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1.
The temporal and seasonal variations of Total Electron Content (TEC) are studied at Agra (Geographic Lat. 27.17°N, Long. 78.89°E, Dip: 41.4°), India, which is in the equatorial anomaly region, for a period of 12 months from 01 January to 31 December, 2007 using a Global Positioning System (GPS) receiver. The mean TEC values show a minimum at 0500 h LT (LT = UT + 5.5 h) and a peak value at about 1400 h LT. The lowest TEC values are observed in winter whereas largest values are observed in equinox and summer. Anomalous variations are found during the period of magnetic disturbances. These results are compared with the TEC derived from IRI-2007 using three different options of topside electron density, NeQuick, IRI01-corr, and IRI-2001. A good agreement is found between the TEC obtained at Agra and those derived from IRI models.  相似文献   

2.
The time series of hourly electron density profiles N(h) obtained from 27 ionosonde stations distributed world-wide have been used to obtain N(h) average profiles on a monthly basis and to extract the expected bottom-side parameters that define the IRI profile under quiet conditions. The time series embrace the time interval from 1998 to 2006, which practically contains the entire solar cycle 23. The Spherical Harmonic Analysis (SHA) has been used as an analytical technique for modeling globally the B0 and B1 parameters as general functions on a spherical surface. Due to the irregular longitudinal distribution of the stations over the globe, it has been assumed that the ionosphere remains approximately constant in form for a given day under quiet conditions for a particular coordinate system. Since the Earth rotates under a Sun-fixed system, the time differences have been considered to be equivalent to longitude differences. The time dependence has been represented by a two-degree Fourier expansion to model the annual and semiannual variations and the year-by-year analyses of the B0 and B1 have furnished nine sets of spherical harmonic coefficients for each parameter. The spatial–temporal yearly coefficients have been further expressed as linear functions of Rz12 to model the solar cycle dependence. The resultant analytical model provides a tool to predict B0 and B1 at any location distributed among the used range of latitudes (70°N–50°S) and at any time that improves the fit to the observed data with respect to IRI prediction.  相似文献   

3.
The aim of this paper is to investigate various aspects of the International Reference Ionosphere (IRI) performance in European area and to evaluate its accuracy and efficiency for: long term prediction of the critical frequencies foF2 and the maximum usable frequencies (MUF); using storm-time correction option (ST); the total electron content (TEC) and the maximum observable frequency (MOF) updating. Data of foF2, TEC, MOF are related to 2005. It is obtained that median values of foF2 can be predicted with the mean error σ(med)∼ 0.49 MHz. For median values of MUF absolute σ was 1.39 MHz and relative σr was 8.8%. For instanteneous values estimates are increased to 1.58σ(med) MHz for foF2 and could reach 3.84 MHz for MUF. Using correction ST-option and TEC values provided ∼30% improvement but TEC seems to be more preferable. However, from considered parameters of the IRI updating (ST-factor, TEC, MOF) the best results were demonstrated by MOF. Using the IRI2007 to calculate TEC gives 20–50% improvement of TEC correspondence to experimental values but this improvement is not enough to treat TEC without the IRI model adaptation.  相似文献   

4.
Monthly median values of foF2, hmF2 and M(3000)F2 parameters, with hourly time interval resolution for the diurnal variation, obtained with DPS-4 digisonde observations at Hainan (19.4°N, 109.0°E) are used to study the low latitude ionospheric variation behavior. The observational results are compared with the International Reference Ionospheric Model (IRI) predictions. The time period coverage of the data used for the present study is from March 2002 to February 2005. Our present study showed that: (1) In general, IRI predictions using CCIR and URSI coefficients follow well the diurnal and seasonal variation patterns of the experimental values of foF2. However, CCIR foF2 and URSI foF2 IRI predictions systematically underestimate the observed results during most time period of the day, with the percentage difference ΔfoF2 (%) values changing between about −5% and −25%, whereas for a few hours around pre-sunrise, the IRI predictions generally overestimate the observational ones with ΔfoF2 (%) sometimes reaching as large as ∼30%. The agreement between the IRI results and the observational ones is better for the year 2002 than for the other years. The best agreement between the IRI results and the observational ones is obtained in summer when using URSI coefficients, with the seasonal average values of ΔfoF2 (%) being within the limits of ±10%. (2) In general, the IRI predicted hmF2 values using CCIR M(3000)F2 option shows a poor agreement with the observational results. However, when using the measured M(3000)F2 as input, the diurnal variation pattern of hmF2 given by IRI2001 has a much better agreement with the observational one with the detailed fine structures including the pre-sunrise and post-sunset peaks reproduced reasonably well. The agreement between the IRI predicted hmF2 values using CCIR M(30,000)F2 option and the observational ones is worst for the afternoon to post-midnight hours for the high solar activity year 2002. During daytime hours the agreement between the hmF2 values obtained with CCIR M(30,000)F2 option and the observational ones is best for summer season. The discrepancy between the observational hmF2 and that obtained with CCIR M(30,000)F2 option stem from the CCIR M(3000)F2 model, which does not produce the small scale structures observed in the measured M(3000)F2.  相似文献   

5.
The IRI model offers a choice of options for the computation of the electron density profile and electron content (TEC). Recently new options for the topside electron density profile have been developed, which have a strong impact on TEC. Therefore it is important to test massively the IRI and the new options with experimental data. A large number of permanent stations record dual frequency GPS data from which it is possible to obtain TEC values. Thirty-one worldwide distributed stations have been selected to investigate the capabilities of the IRI to reproduce experimental TEC. Data for years 2000 (high solar activity) and 2004 (medium solar activity) have been analyzed computing modeled values with the IRI-2001 and the IRI-2007-NeQuick topside options. It is found that IRI-2007-NeQuick option generally improves the estimate of the slant TEC, especially in the case of high latitudes stations during high solar activity.  相似文献   

6.
Computerized ionospheric tomography (CIT) is a method to estimate ionospheric electron density distribution by using the global positioning system (GPS) signals recorded by the GPS receivers. Ionospheric electron density is a function of latitude, longitude, height and time. A general approach in CIT is to represent the ionosphere as a linear combination of basis functions. In this study, the model of the ionosphere is obtained from the IRI in latitude and height only. The goal is to determine the best representing basis function from the set of Squeezed Legendre polynomials, truncated Legendre polynomials, Haar Wavelets and singular value decomposition (SVD). The reconstruction algorithms used in this study can be listed as total least squares (TLS), regularized least squares, algebraic reconstruction technique (ART) and a hybrid algorithm where the reconstruction from the TLS algorithm is used as the initial estimate for the ART. The error performance of the reconstruction algorithms are compared with respect to the electron density generated by the IRI-2001 model. In the investigated scenario, the measurements are obtained from the IRI-2001 as the line integral of the electron density profiles, imitating the total electron content estimated from GPS measurements. It has been observed that the minimum error between the reconstructed and model ionospheres depends on both the reconstruction algorithm and the basis functions where the best results have been obtained for the basis functions from the model itself through SVD.  相似文献   

7.
We have employed the hourly values of the ionospheric F-region critical frequency (foF2) obtained from Ouagadougou ionosonde, Burkina Faso (geographic coordinates 12° N, 1.8° W) during the interval of 1985–1995 (solar cycle 22) and solar radio flux of 10 cm wavelength (F10.7) to develop a local model (LM) for the African low-latitude station. The model was developed from regression analysis method, using the two-segmented regression analysis. We validated LM with foF2 data from Korhogo observatory, Cote d’Ivorie (geographical coordinates 9.3° N, 5.4° W). LM as well as the International Reference Ionosphere (IRI) agrees well with observations. LM gave some improvement on the IRI-predicted foF2 values at the sunrise (06 LT) at all solar flux levels and in all seasons except June solstice. The performance of the models at the representing the salient features of the equatorial foF2 was presented. Considering daytime and nighttime performances, LM and IRI are comparable in low solar activity (LSA), LM performed better than IRI in moderate solar activity (MSA), while IRI performed better than LM in high solar activity (HSA). CCIR has a root mean square error (r.m.s.e), which is only 0.10 MHz lower than that of LM while LM has r.m.s.e, which is about 0.05 MHz lower than that of URSI. In general, our result shows that performance of IRI, especially the CCIR option of the IRI, is quite comparable with the LM. The improved performance of IRI is a reflection of the numerous contributions of ionospheric physicists in the African region, larger volume of data for the IRI and the diversity of data sources, as well as the successes of the IRI task force activities.  相似文献   

8.
Monthly median values of foF2, hmF2 and M(3000)F2 parameters, with quarter-hourly time interval resolution for the diurnal variation, obtained with DPS4 digisonde at Hainan (19.5°N, 109.1°E; Geomagnetic coordinates: 178.95°E, 8.1°N) are used to investigate the low-latitude ionospheric variations and comparisons with the International Reference Ionosphere (IRI) model predictions. The data used for the present study covers the period from February 2002 to April 2007, which is characterized by a wide range of solar activity, ranging from high solar activity (2002) to low solar activity (2007). The results show that (1) Generally, IRI predictions follow well the diurnal and seasonal variation patterns of the experimental values of foF2, especially in the summer of 2002. However, there are systematic deviation between experimental values and IRI predictions with either CCIR or URSI coefficients. Generally IRI model greatly underestimate the values of foF2 from about noon to sunrise of next day, especially in the afternoon, and slightly overestimate them from sunrise to about noon. It seems that there are bigger deviations between IRI Model predictions and the experimental observations for the moderate solar activity. (2) Generally the IRI-predicted hmF2 values using CCIR M(3000)F2 option shows a poor agreement with the experimental results, but there is a relatively good agreement in summer at low solar activity. The deviation between the IRI-predicted hmF2 using CCIR M(3000)F2 and observed hmF2 is bigger from noon to sunset and around sunrise especially at high solar activity. The occurrence time of hmF2 peak (about 1200 LT) of the IRI model predictions is earlier than that of observations (around 1500 LT). The agreement between the IRI hmF2 obtained with the measured M(3000)F2 and the observed hmF2 is very good except that IRI overestimates slightly hmF2 in the daytime in summer at high solar activity and underestimates it in the nighttime with lower values near sunrise at low solar activity.  相似文献   

9.
The International Reference Ionosphere IRI-2001 model contains geomagnetic activity dependence based on an empirical storm time ionospheric correction (STORM model). An extensive validation of the STORM model for the middle latitude region has been performed. In this paper the ability of the STORM model to predict foF2 values at high latitudes is analyzed. For this, ionosonde data obtained at Base Gral. San Martin (68.1°S, 293°E) are compared with those obtained by the IRI-2001 model with or without storm correction during four geomagnetic storms that occurred in 2000 (Rz12 = 117) and 2001 (Rz12 = 111). The results show that predicted values with the STORM model follow the behaviour of foF2 experimental data better than without the STORM model. The relative deviation between measured and predicted foF2 reaches values of up to 24% and 43% with and without the STORM model in IRI-2001, during the main phase of the storms. In order to explain increases of electron density that occurred prior to the storm onset and also decreases of electron density observed during the first part of the recovery of the storm, possible physical mechanisms are discussed.  相似文献   

10.
In this paper, data of (B0, B1) parameters deduced from the electron density profiles that are inverted from the ionograms recorded at Hainan (19.4°N, 109.0°E), China during a three year period from March 2002 to February 2005 are used to study the diurnal and seasonal variation of (B0, B1) parameters at low latitude. The observational results are compared with the IRI2001 model predictions. Variability study of (B0, B1) in terms of percentage ratio of the inter-quartiles to the median values and correlative analysis between (B0, B1) parameters and other ionospheric characteristics such as hmF2 and M(3000)F2 are also made. Our present study showed that: (1) for daytime hours, the IRI2001 model results with new table option (B0_Tab) is in a better agreement with the observational results (B0_Obs) than the IRI2001 model results with Gulyaeva option (B0_Gul) for summer season, whereas B0_Gul is in a better agreement with B0_Obs than B0_Tab for winter season. For nighttime, in general, B0_Gul is in a better agreement with B0_Obs than B0_Tab. For other occasions, both B0_Tab and B0_Gul showed some systematic deviations from the observational ones. Moreover, the deviations of B0_Tab and B0_Gul from B0_Obs showed opposite trends; (2) the monthly upper (lower) quartiles of (B0, B1) parameter showed a good linear relationship with the monthly median values, this makes it possible to do the regression analysis between the monthly upper (lower) quartiles and the monthly median values, which can give a measure of the variability of these parameters. In terms of the percentage ratio of the inter-quartiles to the median values, the variability of B0 showed a diurnal variation ranging between 22% and 36% with maximum value occurring at pre-sunrise hours, whereas the variability of B1 showed a diurnal variation ranging between 15% and 30% with higher value by daytime than at night; (3) B0 shows high linear correlative relationships with hmF2 and M(3000)F2 for most of the local time period of a day except for a few hours around midnight, whereas B1 showed high linear correlations with B0, hmF2 for daytime hours, but not for nighttime hours. This suggests that it maybe is possible to obtain the synthetic database of (B0, B1) parameter or to construct the model of (B0, B1) using database of hmF2 or M(3000)F2 which is much easier to obtain from experimental measurements.  相似文献   

11.
Total electron content (TEC) measured simultaneously using Global Positioning System (GPS) ionospheric monitors installed at some locations in Nigeria during the year 2011 (Rz = 55.7) was used to study the diurnal, seasonal, and annual TEC variations. The TEC exhibits daytime maximum, seasonal variation and semiannual variations. Measured TEC were compared with those predicted by the improved versions of the International Reference Ionosphere (IRI) and NeQuick models. The models followed the diurnal and seasonal variation patterns of the observed values of TEC. However, IRI model produced better estimates of TEC than NeQuick at all locations.  相似文献   

12.
The International Reference Ionosphere (IRI) parameters B0 and B1 provide a representation of the thickness and shape, respectively, of the F2 layer of the bottomside ionosphere. These parameters can be derived from electron density profiles that are determined from vertical incidence ionograms. This paper aims to illustrate the variability of these parameters for a single mid latitude station and demonstrate the ability of the Neural Network (NN) modeling technique for developing a predictive model for these parameters. Grahamstown, South Africa (33.3°S, 26.5°E) was chosen as the mid latitude station used in this study and the B0 and B1 parameters for an 11 year period were determined from electron density profiles recorded at that station with a University of Massachusetts Lowell Center for Atmospheric Research (UMLCAR) Digisonde. A preliminary single station NN model was then developed using the Grahamstown data from 1996 to 2005 as a training database, and input parameters known to affect the behaviour of the F2 layer, such as day number, hour, solar and magnetic indices. An analysis of the diurnal, seasonal and solar variations of these parameters was undertaken for the years 2000, 2005 and 2006 using hourly monthly median values. Comparisons between the values derived from measured data and those predicted using the two available IRI-2001 methods (IRI tables and Gulyaeva, T. Progress in ionospheric informatics based on electron density profile analysis of ionograms. Adv. Space Res. 7(6), 39–48, 1987.) and the newly developed NN model are also shown in this paper. The preliminary NN model showed that it is feasible to use the NN technique to develop a prediction tool for the IRI thickness and shape parameters and first results from this model reveal that for the mid latitude location used in this study the NN model provides a more accurate prediction than the current IRI model options.  相似文献   

13.
This paper presents the development of a Total Electron Content (TEC) map for the Nigerian ionosphere. In this work, TEC measurements obtained from the AFRL-SCINDA GPS (Air Force Research Laboratory-Scintillation Network Decision Aid, Global Positioning System) equipment installed at Nsukka (6.87°N, 7.38°E) are used to adapt the International Reference Ionosphere (IRI) model for the Nigerian Ionosphere. The map is being developed as a computer program (implemented in the MATLAB programming language) that shows spatial and temporal representations of TEC for the Nigerian ionosphere. The method is aimed at showing how the IRI model can be used to estimate VTEC over wide areas by incorporating GPS measurements. This method is validated by using GPS VTEC data collected from a station in Ilorin (8.50°N, 4.55°E).  相似文献   

14.
This paper reports the diurnal, seasonal, and long term variability of the E layer critical frequency (foE) and peak height (hmE) derived from Digisonde measurements from 2009 to 2016 at the low-middle latitude European station of Nicosia, Cyprus (geographical coordinates: 35°N, 33°E, geomagnetic lat. 29.38°N, I = 51.7°). Manually scaled monthly median values of foE and hmE are compared with IRI-2012 predictions with a view to assess the predictability of IRI. Results show that in general, IRI slightly overestimates foE values both at low and high solar activity. At low solar activity, overestimations are mostly limited to 0.25?MHz (equivalent electron density, 0.775?×?103?el/m?3) but can go as high as 0.5?MHz (equivalent electron density, 3.1?×?103?el/m?3, during noon) around equinox. In some months, underestimations, though sporadic in nature, up to 0.25?MHz are noted (mostly during sunrise and sunset). At high solar activity, a similar pattern of over-/underestimation is evident. During the entire period of study, over-/under estimations are mostly limited to 0.25?MHz. In very few cases, these exceed 0.25?MHz but are limited to 0.5?MHz. Analysis of hmE reveals that: (1) hmE remains almost constant during ±2 to ±4?h around local noon, (2) hmE values are higher in winter than in spring, summer and autumn, (3) there are two maxima near sunrise and sunset with a noontime minimum in between. During the entire period of study, significant differences between observed hmE and the IRI predictions have been noted. IRI fails to predict hmE and outputs a constant value of 110?km, which is higher than most of the observed values. Over- and under estimations range from 3 to 13?km and from 0 to 3?km respectively.  相似文献   

15.
A method is proposed for reconstructing the electron density profiles N(h) of the IRI model from ionograms of topside satellite sounding of the ionosphere. An ionograms feature is the presence of traces of signal reflection from the Earth's surface. The profile reconstruction is carried out in two stages. At the first stage, the N(h) –profile is calculated from the lower boundary of the ionosphere to the satellite height (total profile) by the method presented in this paper using the ionogram. In this case, the monotonic profile of the topside ionosphere is calculated by the classical method. The profile of the inner ionosphere is represented by analytical functions, the parameters of which are calculated by optimization methods using traces of signal reflection, both from the topside ionosphere and from the Earth. At the second stage, the profile calculated from the ionogram is used to obtain the key parameters: the height of the maximum hmF2 of the F2 layer, the critical frequency foF2, the values of B0 and B1, which determine the profile shape in the F region in the IRI model. The input of key parameters, time of observation, and coordinates of sounding into the IRI model allows obtaining the IRI-profile corrected to real experimental conditions. The results of using the data of the ISIS-2 satellite show that the profiles calculated from the ionograms and the IRI profiles corrected from them are close to each other in the inner ionosphere and can differ significantly in the topside ionosphere. This indicates the possibility of obtaining a profile in the inner ionosphere close to the real distribution, which can significantly expand the information database useful for the IRTAM (IRI Realmax Assimilative Modeling) model. The calculated profiles can be used independently for local ionospheric research.  相似文献   

16.
A new set of data obtained at low solar activity from Ilorin, Nigeria (geog. latitude 8.5°N, geog longitude, 4.6°E, dip 4.1°S) is used to validate the IRI 2001 model at low solar activity. The results show in general a good agreement between model and observed B0 at night but an over estimation during daytime. The overestimation is greatest during the morning period (0600LT–1000LT). The model prediction for B1 is fairly good at night and during the day. A dependence of B0 on solar zenith angle χ is observed during the daytime. A formulation of the form B0 = A[cos(χ)n] is therefore proposed. Values of the constants n and A were determined for the period of low solar activity for this station.  相似文献   

17.
The hourly measurements of M(3000)F2 (M(3000)F2meas) and the hourly quiet-time values of M(3000)F2 (M(3000)F2QT) relative to the ionospheric observatories of Poitiers, Lannion, Dourbes, Slough, Rome, Juliusruh, Kaliningrad, Uppsala, Lyckesele, Sodankyla, and Kiruna as well as the hourly time-weighted accumulation series derived from the geomagnetic planetary index ap (ap(τ)), were considered during the period January 1957–December 2003 and used for the development of 11 short-term forecasting local models (STFLM) of M(3000)F2.  相似文献   

18.
An ionospheric spatial gradient represents the ionosphere delay difference between different locations, and its variation over a specific area is important for implementing differential GNSS systems. An estimation method for the ionospheric spatial gradient over a small regional area is proposed. A plate map model is implemented for the direct estimation of the gradients. Nine years of GPS data were processed to figure out the annual variation of the mean gradient at the mid-geomagnetic latitude of 30° N. Gradients along the north–south direction have a mean of 0.65 mm/km and follow solar-cycle variations.  相似文献   

19.
We have used the technique of expansion in Empirical Orthogonal Functions (EOFs) to develop regional models of the critical frequencies of E and F2 layers (foE, foF2), peak height (hmF2), and semi-thickness of F2 layer (YmF2) over Pakistan. In the present study levels of solar activity specified by Smoothed Sunspot Number (R) from 10 to 200 are taken into account. The magnetic dip angle for the model ranges from 30° to 60°. We have compared the regional model and the International Reference Ionosphere (IRI) with measurements of three ionosondes in Pakistan. The model parameters foE and foF2 are found overall comparable to the observed hourly median values during daytime at Karachi (geographic latitude = 24.95°N, longitude = 67.13°E, magnetic inclination = 37°), Multan (30.18°N, 71.48°E, 45°) and Islamabad (33.75°N, 73.13°E, 51.5°) during the years 1988, 1996 and 2000. For hmF2 the computed values by regional and IRI model for the year 1995 are found close to each other. However, for YmF2the results are better during daytime as compared to nighttime.  相似文献   

20.
This paper presents results from the Storm-Time Ionospheric Correction Model (STORM) validation for selected Northern and Southern Hemisphere middle latitude locations. The created database incorporated 65 strong-to-severe geomagnetic storms, which occurred within the period 1995–2007. This validation included data from some ionospheric stations (e.g., Pruhonice, El Arenosillo) that were not considered in the development or previous validations of the model. Hourly values of the F2 layer critical frequency, foF2, measured for 5–7 days during the main and recovery phases of each selected storm were compared with the predicted IRI 2007 foF2 with the STORM model option activated. To perform a detailed comparison between observed values, medians and predicted foF2 values the correlation coefficient, the root-mean-square error (RMSE), and the percentage improvement were calculated. Results of the comparative analysis show that the STORM model captures more effectively the negative phases of the summer ionospheric storms, while electron density enhancement during winter storms and the changeover of the different storm phases is reproduced with less accuracy. The STORM model corrections are less efficient for lower-middle latitudes and severe geomagnetic storms.  相似文献   

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