Intercomparison of different physics schemes in the WRF model over the Asian summer monsoon region

WRF模式对包含西太平洋、东印度洋和中国大陆的大区域气候模拟能力的提高对东亚夏季风气候的预测非常重要。本文的研究目的是找出合理的物理方案组合来模拟中国大陆、东印度洋和西太平洋这一特大区域的降水和温度。通过模拟2008年夏季气候并与观测进行对比分析,主要比较了Mellor–Yamada–Janjic(MYJ)和Yonsei University(YSU)边界层方案、WSM3和WSM5微物理过程方案、Betts–Miller–Janjic(BMJ)和Tiedtke积云参数化方案对这一区域的气候模拟结果。研究表明:各种物理方案的组合对于温度空间分布的模拟与观测类似;边界层方案的选择对降水影响较大,MYJ方案比YSU方案对降水的模拟效果要好;积云方案Tiedtke对雨带分布,特别是赤道辐合带(ITCZ)降水模拟更加合理。     

Multiseason evaluation of the MM5, COAMPS and WRF over southeast United States

Three models, MM5, COAMPS, and WRF, have been applied for the warm season in 2003 and the cool season in 2003?C2004 to evaluate their performances. All models run over the same domain area covering the north Gulf Mexico and southeastern United States (US) region with the same spatial resolution of 27?km. It was found that the temporal variations of the mean error distribution and strength at 24 and 36?h were rather weak for surface temperature, sea level pressure, and surface wind speed for all models. A warm bias in surface temperature forecasts dominated over land during the warm season, whereas a cool bias existed during the cool season. The MM5 and WRF produced negative biases of sea level pressure during the warm season and positive biases during the cool season while the COAMPS yielded a similar distribution of sea level pressure biases during both seasons. During both seasons, similar surface wind speed biases produced by each model included a high wind speed forecast over most areas by MM5 while the COAMPS and WRF yielded weak surface winds over the western Plains and stronger surface winds over the eastern Plains. Root-mean-squared errors revealed that the forecast of surface temperature, sea level pressure, and surface wind speed were degraded with the increase of forecast time. For rainfall evaluation, it was found that the MM5 underpredicted seasonal precipitation while the COAMPS and WRF overpredicted. The bias scores revealed that the MM5 yielded an underprediction of the coverage of precipitation areas, especially for heavier rainfall events. The MM5 presented the lower threat score at lighter rainfall events compared to the COAMPS and WRF. For moderate and heavier thresholds, all models lacked forecast accuracy. The WRF accuracy in predicting precipitation was heavily dependent upon the performance of the selected cumulus parameterization scheme. Use of the Grell?CDevenyi and Bette?CMiller?CJanjic schemes helps suppress precipitation overprediction.     

Impact of assimilation of INSAT-3D retrieved atmospheric motion vectors on short-range forecast of summer monsoon 2014 over the South Asian region

The Weather Research and Forecasting (WRF) model and its three-dimensional variational data assimilation system are used in this study to assimilate the INSAT-3D, a recently launched Indian geostationary meteorological satellite derived from atmospheric motion vectors (AMVs) over the South Asian region during peak Indian summer monsoon month (i.e., July 2014). A total of four experiments were performed daily with and without assimilation of INSAT-3D-derived AMVs and the other AMVs available through Global Telecommunication System (GTS) for the entire month of July 2014. Before assimilating these newly derived INSAT-3D AMVs in the numerical model, a preliminary evaluation of these AMVs is performed with National Centers for Environmental Prediction (NCEP) final model analyses. The preliminary validation results show that root-mean-square vector difference (RMSVD) for INSAT-3D AMVs is ～3.95, 6.66, and 5.65 ms^?1 at low, mid, and high levels, respectively, and slightly more RMSVDs are noticed in GTS AMVs (～4.0, 8.01, and 6.43 ms^?1 at low, mid, and high levels, respectively). The assimilation of AMVs has improved the WRF model of produced wind speed, temperature, and moisture analyses as well as subsequent model forecasts over the Indian Ocean, Arabian Sea, Australia, and South Africa. Slightly more improvements are noticed in the experiment where only the INSAT-3D AMVs are assimilated compared to the experiment where only GTS AMVs are assimilated. The results also show improvement in rainfall predictions over the Indian region after AMV assimilation. Overall, the assimilation of INSAT-3D AMVs improved the WRF model short-range predictions over the South Asian region as compared to control experiments.     

Simulation of heavy rainfall events over Indian monsoon region using WRF-3DVAR data assimilation system

We present the results of the impact of the 3D variational data assimilation (3DVAR) system within the Weather Research and Forecasting (WRF) model to simulate three heavy rainfall events (25–28 June 2005, 29–31 July 2004, and 7–9 August 2002) over the Indian monsoon region. For each event, two numerical experiments were performed. In the first experiment, namely the control simulation (CNTL), the low-resolution global analyses are used as the initial and boundary conditions of the model. In the second experiment (3DV-ANA), the model integration was carried out by inserting additional observations in the model’s initial conditions using the 3DVAR scheme. The 3DVAR used surface weather stations, buoy, ship, radiosonde/rawinsonde, and satellite (oceanic surface wind, cloud motion wind, and cloud top temperature) observations obtained from the India Meteorological Department (IMD). After the successful inclusion of additional observational data using the 3DVAR data assimilation technique, the resulting reanalysis was able to successfully reproduce the structure of convective organization as well as prominent synoptic features associated with the mid-tropospheric cyclones (MTC). The location and intensity of the MTC were better simulated in the 3DV-ANA as compared to the CNTL. The results demonstrate that the improved initial conditions of the mesoscale model using 3DVAR enhanced the location and amount of rainfall over the Indian monsoon region. Model verification and statistical skill were assessed with the help of available upper-air sounding data. The objective verification further highlighted the efficiency of the data assimilation system. The improvements in the 3DVAR run are uniformly better as compared to the CNTL run for all the three cases. The mesoscale 3DVAR data assimilation system is not operational in the weather forecasting centers in India and a significant finding in this study is that the assimilation of Indian conventional and non-conventional observation datasets into numerical weather forecast models can help improve the simulation accuracy of meso-convective activities over the Indian monsoon region. Results from the control experiments also highlight that weather and regional climate model simulations with coarse analysis have high uncertainty in simulating heavy rain events over the Indian monsoon region and assimilation approaches, such as the 3DVAR can help reduce this uncertainty.     

Atmosphere data assimilation system for the Siberian region with the WRF-ARW model and three-dimensional variational analysis WRF 3D-Var

The system of the cyclic assimilation of data on atmospheric conditions used in the West Siberian Administration for Hydrometeorology and Environmental Monitoring is described. It is based on the WRF-ARW mesoscale atmospheric model and on the WRF 3D-Var system of the three-dimensional variational analysis of data. The system is verified when the first approximation data (6-hour forecast) and WRF-ARW forecasts with the lead time up to 24 hours are compared with the observational data. The problems of assimilation of observations from the AMSU-A and AIRS satellite instruments are considered. The effect of using AMSU-A and AIRS for the analysis in the Novosibirsk region is estimated. The experiments demonstrated that the cyclic data assimilation system operates successfully. The AMSU-A observations improve the quality of analyses and forecasts in winter. In summer the impact of satellite observations on the forecast skill scores is ambiguous. Good short-term forecasts are provided by the initial conditions obtained using the system of detailing of the NCEP large-scale analysis.     

雷达反射率资料的三维变分同化研究

应用天气研究和预报模式(WRF)三维变分系统中一种新的雷达反射率资料间接同化方法来进行反射率资料的三维变分同化研究,评估雷达反射率资料对夏季短时定量降水预报的作用.该方法不直接同化雷达反射率资料,而是同化由反射率资料反演出的雨水和估计的水汽.以2009年夏季北京地区发生的4次强降水过程为例,考察了北京市气象局业务运行的快速更新循环同化预报系统对京津冀地区雷达网的雷达反射率资料的同化性能以及雷达反射率资料和径向风资料同时同化的效果.数值试验结果表明:(1)同化反演雨水或水汽都能改善降水预报,但同化反演水汽对降水预报效果的改善起了更重要的作用;(2)同化反射率资料能极大地提高短时降水预报的效果,其稳定的正面效果可以延伸到6h的预报时效,而同化径向风资料不能得到稳定的正效果;(3)同化雷达资料时,应用快速更新循环同化预报系统是提高短时定量降水预报的一个有效途径.     

Impact of ECMWF,NCEP, and NCMRWF global model analysis on the WRF model forecast over Indian Region

The global model analysis has significant impact on the mesoscale model forecast as global model provides initial condition (IC) and lateral boundary conditions (LBC) for the mesoscale model. With this objective, four operational global model analyses prepared from the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS), NCEP Global Forecasting System (GFS), and National Centre for Medium Range Weather Forecasting (NCMRWF) are used daily to generate IC and LBC of the mesoscale model during 13th December 2012 to 13th January 2013. The Weather Research and Forecasting (WRF) model version 3.4, broadly used for short-range weather forecast, is adopted in this study as mesoscale model. After initial comparison of global model analyses with Atmospheric Infrared Sounder (AIRS) retrieved temperature and moisture profiles, daily WRF model forecasts initialized from global model analyses are compared with in situ observations and AIRS profiles. Results demonstrated that forecasts initialized from the ECMWF analysis are closer to AIRS-retrieved profiles and in situ observations compared to other global model analyses. No major differences are occurred in the WRF model forecasts when initialized from the NCEP GDAS and GFS analyses, whereas these two analyses have different spatial resolutions and observations used for assimilation. Maximum RMSD is seen in the NCMRWF analysis-based experiments when compared with AIRS-retrieved profiles. The rainfall prediction is also improved when WRF model is initialized from the ECMWF analysis compared to the NCEP and NCMRWF analyses.     

Evaluation of Forecast Performance of an Economical Explicit Time Integration Scheme in a Limited Area Model over Indian Region

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Intercomparison and Evaluation of MM5 and Meso-NH mesoscale models in the stable boundary layer

Atmospheric numerical models depend critically on realistic treatment of the lower boundary conditions. In strongly thermally-stratified conditions, turbulence may be very weak and the models may find it difficult to produce a good forecast near the surface. Under clear skies and for weak synoptic winds the determining factors are the turbulent kinetic energy and surface-layer parameterizations, which can be very different between models. Here, two state-of-the-art mesoscale models (MM5 and Meso-NH) are operated under exactly the same conditions for two different nights over the Duero basin in the Iberian Peninsula: one night with a well-defined synoptic wind and a second with practically no horizontal pressure gradient. The models are inter-compared and checked against available information, and their performances are evaluated.     

Impact of surface meteorological observations on RAMS forecast of monsoon weather systems over the Indian region

Summary An attempt has been made to study the impact of surface meteorological observations on the Regional Atmospheric Modelling System (RAMS) simulation of a monsoon depression and two low pressure systems. The surface observations are blended with the GEWEX Asian Monsoon Experiment (GAME) gridded analyses for these cases. In one set of experiments the model is run in 12 hour nudging mode initially and then in forecast mode using GAME gridded data without incorporating surface observations. In another set of experiments surface data are incorporated to enhance the signature of the systems in the large scale GAME analyses and nudging is applied initially for twelve hours. Subsequently the model is run in forecast mode to see the temporal and spatial evolution of different meteorological features associated with the systems. It is found that inclusion of the surface data has in general enhanced the signature of the systems in the analysis and subsequently shows improvement in the forecast of sea-level pressure, geopotential, wind field, etc. and the associated forecast of heavy rainfall, in particular. To make a quantitative comparison of the predicted rainfall with the observed one, equitable threat score and bias are calculated for different threshold values of rainfall. It is clearly noted that inclusion of surface data has improved the precipitation forecast over the Indian land mass as indicated by the equitable threat score and bias for all the threshold rainfall categories.     

Experiments of the WRF three-/four-dimensional variational (3/4DVAR) data assimilation in the forecasting of Antarctic cyclones

The three-/four-dimensional variational data assimilation systems (3/4DVAR) of the Weather Research and Forecasting (WRF) model were explored in the forecasting of two Antarctic synoptic cyclones, which had large influence on the Ross Sea/Ross Ice Shelf region in October 2007. A suite of variational data assimilation experiments, including regular 3DVAR, high-resolution 3DVAR, and 4DVAR experiments, were designed to evaluate their performances in weather analysis and forecasting in Antarctica. In general, both 4DVAR and high-resolution 3DVAR experiments showed better forecasting skill than regular 3DVAR experiments. High-resolution 3DVAR experiments were the most efficient in reducing the analysis errors of surface winds and temperature, and had the best performance during the first 24 h of forecasting. However, during the following forecast period, 4DVAR experiments showed either better or about comparable performance to high-resolution 3DVAR experiments. These results indicate that increasing the spatial resolution during 3DVAR is an economical approach to improving the weather analysis and forecasting over Antarctica. At the same time, the 4DVAR approach had a longer impact on forecasting than the high-resolution 3DVAR approach. Understandably, both of the variational assimilation approaches are promising techniques toward improving the regional analysis and forecasting over Antarctica.     

The performance of two convective parameterization schemes in a mesoscale model over the Indian region

Summary A comparative study has been carried out using two cumulus parameterization schemes, namely the Kain-Fritsch and Betts-Miller-Janjic schemes within the Atmospheric Regional Prediction System model. The performances of these two schemes are examined for four weather disturbances over the Indian region. The results are evaluated using predicted parameters such as mean sea level pressure, wind, temperature/moisture fields and rainfall. Rainfall and other predicted parameters are discussed on the basis of known synoptic features associated with the disturbances. Rainfall prediction is subjectively assessed based on the amount and spatial distribution. Results indicate that out of the four cases examined, in three, the Betts-Miller-Janjic scheme produced better results whilst in the fourth, the Kain-Fritsch scheme performed better. The Betts-Miller-Janjic convection scheme produced smoother and more convective rainfall rates in all cases.     

Mesoscale data assimilation and prediction of low stratus in the Alpine region

Summary A number of problems related to mesoscale numerical prediction of low stratus in the Alpine region are formulated, and addressed in a series of experiments for two wintertime cases. These problems include modelling aspects and issues of data assimilation which are relevant particularly in relation to the observation nudging technique. A focus is on the influence of orography.A comparison of operational optimum interpolation, and nudging of routine rawinsonde and surface-level data reveals that nudging often yields better analyses and forecasts of low stratus, and notably of the sharp vertical temperature and humidity gradients. However, the humidity advection scheme of the model and, near steep terrain, particularly the horizontal diffusion along the model's -levels are identified to contribute to spurious vertical smoothing which can result in erroneous cloud dissipation. On occasions, forecasts succeeding a nudging period are more sensitive to this process due to the sharper initial vertical gradients.Specific problems of representiveness arise when low-level rawinsonde information is spread laterally along the sloping -levels from low to high terrain. A new concept for -layer models is introduced by speading the observational information along isentropic surfaces, and this tends to improve the low stratus prediction over steep and even moderate orography. A partly successful attempt to take advantage of the steep Alpine orography is made by applying this concept to surface-level humidity data from a high-resolution network of Alpine surface stations which are distributed relatively uniformly in the vertical.With 19 Figures     

An ocean data assimilation system in the Indian Ocean and west Pacific Ocean

The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian and West Pacific oceans is an endeavor motivated by this goal. In this study, we describe the system in detail. Moreover, the reanalysis in the joint area of Asia, the Indian Ocean, and the western Pacific Ocean(hereafter AIPOcean) constructed using multi-year model integration with data assimilation is used to test the performance of this system. The ocean model is an eddy-resolving,hybrid coordinate ocean model. Various types of observations including in-situ temperature and salinity profiles(mechanical bathythermograph, expendable bathythermograph, Array for Real-time Geostrophic Oceanography, Tropical Atmosphere Ocean Array, conductivity–temperature–depth, station data), remotely-sensed sea surface temperature, and altimetry sea level anomalies, are assimilated into the reanalysis via the ensemble optimal interpolation method. An ensemble of model states sampled from a long-term integration is allowed to change with season, rather than remaining stationary. The estimated background error covariance matrix may reasonably reflect the seasonality and anisotropy. We evaluate the performance of AIPOcean during the period 1993–2006 by comparisons with independent observations, and some reanalysis products. We show that AIPOcean reduces the errors of subsurface temperature and salinity, and reproduces mesoscale eddies. In contrast to ECCO and SODA products, AIPOcean captures the interannual variability and linear trend of sea level anomalies very well. AIPOcean also shows a good consistency with tide gauges.     

MM5和WRF对中国东部地区冬季边界层模拟效果比较

应用MM5和WRF模式对2006年和2007年12月中国东部地区边界层气象要素进行了逐日模拟,利用地面常规观测资料及南京和安庆逐日探空资料对两个模式模拟的地面及边界层内气象要素进行了客观评估与比较。结果表明:MM5和WRF模式模拟的地面温度和相对湿度均较理想,风速效果略差;两个模式模拟的温、湿、风效果均是白天优于夜间;根据观测与模拟的相关性,对温度的模拟效果东部优于西部,相对湿度的模拟效果由东南向西北变差,风速模拟效果平原优于丘陵和山区。总体上,WRF模式对地面温度和湿度的模拟效果均优于MM5模式。以南京、安庆两站为例的边界层内气象要素模拟效果评估结果表明:MM5和WRF模式模拟的150 m以上边界层内温、风、湿廓线均较可信,150 m以下的效果略差,20:00比08:00(北京时)模拟效果好;总体上,WRF模式对温度和湿度的模拟效果较好,而MM5模式对风速模拟效果稍好;两个模式均能再现近地层逆温,都有高估逆温频率的倾向。     

Evolution of geophysical parameters over the Indian Ocean region during contrasting monsoon years of 2002 and 2003 using TRMM/TMI data

Summary The evolution of geophysical parameters over Indian Ocean during two contrasting monsoon years 2002 (drought) and 2003 (normal) were studied using TRMM/TMI satellite data. Analysis indicates that there was a lack of total water vapour (TWV) build up over Western Indian Ocean (WIO) during May 2002 (drought) when compared to 2003 (normal). Negative (positive) TWV anomalies were found over the WIO in May 2002 (2003). In 2002, negative SST anomaly of ∼1.5 °C is found over entire WIO when compared to 2003. Anomalously high sea surface wind speed (SWS) anomaly over the South West Indian Ocean (SWIO) and WIO would have resulted in cooling of the sea surface in May 2002 in comparison to 2003. In 2003 the wind speed anomaly over entire WIO and Arabian Sea (AS) was negative, whereas sea surface temperature (SST) anomaly was positive over the same region, which would have resulted in higher moisture availability over these regions. A negative (positive) TWV anomaly over Eastern Arabian Sea (EAS) and positive (negative) anomaly over WIO forms a dipole structure. In the month of June no major difference is seen in all these parameters over the Indian Ocean. In July 2002 the entire WIO and AS was drier by 10–15 mm as compared to 2003. The pentad (5 day) average TWV values shows high (>55 mm) TWV convergence over EAS and Bay of Bengal (BoB) during active periods of 2003, which gives high rainfall over these regions. However, during 2002 although TWV over BoB was >55 mm but it was ∼45–55 mm over EAS during entire July and hence less rainfall. The evaporation has been calculated from the bulk aerodynamic formula using TRMM/TMI geophysical products. It has been seen that the major portion of evaporative moisture flux is coming from southern Indian Ocean (SIO) between 15 and 25° S. Evaporation in June was more over AS and SIO in 2003 when compared to 2002 which may lead to reduce moisture supply in July 2002 and hence less rainfall compared to July 2003.     

Diurnal variation of deep cloud systems over the Indian region using INSAT-1B pixel data

Summary Among the various time scales of deep clouds, diurnal variation is found to be prominent over the tropics. The present study examines the diurnal variation in the number and area cover associated with the cloud systems over the tropical Indian region using INSAT-1B pixel data. Three periods, namely, April–May 1988, July–August 1988, and January–February 1989 are considered. The dependence of diurnal characteristics on the temperature threshold, life duration and size of cloud systems, and land-sea contrast has been explored. The diurnal characteristics of cloud systems living for more than a day have been studied for the first time. It is shown that cloud systems exhibit strong diurnal dependence at the coldest temperature threshold used (201 K). Also, the diurnal variation is more for larger cloud systems and for longer living systems. In general, more deep cloud activity is found from the satellite data during the pre-dawn and early morning hours. Precipitation is enhanced during morning to early noon hours. Further, using data from a recent field experiment, clear evidence of diurnal variation in precipitation over the Bay of Bengal is also presented. Received March 20, 2000/Revised October 3, 2000