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Xie Z.Q.,Jiangsu Institute of Meteorological science | Du Y.,Nanjing University of Information Science and Technology | Zeng Y.,Jiangsu Institute of Meteorological science | Yan M.L.,Jiangsu Institute of Meteorological science | Zhu C.Y.,Jiangsu Institute of Meteorological science
Quaternary International | Year: 2010

A zigzag city belt along the Yangtze River and Hangzhou rim has formed in the Yangtze River Delta in China due to the accelerated development of human activities and urbanization. Local climate change in the belt has affected the spatial patterns of surface air temperature (SAT). (1) There exist six major warmer centers with increasing rates of SAT from 0.28 to 0.54°C per decade during 1961-2006 along the belt, namely Yangzhou, Nanjing, Jiangyin, Shanghai, Hangzhou and Ningbo. As the greatest areas of human activities and rapid urbanization in the Yangtze River Delta, Shanghai metropolitan areas have the maximum rates of increases in annual and seasonal mean SAT, which range from 0.23 to 0.50°C per decade, and the strongest urban heat island effects, which are increasing at rates in the range of 0.11-0.15°C per decade. (2) Local warming and urban heat island effects have created the largest and warmest SAT core in the Shanghai metropolitan areas, contributing to spatial pattern changes in SAT over the Yangtze River Delta. The spatial patterns of SAT for 2001-2006 and 1971-2000 significantly differ in the typical latitudinal pattern for 1971-2000 that has changed, mainly in Shanghai metropolitan areas. (3) The annual mean of the regional SAT will increase from 15.4°C in 1961-1990 to 18.5°C in 2071-2100 due to global warming and urban heat island effects according to the IPCC SRES A2 Scenario. This increase is notably higher than the increment of 2.5°C from 15.4°C to 17.9°C due to global warming alone. The spatial distribution of the projected SAT with global warming and urban heat island effects is markedly different from that for global warming alone. In 2071-2100, the Shanghai metropolitan areas will have summer average temperatures of about 30.0-30.5°C, which are higher than summer average temperatures of about 28.7°C that would be expected from global warming alone. Higher average temperatures can have negative implications for energy and water consumption, human health and local ecosystems. The development and implementation of adaptation strategies are important and required by the policy makers from local government and city planning departments. © 2010 Elsevier Ltd and INQUA.

Liu M.,CAS Institute of Genetics and Developmental Biology | Liu M.,University of Chinese Academy of Sciences | Shen Y.,CAS Institute of Genetics and Developmental Biology | Zeng Y.,Jiangsu Institute of Meteorological science | Liu C.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research
Journal of Geographical Sciences | Year: 2010

Trends in pan evaporation are widely relevant to the hydrological community as indicators of hydrological and climate change. Pan evaporation has been decreasing in the past few decades over many large areas with differing climates globally. This study analyzes pan evaporation data from 671 stations in China over the past 50 years in order to reveal the trends of it and the corresponding trend attribution. Mann-Kendall test shows a significant declining trend in pan evaporation for most stations, with an average decrease of 17. 2 mm/10a in China as a whole, the rate of decline was the steepest in the humid region (29. 7 mm/10a), and was 17. 6 mm/10a and 5. 5 mm/10a in the semi-humid/semi-arid region and arid region, respectively. Complete correlation coefficients of pan evaporation with 7 climate factors were computed, and decreases in diurnal temperature range (DTR), SD (sunshine duration) and wind speed were found to be the main attributing factors in the pan evaporation declines. Decrease in DTR and SD may relate to the increase of clouds and aerosol as well as the other pollutants, and decrease in wind speed to weakening of the Asian winter and summer monsoons under global climate warming. © 2010 Science in China Press and Springer-Verlag Berlin Heidelberg.

Wang G.,Chinese Academy of Meteorological Sciences | Wang G.,Jiangsu Institute of Meteorological Science | Yang J.,Jiangsu Institute of Meteorological Science | Wang D.,National Meteorological Center | Liu L.,Chinese Academy of Meteorological Sciences
Atmospheric Research | Year: 2016

Extrapolation techniques and storm-scale Numerical Weather Prediction (NWP) models are two primary approaches for short-term precipitation forecasts. The primary objective of this study is to verify precipitation forecasts and compare the performances of two nowcasting schemes: a Beijing Auto-Nowcast system (BJ-ANC) based on extrapolation techniques and a storm-scale NWP model called the Advanced Regional Prediction System (ARPS). The verification and comparison takes into account six heavy precipitation events that occurred in the summer of 2014 and 2015 in Jiangsu, China. The forecast performances of the two schemes were evaluated for the next 6 h at 1-h intervals using gridpoint-based measures of critical success index, bias, index of agreement, root mean square error, and using an object-based verification method called Structure-Amplitude-Location (SAL) score. Regarding gridpoint-based measures, BJ-ANC outperforms ARPS at first, but then the forecast accuracy decreases rapidly with lead time and performs worse than ARPS after 4-5 h of the initial forecast. Regarding the object-based verification method, most forecasts produced by BJ-ANC focus on the center of the diagram at the 1-h lead time and indicate high-quality forecasts. As the lead time increases, BJ-ANC overestimates precipitation amount and produces widespread precipitation, especially at a 6-h lead time. The ARPS model overestimates precipitation at all lead times, particularly at first. © 2016 The Authors.

Liu Y.,Jiangsu Meteorological Observation Center | Liu Y.,Jiangsu Institute of Meteorological science | Liu Y.,Nanjing University of Information Science and Technology | Zhang W.,Nanjing University of Information Science and Technology
Meteorology and Atmospheric Physics | Year: 2016

This study develops a proper way to incorporate Atmospheric Infrared Sounder (AIRS) ozone data into the bogus data assimilation (BDA) initialization scheme for improving hurricane prediction. First, the observation operator at some model levels with the highest correlation coefficients is established to assimilate AIRS ozone data based on the correlation between total column ozone and potential vorticity (PV) ranging from 400 to 50 hPa level. Second, AIRS ozone data act as an augmentation to a BDA procedure using a four-dimensional variational (4D-Var) data assimilation system. Case studies of several hurricanes are performed to demonstrate the effectiveness of the bogus and ozone data assimilation (BODA) scheme. The statistical result indicates that assimilating AIRS ozone data at 4, 5, or 6 model levels can produce a significant improvement in hurricane track and intensity prediction, with reasonable computation time for the hurricane initialization. Moreover, a detailed analysis of how BODA scheme affects hurricane prediction is conducted for Hurricane Earl (2010). It is found that the new scheme developed in this study generates significant adjustments in the initial conditions (ICs) from the lower levels to the upper levels, compared with the BDA scheme. With the BODA scheme, hurricane development is found to be much more sensitive to the number of ozone data assimilation levels. In particular, the experiment with the assimilation of AIRS ozone data at proper number of model levels shows great capabilities in reproducing the intensity and intensity changes of Hurricane Earl, as well as improve the track prediction. These results suggest that AIRS ozone data convey valuable meteorological information in the upper troposphere, which can be assimilated into a numerical model to improve hurricane initialization when the low-level bogus data are included. © 2016 Springer-Verlag Wien

Huang S.-C.,Jiangsu Institute of Meteorological science | Zhou J.-L.,Jiangsu Institute of Meteorological science
International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2013 | Year: 2013

This is a study to improve the pertinence and accuracy of bridge-construction meteorological risk assessment. The multi-source information including meteorological observations, the disaster information, and the meteorological conditions of construction unit were used. Taken a large-scale bridge construction in northern Jiangsu of China as an example, the paper researched the dialectical relationship between the construction weather risk and meteorological disaster risk, put forward the main evaluation indicators and evaluation methods for meteorological risk that fused multi-source information, and then established the assessment process of meteorological risk for bridge construction based on multi-source data. The results show that the meteorological factors such as temperature, wind speed, visibility and others, are the main weather risk indicators in the construction of the bridge, and high-impact weather disaster risk such as strong wind, rain and snow, frozen are important parts of the bridge construction risk. Bridge construction meteorological risk assessment base on multi-source information could be divided into three aspects: meteorological background investigation, the project site meteorological observation and analysis, and numerical model simulate. The results implied that while the risk assessment conclusions based on the former two aspects could suitable for the project purpose, the meteorological risk assessment results based on multi-source information and statistical downscaling techniques have greater reliability. © 2013. The authors.

Li N.,Nanjing University of Information Science and Technology | Wei M.,Nanjing University of Information Science and Technology | Niu B.,Wuhan Central Meteorological Observatory | Mu X.,Jiangsu Institute of Meteorological science
Meteorological Applications | Year: 2012

A new storm identification and warning technique is proposed which exclusively uses radar data as input. The new identification method assembles contiguous storm points to constitute 2D storm components and improve the vertical association of storm components to construct 3D storms, which can overcome the deficiencies existing in traditional identification methods. Based on the evolution properties and characteristic distributions, strong storms and general storms are specified to train support vector machines (SVMs) which then can be used to discriminate storms. The performance of the SVM shows that it can indicate the intensity and development of a storm, providing an important aid in severe weather warning. © 2011 Royal Meteorological Society.

Li Y.,Jiangsu Institute of Meteorological science | Wu B.,Chinese Academy of Meteorological Sciences | Yang Q.,Jiangsu Institute of Meteorological science | Huang S.,Jiangsu Institute of Meteorological science
Acta Meteorologica Sinica | Year: 2013

Observational and reanalysis data are used to investigate the different relationships between boreal spring sea surface temperature (SST) in the Indian and Pacific oceans and summer precipitation in China. Partial correlation analysis reveals that the effects of spring Indian Ocean SST (IO SST) and Pacific SST (PSST) anomalies on summer precipitation in China are qualitatively opposite. When IO SST anomalies are considered independently of PSST anomalies, precipitation decreases south of the Yangtze River, in most areas of Inner Mongolia, and in some parts of Liaoning Province, and increases in the Yangtze River valley, parts of southwestern and northern China, northeastern Inner Mongolia, and Heilongjiang Province. This results in a negative-positive-negative-positive pattern of precipitation anomalies in China from south to north. When PSST anomalies (particularly those in the Niño3.4 region) are considered independently of IO SST anomalies, the pattern of precipitation anomalies in China is positive-negative-positive-negative from south to north. The genesis of summer precipitation anomalies in China is also examined when El Niño-Southern Oscillation (ENSO) signals are removed from the ocean and atmosphere. An anticyclonic low-level wind anomaly forms in the South China Sea-Northwest Pacific area when the IO SST anomaly (SSTA) is warm and the Northwest Pacific SSTA is cold. This anticyclonic anomaly substantially influences summer precipitation in China. Anomalous warming of tropical IO SST induces positive geopotential height anomalies in the subtropics and an east-west dipole pattern in midlatitudes over Asia. These anomalies also affect summer precipitation in China. © 2013 The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg.

He J.,Nanjing University of Information Science and Technology | Fan S.,Nanjing University of Information Science and Technology | Meng Q.,Nanjing University of Information Science and Technology | Sun Y.,Nanjing University of Information Science and Technology | And 2 more authors.
Atmospheric Environment | Year: 2014

A study of 16 polycyclic aromatic hydrocarbons (PAHs) associated with fine particulate matters at suburban and urban sites in Nanjing was carried out each season from November 2009 to July 2010. At the suburban and urban sites, the concentrations of total PAHs (T-PAHs) were in the ranges of 30.76-102.26ng/m3 and 25.92-90.80ng/m3, respectively. This paper elucidates the distributions, sources of PAHs and meteorological influences: 1) PAHs concentrations at the two sites were close to each other and similarity between PAHs profiles of the two sites indicated they had common sources, which were attributed to the combined effect of regional transport and local emission. 2) At both sites, the profiles displayed obvious seasonal variations, as a result of the seasonality of sources and meteorological influences. The T-PAHs concentrations were in the order of winter>spring>autumn>summer. 3) Source apportionment showed vehicle exhaust (72.93-87.24%) was the greatest contributor in all seasons. The coal combustion and coke production (coal/coke) (10.02-18.63%) were identified in all but summer seasons, because of the low collection efficiency of PAHs markers of coal/coke under high temperature. For autumn, biomass burning (10.58%) was an extra contributor. 4) Regarding meteorological parameters, a negative effect of temperature over PAHs was confirmed, with a correlation coefficient of-0.51 (p<0.05). Precipitation could remove PAHs to some extent. Both positive and negative correlations between PAHs concentration and wind speed in each season were analyzed in combination with air mass back-trajectories so as to evaluate the effects of regional air transport. The results showed that polluted air from ENE-S and NNW-NE brought in outside sources to the study area and played a major role in the accumulation of fine-particulate PAHs in spring and winter respectively, while clean air from southwest contributed to the dilution in summer. © 2014 Elsevier Ltd.

Die H.,Lanzhou Institute of Arid Meteorology | Lei Z.,Lanzhou University | Hongbin W.,Jiangsu Institute of Meteorological science
IOP Conference Series: Earth and Environmental Science | Year: 2014

In this study, Aerosol Optical Depth (AOD) at 550nm from the MODIS sensor on board the Terra/Aqua satellites were compared with sun photometer (CE-318) measurements from 11 AERONET stations in China. The average correlation coefficient (R) value from the AOD product, using the Aqua-MODIS Deep Blue algorithm, in the Hexi Corridor was 0.67. The MODIS Dark Target algorithm AOD product is superior to Deep Blue algorithm AOD products in SACOL of the Semi-arid regions of the Loess Plateau. These two kinds of algorithm are not applicable to sites in Lanzhou city. The average R value of Dark Target algorithm AOD MODIS products is 0.91 for Terra and 0.88 for Aqua in the eastern part of China. According to the analysis of spatial and temporal characteristics of the two MODIS AOD products in China, high value areas are mainly distributed in the southern part of Xinjiang (0.5∼0.8), Sichuan Basin (0.8∼0.9), North China (0.6∼0.8) and the middle and lower reaches of the Changjiang River (0.8∼1.0). The Deep Blue algorithm for Aqua-MODIS is a good supplement for the retrieval of AOD above bright surfaces of deserts in Northwest China.

PubMed | Jiangsu Institute of Meteorological science, National Research Center for Environmental Analysis and Measurement, Meteorological Observation Center and Beijing Urban Meteorological Engineering Technology Research Center
Type: | Journal: Journal of environmental sciences (China) | Year: 2015

The characteristics of water-soluble ions in airborne particulate matter in Beijing were investigated using ion chromatography. The results showed that the total concentrations of ions were 83.7 48.9 g/m(3) in spring, 54.0 17.0 g/m(3) in summer, 54.1 42.9 g/m(3) in autumn, and 88.8 47.7 g/m(3) in winter, respectively. Furthermore, out of all the ions, NO3(-), SO4(2-) and NH4(+) accounted for 81.2% in spring, 78.5% in summer, 74.6% in autumn, and 76.3% in winter. Mg(2+) and Ca(2+) were mainly associated with coarse particles, with a peak that ranged from 5.8 to 9.0 m. Na(+), NH4(+) and Cl(-) had a multi-mode distribution with peaks that ranged from 0.43 to 1.1 m and 4.7 to 9.0 m. K(+), NO3(-), and SO4(2-) were mainly associated with fine particles, with a peak that ranged from 0.65 to 2.1 m. The concentrations of Na(+), K(+), Mg(2+), Ca(2+), NH4(+), Cl(-), NO3(-) and SO4(2-) were 2.69, 2.32, 1.01, 4.84, 16.9, 11.8, 42.0, and 44.1 g/m(3) in particulate matter (PM) on foggy days, respectively, which were 1.4 to 7.3 times higher than those on clear days. The concentrations of these ions were 2.40, 1.66, 0.92, 4.95, 17.5, 7.00, 32.6, and 34.7 g/m(3) in PM on hazy days, respectively, which were 1.2-5.7 times higher than those on clear days.

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