Conditional simulation of surface rainfall fields using modified phase annealing

Abstract. The accuracy of quantitative precipitation estimation (QPE) over a certain region and period is of vital importance across multiple domains and disciplines. However, due to the intricate tempo-spatial variability and the intermittent nature of precipitation, it is challenging to obtain QPE with adequate accuracy. This paper aims at simulating rainfall fields honoring both the local constraints subject by the point-wise rain-gauge observations and the global constraints subject by the field measurement from weather radar. The employed conditional simulation method is the modified phase annealing (PA), which is practically an evolvement of the traditional simulated annealing (SA). Yet, unlike SA which implements perturbations in the spatial field, PA implements perturbations in the Fourier space, making it superior to SA in many aspects. The modification of PA is reflected in two aspects. First, taking advantage of the global characteristic of PA, the method is only used to deal with global constraints, and the local ones are handed over to residual kriging. Second, except for the system temperature, the number of perturbed phases is also annealed during the simulation process, making the influence of the perturbation more global at initial phases. The impact of the perturbation decreases gradually as the number of the perturbed phases decreases. The proposed method is used to simulate the rainfall field for a 30-min-event using different scenarios: with and without integrating the uncertainty of the radar-indicated rainfall pattern and with different objective functions.