The increasing volume of data in the area of environmental sciences needs analysis and interpretation. Among the challenges generated by this “data deluge”, the development of efficient strategies for the knowledge ...The increasing volume of data in the area of environmental sciences needs analysis and interpretation. Among the challenges generated by this “data deluge”, the development of efficient strategies for the knowledge discovery is an important issue. Here, statistical and tools from computational intelligence are applied to analyze large data sets from meteorology and climate sciences. Our approach allows a geographical mapping of the statistical property to be easily interpreted by meteorologists. Our data analysis comprises two main steps of knowledge extraction, applied successively in order to reduce the complexity from the original data set. The goal is to identify a much smaller subset of climatic variables that might still be able to describe or even predict the probability of occurrence of an extreme event. The first step applies a class comparison technique: p-value estimation. The second step consists of a decision tree (DT) configured from the data available and the p-value analysis. The DT is used as a predictive model, identifying the most statistically significant climate variables of the precipitation intensity. The methodology is employed to the study the climatic causes of an extreme precipitation events occurred in Alagoas and Pernambuco States (Brazil) at June/2010.展开更多
Two-dimensional tidal open boundary conditions of the M2 constituent in the Bohai and Yellow Seas(BYS) have been estimated by assimilating T/P altimeter data.During inversion,independent point(IP) strategy was used,in...Two-dimensional tidal open boundary conditions of the M2 constituent in the Bohai and Yellow Seas(BYS) have been estimated by assimilating T/P altimeter data.During inversion,independent point(IP) strategy was used,in which several IPs on the open boundary is assumed,values at these IPs can be optimized with an adjoint method,and those at other grid points are determined by linearly interpolating the values at IPs.The reasonability and feasibility of the model are tested by ideal twin experiments.In the practical experiment(PE) after assimilation,the cost function may reach 1% or less of its initial value.Mean absolute errors in amplitude and phase can be less than 5 cm and 5°,respectively,and the obtained co-chart can show the character of the M2 constituent in the BYS.The results of the PE indicate that using only two IPs on the open boundary can yield better simulated results.展开更多
The sea level derived from TOPEX/Poseidon （T/P） altimetry data shows prominent long term trend and inter-annual variability. The global mean sea level rising rate during 1993-2003 was 2.9mm a^-1. The T/P sea level t...The sea level derived from TOPEX/Poseidon （T/P） altimetry data shows prominent long term trend and inter-annual variability. The global mean sea level rising rate during 1993-2003 was 2.9mm a^-1. The T/P sea level trend maps the geographical variability. In the Northern Hemisphere （15°-64°N）, the sea level rise is very fast at the mid-latitude （20°-40°N） but much slower at the high-latitude, for example, only 0.5 mm a^-1 in the latitude band 40°-50°N. In the Southern Hemisphere, the sea level shows high rising rate both in mid-latitude and high-latitude areas, for example, 5.1 mm a^-1 in the band 40°- 50°S. The global thermosteric sea level （TSL） derived from Ishii temperature data was rising during 1993-2003 at a rate of 1.2 mm a^-1 and accounted for more than 40% of the global T/P sea level rise. The contributions of the TSL distribution are not spatially uniform; for instance, the percentage is 67% for the Northern Hemisphere and only 29% for the Southern Hemisphere （15°-64°S） and the maximum thermosteric contribution appears in the Pacific Ocean, which contributes more than 60% of the global TSL. The sea level change trend in tropical ocean is mainly caused by the thermosteric effect, which is different from the case of seasonal variability in this area. The TSL variability dominates the T/P sea level rise in the North Atlantic, but it is small in other areas, and shows negative trend at the high-latitude area （40°-60°N, and 50°-60°S）. The global TSL during 1945-2003 showed obvious rising trend with the rate of about 0.3 mm a-l and striking inter-annual and decadal variability with period of 20 years. In the past 60 years, the Atlantic TSL was rising continuously and remarkably, contributing 38% to the global TSL rising. The TSL in the Pacific and Indian Ocean rose with significant in- ter-annual and decadal variability. The first EOF mode of the global TSL from Ishii temperature data was the ENSO mode in which the time series of the first mode showed steady rising trend. Among the three oceans, the first mode of the Pacific TSL presented the ENSO mode; there was relatively steady rising trend in the Atlantic Ocean, and no dominant mode in the Indian Ocean.展开更多
文摘The increasing volume of data in the area of environmental sciences needs analysis and interpretation. Among the challenges generated by this “data deluge”, the development of efficient strategies for the knowledge discovery is an important issue. Here, statistical and tools from computational intelligence are applied to analyze large data sets from meteorology and climate sciences. Our approach allows a geographical mapping of the statistical property to be easily interpreted by meteorologists. Our data analysis comprises two main steps of knowledge extraction, applied successively in order to reduce the complexity from the original data set. The goal is to identify a much smaller subset of climatic variables that might still be able to describe or even predict the probability of occurrence of an extreme event. The first step applies a class comparison technique: p-value estimation. The second step consists of a decision tree (DT) configured from the data available and the p-value analysis. The DT is used as a predictive model, identifying the most statistically significant climate variables of the precipitation intensity. The methodology is employed to the study the climatic causes of an extreme precipitation events occurred in Alagoas and Pernambuco States (Brazil) at June/2010.
基金Supported by the State Ministry of Science and Technology of China (Nos.2007AA09Z118,2008AA09A402)the National Natural Science Foundation of China(No.41076006)the Ministry of Education's 111 Project(No.B07036)
文摘Two-dimensional tidal open boundary conditions of the M2 constituent in the Bohai and Yellow Seas(BYS) have been estimated by assimilating T/P altimeter data.During inversion,independent point(IP) strategy was used,in which several IPs on the open boundary is assumed,values at these IPs can be optimized with an adjoint method,and those at other grid points are determined by linearly interpolating the values at IPs.The reasonability and feasibility of the model are tested by ideal twin experiments.In the practical experiment(PE) after assimilation,the cost function may reach 1% or less of its initial value.Mean absolute errors in amplitude and phase can be less than 5 cm and 5°,respectively,and the obtained co-chart can show the character of the M2 constituent in the BYS.The results of the PE indicate that using only two IPs on the open boundary can yield better simulated results.
基金supported by the National Basic Research Program of China (No 2007CB411807)the NSFC project (Nos 40976006 and 40906002)+1 种基金the National Key Technology R&D Program (No 2007BAC03A06-06)the project of Key Laboratory of Coastal Disasters and Defence (No 200802)
文摘The sea level derived from TOPEX/Poseidon （T/P） altimetry data shows prominent long term trend and inter-annual variability. The global mean sea level rising rate during 1993-2003 was 2.9mm a^-1. The T/P sea level trend maps the geographical variability. In the Northern Hemisphere （15°-64°N）, the sea level rise is very fast at the mid-latitude （20°-40°N） but much slower at the high-latitude, for example, only 0.5 mm a^-1 in the latitude band 40°-50°N. In the Southern Hemisphere, the sea level shows high rising rate both in mid-latitude and high-latitude areas, for example, 5.1 mm a^-1 in the band 40°- 50°S. The global thermosteric sea level （TSL） derived from Ishii temperature data was rising during 1993-2003 at a rate of 1.2 mm a^-1 and accounted for more than 40% of the global T/P sea level rise. The contributions of the TSL distribution are not spatially uniform; for instance, the percentage is 67% for the Northern Hemisphere and only 29% for the Southern Hemisphere （15°-64°S） and the maximum thermosteric contribution appears in the Pacific Ocean, which contributes more than 60% of the global TSL. The sea level change trend in tropical ocean is mainly caused by the thermosteric effect, which is different from the case of seasonal variability in this area. The TSL variability dominates the T/P sea level rise in the North Atlantic, but it is small in other areas, and shows negative trend at the high-latitude area （40°-60°N, and 50°-60°S）. The global TSL during 1945-2003 showed obvious rising trend with the rate of about 0.3 mm a-l and striking inter-annual and decadal variability with period of 20 years. In the past 60 years, the Atlantic TSL was rising continuously and remarkably, contributing 38% to the global TSL rising. The TSL in the Pacific and Indian Ocean rose with significant in- ter-annual and decadal variability. The first EOF mode of the global TSL from Ishii temperature data was the ENSO mode in which the time series of the first mode showed steady rising trend. Among the three oceans, the first mode of the Pacific TSL presented the ENSO mode; there was relatively steady rising trend in the Atlantic Ocean, and no dominant mode in the Indian Ocean.
