中低纬电离层暴的统计分析与经验建模

As a key issue of ionospheric weather study, systemic studies on ionospheric storms can not only further improve our understanding of the response of the ionosphere to solar and geomagnetic disturbances, but also help us to reveal the chemical, dynamic and electro-dynamic mechanisms during storms. Empirical modelling for regional ionospheric storm is also very useful, because it can provide us with tools and references for the forecasting and further practical application of ionospheric activity. In this thesis, we focus on describing and forecasting of ionospheric storms at middle and low latitudes. The main points of my investigations are listed as follows. (1) By using magnetic storms during the period over 50 years, the dependence of the type, onset time and time delay of the ionospheric storms on magnetic latitude, season and local time at middle and low latitudes in the East-Asian sector are studied. The results show that the occurrences of the types of ionospheric disturbances differ in latitude and season. The onset of the ionospheric storms depends on local time. At middle latitudes, most negative phase onsets are within the local time interval from night to early morning, and they rarely occurred in the local noon and afternoon sectors. At low latitudes, positive phases commence most frequently in the daytime sector as well as pre-midnight sector. The average time delays for both the positive and negative ionospheric storms increase with descending latitudes. The time delay has significant dependence on the local time of main phase onset (MPO). The time delay of positive response is shorter for daytime MPO and longer for night-time MPO, whereas the opposite applies for negative response. (2) Based on some previous researches, a primary empirical model for mid-latitude ionospheric disturbance is set up. By fitting to the observed data, we get a high accuracy with a mean RMSE of only 12-14% in summer and equinox. The model output has been compared with the output of STORM model, and the results show that, our model is much better than STORM in summer and a little better for some mid-latitude stations at equinox. Especially, for the type of two-step geomagnetic storm, our model can present twice descending of foF2 very well. In addition, our model can forecast positive ionospheric storms.

Diagnostics of equatorial and low latitude ionosphere by TEC mapping over Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The first real-time worldwide ionospheric predictions network: an advance in support of spaceborne experimentation, on-line model validation, and space weather

We report on the first realtime ionospheric predictions network and its capabilities to ingest a global database and forecast F-layer characteristics and "in situ" electron densities along the track of an orbiting spacecraft. A global network of ionosonde stations reported around-the-clock observations of F-region heights and densities, and an on-line library of models provided forecasting capabilities. Each model was tested against the incoming data; relative accuracies were intercompared to determine the best overall fit to the prevailing conditions; and the best-fit model was used to predict ionospheric conditions on an orbit-to-orbit basis for the 12-hour period following a twice-daily model test and validation procedure. It was found that the best-fit model often provided averaged (i.e., climatologically-based) accuracies better than 5% in predicting the heights and critical frequencies of the F-region peaks in the latitudinal domain of the TSS-1R flight path. There was a sharp contrast however, in model-measurement comparisons involving predictions of actual, unaveraged, along-track densities at the 295 km orbital altitude of TSS-1R In this case, extrema in the first-principle models varied by as much as an order of magnitude in density predictions, and the best-fit models were found to disagree with the "in situ" observations of Ne by as much as 140%. The discrepancies are interpreted as a manifestation of difficulties in accurately and self-consistently modeling the external controls of solar and magnetospheric inputs and the spatial and temporal variabilities in electric fields, thermospheric winds, plasmaspheric fluxes, and chemistry.

Influence of short-term solar disturbances on the fair weather conduction current

The fair weather atmospheric electrical current (Jz) couples the ionosphere to the lower atmosphere and thus provides a route by which changes in solar activity can modify processes in the lower troposphere. This paper examines the temporal variations and spectral characteristics of continuous measurements of Jz conducted at the Wise Observatory in Mitzpe-Ramon, Israel (30°35′ N, 34°45′ E), during two large CMEs, and during periods of increased solar wind density. Evidence is presented for the effects of geomagnetic storms and sub-storms on low latitude Jz during two coronal mass ejections (CMEs), on 24–25th October 2011 and 7–8th March 2012, when the variability in Jz increased by an order of magnitude compared to normal fair weather conditions. The dynamic spectrum of the increased Jz fluctuations exhibit peaks in the Pc5 frequency range. Similar low frequency characteristics occur during periods of enhanced solar wind proton density. During the October 2011 event, the periods of increased fluctuations in Jz lasted for 7 h and coincided with fluctuations of the inter-planetary magnetic field (IMF) detected by the ACE satellite. We suggest downward mapping of ionospheric electric fields as a possible mechanism for the increased fluctuations.

Tackling ionospheric scintillation threat to GNSS in Latin America

Scintillations are rapid fluctuations in the phase and amplitude of transionospheric radio signals which are caused by small-scale plasma density irregularities in the ionosphere. In the case of the Global Navigation Satellite System (GNSS) receivers, scintillation can cause cycle slips, degrade the positioning accuracy and, when severe enough, can even lead to a complete loss of signal lock. Thus, the required levels of availability, accuracy, integrity and reliability for the GNSS applications may not be met during scintillation occurrence; this poses a major threat to a large number of modern-day GNSS-based applications. The whole of Latin America, Brazil in particular, is located in one of the regions most affected by scintillations. These effects will be exacerbated during solar maxima, the next predicted for 2013. This paper presents initial results from a research work aimed to tackle ionospheric scintillation effects for GNSS users in Latin America. This research is a part of the CIGALA (Concept for Ionospheric Scintillation Mitigation for Professional GNSS in Latin America) project, co-funded by the EC Seventh Framework Program and supervised by the GNSS Supervisory Authority (GSA), which aims to develop and test ionospheric scintillation countermeasures to be implemented in multi-frequency, multi-constellation GNSS receivers.

A total electron content space weather study of the Nighttime Weddell Sea Anomaly of 1996/97 southern summer with TOPEX/Poseidon radar altimetry

This paper reports on a total electron content space weather study of the nighttime Weddell Sea Anomaly, overlooked by previously published TOPEX/Poseidon climate studies, and of the nighttime ionosphere during the 1996/1997 southern summer. To ascertain the morphology of spatial TEC distribution over the oceans in terms of hourly, geomagnetic, longitudinal and summer-winter variations, the TOPEX TEC, magnetic, and published neutral wind velocity data are utilized. To understand the underlying physical processes, the TEC results are combined with inclination and declination data plus global magnetic field-line maps. To investigate spatial and temporal TEC variations, geographic/magnetic latitudes and local times are computed. As results show, the nighttime Weddell Sea Anomaly is a large (∼1,600(°)2; ∼22 million km2 estimated for a steady ionosphere) space weather feature. Extending between 200°E and 300°E (geographic), it is an ionization enhancement peaking at 50°S–60°S/250°E–270°E and continuing beyond 66°S. It develops where the spacing between the magnetic field lines is wide/medium, easterly declination is large-medium (20°–50°), and inclination is optimum (∼55°S). Its development and hourly variations are closely correlated with wind speed variations. There is a noticeable (∼43%) reduction in its average area during the high magnetic activity period investigated. Southern summer nighttime TECs follow closely the variations of declination and field-line configuration and therefore introduce a longitudinal division of four (Indian, western/eastern Pacific, Atlantic). Northern winter nighttime TECs measured over a limited area are rather uniform longitudinally because of the small declination variation. TOPEX maps depict the expected strong asymmetry in TEC distribution about the magnetic dip equator.

The Spanish Space Weather Service SeNMEs. A Case Study on the Sun-Earth Chain

The Spanish Space Weather Service SeNMEs, www.senores.es, is a portal created by the SRG-SW of the Universidad de Alcala, Spain, to meet societal needs of near real-time space weather services. This webpage-portal is divided in different sections to fulfill users needs about space weather effects: radio blackouts, solar energetic particle events, geomagnetic storms and presence of geomagnetically induced currents. In less than one year of activity, this service has released a daily report concerning the solar current status and interplanetary medium, informing about the chances of a solar perturbation to hit the Earth's environment. There are also two different forecasting tools for geomagnetic storms, and a daily ionospheric map. These tools allow us to nowcast a variety of solar eruptive events and forecast geomagnetic storms and their recovery, including a new local geomagnetic index, LDin, along with some specific new scaling. In this paper we also include a case study analysed by SeNMEs. Using different high resolution and cadence data from space-borne solar telescopes SDO, SOHO and GOES, along with ionospheric and geomagnetic data, we describe the Sun-Earth feature chain for the event.

Weather variability, tides, and Barmah Forest Virus Disease in the Gladstone region, Australia

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

Cross-correlations between weather variables in Australia

The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.

A Method of Preparing Future Hourly Weather Data for the Study of Global Warming Impact on the Built Environment

The dynamic interaction between building systems and external climate is extremely complex, involving a large number of difficult-to-predict variables. In order to study the impact of global warming on the built environment, the use of building simulation techniques together with forecast weather data are often necessary. Since all building simulation programs require hourly meteorological input data for their thermal comfort and energy evaluation, the provision of suitable weather data becomes critical. Based on a review of the existing weather data generation models, this paper presents an effective method to generate approximate future hourly weather data suitable for the study of the impact of global warming. Depending on the level of information available for the prediction of future weather condition, it is shown that either the method of retaining to current level, constant offset method or diurnal modelling method may be used to generate the future hourly variation of an individual weather parameter. An example of the application of this method to the different global warming scenarios in Australia is presented. Since there is no reliable projection of possible change in air humidity, solar radiation or wind characters, as a first approximation, these parameters have been assumed to remain at the current level. A sensitivity test of their impact on the building energy performance shows that there is generally a good linear relationship between building cooling load and the changes of weather variables of solar radiation, relative humidity or wind speed.

Weather variability, sunspots, and the blooms of cyanobacteria

The roles of weather variability and sunspots in the occurrence of cyanobacteria blooms, were investigated using cyanobacteria cell data collected from the Fred Haigh Dam, Queensland, Australia. Time series generalized linear model and classification and regression (CART) model were used in the analysis. Data on notified cell numbers of cyanobacteria and weather variables over the periods 2001 and 2005 were provided by the Australian Department of Natural Resources and Water, and Australian Bureau of Meteorology, respectively. The results indicate that monthly minimum temperature (relative risk [RR]: 1.13, 95% confidence interval [CI]: 1.02-1.25) and rainfall (RR: 1.11; 95% CI: 1.03-1.20) had a positive association, but relative humidity (RR: 0.94; 95% CI: 0.91-0.98) and wind speed (RR:0.90; 95% CI: 0.82-0.98) were negatively associated with the cyanobacterial numbers, after adjustment for seasonality and auto-correlation. The CART model showed that the cyanobacteria numbers were best described by an interaction between minimum temperature, relative humidity, and sunspot numbers. When minimum temperature exceeded 18%C and relative humidity was under 66%, the number of cyanobacterial cells rose by 2.15-fold. We conclude that the weather variability and sunspot activity may affect cyanobacterial blooms in dams.

Preparation of future weather data to study the impact of climate change on buildings

The dynamic interaction between building systems and external climate is extremely complex, involving a large number of difficult-to-predict variables. In order to study the impact of climate change on the built environment, the use of building simulation techniques together with forecast weather data are often necessary. Since most of building simulation programs require hourly meteorological input data for their thermal comfort and energy evaluation, the provision of suitable weather data becomes critical. In this paper, the methods used to prepare future weather data for the study of the impact of climate change are reviewed. The advantages and disadvantages of each method are discussed. The inherent relationship between these methods is also illustrated. Based on these discussions and the analysis of Australian historic climatic data, an effective framework and procedure to generate future hourly weather data is presented. It is shown that this method is not only able to deal with different levels of available information regarding the climate change, but also can retain the key characters of a “typical” year weather data for a desired period.

Distribution profiles of key weather variables in Australian capital cities : implications for energy efficient building design

Local climate is a critical element in the design of energy efficient buildings. In this paper, ten years of historical weather data in Australia's eight capital cities were profiled and analysed to characterize the variations of climatic variables in Australia. The method of descriptive statistics was employed. Either the pattern of cumulative distribution and/or the profile of percentage distribution are presented. It was found that although weather variables vary with different locations, there is often a good, nearly linear relation between a weather variable and its cumulative percentage for the majority of middle part of the cumulative curves. By comparing the slopes of these distribution profiles, it may be possible to determine the relative range of changes of the particular weather variables for a given city. The implications of these distribution profiles of key weather variables on energy efficient building design are also discussed.