High‐resolution precipitation downscaling in mountainous areas over China: development and application of a statistical mapping approach

Abstract

High-resolution precipitation distributions in mountainous areas are important for hydrological and ecological assessments, especially in regions with few weather stations. In this study, we proposed an improved model for precipitation downscaling by adding two new parameters, i.e. the maximum precipitation increment direction and the prevailing precipitation direction, which represent the impacts of elevation and the sources of precipitation, respectively. The model parameterization is based on observations made at meteorological stations, terrain factors (e.g. elevation, aspect, and slope), and the new parameters. To evaluate the model, we used six sub-models, each of which considers different influencing factors, to estimate the precipitation distribution and compare their estimation errors. Based on the mean absolute error (MAE) and the root-mean-square error (RMSE) at the validation stations, we found that the sixth sub-model, which includes all the influencing factors, clearly ranks above the others in terms of precipitation downscaling. The monthly MAE and the RMSE of our downscaled precipitation range from 2.2 to 16.1 mm and from 3.4 to 22.7 mm, respectively, indicating more accurate estimation than the raw tropical precipitation measuring mission (TRMM) products (monthly MAE: 3.6-22.0 mm; monthly RMSE: 5.1-28.6%). Our results also show that the sixth sub-model performs better than the Auto-Searched Orographic and Atmospheric Effects Detrended Kriging model (ASOADeK model or Guan's model) due to the inclusion of the elevation and the sources of precipitation. Based on the sixth sub-model and the TRMM 3B43 products, we developed the monthly precipitation products in China from 2000 to 2007 at a spatial resolution of 1 km. Our improved approach to precipitation downscaling could be used for regions where the precipitation distribution is greatly affected by the terrain and few observations are available for estimating the precipitation distribution.

Climatology of Orographic Precipitation Gradients in the Contiguous Western United States

“…Others have used more complex combinations of precipitation observations and terrain features to determine typical precipitation distributions on daily, monthly, annual, and climatological time scales, such as those from the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) Climate Group. These gridded analyses for weather and climate variables have been useful to downscale numerical weather model output or climate model output to produce finescale products based on climatological distributions of meteorological variables (Daly et al 1994(Daly et al , 2008Praskievicz 2017;Wang et al 2017;Zhu et al 2017;Lewis et al 2017). High-resolution, gridded precipitation analyses are useful for validating weather/climate models and developing improved analyses but varying gridded analyses show large differences in precipitation amounts and distributions, especially in complex terrain of the western United States (Henn et al 2018).…”

A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property

“…For example, outputs of the climate model can be downscaled again using the proposed method. Applying the statistical downscaling method to the outputs of the climate models is a popular approach to obtain data with fine temporal and spatial resolutions in the climate change field [5,[64][65][66][67]. Additionally, the proposed method can be employed to remote wind speed observations such as QuikSCAT and OSCAT.…”

High-Resolution Precipitation Modeling in Complex Terrains Using Hybrid Interpolation Techniques: Incorporating Physiographic and MODIS Cloud Cover Influences

“…The independent factors were chosen from the most frequently referenced geo-climatic parameters in the literature [83,84], considering their availability and relationships with precipitation in the study. Elevation (Elv.)…”