Numerical investigations for the impacts of triple-moment and double-moment condensation schemes on the warm rain formation

在暖云发展过程中,云滴谱的凝结不仅为对流提供能量而且直接影响暖雨的形成和发展。目前国际上广泛使用的云滴谱凝结方案主要为双参数方案,此类方案模拟的云滴谱在凝结过程中呈不正常拓宽现象,三参数云滴谱方案有效解决了该问题。为了比较两种凝结方案对暖雨初始形成和发展强度的影响,本文采用WRF模式中的理想性大涡模拟个例在相同背景条件下,分别使用两种方案模拟了一个对流热泡中暖雨的形成、发展过程。模拟结果表明:在雨滴初始形成阶段,三参数方案因为克服了双参方案中的拓宽问题,推迟了暖雨形成的时间;在暖雨发展阶段,三参数凝结方案有效削弱了暖雨区的中心强度;但在暖雨发展后期,两个凝结方案模拟结果的差异逐渐缩小。

Bias-Corrected Short-Range Ensemble Forecasts for Near-Surface Variables during the Summer Season of 2010 in Northern China

A running mean bias(RMB) correction approach was applied to the forecasts of near-surface variables in a seasonal short-range ensemble forecasting experiment with 57 consecutive cases during summer 2010 in the northern China region. To determine a proper training window length for calculating RMB, window lengths from 2 to 20 days were evaluated, and 16 days was taken as an optimal window length, since it receives most of the benefit from extending the window length. The raw and 16-day RMB corrected ensembles were then evaluated for their ensemble mean forecast skills. The results show that the raw ensemble has obvious bias in all near-surface variables. The RMB correction can remove the bias reasonably well, and generate an unbiased ensemble. The bias correction not only reduces the ensemble mean forecast error, but also results in a better spreaderror relationship. Moreover, two methods for computing calibrated probabilistic forecast(PF) were also evaluated through the 57 case dates: 1) using the relative frequency from the RMB-corrected ensemble; 2) computing the forecasting probabilities based on a historical rank histogram. The first method outperforms the second one, as it can improve both the reliability and the resolution of the PFs, while the second method only has a small effect on the reliability, indicating the necessity and importance of removing the systematic errors from the ensemble.

Observations and Modeling of Ice Water Content in a Mixed-Phase Cloud System

The ice water content(IWC) distribution in a mixed-phase cloud system was investigated using Cloud-Sat data,aircraft measurements,and the Weather Research and Forecasting(WRF) model.Simulated precipitation and IWC were in general agreement with rain gauge,sat-ellite,and aircraft observations.The cloud case was char-acterized by a predominant cold layer and high IWC throughout the cloud-development and precipitation stages.The CloudSat-retrieved products suggested that the IWC was distributed from 4.0 to 8.0 km,with the maximum values(up to 0.5 g m-3) at 5.0-6.0 km at the earlymature stage of cloud development.High IWC(up to 0.8 g m-3) was also detected by airborne probes at 4.2 and 3.6 km at the late-mature stage.The WRF model simulation re-vealed that the predominant riming facilitated rapid ac-cumulation of high IWC at 3.0-6.0 km.

Aircraft observation of cloud microphysical characteristics of pre-stratiform-cloud precipitation in Jiangxi Province

本文利用2015年11月11日江西省赣州市一次降水前期层状云的DMT资料,结合雷达数据,综合分析了在高空槽影响下云系的宏微观结构特征。结果表明:(1)探测属于降水前期,云系呈多层分布。(2)层状云系在水平和垂直方向存在不均匀性,0°C层上下满足播种云-供应云机制。0°C层以上为播种云,凝华,粘连增长占主要过程。0°C层以下的暖层为供应云,粒子在液态水含量丰富的供应云体中长大,冰晶的融化聚并过程使得有效直径显著增大。下降到4150m的高度,冰晶完全融化变为雨滴。

Cloud Seedability Study with a Dual-Model System

In this research,a novel dual-model system,one-dimensional stratiform cold cloud model(1DSC) coupled to Weather Research and Forecast(WRF) model(WRF-1DSC for short),was employed to investigate the effects of cloud seeding by silver iodide(AgI) on rain enhancement.Driven by changing environmental conditions extracted from the WRF model,WRF-1DSC could be used to assess the cloud seeding effects quantitatively.The employment of WRF-1DSC,in place of a one-dimensional two-moment cloud seeding model applied to a three-dimensional mesoscale cloud-resolving model,was found to result in massive reduction of computational resources.Numerical experiments with WRF-1DSC were conducted for a real stratiform precipitation event observed on 4-5 July 2004,in Northeast China.A good agreement between the observed and modeled cloud system ensured the ability of WRF-1DSC to simulate the observed precipitation process efficiently.Sensitivity tests were performed with different seeding times,locations,and amounts.Experimental results showed that the optimum seeding effect(defined as the percentage of rain enhancement or rain enhancement rate) could be achieved through proper seeding at locations of maximum cloud water content when the updraft was strong.The optimum seeding effect was found to increase by 5.61% when the cloud was seeded at 5.5 km above ground level around 2300 UTC 4 July 2004,with the maximum AgI mixing ratio(X s) equaling 15 ng kg 1.On the other hand,for an overseeded cloud,a significant reduction occurred in the accumulated precipitation(-12.42%) as X s reached 100 ng kg 1.This study demonstrates the potential of WRF1DSC in determining the optimal AgI seeding strategy in practical operations of precipitation enhancement.

Numerical Simulation of Effects of Cloud Top Temperatures and Generating Cells on Secondary Ice Production in Stratiform Clouds with a Detailed Microphysical Model

This paper outlines a one-dimensional,heightdependent bin model with detailed microphysical processes in which ice splinters are produced by a riming process.The model is then applied to simulate the shift of particle size distribution effected by the secondary ice production process within clouds with different generating cells and cloud top temperatures.The result of model simulations reveals the general effects of cloud updrafts on increasing ice particle concentration by extending the residence time of ice particles in clouds and providing sufficiently large supercooled water droplets.The rimesplintering mechanism is more effective in clouds with lower ice seeding rates than those with higher rates.Evolutions of hydrometeor size distribution triggered by the rime-splintering mechanism indicate that the interaction between large ice particles and supercooled water drops adds a "second maximum" to the primary ice spectra.