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Abstract: Beijing’s mountainous areas have an important ecological significance because they are ecological conservation and water source protection areas of Beijing. The impact of precipitation on the vegetation coverage of Beijing’s mountainous areas is qualitatively analyzed using multi-temporal Landsat images obtained during the last 20 years. Firstly, the influence of external factors, such as phenology and relative radiometric correction, on the normalized difference vegetation index (NDVI) are removed by the normalization of remote sensing images for different periods. Then, the vegetation coverage is calculated using the method of the dimidiate pixel model. Finally, based on that, the relationship between precipitation in different seasons and change of vegetation coverage is discussed. The results indicate that the mean vegetation coverage has the same change trends with winter and summer precipitation, but an opposite change trend with spring precipitation. The paper provides a theoretical basis and data support for further research on driving models of natural vegetation restoration in Beijing’s mountainous areas. [Copyright &y& Elsevier]

Urban areas demonstrate great influence on precipitation, yet the spatial clustering features of precipitation are still unclear over urban areas. This study quantitatively examines the spatial clustering of precipitation intensity in 130 urban-affected regions over mainland China during 2008-15 using a high-resolution merged precipitation product. Results show that the spatial heterogeneity patterns display diverse distribution and vary with precipitation intensity and urban sizes. Extreme and heavy precipitation has higher spatial heterogeneity than light precipitation over the urban-affected regions of grade 1 cities, and their mean Moran's I are 0.49, 0.47, and 0.37 for the intensity percentiles of ≥95%, 75%-95%, and < 75%, respectively. The urban signatures in the spatial clustering of precipitation extremes are observed in 37 cities (28%),mainly occurring in the Haihe River basin, the Yangtze River basin, and the Pearl River basin. The spatial clustering patterns of precipitation extremes are affected by the local dominant synoptic conditions, such as the heavy storms of convective precipitation in Beijing (Moran's I = 0.47) and the cold frontal system in the Pearl River delta (Moran's I = 0.78), resulting in large regional variability. The role of urban environments for the spatial clustering is more evident in wetter conditions [e.g., relative humidity (RH) > 75% over Beijing and RH > 85% over the Pearl River delta] and warmer conditions (T > 258C over Beijing and T > 288C over the Pearl River delta). This study highlights the urban modification on the spatial clustering of some precipitation extremes, and calls for precautions and adaptation strategies to mitigate the adverse effect of the highly clustered extreme rainfall events. [ABSTRACT FROM AUTHOR]

A time-lagged ensemble method is used to improve 6-15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model, version 2.0.1. The approach averages the deterministic predictions of precipitation from the most recent model run and from earlier runs, all at the same forecast valid time. This lagged average forecast (LAF) method assigns equal weight to each ensemble member and produces a forecast by taking the ensemble mean. Our analyses of the Equitable Threat Score, the Hanssen and Kuipers Score, and the frequency bias indicate that the LAF using five members at time-lagged intervals of 6 h improves 6-15 day forecasts of precipitation frequency above 1 mm d and 5 mm d in many regions of China, and is more effective than the LAF method with selection of the time-lagged interval of 12 or 24 h between ensemble members. In particular, significant improvements are seen over regions where the frequencies of rainfall days are higher than about 40%-50% in the summer season; these regions include northeastern and central to southern China, and the southeastern Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Finescale simulations (with 500-m grid spacing) using the Weather Research and Forecasting Model (WRF) were used to investigate impacts of urban processes and urbanization on a localized, summer, heavy rainfall in Beijing. Evaluation using radar and gauge data shows that this configuration of WRF with three-dimensional variational data assimilation of local weather and GPS precipitable water data can simulate this event generally well. Additional WRF simulations were conducted to test the sensitivity of simulation of this storm to different urban processes and urban land-use scenarios. The results confirm that the city does play an important role in determining storm movement and rainfall amount. Comparison of cases with and without the presence of the city of Beijing with respect to the approaching storm shows that the urban effect seems to lead to the breaking of the squall line into convective cells over the urban area. The change of precipitation amount depends on the degree of urbanization (i.e., the change over time in the extent of Beijing city). Model results show that an early urbanization prior to 1980 decreases the maximum rainfall, whereas further urbanization in Beijing is conducive to bifurcating the path of rainfall. According to sensitivity results with a single-layer urban canopy model, the thermal transport (sensible and latent heating) induced by the presence of an urban area apparently is more important than associated momentum transport, with latent and sensible heating apparently having equally important roles in the modification of simulated precipitation. Urban surfaces tend to cause the rainfall to be more locally concentrated. High-rise urban cores may bifurcate the path of rainfall as well as increase the area percentage of heavy rainfall. [ABSTRACT FROM AUTHOR]