Variables In China Research Articles

Weak Cooling of Cold Extremes Versus Continued Warming of Hot Extremes in China During the Recent Global Surface Warming Hiatus

AbstractUsing daily maximum temperature (Tmax), minimum temperature (Tmin), and mean temperature data of 437 weather stations in China, we compared variations of the mean with extreme ends of probability distribution of temperatures in China from 1960 to 2015. Our analysis confirmed that annual mean Tmax and Tmin experienced warming hiatus in China after 1998. The warming hiatus is also reflected by the weak cooling of cold extremes across China, but hot extremes continue the significant warming trend nationally and in climate regions of East China, Southwest China, and the Tibetan Plateau. During 1999–2015, the hot day frequency (Tx90, based on base period 1961–1990) and averaged Tmax above the 90th percentile of each year (Txp90) increased significantly by 3.70 d/decade and 0.20°C/decade nationally. But there were significant cooling trends of cold extremes in East China and Southeast China from 1999 to 2015. During the warming hiatus period, the obvious decline in warm season precipitation contributed to the ongoing warming of hot extremes in East China and Southwest China. Both the decrease of warming season solar irradiance and increase of warm season precipitation facilitated the weak cooling trends of hot extremes in Northeast China and North China Plain. Although mean temperature experienced warming hiatus after 1998, the continued warming of hot extremes and reverse from warming to weak cooling of cold extremes imply an increase of temperature variability in China simultaneously.

Party and state policy documents and China’s economy: some macro-level empirical evidence

This paper compares a unique dataset tracking the content of all Central Committee and State Council documents with economic variables in China in the period 2003–2015. After motivating the dataset, two time-series measuring the relative importance of economic issues within the Party and the State are constructed. These two time-series are then compared with measures of China’s real economy using a Granger test. The results suggest that past measures of China’s economy can better help predict the State Council’s future prioritisation of economic issues, but not vice versa. A similar relation is not found for the Central Committee’s prioritisation of economic issues. This result is consistent with the view that it is the State that takes a more active role in managing the Chinese economy.

Responses of runoff to historical and future climate variability over China

Abstract. China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal–spatial patterns of water resources. Based on the long-term (1960–2008) water budget data and climate projections from 28 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.1 to 3.2) and potential evaporation (PET) elasticity (from −2.2 to −0.1) across China. The P elasticity is larger in north-eastern and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties' elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960–2008, the climate contribution to R ranges from −2.4 to 3.6 % yr−1 across China, with the negative contribution in north-eastern China and the positive contribution in western China and some parts of the south-west. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071–2100, the mean annual P is projected to increase in most parts of China, especially the western regions, while the mean annual PET is projected to increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China are projected to become wetter and drier in the period 2071–2100, respectively (relative to the baseline 1971–2000).

Simulating the potential distribution of Elaeagnus angustifolia L. based on climatic constraints in China

Elaeagnus angustifolia L. has considerable ecological value and plays an important role in windbreak and sand fixation, soil and water conservation, vegetation restoration and afforestation in Asia. Understanding the potential distribution and the limiting climatic factors is the first step for sustainable use of this species at regional scale. Here, we simulated the potential distribution of E. angustifolia and evaluated its limiting climatic factors using a maximum entropy model (MaxEnt) and geographical information system (GIS) in China, based on 190 occurrence grid cells and 13 climatic variables in China. The results show that: (1) annual range of temperature (ART), annual mean temperature (AMT), humidity index (HI), and coldness index (CI) are the dominant climatic factors limiting its potential distribution range; (2) low temperature is an important climatic factor that limits both southern and northern distribution boundaries, and high rainfall is another climatically limiting factor for the southern boundary, and (3) the potential distribution areas are mainly located in the warm temperate and middle temperate zone with cold and dry winters, and in the arid and semi-arid regions of China between 30°N and 50°N. The simulating results can improve our understanding of the geographical and ecological characteristics of E. angustifolia, and provide references for the introduction of this species for control and restoration of degraded land in China.

First surface-based estimation of the aerosol indirect effect over a site in southeastern China

The deployment of the U.S. Atmospheric Radiation Measurement mobile facility in Shouxian from May to December 2008 amassed the most comprehensive set of measurements of atmospheric, surface, aerosol, and cloud variables in China. This deployment provided a unique opportunity to investigate the aerosol–cloud interactions, which are most challenging and, to date, have not been examined to any great degree in China. The relationship between cloud droplet effective radius (CER) and aerosol index (AI) is very weak in summer because the cloud droplet growth is least affected by the competition for water vapor. Mean cloud liquid water path (LWP) and cloud optical depth (COD) significantly increase with increasing AI in fall. The sensitivities of CER and LWP to aerosol loading increases are not significantly different under different air mass conditions. There is a significant correlation between the changes in hourly mean AI and the changes in hourly mean CER, LWP, and COD. The aerosol first indirect effect (FIE) is estimated in terms of relative changes in both CER (FIECER) and COD (FIECOD) with changes in AI for different seasons and air masses. FIECOD and FIECER are similar in magnitude and close to the typical FIE value of ∼ 0.23, and do not change much between summer and fall or between the two different air mass conditions. Similar analyses were done using spaceborne Moderate Resolution Imaging Spectroradiometer data. The satellite-derived FIE is contrary to the FIE estimated from surface retrievals and may have large uncertainties due to some inherent limitations.

Human papillomavirus (HPV) 18 genetic variants and cervical cancer risk in Taizhou area, China

Human papillomavirus (HPV) type 18 is predominantly associated with the development of cervical adenocarcinomas, whereas data on HPV18 genetic variability in China are limited. HPV18 genetic variants were formed phylogenetic tree, including lineages A, B, and C. We aimed to evaluate the diversity of HPV18 genetic variants by sequencing the entire E6, E7 and L1 genes. Between 2012 and 2015, a total of 138 (0.8%, 138/17669) women with single HPV18 infection were selected in this study. Finally, we observed 122 HPV18 isolates of the complete E6-E7-L1 sequences, and obtained 36 distinct variation patterns which the accession GenBank numbers as KY457805-KY457840. Except KY457805, KY457813, KY457819, KY457827, KY457829, the rest of HPV18 isolates (81.1%, 31/36) are novel variants. All of HPV18 variants belong to lineage A, while no lineage B, and C was found in our population of Taizhou region, Southeast China. Sublineage A1 was the most common variants (85.2%, 104/122), followed by sublineage A4, A3 and A5, while no sublineage A2 was obtained. Based on the tree topologies, there were three newly identified candidates' sublineages A6-A8. Out of 122 women, 67 (54.9%) had diagnosed by biopsy, including 49 women who diagnosed with cervicitis, 12 with cervical intraepithelial neoplasia (CIN)1, 4 with CIN2/3, and 2 with adenocarcinomas, respectively. Nevertheless, there was no association between HPV18 (sub) lineages and CIN1 or worse (CIN1+) lesions comparing with normal biopsies (P = .469). In conclusion, knowledge of the distribution of geographic/ethnical HPV18 genetic diversity provides critical information for developing diagnostic probes, epidemiologic correlate of cervical cancer risk and design of HPV vaccines for targeted populations.

Links between Western Pacific Subtropical High and vegetation growth in China

There is a lack of simple ways to predict the vegetation responses to the East Asian Monsoon (EAM) variability in China due to the complexity of the monsoon system. In this study, we found the variation of the Western Pacific Subtropical High (WPSH), which is one of the major components of the EAM, has a profound influence on the vegetation growth in China. When the WPSH is located more to the west of its climate average, the eastern and northwestern parts experience increased yearly-averaged normalized difference vegetation index (NDVI) and gross primary productivity (GPP) by 0.3%–2.2%, and 0.2%–2.2%, respectively. In contrast, when the WPSH is located more to the east of its climate average, the above areas experience decreased yearly-averaged NDVI and GPP by 0.4% to 1.6%, and 1.3% to 4.5%, respectively. The WPSH serves as a major circulation index to predict the response of vegetation to monsoon.

FOREIGN DIRECT INVESTMENT, TRADE OPENNESS AND GDP IN CHINA, INDIA AND MEXICO

This paper examines the short and long-run relationships between Foreign Direct Investment (FDI), Trade Openness and GDP in China, India and Mexico from 1980 to 2011. Based on the properties of individual time series data, the paper estimates the VAR or VECM of the three variables to determine short and long-run causal relationships. The results confirm the existence of long-run causal relationships between the three variables for China and Mexico. The results also point to sharp differences in short-run causal relationships in the three countries and several plausible explanations consistent with the findings are offered.

A Study on the Relationship between Money Supply and Macroeconomic Variables in China

AbstractMany scholars have examined the importance of the money supply to the macroeconomics in developed countries. However, few studies have explored this proposition in developing countries. So, in this paper, annual series data from 2000 to 2016 is applied to analyze the relationship between the money supply (M2) and the macroeconomic variables (the real GDP, the inflation rate & the interest rate) under the vector auto regression (VAR) model in China. The purpose of this paper is to verify the impact of these variables on the money supply in China. After performing an empirical analysis, conclusions can be obtained that an increase in the real GDP can result in an increase in the money supply; Also, an increase in the inflation rate can lead to an increase in the money supply; Conversely, an increase in the interest rate can cause a decrease in the money supply. Therefore, via adjusting the change of real GDP, inflation rate and interest rate, a better control of the money supply can be performed for the policy-makers in China.

Regional growth differences in China for 1995–2013: an empirical integrative analysis of their sources

An integrative empirical analysis of several regional economic outcome variables in China for the period of 1995–2013 reveal the major sources of regional growth differences in China. Patterns of growth in population, per capita income, gross regional product, housing prices and changes in unemployment rates are identified using principal components analysis. Regression analysis of principal component scores is applied to identify geographic and administrative status patterns in the sources of the growth. The analysis suggests that shifts in labor supply largely were responsible for the regional growth differences over the period, though shifts in labor demand were nearly equally as important. The results have implications for evaluating the success of regional development policies such as the Western Development Strategy.

A comprehensive analysis of coherent rainfall patterns in China and potential drivers. Part II: intraseasonal variability

The causes of subseasonal precipitation variability in China are investigated using observations and reanalysis data for extended winter (November–April) and summer (May–October) seasons from 1982 to 2007. For each season, the three dominant regions of coherent intraseasonal variability are identified with Empirical Orthogonal Teleconnection (EOT) analysis. While previous studies have focused on particular causes for precipitation variability or on specific regions, here a comprehensive analysis is carried out with an objective method. Furthermore, the associated rainfall anomaly timeseries are tied to specific locations in China, which facilitates their interpretation. To understand the underlying processes associated with spatially coherent patterns of rainfall variability, fields from observations and reanalysis are regressed onto EOT timeseries. The three dominant patterns in winter together explain 43% of the total space–time variance and have their origins in midlatitude disturbances that appear two pentads in advance. Winter precipitation variability along the Yangtze River is associated with wave trains originating over the Atlantic and northern Europe, while precipitation variability in southeast China is connected to the Mediterranean storm track. In summer, all patterns have a strong relationship with the Boreal Summer Intraseasonal Oscillation and are modulated by the seasonal cycle of the East Asian summer monsoon. The wet and dry phases of the regional patterns can substantially modulate the frequency of daily rainfall across China. The discovered links between weather patterns, precursors, and effects on local and remote precipitation may provide a valuable basis for hydrological risk assessments and the evaluation of numerical weather prediction models.

A comprehensive analysis of coherent rainfall patterns in China and potential drivers. Part I: Interannual variability

Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. To improve its understanding and prediction, many studies have associated precipitation variability with particular causes for specific seasons and regions. Here, a consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to 1951–2007 high-resolution precipitation observations over China in all seasons. Instead of maximizing the explained space–time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. The EOT method is validated by the reproduction of known relationships to the El Niño Southern Oscillation (ENSO): high positive correlations with ENSO are found in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that wintertime rainfall variability along the southeast coast is associated with anomalous convection over the tropical eastern Atlantic and communicated to China through a zonal wavenumber-three Rossby wave. Furthermore, spring rainfall variability in the Yangtze valley is related to upper-tropospheric midlatitude perturbations that are part of a Rossby wave pattern with its origin in the North Atlantic. A circumglobal wave pattern in the northern hemisphere is also associated with autumn precipitation variability in eastern areas. The analysis is objective, comprehensive, and produces timeseries that are tied to specific locations in China. This facilitates the interpretation of associated dynamical processes, is useful for understanding the regional hydrological cycle, and allows the results to serve as a benchmark for assessing general circulation models.

Changes in record-breaking temperature events in China and projections for the future

As global warming intensifies, more record-breaking (RB) temperature events are reported in many places around the world where temperatures are higher than ever before . The RB temperatures have caused severe impacts on ecosystems and human society. Here, we address changes in RB temperature events occurring over China in the past (1961–2014) as well as future projections (2006–2100) using observational data and the newly available simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The number of RB events has a significant multi-decadal variability in China, and the intensity expresses a strong decrease from 1961 to 2014. However, more frequent RB events occurred in mid-eastern and northeastern China over last 30 years (1981–2010). Comparisons with observational data indicate multi-model ensemble (MME) simulations from the CMIP5 model perform well in simulating RB events for the historical run period (1961–2005). CMIP5 MME shows a relatively larger uncertainty for the change in intensity. From 2051 to 2100, fewer RB events are projected to occur in most parts of China according to RCP 2.6 scenarios. Over the longer period from 2006 to 2100, a remarkable increase is expected for the entire country according to RCP 8.5 scenarios and the maximum numbers of RB events increase by approximately 600 per year at end of twenty-first century.

Effects of government spending shocks in China, Japan, and Korea

ABSTRACTThis study investigates the effects of government spending shocks on various key macro variables in China, Korea, and Japan using structural VAR models. The main empirical findings are as follows. Government spending multipliers of all three countries are far larger than 1 in recent years. The effectiveness of fiscal expansion has not changed markedly in China but substantially increased in Korea (after the Asian financial crisis) and Japan (during zero lower bound period). Increases in the effectiveness of fiscal expansion are associated with changes in the monetary and exchange rate policy regimes and institutions of these countries. Among the three countries, the government spending multiplier is relatively large in China but relatively small in Japan in recent years. Although the effects on exchange rate and trade balance vary across countries and sample periods, real exchange rate tends to depreciate, whereas trade balance tends to improve under flexible exchange rate regimes. Some empirical findings are consistent with standard theory, but others are not.Abbreviations: NK: New Keynesian VAR: Vector Autoregressive ZLB: Zero Lower Bound

Linking above- and belowground traits to soil and climate variables: an integrated database on China's grassland species.

Knowledge of plant functional traits and trait-environment interactions is important for characterizing species strategies and understanding ecological processes. However, comprehensive field data on both above- and belowground traits, together with their environmental variables are scarce. Biome-scale studies are particularly lacking. Here we present two large-scale data sets that include functional traits of leaves and fine roots and their corresponding soil and climatic variables in China's grasslands. Leaf, fine root, and soil samples were collected in three biogeographic regions: temperate grassland on the Inner Mongolia Plateau, alpine grassland on the Tibetan Plateau, and mountain grassland in the Xinjiang mountain areas. Field data were collected over two periods. The first data set collected between 2003 and 2004 includes 13 foliar traits (leaf mass per area, LMA; photosynthetic nitrogen use efficiency, PNUE; water use efficiency, WUE; stomatal conductance for water vapor, Gs; transpiration rate, TR; mass- and area-based photosynthetic capacity, Amass and Aarea; mass- and area-based carbon concentrations, Cmass and Carea; nitrogen concentrations, Nmass and Narea; and phosphorus concentrations, Pmass and Parea) for 170 species at 173 sites. The second data set collected between 2006 and 2007 includes six sets of analogous traits for both leaves and fine roots (C, N, and P concentrations; leaf thickness/root diameter; specific leaf area, SLA; specific root length, SRL; and tissue density) for 139 species at 82 sites, along with soil attributes (soil total and organic carbon, STC and SOC; total and available N, STN and SAN; total and available P, STP and SAP; pH, bulk density, and moisture). Moreover, associated information was also gathered, including geographical location (latitude, longitude, and altitude), climate (mean annual temperature, MAT; mean annual precipitation, MAP; growing season temperature, GST; growing season precipitation, GSP; potential evapotranspiration, PET; and actual evapotranspiration, AET) and site descriptions (vegetation and soil types). The data sets are unique because they integrate plant above- and belowground traits, climate, and soil factors over broad regional, elevational, and taxonomic ranges in understudied regions (e.g., the Tibetan Plateau). This is the only database on China's grassland species for unrestricted global access. These data sets will make a valuable contribution to future large-scale trait-based ecological studies.

ARIMA Forecasting Chinese Macroeconomic Variables Based on Factor and Principal Component Backdating

In this paper the backdating methods based on factors and principal components are applied for the first time to emulate the historical macroeconomic variables in China. The numerical results show that these procedures are useful to backdate some missing or not available historical data. ARIMA forecasting experiments based on backdated historical data are conducted and compared with forecasting procedures using directly factors and principal components. Our results suggest that some key variables like GDP can indeed be forecasted more precisely with the principal components backdated data.

Vegetation Dynamics and Their Response to Climatic Variability in China

Based on SPOT VEGETATION data and meteorological data, NDVI (Normalized Difference Vegetation Index) and its response to temperature and precipitation in China and its different regions were investigated over the period 1998–2013 by using the maximum value composite and linear regression methods. The results showed that NDVI presented significant increase (0.0046/a) for all of China and all the regions over the last 16 years. Meanwhile, annual mean temperature of China presented a slightly increasing trend, while the annual precipitation showed a slightly decreasing trend over the last 16 years. Nevertheless, there were differences between temperature and precipitation in the subregions of China. The Annual NDVI had better relationships with precipitation (r=0.126) compared to temperature (r=-0.094), and NDVI also had a good correlation with precipitation rather than temperature in different subregions of China. Additionally, human activities also made a difference to the trends of NDVI in some regions. This study is conductive to the effects of climate change on vegetation activity in future research.

Nonlinear changes in aridity due to precipitation and evapotranspiration in China from 1961 to 2015

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 74:263-281 (2018) - DOI: https://doi.org/10.3354/cr01500 Nonlinear changes in aridity due to precipitation and evapotranspiration in China from 1961 to 2015 Yunhe Yin1,*, Danyang Ma1,2, Shaohong Wu1,2 1Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, PR China 2University of Chinese Academy of Sciences, Beijing 100049, PR China *Corresponding author: yinyh@igsnrr.ac.cn ABSTRACT: Changes in regional aridity have complicated spatio-temporal features during the past several decades and have important implications for hydrologic cycles under global climate change. However, nonlinear changes in aridity and its spatial variability in China remain poorly understood. Here, we analyzed the spatial-temporal changes in hydroclimatic variables, including reference evapotranspiration (ETo), precipitation (P), aridity index (AI) and their relationships, mainly based on the ensemble empirical mode decomposition method. A climate dataset from 573 meteorological stations in China was used for the period 1961-2015. The results show that the nonlinearity of changes in aridity was complex, with distinct spatial differences. Approximately 76.09% of stations showed reversed trends in AI during 1961-2015, among which AI initially decreased and then increased, mainly in Inner Mongolia and the areas south of the middle and lower reaches of the Yangtze River. However, their reversal times were not synchronous. The drying to wetting transition mainly occurred in northern areas, including the southern part of Northeast China, the eastern Loess Plateau and the southern North China Plain. Although the majority of stations experienced reversals from downward to upward trends of ETo (53.92%) mainly around the 1990s, increasing precipitation exerted a larger effect on AI. For most eco-geographical regions in China, the nonlinear variations in ETo and P jointly led to the decline in AI over the past 55 yr, and the P trend contributed more than the ETo trend to the change in AI, except in subtropical regions, where ETo variations played a key role. KEY WORDS: Aridity · Precipitation · Reference evapotranspiration · Nonlinear · Climate change · Ensemble empirical mode decomposition · EEMD Full text in pdf format PreviousCite this article as: Yin Y, Ma D, Wu S (2018) Nonlinear changes in aridity due to precipitation and evapotranspiration in China from 1961 to 2015. Clim Res 74:263-281. https://doi.org/10.3354/cr01500 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 74, No. 3. Online publication date: February 28, 2018 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2018 Inter-Research.

High‐frequency daily temperature variability in China and its relationship to large‐scale circulation

ABSTRACTTwo measures of intra‐seasonal variability, indicated respectively by standard deviations (SD) and day‐to‐day (DTD) fluctuations denoted by absolute differences between adjacent 2‐day periods, as well as their relationships with large‐scale circulation patterns were investigated in China during 1962–2008 on the basis of homogenized daily temperature records from 549 local stations and reanalysis data. Our results show that both the SD and DTD of daily minimum temperatures (Tmin) in summer as well as the minimum and maximum temperatures in winter have been decreasing, while the daily maximum temperature (Tmax) variability in summer is fluctuating more, especially over southern China. In summer, an attribution analysis indicates that the intensity of the Western Pacific Subtropical High (WPSH) and high‐level East Asian Subtropical Jet stream (EASJ) are positively correlated with both SD and DTD, but the correlation coefficients are generally greater with the SD than with the DTD of the daily maximum temperature, Tmax. In contrast, the location of the EASJ shows the opposite correlation pattern, with intensity regarding the correlation with both SD and DTD. In winter, the Arctic Oscillation (AO) is negatively correlated with both the SD and DTD of the daily minimum temperature, but its intra‐seasonal variability exhibits good agreement with the SD of the Tmin. The Siberian High acts differently with respect to the SD and DTD of the Tmin, demonstrating a regionally consistent positive correlation with the SD. Overall, the large‐scale circulation can well explain the intra‐seasonal SD, but DTD fluctuations may be more local and impacted by local conditions, such as changes in the temperature itself, the land surface, and so on.

Critical brand innovation factors (CBIF): Understanding innovation and market performance in the Chinese high-tech service industry

Brand innovation sweeps aside established practices and disrupts the status quo, resulting in the transformation of markets. The present study develops and tests a model of critical brand innovation factors (CBIF) by examining key factors influencing firm-level brands' innovation and increased market performance. Adapting both organizational elements and market response characteristics, the model integrates four key variables in China's industrial service markets: innovation, internationalization, market orientation, and organizational learning. Findings provide a foundation for understanding how firms improve their innovation and subsequent market performance in an emerging and dynamic market. The study demonstrates that when brands are more innovative, their performance increases: Brand innovation plays a fully mediating role on the effects of market orientation and organizational learning to market performance, but has no mediating effect on internationalization and market performance. A lack of innovation reduces market performance even when internationalization, market orientation, and organizational learning are present.