On the use of radiosonde humidity observations in mid-latitude NWP

Summary We compare radiosonde observations of relative humidity with NWP versions of the Meteorological Office Unified Model, and attempt to understand the causes of the systematic differences seen. The differences are found to have a different structure in cyclonic and anticyclonic situations over the UK. In cyclonic situations the mid-tropospheric temperature and humidity differences could be due to model biases, consistent with the conservation of energy; the latent heating from precipitation of the model's excess moisture would remove the model's cold bias. There is also some evidence for observational bias. Wetting of the sonde sensor in cloud can cause a moist bias at higher levels. The Väisala RS80 sonde also appears to have a dry bias near saturation.The Unified Model has a parameterisation for stratiform cloud which calculates the fractional cloud cover in a gridbox from the box-average relative humidity, allowing for sub-grid-scale variability within the box. This scheme has been tuned to give reasonable cloud amounts with the model's relative humidities. The cloud amounts implied (by the scheme) for radiosonde relative humidities are systematically less than the observed cloud. So assimilation of the observed humidities can significantly degrade analyses and predictions of cloud. Bias corrections for the radiosonde humidities have been calculated to compensate for this.Experiments have been performed to test the effect of the bias correction on the assimilation and prediction of cloud and precipation. With the control system, cloud cover and precipitation spins-up during the forecast period; the bias correction improves this. A large improvement was also found when the relationship between the temperature and humidity assimilation was changed; it is better to assume that temperature and relative humidity errors are uncorrelated, rather than temperature and specific humidity.With 16 Figures     

不同初始场及其扰动对WRF 模拟暴雨的影响

使用ERA-interim和FNL再分析资料分别驱动WRF,对2013年7月12—13日的一次暴雨过程进行数值模拟,详细比较了WRF模拟结果之间的差异。结果表明:(1)两种资料在次天气尺度上存在着较大差异,并由此造成了模拟结果之间的差异,ERA-interim作为初始场对降水的模拟优于FNL资料,反映了WRF对初、边界条件的敏感性;(2)从区域总降水量来看,湿度场扰动对降水量的影响最大,其次是风场扰动和温度场扰动,最小的是侧边界扰动;(3)从降水误差来看,湿度场扰动引起的降水误差最大,在积分20 h内风场扰动的降水误差大于温度场,积分21~24 h则相反,侧边界扰动引起的降水误差在前期比较小且增长缓慢,积分一段时间之后与单个气象要素扰动引起的降水误差相当。     

1981-2012年辽宁省春播期土壤相对湿度月尺度数据重建

辽宁省现有测站春播期土壤相对湿度数据存在不连续性及长时间序列缺失问题。以海城站为例,分析现有土壤相对湿度（0-20 cm）与气象因子及临近站点土壤相对湿度的相关关系,构建海城春播期土壤相对湿度统计回归模型,模拟缺测时段春播期土壤相对湿度。进而以此方法重建辽宁省20个观测站1981-2012年春播期土壤相对湿度月尺度数据。结果表明：海城土壤相对湿度与降水量和秋季封冻雨关联较大,相关系数分别超过0.60和0.30,与同期临近站点本溪站土壤相对湿度相关性也超过0.40,依据该3要素构建的4月和5月土壤相湿度统计回归模型复相关系数R2分别达0.79和0.77,模拟结果与实测资料平均相对误差为2.6 %,模拟效果较好;对辽宁省其他数据缺失站点构建的回归模型复相关系数均高于0.50,模型拟合精度优于85 %,拟合值和实测值平均相对误差基本控制在15 %以内,较好完成辽宁省20个测站1981-2012年春播期土壤相对湿度月尺度数据重建。     

2016年梅雨持续性强降水期间大气环流稳定分量研究

梅雨降水具有显著的阶段变化特征,研究持续强降水期间的关键环流稳定分量,对于分析和预测梅雨降水具有重要意义。利用NCEP-DOE1979～2016年逐日再分析资料,对2016年梅雨持续强降水期间位势高度场、风场和相对湿度场进行分析,提取环流系统的关键稳定分量,并对其空间结构、演变特征及更长时间尺度的背景形势进行分析,为梅雨区阶段性强降水的延伸期预报提供依据和参考。研究发现:（1）在位势高度场稳定分量中存在的“三极”分布形势,是维持2016年梅雨持续强降水的关键系统。“三极”分别对应着乌拉尔山阻塞高压、鄂霍茨克海阻塞高压以及偏东偏强的南亚高压和偏西偏强的西太平洋副热带高压（副高）。这种配置结构有利于冷暖空气在梅雨区交汇形成持续性强降水。（2）在中高纬度两个正距平区之间,是相对深厚的负距平区,有利于建立冷空气的向南输送通道,同时相对湿度场稳定分量表明北支气流对水汽的输送和汇聚作用对于梅雨区持续降水起到重要作用。（3）中低纬度的正距平区域呈纬向带状分布,且主要存在于对流层中高层,在梅雨区东西两侧各有一个正距平下沉支,它们共同加强了梅雨区南侧暖湿气流的汇聚输送作用。（4）通过对稳定分量的演变分析发现,“三极”系统的建立和演化与梅雨区降水强弱的阶段变化密切相关。（5）更长时间尺度（60 d）环流稳定分量为持续强降水时段的“三极”关键稳定分量提供了重要的环流背景。     

降水与相对湿度协同算法研究

本文利用天津地区国家气象观测站2016-2017年常规观测数据和欧洲中心数值模式数据,建立降水和相对湿度协同统计订正算法并检验评估,结果表明：观测资料显示降水量级越小,其相对湿度的离散度越大,且日变化特征。雨量越大、降水持续时间越长,相对湿度稳定在90%以上。模式预报降水时的相对湿度分布离散度较大,需订正。基于降水与相对湿度的统计关系,建立的降水和相对湿度协同算法,算法对于小雨的相对湿度订正偏高,而对于中雨以上订正偏低；协同订正效果不理想的可能原因是模式数据的时间分辨率不高,协同统计算法还有待进一步优化。     

Impact of surface observations on simulation of rainfall over NCR Delhi using regional background error statistics in WRF-3DVAR model

In this study, efforts are made to improve the simulation of heavy rainfall events over National Capital Region (NCR) Delhi during 2010 summer monsoon, using additional observations from automatic weather stations (AWS). Two case studies have been carried out to simulate the relative humidity, wind speed and precipitation over NCR Delhi in 48-h model integrations; one from 00UTC, August 20, 2010, and the other from 00UTC, September 12, 2010. Several AWS installed over NCR Delhi in the recent past provide valuable surface observations, which are assimilated into state-of-the-art weather research and forecasting (WRF) model using the three-dimensional variational data assimilation (3DVAR). The quality of background error statistics (BES) is a key component in successful 3DVAR data assimilation in a mesoscale model. In this study, the domain-dependent regional background error statistics (RBS) are estimated using National Meteorological Center method in the months of August and September 2010 and then compared with the global background error statistics (GBS) in the WRF model. The model simulations are analyzed and validated against AWS and radiosonde observations to quantify the impact of RBS. The root mean square differences in the spatial distributions of precipitation, relative humidity and wind speed at the surface showed significant differences between both the global and regional BES. Similar differences are also observed in the vertical distributions along the latitudinal cross section at 28.5°N. Model-simulated fields are analyzed at five different surface stations and one upper air station located in NCR Delhi. It is found that in 24-h model simulation, the RBS significantly improves the model simulations in case of precipitation, relative humidity and wind speed as compared to GBS.     

2020年梅汛期强降水事件的预报误差来源分析

基于WRF模式（Weather Research and Forecasting Model）分析2020年超长梅汛期内11次强降水事件的预报误差来源。分别以FNL（Final Global Data Assimilation System）、TIGGE_EC（THORPEX Interactive Grand Global Ensemble from European Centre for Medium-Range Weather Forecasts）作为初始场进行预报,对比预报结果发现,TIGGE_EC初始场的预报结果普遍优于FNL,这说明初始条件的不确定性对预报结果有重要影响。进一步探究初始条件不确定性（初始误差）来源的区域（敏感区）和变量（敏感变量）发现,敏感区集中分布于降水区西侧上游,相对应的敏感变量为水汽场。分别考察动能、有效位能以及比湿能在初始误差总能量中的占比,结果表明,扰动比湿能占比最小,但敏感性试验 表明比湿场扰动对预报效果的影响最大。选取比湿场扰动对预报效果影响最大且WRF_EC具有更好预报效果的6个暴雨事件,通过HYSPLIT后向轨迹模式分别追踪其累计降水量最大值点的水汽来源及路径发现,有6个事件均有向降水区西侧上游延伸的水汽来源通道,进一步表明了敏感区的初始水汽场的准确性对暴雨预报的影响。因此降水区西侧上游的水汽场的误差是这11次梅汛期暴雨过程重要的预报误差来源,对其准确描述可有助于预报效果的提升。     

雷达反射率三维拼图观测资料在北方区域数值模式预报系统中的同化应用研究

以业务应用为目标,开展雷达反射率三维拼图观测资料在北方区域数值预报系统中的同化应用研究。采用雷达反射率间接同化方法同化北方雷达反射率拼图观测资料,重点关注其对降水、湿度、温度及风的预报能力影响。首先,基于2017年8月雷达拼图观测资料批量同化和对比试验,对雷达拼图资料同化应用效果进行定量评估,结果表明雷达拼图资料同化虽然加大了地面风场预报误差,但在降水预报和湿度、温度预报等方面有明显的改善作用。其次,选择在业务中预报难度较大的强降水个例开展分析研究,分析表明:（1）同化雷达拼图观测资料有效提高了模式降水预报性能,临近降水发生的循环起报时次预报效果更好;（2）对于短时间多次强降水过程发生的预报,循环同化雷达拼图资料可及时弥补模式中由于前次降水导致的水汽、能量等消耗及热/动力条件削弱,持续支持降水系统发展。最后,通过考察雷达反射率的不同同化方案,发现同化反演水凝物或者估计水汽均能改善模式降水预报性能,但是同化估计水汽对降水预报性能的改善更为明显,联合使用两方案能同时对水凝物分布、热力场等进行调整,可提高模式降水预报性能。      

中尺度暴雨集合预报系统研发中的初值扰动试验

针对2006年5月24～25日一次暴雨过程, 通过一系列初值扰动试验探讨实际业务中建立集合预报系统的方法。运用45 km的WRF模式构建一个11个成员的集合预报系统来比较分析不同的扰动方案、 扰动的空间结构和扰动振幅对集合预报的影响, 结果表明： （1）初值扰动的空间结构对暴雨集合预报的离散度影响很关键, 而扰动振幅的影响却居次要地位。具有动力学结构的孵化扰动明显优于随机扰动。（2）集合预报比单一控制预报提供了更有价值的预报信息。例如在该个例控制预报中漏报的湖北监利强降水中心, 在集合预报中有20%的概率, 并且实况被包含在集合预报的预报范围之中。集合平均预报也明显优于控制预报\.例如矫正了在控制预报中明显虚报的鄂东北的大暴雨中心, 且集合平均预报的暴雨中心落在实际观测暴雨中心的附近。（3）集合离散度较好地反映了实际降水过程的可预报性。例如应用孵化扰动, 其离散度的空间结构同降水预报误差的空间分布大致对应。     

基于数字摄像能见度仪的北京地区降雨和雾霾天气能见度对比分析

数字摄像能见度仪（Digital Photographic Visibility System,DPVS）仿照人工目测能见度的原理测量大气能见度。本文应用2017年3—8月北京地区DPVS、前向散射仪（PWD22）、大气透射仪（LT31）三种观测仪器在降雨天气和雾霾天气观测数据进行了对比。结果表明：能见度观测数据与相对湿度、颗粒物浓度、降水粒子等要素之间有明显的负相关性;在低能见度天气条件下,三种仪器观测数据变化趋势一致,但存在一定的差异;DPVS在中雨天气、大雨天气、暴雨天气和中度雾霾天气中,观测数据离散性更小,稳定性更好。但DPVS在白天和夜间的交替过渡期观测值不够稳定,这也是今后算法优化的重点方向。     

2012年8月中旬四川大暴雨的数值模拟及地形影响试验

利用WRF模式对2012年8月17~18日四川出现的一次大暴雨过程进行模式模拟和诊断分析,并通过对地形敏感性试验讨论川西高原至川东过渡带陡峭地形对此次暴雨的影响。结果表明,WRF基本成功模拟出2012年8月中旬四川中部大暴雨过程,对环流形式预报与实况较为一致。此次过程水汽来源台风低压及副高外围携带的水汽。川中云团发展阶段对应四川中部多个站出现强降水,该对流云团发展是引发本次降水的重要因素,而对流层中低层高温高湿环境对对流云团发展提供有力的环境。地形敏感性试验表明,陡峭地形高度与降水强度呈正比,通过影响陡峭地形周边物理量特征场分布从而影响暴雨区降水强度;相对湿度的影响小于温度对降水强度的影响作用。     

A Numerical Study on the Winter Monsoon and Cold Surge over East Asia

By using the improved regional climate model （RegCM_NCC）, a numerical study has been undertaken for the East Asia region over a period of 5 years （1998-2002） in an effort to evaluate the model＇s ability to reproduce the winter monsoon conditions that were observed. The results showed that the model can successfully simulate the basic characteristics of the winter monsoon circulations, including the location and intensity of the cold-surface, high-pressure system, as well as the wind patterns and the intensity of the winter monsoon. The simulated occurrence frequency and regions of the cold surge were consistent with the observations. The simulated rainfall distribution over China was consistent with the observations collected in South China. The features of the simulated moisture transport were also in good agreement with the observations that were derived from the NCEP reanalysis data, indicating that moisture transport coming from the Bay of Bengal trough plays a crucial role in supplying moisture needed for precipitation in South China. In addition, the moisture transport coming from the near-equatorial west-Pacific was also important. These two branches of moisture transport converged in South China, as a prerequisite for occurrence of the precipitation that was observed there. Heat budgets have shown that the development of a heat sink over the East Asian continent was remarkable and its thermal contrast relative to the neighboring seas was the important forcing factor for the winter monsoon activity. The simulation also indicated that the significant differences in circulation patterns and rainfalls during the winters of 1997/98 and 1998/99 were affected by cold and warm ENSO events, respectively. The above analysis demonstrated the model＇s ability to simulate the East Asian winter monsoon.     

Barotropic processes associated with the development of the Mei-yu precipitation system

The barotropic processes associated with the development of a precipitation system are investigated through analysis of cloud-resolving model simulations of Mei-yu torrential rainfall events over eastern China in mid-June 2011. During the model integration period, there were three major heavy rainfall events: 9–12, 13–16 and 16–20 June. The kinetic energy is converted from perturbation to mean circulations in the first and second period, whereas it is converted from mean to perturbation circulations in the third period. Further analysis shows that kinetic energy conversion is determined by vertical transport of zonal momentum. Thus, the prognostic equation of vertical transport of zonal momentum is derived, in which its tendency is associated with dynamic, pressure gradient and buoyancy processes. The kinetic energy conversion from perturbation to mean circulations in the first period is mainly associated with the dynamic processes. The kinetic energy conversion from mean to perturbation circulations in the third period is generally related to the pressure gradient processes.     

Numerical Experiments on the Spin-up Time for Seasonal-Scale Regional Climate Modeling

In this paper,the numerical experiments on the issue of spin-up time for seasonal-scale regional climate modeling were conducted with the newly Regional Climate Model (RegCM3),in the case of the abnormal climate event during the summer of 1998 in China.To test the effect of spin-up time on the regional climate simulation results for such abnormal climate event,a total of 11 experiments were performed with different spin-up time from 10 days to 6 months,respectively.The simulation results show that,for the meteorological variables in the atmosphere,the model would be running in"climate mode"after 4-8-day spin-up time,then, it is independent of the spin-up time basically,and the simulation errors are mainly caused by the model's failure in describing the atmospheric processes over the model domain.This verifies again that the regional climate modeling is indeed a lateral boundary condition problem as demonstrated by earlier research work. The simulated mean precipitation rate over each subregion is not sensitive to the spin-up time,but the precipitation scenario is somewhat different for the experiment with different spin-up time,which shows that there exists the uncertainty in the simulation to precipitation scenario,and such a uncertainty exhibits more over the areas where heavy rainfall happened.Generally,for monthly-scale precipitation simulation,a spin-up time of 1 month is enough,whereas a spin-up time of 2 months is better for seasonal-scale one. Furthermore,the relationship between the precipitation simulation error and the advancement/withdrawal of East Asian summer monsoon was analyzed.It is found that the variability of correlation coefficient for precipitation is more significant over the areas where the summer monsoon is predominant.Therefore,the model's capability in reproducing precipitation features is related to the heavy rainfall processes associated with the advancement/withdrawal of East Asian summer monsoon,which suggests that it is necessary to develop a more reliable parameterization scheme to capture the convective precipitation of heavy rainfall pro- cesses associated with the activities of East Asian summer monsoon,so as to improve the climate modeling over China.     

青岛市一次局地大暴雨天气成因和逆风区特征分析

利用地面和探空气象观测数据、雷达探测资料以及ECMWF（ERA5）0.25°×0.25°全球再分析数据,分析了2016年8月19日青岛市环胶州湾一次局地大暴雨过程的环流形势、环境条件及逆风区演变特征。结果表明:副热带高压边缘的地面冷锋进入倒槽,冷空气向地面辐合线的暖区渗透触发对流天气是此次过程的形成机制。此次大暴雨过程与地形关系紧密,主要分布在低层暖湿气流和山脉抬升作用形成的迎风坡前位涡大值区,该区域中低空垂直上升运动和相对湿度配合较好。大暴雨区站点的强降水时段与垂直上升运动时段吻合,小时最大雨量出现在垂直上升运动强度的跃增阶段。过程降水开始前,0℃层高度和近地面层比湿变化不大,CAPE值、K指数以及垂直风切变等各项不稳定指数均较08时明显增强。雷达产品分析显示,造成大暴雨的对流单体呈暖区对流特征,强降水前20~30min垂直风切变增强。此次降水过程产生的4处逆风区均出现在对流单体生成之后,为对流单体下沉气流产生的与环境风相反方向的辐散气流。其中2处低层相对湿度大值区的逆风区能得到发展增强,而逆风区的发展则进一步促进了对流增强,此演变特征对本次大暴雨过程的临近预报预警有较好的指示作用。      

NCAR RegCM2对1991年夏季江淮流域异常降水事件中关键物理过程的模拟能力检验(英文)

选取１９９１年夏季江淮流域发生的持续性特大暴雨洪涝个例，利用ＮＣＡＲ第二代区域气候模式ＲｅｇＣＭ２对逐日降水过程及其关键物理因子进行了数值模拟。模式的侧边界条件出ＥＣＭＷＦ的大尺度分析资料提供，模拟时间为１９９１年５－８月。模式范围包括东亚地区及相邻海域，水平分辨率为 ６０ ｋｍ × ６０ ｋｍ，垂直方向为 ２３层。试验结果显示，该模式能够合理地模拟出１９９１年夏季东亚地区的逐日降水过程，特别是在江淮流域发生的异常降水事件。对一些关键物理变量和过程时空结构的分析表明，大气垂直速度和水平散度的时间演变与江淮流域的５次降水事件一致；形成异常降水的水汽来源主要是大气的水平运动输送。西太平洋副热带高压控制着东亚夏季季风的进退，ＲｅｇＣＭ２能够模拟出西太平洋副高的南北位置移动。而且，模式能够较好地再现出对水汽输送至关重要的低空急流的逐日变化。     

中国月平均降水场的时空相关特征

本文通过对我国1951～1984年月平均降水资料的分析,给出了我国东部降水的空间分布具有三种类型,一种类型是长江流域多雨,华南和华北及东北少雨;另一种类型与此型相反;第三种类型为正常型,降水距平百分率全场都很小。并指出了长江中下游地区降水时间特征具有明显的半年韵律现象,冬季1月和12月的降水可以作为6～8月降水的信息期。同时还表明在1951～1984年中9个ElNino年的下一年6～8月汛期降水具有不完全相同的类型。     

Nudging方法对中国西北强降水过程的模拟试验研究

通过在WRF(Weather Research and Forecasting)模式中运用松弛逼近方法(Nudging)同化NCEP-FNL资料,对中国西北地区夏季3次对流降水过程进行了模拟试验,检验了模式运用谱逼近(Spectral Nudging,SN)和格点逼近(Grid Nudging,GN)方案后对研究区域内降水过程的模拟性能。结果表明:SN和GN试验相对于控制试验,模拟的降水结果更接近于站点观测。在降水落区和量级的模拟效果上都有显著提高,且SN试验所得结果优于GN试验。通过分析两个同化试验在降水时段的基本要素场(湿度、温度和风速)变化,在近地面层,GN试验模拟的风速和温度较SN试验更接近观测;但700 hPa上,SN试验中风速、风向、温度、湿度的增量场变化及分布同降水的模拟结果存在较好的对应关系。最后,从物理诊断量—水汽通量散度的空间垂直变化来看,SN试验中600 hPa和700 hPa的水汽通量散度的正负分布有效调节降水的空间分布,更逼近观测。因此700 hPa的物理量场变量增量是降水模拟效果改善的主要原因之一。     

四川盆地暴雨对初值敏感性的模拟研究

本文基于区域暴雨数值预报模式AREM,针对2007年7月发生在四川地区的多次强降水过程进行数值试验,检验了NCEP和站点资料(STN)初始分析场资料预报结果,发现由于台站资料稀少,NCEP资料在四川地区的评分较高。讨论了四川盆地降水对初值的高度敏感性,揭示了四川盆地降水对初值中各个物理量场的不同敏感性,其中,降水对初值中湿度场的响应最为显著。初值不仅决定着降水的范围和强度,还对降水的发生时间产生明显影响。      

分辨率对区域气候极端事件模拟的影响

利用NCAR MM5V3对1999年6月长江流域的极端异常降水事件进行了模拟,主要研究不同水平和垂直分辨率对极端区域气候事件模拟的影响。数值模拟试验表明:模式能够模拟出极端强降水的主要分布特征;水平分辨率的提高降低了模式模拟的强降水偏差,对逐日降水变化的模拟更加合理,而垂直分辨率的提高基本上也都减小了模拟的强降水过程的偏差,改善对强降水的模拟能力;模式水平、垂直分辨率的提高在一定程度上增强了对强降水过程的模拟能力。水平分辨率的提高能够改善模式对海平面气压的模拟,而垂直分辨率的提高可以改善模式模拟的地面气温和低层环流。分辨率对中层大气环流的影响不是很敏感。不同积云对流参数化方案模拟的对流降水比率随水平分辨率的变化是不同的,Grell方案对流降水比例随分辨率的提高而增加,而Kain-Fritsch方案的结果相反。