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.     

Debris flux comparisons from the Goldstone Radar,Haystack Radar,and Hax Radar prior,during, and after the last solar maximum

The continual monitoring of the low Earth orbit (LEO) debris environment using highly sensitive radars is essential for an accurate characterization of these dynamic populations. Debris populations are continually evolving since there are new debris sources, previously unrecognized debris sources, and debris loss mechanisms that are dependent on the dynamic space environment. Such radar data are used to supplement, update, and validate existing orbital debris models. NASA has been utilizing radar observations of the debris environment for over a decade from three complementary radars: the NASA JPL Goldstone radar, the MIT Lincoln Laboratory (MIT/LL) Long Range Imaging Radar (known as the Haystack radar), and the MIT/LL Haystack Auxiliary radar (HAX). All of these systems are highly sensitive radars that operate in a fixed staring mode to statistically sample orbital debris in the LEO environment. Each of these radars is ideally suited to measure debris within a specific size region. The Goldstone radar generally observes objects with sizes from 2 mm to 1 cm. The Haystack radar generally measures from 5 mm to several meters. The HAX radar generally measures from 2 cm to several meters. These overlapping size regions allow a continuous measurement of cumulative debris flux versus diameter from 2 mm to several meters for a given altitude window. This is demonstrated for all three radars by comparing the debris flux versus diameter over 200 km altitude windows for 3 nonconsecutive years from 1998 to 2003. These years correspond to periods before, during, and after the peak of the last solar cycle. Comparing the year to year flux from Haystack for each of these altitude regions indicate statistically significant changes in subsets of the debris populations. Potential causes of these changes are discussed. These analysis results include error bars that represent statistical sampling errors.     

Structure of the migrating diurnal tide in the Whole Atmosphere Community Climate Model (WACCM)

As part of an ongoing effort to understand the migrating diurnal tide generated by the NCAR Whole Atmosphere Community Climate Model, version 3 (WACCM3), we compare the WACCM3 migrating diurnal tide in the horizontal wind and temperature fields to similar results from the Global Scale Wave Model (GSWM). The WACCM3 diurnal tidal wind fields are also compared to tropical radar measurements at Kauai (22°N, 200.2°E) and Rarotonga (21.3°S, 199.7°E). The large-scale features of the WACCM3 results, such as the global spatial structure and the semiannual amplitude variation are in general agreement with past tidal studies; however, several differences do exist. WACCM3 exhibits a much higher degree of hemispheric asymmetry, lower overall amplitudes around the equinoxes, and peaks which are more confined in latitude when compared with the GSWM. Factors which may contribute to such differences between WACCM3 and GSWM are the solar heating profiles from ozone and water vapor, dissipation, and the zonal mean zonal winds. We find that the internally generated heating in WACCM3 and eddy dissipation values are both smaller than the values specified in the GSWM; the eddy dissipation fields and zonal mean zonal winds of the two models also display measurable differences in spatial structure. Comparisons with radar data show several differences in spatial and seasonal structure. In particular, the diurnal tide zonal winds in WACCM3 above Kauai are considerably larger in amplitude than those observed in the radar data, due to contributions from nonmigrating tidal components including wave numbers eastward 1 through 3, westward 2, and stationary components, which interfere constructively with the migrating component around equinox in WACCM3.     

Plants survive rapid decompression: Implications for bioregenerative life support

Radish (Raphanus sativus), lettuce (Latuca sativa), and wheat (Triticum aestivum) plants were grown at either 98 kPa (ambient) or 33 kPa atmospheric pressure with constant 21 kPa oxygen and 0.12 kPa carbon dioxide in atmospherically closed pressure chambers. All plants were grown rockwool using recirculating hydroponics with a complete nutrient solution. At 20 days after planting, chamber pressures were pumped down as rapidly as possible, reaching 5 kPa after about 5 min and ∼1.5 kPa after about 10 min. The plants were held at 1.5 kPa for 30 min and then pressures were restored to their original settings. Temperature (22 °C) and humidity (65% RH) controls were engaged throughout the depressurization, although temperatures dropped to near 16 °C for a brief period. CO₂ and O₂ were not detectable at the low pressure, suggesting that most of the 1.5 kPa atmosphere consisted of water vapor. Following re-pressurization, plants were grown for another 7 days at the original pressures and then harvested. The lettuce, radish, and wheat plants showed no visible effects from the rapid decompression, and there were no differences in fresh or dry mass when compared to control plants maintained continuously at 33 or 98 kPa. But radish storage root fresh mass and lettuce head fresh and dry masses were less at 33 kPa compared to 98 kPa for both the controls and decompression treatment. The results suggest that plants are extremely resilient to rapid decompression, provided they do not freeze (from evaporative cooling) or desiccate. The water of the hydroponic system was below the boiling pressure during these tests and this may have protected the plants by preventing pressures from dropping below 1.5 kPa and maintaining humidity near 1.5 kPa. Further testing is needed to determine how long plants can withstand such low pressure, but the results suggest there are at least 30 min to respond to catastrophic pressure losses in a plant production chamber that might be used for life support in space.     

Response of the lower atmosphere to intense geomagnetic storms

In this short paper we examine the possible connection between atmospheric parameters measured at low and middle altitudes and geomagnetic storms occurred in 2000 and 2003. For that, from a chain of stations located near the meridian 60°W we compare the storm time values of temperature and wind speed with their standard deviation 2σ obtained from quiet time values. We observed statistically significant variations at several altitudes during the storm recovery phase and after it, both in neutral wind speed and temperature. The results obtained suggest that atmospheric parameters could be affected by geomagnetic storms.     

基于THz大气窗口的金星地表遥感研究

文章以金星快车VIRTIS载荷相关数据为出发点,验证金星大气模型相适应参数及其窗口。并通过模型参数中的THz频谱分布,阐述实现金星地表遥感探测科学目标的THz相适应理论基础,并提出多功能金星遥感构想。     

大气偏振光导航技术

为克服现有导航技术在战场应用中存在的不足,借鉴生物光学导航机理,开发新的导航方式,是未来导航技术研究的一个重要发展趋势。本文对自然界中的昆虫光学导航机理进行了介绍和分析,并对大气偏振光导航的发展趋势进行了探讨,提出了大气振光导航技术发展过程中需要解决的关键问题。     

Water surface temperature estimation from Landsat 7 ETM+ thermal infrared data using the generalized single-channel method: Case study of Embalse del Río Tercero (Córdoba,Argentina)

Monitoring of warm distribution in water is fundamental to understand the performance and functioning of reservoirs and lakes. Surface water temperature is a key parameter in the physics of aquatic systems processes since it is closely related to the energy fluxes through the water–atmosphere interface. Remote sensing applied to water quality studies in inland waterbodies is a powerful tool that can provide additional information difficult to achieve by other means. The combination of good real-time coverage, spatial resolution and free availability of data makes Landsat system a proper alternative. Many papers have developed algorithms to retrieve surface temperature (principally, land surface temperature) from at-sensor and surface emissivity data. The aim of this study is to apply the single-channel generalized method (SCGM) developed by Jiménez-Muñoz and Sobrino (2003) for the estimation of water surface temperature from Landsat 7 ETM+ thermal bands. We consider a constant water emissivity value (0.9885) and we compare the results with radiative transfer classic method (RTM).     

Different mechanisms controlling interannual phytoplankton variation in the South China Sea and the western North Pacific subtropical gyre: A satellite study

A time series of remotely-sensed chlorophyll a (chl a) in 1997–2010 was evaluated to determine mechanisms of phytoplankton variation in recent decade in the South China Sea (SCS) and the western North Pacific subtropical gyre (WNPSG). Satellite-derived sea surface temperature (SST) and aerosol optical thickness (AOT) were used as proxies for vertical nutrient supply and atmospheric aerosol, respectively. Chl a in the WNPSG was not significantly correlated with SST (r = 0.18, p > 0.05), but was with AOT (r = 0.31, p < 0.05), indicating the chl a was influenced by atmospheric deposition. Chl a in the SCS was negatively correlated with SST (r = −0.60, p < 0.05) and was positively with AOT (r = 0.20, p < 0.05). The correlation between AOT and chl a in the SCS does not reflect a major contribution from atmospheric deposition to chl a; instead, the relationship resulted from concurrence of the peaks of AOT and wind speed, which drive water mixing and nutrient supply. Consequently, chl a in the SCS would be regulated primarily by the nutrient supply from deep waters. Because SST was controlled by the ENSO teleconnection in the SCS, the chl a was coupled with ENSO events. The present study demonstrated that interannual phytoplankton variation could be controlled by different factors even in neighboring oligotrophic regions.     

Temporal and spatial stochastic behaviour of high-frequency slant tropospheric delays from simulations and real GPS data

In this paper, a turbulence theory-based simulation procedure for slant tropospheric delay variations is presented. Based on this procedure tropospheric delay variations are simulated for three different geometric scenarios. The stochastic behaviour of the generated time series is assessed in terms of temporal structure functions. It is shown that the temporal structure functions – in general – follow a 5/3 to 2/3 power-law behaviour. Deviations from this behaviour due to the complex interaction between varying observation geometry and atmospheric/turbulent conditions are discussed.