Advances in Earth Science ›› 2017, Vol. 32 ›› Issue (10): 1102-1111. doi: 10.11867/j.issn.1001-8166.2017.10.1102

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Study on Precipitation Image Downscaling Based on the Method of Ill-posed Problems Solving

Gen Wang 1, 2( ), Shaoxue Sheng 1, Yong Huang 3, Rong Wu 4, Huilan Liu 1   

  1. 1.Anhui Meteorological Information Centre Anhui Key Laboratody of Atmospheric Science and Satellite Remote Sensing, Hefei 230031, China
    2.The Institute of Atmospheric Environment, China Meteorological Administration, Shenyang 110000, China
    3.Anhui Institute of Meteorological, Hefei 230031, China
    4.Anhui Climate Center, Hefei 230031, China
  • Received:2017-04-05 Revised:2017-08-02 Online:2017-12-20 Published:2017-10-20
  • About author:

    First author:Wang Gen(1983-),male,Taizhou City, Jiangsu Province, Engineer. Research areas include satellite data assimilation, numerical simulation of GRAPES and multi-source data

  • Supported by:
    Project supported by the Natural Science Foundation of Anhui Province“Generalised variational assimilation of AIRS water vapor channel brightness temperature and the application study in severe convective weather in Anhui Province”(No.1708085QD89);The Open Research Fund of Huai River Basin in Meteorological “Study of precipitation data fusion algorithm in Jianghuai Basin based on the ground and satellite observations”(No.HRM201407).

Gen Wang, Shaoxue Sheng, Yong Huang, Rong Wu, Huilan Liu. Study on Precipitation Image Downscaling Based on the Method of Ill-posed Problems Solving[J]. Advances in Earth Science, 2017, 32(10): 1102-1111.

Downscaling of remote sensing precipitation products and the forecasting of circulation model are always the intense interests in hydrology and meteorology. The essence of downscaling is primarily to enhance resolution of observation or simulated rainfall field, and to appropriately increase its details or high frequency characteristics. Precipitation, as the main driving factors of the earth’s hydrologic cycle, not only affects the moisture and heat condition of a certain river basin, but also affects the global water and heat circulation. Based on the properties of rainfall self-similarity structure, the mathematically ill-posed precipitation problem solving method was used in low resolution downscaling precipitation for high resolution reconstruction. When solving the downscaling ill-posed problem, the greedy method of orthogonal matching pursuit was introduced so as to get the best high-resolution estimation in an optimal sense. It is hard to imagine that we might be able to find very similar (in mathematical norms) precipitation patterns over relatively large storm-scales. However, finding similar features over sufficiently small sub-storm scales seems more feasible. Based on the characteristics that small scale organized precipitation features tend to recur across different storm environments, the precipitation of both high and low resolution was obtained by training, which could be used to reconstruct the desired high-resolution precipitation field. Multi-source merged precipitation products were used in this experiment. Given the consideration of incompleteness of merged precipitation dataset, it was firstly interpolated based on the method of Fields of Experts (FoEs), which could solve the problem that common interpolation method could hardly work on the interpolation for dataset where consecutive missing data exists. Secondly, ideal experiments of precipitation products downscaling were carried out, where smooth coupling sampling and resampling operator were adopted respectively. Assessment based on the metrics of fidelity and spatial structural similarity demonstrates that the method used in this paper is feasible.

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