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1.
本文针对中国暴雨发生发展天气特征,改进和发展了一种适合于描述东亚暴雨的中尺度积云参数化方案.首先基于近年来(1990—2010)江淮流域汛期降水合成分析的基础上,诊断出组织化对流降水环境的动力参数;其次利用该动力参数作为动力控制条件,改进了Kain-Fritsch Eta中尺度积云对流参数化方案;最后利用改进的中尺度积云参数化方案对梅雨期暴雨、华南前汛期暴雨过程进行了数值模拟,结果表明:改进后的中尺度积云参数化方案对上述两次暴雨过程的落区及强度的模拟,均有明显改进. 相似文献
2.
Ernst Kerkhoven Thian Yew Gan Michiharu Shiiba Gerhard Reuter Kenji Tanaka 《水文研究》2006,20(9):1961-1978
In order to evaluate cumulus parameterization (CP) schemes for hydrological applications, the Pennsylvania State University–National Center for Atmospheric Research's fifth‐generation mesoscale model (MM5) was used to simulate a summer monsoon in east China. The performances of five CP schemes (Anthes–Kuo, Betts–Miller, Fritsch–Chappell, Kain–Fritsch, and Grell) were evaluated in terms of their ability to simulate amount of rainfall during the heavy, moderate, and light phases of the event. The Grell scheme was found to be the most robust, performing well at all rainfall intensity and spatial scales. The Betts–Miller scheme also performed well, particularly at larger scales, but its assumptions may make it inapplicable to non‐tropical environments and at smaller scales. The Kain–Fritsch scheme was the best at simulating moderate rainfall rates, and was found to be superior to the Fritsch–Chappell scheme on which it was based. The Anthes–Kuo scheme was found to underpredict precipitation consistently at the mesoscale. Simulation performance was found to improve when schemes that included downdrafts were used in conjunction with schemes that did not include downdrafts. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
3.
本文利用中尺度模式Weather Research and Forecasting Model (WRF) 3.1版本及National Centers for Environmental Prediction (NCEP)分析资料,就2003年6月下旬我国江淮及南方地区的强降水事件, 以24 h短期天气模拟的方式,研究了模式中四个不同陆面方案对降水模拟的影响.结果表明,此次暴雨事件模拟对不同陆面方案是比较敏感的,模拟区域内雨量级别越高,不同方案的TS评分差异就越大,较大范围雨量可存在30%的差异,四种方案的暴雨中心值可存在100%～150%的较大差别;不同陆面方案还导致了模拟平均感热通量及潜热通量的系统性差异,这些差异的分布具有地域特点;陆面方案通过两种机理对模拟降水产生重要影响,即主要影响地表蒸发量,以及主要影响低层环流及水汽辐合,从而分别影响模拟的较大范围降水(如,平均约7%、最大约30%的较大范围雨量差异)及包含模拟降水中心的较小范围暴雨(如,方案间暴雨中心雨量可存在100%～150%的较大差别).可见,不同陆面过程可从不同空间尺度、不同程度上影响暴雨天气,改进陆面方案可以提高WRF模式对暴雨的模拟能力. 相似文献
4.
The overall objective of this study is to improve the forecasting accuracy of the precipitation in the Singapore region by means of both rainfall forecasting and nowcasting. Numerical Weather Predication (NWP) and radar‐based rainfall nowcasting are two important sources for quantitative precipitation forecast. In this paper, an attempt to combine rainfall prediction from a high‐resolution mesoscale weather model and a radar‐based rainfall model was performed. Two rainfall forecasting methods were selected and examined: (i) the weather research and forecasting model (WRF); and (ii) a translation model (TM). The WRF model, at a high spatial resolution, was run over the domain of interest using the Global Forecast System data as initializing fields. Some heavy rainfall events were selected from data record and used to test the forecast capability of WRF and TM. Results obtained from TM and WRF were then combined together to form an ensemble rainfall forecasting model, by assigning weights of 0.7 and 0.3 weights to TM and WRF, respectively. This paper presented results from WRF and TM, and the resulting ensemble rainfall forecasting; comparisons with station data were conducted as well. It was shown that results from WRF are very useful as advisory of anticipated heavy rainfall events, whereas those from TM, which used information of rain cells already appearing on the radar screen, were more accurate for rainfall nowcasting as expected. The ensemble rainfall forecasting compares reasonably well with the station observation data. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
5.
利用WRF模式探讨了两种近地层参数化方案(MM5方案和Eta方案)对2013年5月31日海南岛一次海风降水过程模拟的影响.结果表明,改变近地层方案可对当地的海风环流及相应的降水特征产生明显影响,两个试验最重要的差别主要体现在模拟的海风及降水的强度差异上,与MM5试验相比,Eta试验的低层海风及辐合程度更强,相应的降水也更强,表现为岛屿总格点降水量、大于10mm的降水区域、最大格点降水三个量化指标均比较大.通过分析两种方案在不同降水阶段的地表通量及近地层变量场,发现Eta试验模拟的降水前环境场更有利于对流的启动,随着午后热力湍流的不断增强,将MM5方案替换为Eta方案可使近地层感热通量、潜热通量分别增加约3.57%、5.65%,动量通量减小约10.79%,感热、潜热的增加使Eta试验中近地层大气的加热加湿作用更加明显,相应的低层大气不稳定度更高,再配合海风锋前较强的辐合上升运动,局地不稳定能量的释放变的更加容易,因此降水强度更大. 相似文献
6.
Sustainable water resources management require scientifically sound information on precipitation, as it plays a key role in hydrological responses in a catchment. In recent years, mesoscale weather models in conjunction with hydrological models have gained great attention as they can provide high‐resolution downscaled weather variables. Many cumulus parameterization schemes (CPSs) have been developed and incorporated into three‐dimensional Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) mesoscale model 5 (MM5). This study has performed a comprehensive evaluation of four CPSs (the Anthes–Kuo, Grell, Betts–Miller and Kain–Fritsch93 schemes) to identify how their inclusion influences the mesoscale model's precipitation estimation capabilities. The study has also compared these four CPSs in terms of variability in rainfall estimation at various horizontal and vertical levels. For this purpose, the MM5 was nested down to resolution of 81 km for Domain 1 (domain span 21 × 81 km) and 3 km for Domain 4 (domain span 16 × 3 km), respectively, with vertical resolutions at 23, 40 and 53 vertical levels. The study was carried out at the Brue catchment in Southwest England using both the ERA‐40 reanalysis data and the land‐based observation data. The performances of four CPs were evaluated in terms of their ability to simulate the amount of cumulative rainfall in 4 months in 1995 representing the four seasonal months, namely, January (winter), March (spring), July (summer) and October (autumn). It is observed that the Anthes–Kuo scheme has produced inferior precipitation values during spring and autumn seasons while simulations during winter and summer were consistently good. The Betts–Miller scheme has produced some reasonable results, particularly at the small‐scale domain (3 km grid size) during winter and summer. The KF2 scheme was the best scheme for the larger‐scale (81 km grid size) domain during winter season at both 23 and 53 vertical levels. This scheme tended to underestimate rainfall for other seasons including the small‐scale domain (3 km grid size) in the mesoscale. The Grell scheme was the best scheme in simulating rainfall rates, and was found to be superior to other three schemes with consistently better results in all four seasons and in different domain scales. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
7.
Accurate information of rainfall is needed for sustainable water management and more reliable flood forecasting. The advances in mesoscale numerical weather modelling and modern computing technologies make it possible to provide rainfall simulations and forecasts at increasingly higher resolutions in space and time. However, being one of the most difficult variables to be modelled, the quality of the rainfall products from the numerical weather model remains unsatisfactory for hydrological applications. In this study, the sensitivity of the Weather Research and Forecasting (WRF) model is investigated using different domain settings and various storm types to improve the model performance of rainfall simulation. Eight 24‐h storm events are selected from the Brue catchment, southwest England, with different spatial and temporal distributions of the rainfall intensity. Five domain configuration scenarios designed with gradually changing downscaling ratios are used to run the WRF model with the ECMWF 40‐year reanalysis data for the periods of the eight events. A two‐dimensional verification scheme is proposed to evaluate the amounts and distributions of simulated rainfall in both spatial and temporal dimensions. The verification scheme consists of both categorical and continuous indices for a first‐level assessment and a more quantitative evaluation of the simulated rainfall. The results reveal a general improvement of the model performance as we downscale from the outermost to the innermost domain. Moderate downscaling ratios of 1:7, 1:5 and 1:3 are found to perform better with the WRF model in giving more reasonable results than smaller ratios. For the sensitivity study on different storm types, the model shows the best performance in reproducing the storm events with spatial and temporal evenness of the observed rainfall, whereas the type of events with highly concentrated rainfall in space and time are found to be the trickiest case for WRF to handle. Finally, the efficiencies of several variability indices are verified in categorising the storm events on the basis of the two‐dimensional rainfall evenness, which could provide a more quantitative way for the event classification that facilitates further studies. It is important that similar studies with various storm events are carried out in other catchments with different geographic and climatic conditions, so that more general error patterns can be found and further improvements can be made to the rainfall products from mesoscale numerical weather models. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
8.
The evolution and structure of rainstorms associated with a flash‐flood event are simulated by the Advanced Weather Research and Forecasting (WRF‐ARW) model of the National Center for Atmospheric Research and the Gridpoint Statistical Interpolation (GSI) data assimilation (DA) system of the National Oceanic and Atmospheric Administration (NOAA) of the United States. The event is based on a flash flood that occurred in the central Guangdong Province of south‐east China during 20–21 June 2005. Compared to an hourly mixed rain‐gauge and satellite‐retrieved precipitation data, the model shows the capability to reproduce the intensity and location of rainfall; however, the simulation depends on three conditions to a large extent: model resolution, physical processes schemes and initial condition. In this case, the Eta Ferrier microphysics scheme and the initialization with satellite radiance DA with a fine 4‐km grid spacing nested grid and coarse 12‐km grid spacing outer grid are the best options. The model‐predicted rain rates, however, are slightly overestimated, and the activities of the storms do not precisely correspond with those observed, although peak values are obtained. Abundant moisture brought by the south‐westerly winds with a mesoscale low‐level jet from the South China Sea or Bay of Bengal and trapped within the XingfengJiang region encompassed by northern Jiulian, southern Lianhua and eastern small mountains are apparently the primary elements responsible for the flood event. All simulated rainstorms were initiated over the southern slopes of the Jiulian Mountain and moved south or north‐eastward within the Xingfengjiang region. Meanwhile, the Skew‐T/Log‐P diagrams show that there is a fairly high convective available potential energy (CAPE) over the active areas of the rainstorms. The higher CAPE provides a beneficial thermodynamic condition for the development of rainstorms, but the higher convective inhibition near the northern, eastern and southern mountains prohibits the storms from moving out of the region and causes heavy rainfall that is trapped within the area. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
9.
The mesoscale Numerical Weather Prediction (NWP) model is gaining popularity among the hydrometeorological community in providing high‐resolution rainfall forecasts at the catchment scale. Although the performance of the model has been verified in capturing the physical processes of severe storm events, the modelling accuracy is negatively affected by significant errors in the initial conditions used to drive the model. Several meteorological investigations have shown that the assimilation of real‐time observations, especially the radar data can help improve the accuracy of the rainfall predictions given by mesoscale NWP models. The aim of this study is to investigate the effect of data assimilation for hydrological applications at the catchment scale. Radar reflectivity together with surface and upper‐air meteorological observations is assimilated into the Weather Research and Forecasting (WRF) model using the three‐dimensional variational data‐assimilation technique. Improvement of the rainfall accumulation and its temporal variation after data assimilation is examined for four storm events in the Brue catchment (135.2 km2) located in southwest England. The storm events are selected with different rainfall distributions in space and time. It is found that the rainfall improvement is most obvious for the events with one‐dimensional evenness in either space or time. The effect of data assimilation is even more significant in the innermost domain which has the finest spatial resolution. However, for the events with two‐dimensional unevenness of rainfall, i.e. the rainfall is concentrated in a small area and in a short time period, the effect of data assimilation is not ideal. WRF fails in capturing the whole process of the highly convective storm with densely concentrated rainfall in a small area and a short time period. A shortened assimilation time interval together with more efficient utilisation of the weather radar data might help improve the effectiveness of data assimilation in such cases. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
10.
U. C. Mohanty A. Routray Krishna K. Osuri S. Kiran Prasad 《Pure and Applied Geophysics》2012,169(3):381-399
An attempt is made to evaluate the impact of the three dimensional variational (3DVAR) data assimilation within the Weather
Research Forecasting (WRF) modeling system to simulate two heavy rainfall events which occured on 26–27 July 2005 and 27–30
July 2006. During the 26–27 July 2005 event, the unprecedented localized intense rainfall 90–100 cm was recorded over the
northeast parts of Mumbai city; however, southern parts received only 10 cm. Model simulation with the data assimilation experiment
is reasonably well predicted for the rainfall intensity (800 mm) in 24 h and with accurate location over Mumbai agreeing with
observation. Divergence, vorticity, vertical velocity and moisture parameters are evaluated during the various stages of the
event. It is noticed that maximum convergence and vorticity during the mature stage; at the same time the vertical velocity
also follows a similar trend during the period in the assimilation experiment. Vorticity budget terms over the location of
heavy rainfall revealed that the contribution of the positive tilting term produced positive vorticity which triggered the
convection and negative contribution to vorticity from the tilting term to precede the dissipation of the system. Model simulations
from the second rain event, the off-shore trough at sea level along the west coast of India, is well represented after assimilation
of observations during day-1 and day-2 as compared to the control simulations; the orientation of the off-shore trough is
well matched with that of the observed. The intensity and spatial distribution of the rainfall has considerably improved in
the assimilation simulation. The statistical skill scores also revealed that the precipitation forecast during the period
has appreciably improved due to assimilation of observations. The results of this study indicate a positive impact of the
3DVAR assimilation on the simulation of heavy rainfall events. 相似文献
11.
Better parameterization of a hydrological model can lead to improved streamflow prediction. This is particularly important for seasonal streamflow forecasting with the use of hydrological modelling. Considering the possible effects of hydrologic non‐stationarity, this paper examined ten parameterization schemes at 12 catchments located in three different climatic zones in east Australia. These schemes are grouped into four categories according to the period when the data are used for model calibration, i.e. calibration using data: (1) from a fixed period in the historical records; (2) from different lengths of historical records prior to prediction year; (3) from different climatic analogue years in the past; and (4) data from the individual months. Parameterization schemes were evaluated according to model efficiency in both the calibration and verification period. The results show that the calibration skill changes with the different historic periods when data are used at all catchments. Comparison of model performance between the calibration schemes indicates that it is worth calibrating the model with the use of data from each individual month for the purpose of seasonal streamflow forecasting. For the catchments in the winter‐dominant rainfall region of south‐east Australia, a more significant shift in rainfall‐runoff relationships at different periods was found. For those catchments, model calibration with the use of 20 years of data prior to the prediction year leads to a more consistent performance. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
12.
Heavy rainfall events during the fall season are causing extended damages in Mediterranean catchments. A peaks‐over‐threshold model is developed for the extreme daily areal rainfall occurrence and magnitude in fall over six catchments in Southern France. The main driver of the heavy rainfall events observed in this region is the humidity flux (FHUM) from the Mediterranean Sea. Reanalysis data are used to compute the daily FHUM during the period 1958–2008, to be included as a covariate in the model parameters. Results indicate that the introduction of FHUM as a covariate can improve the modelling of extreme areal precipitation. The seasonal average of FHUM can improve the modelling of the seasonal occurrences of heavy rainfall events, whereas daily FHUM values can improve the modelling of the events magnitudes. In addition, an ensemble of simulations produced by five different general circulation models are considered to compute FHUM in future climate with the emission scenario A1B and hence to evaluate the effect of climate change on the heavy rainfall distribution in the selected catchments. This ensemble of climate models allows the evaluation of the uncertainties in climate projections. By comparison to the reference period 1960–1990, all models project an amplification of the mean seasonal FHUM from the Mediterranean Sea for the projection period 2070–2099, on average by +22%. This increase in FHUM leads to an increase in the number of heavy rainfall events, from an average of 2.55 events during the fall season in present climate to 3.57 events projected for the period 2070–2099. However, the projected changes have limited effects on the magnitude of extreme events, with only a 5% increase in the median of the 100‐year quantiles. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
13.
The study focuses on the spatial and temporal variations of intense/extreme rainfall events over Gujarat State (India) during the period 1970–2014. Average monsoon rainfall for the state shows a significant increasing trend, with an increase of 48 mm/decade. Some of the stations in the Saurashtra region show a statistically significant increasing trend but none of the stations in the state show a decreasing trend. The increasing trend in monsoon rainfall is very significant for the past three decades, with an increase of 167 mm/decade. Instead of fixed absolute threshold values, relative threshold values of rainfall corresponding to the 95th, 98th, 99th and 99.5th percentiles for each station have been proposed to represent heavy, very heavy, intense and extreme rainfall, which varied between 70–120, 105–160, 130–210 and 165–280 mm, respectively. Significant increasing trends are observed for the frequency of heavy and very heavy rainfall events over the state. 相似文献
14.
S. K. Deb H. C. Upadhyaya O. P. Sharma J. Y. Grandpeix 《Pure and Applied Geophysics》2007,164(8-9):1667-1681
A new analytical formulation of entrainment and detrainment in the Tiedtke's mass flux cumulus parameterization is presented
here in which cloud height is one of the key parameters. The proposed analytical profiles of entrainment and detrainment are
tested in GCM for long-term simulation and are evaluated in the light of the results from the original Tiedtke's scheme and
another mass flux scheme due to Emanuel. The variations of Indian monsoon rainfall have been examined with these schemes in
a general circulation model. Evaluation of the simulated rainfall against observations is done by empirical orthogonal function
(EOF) analysis for the Indian Monsoon region. It is noted that the spatial and temporal variations of the all-India monsoon
rainfall are sensitive to the formulation of entrainment and detrainment in a mass flux scheme, and that the new formulation
can effectively represent the increased dilution with height in deep clouds. 相似文献
15.
Han-Ru Cho 《Pure and Applied Geophysics》1975,113(1):837-849
The latent heat released by cumulus clouds is very important to the energies of many large-scale tropical disturbances. The number of cumulus clouds involved in these disturbances is usually very large. The collective effects of cumulus clouds must therefore be incorporated into a large-scale model in a parameterized fashion. Present parameterization schemes are briefly reviewed. Recent advances in our understanding of the control and feedback processes between cumulus clouds and the large-scale circulations are discussed. Emphasis is placed on the implications of the results of recent diagnostic studies on the future development of the theory of cumulus parameterization. 相似文献
16.
Abstract Heavy rainfall events often occur in southern French Mediterranean regions during the autumn, leading to catastrophic flood events. A non-stationary peaks-over-threshold (POT) model with climatic covariates for these heavy rainfall events is developed herein. A regional sample of events exceeding the threshold of 100 mm/d is built using daily precipitation data recorded at 44 stations over the period 1958–2008. The POT model combines a Poisson distribution for the occurrence and a generalized Pareto distribution for the magnitude of the heavy rainfall events. The selected covariates are the seasonal occurrence of southern circulation patterns for the Poisson distribution parameter, and monthly air temperature for the generalized Pareto distribution scale parameter. According to the deviance test, the non-stationary model provides a better fit to the data than a classical stationary model. Such a model incorporating climatic covariates instead of time allows one to re-evaluate the risk of extreme precipitation on a monthly and seasonal basis, and can also be used with climate model outputs to produce future scenarios. Existing scenarios of the future changes projected for the covariates included in the model are tested to evaluate the possible future changes on extreme precipitation quantiles in the study area. Editor Z.W. Kundzewicz; Associate editor K. Hamed Citation Tramblay, Y., Neppel, L., Carreau, J., and Najib, K., 2013. Non-stationary frequency analysis of heavy rainfall events in southern France. Hydrological Sciences Journal, 58 (2), 280–294. 相似文献
17.
Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5 总被引：1，自引：0，他引：1
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. 相似文献
18.
An effective bias correction procedure using gauge measurement is a significant step for radar data processing to reduce the systematic error in hydrological applications. In these bias correction methods, the spatial matching of precipitation patterns between radar and gauge networks is an important premise. However, the wind-drift effect on radar measurement induces an inconsistent spatial relationship between radar and gauge measurements as the raindrops observed by radar do not fall vertically to the ground. Consequently, a rain gauge does not correspond to the radar pixel based on the projected location of the radar beam. In this study, we introduce an adjustment method to incorporate the wind-drift effect into a bias correlation scheme. We first simulate the trajectory of raindrops in the air using downscaled three-dimensional wind data from the weather research and forecasting model (WRF) and calculate the final location of raindrops on the ground. The displacement of rainfall is then estimated and a radar–gauge spatial relationship is reconstructed. Based on this, the local real-time biases of the bin-average radar data were estimated for 12 selected events. Then, the reference mean local gauge rainfall, mean local bias, and adjusted radar rainfall calculated with and without consideration of the wind-drift effect are compared for different events and locations. There are considerable differences for three estimators, indicating that wind drift has a considerable impact on the real-time radar bias correction. Based on these facts, we suggest bias correction schemes based on the spatial correlation between radar and gauge measurements should consider the adjustment of the wind-drift effect and the proposed adjustment method is a promising solution to achieve this. 相似文献
19.
This paper investigates the sensitivity of the numerical simulations of a near equatorial Typhoon Vamei (2001) to various
planetary boundary layer (PBL) parameterization schemes in the Pennsylvania State University (PSU)/National Centre for Atmospheric
Research (NCAR) non-hydrostatic mesoscale model (MM5). The numerical simulations are conducted on two domains at 45 and 15 km
grids nested in a one-way fashion. Four different PBL parameterization schemes including the Blackadar (BLK) scheme, the Burk–Thompson
(BURKT) scheme, the NCEP Eta model scheme and the NCEP medium range forecast (MRF) model scheme are investigated. Results
indicate that the intensity and propagation track of the simulated near equatorial typhoon system is not very sensitive to
the different PBL treatments. The simulated minimum central pressures and the maximum surface wind speeds differ by only 5–6 hPa
and 6–8 ms−1, respectively. Larger variations between the simulations occur during the weakening phase of the typhoon system. While all
schemes simulated the typhoon with reasonable accuracy, the ETA scheme produces the strongest storm intensity with the largest
heat exchanges over the marine environment and the highest warm moisture air content in the PBL around the core of the storm. 相似文献
20.
This study examines the roles of the multi-physics approach in accounting for model errors for typhoon forecasts with the local ensemble transform Kalman filter (LETKF). Experiments with forecasts of Typhoon Conson (2010) using the weather research and forecasting (WRF) model show that use of the WRF’s multiple physical parameterization schemes to represent the model uncertainties can help the LETKF provide better forecasts of Typhoon Conson in terms of the forecast errors, the ensemble spread, the root mean square errors, the cross-correlation between mass and wind field as well as the coherent structure of the ensemble spread along the storm center. Sensitivity experiments with the WRF model show that the optimum number of the multi-physics ensemble is roughly equal to the number of combinations of different physics schemes assigned in the multi-physics ensemble. Additional idealized experiments with the Lorenz 40-variable model to isolate the dual roles of the multi-physics ensemble in correcting model errors and expanding the local ensemble space show that the multi-physics approach appears to be more essential in augmenting the local rank representation of the LETKF algorithm rather than directly accounting for model errors during the early cycles. The results in this study suggest that the multi-physics approach is a good option for short-range forecast applications with full physics models in which the spinup of the ensemble Kalman filter may take too long for the ensemble spread to capture efficiently model errors and cross-correlations among model variables. 相似文献