The influence of aurora on ionospheric electron content

The ionospheric electron content was measured at La Ronge, Sask. for a variety of auroral conditions during the Pulsating Aurora Campaign in February of 1980. The two-frequency differential phase technique was used with the NNSS satellite beacons. Comparisons of optical data and the radio results indicate that for quite strong pulsations the electron content is modulated by less than 2%. Even this small change is somewhat larger than the purely temporal variations to be expected on the basis of currently accepted relaxation times in the ionosphere. If the observed fluctuations are interpreted as representing both temporal and spatial variations, good agreement is obtained with model calculations. For irregularity sizes and strengths to which the experiment is sensitive, structure was present in diffuse or patchy aurora but absent from at least some well defined forms. This suggests that the technique can be used to explore the mechanism of formation of the irregularities.

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Spatio-temporal variations of NO<sub>y</sub> species in the northern latitudes stratosphere measured with the balloon-borne MIPAS instrument

Atmospheric Chemistry and Physics ◽

10.5194/acp-9-1151-2009 ◽

2009 ◽

Vol 9 (4) ◽

pp. 1151-1163 ◽

Cited By ~ 10

Author(s):

A. Wiegele ◽

A. Kleinert ◽

H. Oelhaf ◽

R. Ruhnke ◽

G. Wetzel ◽

...

Keyword(s):

Continuous Measurement ◽

Temporal Distribution ◽

Polar Vortex ◽

Temporal Variations ◽

Model Calculations ◽

Mixing Ratios ◽

Northern Latitudes ◽

Photolysis Rates ◽

Spatio Temporal ◽

Good Agreement

Abstract. This paper presents the spatio-temporal distribution of NOy species at altitudes between 14 and 31 km as measured with the MIPAS-B instrument on the morning of 21 March 2003 in northern Scandinavia. At lower altitudes (below about 22 km), temperature variations, the distribution of ClONO2, and the tracer N2O reveal the dynamics through the edge of the late arctic polar vortex. At higher altitudes, continuous measurement before, during, and after sunrise provides information about photochemistry illustrating the evolution of the photochemically active gases NO2 and N2O5 around sunrise. The measured temporal evolution of NO2 and N2O5 is compared to box modelling that is run along backward calculated trajectories. While the comparison of measured and modelled N2O5 reveals significant differences, there is a good agreement between the model and observations for NO2 in terms of volume mixing ratios but the simulated decrease shortly after sunrise is underestimated compared to the measurements. The differences are attributed to the photolysis rates used in the box model calculations.

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Functional model modification of precise point positioning considering the time-varying code biases of a receiver

Satellite Navigation ◽

10.1186/s43020-021-00040-4 ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Baocheng Zhang ◽

Chuanbao Zhao ◽

Robert Odolinski ◽

Teng Liu

Keyword(s):

Precise Point Positioning ◽

Functional Model ◽

Geodetic Network ◽

Temporal Variations ◽

Gps Data ◽

Electron Content ◽

Time Varying ◽

Dual Frequency ◽

Total Electron ◽

Point Positioning

AbstractPrecise Point Positioning (PPP), initially developed for the analysis of the Global Positing System (GPS) data from a large geodetic network, gradually becomes an effective tool for positioning, timing, remote sensing of atmospheric water vapor, and monitoring of Earth’s ionospheric Total Electron Content (TEC). The previous studies implicitly assumed that the receiver code biases stay constant over time in formulating the functional model of PPP. In this contribution, it is shown this assumption is not always valid and can lead to the degradation of PPP performance, especially for Slant TEC (STEC) retrieval and timing. For this reason, the PPP functional model is modified by taking into account the time-varying receiver code biases of the two frequencies. It is different from the Modified Carrier-to-Code Leveling (MCCL) method which can only obtain the variations of Receiver Differential Code Biases (RDCBs), i.e., the difference between the two frequencies’ code biases. In the Modified PPP (MPPP) model, the temporal variations of the receiver code biases become estimable and their adverse impacts on PPP parameters, such as ambiguity parameters, receiver clock offsets, and ionospheric delays, are mitigated. This is confirmed by undertaking numerical tests based on the real dual-frequency GPS data from a set of global continuously operating reference stations. The results imply that the variations of receiver code biases exhibit a correlation with the ambient temperature. With the modified functional model, an improvement by 42% to 96% is achieved in the Differences of STEC (DSTEC) compared to the original PPP model with regard to the reference values of those derived from the Geometry-Free (GF) carrier phase observations. The medium and long term (1 × 104 to 1.5 × 104 s) frequency stability of receiver clocks are also significantly improved.

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A Meta-Methodology for Improving Land Cover and Land Use Classification with SAR Imagery

Remote Sensing ◽

10.3390/rs12060961 ◽

2020 ◽

Vol 12 (6) ◽

pp. 961 ◽

Cited By ~ 1

Author(s):

Marinalva Dias Soares ◽

Luciano Vieira Dutra ◽

Gilson Alexandre Ostwald Pedro da Costa ◽

Raul Queiroz Feitosa ◽

Rogério Galante Negri ◽

...

Keyword(s):

Remote Sensing Data ◽

Data Classification ◽

Test Site ◽

Radar Data ◽

Input Image ◽

Optical Data ◽

Land Use Classification ◽

Object Based ◽

Sar Imagery ◽

Small Change

Per-point classification is a traditional method for remote sensing data classification, and for radar data in particular. Compared with optical data, the discriminative power of radar data is quite limited, for most applications. A way of trying to overcome these difficulties is to use Region-Based Classification (RBC), also referred to as Geographical Object-Based Image Analysis (GEOBIA). RBC methods first aggregate pixels into homogeneous objects, or regions, using a segmentation procedure. Moreover, segmentation is known to be an ill-conditioned problem because it admits multiple solutions, and a small change in the input image, or segmentation parameters, may lead to significant changes in the image partitioning. In this context, this paper proposes and evaluates novel approaches for SAR data classification, which rely on specialized segmentations, and on the combination of partial maps produced by classification ensembles. Such approaches comprise a meta-methodology, in the sense that they are independent from segmentation and classification algorithms, and optimization procedures. Results are shown that improve the classification accuracy from Kappa = 0.4 (baseline method) to a Kappa = 0.77 with the presented method. Another test site presented an improvement from Kappa = 0.36 to a maximum of 0.66 also with radar data.

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