Rwanda Astrophysics, Space and Climate Science Research Group (RASCSRG)

Publications from 2011:

Author, year, Title, Journal Abstracts
International Journals
J Uwamahoro and J.B. Habarulema: Empirical modeling of the storm time geomagnetic indices: a comparison between the local K and global Kp indices; Earth Planets and Space, 2014, 66:95. This paper describes a neural network-based model developed to predict geomagnetic storms time K index as measured at a magnetic observatory located in Hermanus (34°25 S; 19°13 E), South Africa. The parameters used as inputs to the neural network were the solar wind particle density N, the solar wind velocity V, the interplanetary magnetic field (IMF) total average field Bt as well as the IMF Bz component. Averaged hourly OMNI-2 data comprising storm periods extracted from solar cycle 23 (SC23) were used to train the neural network. The prediction performance of this model was tested on some moderate to severe storms (with K≥5) that were not included in the training data set and the results are compared to the prediction of the global geomagnetic Kp index. The model results show a good predictability of the Hermanus storm time K index with a correlation coefficient of 0.8.
L.L. Yadav, M.K. Mishra and S.K. Jain (2014): Electrostatic sinusoidal waves in an electron-positron-ion plasma (to be submitted in Astrophysics and Space Science)
1. Nsengiyumva, F.; Mace, R. L.; Hellberg, M. A. Ion Bernstein waves in a plasma with a kappa velocity distribution . Physics of Plasmas, Volume 20, Issue 10, pp. 102107-102107-10 (2013). Using a Vlasov-Poisson model, a numerical investigation of the dispersion relation for ion Bernstein waves in a kappa-distributed plasma has been carried out. The dispersion relation is found to depend significantly on the spectral index of the ions, κi, the parameter whose smallness is a measure of the departure from thermal equilibrium of the distribution function. Over all cyclotron harmonics, the typical Bernstein wave curves are shifted to higher wavenumbers (k) if κi is reduced. For waves whose frequency lies above the lower hybrid frequency, ωLH, an increasing excess of superthermal particles (decreasing κi) reduces the frequency, ωpeak, of the characteristic peak at which the group velocity vanishes, while the associated kpeak is increased. As the ratio of ion plasma to cyclotron frequency (ωpi/ωci) is increased, the fall-off of ω at large k is smaller for lower κi and curves are shifted towards larger wavenumbers. In the lower hybrid frequency band and harmonic bands above it, the frequency in a low-κi plasma spans only a part of the intraharmonic space, unlike the Maxwellian case, thus exhibiting considerably less coupling between adjacent bands for low κi. It is suggested that the presence of the ensuing stopbands may be a useful diagnostic for the velocity distribution characteristics. The model is applied to the Earth's plasma sheet boundary layer in which waves propagating perpendicularly to the ambient magnetic field at frequencies between harmonics of the ion cyclotron frequency are frequently observed. Keywords: atmospheric boundary layer, numerical analysis, plasma Bernstein waves, plasma boundary layers, plasma electromagnetic wave propagation, plasma hybrid waves, plasma transport processes, Poisson equation, Vlasov equation; Electromagnetic waves, Numerical simulation, solution of equations, Transport properties DOI: 10.1063/1.4824615
2. Whitelock, Patricia A.; Menzies, John W.; Feast, Michael W.; Nsengiyumva, Francois; Matsunaga, Noriyuki . The Local Group galaxy NGC 6822 and its asymptotic giant branch stars . MNRAS, Volume 428, Issue 3, p.2216-2231, DOI:10.1093/mnras/sts188 (2013) JHKS photometry is presented from a 3.5 yr survey of the central regions of the irregular galaxy NGC 6822. The morphology of the colour-magnitude and colour-colour diagrams is discussed with particular reference to M-, S- and C-type asymptotic giant branch (AGB) stars and to M supergiants. Mean JHKS magnitudes and periods are given for 11 O-rich and 50 presumed C-rich Miras. Data are also listed for 27 large-amplitude AGB stars without periods and for 69 small-amplitude AGB variables. The slope of the bolometric period-luminosity relation for the C-rich Miras is in good agreement with that in the Large Magellanic Cloud. Distance moduli derived from the C- and O-rich Miras are in agreement with other estimates. The period distribution of C-rich Miras in NGC 6822 is similar to that in the Magellanic Clouds, but differs from that in the dwarf spheroidals in the Local Group. In the latter there is a significant proportion of large-amplitude, short-period variables indicating a population producing old carbon-rich AGB stars. Keywords:stars: carbon, galaxies: distances and redshifts, galaxies: individual: NGC 6822, Local Group, infrared: stars, stars: AGB and post-AGB
3. J. Uwamahoro and L. A. Mackinnell, “ Solar and interplanetary precursors of geomagnetic storms in solar cycle 23”, Advances in Space Research , Vol 51, pp.395 – 410, 2013. Estimating the magnetic storm effectiveness of solar and associated interplanetary phenomena is of practical importance for space weather modelling and prediction. This article presents results of a qualitative and quantitative analysis of the probable causes of geomagnetic storms during the 11-year period of solar cycle 23: 1996 - 2006. Potential solar causes of 229 magnetic storms (Dst < or = -50 nT) were investigated with a particular focus on halo coronal mass ejections (CMEs). A 5-day time window prior to the storm onset was considered to track backward the Sun's eruptions of halo CMEs using the SOHO/LASCO CMEs catalogue list. Solar and interplanetary (IP) properties associated with halo CMEs were investigated and correlated to the resulting geomagnetic storms (GMS). In addition, a comparative analysis between full and partial halo CME-driven storms is established. The results obtained show that about 83% of intense storms (Dst < or = -100 nT) were associated with halo CMEs. For moderate storms (-100 nT < Dst < -50 nT), only 54% had halo CME background, while the remaining 46% were assumed to be associated with corotating interaction regions (CIRs) or undetected frontside CMEs. It was observed in this study that intense storms were mostly associated with full halo CMEs, while partial halo CMEs were generally followed by moderate storms. This analysis also indicates that up to 86% of intense storms were associated with interplanetary coronal mass ejections (ICMEs) at 1AU, as compared to moderate storms with only 44% of ICME association. Many other quantitative results are presented in this paper, providing an estimate of solar and IP precursor properties of GMS within an average 11-year solar activity cycle. The results of this study constitute a key step towards improving space weather modelling and prediction.
4. Nkundabakura, P. , & Meintjes, P. Unveiling the nature of two unidentified egret blazar candidates through spectroscopic observations. Monthly Notices of the Royal Astronomical Society, 427(1), 859-871, 2012. 25% has been performed at the home University. Studies using the Energetic Gamma-Ray Experiment Telescope (EGRET) revealed that blazars [flat-spectrum radio quasars (FSRQs) and BL Lac objects] emit most of their luminosity in the high-energy gamma-ray (E > 100 MeV) range. From the 271 sources observed by EGRET, 131 are still unidentified. A systematic search is conducted to identify possible high-energy gamma-ray blazars among the unidentified EGRET population. Based upon multiwavelength emission properties, 13 extragalactic radio sources were selected in the EGRET error boxes for further investigation. From the above-mentioned sample, results of a multiwavelength follow-up of two EGRET sources, 3EG J0821-5814 and 3EG J0706-3837, are presented. These sources are associated with their radio counterparts PKS J0820-5705 and PMN J0710-3850, respectively. Spectroscopic observations utilizing the SOAR/Goodman spectrograph at the Cerro Tololo Inter-American Observatory in Chile reveal a spectrum of PKS J0820-5705 that corresponds to that of a radio-loud active galactic nucleus (FSRQ) with redshift z = 0.06 ± 0.01, while the visibility of wide and narrow emission lines in the spectrum of PMN J0710-3850 resembles that of a low-ionization nuclear emission-line region (LINER) or type 1 Seyfert galaxy at z = 0.129 ± 0.001. The observed Ca II K&H lines depression ratio at 4000 Å showed a shallow depression of 8.8 ± 2.5 per cent for PKS J0820-5705 and 80 ± 1 per cent for PMN J0710-3850, suggesting the presence of a strong non-thermal optical contribution in PKS J0820-5705, which clearly distinguishes its spectrum from that of a radio galaxy. The weaker optical non-thermal contribution for PMN J0710-3850 is in accordance with that expected of a LINER. For PMN J0710-3850 the line flux ratios [O III] λ5007/Hβ > 3 and [N II] λ6583/Hα > 0.6 which are in agreement with the expected ratios of LINERs. However, the absence of [O II] λ3727 implies an anomalously low [O II]/[O III] < 0.5 ratio for a LINER, and agrees more with the ratio observed in type 1 Seyfert galaxies. The average velocities inferred from the Balmer lines range between 2300 and 4300 km s-1, while [O I] and [O III] velocities range between 420 and 490 km s-1, consistent with both LINERs and type 1 Seyfert galaxies. The X-ray luminosities of these two sources are LX ~9 × 1043 erg s-1 (PKS J0820-5705) and LX ~9 × 1042 erg s-1 (PMN J0710-3850), respectively. The X-ray luminosity of PMN J0710-3850 is an order of magnitude higher than the upper limit detected from LINERs, and correlates well with the typical X-ray luminosities observed in type 1 Seyfert galaxies. The X-ray luminosity of PKS J0820-5705 is consistent with the observed luminosity of FSRQs. Optical photometry carried out with the South African Astronomical Observatory 1.0-m telescope displayed 1-2 mag variability in the B and R bands for PKS J0821-5705, on time-scales of hours, while a 5σ variability of the average R-band magnitude could be discerned over a 3 day time span. A smaller 0.5 mag variability is visible in the B band for PMN J0710-3850 on time-scales of hours. No variability was detected in the R band for this source.
5. J. Uwamahoro, L. A. McKinnell and J. B. Habarulema, Estimating the geoeffectiveness of halo CMEs from associated solar and interplanetary parameters using neural networks, Annales Geophysicae., 30, 963–972, 2012. Estimating the geo-effectiveness of solar events is of significant importance for space weather modeling and prediction. This paper describes the development of a neural network based model for estimating the probability occurrence of geomagnetic storms following halo coronal mass ejection (CME) and related interplanetary (IP) events. This model incorporates both solar and IP variable inputs that characterize geoeffective halo CMEs. Solar inputs include numeric values of the halo CME angular width (AW), the CME speed Vcme, and the comprehensive flare index (cfi) which represents the flaring activity associated with halo CMEs. IP parameters used as inputs are the numeric peak values of the solar wind speed (Vsw) and the southward Z-component of the interplanetary magnetic field (IMF) or (Bs). IP inputs were considered within a 5 day time window after a halo CME eruption. The neural network (NN) model training and testing datasets were constructed based on 1202 halo CMEs (both full and partial halo and their properties) observed between 1997 and 2006. The performance of the developed NN model was tested using a validation dataset (not part of the training dataset) covering the years 2000 and 2005. Under the condition of halo CME occurrence, this model could capture 100% of the subsequent intense geomagnetic storms (Dst < or = -100 nT). For moderate storms (-100 < Dst <= -50), the model is successful up to 75%. This model's estimate of the storm occurrence rate from halo CMEs is estimated at a probability of 86%.
B. SAFARI, Trend Analysis of the Mean Annual Temperature in Rwanda during the Last Fifty Two Years, Journal of Environmental Protection 3(6):538-551. DOI:10.4236/jep.2012.36065,06/2012. Climate change and global warming are widely recognized as the most significant environmental dilemma the world is experiencing today. Recent studies have shown that the Earth’s surface air temperature has increased by 0.6°C - 0.8°C during the 20th century, along with changes in the hydrological cycle. This has alerted the international community and brought great interest to climate scientists leading to several studies on climate trend detection at various scales. This paper examines the long-term modification of the near surface air temperature in Rwanda. Time series of near surface air temperature data for the period ranging from 1958 to 2010 for five weather observatories were collected from the Rwanda National Meteorological Service. Variations and trends of annual mean temperature time series were examined. The cumulative sum charts (CUSUM) and bootstrapping and the sequential version of the Mann Kendall Rank Statistic were used for the detection of abrupt changes. Regression analysis was performed for the trends and the Mann-Kendall Rank Statistic Test was used for the examination of their significance. Statistically significant abrupt changes and trends have been detected. The major change point in the annual mean temperature occurred around 1977-1979. The analysis of the annual mean temperature showed for all observatories a not very significant cooling trend during the period ranging from 1958 to 1977-1979 while a significant warming trend was furthermore observed for the period after the 1977-1979 where Kigali, the Capital of Rwanda, presented the highest values of the slope (0.0455/year) with high value of coefficient of determination (R2 = 0.6798), the Kendall’s tau statistic (M-K = 0.62), the Kendall Score (S = 328) with a two-sided p-value far less than the confidence level α of 5%). This is most likely explained by the growing population and increasing urbanization and industrialization the country has experienced, especially the Capital City Kigali, during the last decades.
7. R. Mbonye, Nicholas Batista and Benjamin Farr, Time evolution of a non-singular blackhole, Int. J. Mod. Phys. D 20  1-19 (2011) There is growing notion that black holes may not contain curvature singularities (and that indeed nature in general may abhor such spacetime defects). This notion could have implications on our understanding of the evolution of primordial black holes (PBHs) and possibly on their contribution to cosmic energy. This paper discusses the evolution of a non-singular black hole (NSBH) based on a recent model [1]. We begin with a study of the thermodynamic process of the black hole in this model, and demonstrate the existence of a maximum horizon temperature T_{max}, corresponding to a unique mass value. At this mass value the specific heat capacity C changes signs to positive and the body begins to lose its black hole characteristics. With no loss of generality, the model is used to discuss the time evolution of a primordial black hole (PBH), through the early radiation era of the universe to present, under the assumption that PBHs are non-singular. In particular, we track the evolution of two benchmark PBHs, namely the one radiating up to the end of the cosmic radiation domination era, and the one stopping to radiate currently, and in each case determine some useful features including the initial mass m_{f} and the corresponding time of formation t_{f}. It is found that along the evolutionary history of the universe the distribution of PBH remnant masses (PBH-RM) PBH-RMs follows a power law. We believe such a result can be a useful step in a study to establish current abundance of PBH-MRs.
8. Bonfils Safari. Modeling wind speed and wind power distributions in Rwanda, Renewable and Sustainable Energy Reviews 15 (2011) 925–935. DOI:10.1016/j.rser.2010.11.001 Utilization of wind energy as an alternative energy source may offer many environmental and economical advantages compared to fossil fuels based energy sources polluting the lower layer atmosphere. Wind energy as other forms of alternative energy may offer the promise of meeting energy demand in the direct, grid connected modes as well as standalone and remote applications. Wind speed is the most significant parameter of the wind energy. Hence, an accurate determination of probability distribution of wind speed values is very important in estimating wind speed energy potential over a region. In the present study, parameters of five probability density distribution functions such as Weibull, Rayleigh, Lognormal, Normal and Gamma were calculated in the light of long term hourly observed data at four meteorological stations in Rwanda for the period of the year with fairly useful wind energy potential (monthly hourly mean wind speed). In order to select good fitting probability density distribution functions, graphical comparisons to the empirical distributions were made. In addition, RMSE and MBE have been computed for each distribution and magnitudes of errors were compared. Residuals of theoretical distributions were visually analyzed graphically. Finally, a selection of three good fitting distributions to the empirical distribution of wind speed measured data was performed with the aid of a χ2 goodness-of-fit test for each station.
Regional Journals
National Journals
9. B. Safari, J. Gasore, Monthly Wind Characteristics and Wind Energy in Rwanda, Rwanda Journal, Vol.20, Série C (2011). Evaluating wind power potential for a site is indispensable before making any decision for the installation of wind energy infrastructures and planning for relating projects. This paper presents a branch of a composite analysis whose objective was to investigate the potential of wind energy resource in Rwanda. Statistical methods were used to analyze long term time series of monthly daily wind speed measured on four meteorological stations in Rwanda for the period between 1981 and 1993. The Weibull distribution was used to model empirical distribution of measured long term monthly average wind speeds. The scale and shape parameters were estimated using four methods, the least square method, the likelihood method, the method of moments and the Chi-square method. It was observed that the method used for the estimates of the probability density of wind speed and giving the best overall fit to the distribution of the measured wind data varies from a location to another. However, the energy output calculated using wind speeds derived from the Chi-square method gave the best overall fit to the empirical distribution of the wind power density.