The key zones of returning farmland to forestland and grassland in Ningxia were studied. By using the ＂stepwise revised method＂,the climate productive potential,light and temperature productive potential in the zone...The key zones of returning farmland to forestland and grassland in Ningxia were studied. By using the ＂stepwise revised method＂,the climate productive potential,light and temperature productive potential in the zone in recent 50 years were counted. The light and temperature productive potential of corn in Ningxia irrigated area,the central arid zone and the southern mountain area presented the linear increase trend. But when considered the climate productive potentials of light,temperature and water,the numerical value was very low because of the scarce rainfall,and no agriculture without the irrigation. The light and temperature productive potential,climate productive potential of winter wheat in the central arid zone had no significant trend,but the variation range of climate productive potential was very big. The light and temperature productive potential of winter wheat in the southern mountain area had no significant variation trend,and the climate productive potential presented the weak decline trend. It illustrated that the productive of winter wheat was greatly restricted by the water content. By using the meteorological factor data which were simulated by RegCM3-WOFOST/LINGRA coupled model,the future climate productive potentials of winter wheat in the central south of Ningxia was counted. They both presented the weak increase trend. It illustrated that the climate in Ningxia was favorable to improve the yield of winter wheat after returning farmland to forestland.展开更多
In this study, a method of analogue-based correction of errors(ACE) was introduced to improve El Ni?o-Southern Oscillation(ENSO) prediction produced by climate models. The ACE method is based on the hypothesis that th...In this study, a method of analogue-based correction of errors(ACE) was introduced to improve El Ni?o-Southern Oscillation(ENSO) prediction produced by climate models. The ACE method is based on the hypothesis that the flow-dependent model prediction errors are to some degree similar under analogous historical climate states, and so the historical errors can be used to effectively reduce such flow-dependent errors. With this method, the unknown errors in current ENSO predictions can be empirically estimated by using the known prediction errors which are diagnosed by the same model based on historical analogue states. The authors first propose the basic idea for applying the ACE method to ENSO prediction and then establish an analogue-dynamical ENSO prediction system based on an operational climate prediction model. The authors present some experimental results which clearly show the possibility of correcting the flow-dependent errors in ENSO prediction, and thus the potential of applying the ACE method to operational ENSO prediction based on climate models.展开更多
Mixed integer linear programming （MILP） approach for simultaneous gross error detection and data reconciliation has been proved as an efficient way to adjust process data with material, energy, and other balance con...Mixed integer linear programming （MILP） approach for simultaneous gross error detection and data reconciliation has been proved as an efficient way to adjust process data with material, energy, and other balance constrains. But the efficiency will decrease significantly when this method is applled in a large-scale problem because there are too many binary variables involved. In this article, an improved method is proposed in order to gen- erate gross error candidates with reliability factors before data rectification. Candidates are used in the MILP objec- tive function to improve the efficiency and accuracy by reducing the number of binary variables and giving accurate weights for suspected gross errors candidates. Performance of this improved method is compared and discussed by applying the algorithm in a widely used industrial example.展开更多
The holographic dark energy （HDE） is now an studied extensively in the literature. In the derivation of HDE, interesting candidate of dark energy, which has been the black hole entropy plays an important role. In fa...The holographic dark energy （HDE） is now an studied extensively in the literature. In the derivation of HDE, interesting candidate of dark energy, which has been the black hole entropy plays an important role. In fact, the entropy-area relation can be modified due to loop quantum gravity or other reasons. With the modified entropyarea relation, we propose the so-called ＂entropy-corrected holographic dark energy＂ （ECHDE） in the present work. We consider many aspects of ECHDE and tlnd some interesting results. In addition, we briefly consider the so-called ＂entropy-eorreeted agegraphic dark energy＂ （ECADE）.展开更多
Change in Arctic sea ice extent is one of the indicators of global climate changes. Spatio-temporal change and change patterns can be identified using various methods to facilitate human understanding global climate c...Change in Arctic sea ice extent is one of the indicators of global climate changes. Spatio-temporal change and change patterns can be identified using various methods to facilitate human understanding global climate changes. Three empirical orthogonal function(EOF) techniques are discussed and applied to decades of sea-ice concentration(SIC) dataset in Arctic area for identifying independent patterns. It was found that: 1) discrepancies exist in magnitude and scope for each EOF pattern, however, the first two leading EOFs of variability possess high similarities in structure and shape; 2) Even though there are somewhat differences in amplitude of each PC mode, the first two leading PC modes maintain consistent in overall trend and periodicity; 3) There are significant discrepancies and inconsistencies in the third and fourth leading EOF and PC modes. The accuracies of three techniques are further validated in representing the physical phenomena of SIC anomaly patterns.展开更多
Soil organic carbon (SOC) has great impacts on global warming, land degradation and food security. Classic statistical and geostatistical methods were used to characterize and compare the spatial heterogeneity of SOC ...Soil organic carbon (SOC) has great impacts on global warming, land degradation and food security. Classic statistical and geostatistical methods were used to characterize and compare the spatial heterogeneity of SOC and related factors, such as topography, soil type and land use, in the Liudaogou watershed on the Loess Plateau of North China. SOC concentrations followed a log-normal distribution with an arithmetic and geometric means of 23.4 and 21.3 g kg-1, respectively, were moderately variable (CV = 75.9%), and demonstrated a moderate spatial dependence according to the nugget ratio (34.7%). The experimental variogram of SOC was best-fitted by a spherical model, after the spatial outliers had been detected and subsequently eliminated. Lower SOC concentrations were associated with higher elevations. Warp soils and farmland had the highest SOC concentrations, while aeolian sand soil and shrublands had the lowest SOC values. The geostatistical characteristics of SOC for the different soil and land use types were different. These patterns were closely related to the spatial structure of topography, and soil and land use types.展开更多
基金Supported by the National Natural Science Fund Item (40675071)~~
文摘The key zones of returning farmland to forestland and grassland in Ningxia were studied. By using the ＂stepwise revised method＂,the climate productive potential,light and temperature productive potential in the zone in recent 50 years were counted. The light and temperature productive potential of corn in Ningxia irrigated area,the central arid zone and the southern mountain area presented the linear increase trend. But when considered the climate productive potentials of light,temperature and water,the numerical value was very low because of the scarce rainfall,and no agriculture without the irrigation. The light and temperature productive potential,climate productive potential of winter wheat in the central arid zone had no significant trend,but the variation range of climate productive potential was very big. The light and temperature productive potential of winter wheat in the southern mountain area had no significant variation trend,and the climate productive potential presented the weak decline trend. It illustrated that the productive of winter wheat was greatly restricted by the water content. By using the meteorological factor data which were simulated by RegCM3-WOFOST/LINGRA coupled model,the future climate productive potentials of winter wheat in the central south of Ningxia was counted. They both presented the weak increase trend. It illustrated that the climate in Ningxia was favorable to improve the yield of winter wheat after returning farmland to forestland.
基金supported by the Integration and Application Project for Key Meteorology Techniques in China Meteorological Administration (Grant No. CMAGJ2014M64)the China Meteorological Special Project (Grant No. GYHY2012 06016)the National Basic Research Program of China (973 Program, Grant No. 2010CB950404)
文摘In this study, a method of analogue-based correction of errors(ACE) was introduced to improve El Ni?o-Southern Oscillation(ENSO) prediction produced by climate models. The ACE method is based on the hypothesis that the flow-dependent model prediction errors are to some degree similar under analogous historical climate states, and so the historical errors can be used to effectively reduce such flow-dependent errors. With this method, the unknown errors in current ENSO predictions can be empirically estimated by using the known prediction errors which are diagnosed by the same model based on historical analogue states. The authors first propose the basic idea for applying the ACE method to ENSO prediction and then establish an analogue-dynamical ENSO prediction system based on an operational climate prediction model. The authors present some experimental results which clearly show the possibility of correcting the flow-dependent errors in ENSO prediction, and thus the potential of applying the ACE method to operational ENSO prediction based on climate models.
基金Supported by the National High Technology Research and Development Program of China (2007AA40702 and 2007AA04Z191)
文摘Mixed integer linear programming （MILP） approach for simultaneous gross error detection and data reconciliation has been proved as an efficient way to adjust process data with material, energy, and other balance constrains. But the efficiency will decrease significantly when this method is applled in a large-scale problem because there are too many binary variables involved. In this article, an improved method is proposed in order to gen- erate gross error candidates with reliability factors before data rectification. Candidates are used in the MILP objec- tive function to improve the efficiency and accuracy by reducing the number of binary variables and giving accurate weights for suspected gross errors candidates. Performance of this improved method is compared and discussed by applying the algorithm in a widely used industrial example.
基金Supported by the Excellent Young Scholars Research Fund of Beijing Institute of Technology
文摘The holographic dark energy （HDE） is now an studied extensively in the literature. In the derivation of HDE, interesting candidate of dark energy, which has been the black hole entropy plays an important role. In fact, the entropy-area relation can be modified due to loop quantum gravity or other reasons. With the modified entropyarea relation, we propose the so-called ＂entropy-corrected holographic dark energy＂ （ECHDE） in the present work. We consider many aspects of ECHDE and tlnd some interesting results. In addition, we briefly consider the so-called ＂entropy-eorreeted agegraphic dark energy＂ （ECADE）.
基金Project(41301420)supported by the National Natural Science Foundation of ChinaProject(12JJB005)supported by the Hunan Provincial Natural Science Foundation of China+1 种基金Project(2014VGE03)supported by the Key Lab of Virtual Geographic Environment from Ministry of Education,ChinaProject(LEND2013B04)supported by the NASA Key Laboratory of Land Environment and Disaster Monitoring,USA
文摘Change in Arctic sea ice extent is one of the indicators of global climate changes. Spatio-temporal change and change patterns can be identified using various methods to facilitate human understanding global climate changes. Three empirical orthogonal function(EOF) techniques are discussed and applied to decades of sea-ice concentration(SIC) dataset in Arctic area for identifying independent patterns. It was found that: 1) discrepancies exist in magnitude and scope for each EOF pattern, however, the first two leading EOFs of variability possess high similarities in structure and shape; 2) Even though there are somewhat differences in amplitude of each PC mode, the first two leading PC modes maintain consistent in overall trend and periodicity; 3) There are significant discrepancies and inconsistencies in the third and fourth leading EOF and PC modes. The accuracies of three techniques are further validated in representing the physical phenomena of SIC anomaly patterns.
基金Project supported by the National Key Basic Research Program (973 Program) of China (No.2007CB106803)the National Programs for Science and Technology Development of China (No.2006BAD09B06)the Scientific ResearchInnovation Team Support Program of the Northwest A&F University, China
文摘Soil organic carbon (SOC) has great impacts on global warming, land degradation and food security. Classic statistical and geostatistical methods were used to characterize and compare the spatial heterogeneity of SOC and related factors, such as topography, soil type and land use, in the Liudaogou watershed on the Loess Plateau of North China. SOC concentrations followed a log-normal distribution with an arithmetic and geometric means of 23.4 and 21.3 g kg-1, respectively, were moderately variable (CV = 75.9%), and demonstrated a moderate spatial dependence according to the nugget ratio (34.7%). The experimental variogram of SOC was best-fitted by a spherical model, after the spatial outliers had been detected and subsequently eliminated. Lower SOC concentrations were associated with higher elevations. Warp soils and farmland had the highest SOC concentrations, while aeolian sand soil and shrublands had the lowest SOC values. The geostatistical characteristics of SOC for the different soil and land use types were different. These patterns were closely related to the spatial structure of topography, and soil and land use types.
