不同积云对流参数化方案对黑河流域降水模拟的影响

使用NCEP-fnl再分析资料作为黑河流域高分辨率区域气候模式的初始场和边界场,利用该模式中常用的3种积云对流参数化方案:Grell,Bett-Miller(BM)和不采用积云对流参数化方案(NON)对黑河流域进行2000年1月1日至12月31日的积分试验,重点考察水平分辨率在3 km条件下不同积云对流参数化方案对黑河流域降水模拟的敏感性。结果表明:①卫星遥感反演的黑河流域的降水较观测台站降水偏少,卫星遥感反演日降水与观测台站日降水的相关系数达到0.34,相关系数通过99%置信度检验;②模式采用3种参数化方案都能够较好地模拟出年降水空间分布以及不同区域日平均降水随时间演变,与观测之间的相关系数都通过99%置信度检验;③对于黑河流域来说,在水平分辨率为3 km条件下区域气候模式采用Grell积云对流参数化方案较其他2种方案无论从空间和时间演变来说均更加接近观测。     

RegCM3在青藏高原地区的应用研究:积云参数化方案的敏感性

为检验区域气候模式RegCM3在青藏高原地区的模拟能力,选择青藏高原地区的两个气候异常年(1997年少雨年和1998年多雨年)进行模拟,选取夏季(6-8月)分析RegCM3对青藏高原地区气候异常的模拟能力;积云参数化方案敏感性研究分别对1997年和1998年夏季选取不同的积云参数化方案进行对比分析.结果显示:RegCM3能够模拟出青藏高原1997年少雨年和1998年的多雨年气温基本特征,但在地形起伏较大地区模拟的温度偏低,对降水基本特征的模拟欠佳;两种积云参数化方案中,与Grell方案对比,Anthes-Kuo方案中总降水量的数量模拟更接近观测,但就温度和降水模拟的相关性上,Grell方案优于Anthes-Kuo方案.将RegCM3应用于青藏高原地区进行气候模拟时,选择Grell积云参数化方案比Anthes-Kuo方案更为适宜.     

物理过程参数化方案对中国夏季降水日变化模拟的影响

系统地分析了不同陆面过程、辐射传输以及积云对流参数化方案对区域气候模式模拟中国夏季降水日变化能力的影响,发现日内最大标准化降水及其出现时刻的模拟对不同模式物理过程的组合方案敏感。陆面过程、辐射传输参数化方案只影响降水强度的模拟,而对降水日变化形式和峰值出现时间模拟的影响较小,降水日变化形式的模拟对积云对流参数化方案敏感且与模拟区域的选择关系密切。Grell方案对青藏高原东部、长江中游地区夏季降水的日变化特征具有较好模拟能力,Kuo和Anthes-Kuo方案较好地模拟出了东北、华南地区夏季降水的日变化特征,BM方案仅能模拟华南地区夏季降水的日变化特征。4种积云对流参数化方案均不能模拟出江淮—华北地区夏季降水日变化的双峰值结构。     

物理过程参数化方案对中国夏季降水日变化模拟的影响

系统地分析了不同陆面过程、辐射传输以及积云对流参数化方案对区域气候模式模拟中国夏季降水日变化能力的影响,发现日内最大标准化降水及其出现时刻的模拟对不同模式物理过程的组合方案敏感。陆面过程、辐射传输参数化方案只影响降水强度的模拟,而对降水日变化形式和峰值出现时间模拟的影响较小, 降水日变化形式的模拟对积云对流参数化方案敏感且与模拟区域的选择关系密切。Grell方案对青藏高原东部、长江中游地区夏季降水的日变化特征具有较好模拟能力,Kuo和Anthes Kuo方案较好地模拟出了东北、华南地区夏季降水的日变化特征,BM方案仅能模拟华南地区夏季降水的日变化特征。4种积云对流参数化方案均不能模拟出江淮—华北地区夏季降水日变化的双峰值结构。     

不同陆面方案对降水模拟的影响

基于区域气候模式RegCM4.0(Regional Climate Model 4.0),分别选取BATS(Biosphere Atmosphere Transfer Scheme)和CLM(Community Land Model)陆面方案,对2001-2005年中国的气候状况进行模拟,并将模拟结果与CRU(Climatic Research Unit)及GPCP(Global Precipitation Climatology Project)降水资料进行对比,研究不同陆面方案对降水模拟的影响。结果表明:在两种陆面方案下,区域气候模式均较合理地模拟出了中国降水的空间分布、时间变化;模拟降水对陆面方案敏感,RegCM_BATS总体上表现为正偏差,在东北区域的模拟偏差较大;RegCM_CLM表现为负偏差,在长江以南区域的模拟偏差较大;模拟结果的偏差在夏季较大,冬季较小;两模式模拟结果间的差异在空间上由东南向西北减少;两模式均较准确地模拟了不同强度降水出现频率的分布形势,总体上RegCM_CLM模拟低强度降水偏多;高强度降水偏少,而RegCM_BATS模拟低强度降水偏少,高强度降水偏多;不同陆面方案对地表蒸发量以及地表潜热通量模拟的差异是导致模拟降水差异的主要原因,夏季地表蒸发对降水的影响较冬季更强;水汽平流输送对两模式模拟降水差异的影响较小。     

东亚地区区域气候模拟的研究进展

由于大气环流模式对东亚地区区域气候特征的模拟存在很大不足,采用区域气候模式模拟该地区特殊的季风气候成为目前发展的一个重要研究方向,并取得了显著的研究进展。通过回顾当前东亚地区区域气候模拟的现状,表明大部分区域气候模式都不同程度地模拟出了东亚季风区持续性洪涝现象的大尺度环流特征和演变过程,再现了东亚各主要气候区降水的年际、季节和季节内变化及主要雨带的季节进退和降水的时空演变特征。但是,大部分模式没能很好地模拟出大尺度特征的强度和量值,模拟的温度和降水存在系统性偏差。原因分析表明,进一步完善和改进区域气候模式的物理过程参数化方案及动力框架可以改善模拟效果。最后对区域气候模式未来的发展给出展望。     

区域气候模式分辨率对夏季降水模拟的影响

利用最新发布的区域气候模式RegCM4,选取3种水平分辨率,3种垂直分辨率,对2001～2003年6～8月气候状况进行模拟,将模拟降水与GPCP降水资料在季、月、日尺度进行对比分析,研究分辨率对夏季降水模拟的影响,得到主要结论:RegCM4模拟结果能较好地反映模拟区域降水由东南向西北递减的分布趋势,模拟降水量随水平、垂直分辨率的增加而减小,当水平分辨率为30 km,垂直分辨率为14层时,全区域模拟降水偏差最小;不同区域、不同月份区域平均降水对分辨率的敏感性存在明显差异;在高海拔区域,分辨率对降水模拟影响显著,随着水平分辨率的提高,模拟降水更接近观测值;模拟日降水强度分布的峰值随着垂直分辨率的提高,向弱降水方向移动显著;分辨率配置主要影响模拟降水偏差的低频分量及24 d周期分量,通过合理调整分辨率配置可以有效减小模拟系统误差。     

对称不稳定对梅雨锋暴雨影响的数值模拟

在Kuo-Anthes垂直对流参数化方案和Nordeng倾斜对流参数化方案基础上,提出了垂直-倾斜对流一体化参数化方案,在引入MM5模式后,对1999年6月发生在长江流域的一次大尺度带状强降水过程进行了数值模拟及敏感性试验。结果表明:在模式中引入倾斜对流参数化方案,可有效改进模式模拟的降水强度和位置,加快形成锋面附近的垂直环流并使之得到增强,模拟结果更接近实况。同时也表明,在模拟和预报具有对称不稳定的天气系统时,在模式中考虑倾斜对流参数化方案是必要的。     

区域气候模式在中国西北地区气温和降水长时间序列模拟的误差分析

气温和降水微小的变化都可能引起中国西北地区脆弱生态环境空间格局剧烈变化.由于西北地区气象站点分布稀疏,站点观测结果难于完全代表西北地区复杂地貌的气象要素空间分布格局.区域气候模式模拟可以弥补现有观测资料的不足,但模式模拟存在的误差,往往制约着西北区域气候变化评估工作.本文在CN05格点数据和站点数据基础上,从空间格局、极值模拟等方面对高分辨率WRF模式数据气温和降水模拟精度进行评估,假定偏差恒定基础上,使用分类回归树模型建立偏差预测模型.结果表明:CN05数据和WRF模式多年年平均气温和多年平均年降水数据空间格局基本一致,但WRF模式结果空间格局更加细致.WRF模式结果在山区和湖泊地区降水偏高估,气温和降水距平在新疆地区相对于其他地区变化较为一致;95%分位数的降水在甘肃和新疆地区模拟结果好于宁夏、青海和陕西;5%和95%分位数气温,WRF模式大部分站点表现为暖偏差,而CN05数据表现为冷偏差;不同的地貌单元区域气温和降水的偏差时间序列存在一定的相关性.在西北五省区气温和降水的分类树模型中,由于高程和地形复杂度对偏差预测模型影响较大,无法在整个西北地区建立统一的误差预测模型.     

RegCM3模式在西北地区的应用研究I:对极端干旱事件的模拟

为了检验区域气候模式RegCM3在西北地区的模拟能力,对2001年夏季西北地区极端干旱事件进行了模拟.结果表明:模式能很好地再现西北地区主要的环流特征和温度及降水的变化情况,主要的偏差在于高原上低压中心的模拟偏低,对西北东部对流层低层位势高度的模拟偏高.区域平均的温度模拟存在着1~3℃的冷偏差,偏差产生的原因与地表净辐射的负偏差有关.月降水量模拟远远偏大,最小的百分比偏差也达到了30%.模拟结果同时表明,由于受模式初始场的影响,6月降水和气温的模拟效果最差.RegCM3的模拟中还存在着许多问题,必须开展进一步的工作来提高模式的模拟效果,减少偏差.     

A Study on the Impact of Parameterization of Physical Processes on Prediction of Tropical Cyclones over the Bay of Bengal With NCAR/PSU Mesoscale Model

Prediction of the track and intensity of tropical cyclones is one of the most challenging problems in numerical weather prediction (NWP). The chief objective of this study is to investigate the performance of different cumulus convection and planetary boundary layer (PBL) parameterization schemes in the simulation of tropical cyclones over the Bay of Bengal. For this purpose, two severe cyclonic storms are simulated with two PBL and four convection schemes using non-hydrostatic version of MM5 modeling system. Several important model simulated fields including sea level pressure, horizontal wind and precipitation are compared with the corresponding verification analysis/observation. The track of the cyclones in the simulation and analysis are compared with the best-fit track provided by India Meteorological Department (IMD). The Hong-Pan PBL scheme (as implemented in NCAR Medium Range Forecast (MRF) model) in combination with Grell (or Betts-Miller) cumulus convection scheme is found to perform better than the other combinations of schemes used in this study. Though it is expected that radiative processes may not have pronounced effect in short-range forecasts, an attempt is made to calibrate the model with respect to the two radiation parameterization schemes used in the study. And the results indicate that radiation parameterization has noticeable impact on the simulation of tropical cyclones.     

The WRF model performance for the simulation of heavy precipitating events over Ahmedabad during August 2006

The summer monsoon season of the year 2006 was highlighted by an unprecedented number of monsoon lows over the central and the western parts of India, particularly giving widespread rainfall over Gujarat and Rajasthan. Ahmedabad had received 540.2mm of rainfall in the month of August 2006 against the climatological mean of 219.8mm. The two spells of very heavy rainfall of 108.4mm and 97.7mm were recorded on 8 and 12 August 2006 respectively. Due to meteorological complexities involved in replicating the rainfall occurrences over a region, the Weather Research and Forecast (WRF-ARW version) modeling system with two different cumulus schemes in a nested configuration is chosen for simulating these events. The spatial distributions of large-scale circulation and moisture fields have been simulated reasonably well in this model, though there are some spatial biases in the simulated rainfall pattern. The rainfall amount over Ahmedabad has been underestimated by both the cumulus parameterization schemes. The quantitative validation of the simulated rainfall is done by calculating the categorical skill scores like frequency bias, threat scores (TS) and equitable threat scores (ETS). In this case the KF scheme has outperformed the GD scheme for the low precipitation threshold.     

China summer precipitation simulations using an optimal ensemble of cumulus schemes

RegCM3 (REGional Climate Model) simulations of precipitation in China in 1991 and 1998 are very sensitive to the cumulus parameterization. Among the four schemes available, none has superior skills over the whole of China, but each captures certain observed signals in distinct regions. The Grell scheme with the Fritsch-Chappell closure produces the smallest biases over the North; the Grell scheme with the Arakawa-Schubert closure performs the best over the southeast of 100°E; the Anthes-Kuo scheme is superior over the northeast; and the Emanuel scheme is more realistic over the southwest of 100°E and along the Yangtze River Basin. These differences indicate a strong degree of independence and complementarity between the parameterizations. As such, an ensemble is developed from the four schemes, whose relative contributions or weights are optimized locally to yield overall minimum root-mean-square errors from observed daily precipitation. The skill gain is evaluated by applying the identical distribution of the weights in a different period. It is shown that the ensemble always produces gross biases that are smaller than the individual schemes in both 1991 and 1998. The ensemble, however, cannot eliminate the large rainfall deficits over the southwest of 100°E and along the Yangtze River Basin that are systematic across all schemes. Further improve-ments can be made by a super-ensemble based on more cumulus schemes and/or multiple models.     

A preliminary evaluation of the necessity of using a cumulus parameterization scheme in high-resolution simulations of Typhoon Haiyan (2013)

The Weather Research and Forecasting model was used to test the sensitivity of Typhoon Haiyan (2013) to the use of a cumulus parameterization scheme, specifically the revised Kain–Fritsch (rKF) scheme, at high horizontal resolutions with grid spacing varying from 9 to 2 km. The rKF scheme simulated the typhoon in best agreement with the observation compared with other schemes, but some fundamental drawbacks relating the rKF scheme, e.g., neglecting the momentum adjustment and being less applicable to high-resolution modeling than multi-scaled schemes, could influence the results and were discussed. Initial results showed that the typhoon track simulations benefited little from the use of the rKF scheme or a fine resolution, partially because of the similar large-scale steering flows induced by the analyzed boundary conditions used in each simulation. The influences of using the rKF scheme on typhoon intensity, size, structure, and precipitation were dependent on the grid spacing, and the most apparent changes occurred near a grid length of 4 km. At 9–4-km grid spacings, using the rKF scheme produced typhoons much stronger with more rainfall and surface latent heat flux than did using no cumulus parameterization scheme. At 3- or 2-km grid spacing, using the rKF scheme caused little changes on typhoon intensity, and the changes in precipitation and surface latent heat flux were relatively small. These results suggested that the grid spacing of 2 km for simulations using no cumulus parameterization scheme or the grid spacing of 4 km for simulations using the rKF scheme facilitated reproducing the observed Typhoon Haiyan.     

中国过去300年土地利用变化及其气候效应

以两种植被数据为基础,分别利用区域和全球气候模式对过去300年土地利用和地表覆盖变化的气候效应进行了模拟研究。结果表明,耕地面积不断扩大所造成的自然植被破坏可能对区域性气候产生显著影响。通过对不同时期植被特征下地面温度、降水和低层大气环流的比较分析发现,中国东部地区耕地取代自然植被后,全年平均温度有所降低,且存在明显季节差异。植被退化地区的夏季温度有明显升高而冬季温度则显著降低; 同时夏季降水和850hPa风场发生显著变化： 夏季降水明显减少,而这一结果与低层(850hPa)大气环流的反气旋性增强相联系,即植被退化使中国东部夏季风环流减弱,这与目前观测事实是一致的。土地利用引起的地表覆盖的变化可能是东亚季风减弱的原因之一。     

PRECIS模式对宁夏气候变化情景的模拟分析*

使用英国Hadley气候中心区域气候模式PRECIS,分析了B2温室气体排放情景下,相对于气候基准时段1961~1990年宁夏2071~2100年(2080s)地面气温、降水量等的变化。结果表明:PRECIS模式能够很好地模拟宁夏气温的分布特征,对夏季最高气温的模拟效果好于冬季最低气温;较好地模拟出了宁夏降水南多北少的空间差异特征,且对夏季降水的模拟能力明显强于年均降水和冬季降水。相对于气候基准时段, 在B2情景下,2080s宁夏年平均、冬季和夏季平均气温均明显上升,宁夏北部和南部的部分地区气温上升幅度最大,夏季平均气温和最高气温上升幅度大于冬季平均气温和最低气温;未来宁夏年、冬季和夏季平均降水较基准时段均有所增加,但降水随年代际却呈减少趋势,由于气温和降水的气候变率加大,2080s宁夏出现高温、干旱、洪涝等异常天气事件的可能性增大。     

Simulation of severe thunder storm event: a case study over Pune,India

Numerical simulation of a typical tropical thunder storm event at Pune (18.53°N, 73.85°E), India, has been performed using the three nested domain configuration of Weather Research and Forecasting-Advanced Research Weather Model (version 3.2). The model simulations have been compared with observations. Sensitivity to cumulus parameterization schemes, namely Betts–Miller (BM), Grell–Devenyi (GD), and Kain–Fritsch (KF), for simulation of vertical structure and time evolution of weather parameters has been evaluated using observations from automatic weather station and global positioning system radiosonde ascents. Comparison of spatial distribution of 24-h accumulated rain with Tropical Rainfall Measuring Mission data shows that BM scheme could simulate better rain than GD and KF schemes. The BM scheme could well simulate the development of storm and heavy rain as it could generate sufficiently humid and deep layer in the lower and middle atmosphere, along with co-existence of updrafts and downdrafts and frozen hydrometeors at the middle level and rain water near the surface.     

Stochastic Simulation of Nonstationary Rainfall Fields, Accounting for Seasonality and Atmospheric Circulation Pattern Evolution

A model for generating daily spatial correlated rainfall fields suitable for evaluating the impacts of climate change on water resources is presented. The model, termed Stochastic Rainfall Generating Process, is designed to incorporate two major nonstationarities: changes in the frequencies of different precipitation generating mechanisms (frontal and convective), and spatial nonstationarities caused by interactions of mesoscale atmospheric patterns with topography (orographic effects). These nonstationarities are approximated as discrete sets of the time-stationary Stochastic Rainfall Generating Process, each of which represents the different spatial patterns of rainfall (including its variation with topography) associated with different atmospheric circulation patterns and times of the year (seasons). Each discrete Stochastic Rainfall Generating Process generates daily correlated rainfall fields as the product of two random fields. First, the amount of rainfall is generated by a transformed Gaussian process applying sequential Gaussian simulation. Second, the delimitation of rain and no-rain areas (intermittence process) is defined by a binary random function simulated by sequential indicator simulations. To explore its applicability, the model is tested in the Upper Guadiana Basin in Spain. The result suggests that the model provides accurate reproduction of the major spatiotemporal features of rainfall needed for hydrological modeling and water resource evaluations. The results were significantly improved by incorporating spatial drift related to orographic precipitation into the model.