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Ma J.,China Agricultural University | Ma J.,CAS Institute of Atmospheric Physics | Liu Y.,China Agricultural University | Yang X.,China Agricultural University | And 3 more authors.
Shengtai Xuebao/ Acta Ecologica Sinica

In the past few decades, significant changes of climate resources had taken place across the North China Plain (NCP), corresponding to global climate changes. Climate change has caused far-reaching impacts to agricultural production in the North China Plain, where is one of the most important food production regions in China. In this study, characteristics of regional distribution of climate resources during the five different decades from 1961 to 2007 were analyzed by using daily weather data from 59 typical agro-meteorological stations located the North China Plain. The major results showed: (1) heat resources in the North China Plain were significantly enriched during the study period due to global climatic warming, such as ≤0°C and ≤10°C acumulative air temperature markedly increased, specially, in north and east. (2) Annual precipitation decreased about 20 mm per decade from 1961 to 2007. Seasonal precipitation in summer and autumn also decreased with rate ranging from 25 mm/10 a to 40 mm/10 a, however, slightly increased in spring and winter. In addition, yearly mean of reference crop evapotranspiration (ET0) was declined in the North China Plain. The decreasing rate of rainfall was a little more than that of ET0. (3) Sunshine hours in the North China Plain showed a significant declination, especially in large and middle size urban area. Source

Guo P.,Henan Institute of Meteorological Science
Proceedings of SPIE - The International Society for Optical Engineering

Sea surface temperature (SST) is one of the most important variables related to the global ocean-atmosphere system, which play an important role in studies of air-sea heat exchange, upper ocean processes, and weather forecast. SST data are routinely measured from ships, buoys and offshore platforms. In this paper, the weekly 4 km resolution AVHRR SST data (1985-2006), the weekly 4 km resolution MODIS SST data (2002-2007) and the daily 25 km resolution AMSR-E SST data (2002-2007) are chosen for merging. These SST data are derived from different Remote Sensors with different spatial and temporal resolution. By merging these SST data, we can get a new SST product and obtain more information. The bayesian hierarchical model using Markov Chain Monte Carlo (MCMC) simulation methods was used to merging the thermal infrared MODIS SST data and passive microwave AMSR-E SST data. The results show that merged SST data have a better completeness than MODIS SST and AMSR-E SST products. Comparing merged SST data with drift buoy SST, the validation result shows that the bias is 0.32118K and RMSE is 0.8026K. © 2010 Copyright SPIE - The International Society for Optical Engineering. Source

Yang F.,China Meteorological Administration Training Center | Zhu Y.,China Meteorological Administration Training Center | Liu W.,Henan Institute of Meteorological Science
Journal of Natural Disasters

Based on the index of the occurrence of dryhot wind in winter wheat region, an index of its occurrence intensity was established and the occurrence rule of dry-hot wind was inverted for the main winter wheat producing areas in the North China Plain since 1961. According to the results, the winter wheat area of the middle and south of Hebei, the west and north of Shandong and the north of Henan are the high risk zones of dry-hot wind, and the occurrence has reduced since the beginning of 1980' s. Thus, using the winter wheat observatory meteorological data, production structure material, yield, growth phase and other data, a dry-hot wind risk assessment model was established after the construction of the dry-hot wind risk evaluation index system that cover the dry-hot wind strength risk index and integrated disaster resisting capability index of the winter wheat. The dry-hot risk in main winter wheat producing areas of north China was then assessed using the model, and the dry-hot wind risk zoning assessment map was made for the areas. Assessment results show that, southeast of Hebei and northwest of Shandong are areas with high risk of the dry-hot wind influence, while south of Henan, east of Shandong and Hebei are low risk areas. Source

Liu Y.,Key Laboratory of Agricultural Environment | Liu Y.,Chinese Academy of Agricultural Sciences | Liu Y.,China Agricultural University | Yang X.,China Agricultural University | And 2 more authors.
Regional Environmental Change

El Niño-Southern Oscillation (ENSO) contributes to climate anomalies, especially those related to regional rainfall, which affect crop production. Although the North China Plain (NCP) is the most important agricultural production region in China, the impact of ENSO events on local climate and crop production has received only limited attention. Therefore, the impact of different phases of ENSO on local climate and production of winter wheat and summer maize, both rain fed and irrigated, was investigated at three sites using the agricultural production systems simulator model. Data on daily temperature, precipitation, and sunshine hours for 50 years (1956-2006) were analysed to build climate scenarios for three categories of ENSO: years with El Niño events, years with La Niña events, and neutral years. The pattern of climate change was generally similar across the three sites: annual precipitation decreased slightly and annual mean sunshine hours decreased significantly, whereas annual mean minimum temperature increased significantly, leading to a significant increase in mean air temperature. Precipitation decreased and temperature and sunshine hours increased in both El Niño and La Niña years but remained stable in neutral years. Under full irrigation, the probability of exceeding distribution that crop yield would be higher was not markedly affected (P > 0.05), although the yields in both El Niño and La Niña years differed markedly from those in neutral years, especially in maize. Under rain-fed conditions, the yield of maize was decreased greatly (P < 0.05), the probability distribution of such reduction being the highest in La Niña years at all the sites (P < 0.05). At the provincial level, yields from well-managed fields differed (P > 0.05) with the ENSO category: production of maize was more vulnerable than that of wheat in El Niño and La Niña years. El Niño and La Niña had similar effects on climatic variables across the NCP: low yields in El Niño and La Niña years due to lower precipitation and high yields in neutral years due to longer sunshine hours and additional irrigation. © 2013 The Author(s). Source

Meng L.,Wuhan University | Duan H.,Wuhan University | Huang C.,Wuhan University | Li Y.,Henan Institute of Meteorological Science
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University

Based on the XML data streaming transformation technology, a streaming transformation method is proposed for transforming GML to GeoOWL. Firstly, an element mapping transformation model is built by analyzing the mapping between GML elements and GeoOWL elements, then it is described using STX, finally the method is implemented using streaming transformation technology. Experiments show that our method is accurate, efficient and less memory is consumed, thus suitable for large GML file transformation. Source

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