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Xue Yi
,
Deqin Li
,
Chunyu Zhao
,
Lidu Shen
, and
Xiaoyu Zhou

Abstract

High-density surface networks have become available in recent years in a number of regions throughout the world, but their utility in high-resolution dynamic downscaling has not been examined. As an attempt to fill such a gap, a suite of high-resolution (4 km) dynamical downscaling simulations is developed in this study with the Weather Research and Forecasting (WRF) Model and observation nudging over Liaoning in northeastern China. Three experiments, including no nudging (CTL), analysis nudging (AN), and combined analysis nudging and observation nudging with surface observations (AON), are conducted to downscale the CFSv2 reanalysis with the WRF Model for the year 2015. The three 1-yr regional climate simulations were compared with the independent surface observations. The results show that observational nudging can improve the simulation of surface variables, including temperature, wind speed, humidity, and pressure, more than nudging large-scale driving data with AN alone. The two nudging simulations can improve the cold bias for the temperature of the WRF Model. For precipitation, both the simulations with AN and observation nudging can capture the pattern of precipitation; however, with the introduction of small-scale information at the surface, AON cannot further improve the simulation of precipitation.

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Lei Wang
,
Lan Cuo
,
Dongliang Luo
,
Fengge Su
,
Qinghua Ye
,
Tandong Yao
,
Jing Zhou
,
Xiuping Li
,
Ning Li
,
He Sun
,
Lei Liu
,
Yuanwei Wang
,
Tian Zeng
,
Zhidan Hu
,
Ruishun Liu
,
Chenhao Chai
,
Guangpeng Wang
,
Xiaoyang Zhong
,
Xiaoyu Guo
,
Haoqiang Zhao
,
Huabiao Zhao
, and
Wei Yang

Abstract

Upper Brahmaputra (UB) is the largest (∼240,000 km2) river basin of the Tibetan Plateau, where hydrological processes are highly sensitive to climate change. However, constrained by difficult access and sparse in situ observations, the variations in precipitation, glaciers, frozen ground, and vegetation across the UB basin remain largely unknown, and consequently the impacts of climate change on streamflow cannot be accurately assessed. To fill this gap, this project aims to establish a basinwide, large-scale observational network (that includes hydrometeorology, glacier, frozen ground, and vegetation observations), which helps quantify the UB runoff processes under climate–cryosphere–vegetation changes. At present, a multisphere observational network has been established throughout the catchment: 1) 12 stations with custom-built weighing automatic rain/snow meters and temperature probes to obtain elevation-dependent gradients; 2) 9 stations with soil moisture/temperature observations at four layers (10, 40, 80, 120 cm) covering Alpine meadow, grasslands, shrub, and forest to measure vegetation (biomass and vegetation types) and soil (physical properties) simultaneously; 3) 34 sets of probes to monitor frozen ground temperatures from 4,500 to 5,200 m elevation (100-m intervals), and two observation systems to monitor water and heat transfer processes in frozen ground at Xuegela (5,278 m) and Mayoumula (5,256 m) Mountains, for improved mapping of permafrost and active layer characteristics; 4) 5 sets of altimetry discharge observations along ungauged cross sections to supplement existing operational gauges; 5) high-precision glacier boundary and ice-surface elevation observations at Namunani Mountain with differential GPS, to supplement existing glacier observations for validating satellite imagery. This network provides an excellent opportunity to monitor UB catchment processes in great detail.

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