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1.
In this paper,the role of constant optimal forcing(COF) in correcting forecast models was numerically studied using the well-known Lorenz 63 model.The results show that when we only consider model error caused by parameter error,which also changes with the development of state variables in a numerical model,the impact of such model error on forecast uncertainties can be offset by superimposing COF on the tendency equations in the numerical model.The COF can also offset the impact of model error caused by stochastic processes.In reality,the forecast results of numerical models are simultaneously influenced by parameter uncertainty and stochastic process as well as their interactions.Our results indicate that COF is also able to significantly offset the impact of such hybrid model error on forecast results.In summary,although the variation in the model error due to physical process is time-dependent,the superimposition of COF on the numerical model is an effective approach to reducing the influence of model error on forecast results.Therefore,the COF method may be an effective approach to correcting numerical models and thus improving the forecast capability of models. 相似文献
2.
3.
The need for simplifi ed physical models representing frequency dependent soil impedances has been the motivation behind many researches throughout history. Generally, such models are generated to capture impedance functions in a wide range of excitation frequencies, which leads to relatively complex models. That is while there is just a limited range of frequencies that really in? uence the response of the structure. Here, a new methodology based on the response-matching concept is proposed, which can lead to the development of simpler discrete models. The idea is then used to upgrade an existing simple model of surface foundations to the case of embedded foundations. The applicability of the model in both frequency domain and time domain analyses of soil-structure systems with embedded foundations is discussed. Moreover, the accuracy of the results is compared with another existing discrete model for embedded foundations. 相似文献
4.
Alpine snowmelt is an important generation mode for runoff in the source region of the Tarim River basin, which covers four subbasins characterized by large area, sparse gauge stations, mixed runoff supplied by snowmelt and rainfall, and remarkably spatially heterogeneous precipitation. Taking the Kaidu River basin as a research area, this study analyzes the influence of these characteristics on the variables and parameters of the Snow Runoff Model and discusses the corresponding determination strategy to improve the accuracy of snowmelt simulation and forecast. The results show that: (i) The temperature controls the overall tendency of simulated runoff and is dominant to simulation accuracy, as the measured daily mean temperature cannot represent the average level of the same elevation in the basin and that directly inputting it to model leads to inaccurate simulations. Based on the analysis of remote sensing snow maps and simulation results, it is reasonable to approximate the mean temperature with 0.5 time daily maximum temperature. (ii) For the conflict between the limited gauge sta-tion and remarkably spatial heterogeneity of rainfall, it is not realistic to compute rainfall for each elevation zone. After the measured rainfall is multiplied by a proper coefficient and adjusted with runoff coefficient for rainfall, the measured rainfall data can satisfy the model demands. (iii) Adjusting time lag according to the variation of snowmelt and rainfall position can improve the simulation precision of the flood peak process. (iv) Along with temperature, the rainfall increases but cannot be completely monitored by limited gauge stations, which results in precision deterioration. 相似文献
5.
This paper refers to the CNOP-related algorithms and formulates the practical method and forecast techniques of extracting predictable components in a numerical model for predictable components on extended-range scales.Model variables are divided into predictable components and unpredictable chaotic components from the angle of model prediction error growth.The predictable components are defined as those with a slow error growth at a given range.A targeted numerical model for predictable components is established based on the operational dynamical extended-range forecast(DERF)model of the National Climate Center.At the same time,useful information in historical data are combined to find the fields for predictable components in the numerical model that are similar to those for the predictable components in historical data,reducing the variable dimensions in a similar judgment process and further correcting prediction errors of predictable components.Historical data is used to obtain the expected value and variance of the chaotic components through the ensemble forecast method.The numerical experiment results show that this method can effectively improve the forecast skill of the atmospheric circulation field in the 10–30 days extended-range numerical model and has good prospects for operational applications. 相似文献
6.
One-dimensional numerical simulation of non-uniform sediment transport under unsteady flows 总被引：16，自引：9，他引：7
One-dimensional numerical models are popularly used in sediment transport research because they can be easily programmed and cost less time compared with two- and three-dimensional numerical models. In particular, they possess greater capacity to be applied in large river basins with many tributaries. This paper presents a one-dimensional numerical model capable of calculating total-load sediment transport. The cross-section-averaged sediment transport capacity and recovery coefficient are addressed in the suspended load model. This one-dimensional model, therefore, can be applied to fine suspended loads and to hyperconcentrated flows in the Yellow River. Moreover, a new discretization scheme for the equation of unsteady non-uniform suspended sediment transport is proposed. The model is calibrated using data measured from the Yantan Reservoir on the Hongshui River and the Sanmenxia Reservoir on the Yellow River. A comparison of the calculated water level and river bed deformation with field measurements Shows that the improved numerical model is capable of predicting flow, sediment transport, bed changes, and bed-material sorting in various situations, with reasonable accuracy and reliability. 相似文献
7.
Guo Yuanyuan Zhang Ruijie Wen Zhiping Li Juncong Zhang Chao Zhou Zijiang 《中国科学:地球科学(英文版)》2021,64(10):1619-1632
Extreme Meiyu rainfall in 2020, starting from early June to the end of July, has occurred over the Yangtze River valley(YRV), with record-breaking accumulated precipitation amount since 1961. The present study aims to examine the possible effect of sea surface temperature(SST) on the YRV rainfall in Meiyu season from the interdecadal perspective. The results indicate that YRV rainfall in June exhibits more significant variability on interdecadal time scale than that in July. The interdecadal-filtered atmospheric circulation in June, compared with the counterpart in July, shows a more predominant and better-organized Western North Pacific Anticyclone(WNPAC) anomaly, which could transport abundant moisture to the YRV by anomalous southwesterly prevailing in northwestern flank of anomalous WNPAC. Both observation and numerical experiment indicate that the interdecadal change of the SST anomaly in tropical western Indian Ocean(TWI) from preceding May to June can significantly affect the anomalous WNPAC, leading to enhanced YRV rainfall in June. The TWI SST anomaly shifts from a cold phase to a warm phase around the early 2000 s, with a magnitude of 0.7℃ in 2020, which implies that such interdecadal warming might partly contribute to the heavy rainfall in June 2020 by providing a large-scale favorable background flow. 相似文献
8.
NUMERICAL MODELING OF HEAVY METAL POLLUTANT TRANSPORT-TRANSFORMATION IN FLUVIAL RIVERS：A REVIEW 总被引：2，自引：1，他引：1
S. L. HUANG Z. H. WAN P. SMITH 《国际泥沙研究》2007,22(1):16-26
A detailed discussion of existing three kinds of mathematical models of heavy metal pollutant transport-transformation in fluvial rivers is presented, with an emphasis on the mathematical model of heavy metal pollutant transport-transformation dynamics. The imperfection of two kinds of mathematical models, that is, mathematical model of chemical thermodynamic equilibrium and that of chemical reaction kinetics, and the shortcoming of existing mathematical models of heavy metal pollutant transport-transformation dynamics are pointed out. Furthermore, the structure of mathematical model of heavy metal pollutant transport-transformation dynamics in fluvial rivers is suggested. Equations in the mathematical model of heavy metal pollutant transport-transformation dynamics in fluvial rivers will be discussed in the following paper. 相似文献
9.
The popularly used viscoelastic models have some shortcomings in describing relationship between quality factor (Q) and frequency, which is not consistent with the observation data. Based on the theory of viscoelasticity, a new approach to construct constant-Q viscoelastic model in given frequency band with three parameters is developed. The designed model describes the frequency-independence feature of quality factor very well, and the effect of viscoelasticity on seismic wave field can be studied relatively accurate in theory with this model. Furthermore, the number of required parameters in this model has been reduced fewer than that of other constant-Q models, this can simplify the solution of the viscoelastic problems to some extent. At last, the accuracy and application range have been analyzed through numerical tests. The effect of viscoelasticity on wave propagation has been briefly illus-trated through the change of frequency spectra and waveform in several different viscoelastic models. 相似文献
10.
The popularly used viscoelastic models have some shortcomings in describing relationship between quality factor （Q） and frequency, which is not consistent with the observation data. Based on the theory of viscoelasticity, a new approach to construct constant-Q viscoelastic model in given frequency band with three parameters is developed. The designed model describes the frequency-independence feature of quality factor very well, and the effect of viscoelasticity on seismic wave field can be studied relatively accurate in theory with this model. Furthermore, the number of required parameters in this model has been reduced fewer than that of other constant-Q models, this can simplify the solution of the viscoelastic problems to some extent. At last, the accuracy and application range have been analyzed through numerical tests. The effect of viscoelasticity on wave propagation has been briefly illustrated through the change of frequency spectra and waveform in several different viscoelastic models. 相似文献
11.
Scale recursive estimation (SRE) is adopted for short term quantitative precipitation forecast (QPF). The precipitation field is modelled using a lognormal random cascade, well suited to properly represent the scaling properties of rainfall fields. To estimate the random cascade parameters, scale recursive maximum likelihood estimation (MLE) is carried out by the iterative expectation maximization (EM) algorithm. To illustrate the potentiality of the SRE, forecast of a synthetically generated rainfall time series is shown. Adaptive estimation of the process parameters is carried out and precipitation forecasts are issued. The forecasts from the SRE are compared with those from standard ARMA models, showing a good performance. The SRE is then adopted for forecasting of an observed half hourly precipitation series for a two day storm event in northern Italy. The SRE provides good performance and it can therefore be adopted as a tool for short term QPF. 相似文献
12.
Forecasting the summer rainfall in North China using the year-to-year increment approach 总被引：5，自引：0，他引：5
A new approach to forecasting the year-to-year increment of rainfall in North China in July–August (JA) is proposed. DY is
defined as the difference of a variable between the current year and the preceding year (year-to-year increment). NR denotes
the seasonal mean precipitation rate over North China in JA. After analyzing the atmospheric circulation anomalies associated
with the DY of NR, five key predictors for the DY of NR have been identified. The prediction model for the DY of NR is established
by using multi-linear regression method and the NR is obtained (the current forecasted DY of NR added to the preceding observed
NR). The prediction model shows a high correlation coefficient (0.8) between the simulated and the observed DY of NR throughout
period 1965–1999, with an average relative root mean square error of 19% for the percentage of precipitation rate anomaly
over North China. The prediction model makes a hindcast for 2000–2007, with an average relative root mean square error of
21% for the percentage of precipitation rate anomaly over North China. The model reproduces the downward trend of the percentage
of precipitation rate anomaly over North China during 1965–2006. Because the current operational prediction models of the
summer precipitation have average forecast scores of 60%–70%, it has been more difficult to forecast the summer rainfall over
North China. Thus this new approach for predicting the year-to-year increment of the summer precipitation (and hence the summer
precipitation itself) has the potential to significantly improve operational forecasting skill for summer precipitation.
Supported by National Basic Research Program of China (Grant No. 2009CB421406), National Natural Science Foundation of China
(Grant Nos. 40631005, 40775049) and Excellent Ph. D Dissertation in Chinese Academy of Sciences 相似文献
13.
S. Abhilash A. K. Sahai K. Mohankumar John P. George Someshwar Das 《Pure and Applied Geophysics》2012,169(11):2047-2070
In this paper the impact of Doppler weather radar (DWR) reflectivity and radial velocity observations for the short range forecasting of a tropical storm and associated rainfall event have been examined. Doppler radar observations of a tropical storm case that occurred during 29–30 October 2006 from SHARDWR (13.6° N, 80.2° E) are assimilated in the WRF 3DVAR system. The observation operator for radar reflectivity and radial velocity is included within latest version of WRF 3DVAR system. Keeping all model physics the same, three experiments were conducted at a horizontal resolution of 30?km. In the control experiment (CTRL), NCEP Final Analysis (FNL) interpolated to the model grid was used as the initial condition for 48-h free forecast. In the second experiment (NODWR), 6-h assimilation cycles have been carried out using all conventional (radiosonde and surface data) and non-conventional (satellite) observations from the Global Telecommunication System (GTS). The third experiment (DWR) is the same as the second, except Doppler radar radial velocity and reflectivity observations are also used in the assimilation cycle. Continuous 6-h assimilation cycle employed in the WRF-3DVAR system shows positive impact on the rainfall forecast. Assimilation of DWR data creates several small scale features near the storm centre. Additional sensitivity experiments were conducted to study the individual impact of reflectivity and radial velocity in the assimilation cycle. Radar data assimilation with reflectivity alone produced large analysis response on both thermodynamical and dynamical fields. However, radial velocity assimilation impacted only on dynamical fields. Analysis increments with radar reflectivity and radial velocity produce adjustments in both dynamical and thermodynamical fields. Verification of QPF skill shows that radar data assimilation has a considerable impact on the short range precipitation forecast. Improvement of the QPF skill with radar data assimilation is more clearly seen in the heavy rainfall (for thresholds >7?mm) event than light rainfall (for thresholds of 1 and 3?mm). The spatial pattern of rainfall is well simulated by the DWR experiment and is comparable to TRMM observations. 相似文献
14.
Orissa State, a meteorological subdivision of India, lies on the east coast of India close to north Bay of Bengal and to the
south of the normal position of the monsoon trough. The monsoon disturbances such as depressions and cyclonic storms mostly
develop to the north of 15° N over the Bay of Bengal and move along the monsoon trough. As Orissa lies in the southwest sector
of such disturbances, it experiences very heavy rainfall due to the interaction of these systems with mesoscale convection
sometimes leading to flood. The orography due to the Eastern Ghat and other hill peaks in Orissa and environs play a significant
role in this interaction. The objective of this study is to develop an objective statistical model to predict the occurrence
and quantity of precipitation during the next 24 hours over specific locations of Orissa, due to monsoon disturbances over
north Bay and adjoining west central Bay of Bengal based on observations to up 0300 UTC of the day. A probability of precipitation
(PoP) model has been developed by applying forward stepwise regression with available surface and upper air meteorological
parameters observed in and around Orissa in association with monsoon disturbances during the summer monsoon season (June-September).
The PoP forecast has been converted into the deterministic occurrence/non-occurrence of precipitation forecast using the critical
value of PoP. The parameters selected through stepwise regression have been considered to develop quantitative precipitation
forecast (QPF) model using multiple discriminant analysis (MDA) for categorical prediction of precipitation in different ranges
such as 0.1–10, 11–25, 26–50, 51–100 and >100 mm if the occurrence of precipitation is predicted by PoP model. All the above
models have been developed based on data of summer monsoon seasons of 1980–1994, and data during 1995–1998 have been used
for testing the skill of the models. Considering six representative stations for six homogeneous regions in Orissa, the PoP
model performs very well with percentages of correct forecast for occurrence/non-occurrence of precipitation being about 96%
and 88%, respectively for developmental and independent data. The skill of the QPF model, though relatively less, is reasonable
for lower ranges of precipitation. The skill of the model is limited for higher ranges of precipitation.
accepted September 2006 相似文献
15.
Feed forward Artificial Neural Network model to predict the average summer-monsoon rainfall in India
Surajit Chattopadhyay 《Acta Geophysica》2007,55(3):369-382
In the present research, possibility of predicting average summer-monsoon rainfall over India has been analyzed through Artificial
Neural Network model. In formulating the ANN — based predictive model, three-layer network has been constructed with sigmoid
non-linearity. The monthly summer monsoon rainfall totals, tropical rainfall indices and sea surface temperature anomalies
have been considered as predictors while generating the input matrix for the ANN. The data pertaining to the years 1950–1995
have been explored to develop the predictive model. Finally, the prediction performance of neural net has been compared with
persistence forecast and Multiple Linear Regression forecast and the supremacy of the ANN has been established over the other
processes. 相似文献
16.
This paper analyses the skills of fuzzy computing based rainfall–runoff model in real time flood forecasting. The potential of fuzzy computing has been demonstrated by developing a model for forecasting the river flow of Narmada basin in India. This work has demonstrated that fuzzy models can take advantage of their capability to simulate the unknown relationships between a set of relevant hydrological data such as rainfall and river flow. Many combinations of input variables were presented to the model with varying structures as a sensitivity study to verify the conclusions about the coherence between precipitation, upstream runoff and total watershed runoff. The most appropriate set of input variables was determined, and the study suggests that the river flow of Narmada behaves more like an autoregressive process. As the precipitation is weighted only a little by the model, the last time‐steps of measured runoff are dominating the forecast. Thus a forecast based on expected rainfall becomes very inaccurate. Although good results for one‐step‐ahead forecasts are received, the accuracy deteriorates as the lead time increases. Using the one‐step‐ahead forecast model recursively to predict flows at higher lead time, however, produces better results as opposed to different independent fuzzy models to forecast flows at various lead times. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
17.
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18.
Zhaohui Lin Jason K. Levy Xingkui Xu Sixiong Zhao Jens Hartmann 《Stochastic Environmental Research and Risk Assessment (SERRA)》2005,19(6):428-437
This paper describes the use of numerical weather and climate models for predicting severe rainfall anomalies over the Yangtze
River Basin (YRB) from several days to several months in advance. Such predictions are extremely valuable, allowing time for
proactive flood protection measures to be taken. Specifically, the dynamical climate prediction system (IAP DCP-II), developed
by the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP), is applied to YRB rainfall prediction and flood
planning. IAP DCP-II employs ensemble prediction with dynamically conditioned perturbations to reduce the uncertainty associated
with seasonal climate prediction. IAP DCP-II was shown to successfully predict seasonal YRB summer flooding events based on
a 15-year (1980–1994) hindcast experiment and the real-time prediction of two summer flooding events (1999 and 2001). Finally,
challenges and opportunities for applying seasonal dynamical forecasting to flood management problems in the YRB are discussed. 相似文献
19.
大别山库区降水预报性能评估及应用对策 总被引：1，自引：0，他引：1
对降水预报进行性能评估及应用对策研究可以更好地发挥降水预报在水库调度中的决策支持作用.基于大别山库区近10 a汛期(2007—2016年5月1日—9月30日)24~168 h共7个预见期降水预报和地面降水观测资料,采用正确率、TS评分、概率统计、ROC曲线以及CTS等方法评估大别山库区降水预报性能,并以响洪甸水库为重点研究区域分析降水预报在水库调度中的应用对策.结果表明:1)大别山库区各量级的降水预报都有正预报技巧;24~72 h预见期降水预报的TS评分较高且空报率、漏报率也较低,具有较高的预报性能;但96 h及以上预见期降水预报性能明显下降,中雨以上量级空报率、漏报率较大,特别是对大暴雨及其以上量级的降水预报性能显著下降.2)大别山库区预报降水量级与实况降水量级基本符合,预报降水量级大于等于实况降水量级的概率超过75%;虽然降水预报量级上呈现出过度预报的现象,但降水过程预报对水库调度仍有较好的应用价值,应用时要考虑到降水预报量级可能存在偏差.3)转折性天气预报96 h及以上预见期CTS评分较低,但72 h以内预见期的性能明显改进,尤其是24 h预见期CTS评分也提高到了38.2%;水库调度可从长预见期的降水预报获取降水过程及其可能发生转折的信息,根据短预见期的降水预报进行调度方案调整. 相似文献
20.
This study examines the short-range forecast accuracy of the Pennsylvania State University-National Center for Atmospheric
Research Mesoscale Model (MM5) as applied to the July 2006 episode of the Indian summer monsoon (ISM) and the model's sensitivity
to the choice of different cumulus parameterization schemes (CPSs), namely Betts-Miller, Grell (GR) and Kain-Fritsch (KF).
The results showed that MM5 day 1 (0–24 h prediction) and day 2 (24–48 h prediction) forecasts using all three CPSs overpredicted
monsoon rainfall over the Indian landmass, with the larger overprediction seen in the day 2 forecasts. Among the CPSs, the
rainfall distribution over the Indian landmass was better simulated in forecasts using the KF scheme. The KF scheme showed
better skill in predicting the area of rainfall for most of the rainfall thresholds. The root mean square error (RMSE) in
day 1 and day 2 rainfall forecasts using different CPSs showed that rainfall simulated using the KF scheme agreed better with
the observed rainfall. As compared to other CPSs, simulation using the GR scheme showed larger RMSE in wind speed prediction
at 850 and 200 hPa over the Indian landmass. MM5 24-h temperature forecasts at 850 hPa with all the CPSs showed a warm bias
of the order of 1 K over the Indian landmass and the bias doubled in 48-h model forecasts. The mean error in temperature prediction
at 850 hPa over the Indian region using the KF scheme was comparatively smaller for all the forecast intervals. The model
with all the CPSs overpredicted humidity at 850 hPa. The improved prediction by MM5 with the KF scheme is well complemented
by the smaller error shown by the KF scheme in vertical distribution of heat and mean moist static energy in the lower troposphere.
In this study, the KF scheme which explicitly resolve the downdrafts in the cloud column tended to produce more realistic
precipitation forecasts as compared to other schemes which did not explicitly incorporate downdraft effects. This is an important
result especially given that the area covered by monsoon-precipitating systems is largely from stratiform-type clouds which
are associated with strong downdrafts in the lower levels. This result is useful for improving the treatment of cumulus convection
in numerical models over the ISM region. 相似文献