Journal of Atmospheric and Solar-Terrestrial Physics最新文献

The effects of aerosols (i.e., CCN) on the lifecycle of a well-documented mesoscale cloud cluster (CC) over the Indian peninsula are investigated in this study. The WRF model coupled with a sophisticated spectral bin microphysics scheme is employed to simulate the observed cloud system under various CCN scenarios. The CCN sensitivity experiments were carried out using three different background CCN concentrations (250, 1000, and 3000 cm⁻³). The prevailing environment featured a relatively dry mid-level. The introduction of more aerosols weakened the convection and moistened the upper troposphere in the initiation and mature phases. The major impacts of the enhanced aerosols include the dissipation of shallow clouds, a decrease in the number of convective cells and their overall coverage, enhanced convective organization in the early phase(s) of the lifecycle, enhancement of the cloud-free area, etc. The key microphysical changes due to enhanced aerosols are the increase in cloud liquid water, presence of numerous smaller cloud droplets, enhancement of condensation and evaporation, formation of smaller ice crystals, reduced snow mass and reduction in the aggregation process, high graupel mass and number and a reduction in graupel size, fewer raindrops with slight enhancement in raindrop size, etc. Cloud growth is significantly limited in the high aerosol scenarios due to large evaporation favored by a relatively dry environment and no invigoration effect is noted. A significant reduction in the rainfall (and associated rainfall-type) from isolated convective cores is noted due to high aerosols, especially in the initiation and mature phases. The eventual impact on the surface precipitation is a decrease in overall rainfall in the enhanced aerosol scenarios, with suppression of heavy rain. The study indicates that in a dry environment, the microphysical changes in various CCN scenarios cumulatively lead to macrophysical changes, which are found to be the primary controller of the overall surface rainfall associated with the CC.

Long-term trends in the evolution of ionospheric plasma at Hyderabad (17.38${}^{\circ }$N, 78.48${}^{\circ }$E; 8.52${}^{\circ }$N Magnetic Latitude), a near-equatorial anomaly (EIA) crest region of the Indian ionospheric sector, have been studied using 9 years of vertical Total Electron Content (TEC) data from 2004 to 2009 and 2011 to 2013 using global positioning satellites (GPS) measurements. The study examined the mean diurnal, monthly, seasonal, and yearly variations of TEC during geomagnetic quiet days in different seasons from 2004 to 2013. The findings reveal that the daytime TEC at the anomaly crest region exhibits semi-annual variations throughout the study period, while midnight TEC shows semi-annual variation only during the high solar activity years of 2011–2013. The winter anomaly was observed in 2004 and 2006. The study also assessed the performance of the International Reference Ionosphere (IRI) 2016 model in reproducing GPS TEC variability at the equatorial crest region. The diurnal and seasonal variation patterns in IRI-TEC show a good correlation with GPS TEC. However, the IRI 2016 model tends to overestimate TEC values during low solar activity conditions (2006–2009) but represents TEC variations reasonably well during high solar activity periods (2011–2013). Nevertheless, the IRI model fails to capture the wide plateau-like structure in the peak TEC, typically occurring between 1200–1600 IST at Hyderabad. Additionally, IRI-TEC consistently indicates very low TEC values during the early morning hours, whereas GPS-TEC measurements suggest a significant presence of plasma density. The study suggests a strong influence of the solar cycle on TEC variations at Hyderabad, evident from the positive correlation (R${}^2=$ 0.71) with the F10.7 cm index. This characteristic is also well represented by the IRI 2016 model.

Pc5 geomagnetic pulsations can accelerate electrons in the radiation belts, which can pose adverse threats to both astronauts and satellites in space. The estimation of Pc5 waves in space is crucial to radiation belt dynamics studies and will help mitigate these challenges. Here, we explore the advantages of the Feed-forward Neural Network (FFNN) and Random Forest (RF) algorithm for effective estimation of Pc5 geomagnetic pulsations observed in space at geostationary orbit during solar cycle 23. The dataset used in this study is the vector magnetic field measurements retrieved from the Geostationary Operational Environmental Satellite-10 (GOES-10) and the solar wind parameters: $B_z$ and $V_x$ component of the solar wind in the Geocentric Solar Ecliptic (GSE) coordinate system, proton density, flow pressure, and plasma beta obtained from the OMNI Web database during part of solar cycle 23. Pc5 geomagnetic pulsations were extracted from the toroidal component of the magnetic field time series using a bandpass Butterworth filter. The continuous wavelet transform (CWT) was utilized to study the characteristics of the extracted wave in the time-frequency domain for its validation. The validated Pc5 events were used as the target in the model's development, with the solar wind parameters as the inputs. In addition to the solar wind parameters, we included an attribute of the magnetic field time series as an input variable in the model. The dataset is carefully divided to ensure effective training and testing of the models. Finally, we trained both models using the same inputs and targets and explored their estimation abilities. The model was tested during the maximum, descending, and minimum phases of solar cycle 23. Both the FFNN and RF models have a similar estimation, with average cross-correlation score (R) values of 0.74 and 0.73 and corresponding average root mean squared error (RMSEs) of 0.16 nT and 0.67 nT, respectively. The model was deployed to investigate the response of Pc5 waves during three storm days in each testing year. The machine learning (ML) model outputs showed good coherence with the observed Pc5 waves. To validate the models, we studied the correlation between the estimated Pc5 events with the Kp index, and a good correlation was seen to exist between both events. This validates the good performance of the developed models. This work will aid in the study of radiation belt dynamics and the construction of electron depletion regions in the radiation belt.

– Development of magnetospheric substorm from standpoint of energy evolution in geomagnetic tail is considered. In this approach, geomagnetic tail is taken to be an open thermodynamic system (OTS) with infinite number of conserved energy links to external space environment. General self-consistent theory of energy evolution in OTS was presented earlier. In contrast to existing models of magnetospheric activity, presented model suggests believing that shaping of geomagnetic activity is controlled by the system nature of geomagnetic tail. From this angle, energy profile of disturbance is determined by particular qualities of energy development in OTS. Intercoupling between the system factors of the tail and flow of raw energy from space sources can produce different forms of magnetospheric activity including substorms. As an example, suggested system mechanism is considered for interpretation of the classic energy profile of isolated magnetospheric substorm, comparison with some experimental features of substorm is also provided.

A new VLF (Very low Frequency) receiver has been developed by the Peruvian Space Agency (CONIDA) for space weather studies. The receiver has been designed based on a Red Pitaya board which performs an SDR (Software Defined Radio) to digitize, process and store the signal. The receiver is composed of a vertical antenna, a preamplifier to filter and amplify the incoming VLF signals from several transmitters located around the world. The receiver is able to cover a bandwidth from 1 up to 50 kHz and it has been developed in such a way as to be cost-effective, autonomous and solar-powered, making it suitable for installation in multiple locations with different geographic conditions. We show the performance of the receiver, the typical daily pattern of the lower ionosphere for the NAA VLF signal, as observed in Peru, and the first solar flares observed. The VLF amplitude curves recorded are validated by comparing them with data from SAVNET (The South American VLF Network) receiver installed in Peru. In a first effort to investigate the impact of solar flares on the lower ionosphere, we conducted a statistical analysis between VLF amplitude perturbations and 1–8 Å solar X-rays flux provided by GOES satellites, resulting in a linear relationship.

We compare Joule Heating rates as derived from ground-based magnetic field and all-sky camera data, from Low Earth Orbit satellite data (ESA Swarm) and from a MHD simulation (GUMICS-5) with each other in a case study of an auroral arc system. The observational estimates of Joule Heating rates provide information on regional scales and with high spatial resolution (10–100 km). Their comparison with global MHD results is conducted for a quiet time interval of a few minutes, just before a magnetic substorm. Analysis of the ground-based observations yields electric field with dominating North-South component pointing towards the arcs and having maxima values in the range 20–35 V/km. Combining these values with Pedersen conductance estimates from optical data (5–10 S) yields Joule Heating rates in the range 2.5–3.5 mW/m${}^2$. Swarm electric field measurements are consistent in their direction and intensity with the ground-based estimates. They also show that heating is increased particularly in the region where the conductance is low. The total amount of Joule heating in the area between the Swarm A and C satellite footprints while crossing the all-sky camera field of view is estimated to be 46 MW and the total amount energy dissipation during the 80 s overflight is around 3.6 GJ (1000 kWh). GUMICS-5 estimate of the peak Joule Heating in the magnetic local time sector of the arc system is smaller than that from the ground-based data with a factor of 2.9. Comparisons of GUMICS-5 results with Space Weather Modeling Framework (SWMF), shows that the latter gives on average larger heating rates being thus more consistent with our regional observations. However, both MHD-codes yield smaller Joule Heating rates around the time of the arcs and during the following substorm than the CTIP-e code. CTIP-e has a more detailed description of ionosphere-thermosphere interactions than the MHD-codes and its convection electric field is enhanced with a randomly varying additional component mimicking small scale structures. GUMICS-SWMF comparisons of global Joule Heating patterns in the Northern polar area reveal that the two simulations have significant differences in their spatial distribution of heating rates. Main cause for these deviations is the difference in the derivation of ionospheric Pedersen conductance. Our results emphasize the fact that future estimates of the global energetics in the magnetosphere–ionosphere–thermosphere system require better knowledge on ionospheric conductivities, both by new measurement concepts and by better understanding on the background physics controlling conductivity variations.

Increasing lightning fatalities over India is a concerning subject. Especially, it is pretty crucial over North-Eastern part of the country where lightning is extremely frequent. Given the complex nature of the problem, machine learning can be an excellent option in such forecasting scenarios. However, such dynamic processes seek proper transparency of the model. The current work attempts to devise a model for short range prediction (one month ahead) of lightning density based on primary atmospheric parameters from satellite data with a lead time of one month over North –Eastern and Eastern part of the country. Random Forest regression seems to outperform other models explored, with a R² of 0.86 and an MAE of 0.0071. The interpretation of the model output using SHAP index reveals that 2 m temperature at previous two months and CAPE and K-index at previous month has a positive impact on the output of the model whereas, instantaneous surface heat flux of previous month and two month prior K-index has an inhibiting effect on model's output. The use of machine learning techniques for atmospheric predictions without the shed of the black box can be of importance to the scientific community. Such studies especially over lightning prone tropical regions can be crucial in meteorological forecasting applications.

In this study, we present the statistical features of gravity wave (GW) and sporadic E layer (E_S) by using the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) data aboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occulation measurements during 2007–2018. Statistical analysis of occurrences of GW and E_S shows that daytime GW and E_S are frequently observed on the eastern sides of the Tibetan plateau during summer, while less consistency between nighttime GW and E_S occurrences was presented in our observations. The concurrence of GW and E_S shows that nearly 60% E_S occurred simultaneously with local strong GW occurrence. These results provide observational evidence suggesting that the effect of strong GW activities is significant in the generation of E_S.

A comparative overview of Terrestrial and Martian space weather is presented, with emphasis on applying the tools of complexity and nonlinear dynamics to study the spatiotemporal dynamics and structures of sun–Earth and sun–Mars space environment. The following topics are reviewed: (1) complex systems approach to solar atmosphere and solar wind; (2) complex systems approach to planetary bow shock and magnetosphere–ionosphere; (3) Martian space weather, bow shock, and magnetosphere–ionosphere; (4) imaging planetary magnetosphere–ionosphere.

In this paper, Very-High Frequency (VHF) radiation pulses associated with 11 negative Narrow Bipolar Events (NBEs) produced by a tropical storm over Malacca Strait are examined. The lightning data were recorded from a measurement station (ST) which consisted of a fast antenna (FA) and three VHF sensors (two 5 m perpendicular baselines interferometer). The average rise time (RT), average zero-crossing time (ZCT), average pulse duration (PD), and range of peak currents of the negative NBEs were 1.4 ± 0.4 μs, 2.7 ± 1.0 μs, 12.0 ± 6.9 μs, and −10 to −64 kA, respectively. The key finding is that all VHF radiation pulses have been found to precede the negative NBEs with an average lead time of 0.7 ± 0.3 μs. An interferometer map for one negative NBE (labelled as NBE10) detected at 35.7 km from ST has shown a characteristic of mixed propagation direction of fast streamers. The first VHF radiation source was detected at 12.4 ± 0.4 km above sea level. The total length and estimated velocity of the main propagation of the VHF radiation sources were 2.2 ± 0.7 km and between 1.4 × 10⁸ and 2.8 × 10⁸ ms⁻¹, respectively. Moreover, based on the Himawari satellite image, the maximum extent of the cloud top height was estimated to be around 20.9 km over sea level (over Malacca Strait). All the VHF radiation sources associated with NBE10 were suggested to be detected above the main negative charge region (6 km altitude that corresponds to −10 °C). Thus, it could be suggested that NBE10 was initiated most likely in the environment of the ice crystals alone, based on the first altitude of the VHF radiation source and maximum extent of cloud top height.