AIUB-CHAMP02S: The influence of GNSS model changes on gravity field recovery using spaceborne GPS

The gravity field model AIUB-CHAMP02S, which is based on six years of CHAMP GPS data, is presented here. The gravity field parameters were derived using a two step procedure: In a first step a kinematic trajectory of a low Earth orbiting (LEO) satellite is computed using the GPS data from the on-board receiver. In this step the orbits and clock corrections of the GPS satellites as well as the Earth rotation parameters (ERPs) are introduced as known. In the second step this kinematic orbit is represented by a gravitational force model and orbit parameters.     

Improved kHz-SLR tracking techniques and orbit quality analysis for LEO missions

Satellite gravity field missions such as CHAMP, GRACE and GOCE are designed as low Earth orbiting spacecraft (LEO) with orbit heights of about 250–500 km. The challenging mission objectives require a very precise knowledge of the satellite orbit position in space. For these missions precise orbit information is typically provided by GPS satellite-to-satellite tracking (SST) observations supported by satellite laser ranging (SLR).     

Global GPS reference frame solutions of unlimited size

This paper reports on the Dancer project, which is one of three related projects initiated by working group 1 of the International Association of Geodesy. The Dancer project develops JAVA parameter estimation software that runs in the form of a distributed process on the internet, in such a way that each processing node handles the data of a single geodetic instrument. By exchanging a minimum amount of information among all processing nodes, the same global normal equation solution is found by all instruments. The result is a fully scalable least squares solution that has no practical limit to the number of GPS receivers or other tracking devices that may be included in a single reference frame realization.     

High vertical resolution water vapour profiles in the upper troposphere and lower stratosphere retrieved from MAESTRO solar occultation spectra

An algorithm has been developed that retrieves water vapour profiles in the upper troposphere and lower stratosphere from optical depth spectra obtained by the Measurements of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (MAESTRO) instrument onboard the SCISAT satellite as part of the Atmospheric Chemistry Experiment (ACE) mission. The retrieval relies on ro-vibrational absorption of solar radiation by water vapour in the 926–970 nm range. During the iterative inversion process, the optical depth spectra are simulated at the spectral resolution and sampling frequency of MAESTRO using the correlated-k approximation. The Chahine inversion updates the water vapour volume mixing ratio (VMR), adjusting all retrieval layers simultaneously, to match the observed differential optical depth due to absorption by water vapour and ozone at each tangent height. This approach accounts for significant line saturation effects. Profiles are typically obtained from ∼22 km down to the cloud tops or to 5 km, with relative precision as small as 3% in the troposphere. In the lower stratosphere, the precision on water vapour VMR is ∼1.3 μmol/mol in an individual retrieval layer (∼1 km thick). The spectral capability of MAESTRO allows for the clear separation of extinction due to water vapour and aerosol, and for the fitting quality to be quantified and used to determine an altitude-dependent convergence criterion for the retrieval. In the middle troposphere, interhemispheric differences in water vapour VMR are driven by oceanic evaporation whereas in the upper troposphere, deep convection dominates and a strong seasonal cycle is observed at high latitudes.     

Gnevyshev gap, Forbush decreases, ICMEs and solar wind electric field: relationships

We have studied annual frequency distribution of the Forbush decreases for three solar cycles (20, 21, 22); most are associated with the fast ICMEs and SSCs. The frequency varies in step with the solar cycle but the distribution has a notable gap embedded in it, near the maximum of the cycle leading to two peaks in Forbush decreases per cycle. We show that the gap coincides with the epoch of solar polar field reversal. There is an indication of an odd/even cycle effect in the frequency distribution of Forbush decreases and the associated SSCs. We find that two peaks in Forbush decrease and SSC distributions are separated by the Gnevyshev gap; second peaks occur well before the onset of the high-speed streams in the descending phase of a cycle which do not cause Forbush decreases but do contribute to a peak in the geomagnetic activity index Ap. We compare Forbush decrease and SSC distributions with the corresponding distribution of the solar wind electric field and find that a large amplitude of the electric field of itself does not cause a Forbush decrease to occur unless it is also associated with a fast ICME/SSC.     

On the correlation of the solar wind observed at the L5 point and at the Earth

The L5 point is a promising location for forecasting co-rotating high-speed streams in the solar wind arriving at the Earth. We correlated the solar wind data obtained by the Nozomi spacecraft in interplanetary space and by the Advanced Composition Explorer (ACE) at the L1 point, and found that the correlation is significantly improved from that of the 27-day recurrence of ACE data. Based on the correlation between the two spacecraft observations, we estimated the correlation of the solar wind velocity between the L5 point and at the Earth, and found that the correlation coefficient was about 0.78 in late 1999, while that of the 27-day recurrence was 0.51. Eighty-eight percent of the velocity difference falls within 100 km/s between the L5 point and the Earth. This demonstrates the potential capability of solar wind monitoring at the L5 point to forecast the geomagnetic disturbances 4.5 days in advance.     

Space weather and commercial airlines

Space weather phenomena can effect many areas of commercial airline operations including avionics, communications and GPS navigation systems. Of particular importance at present is the recently introduced EU legislation requiring the monitoring of aircrew radiation exposure, including any variations at aircraft altitudes due to solar activity. With the introduction of new ultra-long-haul “over-the-pole” routes, “more-electric” aircraft in the future, and the increasing use of satellites in the operation, the need for a better understanding of the space weather impacts on future airline operations becomes all the more compelling. This paper will present the various space weather effects, some provisional results of an ongoing 3-year study to monitor cosmic radiation in aircraft, and conclude by summarising some of the identified key operational issues, which must be addressed, with the help of the science community, if the airlines want to benefit from the availability of space weather services.     

Space weather in Japan

In Japan, Communications Research Laboratory engages in operational space environment information services as National Forecasting Center and Regional Warning Center of ISES. Data from local observations and data collected via internet from domestic and foreign institutes are used for the daily operational forecast. Fundamental research on space weather issues has been carried out at several institutes and universities, including STE Laboratory and NASDA. In this presentation, an overview of current space weather forecast operations and a system for information outreach in Japan will be presented. Current and future observation programs from ground-base and space will be also briefly reviewed.     

Classification of solar wind structures and intense geomagnetic storm alarms with self-organizing maps

Intense geomagnetic storms (D_st < −100 nT) usually occur when a large interplanetary duskward-electric field (with Ey > 5 mV m⁻¹) lasts for more than 3 h. In this article, a self-organizing map (SOM) neural network is used to recognize different patterns in the temporal variation of hourly averaged Ey data and to predict intense storms. The input parameters of SOM are the hourly averaged Ey data over 3 h. The output layer of the SOM has a total of 400 neurons. The hourly Ey data are calculated from solar wind data, which are provided by NSSDC OMNIWeb and ACE spacecraft and contain information on 143 intense storms and a fair number of moderate storms, weak storms and quiet periods between September 3, 1966 and June 30, 2002. Our results show that SOM is able to classify solar wind structures and therefore to give timely intense storm alarms. In our SOM, 21 neurons out of 400 are identified to be closely associated with the intense storms and they successfully predict 134 intense storms out of the 143 ones selected. In particular, there are 14 neurons for which, if one or more of them are present, the occurrence probability of intense storms is about 90%. In addition, several of these 14 neurons can predict big magnetic storm (D_st  −180 nT). In summary, our method achieves high accuracy in predicting intense geomagnetic storms and could be applied in space environment prediction.