Seasonal Predictions of Summer Precipitation in the Middle-lower Reaches of the Yangtze River with Global and Regional Models Based on NUIST-CFS1.0

Accurate prediction of the summer precipitation over the middle and lower reaches of the Yangtze River(MLYR) is of urgent demand for the local economic and societal development. This study assesses the seasonal forecast skill in predicting summer precipitation over the MLYR region based on the global Climate Forecast System of Nanjing University of Information Science and Technology(NUIST-CFS1.0, previously SINTEX-F). The results show that the model can provide moderate skill in predicting the i...     

基于三种WRF陆面过程方案的东南亚毁林增温响应研究

选取东南亚中南半岛地区作为模拟区域,基于高分辨率的遥感观测森林变化数据和WRF数值模式,设计毁林前后的两种情景对旱季气候进行模拟,评估NoahMP、CLM和Noah mosaic三种陆面过程方案对热带毁林增温响应的模拟能力。结果表明,CLM方案在模拟历史气温中有着更好的表现,Noah mosaic方案的结果存在明显低估。然而,对比毁林前后两种情景的模拟结果,本文发现,只有采用了"次格网"方式的Noah mosaic方案较好地模拟出毁林增温响应特征。在格网尺度采用"主导类型"计算方式的NoahMP方案没有合理地呈现出森林损失对区域气候的影响。理论上,CLM模式在计算中同时考虑格网内所有植被类型,然而本文发现CLM方案在主导类型不变的格网对森林损失比例不敏感,而且对毁林反馈的模拟结果与NoahMP方案的结果更接近。据此推测,在WRF模式耦合CLM方案的过程中,格网内参数处理方式可能产生了错误,实际采用的是"主导类型"方式。在模拟土地覆盖类型变化对气候的影响时,本文推荐使用Noah mosaic方案。同时,建议在未来版本的WRF模型中修正目前耦合的CLM方案关于次格网方法的处理方式,提供更合理的水热通量模拟。     

海陆差异对一次强暴发性气旋影响的数值模拟研究

本文利用多种观测资料、再分析资料及WRF（Weather Research and Forecasting Model）模式,对2017年12月23—25日发生于中国东部沿海入海加强的一个强暴发性气旋进行了研究,并探讨了海陆地形和热力差异对暴发性气旋发展的影响。该暴发性气旋的最大加深率为1.7Bergerons,其下垫面经历的“海洋-陆地-海洋”的复杂变化对其发展过程产生了显著影响。该气旋登陆朝鲜半岛时,气温降低,水平风速减小,上升运动增强,降水增加;而离开朝鲜半岛后,气温升高,上升运动减弱,降水减少。海陆差异的敏感性试验表明,陆地下垫面对气旋发展的动力作用主要是通过地面摩擦和地形抬升来实现的,而海洋对气旋发展的作用则主要表现在海表面热量和水汽传输方面。当气旋经过陆地时,由于陆地表面摩擦较大,气旋中心近地面水平风速减小。而较高的地形则会产生较强的上升运动,形成较强降水,促进类CISK（Conditional Instability of Second Kind）机制,使气旋加强。当气旋位于海面上时,冬季海面温度高于陆地,海洋向气旋输送更多的热量和水汽,从而更有利于气旋的发展。     

北京地区景观城市化进程对暴雨过程的影响——以“7·21”暴雨为例

利用美国环境预测中心（NCEP）和美国国家大气研究中心（NCAR）等美国科研机构开发的气象模式WRF 3.8版本,采用北京地区不同时期的土地利用数据,选取影响北京的一次典型暴雨过程,应用包含多层城市穹顶模式的模式参数化方案对其进行模拟研究。从小时降水模拟结果来看,景观城市化区域（城市下垫面）的扩张使得暴雨持续更久,使用2010年土地利用数据模拟的2012年7月21日暴雨过程小时降水量大于16 mm的时长较使用1990年土地利用数据模拟的结果增加了1 h;从累积降水结果来看,使用2010年土地利用数据模拟的24 h累积降水大于150 mm的区域较使用1990年土地利用数据模拟的结果增加了1534 km ²。本文中模拟的逐小时降水与实际情况存在一定的差距,未来的工作会深入研究模式的参数化方案和降水产生的机理进而深入地研究景观城市化进程对暴雨过程的影响。进一步研究需针对城市人为活动产生的大气气溶胶粒子、景观城市化密度变化等因子,探究景观城市化对暴雨的可能影响。     

Fedore Core 4.0下 WRF模式系统的配置安装及运行

介绍操作系统平台为Fedore Core 4.0下,WRF模式的安装和运行。重点介绍了PGI6.16编译器的配置、Fedore Core 4.0的配置和WRF模式的多重嵌套及其运行步骤的关键设置。     

The role of meteorological forcing and snow model complexity in winter glacier mass balance estimation,Columbia River basin,Canada

Glaciers are commonly located in mountainous terrain subject to highly variable meteorological conditions. High resolution meteorological (HRM) data simulated by atmospheric models can complement meteorological station observations in order to assess changes in glacier energy fluxes and mass balance. We examine the performance of two snow models, SnowModel and Alpine3D, forced by different meteorological data for winter mass balance simulations at four glaciers in the Canadian portion of the Columbia Basin. The Weather Research and Forecasting model (WRF) with resolution of 1 km and the North American Land Data Assimilation System with ~12 km resolution, provide HRM data for the two snow models. Evaluation is based on the ability of the snow models to simulate snow depth at both point locations (automated snow weather stations) and over the entire glacier surface (airborne LiDAR [Light Detection and Ranging] surveys) during the 2015/2016 winter accumulation. When forced with HRM data, both models can reproduce snow depth to within ±15% of observed values. Both models underestimate winter mass balance when forced by HRM data. When driven with WRF data, SnowModel underestimates winter mass balance integrated over the glacier area by 1 and 10%, whilst Alpine3D underestimates winter mass balance by 12 and 22% compared with LiDAR and stake measurements, respectively. The overall results show that SnowModel forced by WRF simulated winter mass balance the best.     

Exploring the effect of data assimilation by WRF‐3DVar for numerical rainfall prediction with different types of storm events

The mesoscale Numerical Weather Prediction (NWP) model is gaining popularity among the hydrometeorological community in providing high‐resolution rainfall forecasts at the catchment scale. Although the performance of the model has been verified in capturing the physical processes of severe storm events, the modelling accuracy is negatively affected by significant errors in the initial conditions used to drive the model. Several meteorological investigations have shown that the assimilation of real‐time observations, especially the radar data can help improve the accuracy of the rainfall predictions given by mesoscale NWP models. The aim of this study is to investigate the effect of data assimilation for hydrological applications at the catchment scale. Radar reflectivity together with surface and upper‐air meteorological observations is assimilated into the Weather Research and Forecasting (WRF) model using the three‐dimensional variational data‐assimilation technique. Improvement of the rainfall accumulation and its temporal variation after data assimilation is examined for four storm events in the Brue catchment (135.2 km²) located in southwest England. The storm events are selected with different rainfall distributions in space and time. It is found that the rainfall improvement is most obvious for the events with one‐dimensional evenness in either space or time. The effect of data assimilation is even more significant in the innermost domain which has the finest spatial resolution. However, for the events with two‐dimensional unevenness of rainfall, i.e. the rainfall is concentrated in a small area and in a short time period, the effect of data assimilation is not ideal. WRF fails in capturing the whole process of the highly convective storm with densely concentrated rainfall in a small area and a short time period. A shortened assimilation time interval together with more efficient utilisation of the weather radar data might help improve the effectiveness of data assimilation in such cases. Copyright © 2012 John Wiley & Sons, Ltd.     

Modeling the climatic effects of the land use/cover change in eastern China

This study aims to quantify the contribution of land use/cover change (LUCC) during the last three decades to climate change conditions in eastern China. The effects of farmland expansion in Northeast China, grassland degradation in Northwest China, and deforestation in South China were simulated using the Weather Research and Forecasting (WRF) model in addition to the latest actual land cover datasets. The simulated results show that when forestland is converted to farmland, the air temperature decreased owing to an increase in surface albedo in Northeast China. The climatic effect of grassland degradation on the Loess Plateau was insignificant because of the negligible difference in albedo between grassland and cropland. In South China, deforestation generally led to a decrease in temperature. Furthermore, the temperature decrease caused by the increase in albedo counteracted the warming effects of the evapotranspiration decrease, so the summer temperature change was not significant in South China. Excluding the effects of urbanization in the North China Plain, the LUCC effects across the entire region of East China presented an overall cooling trend. However, the variation in temperature scale and magnitude was less in summer than that in winter. This result is due mainly to the cooling caused by the increase in albedo offset partly by the increase in temperature caused by the decrease in evaporation in summer. Summer precipitation showed a trend of increasing–decreasing–increasing from southeast to northwest after LUCC, which was induced mainly by the decrease in surface roughness and cyclone circulations appearing northwest of Northeast China, in the middle of the Loess Plateau, and in Yunnan province at 700 hPa after forests were converted into farmland. All results will be instructive for understanding the influence of LUCC on regional climate and future land planning in practice.     

南京地区太阳能屋顶缓解夏季高温的模拟研究

太阳能屋顶的安装预计能在一定程度上缓解城市化带来的能源危机及对城市热环境的破坏。利用耦合了城市单层冠层方案（UCM）的WRF模式,以南京2010年7月27日至8月5日夏季晴天微风天气为背景,模拟了不同发电效率的太阳能屋顶的安装对城市高温的缓解效应。结果表明:（1）太阳能屋顶可以通过削弱到达城市表面的太阳辐射使城市2 m高气温降低,随着发电效率的提高,降温效果更明显,且白天降温效果明显优于夜间;白天2 m高气温最大降低0.4-1.3℃,夜间降低0.2-0.5℃。（2）太阳能屋顶可使边界层内气温降低,白天在边界层400 m以下降温显著,夜间在边界层高度200 m以下降温显著;白天边界层内最大降温出现在中午前后,降温0.1-0.8℃,夜间边界层内最大降温0.5℃。（3）发电效率为40%时,模拟期间的发电量为18.1×109 kW·h。      

多普勒雷达资料同化在福建地区暴雨过程中的模拟试验

利用中尺度模式WRFV3.5,对福建地区的一次暴雨过程进行了模式参数化方案模拟效果的敏感性试验,并同化了多普勒雷达资料进行了模拟研究。结果表明,WSM5微物理方案与BMJ积云对流方案的组合模拟大雨和暴雨量级降水的TS评分可达0.29,模拟效果优于其他各种组合。在此基础上,采用WRFV3.5三维变分系统,直接同化多普勒雷达资料,并和登陆台风的外围暴雨过程的控制试验比较,结果表明,仅同化反射率资料使得暴雨落区会向南调整,更接近于实况(TS评分提高了0.12),而仅同化径向风资料使得模拟的降水强度更趋近于实况(TS评分提高了0.13);同时同化反射率和径向风资料,使得暴雨落区及其强度的模拟最接近于实况(TS评分从0.12提高到0.28);敏感性试验的对比结果以时间间隔为3 h时模拟效果最优,6 h间隔次之。因此,合理同化雷达资料会显著改进福建登陆台风的降水模拟效果。