Evaluation of radar and automatic weather station data assimilation for a heavy rainfall event in southern China

To improve the accuracy of short-term(0–12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System(HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting(WRF-ARW)model and the Advanced Regional Prediction System(ARPS) three-dimensional variational data assimilation(3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station(AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting(QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6–9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score(FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.     

Development and validation of an evaporation duct model. Part II: Evaluation and improvement of stability functions

This study aims to validate and improve the universal evaporation duct (UED) model through a further analysis of the stability function (ψ). A large number of hydrometeorological observations obtained from a tower platform near Xisha Island of the South China Sea are employed, together with the latest variations in ψ function. Applicability of different ψ functions for specific sea areas and stratification conditions is investigated based on three objective criteria. The results show that, under unstable conditions, ψ function of Fairall et al. (1996) (i.e., Fairall96, similar for abbreviations of other function names) in general offers the best performance. However, strictly speaking, this holds true only for the stability (represented by bulk Richardson number R _iB) range ?2.6 ? R _iB < ?0.1; when conditions become weakly unstable (?0.1 ? R _iB < ?0.01), Fairall96 offers the second best performance after Hu and Zhang (1992) (HYQ92). Conversely, for near-neutral but slightly unstable conditions (?0.01 ? R _iB < 0.0), the effects of Edson04, Fairall03, Grachev00, and Fairall96 are similar, with Edson04 being the best function but offering only a weak advantage. Under stable conditions, HYQ92 is the optimal and offers a pronounced advantage, followed by the newly introduced SHEBA07 (by Grachev et al., 2007) function. Accordingly, the most favorable functions, i.e., Fairall96 and HYQ92, are incorporated into the UED model to obtain an improved version of the model. With the new functions, the mean root-mean-square (rms) errors of the modified refractivity (M), 0–5-m M slope, 5–40-m M slope, and the rms errors of evaporation duct height (EDH) are reduced by 21.65%, 9.12%, 38.79%, and 59.06%, respectively, compared to the classical Naval Postgraduate School model.

     

A brief introduction to BNU-HESM1.0 and its earth surface temperature simulations

Integrated assessment models and coupled earth system models both have their limitations in understanding the interactions between human activity and the physical earth system. In this paper,a new human–earth system model,BNUHESM1.0,constructed by combining the economic and climate damage components of the Dynamic Integrated Model of Climate Change and Economy to the BNU-ESM model,is introduced. The ability of BNU-HESM1.0 in simulating the global CO2 concentration and surface temperature is also evaluated. We find that,compared to observation,BNU-HESM1.0underestimates the global CO2 concentration and its rising trend during 1965–2005,due to the uncertainty in the economic components. However,the surface temperature simulated by BNU-HESM1.0 is much closer to observation,resulting from the overestimates of surface temperature by the original BNU-ESM model. The uncertainty of BNU-ESM falls within the range of present earth system uncertainty,so it is the economic and climate damage component of BNU-HESM1.0 that needs to be improved through further study. However,the main purpose of this paper is to introduce a new approach to investigate the complex relationship between human activity and the earth system. It is hoped that it will inspire further ideas that prove valuable in guiding human activities appropriate for a sustainable future climate.     

ERA-Interim地表温度资料在青藏高原多年冻土区的适用性

地表温度综合反映了大气和地表植被、土壤等局地因素相互作用的能量交换状况,是许多冻土分布模型和寒区陆面过程模式的上边界条件,对多年冻土分布和活动层厚度估算具有重要意义。为了检验ERA-Interim再分析地表温度资料在青藏高原(下称高原)多年冻土区的适用性,综合比较了2011年1月1日至2012年12月31日期间高原不同类型多年冻土区3个综合观测场的观测地表温度和ERA-Interim再分析资料之间的偏差、均方差、相关系数、解释方差、均方根误差和平均绝对误差。结果表明,ERA-Interim再分析资料能较好地再现高原多年冻土区3个综合观测场地表温度的基本特征,并能较好地描述高原地表温度的季节变化。但ERA-Interim再分析年平均地表温度比观测值偏低,西大滩、五道梁和唐古拉站依次偏低1.7,1.0和0.9℃;地表温度的再分析值和观测值之间的相关系数和解释方差都较高,均方差也相近。ERA-Interim再分析地表温度资料对观测站点相对稀少且空间分布不均匀的高原多年冻土区具有较好的适用性,可以作为地表温度的有效代用资料。     

“75·8”持续性强降水事件及其大尺度水汽输送特征

首先研究了河南"75·8"强降水事件的极端异常特征,然后从水汽通量的角度定性分析这次事件的水汽输送特征,最后采用了Hysplit模型定量分析了不同源地的水汽来源对河南"75·8"强降水的贡献率。研究表明,1975年8月5-8日在河南省发生的是一次大范围持续性极端降水过程,事件发生期间区域平均降水程度超过其气候平均值3倍标准差。强降水事件是在中高纬度环流异常和台风共同作用下发生的,贝加尔湖以东阻塞高压和副热带高压合并阻挡了7503号台风北上。定量计算结果进一步表明,河南"75·8"强降水的水汽来源与7503号台风具有十分密切的联系。