Measuring atmospheric density using GPS–LEO tracking data

We present a method to estimate the total neutral atmospheric density from precise orbit determination of Low Earth Orbit (LEO) satellites. We derive the total atmospheric density by determining the drag force acting on the LEOs through centimeter-level reduced-dynamic precise orbit determination (POD) using onboard Global Positioning System (GPS) tracking data. The precision of the estimated drag accelerations is assessed using various metrics, including differences between estimated along-track accelerations from consecutive 30-h POD solutions which overlap by 6 h, comparison of the resulting accelerations with accelerometer measurements, and comparison against an existing atmospheric density model, DTM-2000. We apply the method to GPS tracking data from CHAMP, GRACE, SAC-C, Jason-2, TerraSAR-X and COSMIC satellites, spanning 12 years (2001–2012) and covering orbital heights from 400 km to 1300 km. Errors in the estimates, including those introduced by deficiencies in other modeled forces (such as solar radiation pressure and Earth radiation pressure), are evaluated and the signal and noise levels for each satellite are analyzed. The estimated density data from CHAMP, GRACE, SAC-C and TerraSAR-X are identified as having high signal and low noise levels. These data all have high correlations with anominal atmospheric density model and show common features in relative residuals with respect to the nominal model in related parameter space. On the contrary, the estimated density data from COSMIC and Jason-2 show errors larger than the actual signal at corresponding altitudes thus having little practical value for this study. The results demonstrate that this method is applicable to data from a variety of missions and can provide useful total neutral density measurements for atmospheric study up to altitude as high as 715 km, with precision and resolution between those derived from traditional special orbital perturbation analysis and those obtained from onboard accelerometers.     

A study of forest vegetation dynamics in the south of the Krasnoyarskii Krai in spring

Remote sensing applications have greatly enhanced ability to monitor and manage in the areas of forestry. Accurate measurements of regional and global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Study of vegetation phenology is required for understanding of variability in ecosystem. In this paper, monitoring of vegetation dynamics using time series of satellite data is presented. Vegetation variability (vegetation rate) in different topoclimatic areas is investigated. Original software using IDL interactive language for processing of satellite long-term data series was developed. To investigate growth dynamics vegetation rate inferred from remote sensing was used. All estimations based on annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Vegetation rate for Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) was calculated using MODIS data. The time series covers spring seasons of each of 9 years, from 2000 to 2008. Comparison of EVI and NDVI derived growth rates has shown that NDVI derived rates reveal spatial structure better. Using long-term data of vegetation rates variance was estimated that helps to reveal areas with anomalous growth rate. Such estimation shows sensitivity degree of different areas to different topoclimatic conditions. Woods of heights depend on spatial topoclimatic variability unlike woods of lowlands. Principal components analysis shows vegetation with different rate conditions. Also it reveals vegetation of same type in areas with different conditions. It was demonstrated that using of methods for estimating the dynamic state of vegetation based on remote sensing data enables successful monitoring of vegetation phenology.     

Long term changes of altimeter range and geophysical corrections at altimetry calibration sites

Accurate sea level trend determination is fundamentally related to calibration of both the instrument as well as to investigate if there are linear trends in the set of standard geophysical and range corrections applied to the sea level observations. Long term changes in range corrections can leak into the observed sea level record and be interpreted as part of the sea level trend. Particularly if these exhibit anomalous trend close to the satellite calibration sites.     

Detection of volcanic gases and particles by satellite

In this paper the detection of components of volcanic eruption has been carried out investigating, in appropriate bands of the electromagnetic spectrum (6.25, 8.7, 10.8, 12 μm), the values of the brightness temperature. The analysis has been performed in the Thermal Infrared Region (TIR) studying both the absorption–emission and scattering phenomena related to the interactions between electromagnetic radiation and volcanic emissions. The results have been achieved by means of a combined use of numerical simulations, devoted to examining the behaviour of the atmosphere gases and volcanic components, and remotely sensed satellite images. The proposed methodologies allow an estimate of the amount of gaseous and solid components, of the size of the emitted particles, of the height of the volcanic plume and of the distance of the volcanic components from the crater. The processed images come from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) sensor on board the geo-stationary satellite Meteosat Second Generation (MSG) and take into consideration an eruption of the Etna volcano as a study case (1st of April 2012, 04:30 and 05:30 UTC). The procedures are general and may therefore be extended to any other similar case.     

Using the Global Navigation Satellite System and satellite altimetry for combined Global Ionosphere Maps

For deriving global maps of the Total Electron Content (TEC) from space geodetic techniques usually observations from the Global Navigation Satellite System (GNSS) are taken. However, the GNSS stations are inhomogeneously distributed, with large gaps particularly over the sea surface.     

High resolution limb observations of clouds by the CRISTA-NF experiment during the SCOUT-O3 tropical aircraft campaign

The Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere – New Frontiers (CRISTA-NF) experiment on board the Russian research aircraft Geophysica measures limb emission spectra with an unprecedented vertical and horizontal resolution in the 4–15 μm wavelength region. The IR spectra measured during the SCOUT-O3 Tropical Aircraft Campaign have been analysed with respect of cloud occurrence, cloud vertical and horizontal extent, cloud spatial structures and their utilisation for trace gas retrievals. In addition indicators for ice water content and optical thickness of the clouds have been adopted. These new kinds of measurements in the upper troposphere/lower stratosphere region are especially valuable for the design and development of future space borne high resolution limb sounders.     

Statistical comparison of night-time NO2 observations in 2003–2006 from GOMOS and MIPAS instruments

GOMOS (Global Ozone Monitoring by Occultation of Stars) and MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) are remote sensing instruments on board the European Space Agency’s Envisat satellite. GOMOS and MIPAS have been designed for observations of stratospheric and mesospheric constituents, including ozone and nitrogen dioxide. Both instruments have a good global coverage of observations and can provide data also from the polar regions. In this paper, we compare night-time NO₂ data from GOMOS with those from MIPAS. We present statistics of selected sets of data spanning from the year 2003 to 2006. The results for low-to-mid latitudes show that the two instruments are in a good agreement in the middle stratosphere, the differences being typically less than 5%. In the upper stratosphere, GOMOS observations generally show 15% higher values than those from MIPAS. The bias is in virtually all cases smaller than the combined systematic error of the measurements, giving great confidence in the GOMOS and MIPAS data quality. The result for high mesospheric NO₂ mixing ratios observed in the polar regions during winter times indicate a good agreement between GOMOS and MIPAS. In the mesosphere, the difference is less than 35% and smaller than the systematic error. Due to the high mesospheric signal, MIPAS sensitivity decreases in the stratosphere which results in larger differences between the two instruments.     

Recovery of the Earth’s gravity field from formation-flying satellites: Temporal aliasing issues

Temporal and mean gravity field models derived from the twin-satellite, leader–follower mission GRACE have provided a new type of information for Earth sciences. In this contribution, we study the potential of various alternative satellite formations for gravity field determination in the post-GRACE era in a simulation environment. In particular, the effects of spherical harmonic truncation and of temporal aliasing in the processing of gravity products from such future formations are investigated.     

编队卫星相对运动描述方法综述

对于近地轨道卫星编队飞行的相对运动理论研究,可以采用的方法包括直角坐标法和 轨道要素法。利用直角坐标法得到的相对运动动力学方程可以用于编队队形控制研究,轨道 要素法能够给出相对运动的运动学描述,便于定量研究摄动影响和进行编队队形设计。分析 了直角坐标法在描述卫星长期编队飞行方面的局限性,综述了利用轨道要素描述编队卫星相 对运动的各种研究方法,包括轨道要素差法、相对轨道要素法和参照轨道要素法等。     

一种基于分组截短PN码的SOFDM信道估计方法

基于PN序列的信道估计方法的特点是计算过程简明,已被广泛应用在地面无线局域网系统中。在卫星正交频分多路复用传输体制(SOFDM)系统中引入传统PN序列信道估计方法的主要问题在于卫星信道的多径延时远大于SOFDM数据符号的持续时间,信道特性比较复杂,使得传统方法的估计精度严重下降。提出了一种改进的方法,根据信道的近似周期特性对数据帧进行合理的等长度分组,并把长PN序列改为短PN码来跟踪信道局部特性的变化,再对分组后的数据子帧分别进行信道估计。对该方法的设计思想进行了理论分析,并通过仿真验证了该方法的估计精度比传统方法至少提高了10倍。