Strong geomagnetic activity forecast by neural networks under dominant southern orientation of the interplanetary magnetic field

The paper deals with the relation of the southern orientation of the north–south component _Bz$B_z$ of the interplanetary magnetic field to geomagnetic activity (GA) and subsequently a method is suggested of using the found facts to forecast potentially dangerous high GA. We have found that on a day with very high GA hourly averages of _Bz$B_z$ with a negative sign occur at least 16 times in typical cases. Since it is very difficult to estimate the orientation of _Bz$B_z$ in the immediate vicinity of the Earth one day or even a few days in advance, we have suggested using a neural-network model, which assumes the worse of the possibilities to forecast the danger of high GA – the dominant southern orientation of the interplanetary magnetic field. The input quantities of the proposed model were information about X-ray flares, type II and IV radio bursts as well as information about coronal mass ejections (CME). In comparing the GA forecasts with observations, we obtain values of the Hanssen–Kuiper skill score ranging from 0.463 to 0.727, which are usual values for similar forecasts of space weather. The proposed model provides forecasts of potentially dangerous high geomagnetic activity should the interplanetary CME (ICME), the originator of geomagnetic storms, hit the Earth under the most unfavorable configuration of cosmic magnetic fields. We cannot know in advance whether the unfavorable configuration is going to occur or not; we just know that it will occur with the probability of 31%.     

Reanalysis of radiation belt electron phase space density using various boundary conditions and loss models

Data assimilation is becoming an increasingly important tool for understanding the near Earth hazardous radiation environments. Reanalysis of the radiation belts can be used to identify the electron acceleration mechanism and distinguish local acceleration from radial diffusion. However, for any practical applications we need to determine how reliable is reanalysis, and how significant is the dependence of the results on the assumptions of the code and choice of boundary conditions. We present the sensitivity of reanalysis of the radiation belt electron phase space density (PSD) to the assumed location of the outer boundary, using the VERB code and a Kalman filter. We analyze the sensitivity of reanalysis to changes in the electron-loss throughout the domain, and the sensitivity to the assumed boundary condition and its effect on the innovation vector. All the simulations presented in this study for all assumed loss models and boundary conditions, show that peaks in the phase space density of relativistic electrons build up between 4.5 and 6 R_E during relativistic electron flux enhancements in the outer radiation belt. This clearly shows that peaks build up in the heart of the electron radiation belt independent of the assumptions in the model, and that local acceleration is operating there. The work here is also an important step toward performing reanalysis using observations from current and future missions.     

Specification of the Earth’s plasmasphere with data assimilation

In this paper we report on initial work toward data assimilative modeling of the Earth’s plasmasphere. As the medium of propagation for waves which are responsible for acceleration and decay of the radiation belts, an accurate assimilative model of the plasmasphere is crucial for optimizing the accurate prediction of the radiation environments encountered by satellites. On longer time-scales the plasmasphere exhibits significant dynamics. Although these dynamics are modeled well by existing models, they require detailed global knowledge of magnetospheric configuration which is not always readily available. For that reason data assimilation can be expected to be an effective tool in improving the modeling accuracy of the plasmasphere. In this paper we demonstrate that a relatively modest number of measurements, combined with a simple data assimilation scheme, inspired by the ensemble Kalman filtering data assimilation technique does a good job of reproducing the overall structure of the plasmasphere including plume development. This raises hopes that data assimilation will be an effective method for accurately representing the configuration of the plasmasphere for space weather applications.     

Policy for robust space-based earth science,technology and applications

Satellite remote sensing technology has contributed to the transformation of multiple earth science domains, putting space observations at the forefront of innovation in earth science. With new satellite missions being launched every year, new types of earth science data are being incorporated into science models and decision-making systems in a broad array of organizations. Policy guidance can influence the degree to which user needs influence mission design and when, and ensure that satellite missions serve both the scientific and user communities without becoming unfocused and overly expensive. By considering the needs of the user community early on in the mission-design process, agencies can ensure that satellites meet the needs of multiple constituencies. This paper describes the mission development process in NASA and ESA and compares and contrasts the successes and challenges faced by these agencies as they try to balance science and applications within their missions.     

Photon counting detector for space debris laser tracking and lunar laser ranging

We are reporting on a design, construction and performance of solid state photon counting detector package which has been designed for laser tracking of space debris. The detector has been optimized for top photon detection efficiency and detection delay stability. The active area of the commercially available avalanche photodiode manufactured on Si (SAP500 supplied by Laser Components, Inc.) is circular with a diameter of 500 μm. The newly designed control circuit enables to operate the detection sensor at a broad range of biases 5–50 V above its breakdown voltage of 125 V. This permits to select a right trade-off between photon detection efficiency, timing resolution and dark count rate. The photon detection efficiency exceeds 70% at the wavelength of 532 nm. This is the highest photon detection efficiency ever reported for such a device. The timing properties of the detector have been investigated in detail. The timing resolution is better than 80 ps r.m.s, the detection delay is stable within units of picoseconds over several hours of operation. The detection delay stability in a sense of time deviation of 800 fs has been achieved. The temperature change of the detection delay is 0.5 ps/K. The detector has been tested as an echo signal detector in laser tracking of space debris at the satellite laser station in Graz, Austria. Its application in lunar laser ranging is under consideration by several laser stations.     

Gravity field models from kinematic orbits of CHAMP,GRACE and GOCE satellites

The aim of our work is to generate Earth’s gravity field models from GPS positions of low Earth orbiters. Our inversion method is based on Newton’s second law, which relates the observed acceleration of the satellite with forces acting on it. The observed acceleration is obtained as numerical second derivative of kinematic positions. Observation equations are formulated using the gradient of the spherical harmonic expansion of the geopotential. Other forces are either modelled (lunisolar perturbations, tides) or provided by onboard measurements (nongravitational perturbations). From this linear regression model the geopotential harmonic coefficients are obtained.     

Modeling satellite drag coefficients with response surfaces

Satellite drag coefficients are a major source of uncertainty in predicting the drag force on satellites in low Earth orbit. Among other things, accurately predicting the orbit requires detailed knowledge of the satellite drag coefficient. Computational methods are an important tool in computing the drag coefficient but are too intensive for real-time and predictive applications. Therefore, analytic or empirical models that can accurately predict drag coefficients are desired. This work uses response surfaces to model drag coefficients. The response surface methodology is validated by developing a response surface model for the drag coefficient of a sphere where the closed-form solution is known. The response surface model performs well in predicting the drag coefficient of a sphere with a root mean square percentage error less than 0.3% over the entire parameter space. For more complex geometries, such as the GRACE satellite, the Hubble Space Telescope, and the International Space Station, the model errors are only slightly larger at about 0.9%, 0.6%, and 1.0%, respectively.