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A fundamental theorem for eco-environmental surface modelling and its applications
- Source :
- Science China Earth Sciences. 63:1092-1112
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- We propose a fundamental theorem for eco-environmental surface modelling (FTEEM) in order to apply it into the fields of ecology and environmental science more easily after the fundamental theorem for Earth’s surface system modeling (FTESM). The Beijing-Tianjin-Hebei (BTH) region is taken as a case area to conduct empirical studies of algorithms for spatial upscaling, spatial downscaling, spatial interpolation, data fusion and model-data assimilation, which are based on high accuracy surface modelling (HASM), corresponding with corollaries of FTEEM. The case studies demonstrate how eco-environmental surface modelling is substantially improved when both extrinsic and intrinsic information are used along with an appropriate method of HASM. Compared with classic algorithms, the HASM-based algorithm for spatial upscaling reduced the root-mean-square error of the BTH elevation surface by 9 m. The HASM-based algorithm for spatial downscaling reduced the relative error of future scenarios of annual mean temperature by 16%. The HASM-based algorithm for spatial interpolation reduced the relative error of change trend of annual mean precipitation by 0.2%. The HASM-based algorithm for data fusion reduced the relative error of change trend of annual mean temperature by 70%. The HASM-based algorithm for model-data assimilation reduced the relative error of carbon stocks by 40%. We propose five theoretical challenges and three application problems of HASM that need to be addressed to improve FTEEM.
- Subjects :
- 010504 meteorology & atmospheric sciences
Fundamental theorem
Elevation
Systems modeling
010502 geochemistry & geophysics
Sensor fusion
01 natural sciences
Multivariate interpolation
Approximation error
General Earth and Planetary Sciences
Mean radiant temperature
Algorithm
0105 earth and related environmental sciences
Downscaling
Subjects
Details
- ISSN :
- 18691897 and 16747313
- Volume :
- 63
- Database :
- OpenAIRE
- Journal :
- Science China Earth Sciences
- Accession number :
- edsair.doi...........4ab7b756bf8c3a0b10ef4d2a93af6dfa