Within the context of global change, marine sensitive factors or Marine Essential Climate Variables have been defined by many projects, and their sensitive spatial regions and time phases play significant roles in reg...Within the context of global change, marine sensitive factors or Marine Essential Climate Variables have been defined by many projects, and their sensitive spatial regions and time phases play significant roles in regional sea-air interactions and better understanding of their dynamic process. In this paper, we propose a cluster-based method for marine sensitive region extraction and representation. This method includes a kernel expansion algorithm for extracting marine sensitive regions, and a field-object triple form, integration of object-oriented and field-based model, for representing marine sensitive objects. Firstly, this method recognizes ENSO-related spatial patterns using empirical orthogonal decomposition of long term marine sensitive factors and correlation analysis with multiple ENSO index. The cluster kernel, defined by statistics of spatial patterns, is initialized to carry out spatial expansion and cluster mergence with spatial neighborhoods recursively, then all the related lattices with similar behavior are merged into marine sensitive regions. After this, the Field-object triple form of < O, A, F > is used to represent the marine sensitive objects, both with the discrete object with a precise extend and boundary, and the continuous field with variations dependent on spatial locations. Finally, the marine sensitive objects about sea surface temperature are extracted, represented and analyzed as a case of study, which proves the effectiveness and the efficiency of the proposed method.展开更多
To achieve high parallel efficiency for the global MASNUM surface wave model, the algorithm of an irregular quasirectangular domain decomposition and related serializing of calculating points and data exchanging schem...To achieve high parallel efficiency for the global MASNUM surface wave model, the algorithm of an irregular quasirectangular domain decomposition and related serializing of calculating points and data exchanging schemes are developed and conducted, based on the environment of Message Passing Interface(MPI). The new parallel version of the surface wave model is tested for parallel computing on the platform of the Sunway BlueLight supercomputer in the National Supercomputing Center in Jinan. The testing involves four horizontal resolutions, which are 1°×1°,(1/2)°×(1/2)°,(1/4)°×(1/4)°, and(1/8)°×(1/8)°. These tests are performed without data Input/Output(IO) and the maximum amount of processors used in these tests reaches to 131072. The testing results show that the computing speeds of the model with different resolutions are all increased with the increasing of numbers of processors. When the number of processors is four times that of the base processor number, the parallel efficiencies of all resolutions are greater than 80%. When the number of processors is eight times that of the base processor number, the parallel efficiency of tests with resolutions of 1°×1°,(1/2)°×(1/2)° and(1/4)°×(1/4)° is greater than 80%, and it is 62% for the test with a resolution of(1/8)°×(1/8)° using 131072 processors, which is the nearly all processors of Sunway BlueLight. When the processor's number is 24 times that of the base processor number, the parallel efficiencies for tests with resolutions of 1°×1°,(1/2)°×(1/2)°, and(1/4)°×(1/4)° are 72%, 62%, and 38%, respectively. The speedup and parallel efficiency indicate that the irregular quasi-rectangular domain decomposition and serialization schemes lead to high parallel efficiency and good scalability for a global numerical wave model.展开更多
基金supported by the director projects of Centre for Earth Observation and Digital Earth(CEODE)(Nos.Y2ZZ06101B and Y2ZZ18101B)the State Key Laboratory of Resources and Environmental Information System project+1 种基金the National Natural Science Foundation of China(project No.41371385)the National High Technology Research and Development Program of China(project No.2012AA12A403-5)
文摘Within the context of global change, marine sensitive factors or Marine Essential Climate Variables have been defined by many projects, and their sensitive spatial regions and time phases play significant roles in regional sea-air interactions and better understanding of their dynamic process. In this paper, we propose a cluster-based method for marine sensitive region extraction and representation. This method includes a kernel expansion algorithm for extracting marine sensitive regions, and a field-object triple form, integration of object-oriented and field-based model, for representing marine sensitive objects. Firstly, this method recognizes ENSO-related spatial patterns using empirical orthogonal decomposition of long term marine sensitive factors and correlation analysis with multiple ENSO index. The cluster kernel, defined by statistics of spatial patterns, is initialized to carry out spatial expansion and cluster mergence with spatial neighborhoods recursively, then all the related lattices with similar behavior are merged into marine sensitive regions. After this, the Field-object triple form of < O, A, F > is used to represent the marine sensitive objects, both with the discrete object with a precise extend and boundary, and the continuous field with variations dependent on spatial locations. Finally, the marine sensitive objects about sea surface temperature are extracted, represented and analyzed as a case of study, which proves the effectiveness and the efficiency of the proposed method.
基金supported by National Basic Research Program of China (Grant Nos. 2010CB950300, 2010CB950500)Public Science and Technology Research Funds Projects of Ocean (Grant No. 201105019)+1 种基金Key Supercomputing Science-Technology Project of Shandong Province of China (Grant No. 2011YD01107)Scientific Research Foundation of the First Institute of Oceanography, State Oceanic Administration (Grant No. GY02-2010G22)
文摘To achieve high parallel efficiency for the global MASNUM surface wave model, the algorithm of an irregular quasirectangular domain decomposition and related serializing of calculating points and data exchanging schemes are developed and conducted, based on the environment of Message Passing Interface(MPI). The new parallel version of the surface wave model is tested for parallel computing on the platform of the Sunway BlueLight supercomputer in the National Supercomputing Center in Jinan. The testing involves four horizontal resolutions, which are 1°×1°,(1/2)°×(1/2)°,(1/4)°×(1/4)°, and(1/8)°×(1/8)°. These tests are performed without data Input/Output(IO) and the maximum amount of processors used in these tests reaches to 131072. The testing results show that the computing speeds of the model with different resolutions are all increased with the increasing of numbers of processors. When the number of processors is four times that of the base processor number, the parallel efficiencies of all resolutions are greater than 80%. When the number of processors is eight times that of the base processor number, the parallel efficiency of tests with resolutions of 1°×1°,(1/2)°×(1/2)° and(1/4)°×(1/4)° is greater than 80%, and it is 62% for the test with a resolution of(1/8)°×(1/8)° using 131072 processors, which is the nearly all processors of Sunway BlueLight. When the processor's number is 24 times that of the base processor number, the parallel efficiencies for tests with resolutions of 1°×1°,(1/2)°×(1/2)°, and(1/4)°×(1/4)° are 72%, 62%, and 38%, respectively. The speedup and parallel efficiency indicate that the irregular quasi-rectangular domain decomposition and serialization schemes lead to high parallel efficiency and good scalability for a global numerical wave model.
