A new bias-correction method for precipitation over complex terrain suitable for different climate states: a case study using WRF (version 3.8.1)

Abstract

Abstract. This work presents a new bias-correction method for precipitation over complex terrain that explicitly considers orographic characteristics. This consideration offers a good alternative to the standard empirical quantile mapping (EQM) method during colder climate states in which the orography strongly deviates from the present-day state, e.g. during glacial conditions such as the Last Glacial Maximum (LGM). Such a method is needed in the event that absolute precipitation fields are used, e.g. as input for glacier modelling or to assess potential human occupation and according migration routes in past climate states. The new bias correction and its performance are presented for Switzerland using regional climate model simulations at 2 km resolution driven by global climate model outputs obtained under perpetual 1990 and LGM conditions. Comparing the present-day regional climate model simulation with observations, we find a strong seasonality and, especially during colder months, a height dependence of the bias in precipitation. Thus, we suggest a three-step correction method consisting of (i) a separation into different orographic characteristics, (ii) correction of very low intensity precipitation, and (iii) the application of an EQM, which is applied to each month separately. We find that separating the orography into 400 m height intervals provides the overall most reasonable correction of the biases in precipitation. The new method is able to fully correct the seasonal precipitation bias induced by the global climate model. At the same time, some regional biases remain, in particular positive biases over high elevated areas in winter and negative biases in deep valleys and Ticino in winter and summer. A rigorous temporal and spatial cross-validation with independent data exhibits robust results. The new bias-correction method certainly leaves some drawbacks under present-day conditions. However, the application to the LGM demonstrates that it is a more appropriate correction compared to the standard EQM under highly different climate conditions as the latter imprints present-day orographic features into the LGM climate.