47.39%) and Type 2 (32.39%) days are decreasing year by year, modulating the trend of light rainfall, while Type 3 (13.26%) and Type 4 (6.96%) days are steadily increasing, dominating the trend of heavy rainfall. In addition, it was further found that the frequency of light rainfall is decreasing more significantly in cities compared to that in rural areas, while the proportion of heavy and stormy rainfall is increasing more significantly, which is closely related to the effects of rapid urbanization.

Imperial Discourse, Regional Elite, and Local Landscape on the South China Frontier, 1577-1722

2008 ◽  
Vol 12 (2) ◽  
pp. 99-136 ◽  
Author(s):  
Steven Miles
Keyword(s):  
Natural Resources ◽  
South China ◽  
Large Scale ◽  
Civil Service ◽  
Guangdong Province ◽  
Mountainous Area ◽  
The South ◽  
Regional Migration ◽  
Civil Service Examinations ◽  
Military Campaign

AbstractThis article describes the consolidation of imperial control and the increase of regional migration on China's southern frontier from 1577 to 1722. After a large-scale military campaign, the Ming state created two neighboring counties in a mountainous area of Guangdong province that had previously been dominated by an unregistered, unsettled, and unruly segment of the population. The Chinese literati elite residing in the more settled and commercially prosperous delta downstream from the two new counties wrote numerous essays celebrating the spread of imperial rule across this landscape. These essays also reveal some ways in which the socioeconomic interests of the delta elite were served by the state's consolidation of the frontier. The two new counties offered opportunities for various kinds of delta residents: merchants organizing the extraction of natural resources, settlers claiming newly emptied lands, and aspiring literati taking advantage of new quotas and less competition in the civil service examinations.

scholarly journals Leveraging machine learning for quantitative precipitation estimation from Fengyun-4 geostationary observations and ground meteorological measurements

2021 ◽  
Author(s):  
Xinyan Li ◽  
Yuanjian Yang ◽  
Jiaqin Mi ◽  
Xueyan Bi ◽  
You Zhao ◽  
...  
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Large Scale ◽  
Predictive Ability ◽  
Summer Precipitation ◽  
Reanalysis Data ◽  
Probability Of Detection ◽  
Model Framework ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation

Abstract. Deriving large-scale and high-quality precipitation products from satellite remote sensing spectral data is always challenging in quantitative precipitation estimation (QPE), and limited studies have been conducted even using the China’s latest Fengyun-4A (FY-4A) geostationary satellite. Taking three rainstorm events over South China as examples, a Random Forest (RF) model framework for FY-4A QPE during daytime/nighttime is established by using FY-4A multi-band spectral information, cloud parameters, high-density precipitation observations, and physical quantities from reanalysis data. During daytime (nighttime), the probability of detection of the RF model for precipitation is 0.99 (0.99), while the correlation coefficient and root-mean-square error between the retrieved and observed precipitation are 0.77 (0.82) and 1.84 (2.32) mm/h, respectively, indicating that the RF model of FY-4A QPE has high precipitation retrieval accuracy. In particular, the RF model exhibits good spatiotemporal predictive ability for precipitation intensities within the range of 0.5–10 mm/h. For the retrieved accumulated precipitation, the precipitation intensity exhibits a greater impact on the predictive ability of the QPE algorithm than the precipitation duration. Due to the higher density of automatic stations in urban areas, the accuracy of FY-4A QPE over such areas is higher compared with rural areas. Both the accumulated precipitation and the distribution density of automatic stations are more important factors for the predictive ability of the RF model of FY-4A QPE. In general, our proposed FY-4A QPE algorithm has advantages for near-real-time monitoring of summer precipitation over East Asia.

scholarly journals Leveraging machine learning for quantitative precipitation estimation from Fengyun-4 geostationary observations and ground meteorological measurements

2021 ◽  
Vol 14 (11) ◽  
pp. 7007-7023
Author(s):  
Xinyan Li ◽  
Yuanjian Yang ◽  
Jiaqin Mi ◽  
Xueyan Bi ◽  
You Zhao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Rural Areas ◽  
Land Surface ◽  
Large Scale ◽  
Quantitative Estimation ◽  
Summer Precipitation ◽  
Bias Score ◽  
Surface Precipitation ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation

Abstract. Deriving large-scale and high-quality precipitation products from satellite remote-sensing spectral data is always challenging in quantitative precipitation estimation (QPE), and limited studies have been conducted even using China's latest Fengyun-4A (FY-4A) geostationary satellite. Taking three rainstorm events over South China as examples, a machine-learning-based regression model was established using the random forest (RF) method to derive QPE from FY-4A observations, in conjunction with cloud parameters and physical quantities. The cross-validation results indicate that both daytime (DQPE) and nighttime (NQPE) RF algorithms performed well in estimating QPE, with the bias score, correlation coefficient and root-mean-square error of DQPE (NQPE) of 2.17 (2.42), 0.79 (0.83) and 1.77 mm h−1 (2.31 mm h−1), respectively. Overall, the algorithm has a high accuracy in estimating precipitation under the heavy-rain level or below. Nevertheless, the positive bias still implies an overestimation of precipitation by the QPE algorithm, in addition to certain misjudgements from non-precipitation pixels to precipitation events. Also, the QPE algorithm tends to underestimate the precipitation at the rainstorm or even above levels. Compared to single-sensor algorithms, the developed QPE algorithm can better capture the spatial distribution of land-surface precipitation, especially the centre of strong precipitation. Marginal difference between the data accuracy over sites in urban and rural areas indicate that the model performs well over space and has no evident dependence on landscape. In general, our proposed FY-4A QPE algorithm has advantages for quantitative estimation of summer precipitation over East Asia.

scholarly journals Seasonal variability of subsurface high salinity water in the northern South China Sea and its relationship with the northwestern Pacific currents

2014 ◽  
Vol 11 (5) ◽  
pp. 2423-2446
Author(s):  
A. Wang ◽  
Y. Du ◽  
W. Zhuang ◽  
Y. Qi
Keyword(s):  
South China Sea ◽  
South China ◽  
Seasonal Variability ◽  
Large Scale ◽  
High Salinity ◽  
Luzon Strait ◽  
Northwestern Pacific ◽  
High Salinity Water ◽  
The North ◽  
Salinity Water

Abstract. The North Pacific Tropical Water (NPTW), characterized by the subsurface high salinity (> 34.68 PSU), is observed in the South China Sea (SCS) and often used as an indicator of the water intrusion from the northwestern Pacific into the SCS. Based on the assimilation product from a global high-resolution Hybrid Coordinate Ocean Model (HYCOM), this study investigates the seasonal variability of subsurface high salinity water (SHSW) in the northern SCS and the influence from the northwestern Pacific. Results show that there exists obvious seasonal variability in the SHSW at about 100–200 m depth. It extends as far west as 111° E in the northern SCS, reaching its volume maximum (minimum) in January (May). Further analysis shows that the seasonal change of the high salinity water is strongly affected by the seasonal variability of large-scale circulations in the low-latitude northwestern Pacific. The changes of high salinity water volume are highly correlated with the shift of the North Equatorial Current (NEC) bifurcation latitude (NECBL), which reaches the northernmost in December and the southernmost in May. Due to the large-scale wind changes in the Pacific, the Luzon Strait transport weakens (strengthens) when the NECBL shifts to the south (north) during summer (winter), which results in the reduced (enhanced) SHSW intrusion from the northwestern Pacific into the northern SCS. The velocity and salinity distribution in the Luzon Strait show that the intrusion of the SHSW mainly occurs at around 20–21.3° N.

scholarly journals Differentiated Effects of Urbanization on Precipitation in South China

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1386
Author(s):  
Lingli Fan ◽  
Guangya Zhang ◽  
Jianjun Xu
Keyword(s):  
Water Vapor ◽  
South China ◽  
Rural Areas ◽  
Convective Available Potential Energy ◽  
Precipitation Trend ◽  
Rapid Urbanization ◽  
Sea Breezes ◽  
Moisture Recycling ◽  
Urban Cluster ◽  
Cluster A

In this paper, precipitation data from the Tropical Rainfall Measuring Mission (TRMM), together with atmospheric reanalysis data, are employed to identify warm-season precipitation (1998–2014) changes and their association with rapid urbanization in south China. Three urban clusters (Chenyu, Yangtze Delta, and Fujian Guangdong coast) are focused. The results reveal that, for the inland Chengyu urban cluster, a lack of precipitation trend is likely due to insignificant trends in convective available potential energy (CAPE) and total column water vapor (TCWV). They are likely resulted from a reduced local moisture recycling in urban areas, balanced by an increased evapotranspiration of rural areas, together with a stable advection of water vapor input. For the Yangtze River Delta urban cluster, a negative trend in precipitation is associated with a slightly decreased CAPE and an increased TCWV, but is very likely related to urbanization induced an increased planetary boundary layer (PBL) and reduced land surface evaporation. For the Fujian Guangdong coast urban cluster, a marked positive precipitation trend is well explained by positive trends in CAPE and TCWV. The increased precipitation likely benefits from enhanced moisture recycling due to improved vegetation cover in rural areas, and enhanced advection moisture inputs due to urbanization along the coast. These results suggest urbanization effects on precipitation vary with regional conditions. In the coastal area, urbanization enhances sea breezes, which may benefit precipitation if sea breezes go along with the prevailing moisture. In inland area, urbanization likely leads to a warmer-dryer climate if large-scale land cover keeps stationary.

scholarly journals Could the two anticyclonic eddies during winter 2003/2004 be reproduced and predicted in the northern South China Sea?

Ocean Science ◽  
2019 ◽  
Vol 15 (1) ◽  
pp. 97-111 ◽  
Author(s):  
Dazhi Xu ◽  
Wei Zhuang ◽  
Youfang Yan
Keyword(s):  
South China Sea ◽  
South China ◽  
Large Scale ◽  
Numerical Models ◽  
Northern South China Sea ◽  
Mesoscale Eddies ◽  
Nonlinearity Parameter ◽  
Observation Data ◽  
China Sea ◽  
Anticyclonic Eddies

Abstract. Great progress has been made in understanding the mesoscale eddies and their role on the large-scale structure and circulation of the oceans. However, many questions still remain to be resolved, especially with regard to the reproductivity and predictability of mesoscale eddies. In this study, the reproductivity and predictability of mesoscale eddies in the northern South China Sea (NSCS), a region with strong eddy activity, are investigated with a focus on two typical anticyclonic eddies (AE1 and AE2) based on a HYCOM–EnOI assimilated system. The comparisons of assimilated results and observations suggest that generation, evolution, and propagation paths of AE1 and AE2 can be well reproduced and forecasted when the observed amplitude is >8 cm (or the advective nonlinearity parameter U∕c is >2), although their forcing mechanisms are quite different. However, when their amplitudes are less than 8 cm, the generation and decay of these two mesoscale eddies cannot be well reproduced and predicted by the system. This result suggests, in addition to dynamical mechanisms, that the spatial resolution of assimilation observation data and numerical models must be taken into account in reproducing and predicting mesoscale eddies in the NSCS.

Training Aides to Screen Children for Speech and Language Problems

1976 ◽  
Vol 7 (4) ◽  
pp. 236-241 ◽  
Author(s):  
Marisue Pickering ◽  
William R. Dopheide
Keyword(s):  
Rural Areas ◽  
Large Scale ◽  
School Personnel ◽  
School Age Children ◽  
Speech And Language ◽  
Elementary School Age ◽  
Evaluation Procedures ◽  
Language Problems ◽  
Competency Based ◽  
Large Scale Screening

This report deals with an effort to begin the process of effectively identifying children in rural areas with speech and language problems using existing school personnel. A two-day competency-based workshop for the purpose of training aides to conduct a large-scale screening of speech and language problems in elementary-school-age children is described. Training strategies, implementation, and evaluation procedures are discussed.

Why Has There Been No People’s Power Rebellion in North Korea?

2018 ◽  
pp. 1-34
Author(s):  
Andrew Jackson
Keyword(s):  
Rural Areas ◽  
North Korea ◽  
Large Scale ◽  
Political Elite ◽  
Information Control ◽  
Al Jazeera ◽  
The North ◽  
New Information ◽  
Effective System ◽  
The Right

One scenario put forward by researchers, political commentators and journalists for the collapse of North Korea has been a People’s Power (or popular) rebellion. This paper analyses why no popular rebellion has occurred in the DPRK under Kim Jong Un. It challenges the assumption that popular rebellion would happen because of widespread anger caused by a greater awareness of superior economic conditions outside the DPRK. Using Jack Goldstone’s theoretical expla-nations for the outbreak of popular rebellion, and comparisons with the 1989 Romanian and 2010–11 Tunisian transitions, this paper argues that marketi-zation has led to a loosening of state ideological control and to an influx of infor-mation about conditions in the outside world. However, unlike the Tunisian transitions—in which a new information context shaped by social media, the Al-Jazeera network and an experience of protest helped create a sense of pan-Arab solidarity amongst Tunisians resisting their government—there has been no similar ideology unifying North Koreans against their regime. There is evidence of discontent in market unrest in the DPRK, although protests between 2011 and the present have mostly been in defense of the right of people to support themselves through private trade. North Koreans believe this right has been guaranteed, or at least tacitly condoned, by the Kim Jong Un government. There has not been any large-scale explosion of popular anger because the state has not attempted to crush market activities outright under Kim Jong Un. There are other reasons why no popular rebellion has occurred in the North. Unlike Tunisia, the DPRK lacks a dissident political elite capable of leading an opposition movement, and unlike Romania, the DPRK authorities have shown some flexibility in their anti-dissent strategies, taking a more tolerant approach to protests against economic issues. Reduced levels of violence during periods of unrest and an effective system of information control may have helped restrict the expansion of unrest beyond rural areas.

scholarly journals Large-Scale Road Network Congestion Pattern Analysis and Prediction Using Deep Convolutional Autoencoder

2021 ◽  
Vol 13 (9) ◽  
pp. 5108
Author(s):  
Navin Ranjan ◽  
Sovit Bhandari ◽  
Pervez Khan ◽  
Youn-Sik Hong ◽  
Hoon Kim
Keyword(s):  
Traffic Congestion ◽  
Network Architecture ◽  
Road Network ◽  
Large Scale ◽  
Pattern Analysis ◽  
Image Data ◽  
Urban Life ◽  
Prediction Algorithm ◽  
Rapid Urbanization ◽  
Convolutional Autoencoder

The transportation system, especially the road network, is the backbone of any modern economy. However, with rapid urbanization, the congestion level has surged drastically, causing a direct effect on the quality of urban life, the environment, and the economy. In this paper, we propose (i) an inexpensive and efficient Traffic Congestion Pattern Analysis algorithm based on Image Processing, which identifies the group of roads in a network that suffers from reoccurring congestion; (ii) deep neural network architecture, formed from Convolutional Autoencoder, which learns both spatial and temporal relationships from the sequence of image data to predict the city-wide grid congestion index. Our experiment shows that both algorithms are efficient because the pattern analysis is based on the basic operations of arithmetic, whereas the prediction algorithm outperforms two other deep neural networks (Convolutional Recurrent Autoencoder and ConvLSTM) in terms of large-scale traffic network prediction performance. A case study was conducted on the dataset from Seoul city.

scholarly journals Optimal Design of Novel Blade Profile for Savonius Wind Turbines

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3484
Author(s):  
Tai-Lin Chang ◽  
Shun-Feng Tsai ◽  
Chun-Lung Chen
Keyword(s):  
Wind Energy ◽  
Drag Force ◽  
Wind Turbines ◽  
Rural Areas ◽  
Large Scale ◽  
Design Method ◽  
Angular Position ◽  
Vertical Axis ◽  
Blade Profile ◽  
Main Concept

Since the affirming of global warming, most wind energy projects have focused on the large-scale Horizontal Axis Wind Turbines (HAWTs). In recent years, the fast-growing wind energy sector and the demand for smarter grids have led to the use of Vertical Axis Wind Turbines (VAWTs) for decentralized energy generation systems, both in urban and remote rural areas. The goals of this study are to improve the Savonius-type VAWT’s efficiency and oscillation. The main concept is to redesign a Novel Blade profile using the Taguchi Robust Design Method and the ANSYS-Fluent simulation package. The convex contour of the blade faces against the wind, creating sufficient lift force and minimizing drag force; the concave contour faces up to the wind, improving or maintaining the drag force. The result is that the Novel Blade improves blade performance by 65% over the Savonius type at the best angular position. In addition, it decreases the oscillation and noise accordingly. This study achieved its two goals.

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