Kefei Zhang

Geomagnetically induced currents around the world during the 17 March 2015 storm

Geomagnetically induced currents (GICs) represent a significant space weather issue for power grid and pipeline infrastructure, particularly during severe geomagnetic storms. In this study, magnetometer data collected from around the world are analyzed to investigate the GICs caused by the 2015 St. Patricks Day storm. While significant GIC activity in the high-latitude regions due to storm-time substorm activity is shown for this event, enhanced GIC activity was also measured at two equatorial stations in the American and South-East Asian sectors. This equatorial GIC activity is closely examined, and it is shown that it is present both during the arrival of the interplanetary shock at the storm sudden commencement (SSC) in South-East Asia and during the main phase of the storm ∼ 10 hours later in South America. The SSC caused magnetic field variations at the equator in South-East Asia that were twice the magnitude of those observed only a few degrees to the north, strongly indicating that the equatorial electrojet (EEJ) played a significant role. The large equatorial magnetic field variations measured in South America are also examined and the coincident solar wind data are used to investigate the causes of the sudden changes in the EEJ ∼ 10 hours into the storm. From this analysis it is concluded that sudden magnetopause current increases due to increases in the solar wind dynamic pressure, and the sudden changes in the resultant magnetospheric and ionospheric current systems, are the primary drivers of equatorial GICs.

Adaptive Node Parameterization for Dynamic Determination of Boundaries and Nodes of GNSS Tomographic Models

Water vapor is one of the primary greenhouse gases and significantly impacts the atmosphere. Water vapor is the most active meteorological element and varies rapidly in both the spatial and temporal domains. As a promising means, Global Navigation Satellite Systems (GNSS) tomography has been used to construct the 3D distribution of water vapor in high resolutions. Currently, in the most commonly used node parameterization approaches, the region for the 3D modeling has a preset fixed regular shape for all tomographic epochs. As a result, too many unknown parameters need to be estimated and thus to degrade the performance of the tomographic solution. In this study, an innovative node parameterization approach using a combination of three meshing techniques to dynamically adjust both the boundary of the tomographic region and the position of nodes at each tomographic epoch is proposed. The three meshing techniques were boundary extraction, Delaunay triangulation, and force-displacement algorithm. The performance of the tomographic model resulting from the new approach was tested using one month GNSS data in May 2015 from the Hong Kong GNSS network and was compared against that of the conventional node parameterization approach. The reference for the validation of the accuracy of the test results were the radiosonde measurements from Kings Park Meteorological Station (HKKP) in Hong Kong. Results showed that in terms of root-mean-square error the accuracy of the new approach significantly improved in comparison to the traditional approach.

Seasonal Multifactor Modelling of Weighted-Mean Temperature for Ground-Based GNSS Meteorology in Hunan, China

In this study, radiosonde observations during the period of 2012-2013 from three stations in the Hunan region, China, were used to establish regional models (RTMs) that are a fitting function of multiple meteorological factors (, , and ). One-factor, two-factor, and three-factor RTMs were assessed by comparing their against the radiosonde-derived (as the truth) during the period of 2013-2014. Statistical results showed that the bias and RMS of the one-factor RTM, in comparison to the BTM result, were reduced by 88% and 28%, respectively. The two-factor and three-factor RTMs showed similar accuracy and both outperformed the one-factor RTM, with an improvement of 7% in RMS. The bias and RMS of all the four seasonal two-factor RTMs were smaller than the yearly two-factor RTM, with the improvements of 3%, 10%, 2%, and 3% in RMS. The improvement of the conversion factors in mean bias and RMS resulting from the seasonal two-factor RTM is 92% and 31%. The bias and RMS of the PWV resulting from the seasonal two-factor RTM are improved by 37% and 12%, respectively. Therefore, the seasonal two-factor RTMs are recommended for the research and applications of GNSS meteorology in the Hunan region, China.

Unseasonal development of post-sunset F-region irregularities over Southeast Asia on 28 July 2014: 1. Forcing from above?

AbstractThis contribution is the first of a two-part investigation into an unseasonal post-sunset equatorial F-region irregularity (EFI) event over the Southeast Asian region on the evening of 28 July 2014. Ground-based GPS scintillation data, space-based GPS radio occultation (RO) data, and ionosonde data show the existence of EFIs shortly after sunset over a region spanning 30° in longitude and 40° in latitude, centered on the geomagnetic equator. This post-sunset EFI event was observed during a time of the year when post-sunset equatorial plasma bubbles (EPBs) are very infrequent in the Southeast Asian longitude sector. GPS RO data shows that the EFI event over Southeast Asia coincided with the suppression of peak-season EPBs in the African and Pacific longitude sectors. Ionosonde data shows the presence of a strong pre-reversal enhancement (PRE) in the upward plasma drift over Southeast Asia prior to the detection of EFIs. Further, it is reported that this PRE was significantly stronger than on any other day of July 2014. An analysis of the geophysical conditions during this event reveals that this enhanced PRE was not caused by disturbed geomagnetic activity. Therefore, it is hypothesized that forcing from lower altitudes, perhaps tidal/planetary waves, was the potential cause of this strong PRE, and the subsequent EPB/EFI activity, on this day over the Southeast Asian sector.n

Ionospheric responses to typhoons in Australia during 2005–2014 using GNSS and FORMOSAT-3/COSMIC measurements

Tropical cyclones are a serious natural disaster concern in Australia due to El Niño and La Niña phenomena. However, little attention has been paid to the ionospheric responses to severe typhoons that have occurred in Australia. In this study, dual-frequency GPS measurements and ionosonde data were used to investigate the variations in ionospheric total electron content (TEC) and the critical frequency of the F2 layer (foF2) during Typhoons Ingrid, George, Pancho and Gillian. The results showed that the variations in the solar-terrestrial environment during all these typhoons were not significant, with the first three typhoons yielding similar TEC and foF2 results (both increased within 2xa0days of the day when the wind speed reached the peak). However, the results for Typhoon Gillian were different, as its TEC and foF2 values decreased within 2xa0days of the peak wind speed. To further investigate the spatial variation in the ionospheric electron density (IED) during Typhoon Gillian, the IEDs obtained from the FORMOAST-3/COSMIC ionospheric profiles were constructed for both reference and observation periods. The results showed that the differences between the two IED periods in the region around the storm eye ranged from −u20091.0 to −u20091.5u2009×u2009106xa0el/cm3, which is equivalent to about −u200937.5 to −u200950%. These low IED values were mainly focused in the 300–350xa0km altitude range, especially at the 300xa0km altitude level. The results also showed that all the ionospheric anomalies were located at the edge of the typhoon rather than the storm eye. This study will be helpful in deepening our understanding of the ionospheric responses to typhoons in Australia.

Long-Term Subsidence in Lava Fields at Piton de la Fournaise Volcano Measured by InSAR: New Insights for Interpretation of the Eastern Flank Motion

Long-term deformation often occurs in lava fields at volcanoes after flow emplacements. The investigation and interpretation of deformation in lava fields is one of the key factors for the assessment of volcanic hazards. As a typical Hawaiian volcano, Piton de la Fournaise volcano’s (La Reunion Island, France) main eruptive production is lava. Characteristics of the lava flows at Piton de la Fournaise, including the geometric parameters, location, and elevation, have been investigated by previous studies. However, no analysis focusing on the long-term post-emplacement deformation in its lava fields at a large spatial extent has yet been performed. One of the previous studies revealed an instability of the Eastern Flank since the March–April 2007 eruption related to post-emplacement lava subsidence. However, it was only a preliminary investigation. In this paper, an InSAR time series analysis is performed to characterize the long-term deformation in lava fields emplaced between 1998 and 2007 at Piton de la Fournaise, and to conduct an in-depth investigation over the influence of post-emplacement lava subsidence processes on the instability of the Eastern Flank. Results reveal an important regional difference in the subsidence behavior between the lava fields inside and outside of the Eastern Flank Area (EFA), which confirms that, in addition to the post-lava emplacement processes, other processes must have played a role in the observed subsidence in the EFA. The contribution of other processes is estimated to be up to ~78%. The spatial variation of the observed displacement in the EFA suggests that a set of active structures (like normal faults) could control a slip along a pre-existing structural discontinuity beneath the volcano flank. This study provides essential insights for the interpretation of the Eastern Flank motion of Piton de la Fournaise.

Haze Optical Properties from Long-Term Ground-Based Remote Sensing over Beijing and Xuzhou, China

Aerosol haze pollution has had a significant impact on both global climate and the regional air quality of Eastern China, which has a high proportion of high level pollution days. Statistical analyses of aerosol optical properties and direct radiative forcing at two AERONET sites (Beijing and Xuzhou) were conducted from 2013 to 2016. Results indicate: (1) Haze pollution days accounted for 26% and 20% of days from 2013 to 2016 in Beijing and Xuzhou, respectively, with the highest proportions in winter; (2) The averaged aerosol optical depth (AOD) at 550 nm on haze days were about 3.7 and 1.6 times greater than those on clean days in Beijing and Xuzhou, respectively. At both sites, the maximum AOD occurred in summer; (3) Hazes were dominated by fine particles at both sites. However, as compared to Xuzhou, Beijing had larger coarse mode AOD and higher percentage of small α. This data, together with an analysis of size distribution, suggests that the hazes in Beijing were more susceptible to coarse dust particles than Xuzhou; (4) During hazes in Beijing, the single scattering albedo (SSA) is significantly higher when compared to clean conditions (0.874 vs. 0.843 in SSA440 nm), an increase much less evident in Xuzhou. The most noticeable differences in both SSA and the imaginary part of the complex refractive index between Beijing and Xuzhou were found in winter; (5) In Beijing, the haze radiative forcing produced an averaged cooling effect of −113.6 ± 63.7 W/m2 at the surface, whereas the averaged heating effect of 77.5 ± 49.7 W/m2 within the atmosphere was at least twice as strong as clean days. In Xuzhou, such a radiative forcing effect appeared to be much smaller and the difference between haze and clean days was insignificant. Derived from long-term observation, these findings are more significant for the improvement of our understanding of haze formation in China and the assessment of its impacts on radiative forcing of climate change than previous short-term case studies.

The First Comparison Between Swarm‐C Accelerometer‐Derived Thermospheric Densities and Physical and Empirical Model Estimates

The first systematic comparison between Swarm-C accelerometer-derived thermospheric density and both empirical and physics-based model results using multiple model performance metrics is presented. This comparison is performed at the satellites high temporal 10-s resolution, which provides a meaningful evaluation of the models fidelity for orbit prediction and other space weather forecasting applications. The comparison against the physical model is influenced by the specification of the lower atmospheric forcing, the high-latitude ionospheric plasma convection, and solar activity. Some insights into the model response to thermosphere-driving mechanisms are obtained through a machine learning exercise. The results of this analysis show that the short-timescale variations observed by Swarm-C during periods of high solar and geomagnetic activity were better captured by the physics-based model than the empirical models. It is concluded that Swarm-C data agree well with the climatologies inherent within the models and are, therefore, a useful data set for further model validation and scientific research.