Simulation of Tropical Cyclone Circulation Over the Bay of Bengal Using the Arakawa-Schubert Cumulus Parameterization. Part II: Some Sensitivity Experiments

—?The role of sea-surface temperature (SST) and Coriolis parameter in the evolution and intensification of tropical cyclones has been examined using the ten-level axi-symmetric primitive equation model described in the companion paper (Bhaskar Rao and Ashok, 1999). Two experiments have been conducted using the ten-level model to assess the role of Coriolis parameter “f” in tropical cyclone intensity and the size of the storm generated. Six experiments have been performed to assess the importance of Sea-Surface Temperature (SST) in tropical cyclogenesis and intensification. The initial thermodynamic field and the initial vortex are the same as that used to simulate the Bay of Bengal tropical cyclone discussed in the companion paper. Further sensitivity experiments indicated a strong dependency of the model on SSTs. The model initial vortex could not intensify with an SST of 299?K but could with an SST of 300?K. The increase of SST from 300?K to 300.5?K shows rapid intensification with a minimum central surface pressure of 910?hPa and a maximum tangential wind of 80?m/s. Further increase of SST only shows a marginal increase in intensity and a larger radius of maximum wind. Sensitivity experiments to assess the role of the Coriolis parameter suggest that tropical cyclones develop more intensity and are faster at relatively lower latitudes.     

Estimation of tropical cyclone parameters and wind fields from SAR images

The traditional method of Synthetic Aperture Radar(SAR)wind field retrieval is based on an empirical relation between the near surface winds and the normalized radar backscatter cross section to estimate wind speeds,where this relation is called the geophysical model function(GMF).However,the accuracy rapidly decreases due to the impact of rainfall on the measurement of SAR and the saturation of backscattered intensity under the condition of tropical cyclone.Because of no available instrument synchronously monitoring rain rate on the satellite platform of SAR,we have to derive the precipitation of the SAR observation time from non-simultaneous passive microwave observations of rain in combination with geostationary IR images,and then use the model of rain correction to remove the impact of rain on SAR wind field measurements.For the saturation of radar backscatter cross section in high wind speed conditions,we develop an approach to estimate tropical cyclone parameters and wind fields based on the improved Holland model and the SAR image features of tropical cyclone.To retrieve the low-to-moderate wind speed,the wind direction of tropical cyclone is estimated from the SAR image using wavelet analysis.And then the maximum wind speed and the central pressure of tropical cyclone are calculated by a least square minimization of the difference between the improved Holland model and the low-to-moderate wind speed retrieved from SAR.In addition,wind fields are estimated from the improved Holland model using the above-mentioned parameters of tropical cyclone as input.To evaluate the accuracy of our approach,the SAR images of typhoon Aere,typhoon Khanun,and hurricane Ophelia are used to estimate tropical cyclone parameters and wind fields,which are compared with the best track data and reanalyzed wind fields of the Joint Typhoon Warning Center(JTWC)and the Hurricane Research Division(HRD).The results indicate that the tropical cyclone center,maximum wind speed,and central pressure are generally consistent with the best track data,and wind fields agree well with reanalyzed data from HRD.     

A Study on the Impact of Observation Assimilation on the Numerical Simulation of Tropical Cyclones JAL and THANE Using 3DVAR

In this work, the impact of assimilation of conventional and satellite remote sensing observations (Oceansat-2 winds, MODIS temperature/humidity profiles) is studied on the simulation of two tropical cyclones in the Bay of Bengal region of the Indian Ocean using a three-dimensional variational data assimilation (3DVAR) technique. The Weather Research and Forecasting (WRF)-Advanced Research WRF (ARW) mesoscale model is used to simulate the severe cyclone JAL: 5–8 November 2010 and the very severe cyclone THANE: 27–30 December 2011 with a double nested domain configuration and with a horizontal resolution of 27 × 9 km. Five numerical experiments are conducted for each cyclone. In the control run (CTL) the National Centers for Environmental Prediction global forecast system analysis and forecasts available at 50 km resolution were used for the initial and boundary conditions. In the second (VARAWS), third (VARSCAT), fourth (VARMODIS) and fifth (VARALL) experiments, the conventional surface observations, Oceansat-2 ocean surface wind vectors, temperature and humidity profiles of MODIS, and all observations were respectively used for assimilation. Results indicate meager impact with surface observations, and relatively higher impact with scatterometer wind data in the case of the JAL cyclone, and with MODIS temperature and humidity profiles in the case of THANE for the simulation of intensity and track parameters. These relative impacts are related to the area coverage of scatterometer winds and MODIS profiles in the respective storms, and are confirmed by the overall better results obtained with assimilation of all observations in both the cases. The improvements in track prediction are mainly contributed by the assimilation of scatterometer wind vector data, which reduced errors in the initial position and size of the cyclone vortices. The errors are reduced by 25, 21, 38 % in vector track position, and by 57, 36, 39 % in intensity, at 24, 48, 72 h predictions, respectively, for the two cases using assimilation of all observations. Simulated rainfall estimates indicate that while the assimilation of scatterometer wind data improves the location of the rainfall, the assimilation of MODIS profiles produces a realistic pattern and amount of rainfall, close to the observational estimates.     

Assimilation of Doppler Weather Radar Data in WRF Model for Simulation of Tropical Cyclone Aila

For the accurate and effective forecasting of a cyclone, it is critical to have accurate initial structure of the cyclone in numerical models. In this study, Kolkata Doppler weather radar (DWR) data were assimilated for the numerical simulation of a land-falling Tropical Cyclone Aila (2009) in the Bay of Bengal. To study the impact of radar data on very short-range forecasting of a cyclone's path, intensity and precipitation, both reflectivity and radial velocity were assimilated into the weather research and forecasting (WRF) model through the ARPS data assimilation system (ADAS) and cloud analysis procedure. Numerical experiment results indicated that radar data assimilation significantly improved the simulated structure of Cyclone Aila. Strong influences on hydrometeor structures of the initial vortex and precipitation pattern were observed when radar reflectivity data was assimilated, but a relatively small impact was observed on the wind fields at all height levels. The assimilation of radar wind data significantly improved the prediction of divergence/convergence conditions over the cyclone's inner-core area, as well as its wind field in the low-to-middle troposphere (600–900 hPa), but relatively less impact was observed on analyzed moisture field. Maximum surface wind speed produced from DWR–Vr and DWR–ZVr data assimilation experiments were very close to real-time values. The impact of radar data, after final analysis, on minimum sea level pressure was relatively less because the ADAS system does not adjust for pressure due to the lack of pressure observations, and from not using a 3DVAR balance condition that includes pressure. The greatest impact of radar data on forecasting was realized when both reflectivity and wind data (DWR–ZVr and DWR–ZVr00 experiment) were assimilated. It is concluded that after final analysis, the center of the cyclone was relocated very close to the observed position, and simulated cyclone maintained its intensity for a longer duration. Using this analysis, different stages of the cyclone are better captured, and cyclone structure, intensification, direction of movement, speed and location are significantly improved when both radar reflectivity and wind data are assimilated. As compared to other experiments, the maximum reduction in track error was noticed in the DWR–ZVr and DWR–ZVr00 experiments, and the predicted track in these experiments was very close to the observed track. In the DWR–ZVr and DWR–ZVr00 experiments, rainfall pattern and amount of rainfall forecasts were remarkably improved and were similar to the observation over West Bengal, Orissa and Jharkhand; however, the rainfall over Meghalaya and Bangladesh was missed in all the experiments. The influence of radar data reduces beyond a 12-h forecast, due to the dominance of the flow from large-scale, global forecast system models. This study also demonstrates successful coupling of the data assimilation package ADAS with the WRF model for Indian DWR data.     

Simulation of Tropical Cyclone Circulation over Bay of Bengal Using the Arakawa-Schubert Cumulus Parametrization. Part I — Description of the Model, Initial Data and Results of the Control Experiment

—A ten-level axi-symmetric primitive equation model with cylindrical coordinates is used to simulate the tropical cyclone evolution from a weak vortex for the Bay of Bengal region. The physics of the model comprises the parameterization schemes of Arakawa-Schubert cumulus convection (Lord et al., 1982) and Deardorff’s (1972) planetary boundary layer. The initial conditions have been taken from the climate mean data for November of Port Blair (92.4 E, 11.4 N) in the Bay of Bengal, published by the India Meteorological Department. An initial vortex has been designed to have tangential wind maximum of 10 m/s at 120-km radius with a central surface pressure of 1008 hPa. As a control experiment, referred to as ASBB1, the model is integrated for 240 h maintaining the sea-surface temperature (SST) constant at 301 K. The results of the control experiment reveal a slow decrease of the Central Surface Pressure (CSP) from the initial value of 1008 hPa to 970 hPa at 156 h. After 156 h the CSP decreased sharply until 186 h, attaining 890 hPa. The tangential wind at 1 km level attained the Cyclone Threshold Intensity (CTI) of 17 m/s around 78 h and a maximum of 87 m/s was found at 210 h. These features indicate a predeveloping stage up to 156 h, a deepening stage of 30 h from 156–186 h followed by the mature stage. The mature stage is characterized by the simulation of the central eye region, warm core, strong cyclonic circulation in the central 300 km with low-level inflow; strong vertical motion at the eye wall and outflow aloft. The convection features of the different cloud types conform with the circulation features. The control experiment clearly indicates the evolution of a cyclone with hurricane intensity from a weak vortex. In part two of the paper, results from sensitivity experiments with respect to variations in latitude, SST and initial thermodynamic state have been presented.     

半个世纪来热带海洋风暴对中国大陆的影响

本文利用美国海军台风警报中心（JTWC）提供的1945～2002年热带风暴路径资料统计分析了西北太平洋（NWP）和中国南海（SCS）风暴生成及登陆中国大陆热带风暴的时空演变特征.季节变化上，NWP风暴登陆主要集中于6～11月，SCS风暴影响主要集中在6～9月，但后者登陆总数比前者少.西北太平洋风暴在东南沿海(27°N，120°E)附近登陆的频次最高，在此以北随纬度急剧下降.年际变化时间尺度上，登陆大陆的风暴年总数与来自南海的年风暴数成正比.登陆我国的热带风暴年频数有明显的区域差异和显著的2～7年振荡.长期趋势上，两个海域的风暴年生成频数和登陆大陆的年风暴频数在58年中总体呈线性增长趋势，其中登陆频数增长趋势相对缓慢，但近几年登陆风暴数与生成风暴数都表现出减少的趋势.生成频数和登陆频数都呈现出年代际变化，其年代转换发生在1960、1970年和1990年前后.     

Impact of Doppler Radar Wind in Simulating the Intensity and Propagation of Rainbands Associated with Mesoscale Convective Complexes Using MM5-3DVAR System

Pre-monsoon rainfall around Kolkata (northeastern part of India) is mostly of convective origin as 80% of the seasonal rainfall is produced by Mesoscale Convective Systems (MCS). Accurate prediction of the intensity and structure of these convective cloud clusters becomes challenging, mostly because the convective clouds within these clusters are short lived and the inaccuracy in the models initial state to represent the mesoscale details of the true atmospheric state. Besides the role in observing the internal structure of the precipitating systems, Doppler Weather Radar (DWR) provides an important data source for mesoscale and microscale weather analysis and forecasting. An attempt has been made to initialize the storm-scale numerical model using retrieved wind fields from single Doppler radar. In the present study, Doppler wind velocities from the Kolkata Doppler weather radar are assimilated into a mesoscale model, MM5 model using the three-dimensional variational data assimilation (3DVAR) system for the prediction of intense convective events that occurred during 0600 UTC on 5 May and 0000 UTC on 7 May, 2005. In order to evaluate the impact of the DWR wind data in simulating these severe storms, three experiments were carried out. The results show that assimilation of Doppler radar wind data has a positive impact on the prediction of intensity, organization and propagation of rain bands associated with these mesoscale convective systems. The assimilation system has to be modified further to incorporate the radar reflectivity data so that simulation of the microphysical and thermodynamic structure of these convective storms can be improved.     

Mechanism for initial brows-like meso-scale vortex effects on tropical cyclone track

We used a two-dimensional quasi-geostrophic barotropic model simulation to study effects of an initial brows-like meso-scale vortex on tropical cyclone(TC) track.Our results show that the impact of each of the three foundational factors(the environmental current,the asymmetric structure and the asymmetric convection system) on TC track varies with time and the importance of each of the factors is different for the different TC motion time period.They show two kinds of the effects.One is a direct way.The asymmetric outer wind structure and the positive longitudinal wind speed averaged in radial-band(100-300) km in the period of(0-11) h are caused by the introduction of the initial brows-like meso-scale vortex,which results in TC track to turn to the north from the northwest directly.The other is an indirect influence.First,initial TC axisymmetric circulation becomes a non-axisymmetric circulation after the addition of the meso-scale vortex.The initial non-axisymmetric circulation experiences an axisymmetrizational process in the period of(0-11) h.Second,axisymmetrizationed TC horizontal size is enlarged after t=12 h.Third,both the TC asymmetric structure and the TC energy dispersion induced-anticyclone are intensified,which quickens the TC motion and results in the track to turn to the north indirectly.The TC motion is characterized by the unusual track under the direct and the indirect effect.The formation of the unusual track should be attributed to the common effects of three factors,including the environmental flow,the TC asymmetric structure and the asymmetric convection system.     

Development and evaluation of a storm surge warning system in Taiwan

An operational storm surge forecasting system aimed at providing warning information for storm surges has been developed and evaluated using four typhoon events. The warning system triggered by typhoon forecasts from Taiwan Cooperative Precipitation Ensemble Forecast Experiment (TAPEX) has been executed with two storm surge forecasting scenarios with and without tides. Three numerical experiments applying different meteorological inputs have been designed to assess the impact of typhoon forcing on storm surges. One uses synthetic wind fields, and the others use realistic wind fields with and without adjustments to the initial wind fields for the background circulation. Local observations from Central Weather Bureau (CWB) weather stations and tide gauge stations are used to evaluate the wind fields and storm surges from our numerical experiments. The comparison results show that the accuracy of the storm surge forecast is dominated by the track, the intensity, and the driving flow of a typhoon. When the structure of a typhoon is disturbed by Taiwan’s topography, using meteorological inputs from real wind fields can result in a better typhoon simulation than using inputs from synthetic wind fields. The driving flow also determines the impact of topography on typhoon movement. For quickly moving typhoons, storm forcing from TAPEX is reliable when a typhoon is strong enough to be relatively unaffected by environmental flows; otherwise, storm forcing from a sophisticated typhoon initialization scheme that better simulates the typhoon and environmental flows results in a more accurate prediction of storm surges. Therefore, when a typhoon moves slowly and interacts more with the topography and environmental flows, incorporating realistic wind fields with adjustments to the initial wind fields for the background circulation in the warning system will obtain better predictions for a typhoon and its resultant storm surges.     

Wind fluctuations near a cold vortex-tropopause funnel system observed by the MU radar

Vertical and temporal variations of three-dimensional wind velocity associated with an upper-tropospheric cold vortex-tropopause funnel system were observed by an MST radar in Japan (the MU radar). Marked changes of vertical velocity and horizontal wind direction were found between the inside and outside of the cold vortex. The vertical velocity activity outside the vortex was asymmetric; it was most active in a sector before the vortex. Unsaturated internal gravity waves in their generation stage contribute predominantly to the vertical velocity activity, suggesting that tropospheric occluded cyclones may be a possible source of middle-atmospheric gravity waves through the geostrophic adjustment process.     

Improving global rainfall forecasting with a weather type approach in Japan

An automated version of the weather type classification scheme was performed over Japan to characterize daily circulation conditions. A daily gridded field of mean sea-level pressure (MSLP) from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis dataset (ERA-interim) and the THORPEX Interactive Grand Global Ensemble (TIGGE) daily forecast dataset were used. The weather type is advantageous as it provides an opportunity to improve global rainfall prediction by refining statistical bias correction. We distinguished 11 weather types: anticyclone, cyclone, hybrid and eight purely wind directions. The results indicate that the main weather types contributing to the total volume of rainfall are cyclone, hybrid, purely westerly and northwest winds. A gamma-based bias correction decreases the global rainfall forecast root mean square by 10%, while specific weather type gamma bias correction accounts for 5–10% root mean square error reduction, with a total decrease of errors up to a maximum of 20%. Both global and weather type bias corrections improve the extreme dependency scores (EDS), but for different extreme rainfall thresholds. The study advocates the use of weather type bias-correction methods for extreme event rainfall intensity corrections higher than 100 mm/d.

EDITOR

A. Castellarin

ASSOCIATE EDITOR

A. Jain     

Impact of tropical cyclones on the evolution of the monsoon-driven upwelling system in the coastal waters of the northern South China Sea

An upwelling system exists in the coastal waters of the northern South China Sea (NSCS), a region that is frequently affected by tropical cyclones in summer. This study investigates the evolution of the NSCS monsoon-driven upwelling system and the effects of the Talim and Doksuri tropical cyclones on the system using in situ observational data obtained at three mooring stations, one land-based meteorological station, and concurrent satellite remote sensing data for the NSCS coastal waters from May to July 2012. The results show that the occurrence and evolution of the upwelling system were mainly controlled by the Asian southwest monsoon, while the eastward current also made important contributions to the upwelling intensity. A decrease in the bottom water temperature and shifts in the along-shore and cross-shore currents were direct evidence of the establishment, existence, and recovery of this upwelling. Tropical cyclones have significant impacts on hydrodynamics and can thus influence the evolution of the NSCS upwelling system by changing the local wind and current fields. Variations in water level and local current systems impeded the development of upwelling during tropical cyclones Talim and Doksuri in the study area, which have low-frequency fluctuations of approximately 2–10 days. These variations were the results of the coupled interactions between local wind fields, coastal trapped waves, and other factors. The hydrodynamic environment of the marine water (including coastal upwelling system) rapidly recovered to normal sea conditions after each cyclone passed due to the relatively short duration of the impact of a tropical cyclone on the dynamic environment of the waters.     

北欧气旋风暴与欧亚大陆的震动

全球地震台网(GSN)及中国地震台网(CENC)的地震观测数据分析表明:由北大西洋、北冰洋等海域进入北欧的强冷涡气旋(北欧风暴)能引发与其过程相关联的震动,其中由挪威海登陆斯堪的纳维亚半岛的强气旋风暴引发的震动波,几乎可以被整个欧亚大陆的地震仪观测到,该震动主要包含两个信号:一个主频为0.15~0.25 Hz(周期约4~7 s);而另一个是主频为0.08~0.12 Hz(周期8~12 s)的面波信号,它们分别来自不同的产生机理.不同海域和地区的风暴引发的震动信号存在差异,与气旋运动路径经过的地形地貌特征有关,气旋经过的浅海区域、海水深度、登陆地点的地形以及气旋的结构、观测点相对气旋的分布等因素决定了气旋在运动中激发有独特的震动信号.地震观测可以监测气旋在时间和空间的发展变化过程,有助于探索气旋运动过程中与地球表面的相互作用对气旋的影响.     

A semi-empirical wind set-up forecasting model for Lake Champlain

The precision of Lake Champlain's water level estimation is a key component in the flood forecasting process for the Richelieu River. Hydrological models do not typically take into consideration the effects of the wind on the water level (also known as the wind set-up). The objective of this study is to create an empirical wind set-up forecast model for Lake Champlain during high wind events. The proposed model uses wind speed and direction across the Lake, as well as wind gusts as inputs. The model is calibrated to a subset of observations and evaluated on an independent sample, considering four wind speed bins. It is tested and compared to a variant of the Zuider Zee equation on 20 wind set-up events that occurred between 2017 and 2019 using hindcast data from five different numerical weather prediction systems (GDPS, RDPS, HRDPS, NOAA and ECMWF). A quantile mapping-based forecast calibration scheme is implemented for each of the forecast products to correct their biases. Results show that events are successfully predicted by the proposed model at least 72 h in advance. These results are better than the other comparative models found in the literature and tested herein. Overall, significant improvements are obtained by including wind speed and wind gusts from different weather stations.     

Simulations of Severe Tropical Cyclone Nargis over the Bay of Bengal Using RIMES Operational System

The Regional Integrated Multi-Hazard Early Warning System (RIMES), an international, intergovernmental organization based in Thailand is engaged in disaster risk reduction over the Asia–Pacific region through early warning information. In this paper, RIMES’ customized Weather Research Forecast (WRF) model has been used to evaluate the simulations of cyclone Nargis which hit Myanmar on 2 May 2008, the most deadly severe weather event in the history of Myanmar. The model covers a domain of 35oE to 145oE in the east—west direction and 12oS to 40oN in the north—south direction in order to cover Asia and east Africa with a resolution of 9?km in the horizontal and 28 vertical levels. The initial and boundary conditions for the simulations were provided by the National Center for Environmental Prediction-Global Forecast System (NCEP-GFS) available at 1o lon/lat resolution. An attempt is being made to critically evaluate the simulation of cyclone Nargis by seven set of simulations in terms of track, intensity and landfall time of the cyclone. The seven sets of model simulations were initialized every 12?h starting from 0000 UTC 28 April to 01 May 2008. Tropical Rainfall Measurement Mission (TRMM) precipitation (mm) is used to evaluate the performance of the simulations of heavy rainfall associated with the tropical cyclone. The track and intensity of the simulated cyclone are compared by making use of Joint Typhoon Warning Center (JTWC) data sets. The results indicate that the landfall time, the distribution and intensity of the rainfall, pressure and wind field are well simulated as compared with the JTWC estimates. The average landfall track error for all seven simulations was 64?km with an average time error of about 5?h. The average intensity error of central pressure in all the simulations were found out to be approximately 6?hPa more than the JTWC estimates and in the case of wind, the simulations under predicted it by an average of 12?m?s^?1.     

Impact of ATOVS Radiance on the Analysis and Forecasts of a Mesoscale Model over the Indian Region During the 2008 Summer Monsoon

Assimilation experiments are performed with the Weather Research and Forecasting (WRF) models’ three-dimensional variational data assimilation (3D-Var) scheme to evaluate the impact of directly assimilating the Advanced Television and Infrared Observation Satellite Operational Vertical Sounder (ATOVS) radiance, including AMSU-A, AMSU-B and HIRS, on the analysis and forecasts of a mesoscale model over the Indian region. The present study is, to our knowledge, the first where the impact of ATOVS radiance has been evaluated on the analysis and forecasts of a mesoscale model over the Indian region. The control (without ATOVS radiance) as well as experimental (which assimilated ATOVS radiance) run were made for 48 h starting at 0000 UTC during the entire July 2008. The impacts of assimilating the radiances from different instruments (e.g., AMSU-A, AMSU-B and HIRS) were measured in comparison to the control run. The assimilation experiments for July 2008 (30 cases) demonstrated a positive impact of the assimilated ATOVS radiance on both the analysis state as well as subsequent short-range forecasts. Relative to the control run, the moisture analysis was improved with the assimilation of AMSU-B and HIRS radiance, while AMSU-A was mainly responsible for improved temperature analysis. The comparison of the model-predicted temperature, moisture and wind with NCEP analysis indicated that a positive forecast impact is achieved from each of the three instruments. HIRS and AMSU-A radiance yielded only a slight positive forecast impact, while AMSU-B radiance had the largest positive forecast impact for moisture, temperature and wind. The comparison of model-predicted rainfall with observed rainfall indicates that ATOVS radiance, particularly AMSU-B and HIRS, impacted the rainfall positively. This study clearly shows that the improved analysis of mid-tropospheric moisture, due to the assimilation of AMSU-B radiances, is a key factor to improve the short-term forecast skill of a mesoscale model.     

Improvement of Local Categorical Precipitation Forecasts from an NWP Model by Various Statistical Postprocessing Methods

Several statistical postprocessing methods are applied to results from a numerical weather prediction (NWP) model to test the potential for increasing the accuracy of its local precipitation forecasts. Categorical (Yes/No) forecasts for 12hr precipitation sums equalling or exceeding 0.1, 2.0 and 5.0 mm are selected for improvement. The two 12hr periods 0600-1800 UTC and 1800-0600 UTC are treated separately based on NWP model initial times 0000 UTC and 1200 UTC, respectively. Input data are taken from three successive summer seasons, April-September, 1994-96. The forecasts are prepared and verified for five synoptic stations, four located in the western Czech Republic, and one in Germany near the Czech-German border. Two approaches to statistical postprocessing are tested. The first uses Model Output Statistics (MOS) and the second modifies the MOS approach by applying a successive learning technique (SLT). For each approach several statistical models for the relationship between NWP model predictors and predictand were studied. An independent data set is used for forecast verification with the skill measured by a True Skill Score. The results of the statistical postprocessing are compared with the direct model precipitation forecasts from gridpoints nearest the stations, and they show that both postprocessing approaches provide substantially better forecasts than the direct NWP model output. The relative improvement increases with increasing precipitation amount and there is no significant difference in performance between the two 12hr periods. The skill of the SLT does not depend significantly on the size of the initial learning sample, but its results are nevertheless comparable with the results obtained from the MOS approach, which requires larger developmental samples.     

Relationship between the Asian-Pacific oscillation and the tropical cyclone frequency in the western North Pacific

The relationship between the Asian-Pacific oscillation (APO) and the tropical cyclone frequency over the western North Pacific (WNP) in summer is preliminarily investigated through an analysis of ob- served data. The result has shown clearly that APO is significantly and positively correlated to the tropical cyclone frequency in the WNP. If APO is above (below) the normal in summer, more (less) tropical cyclones will tend to appear in the WNP. The present study also addresses the large-scale at- mospheric general circulation changes underlying the linkage between APO and the WNP tropical cy- clone frequency. It follows that a positive phase of summer APO is concurrent with weakened as well as northward and eastward located western Pacific subtropical high (WPSH), low-level convergence and high-level divergence, and reduced vertical zonal wind shear in the WNP, providing favorable envi- ronment for the tropical cyclone genesis, and thus more tropical cyclones will come into being, and vice versa.     

Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5

The identification of the model discrepancy and skill is crucial when a forecast is issued. The characterization of the model errors for different cumulus parameterization schemes (CPSs) provides more confidence on the model outputs and qualifies which CPSs are to be used for better forecasts. Cases of good/bad skill scores can be isolated and clustered into weather systems to identify the atmospheric structures that cause difficulties to the forecasts. The objective of this work is to study the sensitivity of weather forecast, produced using the PSU-NCAR Mesoscale Model version 5 (MM5) during the launch of an Indian satellite on 5th May, 2005, to the way in which convective processes are parameterized in the model. The real-time MM5 simulations were made for providing the weather conditions near the launch station Sriharikota (SHAR). A total of 10 simulations (each of 48 h) for the period 25th April to 04th May, 2005 over the Indian region and surrounding oceans were made using different CPSs. The 24 h and 48 h model predicted wind, temperature and moisture fields for different CPSs, namely the Kuo, Grell, Kain-Fritsch and Betts-Miller, are statistically evaluated by calculating parameters such as mean bias, root-mean-squares error (RMSE), and correlation coefficients by comparison with radiosonde observation. The performance of the different CPSs, in simulating the area of rainfall is evaluated by calculating bias scores (BSs) and equitable threat scores (ETSs). In order to compute BSs and ETSs the model predicted rainfall is compared with Tropical Rainfall Measuring Mission (TRMM) observed rainfall. It was observed that model simulated wind and temperature fields by all the CPSs are in reasonable agreement with that of radiosonde observation. The RMSE of wind speed, temperature and relative humidity do not show significant differences among the four CPSs. Temperature and relative humidity were overestimated by all the CPSs, while wind speed is underestimated, except in the upper levels. The model predicted moisture fields by all CPSs show substantial disagreement when compared with observation. Grell scheme outperforms the other CPSs in simulating wind speed, temperature and relative humidity, particularly in the upper levels, which implies that representing entrainment/detrainment in the cloud column may not necessarily be a beneficial assumption in tropical atmospheres. It is observed that MM5 overestimates the area of light precipitation, while the area of heavy precipitation is underestimated. The least predictive skill shown by Kuo for light and moderate precipitation asserts that this scheme is more suitable for larger grid scale (>30 km). In the predictive skill for the area of light precipitation the Betts-Miller scheme has a clear edge over the other CPSs. The evaluation of the MM5 model for different CPSs conducted during this study is only for a particular synoptic situation. More detailed studies however, are required to assess the forecast skill of the CPSs for different synoptic situations.     

Field campaign for the comparison of SOUSY radar wind measurements with rawinsonde and model data

A field campaign was carried out from 26 October to 7 November 1992, using the SOUSY-VHF radar and a mobile rawinsonde system installed and operated nearby to produce vertical wind profiles. The purpose of this campaign was to compare the two types of wind measurements with one another and with results from forecast models. Numerical algorithms were developed and applied to the radar data in order to eliminate random errors, correct for velocity aliasing, and calculate the effective zenith angle of the off-vertical beams. Differences between wind profiler data and rawinsonde or model results depend not only upon the errors of the different systems, but also on temporal and spatial variations of the wind field. Therefore, methods for the comparison of radar and rawinsonde data were developed which take into consideration these variations. The practical potential of these methods is demonstrated by comparisons of rawinsonde and radar wind profiles. The comparison of radar data and model output shows excellent agreement in the direction and in the speed of the wind at virtually all altitudes. An evaluation of the quality of wind profiler measurements is possible using the estimation of variance and variability of wind components.