A simple model to predict solar radiation under clear sky conditions

Solar radiation is one of the major factors that dominate the thermal behaviors of aerostats in the daytime and the primary energy source of high altitude long endurance aerostats. Therefore, it is necessary to propose an accurate model to predict the solar irradiances. A comprehensive review of the well-known solar radiation models is conducted to help develop the new model. Based on the analysis of the existing models and the available radiation data, the extensive computer tests of the regression and optimization are conducted, from which the new solar radiation model for direct and diffuse irradiances under clear sky conditions is proposed. The new model has excellent prediction accuracy. The coefficient of determination for direct radiation is 0.992, with the root mean square error (RMSE) of 16.9 W/m² and the mean absolute error (MAE) of 2.2%. The coefficient of determination for diffuse radiation is 0.86, with RMSE = 8.7 W/m² and MAE = 9.9%. Comparisons with the well-known existing models show that the new model is much more accurate than the best existing ones.     

Sensitivity analysis for air temperature profile estimation methods around the tropopause using simulated Aqua/AIRS data

A sensitivity analysis is performed to investigate potential improvements to the accuracy of air temperature profile retrievals near the tropopause. A simple inversion method is employed to identify and remove redundant spectral channels from the retrievals using simulated data for the high-spectral resolution sounder AIRS (Atmospheric Infrared Sounder) on the Aqua satellite. Bayesian optimal theory and inverse technique are applied for the atmospheric temperature profile retrievals, and the 15 μm CO₂ absorption bands (620–750 cm⁻¹) are chosen for this study. Sequentially elimination of redundant channels is directly integrated into the inverse scheme for the temperature profile, in order to accurately retain the valuable channels and remove all the redundant channels, for accurate retrieval of the temperature profile. Also, the tropopause and troposphere are treated differently in the inverse scheme to improve the retrieval accuracy in the tropopause. Results of a sensitivity analysis based on this method, for the Tropical and Middle-Latitude Summer models simulated by MODTRAN4.0, show that the estimated accuracies are improved by 2 K around the tropopause, and are only changed by less than 0.2 K in the troposphere.     

Experimental investigation of transient thermal behavior of an airship under different solar radiation and airflow conditions

Knowledge of the thermal behavior of airships is crucial to the development of airship technology. An experiment apparatus is constructed to investigate the thermal response characteristics of airships, and the transient temperature distributions of both hull and inner gas are obtained under the irradiation of a solar simulator and various airflow conditions. In the course of the research, the transient temperature change of the experimental airship is measured for four airflow speeds of 0 m/s (natural convection), 3.26 m/s, 5.5 m/s and 7.0 m/s, and two incident solar radiation values of 842.4 W/m² and 972.0 W/m². The results show that solar irradiation has significant influence on the airship hull and inner gas temperatures even if the airship stays in a ground airflow environment where the heat transfer is dominated by radiation and convection. The airflow around the airship is conducive to reduce the hull temperature and temperature nonuniformity. Transient thermal response of airships rapidly varies with time under solar radiation conditions and the hull temperature remains approximately constant in ∼5–10 min. Finally, a transient thermal model of airship is developed and the model is validated through comparison with the experimental data.     

A prediction model of short-term ionospheric foF2 based on AdaBoost

In this paper, the AdaBoost-BP algorithm is used to construct a new model to predict the critical frequency of the ionospheric F2-layer (foF2) one hour ahead. Different indices were used to characterize ionospheric diurnal and seasonal variations and their dependence on solar and geomagnetic activity. These indices, together with the current observed foF2 value, were input into the prediction model and the foF2 value at one hour ahead was output. We analyzed twenty-two years’ foF2 data from nine ionosonde stations in the East-Asian sector in this work. The first eleven years’ data were used as a training dataset and the second eleven years’ data were used as a testing dataset. The results show that the performance of AdaBoost-BP is better than those of BP Neural Network (BPNN), Support Vector Regression (SVR) and the IRI model. For example, the AdaBoost-BP prediction absolute error of foF2 at Irkutsk station (a middle latitude station) is 0.32 MHz, which is better than 0.34 MHz from BPNN, 0.35 MHz from SVR and also significantly outperforms the IRI model whose absolute error is 0.64 MHz. Meanwhile, AdaBoost-BP prediction absolute error at Taipei station from the low latitude is 0.78 MHz, which is better than 0.81 MHz from BPNN, 0.81 MHz from SVR and 1.37 MHz from the IRI model. Finally, the variety characteristics of the AdaBoost-BP prediction error along with seasonal variation, solar activity and latitude variation were also discussed in the paper.     

3D Imaging of the OH mesospheric emissive layer

A new and original stereo imaging method is introduced to measure the altitude of the OH nightglow layer and provide a 3D perspective map of the altitude of the layer centroid. Near-IR photographs of the OH layer are taken at two sites separated by a 645 km distance. Each photograph is processed in order to provide a satellite view of the layer. When superposed, the two views present a common diamond-shaped area. Pairs of matched points that correspond to a physical emissive point in the common area are identified in calculating a normalized cross-correlation coefficient (NCC). This method is suitable for obtaining 3D representations in the case of low-contrast objects. An observational campaign was conducted in July 2006 in Peru. The images were taken simultaneously at Cerro Cosmos (12°09′08.2″ S, 75°33′49.3″ W, altitude 4630 m) close to Huancayo and Cerro Verde Tellolo (16°33′17.6″ S, 71°39′59.4″ W, altitude 2272 m) close to Arequipa. 3D maps of the layer surface were retrieved and compared with pseudo-relief intensity maps of the same region. The mean altitude of the emission barycenter is located at 86.3 km on July 26. Comparable relief wavy features appear in the 3D and intensity maps. It is shown that the vertical amplitude of the wave system varies as exp (Δz/2H) within the altitude range Δz = 83.5–88.0 km, H being the scale height. The oscillatory kinetic energy at the altitude of the OH layer is comprised between 3 × 10⁻⁴ and 5.4 × 10⁻⁴ J/m³, which is 2–3 times smaller than the values derived from partial radio wave at 52°N latitude.     

Advanced receiver autonomous integrity monitoring (ARAIM) schemes with GNSS time offsets

Within the current Advanced Receiver Integrity Monitoring (ARAIM) scheme, the time offsets between different Global Navigation Satellite System (GNSS) constellations are estimated along with a position solution and the GNSS receiver clock error. This scheme is called the Time-offsets Estimated ARAIM, or the TOE ARAIM. In order to enhance the interoperability and compatibility between different constellations, the time offsets are expected to be broadcast to users in future multi-GNSS positioning and navigation applications. This paper describes two new ARAIM schemes to make use of the Broadcast Time Offsets (BTOs): Time Offset Observed ARAIM (TOO ARAIM) and Time Offset Synchronized ARAIM (TOS ARAIM). It has been shown that the VPL performances of these two new ARAIM schemes rely strongly on the accuracy of BTOs. By varying the error model of the BTOs, the simulation results also demonstrate that the proposed new TOO ARAIM scheme can outperform the existing TOE ARAIM scheme-even if the accuracy of BTOs for integrity is degraded to 4.5 m and the probability of a BTO fault is relaxed to 10⁻² h⁻¹. In addition, the new Time Offset Synchronized ARAIM scheme (TOS ARAIM) can also perform better than the existing TOE ARAIM scheme if the accuracy of BTOs for integrity can reach 0.75 m. As the TOO ARAIM also has a very relaxed requirement on BTOs and better VPL performance, the TOO ARAIM is regarded as a superior ARAIM scheme for multi-GNSS with BTOs available.     

The GFZ real-time GNSS precise positioning service system and its adaption for COMPASS

Motivated by the IGS real-time Pilot Project, GFZ has been developing its own real-time precise positioning service for various applications. An operational system at GFZ is now broadcasting real-time orbits, clocks, global ionospheric model, uncalibrated phase delays and regional atmospheric corrections for standard PPP, PPP with ambiguity fixing, single-frequency PPP and regional augmented PPP. To avoid developing various algorithms for different applications, we proposed a uniform algorithm and implemented it into our real-time software. In the new processing scheme, we employed un-differenced raw observations with atmospheric delays as parameters, which are properly constrained by real-time derived global ionospheric model or regional atmospheric corrections and by the empirical characteristics of the atmospheric delay variation in time and space. The positioning performance in terms of convergence time and ambiguity fixing depends mainly on the quality of the received atmospheric information and the spatial and temporal constraints. The un-differenced raw observation model can not only integrate PPP and NRTK into a seamless positioning service, but also syncretize these two techniques into a unique model and algorithm. Furthermore, it is suitable for both dual-frequency and sing-frequency receivers. Based on the real-time data streams from IGS, EUREF and SAPOS reference networks, we can provide services of global precise point positioning (PPP) with 5–10 cm accuracy, PPP with ambiguity-fixing of 2–5 cm accuracy, PPP using single-frequency receiver with accuracy of better than 50 cm and PPP with regional augmentation for instantaneous ambiguity resolution of 1–3 cm accuracy. We adapted the system for current COMPASS to provide PPP service. COMPASS observations from a regional network of nine stations are used for precise orbit determination and clock estimation in simulated real-time mode, the orbit and clock products are applied for real-time precise point positioning. The simulated real-time PPP service confirms that real-time positioning services of accuracy at dm-level and even cm-level is achievable with COMPASS only.     

Achievable debris orbit prediction accuracy using laser ranging data from a single station

Earlier studies have shown that an orbit prediction accuracy of 20 arc sec ground station pointing error for 1–2 day predictions was achievable for low Earth orbit (LEO) debris using two passes of debris laser ranging (DLR) data from a single station, separated by about 24 h. The accuracy was determined by comparing the predicted orbits with subsequent tracking data from the same station. This accuracy statement might be over-optimistic for other parts of orbit far away from the station. This paper presents the achievable orbit prediction accuracy using satellite laser ranging (SLR) data of Starlette and Larets under a similar data scenario as that of DLR. The SLR data is corrupted with random errors of 1 m standard deviation so that its accuracy is similar to that of DLR data. The accurate ILRS Consolidated Prediction Format orbits are used as reference to compute the orbit prediction errors. The study demonstrates that accuracy of 20 arc sec for 1–2 day predictions is achievable.     

A comparison of different regression models for downscaling Landsat and MODIS land surface temperature images over heterogeneous landscape

Remotely sensed high spatial resolution thermal images are required for various applications in natural resource management. At present, availability of high spatial resolution (<200 m) thermal images are limited. The temporal resolution of such images is also low. Whereas, coarser spatial resolution (∼1000 m) thermal images with high revisiting capability (∼1 day) are freely available. To bridge this gap, present study attempts to downscale coarser spatial resolution thermal image to finer spatial resolution using relationships between land surface temperature (LST) and vegetation indices over a heterogeneous landscape of India. Five regression based models namely (i) Disaggregation of Radiometric Temperature (DisTrad), (ii) Temperature Sharpening (TsHARP), (iii) TsHARP with local variant, (iv) Least median square regression downscaling (LMS_DS) and (v) Pace regression downscaling (PR_DS) are applied to downscale LST of Landsat Thematic Mapper (TM) and Terra MODIS (Moderate Resolution Imaging Spectroradiometer) images. All the five models are first evaluated on Landsat image aggregated to 960 m resolution and downscaled to 480 m and 240 m resolution. The downscale accuracy is achieved using LMS_DS and PR_DS models at 240 m resolution at 0.61 °C and 0.75 °C respectively. MODIS data downscaled from 1000 m to 250 m spatial resolution results root mean square error (RMSE) of 1.43 °C and 1.62 °C for LMS_DS and PR_DS models, respectively. The LMS_DS model is less sensitive to outliers in heterogeneous landscape and provides higher accuracy when compared to other models. Downscaling model is found to be suitable for agricultural and vegetated landscapes up to a spatial resolution of 250 m but not applicable to water bodies, dry river bed sand sandy open areas.     

Lunar exosphere influence on lunar-based near-ultraviolet astronomical observations

The potential effect of the lunar exosphere on the near-ultraviolet sky background emission is predicted for Lunar-based Ultraviolet Telescope (LUT: a funded Chinese scientific payload for the Chang’e-III mission). Using the upper limit on the OH concentration inferred from the recent MIP CHACE results, our calculations show that the sky brightness due to the illuminated exosphere is <8.7 photons⁻¹ cm⁻² arcsec⁻² within the wavelength range 245–340 nm. By evaluating the signal-to-noise ratios of observations of an AB = 13 mag point source at a series of sky background levels, our analysis indicates that the detection performance of LUT can be moderately degraded by the lunar exosphere emission in most cases. An AB = 13 mag point source can still be detected by the telescope at a signal-to-noise ratio more than 8 when the OH concentration is less than 2 × 10⁸ molecules cm⁻³. However, the effect on the performance is considerable when the exosphere is as dense as suggested by CHACE.     

Towards development of a consistent orbit series for TOPEX,Jason-1, and Jason-2

The TOPEX/Poseidon, Jason-1 and Jason-2 set of altimeter data now provide a time series of synoptic observations of the ocean that span nearly 17 years from the launch of TOPEX in 1992. The analysis of the altimeter data including the use of altimetry to monitor the global change in mean sea level requires a stable, accurate, and consistent orbit reference over the entire time span. In this paper, we describe the recomputation of a time series of orbits that rely on a consistent set of reference frames and geophysical models. The recomputed orbits adhere to the IERS 2003 standards for ocean and earth tides, use updates to the ITRF2005 reference frame for both the SLR and DORIS stations, apply GRACE-derived models for modeling of the static and time-variable gravity, implement the University College London (UCL) radiation pressure model for Jason-1, use improved troposphere modeling for the DORIS data, and apply the GOT4.7 ocean tide model for both dynamical ocean tide modeling and for ocean loading. The new TOPEX orbits have a mean SLR fit of 1.79 cm compared to 2.21 cm for the MGDR-B orbits. These new TOPEX orbits agree radially with independent SLR/crossover orbits at 0.70 cm RMS, and the orbit accuracy is estimated at 1.5–2.0 cm RMS over the entire TOPEX time series. The recomputed Jason-1 orbits agree radially with the Jason-1 GDR-C orbits at 1.08 cm RMS. The GSFC SLR/DORIS dynamic and reduced-dynamic orbits for Jason-2 agree radially with independent orbits from the CNES and JPL at 0.70–1.06 cm RMS. Applying these new orbits, and using the latest altimeter corrections for TOPEX, Jason-1, and Jason-2 from September 1992 to May 2009, we find a global rate in mean sea level of 3.0 ± 0.4 mm/yr.     

Onboard orbit determination using GPS observations based on the unscented Kalman filter

Spaceborne GPS receivers are used for real-time navigation by most low Earth orbit (LEO) satellites. In general, the position and velocity accuracy of GPS navigation solutions without a dynamic filter are 25 m (1σ) and 0.5 m/s (1σ), respectively. However, GPS navigation solutions, which consist of position, velocity, and GPS receiver clock bias, have many abnormal excursions from the normal error range for space operation. These excursions lessen the accuracy of attitude control and onboard time synchronization. In this research, a new onboard orbit determination algorithm designed with the unscented Kalman filter (UKF) was developed to improve the performance. Because the UKF is able to obtain the posterior mean and covariance accurately by using the second-order Taylor series expansion through the sampled sigma points that are propagated by using the true nonlinear system, its performance can be better than that of the extended Kalman filter (EKF), which uses the linearized state transition matrix to predict the covariance. The dynamic models for orbit propagation applied perturbations due to the 40 × 40 geo-potential, the gravity of the Sun and Moon, solar radiation pressure, and atmospheric drag. The 7(8)th-order Runge–Kutta numerical integration was applied for orbit propagation. Two types of observations, navigation solutions and C/A code pseudorange, can be used at the user’s discretion. The performances of the onboard orbit determination were verified using real GPS data of the CHAMP and KOMPSAT-2 satellites. The results of the orbit determination were compared with the precision orbit ephemeris (POE) of the CHAMP and KOMPSAT-2 satellites.     

大气密度模型球谐修正研究

大气模型修正是提高模型精度的一种重要方法.利用CHAMP卫星高精度加速仪反演的密度数据,采用球谐函数的形式对NRLMSISE-00模型进行修正.为了消除轨道高度变化对密度修正结果的影响,将密度数据同化到同一高度处,计算修正之后的密度误差,进而对未来三天的密度进行预报.结果表明,经球谐修正后,修正误差和预报误差均有显著降低.在太阳活动高年,修正误差可降至10%左右,提前1~3天预报精度分别提高31.34%,21.39%和13.75%;太阳低年时修正误差可降至14%左右,提前1~3天预报精度分别提高55.03%,47.79%和43.60%.      

Synergetic retrieval of terrestrial AOD from MODIS images of twin satellites Terra and Aqua

Aerosol optical depth (AOD) is one of the most important indicators of atmospheric pollution. It can be retrieved from satellite imagery using several established methods, such as the dark dense vegetation method and the deep blue algorithm. All of these methods require estimation of surface reflectance prior to retrieval, and are applicable to a certain pre-designated type of surface cover. Such limitations can be overcome by using a synergetic method of retrieval proposed in this study. This innovative method is based on the fact that the ratio K of surface reflectance at different angles/geometries is independent of wavelength as reported by Flowerdew and Haigh (1995). An atmospheric radiative transfer model was then established and resolved with the assistance of the ratio K obtained from two Moderate Resolution Imaging Spectroradiometer (MODIS) spectral bands acquired from the twin satellites of Terra and Aqua whose overpass is separated by three hours. This synergetic method of retrieval was tested with 20 pairs of MODIS images. The retrieved AOD was validated against the ground observed AOD at the Taihu station of the AErosol RObotic NETwork (AERONET). It is found that they are correlated with the observations at a coefficient of 0.828 at 0.47 μm and 0.921 at 0.66 μm wavelengths. The retrieved AOD has a mean relative error of 25.47% at 0.47 μm and 24.3% at 0.66 μm. Of the 20 samples, 15 and 17 fall within two standard error of the line based observed AOD data on the ground at the 0.47 μm and 0.66 μm, respectively. These results indicate that this synergetic method can be used to reliably retrieve AOD from the twin satellites MODIS images, namely Terra and Aqua. It is not necessary to determine surface reflectance first.     

Measuring atmospheric density using GPS–LEO tracking data

We present a method to estimate the total neutral atmospheric density from precise orbit determination of Low Earth Orbit (LEO) satellites. We derive the total atmospheric density by determining the drag force acting on the LEOs through centimeter-level reduced-dynamic precise orbit determination (POD) using onboard Global Positioning System (GPS) tracking data. The precision of the estimated drag accelerations is assessed using various metrics, including differences between estimated along-track accelerations from consecutive 30-h POD solutions which overlap by 6 h, comparison of the resulting accelerations with accelerometer measurements, and comparison against an existing atmospheric density model, DTM-2000. We apply the method to GPS tracking data from CHAMP, GRACE, SAC-C, Jason-2, TerraSAR-X and COSMIC satellites, spanning 12 years (2001–2012) and covering orbital heights from 400 km to 1300 km. Errors in the estimates, including those introduced by deficiencies in other modeled forces (such as solar radiation pressure and Earth radiation pressure), are evaluated and the signal and noise levels for each satellite are analyzed. The estimated density data from CHAMP, GRACE, SAC-C and TerraSAR-X are identified as having high signal and low noise levels. These data all have high correlations with anominal atmospheric density model and show common features in relative residuals with respect to the nominal model in related parameter space. On the contrary, the estimated density data from COSMIC and Jason-2 show errors larger than the actual signal at corresponding altitudes thus having little practical value for this study. The results demonstrate that this method is applicable to data from a variety of missions and can provide useful total neutral density measurements for atmospheric study up to altitude as high as 715 km, with precision and resolution between those derived from traditional special orbital perturbation analysis and those obtained from onboard accelerometers.     

Robust extension of the simple sea-surface irradiance model to handle cloudy conditions for the global ocean using satellite remote sensing data

Sea-surface solar radiation (abbreviated as photosynthetically available radiation, PAR) in the visible wavelength (400–700 nm) is an essential parameter to estimate marine primary productivity and understanding phytoplankton dynamics, upper ocean physics and biogeochemical processes. Although many remote-sensing models were developed to estimate daily PAR (DPAR) from ocean colour data, these models often produce biases in the DPAR products under cloudy-sky and complex atmospheric conditions due to the lack of parameterization to deal with the cloud cover conditions and insufficient in-situ DPAR data. This study presents an Extended Sea-surface Solar Irradiance Model (ESSIM) for estimating DPAR over the global ocean. The ESSIM uses the direct and diffuse components from the Simple sea-surface Solar Irradiance Model (SSIM) along with a new parameter to handle cloudy conditions. The ESSIM produced DPAR products with greater accuracy under both clear and cloudy conditions. Its performance was tested on the time-series MODIS-Aqua images and compared with the concurrent in-situ data and the results from two global models. Results showed that the DPAR values produced by ESSIM agree with in-situ data better than the global models for all-sky conditions (with a mean relative error of 11.267 %; a root mean square error of 5.563 Em^?2day^?1; and a mean net bias of 2.917 Em^?2day^?1). The ESSIM performed slightly better than the SSIM for clear conditions and the Frouin's Operational Algorithm (FOA) for all-sky conditions. As the new parameterization accounts for cloudy conditions, the ESSIM produced more accurate results for cloud cover conditions across latitudes (up to 60°). The time-series Level-3 binned MODIS-Aqua data (global gridded) also demonstrated that the ESSIM improved the accuracy of DPAR products and produced spatially and temporally consistent DPAR products over the global ocean regardless of the seasons and sky conditions.     

太阳E10.7指数的反演及预报方法

针对高层大气密度预报和轨道预报业务中对新型太阳紫外辐射指数E_10.7的需求,基于TIMED-SEE观测仪器提供的0.1～105 nm太阳辐射强度数据,开展了E_10.7指数反演和中期预报研究。 E_10.7指数是太阳光谱中波长为0.1～105 nm的辐射流量,单位与F_10.7指数相同（sfu,1 sfu=10–22 W·m–2·Hz–1）。 TIMED-SEE观测仪器提供的0.1～105 nm太阳辐射强度实测值具有高时间分辨率、延迟时间短和易获得的优势,利用最小二乘法拟合可反演出准实时的E_10.7指数,均方根误差为5.445 sfu。利用高阶自回归模型对E_10.7的中期预报效果尚佳,未来27天的预报值平均相对误差为7.83%。利用同样方法还开展了E_10.7指数81天中心滑动平均值未来27天预报试验,未来27天的预报值平均相对误差仅为3.63%。      

Towards a GPS-based TEC prediction model for Southern Africa with feed forward networks

In this paper, first results from a national Global Positioning System (GPS) based total electron content (TEC) prediction model over South Africa are presented. Data for 10 GPS receiver stations distributed through out the country were used to train a feed forward neural network (NN) over an interval of at most five years. In the NN training, validating and testing processes, five factors which are well known to influence TEC variability namely diurnal variation, seasonal variation, magnetic activity, solar activity and the geographic position of the GPS receivers were included in the NN model. The database consisted of 1-min data and therefore the NN model developed can be used to forecast TEC values 1 min in advance. Results from the NN national model (NM) were compared with hourly TEC values generated by the earlier developed NN single station models (SSMs) at Sutherland (32.38°S, 20.81°E) and Springbok (29.67°S, 17.88°E), to predict TEC variations over the Cape Town (33.95°S, 18.47°E) and Upington (28.41°S, 21.26°E) stations, respectively, during equinoxes and solstices. This revealed that, on average, the NM led to an improvement in TEC prediction accuracy compared to the SSMs for the considered testing periods.     

A numerical model approximating extreme energetic electron events involved in the physical and chemical processes of the middle atmosphere

Relativistic electrons (with energies >150 keV) which originate in the outer radiation belt and detected by the Russian ‘Meteor’ series of satellites have been correlated with the atmospheric total ozone data compiled by almost 90 stations located around the world within the latitude zone 40°–70°N. In more than 60% of the stations examined we have detected a clear decrease of the ozone 3–5 days after the electron flux excess. A numerical model has been applied to approximate this effect based on relativistic electron initiated nitric oxides creation in the upper mesosphere with subsequent atmospheric transport (both vertical and horizontal) towards the upper stratosphere. A first attempt of local and temporal prediction of ozone depletion because of energetic electrons impact in the middle atmosphere has been illustrated.     

Variation in the ionospheric propagating factor M(3000)F2 at Ouagadougou,Burkina Faso

We use hourly monthly median values of propagation factor M(3000)F2 data observed at Ouagadougou Ionospheric Observatory (geographic12.4°N, 1.5°W; 5.9^o dip), Burkina Faso (West Africa) during the years Januar1987–December1988 (average F10.7 < 130 × 10⁻²² W/m²/Hz, representative of low solar flux conditions) and for January 1989–December1990 (average F10.7 ? 130 × 10⁻²² W/m²/Hz, representative of high solar epoch) for magnetically quiet conditions to describe local time, seasonal and solar cycle variations of equatorial ionospheric propagation factor M(3000)F2 in the African region. We show that that seasonal trend between solar maximum and solar minimum curves display simple patterns for all seasons and exhibits reasonable disparity with root mean square error (RMSE) of about 0.31, 0.29 and 0.26 for December solstice, June solstice and equinox, respectively. Variability Σ defined by the percentage ratio of the absolute standard deviation to the mean indicates significant dissimilarity for the two solar flux levels. Solar maximum day (10–14 LT) and night (22–02 LT) values show considerable variations than the solar minimum day and night values. We compare our observations with those of the IRI 2007 to validate the prediction capacity of the empirical model. We find that the IRI model tends to underestimate and overestimate the observed values of M(3000)F2, in particular, during June solstice season. There are large discrepancies, mainly during high solar flux equinox and December solstice between dawn and local midnight. On the other hand, IRI provides a slightly better predictions for M(3000)F2 between 0900 and 1500 LT during equinox low and high solar activity and equinox high sunspot number. Our data are of great importance in the area of short-wave telecommunication and ionospheric modeling.