Latitudinal variability of the ionosphere and long-term prediction of the maximum usable frequency of the <Emphasis Type="Italic">F</Emphasis> region along direct and reverse paths

We present maximum usable frequency (MUF) calculation results when a radiowave, radiated at a zero angle, is reflected from the ionosphere along direct and reverse paths when the latitudinal variability of the medium is significant. As an example, we consider the Novorossiysk-California path. Calculations were carried out using a “two-point” method and data of the Monthly MUF Prediction for May 1980 and May 1991. The “two-point” method is validated based on a new way of approximated representation of the Watson integral, which is an exact solution of the benchmark problem related to the point source field in a spherically layered medium. It is shown that MUFs along a reverse path are several MHz higher than MUFs along a direct path during the whole day.     

Adaptation of the average monthly ionospheric model to current conditions using the data on maximum usable frequencies at two-hop reference radio links

The accuracy in determining the maximum usable frequencies (MUF) of reference radio links has been estimated. A method for using the data on MUF, obtained at two-hop reference radio links, in order to specify the horizontal gradients of electron concentration in the ionosphere has been proposed. The results of the observations at a system of two reference radio links are used to assess the efficiency of such a specification. It has been indicated that the developed method makes it possible to specify the values of the ionospheric critical frequency simultaneously in two radio link regions. The application of two-hop radio links together with one-hop lines substantially broadens the number of reference radio stations that can be used to adapt the parameters of the average monthly ionospheric model to the current conditions.     

Application of the theoretical reference ionosphere model for calculating HF-radiowave propagation characteristics

We study the possibilities of the Theoretical Ionosphere Model (TIM) developed at the Institute of Solar-Terrestrial Physics, Siberian Branch, Russian Academy of Sciences, for calculating the HF-radiowave propagation characteristics. The results of simulation based on the TIM are compared with calculations based on the IRI model and data from experimental observations. Analysis of the results of calculations for the maximum usable frequency (MUF) have shown that with the same input data (coordinates of the receipt and transmission points, the route length, date, and time), the differences in the calculated MUFs (using two different models supplying radio routes with ionospheric information) amount to ∼1% in the daytime and reach 10% at night.     

Verification of the reciprocal theorem on polar high-frequency radio paths during magnetic disturbances

Two high-latitude high-frequency (HF) paths of oblique-incidence ionospheric sounding were selected: Gor’kovskaya (GRK)–Dixon Island (DIK) and GRK–Lovozero (LOZ).The following propagation parameters were studied: F2MOF and F2MUF for the main signal, F2MOFl for lateral signals, EsMOF for a signal reflected from the sporadic ionospheric layer, and MOFm for the propagation modes of the M (or N) type. Here MOF and MUF are the maximum observed and usable frequencies, respectively. It was found that the reciprocal theorem is satisfied on two radio paths depending on the studied propagation parameter: the path length and location, time of day, and degree of magnetospheric disturbance. It was found that the reciprocal theorem is satisfied in 78, 50, and 30% of cases on the first path for the F2MUF values in the daytime under moderately disturbed conditions, in the morning, and at night, respectively. For the MOFm and moderately disturbed conditions on this path, the reciprocal theorem is satisfied in 40, 35, and 20% of cases in the daytime, morning, and at night, respectively. For the F2MUF values on the second path, reciprocity is satisfied in 73% of cases in the daytime and under moderately disturbed conditions and in 30% of cases at night during a quiet period. On this path, reciprocity is satisfied in 33% of all cases at night under strongly disturbed conditions. An unusual fact was also detected when ionograms of oblique-incidence ionospheric sounding were analyzed: the F2MUF values in the LOZ–GRK direction are almost always slightly (by 1–4%) larger than in the GRK–LOZ direction. A similar difference in the F2MUF values in the forward and backward directions can apparently be explained by the steep horizontal gradient in the electron density distribution from north to south in the reflection region of this path. Such a situation is not observed on the DIK–GRK line.     

Research on runoff forecast approaches to the Aksu River basin

The Aksu River (the international river between China and Kirghiz) has become the main water source for the Tarim River. It significantly influences the Tarim River’s formation, development and evolution. Along with the western region development strategy and the Tarim River basin comprehensive development and implementation, the research is now focused on the Aksu River basin hydrologic characteristic and hydrologic forecast. Moreover, the Aksu River is representative of rivers supplied with glacier and snow melt in middle-high altitude arid district. As a result, the research on predicting the river flow of the Aksu River basin has theoretical and practical significance. In this paper, considering the limited hydrometeorological data for the Aksu River basin, we have constructed four hydrologic forecast approaches using the daily scale to simulate and forecast daily runoff of two big branches of the Aksu River basin. The four approaches are the upper air temperature and the daily runoff correlation method, AR(p) runoff forecast model, temperature and precipitation revised AR(p) model and the NAM rainfall-runoff model. After comparatively analyzing the simulation results of the four approaches, we discovered that the temperature and precipitation revised AR(p) model, which needs less hydrological and meteorological data and is more predictive, is suitable for the short-term runoff forecast of the Aksu River basin. This research not only offers a foundation for the Aksu River and Tarim Rivers’ hydrologic forecast, flood prevention, control and the entire basin water collocation, but also provides the hydrologic forecast reference approach for other arid ungauged basins.     

Research on runoff forecast approaches to the Aksu River basin

The Aksu River (the international river between China and Kirghiz) has become the main water source for the Tarim River. It significantly influences the Tarim River's formation, development and evolution. Along with the western region development strategy and the Tarim River basin comprehensive devel-opment and implementation, the research is now focused on the Aksu River basin hydrologic charac-teristic and hydrologic forecast. Moreover, the Aksu River is representative of rivers supplied with gla-cier and snow melt in middle-high altitude arid district. As a result, the research on predicting the river flow of the Aksu River basin has theoretical and practical significance. In this paper, considering the limited hydrometeorological data for the Aksu River basin, we have constructed four hydrologic forecast approaches using the daily scale to simulate and forecast daily runoff of two big branches of the Aksu River basin. The four approaches are the upper air temperature and the daily runoff correlation method, AR(p) runoff forecast model, temperature and precipitation revised AR(p) model and the NAM rainfall-runoff model. After comparatively analyzing the simulation results of the four approaches, we discovered that the temperature and precipitation revised AR(p) model, which needs less hydrological and meteorological data and is more predictive, is suitable for the short-term runoff forecast of the Aksu River basin. This research not only offers a foundation for the Aksu River and Tarim Rivers' hydrologic forecast, flood prevention, control and the entire basin water collocation, but also provides the hydrologic forecast reference approach for other arid ungauged basins.     

Influence of the ionosphere, modified by powerful oblique radiowaves, on HF radio wave propagation

Variations of HF probe radio wave parameters caused by the influence on the ionosphere of oblique powerful HF radiowaves are analysed. The analysis is made on the data obtained from the original experiments carried out on single-hop paths in the middle and subauroral latitudes. Powerful and probe waves with some difference in frequency were chosen near MUF and were transmitted in the same direction. The polar diagrams of both transmitting systems overlapped in both the horizontal and vertical planes. The results obtained indicate that the ionospheric plasma parameters can be varied by powerful oblique HF radiowaves under certain geophysical conditions.     

Selection of the data time interval for the prediction of maximum ozone concentrations

This paper highlights the problem of step-length selection for the one-step-ahead prediction of ozone called the data time interval. This is done using a case study-based comparison of two approaches for predicting the maximum daily values of tropospheric ozone. The first approach is the 1-day-ahead prediction and the second is the prediction of the maximum values based on a multi-step-ahead iteration of 1-h predictions. Gaussian process modelling is utilised for this comparison. In particular, evolving Gaussian-process models are used that update on-line with the incoming measurement data. These sorts of models have been successfully used in the past for the prediction of ozone pollution. This paper contributes an assessment of the way that the maximum ozone values are predicted. A comparison of the daily maximum ozone values forecasted by a model based on 1-day-ahead predictions with those obtained by iterated 1-h-ahead predictions of the ozone with predictions at predetermined hours of the day is given. The forecast results are in favour of the on-line model based on hourly predictions when approaching closer to the real maximum values of ozone, and in favour of the daily predictions when they are made on a daily basis.     

Adaptation of the ionospheric radio channel parameters to the current conditions using observations of the signals of reference radio stations

A method of adaptation of the ionospheric channel parameters to the current conditions is proposed. The observational data on the temporal behavior of signals of radio stations with known location and set of working frequencies (the so-called reference stations) are used as information describing the current state of the channel. A facility that makes possible to determine by simple means the moments of radio rises and declines on the reference paths has been created. A technique that relates for these instants working frequencies of the stations with maximum usable frequencies of the paths has been developed. By means of an approximate solution of the inverse problem using the method of characteristics for the calculation of radiowave propagation and the monthly average semiempirical model of the ionosphere, the height profile of electron density in a certain spatial region is refined. The efficiency of the proposed method of adaptation of the ionospheric channel parameters using the data of vertical sounding is assessed and the expediency of practical application of such adaptation is shown.     

Water temperature modelling: comparison between the generalized additive model,logistic, residuals regression and linear regression models

Water temperature has a significant influence on aquatic organisms, including stenotherm fish such as salmonids. It is thus of prime importance to build reliable tools to forecast water temperature. This study evaluated a statistical scheme to model average water temperature based on daily average air temperature and average discharge at the Sainte-Marguerite River, Northern Canada. The aim was to test a non-parametric water temperature generalized additive model (GAM) and to compare its performance to three previously developed approaches: the logistic, residuals regression and linear regression models. Due to its flexibility, the GAM was able to capture some of the nonlinear response between water temperature and the two explanatory variables (air temperature and flow). The shape of these effects was determined by the trends shown in the collected data. The four models were evaluated annually using a cross-validation technique. Three comparison criteria were calculated: the root mean square error (RMSE), the bias error and the Nash-Sutcliffe coefficient of efficiency (NSC). The goodness of fit of the four models was also compared graphically. The GAM was the best among the four models (RMSE = 1.44°C, bias = ?0.04 and NSC = 0.94).     

Real-time flood forecasting with the use of inadequate data

Abstract

A modelling scheme is developed for real-time flood forecasting. It is composed of (a) a rainfall forecasting model, (b) a conceptual rainfall-runoff model, and (c) a stochastic error model of the ARMA family for forecast error correction. Initialization of the rainfall-runoff model is based on running this model on a daily basis for a certain period prior to the flood onset while parameters of the error model are updated through the Recursive Least Squares algorithm. The scheme is suitable for the early stages of operation of flood forecasting systems in the presence of inadequate historical data. A validation framework is set up which simulates real-time flood forecasting conditions. Thus, the effects of the procedures for rainfall-runoff model initialization, forecast error correction and rainfall forecasting are assessed. Two well-known conceptual rainfall-runoff models (the Soil Moisture Accounting model of the US National Weather Service River Forecast Service—SMA-NWSRFS and TANK) together with data from a Greek basin are used for illustration purposes.     

Assimilating Doppler radar observations with an ensemble Kalman filter for convection-permitting prediction of convective development in a heavy rainfall event during the pre-summer rainy season of South China

This study examines the effectiveness of an ensemble Kalman filter based on the weather research and forecasting model to assimilate Doppler-radar radial-velocity observations for convection-permitting prediction of convection evolution in a high-impact heavy-rainfall event over coastal areas of South China during the pre-summer rainy season. An ensemble of 40 deterministic forecast experiments(40 DADF) with data assimilation(DA) is conducted, in which the DA starts at the same time but lasts for different time spans(up to 2 h) and with different time intervals of 6, 12, 24, and 30 min. The reference experiment is conducted without DA(NODA).To show more clearly the impact of radar DA on mesoscale convective system(MCS)forecasts, two sets of 60-member ensemble experiments(NODA EF and exp37 EF) are performed using the same 60-member perturbed-ensemble initial fields but with the radar DA being conducted every 6 min in the exp37 EF experiments from 0200 to0400 BST. It is found that the DA experiments generally improve the convection prediction. The 40 DADF experiments can forecast a heavy-rain-producing MCS over land and an MCS over the ocean with high probability, despite slight displacement errors. The exp37 EF improves the probability forecast of inland and offshore MCSs more than does NODA EF. Compared with the experiments using the longer DA time intervals, assimilating the radial-velocity observations at 6-min intervals tends to produce better forecasts. The experiment with the longest DA time span and shortest time interval shows the best performance.However, a shorter DA time interval(e.g., 12 min) or a longer DA time span does not always help. The experiment with the shortest DA time interval and maximum DA window shows the best performance, as it corrects errors in the simulated convection evolution over both the inland and offshore areas. An improved representation of the initial state leads to dynamic and thermodynamic conditions that are more conducive to earlier initiation of the inland MCS and longer maintenance of the offshore MCS.     

Enhancing tidal prediction accuracy in a deterministic model using chaos theory

The classical deterministic approach to tidal prediction is based on barotropic or baroclinic models with prescribed boundary conditions from a global model or measurements. The prediction by the deterministic model is limited by the precision of the prescribed initial and boundary conditions. Improvement to the knowledge of model formulation would only marginally increase the prediction accuracy without the correct driving forces. This study describes an improvement in the forecasting capability of the tidal model by combining the best of a deterministic model and a stochastic model. The latter is overlaid on the numerical model predictions to improve the forecast accuracy. The tidal prediction is carried out using a three-dimensional baroclinic model and, error correction is instigated using a stochastic model based on a local linear approximation. Embedding theorem based on the time lagged embedded vectors is the basis for the stochastic model. The combined model could achieve an efficiency of 80% for 1 day tidal forecast and 73% for a 7 day tidal forecast as compared to the deterministic model estimation.     

Ensemble-Based Observation Targeting for Improving Ozone Prediction in Houston and the Surrounding Area

This study examines the effectiveness of targeted meteorological observations for improving ozone prediction in Houston and the surrounding area based on perfect-model simulation experiments. Supplementary observations are targeted for the location that has the highest impact factor (maximum Kalman gain) estimated from an ensemble and is expected to minimize ozone forecast uncertainty at the verification time. It is found that the observational impact factor field varies with time and is sensitive to ensemble resolutions and physics parameterizations. The efficiency of observation targeting is further examined through assimilating observations in areas with different impact factors using an ensemble Kalman filter. It is found that the ensemble sensitivity analysis is capable of locating supplementary observations that may reduce meteorological and ozone forecast error, but not as effectively as expected.     

IRI model in the problem of predicting ionospheric radio-wave propagation under conditions of high solar activity

The paper presents the results of an analysis of the correspondence between model representations the monthly mean diurnal dependences of critical frequency and vertical profiles of plasma frequency at local noon at IZMIRAN station for the middle months of the four seasons of 2014, the year of the maximum solar activity in the current 24th cycle. It is shown that in general the IRI model reliably describes the daily variation of foF2, and the smallest discrepancy is achieved when its basic input parameter is given by the ionospheric index of solar activity IG12. An exception is April, for which there is a fundamental discrepancy with the model both in the daily variation of the critical frequency foF2 and in the N _e (h)-profile for local noon time. For this month, the inadequacy in the model representation of the vertical distribution of the electron density turned out to be very significant in the calculation of the MUF: the relative error can reach 20%. The simulation results are confirmed by data from oblique-incidence ionospheric radio sounding.     

Artificial neural networks as routine for error correction with an application in Singapore regional model

This research presents an error correction scheme based on artificial neural networks, and demonstrates its application on water level forecast for the Singapore water. The error correction scheme combines the numerical model outputs with the in situ measurements on a two-step basis: (1) predicting the model errors at the measurement stations and (2) distributing the predicted errors to the nonmeasurement stations. Artificial neural networks are used in both error prediction and error distribution as the mapping function approximators. The efficiency of this scheme is tested on six water level stations in the Singapore regional model domain with four prediction horizons. The results show that this error correction scheme produces high-precision forecasts, and improves the forecast accuracy at both measurement and nonmeasurement stations.     

Prediction of the spatial distribution of the modified mercalli intensity using neural networks

This paper presents the development of an adaptive, non-parametric forecast model for the direct prediction of the spatial distribution of the Modified Mercalli Intensity (MMI) corresponding to an earthquake scenario. The model is based on recent advances in neural networks computation, and is constructed through supervised learning using historical earthquake and regional geological data as training sets. A MMI forecast model for moderate earthquakes with magnitudes between 6 and 7 was developed based on data from the Loma Prieta, Coalinga and Morgan Hill earthquakes. For these data sets, the neural networks forecast model is shown to have excellent data synthesis capability; multiple sets of data can be encapsulated by a relatively simple network architecture. Limited comparison of forecasts made by the neural networks model and conventional models demonstrates that improved accuracy can be achieved. Implementation and operational advantages of the neural networks approach such as general input features, minimum preconceived knowledge of the data sets, the ability to learn and to adapt incrementally and the autonomous and automatic synthesis of the structure underlying the data sets, have been illustrated.     

Time series forecasting by combining the radial basis function network and the self‐organizing map

Based on a combination of a radial basis function network (RBFN) and a self‐organizing map (SOM), a time‐series forecasting model is proposed. Traditionally, the positioning of the radial basis centres is a crucial problem for the RBFN. In the proposed model, an SOM is used to construct the two‐dimensional feature map from which the number of clusters (i.e. the number of hidden units in the RBFN) can be figured out directly by eye, and then the radial basis centres can be determined easily. The proposed model is examined using simulated time series data. The results demonstrate that the proposed RBFN is more competent in modelling and forecasting time series than an autoregressive integrated moving average (ARIMA) model. Finally, the proposed model is applied to actual groundwater head data. It is found that the proposed model can forecast more precisely than the ARIMA model. For time series forecasting, the proposed model is recommended as an alternative to the existing method, because it has a simple structure and can produce reasonable forecasts. Copyright © 2005 John Wiley & Sons, Ltd.     

Input-output model for runoff-sediment yield processes

Runoff (log-transformed) and sediment yield (log-transformed) sequences on a monthly or daily basis can be regarded as input and output for the watershed fluvial system. These sequences are nonstationary in general in different hydrological environments. Frequency and time domain analyses have shown that a parsimonious model can be built directly in terms of these nonstationary input-output sequences on a monthly and daily basis. A first-order dynamic model was found adequate to model the monthly runoff-sediment yield process; a second-order model adequately modeled the daily runoff-sediment yield process. The noise component in both cases possessed the characteristics of a white-noise sequence.     

Analysis of a lower jurassic geomagnetic reversal based on a model that relates transitional fields to variations of flux on the core surface

Summary For the last 12 Myr the transitional virtual geomagnetic poles (VGPs) of different reversals lie close to two preferred and practically antipodal longitudinal paths. In spite of some controversies about these transitional paths, it has been pointed out that they are linked to geomagnetic phenomena. Jurassic transitional VGP paths are quite similar to those of the last 12 Myr. Paleomagnetic data recorded in Stormberg Lavas (195 ± 5 Ma) belonging to two sampling localities of South Africa have been rotated according to an absolute palaeoreconstruction of Africa for the lower Jurassic. In order to avoid the hypothesis about dipolarity implicit in the VGPs calculations, the transitional directions recorded in the lavas were compared with others that were simulated on the basis of a model that relates transitional fields to variations of flux on the Earth's core surface. They were quite similar. For both, recorded and simulated data, the VGPs showed similar paths. Similar conditions could thus have driven both late Cenozoic and Jurassic reversals.