Excitation of planetary electromagnetic waves in the inhomogeneous ionosphere

In this paper we develop a new method for the analysis of excitation and propagation of planetary electromagnetic waves (PEMW) in the ionosphere of the Earth. The nonlinear system of equations for PEMW, valid for any height, from D to F regions, including intermediate altitudes between D and E and between E and F regions, is derived. In particular, we have found the system of nonlinear one-fluid MHD equations in the β-plane approximation valid for the ionospheric F region (Aburjania et al., 2003a, 2005). The series expansion in a "small" (relative to the local geomagnetic field) non-stationary magnetic field has been applied only at the last step of the derivation of the equations. The small mechanical vertical displacement of the media is taken into account. We have shown that obtained equations can be reduced to the well-known system with Larichev–Reznik vortex solution in the equatorial region (see e.g. Aburjania et al., 2002). The excitation of planetary electromagnetic waves by different initial perturbations has been investigated numerically. Some means for the PEMW detection and data processing are discussed

Validation of satellite OPEMW precipitation product with ground-based weather radar and rain gauge networks

Abstract. The Precipitation Estimation at Microwave Frequencies (PEMW) algorithm was developed at the Institute of Methodologies for Environmental Analysis of the National Research Council of Italy (IMAA-CNR) for inferring surface rain intensity (sri) from satellite passive microwave observations in the range from 89 to 190 GHz. The operational version of PEMW (OPEMW) has been running continuously at IMAA-CNR for two years. The OPEMW sri estimates, together with other precipitation products, are used as input to an operational hydrological model for flood alert forecast. This paper presents the validation of OPEMW against simultaneous ground-based observations from a network of 20 weather radar systems and a network of more than 3000 rain gauges distributed over the Italian Peninsula and main islands. The validation effort uses a data set covering one year (July 2011–June 2012). The effort evaluates dichotomous and continuous scores for the assessment of rain detection and quantitative estimate, respectively, investigating both spatial and temporal features. The analysis demonstrates 98% accuracy in correctly identifying rainy and non-rainy areas; it also quantifies the increased ability (with respect to random chance) to detect rainy and non-rainy areas (0.42–0.45 Heidke skill score) or rainy areas only (0.27–0.29 equitable threat score). Performances are better than average during summer, fall, and spring, while worse than average in the winter season. The spatial–temporal analysis does not show seasonal dependence except over the Alps and northern Apennines during winter. A binned analysis in the 0–15 mm h−1 range suggests that OPEMW tends to slightly overestimate sri values below 6–7 mm h−1 and underestimate sri above those values. With respect to rain gauges (weather radars), the correlation coefficient is larger than 0.8 (0.9). The monthly mean difference and standard deviation remain within ±1 and 2 mm h−1 with respect to rain gauges (respectively −2–0 and 4 mm h−1 with respect to weather radars)

A statistical approach for rain intensity differentiation using Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager observations

Abstract. This study exploits the Meteosat Second Generation (MSG)–Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations to evaluate the rain class at high spatial and temporal resolutions and, to this aim, proposes the Rain Class Evaluation from Infrared and Visible observation (RainCEIV) technique. RainCEIV is composed of two modules: a cloud classification algorithm which individuates and characterizes the cloudy pixels, and a supervised classifier that delineates the rainy areas according to the three rainfall intensity classes, the non-rainy (rain rate value < 0.5 mm h-1) class, the light-to-moderate rainy class (0.5 mm h−1 ≤ rain rate value < 4 mm h-1), and the heavy–to-very-heavy-rainy class (rain rate value ≥ 4 mm h-1). The second module considers as input the spectral and textural features of the infrared and visible SEVIRI observations for the cloudy pixels detected by the first module. It also takes the temporal differences of the brightness temperatures linked to the SEVIRI water vapour channels as indicative of the atmospheric instability strongly related to the occurrence of rainfall events. The rainfall rates used in the training phase are obtained through the Precipitation Estimation at Microwave frequencies, PEMW (an algorithm for rain rate retrievals based on Atmospheric Microwave Sounder Unit (AMSU)-B observations). RainCEIV's principal aim is that of supplying preliminary qualitative information on the rainy areas within the Mediterranean Basin where there is no radar network coverage. The results of RainCEIV have been validated against radar-derived rainfall measurements from the Italian Operational Weather Radar Network for some case studies limited to the Mediterranean area. The dichotomous assessment related to daytime (nighttime) validation shows that RainCEIV is able to detect rainy/non-rainy areas with an accuracy of about 97% (96%), and when all the rainy classes are considered, it shows a Heidke skill score of 67% (62%), a bias score of 1.36 (1.58), and a probability of detection of rainy areas of 81% (81%)

Stochastic Electron Acceleration by Temperature Anisotropy Instabilities Under Solar Flare Plasma Conditions

Using 2D particle-in-cell plasma simulations, we study electron acceleration by temperature anisotropy instabilities, assuming conditions typical of above-the-loop-top sources in solar flares. We focus on the long-term effect of Te,⊥ > Te,∥ instabilities by driving the anisotropy growth during the entire simulation time through imposing a shearing or a compressing plasma velocity (Te,⊥ and Te,∥ are the temperatures perpendicular and parallel to the magnetic field). This magnetic growth makes Te,⊥/Te,∥ grow due to electron magnetic moment conservation, and amplifies the ratio ωce/ωpe from ∼0.53 to ∼2 (ωce and ωpe are the electron cyclotron and plasma frequencies, respectively). In the regime ωce/ωpe ≲ 1.2–1.7, the instability is dominated by oblique, quasi-electrostatic modes, and the acceleration is inefficient. When ωce/ωpe has grown to ωce/ωpe ≳ 1.2–1.7, electrons are efficiently accelerated by the inelastic scattering provided by unstable parallel, electromagnetic z modes. After ωce/ωpe reaches ∼2, the electron energy spectra show nonthermal tails that differ between the shearing and compressing cases. In the shearing case, the tail resembles a power law of index αs ∼ 2.9 plus a high-energy bump reaching ∼300 keV. In the compressing runs, αs ∼ 3.7 with a spectral break above ∼500 keV. This difference can be explained by the different temperature evolutions in these two types of simulations, suggesting that a critical role is played by the type of anisotropy driving, ωce/ωpe, and the electron temperature in the efficiency of the acceleration

Stochastic Electron Acceleration by Temperature Anisotropy Instabilities Under Solar Flare Plasma Conditions

We use 2D particle-in-cell (PIC) plasma simulations to study electron acceleration by electron temperature anisotropy instabilities, assuming magnetic fields ($B$), electron densities ($n_e$) and temperatures ($T_e$) typical of the top of contracting magnetic loops in solar flares. We focus on the long-term effect of $T_{e,\perp} > T_{e,\parallel}$ instabilities by driving the anisotropy growth during the whole simulation time ($T_{e,\perp}$ and $T_{e,\parallel}$ are the temperatures perpendicular and parallel to the field). This is achieved by imposing a shear velocity, which amplifies the field due to magnetic flux freezing, making $T_{e,\perp} > T_{e,\parallel}$ due to electron magnetic moment conservation. We use the initial conditions: $T_e \sim 52$ MK, and $B$ and $n_e$ such that the ratio between the electron cyclotron and plasma frequencies $\omega_{ce}/\omega_{pe}=0.53$. When the anisotropy becomes large enough, oblique, quasi-electrostatic (OQES) modes grow, efficiently scattering the electrons and limiting their anisotropy. After that, when $B$ has grown by a factor $\sim 2-3$ (corresponding to $\omega_{ce}/\omega_{pe}\sim 1.2-1.5$), the unstable modes become dominated by parallel, electromagnetic z (PEMZ) modes. In contrast to the OQES dominated regime, the scattering by PEMZ modes is highly inelastic, producing significant electron acceleration. When the field has grown by a final factor $\sim 4$, the electron energy spectrum shows a nonthermal tail that resembles a power-law of index $\sim$ 2.9, plus a high-energy bump reaching $\sim 300$ keV. Our results suggest a critical role played by $\omega_{ce}/\omega_{pe}$ and $T_e$ in determining the efficiency of electron acceleration by temperature anisotropy instabilities in solar flares.Comment: 11 pages, 9 figure

The utilization of wastewater for microalgal biomass propagation and saccharification of carbohydrates into fermentable sugars for bioethanol production.

Master of Science in Life Sciences. University of KwaZulu-Natal, Durban 2017.Abstract available in PDF file

Analysis of Catania Flash Flood Case Study by Using Combined Microwave and Infrared Technique

Abstract In this paper, the analysis of an extreme convective event atypical for the winter season, which occurred on 21 February 2013 on the east coast of Sicily and caused a flash flood over Catania, is presented. In just 1 h, more than 50 mm of precipitation was recorded, but it was not forecast by numerical weather prediction (NWP) models and, consequently, no severe weather warnings were sent to the population. The case study proposed is first examined with respect to the synoptic situation and then analyzed by means of two algorithms based on satellite observations: the Cloud Mask Coupling of Statistical and Physical Methods (MACSP) and the Precipitation Evolving Technique (PET), developed at the National Research Council of Italy. Both of the algorithms show their ability in the near-real-time monitoring of convective cell formation and their rapid evolution. As quantitative precipitation forecasts by NWP could fail, especially for atypical convective events like in Catania, tools like MACSP and PET shall be adopted by civil protection centers to monitor the real-time evolution of deep convection events in aid to the severe weather warning service