Articles | Volume 24, issue 5
Research article
08 May 2020
Research article |  | 08 May 2020

Conditional simulation of surface rainfall fields using modified phase annealing

Jieru Yan, András Bárdossy, Sebastian Hörning, and Tao Tao

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Cited articles

Bárdossy, A. and Hörning, S.: Process-Driven Direction-Dependent Asymmetry: Identification and Quantification of Directional Dependence in Spatial Fields, Math. Geosci., 49, 871–891,, 2017. a, b
Chilès, J. P. and Delfiner, P.: Geostatistics: Modeling Spatial Uncertainty, in: Series In Probability and Statistics, Wiley,, 2012. a, b
Collier, C.: The impact of wind drift on the utility of very high spatial resolution radar data over urban areas, Phys. Chem. Earth Pt. B, 24, 889–893,, 1999. a
Cristiano, E., ten Veldhuis, M.-C., and van de Giesen, N.: Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review, Hydrol. Earth Syst. Sci., 21, 3859–3878,, 2017. a
Deutsch, C. V. and Journel, A. G.: The application of simulated annealing to stochastic reservoir modeling, SPE Adv. Technol. Ser., 2, 222–227,, 1994. a
Short summary
For applications such as flood forecasting of urban- or town-scale distributed hydrological modeling, high-resolution quantitative precipitation estimation (QPE) with enough accuracy is the most important driving factor and thus the focus of this paper. Considering the fact that rain gauges are sparse but accurate and radar-based precipitation estimates are inaccurate but densely distributed, we are merging the two types of data intellectually to obtain accurate QPEs with high resolution.