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1.
The satellite-derived wind from cloud and moisture features of geostationary satellites is an important data source for numerical weather prediction(NWP) models. These datasets and global positioning system radio occultation(GPSRO)satellite radiances are assimilated in the four-dimensional variational atmospheric data assimilation system of the UKMO Unified Model in India. This study focuses on the importance of these data in the NWP system and their impact on short-term24-h forecasts. The quality of the wind observations is compared to the short-range forecast from the model background. The observation increments(observation minus background) are computed as the satellite-derived wind minus the model forecast with a 6-h lead time. The results show the model background has a large easterly wind component compared to satellite observations. The importance of each observation in the analysis is studied using an adjoint-based forecast sensitivity to observation method. The results show that at least around 50% of all types of satellite observations are beneficial. In terms of individual contribution, METEOSAT-7 shows a higher percentage of impact(nearly 50%), as compared to GEOS, MTSAT-2and METEOSAT-10, all of which have a less than 25% impact. In addition, the impact of GPSRO, infrared atmospheric sounding interferometer(IASI) and atmospheric infrared sounder(AIRS) data is calculated. The GPSRO observations have beneficial impacts up to 50 km. Over the Southern Hemisphere, the high spectral radiances from IASI and AIRS show a greater impact than over the Northern Hemisphere. The results in this study can be used for further improvements in the use of new and existing satellite observations. 相似文献
2.
A low pressure system that formed on 21 September 2006 over eastern India/Bay of Bengal intensified into a monsoon depression
resulting in copious rainfall over north-eastern and central parts of India. Four numerical experiments are performed to examine
the performance of assimilation schemes in simulating this monsoon depression using the Fifth Generation Mesoscale Model (MM5).
Forecasts from a base simulation (with no data assimilation), a four-dimensional data assimilation (FDDA) system, a simple
surface data assimilation (SDA) system coupled with FDDA, and a flux-adjusting SDA system (FASDAS) coupled with FDDA are compared
with each other and with observations. The model is initialized with Global Forecast System (GFS) forecast fields starting
from 19 September 2006, with assimilation being done for the first 24 hours using conventional observations, sounding and
surface data of temperature and moisture from Advanced TIROS Operational Vertical Sounder satellite and surface wind data
over the ocean from QuikSCAT. Forecasts are then made from these assimilated states. In general, results indicate that the
FASDAS forecast provides more realistic prognostic fields as compared to the other three forecasts. When compared with other
forecasts, results indicate that the FASDAS forecast yielded lower root-mean-square (r.m.s.) errors for the pressure field
and improved simulations of surface/near-surface temperature, moisture, sensible and latent heat fluxes, and potential vorticity.
Heat and moisture budget analyses to assess the simulation of convection revealed that the two forecasts with the surface
data assimilation (SDA and FASDAS) are superior to the base and FDDA forecasts. An important conclusion is that, even though
monsoon depressions are large synoptic systems, mesoscale features including rainfall are affected by surface processes. Enhanced
representation of land-surface processes provides a significant improvement in the model performance even under active monsoon
conditions where the synoptic forcings are expected to be dominant. 相似文献
3.
Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction(NWP)models.As observations are expensive and logistically challenging,it is important to evaluate the benefit that additional observations could bring to NWP.Atmospheric soundings applying unmanned aerial vehicles(UAVs)have a large potential to supplement conventional radiosonde sounding observations.Here,we applied UAV and radiosonde sounding observations from an RV Polarstern cruise in the ice-covered Weddell Sea in austral winter 2013 to evaluate the impact of their assimilation in the Polar version of the Weather Research and Forecasting(Polar WRF)model.Our experiments revealed small to moderate impacts of radiosonde and UAV data assimilation.In any case,the assimilation of sounding data from both radiosondes and UAVs improved the analyses of air temperature,wind speed,and humidity at the observation site for most of the time.Further,the impact on the results of 5-day-long Polar WRF experiments was often felt over distances of at least 300 km from the observation site.All experiments succeeded in capturing the main features of the evolution of near-surface variables,but the effects of data assimilation varied between different cases.Due to the limited vertical extent of the UAV observations,the impact of their assimilation was limited to the lowermost 1?2-km layer,and assimilation of radiosonde data was more beneficial for modeled sea level pressure and near-surface wind speed. 相似文献
4.
The present study is conducted to verify the short-range forecasts from mesoscale model version5 (MM5)/weather research and forecasting (WRF) model over the Indian region and to examine the impact of assimilation of quick scatterometer (QSCAT) near surface winds, spectral sensor microwave imager (SSM/I) wind speed and total precipitable water (TPW) on the forecasts by these models using their three-dimensional variational (3D-Var) data assimilation scheme for a 1-month period during July 2006. The control (without satellite data assimilation) as well as 3D-Var sensitivity experiments (with assimilating satellite data) using MM5/WRF were made for 48 h starting daily at 0000 UTC July 2006. The control run is analyzed for the intercomparison of MM5/WRF short-range forecasts and is also used as a baseline for assessing the MM5/WRF 3D-Var satellite data sensitivity experiments. As compared to the observation, the MM5 (WRF) control simulations strengthened (weakened) the cross equatorial flow over southern Arabian sea near peninsular India. The forecasts from MM5 and WRF showed a warm and moist bias at lower and upper levels with a cold bias at the middle level, which shows that the convective schemes of these models may be too active during the simulation. The forecast errors in predicted wind, temperature and humidity at different levels are lesser in WRF as compared to MM5, except the temperature prediction at lower level. The rainfall pattern and prediction skill from day 1 and day 2 forecasts by WRF is superior to MM5. The spatial distribution of forecast impact for wind, temperature, and humidity from 1-month assimilation experiments during July 2006 demonstrated that on average, for 24 and 48-h forecasts, the satellite data improved the MM5/WRF initial condition, so that model errors in predicted meteorological fields got reduced. Among the experiments, MM5/WRF wind speed prediction is most benefited from QSCAT surface wind and SSM/I TPW assimilation while temperature and humidity prediction is mostly improved due to latter. The largest improvement in MM5/WRF rainfall prediction is due to the assimilation of SSM/I TPW. The assimilation of SSM/I wind speed alone in MM5/WRF degraded the humidity and rainfall prediction. In summary the assimilation of satellite data showed similar impact on MM5/WRF prediction; largest improvement due to SSM/I TPW and degradation due to SSM/I wind speed. 相似文献
5.
Diana J. M. Greenslade Eric W. Schulz Jeff D. Kepert Graham R. Warren 《Journal of Atmospheric & Ocean Science》2005,10(3):261-287
Recent work has demonstrated that surface marine winds from the Bureau of Meteorology's operational Numerical Weather Prediction (NWP) systems are typically underestimated by 5 to 10%. This is likely to cause significant bias in modelled wave fields that are forced by these winds. A simple statistical adjustment of the wind components is shown to reduce the observed bias in Significant Wave Height considerably. The impact of increasing the vertical resolution of the NWP model and assimilating scatterometer data into the model is assessed by comparing the resulting forecast wind and waves to observations. It is found that, in general, the inclusion of scatterometer observations improves the accuracy of the surface wind forecasts. However, most of the improvement is shown to arise from the increased number of vertical levels in the atmospheric model, rather than directly from the use of the observations. When the wave model is forced with surface winds from the NWP model that includes scatterometer data, it is found that the scatterometer assimilation does not reduce the systematic bias in surface wave forecasts, but that the random errors are reduced. 相似文献
6.
bbGPS/PWV资料三维变分同化改进MM5降水预报连续试验的评估 总被引：5，自引：0，他引：5
利用区域地基GPS网反演的高时空密度的大气垂直方向水汽总量，也称为可降水量（PWV），可大大弥补常规探空探测水汽资料的不足。为了全面评估区域GPS网PWV资料同化对业务数值天气预报改进程度的目的，在个例研究分析的基础上，进行了连续38天的GPS/PWV资料三维同化（3D-Var）改进数值业务预报的试验。研究方法是根据长江三角洲地区GPS气象网在2002年梅雨和盛夏季节观测的刖资料，通过三维变分同化建立中尺度数值预报模式MM5的初始场，逐日作出长江三角洲地区24小时的降水量预报。以6小时累积雨量为对象，与未同化GPS／刖资料的MM5的相应预报比较，通过多种评分方法，评估了GPS／PWV资料改进MM5降水预报的效果。结果表明GPS／PWV资料同化后的MM5降水预报能力在大部分时间和大部分地区都有所提高，主要是伪击率有较明显的下降，对小范围降水预报的改进更为明显。预报明显改进的区域恰好位于GPS站填补常规探空站间距较大的地区。 相似文献
7.
To investigate the impact of various types of data on medium-range forecasts, observing system experiments are performed using an assimilation algorithm based on the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) reanalysis system. Data-denial experiments for radiosonde, satellite, aircraft, and sea surface observations, and selected data experiments for radiosonde and surface data, are conducted for the boreal summer of 1997 and the boreal winter of 1997/1998. The data assimilation system used in this study is remarkably dependent on radiosonde data, which provides information about the three-dimensional structure of the atmosphere. As expected, the impact of radiosonde observations on medium-range forecasts is strongly positive over the Northern Hemisphere and tropics, whereas the satellite system is most beneficial over the Southern Hemisphere. These results are also found in experiments simulating historical changes in observation systems. Over the tropics, assimilation without radiosonde observations generates unbalanced analyses resulting in unrealistic forecasts that must be corrected by the forecast model. Forecasts based on analysis from the observation data before the era of radiosonde observation are found to be less meaningful. In addition, the impacts on forecasts are closely related to the geographical distribution of observation data. The memory of observation data embedded in the analysis tends to persist throughout forecasts. However, cases exist where the effect of forecast error growth is more dominant than that of analysis error, e.g., over East Asia in summer, and where the deficiency in observations is supplemented or the imbalance in analysis is adjusted by the forecast model during the period of forecasts. Forecast error growth may be related to the synoptic correction performed by the data assimilation system. Over data-rich areas, analysis fields are corrected to a greater extent by the data assimilation system than are those over data-poor areas, which can cause the forecast model to produce more forecast errors in medium-range forecasts. It is found that even one month per season is sufficient for forecast skill verification in data impact experiments. Additionally, the use of upper-air observations is found to benefit areas that are downstream of observation data-rich areas. 相似文献
8.
为了进一步提高GRAPES_Meso的分析和预报效果,该文在GRAPES_Meso三维变分同化系统中建立了同化GNSS/RO反演的大气资料的观测算子,实现了对GNSS/RO反演的大气资料的同化应用,并通过2013年7月1个月的同化和预报试验分析了GNSS/RO反演大气资料对GRAPES_Meso模式系统分析和预报的影响。结果表明:增加了GNSS/RO反演大气资料的同化后,GRAPES_Meso位势高度场的分析误差明显减小,平均分析误差减小约8%,预报误差略有减小,平均预报误差减小约1%;湿度场的分析误差和预报误差变化不明显,常规观测资料稀少的青藏高原地区的降水预报技巧有所提高,小雨到大雨的ETS (equitable threat score) 评分提高约0.01,对全国及其他分区的降水预报技巧总体上有正效果。 相似文献
9.
AMSU-A (Advanced Microwave Sounding Unit-A) measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction (NWP) models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting (WRF) model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation (WRF-VAR) system, the surface parameters from the operational Microwave Surface and Precipitation Products System (MSPPS) are introduced to understand the influence of surface parameters on AMSU-A assimilation over land. The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error (RMSE) and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction (NCEP) global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land. 相似文献
10.
Summary A network of ground-based Global Positioning System (GPS) receivers is used to continuously obtain information on variations
in the integrated water vapor (IWV) in the atmosphere. We use GPS data from 1996–1998 to compare the IWV estimates with radiosonde
data. The spatial correlation of estimation errors is important when the GPS results are to be used in assimilation models.
We study and model this effect by comparing the horizontal correlations of the IWV time series derived from the radiosonde
network and the GPS data analysis. Under ideal conditions this method separates the IWV features from the underlying correlation
function for the estimation errors in the GPS data. A sparse radiosonde network limits the quality of the obtained results.
We foresee continued studies including more data and simulations of the errors associated with the GPS technique.
Received November 21, 2000 Revised April 2, 2001 相似文献
11.
Precipitable Water (PW) derived from Global Positioning System (GPS)
measurements and numerical weather prediction (NWP) model analysis data were
compared to further evaluate the efficacy of applying GPS-derived PW to the
NWP model. The spatial and temporal variations of GPS-derived PW during a
rainfall event were also examined.
GPS-derived PW measurements show good agreement with the behavior of water
vapor at a high spatial resolution during the analysis period. Temporal
anomalies of GPS-derived PW moving along with the front are successfully
detected by the GPS array. Large positive anomalies of GPS-derived PW are
indicated immediately before a rainfall event, and the intensity of these
positive anomalies do not seem to decrease significantly as the
precipitation system passes. These results indicate that the Korean GPS
network may have great potential as a PW sensor over the Korean Peninsula.
In contrast with GPS-derived PW, NWP-derived PW shows negative biases. These
biases appear to stem mainly from the differences between modeled and actual
GPS site elevations, as GPS sites were generally located at elevations lower
than those employed by the NWP model. However, there still exists a
discernable dry bias after a PW correction is applied to NWP-derived PW.
GPS-derived PW better reflects the spatial and temporal moisture variations
of precipitation systems, as compared to NWP-derived PW. These results
provide entirely new information for improving the regional NWP system,
since GPS-derived PW produced with data from the Korean GPS network may be
incorporated into the NWP model to improve rainfall forecasts. 相似文献
12.
Summary Structures in atmospheric Integrated Water Vapor (IWV) have been studied for the three successive cyclones, Kerstin, Liane
and Monika, which controlled the meteorological conditions in the Baltic Sea catchment region in the period from 28 August
to 5 September 1995 (part of the PIDCAP observational campaign defined within BALTEX). Several model predictions of these
cyclones have been performed with a regional atmospheric general circulation model (RACMO). The impact of two different versions
of the model physics package (standard ECHAM4 and a revised version with modifications in the cloud and turbulence scheme)
has been investigated. Model predicted IWV has been evaluated with GPS station data from several stations in Sweden and Finland.
For the most strongly developed cyclone Monika, the revised scheme generates more pronounced IWV structures, with well defined
bands of high and low values of IWV curving into the center of the cyclone. In particular, the shape of the minima are in
better agreement with the GPS station data, and the consistency between two subsequent model forecasts is also larger with
the revised physics package. For the weaker systems, Kerstin and Liane, results from both model versions are very similar.
Received August 11, 2000 Revised February 13, 2001 相似文献
13.
TAMDAR Observation Assimilation in WRF 3D-Var and Its Impact on Hurricane Ike (2008) Forecast 总被引：1，自引：0，他引：1 
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下载免费PDF全文 This study evaluates the impact of atmospheric observations from the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observing system on numerical weather prediction of hurricane Ike (2008) using three-dimensional data assimilation system for the Weather Research and Forecast (WRF) model (WRF 3D-Var). The TAMDAR data assimilation capability is added to WRF 3D-Var by incorporating the TAMDAR observation operator and corresponding observation processing procedure. Two 6-h cycling data assimilation and forecast experiments are conducted. Track and intensity forecasts are verified against the best track data from the National Hurricane Center. The results show that, on average, assimilating TAMDAR observations has a positive impact on the forecasts of hurricane Ike. The TAMDAR data assimilation reduces the track errors by about 30 km for 72-h forecasts. Improvements in intensity forecasts are also seen after four 6-h data assimilation cycles. Diagnostics show that assimilation of TAMDAR data improves subtropical ridge and steering flow in regions along Ike’s track, resulting in better forecasts. 相似文献
14.
The coverage of satellite derived winds over the Indian region including Indian Ocean has improved by the operation of India’s first dedicated satellite for meteorology, KALPANA-1 since 12 September 2002. Atmospheric motion vectors (AMVs) are being derived at the India Meteorological Department (IMD), New Delhi on a routine operational basis. The AMV is recognized as an important source of information for numerical weather prediction (NWP) and is particularly suited for tracking the low and middle level clouds mainly because of the good contrast in albedo between target and background, whereas the upper level moisture pattern can be better tracked by water vapor winds (WVW) using water vapor (WV) channel (5.7–7.1 μm). The WVWs proved to be a very useful wind product for predicting the future track position of cyclones, well marked low pressure areas or heavy rainfall warnings in advance and so, often these types of weather systems are steered by the upper level winds. In the present study, the quantitative as well as qualitative analyses of KALPANA-1 WVW have been carried out. The primary change introduced is making use of first guess (FG) forecast fields obtained from National Center for Environmental Prediction (NCEP) and Global Forecast System (GFS), at a resolution of 1° × 1° with T-382/L64 instead of forecasts of operational limited area model (LAM) of IMD. The overall results showed a consistent improvement after using improved FG wind fields from NCEP instead of LAM with a significantly increasing number of good qualities of KALPANA-1 derived WVWs. The quantitative error analysis has also been carried out for the validation of WVWs using collocated radiosonde observations for the period from May 2008 to December 2009 and the available mid-upper level winds derived from METEOSAT-7 data for the period from October to December 2008. The analysis shows that after modification, the RMSE and bias of KALPANA-1 WVWs have reduced considerably. Further, to assess the impact of these winds, a high resolution mesoscale model WRF 3DVAR system is used in the present study for the analysis of tropical cyclone ‘Sidr’. The results show that the wind assimilation experiments (analysis at 200 hPa) using upper level KALPANA-1 WVW have great potential for improving the NWP analysis. The impact of additional wind data in the model is found to be positive and beneficial. 相似文献
15.
A. Routray U. C. Mohanty Dev Niyogi S. R. H. Rizvi Krishna K. Osuri 《Meteorology and Atmospheric Physics》2010,106(1-2):107-125
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. 相似文献
16.
观测发现,西北太平洋区域夏季降水—SST存在显著的负相关,主要是由于El Ni?o衰减年西北太平洋异常反气旋持续至夏季,该过程是检验耦合模式性能的重要参照标准。本文利用中国科学院大气物理研究所近期气候预测系统IAP-DecPreS,通过海洋同化试验、大气模式AMIP试验与观测结果的比较,评估海洋同化试验对西北太平洋夏季局地海气相互作用特征的模拟影响。结果表明,海洋同化试验能够模拟出西北太平洋区域夏季降水—SST负相关,但负相关区域范围偏小。其与观测之间的最大差异出现在8月,西北太平洋负降水异常及异常反气旋位置偏东,强度偏弱。这是由于其模拟的El Ni?o衰减年夏季赤道东印度洋正降水异常偏弱且移动至赤道南侧,对流层增温偏弱,对西太平洋的遥相关作用偏弱。AMIP试验未考虑大气对海洋的反馈作用,不能再现西北太平洋降水—SST负相关,无法模拟出El Ni?o衰减年夏季西北太平洋异常反气旋。研究表明,海洋同化试验对西北太平洋区域局地海气相互作用特征的模拟能力较AMIP试验有所提升,其对8月西北太平洋降水与环流场的模拟偏差与东赤道印度洋降水模拟偏差有关。 相似文献
17.
18.
R. B. Zaripov Yu. V. Martynova V. N. Krupchatnikov A. P. Petrov 《Russian Meteorology and Hydrology》2016,41(11-12):808-815
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. 相似文献
19.
气象卫星资料同化的科学问题与前景 总被引：4，自引：1，他引：3
从数值天气预报资料同化的角度,分析了气象卫星观测与常规气象观测的不同特点形成了卫星资料同化的特殊科学问题.由于各类星载遥感仪器所观测到的是一定波长的电磁辐射,不能像传统的直接观测资料一样被预报模式直接应用.又由于卫星观测对象是整个大气层,而不是特定高度的大气,因此确定卫星观测影响的高度和它的潜在垂直分辨率成为一个关键问题.卫星观测还可能存在着系统性的偏差,这与直接观测的误差互相独立也有很大区别.资料同化通常建立在模式预报(即背景信息)与观测量的比较的基础上,为了实现同化,需要将模式的基本大气变量转换成星载仪器所获得的特定波长的电磁波特征量,或者将观测到的电磁辐射特征量反算成大气的特征量.前者需要引入复杂的观测算子,后者则将复杂的反演过程交给了前处理阶段.这就形成了直接与间接同化卫星资料的两种不同策略,策略的选择取决于同化系统处理复杂观测资料的能力,对同化效果有决定性的影响.逐个分析了目前用于数值预报的5种卫星观测资料,即星载大气垂直探测器资料、大气运动矢量资料、散射仪海面风资料、卫星观测的云与降水信息资料与GPS掩星观测资料的同化的进展与有待解决的主要问题,概述了中国近年在大气垂直探测器等卫星资料同化中的研究进展及其业务应用的效果,并提出了今后需要予以特别关注的研究方向. 相似文献
20.
The ensemble Kalman filter (EnKF), as a unified approach to both data assimilation and ensemble forecasting problems, is used to investigate the performance of dust storm ensemble forecasting targeting a dust episode in the East Asia during 23–30 May 2007. The errors in the input wind field, dust emission intensity, and dry deposition velocity are among important model uncertainties and are considered in the model error perturbations. These model errors are not assumed to have zero-means. The model error me... 相似文献