Large-scale atmospheric forcing and topographic modification of precipitation rates over High Asia – a neural-network-based approach

Abstract

Abstract. The heterogeneity of precipitation rates in high-mountain regions is not sufficiently captured by stateof-the-art climate reanalysis products due to their limited spatial resolution. Thus there exists a large gap between the available data sets and the demands of climate impact studies. The presented approach aims to generate spatially high resolution precipitation fields for a target area in central Asia, covering the Tibetan Plateau and the adjacent mountain ranges and lowlands. Based on the assumption that observed local-scale precipitation amounts are triggered by varying large-scale atmospheric situations and modified by local-scale topographic characteristics, the statistical downscaling approach estimates local-scale precipitation rates as a function of large-scale atmospheric conditions, derived from the ERA-Interim reanalysis and high-resolution terrain parameters. Since the relationships of the predictor variables with local-scale observations are rather unknown and highly nonlinear, an artificial neural network (ANN) was utilized for the development of adequate transfer functions. Different ANN architectures were evaluated with regard to their predictive performance.The final downscaling model was used for the cellwise estimation of monthly precipitation sums, the number of rainy days and the maximum daily precipitation amount with a spatial resolution of 1 km 2 . The model was found to sufficiently capture the temporal and spatial variations in precipitation rates in the highly structured target area and allows for a detailed analysis of the precipitation distribution. A concluding sensitivity analysis of the ANN model reveals the effect of the atmospheric and topographic predictor variables on the precipitation estimations in the climatically diverse subregions.

Quantifying the added value of convection-permitting climate simulations in complex terrain: a systematic evaluation of WRF over the Himalayas

“…The river valleys between these two zones are found to be relatively drier. Such a pattern is in agreement with the station observations , satellite-derived observed estimates (Bookhagen and Burbank, 2006;Shrestha et al, 2012), and simulations (Maussion et al, 2014;Gerlitz et al, 2015). Unlike D2, D1 fails to capture such a spatial pattern, primarily due to the poor representation of topography, as topography, which plays an important role in developing localized convective activity and orographic precipitation, is not represented well on a coarser grid scale.…”

“…It is worth mentioning that (sub)-kilometer-scale simulations for larger areas are computationally very expensive; however, as mentioned earlier, slightly coarser (but still convection-permitting) WRF simulations (with 5 km spatial resolution) capture the essential features of precipitation and temperature over the complex target area. A modeling chain, including dynamical downscaling of climate model results and subsequent statistical downscaling and terrain parameterization approaches (as proposed in Gerlitz et al, 2015) to kilometer and sub-kilometer-scale, might be a feasible option for the region. The main findings of this study are summarized as follows.…”

A statistically based seasonal precipitation forecast model with automatic predictor selection and its application to central and south Asia

“…Mariotti (2007) showed that during winter season, a northward current over the Arabian countries transports tropical air masses into central Asia, which represents an important moisture source for the westerly air masses. While the continental central Asian countries remain under influence of extratropical westerly air masses throughout the year, the tropical monsoon circulation is established over south Asia during the summer season (Bohner, 2006;Bookhagen and Burbank, 2006;Gerlitz et al, 2015). Due to a declining strength of the monsoonal moisture fluxes towards west, a clear gradient of precipitation totals from east to west has been detected (Bohner, 2006;Wulf et al, 2010).…”

“…During the boreal cold season, the entire region is influenced by westerly circulation patterns and precipitation is mainly associated with midlatitude disturbances originating over the Atlantic Ocean and the Mediterranean (Bohner, 2006;Bothe et al, 2011;Gerlitz et al, 2015;Maussion et al, 2014). Since the track of westerly disturbances is mainly determined by the position of the 200 hPa westerly jet stream at the polar frontal zone, a seasonal cycle of precipitation is distinctly defined.…”

“…Since the track of westerly disturbances is mainly determined by the position of the 200 hPa westerly jet stream at the polar frontal zone, a seasonal cycle of precipitation is distinctly defined. Particularly, the western parts of the Himalayas receive a considerable amount of winter precipitation associated with the uplift of westerly air masses, which reaches up to 60 % of the annual precipitation total (Bohner, 2006;Gerlitz et al, 2015;Wulf et al, 2010). During spring, the zone of westerly precipitation migrates towards north, reaches the Hindu Kush region and the Pamir in March and continues to the Tien Shan region in May.…”