Lanzhou Institute of Arid Meteorology

Gansu, China

Lanzhou Institute of Arid Meteorology

Gansu, China

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Wang C.,Nanjing University of Information Science and Technology | Wang C.,Lanzhou Institute of Arid Meteorology | Zhang S.,Lanzhou Institute of Arid Meteorology | Tian Y.,Nanjing University of Information Science and Technology | And 2 more authors.
International Journal of Environmental Research and Public Health | Year: 2014

The effects of simulated heat waves on body weight, body temperature, and biomarkers of cardiac function in ApoE-/- mice were investigated. Heat waves were simulated in a meteorological environment simulation chamber according to data from a heat wave that occurred in July 2001 in Nanjing, China. Eighteen ApoE-/- mice were divided into control group, heat wave group, and heat wave BH4 group. Mice in the heat wave and BH4 groups were exposed to simulated heat waves in the simulation chamber. Mice in BH4 group were treated with gastric lavage with BH4 2 h prior to heat wave exposure. Results showed that the heat waves did not significantly affect body weight or ET-1 levels. However, mice in the heat wave group had significantly higher rectal temperature and NO level and lower SOD activity compared with mice in the control group (p < 0.01), indicating that heat wave had negative effects on cardiac function in ApoE-/- mice. Gastric lavage with BH4 prior to heat wave exposure significantly reduced heat wave-induced increases in rectal temperature and decreases in SOD activity. Additionally, pretreatment with BH4 further increased NO level in plasma. Collectively, these beneficial effects demonstrate that BH4 may potentially mitigate the risk of coronary heart disease in mice under heat wave exposure. These results may be useful when studying the effects of heat waves on humans. © 2014 by the authors; licensee MDPI, Basel, Switzerland.


Zhang X.,Nanjing University of Information Science and Technology | Zhang S.,Lanzhou Institute of Arid Meteorology | Wang C.,Nanjing University of Information Science and Technology | Wang B.,Lanzhou Central Meteorological Observatory | Guo P.,Nanjing University of Information Science and Technology
International Journal of Environmental Research and Public Health | Year: 2014

The effects of cold air on cardiovascular and cerebrovascular diseases were investigated in an experimental study examining blood pressure and biochemical indicators. Zhangye, a city in Gansu Province, China, was selected as the experimental site. Health screening and blood tests were conducted, and finally, 30 cardiovascular disease patients and 40 healthy subjects were recruited. The experiment was performed during a cold event during 27-28 April 2013. Blood pressure, catecholamine, angiotensin II (ANG-II), cardiac troponin I (cTnI), muscle myoglobin (Mb) and endothefin-1 (ET-1) levels of the subjects were evaluated 1 day before, during the 2nd day of the cold exposure and 1 day after the cold air exposure. Our results suggest that cold air exposure increases blood pressure in cardiovascular disease patients and healthy subjects via the sympathetic nervous system (SNS) that is activated first and which augments ANG-II levels accelerating the release of the norepinephrine and stimulates the renin-angiotensin system (RAS). The combined effect of these factors leads to a rise in blood pressure. In addition, cold air exposure can cause significant metabolism and secretion of Mb, cTnI and ET-1 in subjects; taking the patient group as an example, ET-1 was 202.7 ng/L during the cold air exposure, increased 58 ng/L compared with before the cold air exposure, Mb and cTnI levels remained relatively high (2,219.5 ng/L and 613.2 ng/L, increased 642.1 ng/L and 306.5 ng/L compared with before the cold air exposure, respectively) 1-day after the cold exposure. This showed that cold air can cause damage to patients' heart cells, and the damage cannot be rapidly repaired. Some of the responses related to the biochemical markers indicated that cold exposure increased cardiovascular strain and possible myocardial injury. © 2014 by the authors; licensee MDPI, Basel, Switzerland.


Luo B.,Nanjing University of Information Science and Technology | Luo B.,Lanzhou Institute of Arid Meteorology | Zhang S.,Lanzhou Institute of Arid Meteorology | Ma S.,Nanjing University of Information Science and Technology | And 2 more authors.
International Journal of Environmental Research and Public Health | Year: 2012

The purpose of this study is to explore possible potential implications of cold air in cardiovascular disease (CVD) risk in rats. Healthy Wistar rats were exposed to artificial cold air under laboratory conditions, and their systolic blood pressure, heart rate, vasoconstriction, CVD risk factors, and myocardial damage indicators after cold air exposure were determined and evaluated. Systolic blood pressure, whole blood viscosity, and plasma level of norepinephrine, angiotensin II, low density lipoprotein, total cholesterol, and fibrinogen in treatment groups increased significantly compared with control groups. No significant variations were found in plasma Mb and cTnT and myocardial tissue between the treatment and control groups. Results indicate that: (1) higher levels of SBP, WBV and LDL/HDL, total cholesterol (TC), and FG in blood may indicate higher CVD risks during cold air exposure; (2) cold air may exert continuous impacts on SBP and other CVD risk factors. © 2012 by the authors; licensee MDPI, Basel, Switzerland.


Luo B.,Nanjing University of Information Science and Technology | Luo B.,Lanzhou Institute of Arid Meteorology | Zhang S.,Lanzhou Institute of Arid Meteorology | Ma S.,Nanjing University of Information Science and Technology | And 2 more authors.
International Journal of Biometeorology | Year: 2014

Ten-week-old male Wistar rats (systolic blood pressure, 106-116 mmHg; body weight, 300-320 g) and spontaneously hypertensive rats (systolic blood pressure, 160-176 mmHg; body weight, 210.9-244.9 g) were used as healthy and hypertensive subjects to determine the effects of varying degrees of cold-air exposure in a climate chamber box. The three cold-air ranks were cold air I [minimum temperature (TMIN) 6.4 °C, ↓{increment}T48 8.6 °C], cold air II (TMIN 3.8 °C, ↓{increment}T48 11.2 °C), and cold air III (TMIN -0.3 °C, ↓{increment}T48 15.3 °C), as established from the cold-air data of Zhangye City, China. Each cold-air rank consisted of a temperature drop and a temperature increase with the same initial and terminal temperatures (15 °C). After cold-air exposure, the risk factors for cardiovascular disease (CVD) such as systolic blood pressure, whole blood viscosity (10/s and 150/s), plasma fibrinogen, and blood lipids of the rats were determined. The results indicated that the CVD risk factors of the healthy and hypertensive rats increased significantly with cold-air exposure intensities. The increase in systolic blood pressure was greater during temperature drops, whereas the increases in whole blood viscosity and plasma fibrinogen were greater after cold-air exposure. The effects of cold-air exposure on the CVD risk factors of healthy rats, particularly the systolic blood pressure, whole blood viscosity (150/s), and LDL/HDL, were greater than those in hypertensive rats. In conclusion, CVD risk may increase with cold-air ranks. Blood pressure-induced CVD risk may be greater during cold-air temperature drop, whereas atherosclerosis-induced CVD risk may be greater after cold-air exposure. The effect of cold air on the CVD risk factors in healthy subjects may be more significant than those in hypertensive subjects. © 2013 ISB.


Wang J.,CAS Lanzhou Cold and Arid Regions Environmental and Engineering Research Institute | Wang J.,Lanzhou Institute of Arid Meteorology | Li X.,CAS Lanzhou Cold and Arid Regions Environmental and Engineering Research Institute | Lu L.,CAS Lanzhou Cold and Arid Regions Environmental and Engineering Research Institute | Fang F.,Lanzhou Regional Climate Center
European Journal of Agronomy | Year: 2013

Regional crop yield estimations play important roles in the food security of a society. Crop growth models can simulate the crop growth process and predict crop yields, but significant uncertainties can be derived from the input data, model parameters and model structure, especially when applied at the regional scale. Abundant observational information provides the relative true value of surface conditions, and this information includes those areal data from remote sensors and ground observations. Data fusion technology integrates the advantages of crop growth models and multi-source observations, and it provides an innovative means for making precise regional corn yield estimations. A regional corn yield estimation framework based on two types of observation-model fusion methods is recounted in this paper. First, a 2008 application of the WOrld FOod Studies (WOFOST) growth model to the Yingke Oasis of Gansu province in northwest China suggested this method of simulating corn growth trends and yields, with attention to carbon absorption in particular. Second, this study applied a simulated annealing algorithm to obtain an optimized vector of parameters for the WOFOST model by using local multi-source data. After parameter estimation, the root mean square error (RMSE) of the simulated yield decreased from 1676.00kgha-1 to 4.00kgha-1. Moreover, the correlation coefficients between simulated and observed gross primary production (GPP) from 2009 to 2011 were 0.941, 0.967 and 0.962. Validation showed that a parameter estimation algorithm can reduce parameter uncertainties. Afterwards, the optimized model was used in a sequence data assimilation algorithm together with regional CHRIS leaf area index (LAI) data to incorporate spatial heterogeneity and evaluate model performance in estimating the near future regional corn yields. The general crop growth curve and final yield prediction were adjusted by using a real-time LAI variable update of the WOFOST model in each simulation unit. Numerical experiments on the sequence filter showed that the assimilation process can provide accurate regional estimations of crop growth and final yield on the basis of yield statistics from 50 sample points. The RMSE of the regional yield estimation at 50 sample points was 339.14kgha-1. Finally, by fusing a whole CHRIS-LAI image over the corn planting region of Yingke Oasis, a precise spatial distribution map of the estimated corn yield was obtained. © 2013 Elsevier B.V.


Li Y.,Lanzhou University | Zhou Q.,Lanzhou University | Zhou J.,CAS Lanzhou Cold and Arid Regions Environmental and Engineering Research Institute | Zhang G.,Lanzhou University | And 2 more authors.
Ecological Modelling | Year: 2014

Regional crop yield prediction is a significant component of national food policy making and security assessments. A data assimilation method that combines crop growth models with remotely sensed data has been proven to be the most effective method for regional yield estimates. This paper describes an assimilation method that integrates a time series of leaf area index (LAI) retrieved from ETM+ data and a coupled hydrology-crop growth model which links a crop growth model World Food Study (WOFOST) and a hydrology model HYDRUS-1D for regional maize yield estimates using the ensemble Kalman filter (EnKF). The coupled hydrology-crop growth model was calibrated and validated using field data to ensure that the model accurately simulated associated state variables and maize growing processes. To identify the parameters that most affected model output, an extended Fourier amplitude sensitivity test (EFAST) was applied to the model before calibration. The calibration results indicated that the coupled hydrology-crop growth model accurately simulated maize growth processes for the local cultivation variety tested. The coefficient of variations (CVs) for LAI, total above-ground production (TAGP), dry weight of storage organs (WSO), and evapotranspiration (ET) were 13%, 6.9%, 11% and 20%, respectively. The calibrated growth model was then combined with the regional ETM+ LAI data using a sequential data assimilation algorithm (EnKF) to incorporate spatial heterogeneity in maize growth into the coupled hydrology-crop growth model. The theoretical LAI profile for the near future and the final yield were obtained through the EnKF algorithm for 50 sample plots. The CV of the regional yield estimates for these sample plots was 8.7%. Finally, the maize yield distribution for the Zhangye Oasis was obtained as a case study. In general, this research and associated model could be used to evaluate the impacts of irrigation, fertilizer and field management on crop yield at a regional scale. © 2014.


Zhao F.,Lanzhou Institute of Arid Meteorology | Wang R.,Lanzhou Institute of Arid Meteorology
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2014

The mechanism of the damage process for agricultural drought is very complex, and many factors can affect it. Agricultural drought is the main limiting factor for crop yield in rainfed area. For defining drought occurrence during the crop growth, and predicting crop yield, we used pattern recognition based on meteorological data during growing season and yield data of spring wheat in semi-arid rainfed area in Dingxi, China from 1986 to 2011. Owing to the application of deviation for crop yield from its long-term mean to define agricultural drought, we divided the year pattern into two categories: drought series, and normal series on the basis of 30 percent deviation from the mean wheat yield. The iteration method was then applied in order to find a case wherein the drought could be linearly discriminated from normal category. According to our research, we find the spring wheat yield was affected by various factors. They can be categorized as 1) weather conditions, such as temperature, precipitation; 2) farm management factors and crop variety, such as soil tillage, soil depth, planting density, sowing date, crop protection against pests and diseases, and soil fertility level; 3) soil conditions, such as soil physical properties and soil water content. Measuring or estimating some of these factors was often not feasible, and the influence of some other factors may be considered insignificant or constant in an agrometeorological experimental station. It was therefore weather condition alone that can affect crop yield most significantly. However, it was found that no linear relation existed in any cases based on average temperature and precipitation during the main growing period without taking other factors into a consideration. After rejecting years in which the soil relative water content was more than 55%, we can predict if agricultural drought through establishing a linear equation with two parameters, the average temperature and precipitation during the main growth period for spring wheat. From the research, we also found the best parameter to predict the agricultural drought occurrence and factor that determined spring wheat yield was the precipitation in May. A Predictive Equation for spring wheat yield was also established by the least square method based on the precipitation in May. The predictive equation was simple but useful, and it can forecast spring wheat yield one and half month earlier before wheat harvest. Meanwhile, it should be noted that the predictive equation was established after rejecting the years in which the soil relative water content was more than 55%. We suggested that the agricultural drought differ from meteorological drought. As such, we should use the method much more carefully for quantitative prediction of agricultural drought occurrence and crop yield in future research. ©, 2014, Chinese Society of Agricultural Engineering. All right reserved.


Wang J.,CAS Lanzhou Cold and Arid Regions Environmental and Engineering Research Institute | Wang J.,Lanzhou Institute of Arid Meteorology | Li X.,CAS Lanzhou Cold and Arid Regions Environmental and Engineering Research Institute | Lu L.,CAS Lanzhou Cold and Arid Regions Environmental and Engineering Research Institute | Fang F.,Lanzhou Regional Climate Center
Environmental Modelling and Software | Year: 2013

Sensitivity analysis (SA) has become a basic tool for the understanding, application and development of models. However, in the past, little attention has been paid to the effects of the parameter sample size and parameter variation range on the parameter SA and its temporal properties. In this paper, the corn crop planted in 2008 in the Yingke Oasis of northwest China is simulated based on meteorological observation data for the inputs and statistical data for the parameters. Furthermore, using the extended Fourier Amplitude Sensitivity (EFAST) algorithm, SA is performed on the 47 crop parameters of the WOrld FOod STudies (WOFOST) crop growth models. A deep analysis is conducted, including the effects of the parameter sample size and variation range on the parameter SA, the temporal properties and the multivariable output issues of SA. The results show that sample size highly affects the convergence of the sensitivity indices. Two types of parameter variation ranges are used for the analysis, and the results show that the sensitive parameters of the two parameter spaces are distinctly different. In addition, taking the storage organ biomasses at the different growth stages as the objective output, the time-dependent characteristics of the parameter sensitivity are discussed. The results show that several sensitive parameters exist in the grain biomass throughout the entire development stage. In addition, analyzing the twelve sensitive parameters has proven that although certain parameters have no effect on the final yield, they play key roles in certain growth stages, and the importance of these parameters gradually increases. Finally, the sensitivity analyses of different state variable outputs are performed, including the biomass, yield, leaf area index, and transpiration coefficient. The results suggest that the sensitive parameters of various variable processes differ. This study highlights the importance of considering multiple characteristics of the model parameters and the responses of the models in specific phenological stages. © 2013 Elsevier Ltd.


Ren F.,Laboratory for Climate Studies | Cui D.,Laboratory for Climate Studies | Cui D.,Lanzhou University | Gong Z.,Laboratory for Climate Studies | And 5 more authors.
Journal of Climate | Year: 2012

An extreme weather and climate event does not only mean that an extreme occurs at an individual point (station), but more generally it has a certain impacted area and duration, which means that it is a regional extreme event (REE). How to identify a REE is the basis for studies in this area. An objective identification technique for REE (OITREE), which is based on the model of "the string of candied fruits,"is proposed in this study. This technique consists of five steps: to select a daily index for individual points (stations), to partition natural daily abnormality belts, to distinguish the event's temporal continuity, to establish an index system for regional events, and to judge extremity for regional events. In the index system developed specially for regional events, there are five single indices, namely extreme intensity, accumulated intensity, accumulated area, maximum impacted area and duration, as well as an integrated index and the spatial location. In this study, the proposed method was first applied to examine four types of REEs in China: heavy precipitation, drought, high temperature, and low temperature. Results show that the technique is skillful in identifying REEs, demonstrating the usefulness of the proposed method in detecting and studying of REEs and operational application. © 2012 American Meteorological Society.


Zhang Q.,Lanzhou Institute of Arid Meteorology | Zhang J.,Nanjing University | Qiao J.,Meteorological Bureau of Xian City | Wang S.,Lanzhou Institute of Arid Meteorology | Wang S.,Lanzhou University
Science China Earth Sciences | Year: 2011

The atmospheric boundary layer (ABL) is an important physical characteristic of the Earth's atmosphere. Compared with the typical ABL, the ABL in arid regions has distinct features and is formed by particular mechanisms. In this paper, the depth of the diurnal and nocturnal ABLs and their related thermodynamic features of land surface processes, including net radiation, the ground-air temperature difference and sensible heat flux, under typical summer and winter conditions are discussed on the basis of comprehensive observations of the ABL and thermodynamic processes at the land surface carried out in the extreme arid zone of Dunhuang. The relationships of the ABL depth in the development and maintenance stages with these thermodynamic features are also investigated. The results show that the depth of the ABL is closely correlated with the thermodynamic features in both development and maintenance stages and more energy is consumed in the development stage. Further analysis indicates that wind velocity also affects ABL development, especially the development of a stable boundary layer in winter. Taken together, the analysis results indicate that extremely strong thermodynamic processes at the land surface are the main driving factor for the formation of a deep ABL in an arid region. © 2011 Science China Press and Springer-Verlag Berlin Heidelberg.

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