Orbiting Satellite Data Research Articles

Correção Geométrica de Imagens CBERS-4/PAN com Modelos Generalizados Usando como Referência Dados do Sistema Nacional de Gestão Fundiária

As imagens orbitais vêm sendo amplamente empregadas em diversas aplicações no contexto de observação da Terra, as quais exigem diferentes níveis de detalhamento e de acurácia posicional. O Programa CBERS (China–Brazil Earth Resources Satellite Program) originou-se de uma parceria entre Brasil e China no setor técnico-científico espacial. O satélite CBERS-4 é o quinto satélite do Programa CBERS e contém o sensor PAN, que coleta imagens pancromáticas com elemento de resolução espacial (GSD – Ground Sample Distance) de 5 m. Os estudos relacionados à análise da confiabilidade posicional e correção geométrica de imagens CBERS-4 ainda são limitados. Estudos prévios com imagens CBERS-4 PAN com diferentes níveis de processamento indicam deslocamentos posicionais significativos das imagens georreferenciadas, disponibilizadas pelo INPE (Instituto Nacional de Pesquisas Espaciais), incompatíveis com o seu GSD. Nesse sentido, o objetivo desse trabalho consistiu em investigar a aplicação de modelos matemáticos generalizados na correção geométrica de imagens CBERS-4 PAN usando limites das propriedades rurais do INCRA (Instituto Nacional de Colonização e Reforma Agrária) como pontos de controle. Destaca-se que esses limites estão disponíveis para propriedades de todo o Brasil, o que possibilita a replicação do trabalho em nível nacional. Foram consideradas imagens com diferentes níveis de correção prévia (níveis 1 e 2). As imagens de nível 1 são resultantes apenas da aplicação de procedimentos de calibração radiométrica, enquanto as de nível 2 são imagens de nível 1 corrigidas geometricamente a partir de informações de dados orbitais do satélite. Nos experimentos, considerou-se 3 (três) imagens no nível 1 e 1 (uma) imagem no nível 2. Adotaram-se os seguintes modelos generalizados: Polinomiais de ordem 1, 2 e 3; Projetiva e; Thin Plate Spline (TPS). Os modelos generalizados têm por vantagem não exigir o conhecimento dos parâmetros de aquisição do sistema, como a distância focal, o tamanho do sensor, dentre outras. Entretanto, exigem quantidade significativa de pontos de controle com distribuição uniforme ao longo da imagem. Para o processo de correção geométrica utilizou-se diferentes configurações de pontos de controle (30, 25, 20, 15 e 10) coincidentes com os limites das propriedades rurais georreferenciadas no Estado de Mato Grosso do Sul, que apresentam acurácia superior a 50 cm. A validação da correção geométrica foi realizada a partir do REQM (Raiz quadrado do Erro Quadrático Médio) nos pontos de verificação. A transformação Polinomial de ordem 1 apresentou valores elevados (maior que 10 GSD – 50 metros) de REMQ quando comparado aos demais modelos matemáticos, mesmo considerando 30 pontos de controle. O modelo Polinomial de ordem 2 apresentou comportamento mais consistente se comparado aos demais modelos. Mesmo ao considerar apenas 10 GCP apresentou REQM entre 1 e 2 GSD. Nesse modelo não há melhora significativa nos resultados mesmo aumentando a quantidade de pontos de controle. Nos demais modelos (TPS, Projetiva e Polinomial de ordem 3), verificou-se um aumento significativo no REQM ao se reduzir a quantidade de pontos. As imagens utilizadas nesse trabalho recobrem parte do Estado de Mato Grosso do Sul, o qual engloba a maior parte do Pantanal, considerado patrimônio natural da humanidade. Essas imagens orbitais, portanto, podem contribuir para o mapeamento e monitoramento de seus recursos naturais e, consequentemente, na proteção desse patrimônio.

The Research of Low Earth Orbit Prediction of Satellite Based on Deep Neural Network

Satellite orbit prediction is a basic requirement in satellite applications. The current orbit prediction mainly depends on the dynamic model. Because of the limitations of the detection equipment and the satellite orbit data cannot be updated in time, which cause the dynamical model long-term orbit divergence to be serious. Using deep neural network as a method of orbit prediction which can predict the future data by training the satellite orbit data and grasp the implicit relationship between the data. The neural network model is optimized and the prediction data is compared with the actual data. The error of 20 days forecast is reduced to 2km, which improves the accuracy of neural network forecasting satellite orbit.

Surface albedo from the geostationary Communication, Ocean and Meteorological Satellite (COMS)/Meteorological Imager (MI) observation system

The surface albedo is an essential climate variable that is considered in many applications used for predicting climate and understanding the mechanisms of climate change. In this study, surface albedo was estimated using a bidirectional reflectance distribution function model based on Communication, Ocean and Meteorological Satellite/Meteorological Imager data. Geostationary orbiting satellite data are suitable for a level 2 product like albedo, which requires a synthetic process to estimate. The authors modified established methods to consider the geometry of the solar-surface-sensor of COMS/MI. Of note, the viewing zenith angle term was removed from the kernel integration used for estimating spectral albedo. Finally, the spectral (narrow) albedo was converted into the broadband albedo with shortwave length (approximately 0.3–2.5 μm). This study determined conversion coefficients using only one spectral albedo of visible channel. The estimated albedo had a relatively high correlation with Satellite Pour l’Observation de la Terre/Vegetation and low unweighted error values specific for land types or times. The validation results show that estimated albedo has a root mean square error of 0.0134 at Jeju flux site that indicates accuracy similar to that of other satellite-based products.

An adaptive calibration and beamforming technique for a GEO satellite data relay

SummaryHigh throughput data links from low Earth orbit satellites through a geostationary orbit satellite data relay have been proposed to increase the available contact times to ground stations. Accurate antenna beam pointing and tracking of moving targets are key requirements for the relay satellite. In this work, we propose an adaptive calibration and beamforming methodology on the basis of least mean squares, which is suitable for a geostationary orbit data relay. The target system consists of the combination of a high gain reflector fed by a digitally steerable patch antenna array. The proposed method is first presented by numerical cosimulation of the antenna and the calibration algorithm. The results are then validated in an outdoor experimental setup with all digital signal processing implemented in a field‐programmable gate array. We demonstrate the tracking ability and pointing performance of the digitally enhanced reflector antenna with gain fluctuations smaller than 3 dB over a field of view of at least 2,5°. The demonstrated performance shows that the digitally enhanced reflector antenna is a suitable candidate for long‐distance space communications.

Sea-State Observation Using Reflected BeiDou GEO Signals in Frequency Domain

This letter focuses on exploiting parameters, including peak power spectral density (PSD), integrated power, mean frequency, and spectrum width of reflected BeiDou signals in the frequency domain, to retrieve wind speed. The PSD of reflected signals is estimated after choosing proper parameters of the Welch method. Then, the features of PSD are illustrated, and a method is proposed based on fitting estimated PSD with a Gaussian function to evaluate the aforementioned PSD parameters. The estimated parameters of collected BeiDou medium earth orbit (MEO)/inclined geosynchronous satellite orbit (IGSO) and geostationary orbit (GEO) data are fitted with in situ wind speed using polynomial. Fitting results show that the peak PSD, mean frequency, and spectrum width of reflected signals from GEO have more evident dependence on wind speed, compared with MEO/IGSO. To obtain the most accurate results, the impact of delay used in lagging direct replica to align reflected signals is analyzed. Results show that regardless of delay locating within the interval of $[\tau_{0}-\tau_{c},\tau_{0}+\tau_{c}]$ , the better root-mean-square error (rmse) of less than 1.7 m/s and the larger coefficient of determination over 0.8 can be obtained by retrieving from the spectrum width, compared with peak PSD and mean frequency, whose optimal results, with rmse values of 2.03 and 1.70 m/s and coefficient of determination values of 0.73 and 0.81, are obtained as delay is $\tau_{0}-0.85\tau_{c}$ and $\tau_{0}+0.9\tau_{c}$ , respectively, where $\tau_{0}$ is the delay of specular reflection, and $\tau_{c}$ is the length of the B1 code.

Thermospheric mass density measurement from precise orbit ephemeris

Atmospheric drag, which can be inferred from orbit information of low-Earth orbiting (LEO) satellites, provides a direct means of measuring mass density. The temporal resolution of derived mass density could be in the range from minutes to days, depending on the precision of the satellite orbit data. This paper presents two methods potentially being able to estimate thermosphere mass density from precise obit ephemeris with high temporal resolution. One method is based on the drag perturbation equation of the semi-major axis and the temporal resolution of retrieved density could be 150 s for CHAMP satellite. Another method generates corrections to densities computed from a baseline density model through a Kalman filter orbit drag coefficient determination (KFOD) process and the temporal resolution of derived density could be as high as 30 s for CHAMP satellite. The densities estimated from these two methods are compared with densities obtained from accelerometer data of CHAMP satellite. When the accelerometer data based densities are used as reference values, the mean relative accuracy of the densities derived from precision orbit data using the two methods is within approximately 10%. An application of the derived densities shows that the derived densities can reduce orbit predication errors.

Analysis of Mineral Compositions and Crater Morphology on the Moon surface using Moon Orbital Satellite Data

Abstract Analysing vertical and lateral distribution of minerals within an impact crater on lunar surface would aid in understanding the crustal compositions to a larger extent and provides clue about geological evolution of the Moon. The Chandrayaan-1 Moon Mineralogy Mapper (M3) and Lunar Reconnaissance Orbiter Camera (LROC) data have high spectral and spatial resolutions, which help in identifying the mineral compositions and morphological features of impact crater. Here we analyse mineral compositions and their correlations with crater morphology using M3 and LROC satellite data of Eijkman impact cater in SouthPole Atiken (SPA) basin. The result shows that low-Ca pyroxene (LCP) dominant rocks are identified on Central Peak (CP), Crater Floor (CF), Crater Wall (CW) and Crater Rim (CR). An olivine dominant rock is detected on the CW. Fe-Mg-spinel lithological unit is observed on the CF. The results implicate that, (i) Low-Ca pyroxene minerals could be from the lower crust during SPA main event; (ii) Presence of olivine and Fe-Mg-spinel lithology on the surface could be a later stage mafic intrusions or the lower-crustal material exposed on the surface due to major impacts.

Evidence for stratospheric sudden warming effects on the upper thermosphere derived from satellite orbital decay data during 1967–2013

AbstractWe investigate possible impact of stratospheric sudden warmings (SSWs) on the thermosphere by using long‐term data of the global average thermospheric total mass density derived from satellite orbital drag during 1967–2013. Residuals are analyzed between the data and empirical Global Average Mass Density Model (GAMDM) that takes into account density variability due to solar activity, season, geomagnetic activity, and long‐term trend. A superposed epoch analysis of 37 SSW events reveals a density reduction of 3–7% at 250–575 km around the time of maximum polar vortex weakening. The relative density perturbation is found to be greater at higher altitudes. The temperature perturbation is estimated to be −7.0 K at 400 km. We show that the density reduction can arise from enhanced wave forcing from the lower atmosphere.

A method for estimating hourly photosynthetically active radiation (PAR) in China by combining geostationary and polar-orbiting satellite data

Photosynthetically active radiation (PAR) is an important parameter in ecosystem and land surface models. PAR represents the amount of solar radiation in the spectral range of 400–700nm that travels through the atmosphere to the top of the vegetation canopy. In recent years, various methods using different input data to estimate PAR and produce different PAR products have been developed. However, most of the algorithms used in these state-of-the-art studies have not fully compensated for the low spatial and temporal resolution of the data, which affects the accuracy of the PAR estimates. In this study, we have developed a method for estimating hourly PAR based on a combination of geostationary and polar-orbiting satellite data. The Multifunctional Transport Satellite (MTSAT) was selected to retrieve cloud optical depth (COD) with a higher spatial resolution, and the polar orbit satellite data of the Moderate Resolution Imaging Spectroradiometer (MODIS) products were used to derive surface parameters based on multispectral characteristics. A look-up table was established by the Second Simulation of a Satellite Signal in the Solar Spectrum-Vector (6SV) model and the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model consisting the following parameters: solar zenith angle, total water vapor, total ozone column, aerosol optical depth (AOD), COD, surface elevation, surface albedo and PAR. The instantaneous PAR was linearly interpolated from the input data for the selected parameters and the look-up table. The root mean square error (RMSE) between the estimated and observed instantaneous PAR at the Huailai station was 45.72W/m2 for all sky conditions. The RMSE between the estimated and observed daily PAR at the meteorological stations was 17% in the eastern regions of China. The mean bias error (MBE) was between −2.83 and 32.43W/m2 for the Tibetan Plateau. These results indicated that the proposed method can significantly improve the accuracy of PAR estimates and can be used to produce PAR products with high spatial and temporal resolution. However, the method requires further improvement, especially with respect to cloudy conditions.

Altitude and solar activity dependence of 1967–2005 thermospheric density trends derived from orbital drag

AbstractWe examine 1967–2005 thermospheric mass density trends (as well as 1967–2013 trends) derived from satellite orbit data, as a function of altitude, solar flux, and geomagnetic activity. At 400 km altitude, the estimated 1967–2005 trend is −2.0 ± 0.5% per decade. The estimated trends become increasingly negative with increasing height between 250 and 575 km, suggesting an exospheric temperature trend of −1 to −2 K per decade, which is much smaller than temperature trends that have been inferred from ground‐based incoherent scatter radar measurements. The orbit‐derived trend height profiles are in good agreement with model simulations of the enhanced cooling that results from increasing concentration of CO2 in the mesosphere and lower thermosphere. In contrast to earlier results, the solar flux dependence of the estimated trends is weak, relative to the trend uncertainty. There is some indication that the trends may be stronger during very low geomagnetic activity conditions. Estimation of the solar flux and geomagnetic activity dependence of the trends is complicated by monotonic decreases in these drivers over the past four solar minima together with the CO2 increase, all of which drive interminima decreases in density.

An Adaptive Approach of Satellite Baseline Estimation in InSAR

Baseline is an important parameter of radar interferometry. Generally, it can be estimated by satellite orbital data or ground control points. In this paper, an adaptive method is proposed to estimate it with combination satellite orbital data, and the accuracy of baseline estimated can be improved without ground control points; actual data of ERS and ENVISAT ASAR have been used in algorithm development and the final obtained elevation shows that the precise orbit data is more accurate than original orbit data in estimating baseline.

A spherical harmonic model of the lithospheric magnetic field of Mars

AbstractWe present a model of the lithospheric magnetic field of Mars which is based on Mars Global Surveyor orbiting satellite data and represented by an expansion of spherical harmonic (SH) functions up to degree and order 110. Several techniques were applied in order to obtain a reliable and well‐resolved model of the Martian lithospheric magnetic field: A modified Huber‐Norm was used to properly treat data outliers, the mapping phase orbit data was weighted based on an a priori analysis of the data, and static external fields were treated by a joint inversion of external and internal fields. Further, temporal variabilities in the data which lead to unrealistically strong anomalies were considered as noise and handled by additionally minimizing a measure of the horizontal gradient of the vertically down internal field component at surface altitude. Here we use an iteratively reweighted least squares algorithm to approach an absolute measure (L1 norm), allowing for a better representation of strong localized magnetic anomalies as compared to the conventional least squares measure (L2 norm). The resulting model reproduces all known characteristics of the Martian lithospheric field and shows a rich level of detail. It is characterized by a low level of noise and robust when downward continued to the surface. We show how these properties can help to improve the knowledge of the Martian past and present magnetic field by investigating magnetic signatures associated with impacts and volcanoes. Additionally, we present some previously undescribed isolated anomalies, which can be used to determine paleopole positions and magnetization strengths.

The effect of spatial truncation error on variance of gravity anomalies derived from inversion of satellite orbital and gradiometric data

The spatial truncation error (STE) is a significant systematic error in the integral inversion of satellite gradiometric and orbital data to gravity anomalies at sea level. In order to reduce the effect of STE, a larger area than the desired one is considered in the inversion process, but the anomalies located in its central part are selected as the final results. The STE influences the variance of the results as well because the residual vector, which is contaminated with STE, is used for its estimation. The situation is even more complicated in variance component estimation because of its iterative nature. In this paper, we present a strategy to reduce the effect of STE on the a posteriori variance factor and the variance components for inversion of satellite orbital and gradiometric data to gravity anomalies at sea level. The idea is to define two windowing matrices for reducing this error from the estimated residuals and anomalies. Our simulation studies over Fennoscandia show that the differences between the 0.5°×0.5° gravity anomalies obtained from orbital data and an existing gravity model have standard deviation (STD) and root mean squared error (RMSE) of 10.9 and 12.1mGal, respectively, and those obtained from gradiometric data have 7.9 and 10.1 in the same units. In the case that they are combined using windowed variance components the STD and RMSE become 6.1 and 8.4mGal. Also, the mean value of the estimated RMSE after using the windowed variances is in agreement with the RMSE of the differences between the estimated anomalies and those obtained from the gravity model.

Single-frequency Ionosphere-free Precise Point Positioning Using Combined GPS and GLONASS Observations

Single-frequency Precise Point Positioning (PPP) using a Global Navigation Satellite System (GNSS) has been attracting increasing interest in recent years due to its low cost and large number of users. Currently, the single-frequency PPP technique is mainly implemented using GPS observations. In order to improve the positioning accuracy and reduce the convergence time, we propose the combined GPS/GLONASS Single-Frequency (GGSF) PPP approach. The approach is based on the GRoup And PHase Ionospheric Correction (GRAPHIC) to remove the ionospheric effect. The performance of the GGSF PPP was tested using both static and kinematic datasets as well as different types of precise satellite orbit and clock correction data, and compared with GPS-only and GLONASS-only PPP solutions. The results show that the GGSF PPP accuracy degrades by a few centimetres using rapid/ultra-rapid products compared with final products. For the static GGSF PPP, the position filter typically converges at 71, 33 and 59 minutes in the East, North and Up directions, respectively. The corresponding positioning accuracies are 0·057, 0·028 and 0·121 m in the East, North and Up directions. Both positioning accuracy and convergence time have been improved by approximately 30% in comparison to the results from GPS-only or GLONASS-only single-frequency PPP. A kinematic GGSF PPP test was conducted and the results illustrate even more significant benefits of increased accuracy and reliability of PPP solutions by integrating GPS and GLONASS signals.

Orbit determination and time synchronization for a GEO/IGSO satellite navigation constellation with regional tracking network

Aiming at regional services, the space segment of COMPASS (Phase I) satellite navigation system is a constellation of Geostationary Earth Orbit (GEO), Inclined Geostationary Earth Orbit (IGSO) and Medium Earth Orbit (MEO) satellites. Precise orbit determination (POD) for the satellites is limited by the geographic distribution of regional tracking stations. Independent time synchronization (TS) system is developed to supplement the regional tracking network, and satellite clock errors and orbit data may be obtained by simultaneously processing both tracking data and TS data. Consequently, inconsistency between tracking system and TS system caused by remaining instrumental errors not calibrated may decrease navigation accuracy. On the other hand, POD for the mixed constellation of GEO/IGSO/MEO with the regional tracking network leads to parameter estimations that are highly correlated. Notorious example of correlation is found between GEO’s orbital elements and its clock errors. We estimate orbital elements and clock errors for a 3GEO+2IGSO constellation in this study using a multi-satellite precise orbit determination (MPOD) strategy, with which clock error elimination algorithm is applied to separate orbital and clock estimates to improve numerical efficiency. Satellite Laser Ranging (SLR) data are used to evaluate User Ranging Error (URE), which is the orbital error projected on a receiver’s line-of-sight direction. Two-way radio-wave time transfer measurements are used to evaluate clock errors. Experimenting with data from the regional tracking network, we conclude that the fitting of code data is better than 1 m in terms of Root-Mean-Square (RMS), and fitting of carrier phase is better than 1 cm. For orbital evaluation, difference between computed receiver-satellite ranging based on estimated orbits and SLR measurements is better than 1 m (RMS). For clock estimates evaluation, 2-hour linear-fitting shows that the satellite clock rates are about 1.E-10 s/s, while receiver clock rates are about 1×10−13–1×10−12 s/s. For the 72-hour POD experiment, the average differences between POD satellite clock rates estimates and clock measurements based on TS system are about 1×10−13 s/s, and for receiver clock rates, the differences are about 1×10−15 s/s.

Comment on “Variations of tropical upper tropospheric clouds with sea surface temperature and implications for radiative effects” by H. Su et al.

Using TRMM VIRS data, we attempt to replicate the analysis made by Su et al. (2008) to quantify the effect of methodological choices on the magnitude of the observed correlations between upper‐level cloud cover and SST. Using brightness temperature thresholds to identify upper‐level cloud, we recover a relatively small change in the normalized area of cirrus clouds with SST (∼−6%/K compared to ∼−2%/K found by Su et al. (2008)). We discuss the effect of several methodological choices on the magnitude of the signal, namely, the classification of cloudy regions into convective updrafts and anvil, the use of cloud weighted SST, and the truncation and sampling error of the orbital satellite data with respect to the evolution of mesoscale convective systems. Accounting for some of these methodological differences could resolve the discrepancy between the weak signal documented by Su et al. (2008) and the stronger signal documented originally by Lindzen et al. (2001) and others, including the results reported in this comment.

Satellite Remote Sensing and Mesoscale Modeling of the 2007 Georgia/Florida Fires

During April and May 2007, several hundred fires burned uncontrollably in Georgia and Florida. The smoke from these fire events were visible throughout the Southeastern United States and had a major impact on particulate matter (PM) air quality near the surface. In this study, we show the strength of polar orbiting and geostationary satellite data in capturing the spatial distribution and diurnal variability of columnar smoke aerosol optical depth from these fires. We quantitatively evaluate PM air quality from satellites and ground-based monitors, near and far away (> 300 km) from fire source regions. We also show the changes in organic carbon concentrations (a tracer for smoke aerosols) before, during and after these fire events. Finally, we use fire locations and emissions retrieved and estimated from satellite observations as input to a regional mesoscale transport model to forecast the spatial distribution of aerosols and their impact on PM air quality. During the fire events, near the source regions, total column 550 nm aerosol optical thickness (AOT) exceeded 1.0 on several days and ground-based PM2.5 mass (particles less than 2.5 mum in aerodynamic diameter) reached unhealthy levels ( > 65.5 mug m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> ). Since the aerosols were reasonably well mixed in the first 1-2 km (as estimated from meteorology), the column AOT values derived from both geostationary and polar orbiting satellites and the surface PM2.5 were well correlated (linear correlation coefficient, r > 0.7). Several hundred miles away from the fire sources, in Birmingham, AL, the impact of the fires were also seen through the high AOT's and PM2.5 values. Correspondingly, PM2.5 mass due to organic carbon obtained from ground-based monitors showed a three fold increase during fire events when compared to background values. Satellite data were especially useful in capturing PM2.5 air quality in areas where there were no ground-based monitors. Although the mesoscale transport model captured the timing and location of aerosols, when compared to observations, the simulated mass concentrations are underestimated by nearly 70% due to various reasons including uncertainties in fire emission estimates, lack of chemistry in the model, and assumptions on vertical distribution of aerosols. Satellite products such as AOT, fire locations, and emissions from space-borne sensors are becoming a vital tool for assessing extreme events such as fires, smoke, and particulate matter air quality.

Flight performance analysis of GRACE K-band ranging instrument with simulation data

A dual one-way ranging (DOWR) system provides very high accuracy range measurements between two satellites. The GRACE satellite mission implements the DOWR, called KBR (K-band ranging), to measure very small inter-satellite range change in order to map the Earth gravity field. The flight performance of the KBR is analyzed by using a hybrid software simulator that incorporates actual satellite orbit data into a comprehensive KBR simulator, which was earlier used for computing the GRACE baseline accuracy. Three types of experiments were performed. First is the comparison of the flight data with the simulated data in spectral domain. Second is the comparison of double differenced noise level. Third is the comparison of the range-rate difference with GPS clock estimates. The analysis shows a good agreement with the simulation model except some excessive high frequency noise, e.g. 10 −4 m/√Hz at 0.1 Hz. The range-rate difference shows 0.003 cyc/s discrepancy with the clock estimates. These analyses are helpful to refine the DOWR simulation model and can be benefit to future DOWR instrument development.

Development of a virtual active fire product for Africa through a synthesis of geostationary and polar orbiting satellite data

We explore the ability to enhance landscape fire detection and characterization by constructing a ‘virtual’ fire product from a synthesis of geostationary and polar orbiting satellite data. Active fire pixels detected by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) and the Moderate Resolution Imaging Spectroradiometer (MODIS) were spatially and temporally collated across Africa between February 2004 and January 2005. Coincident fire pixels detected by SEVIRI and MODIS were used to populate an empirical database of frequency density (f-D) distributions of fire radiative power (FRP). Frequency density distributions of FRP measured by SEVIRI at 5.0° grid cell resolution and 15-minute temporal resolution were then cross referenced in the database to a set of counterpart f-D distributions of FRP measured by MODIS. This procedure resulted in the first generation of a ‘virtual’ fire product that exhibits the full continental coverage and high temporal resolution of SEVIRI whilst quantifying fire pixel counts and FRP with accuracies approaching those of MODIS. Diurnal cycles extracted from the virtual fire product indicate that SEVIRI measures a greater proportion of the active fire pixels and FRP potentially detectable by MODIS during the day due to the increased prevalence and stronger radiant contribution of highly energetic fire pixels. On a daily basis (sample size n = 365) the peak magnitude in the diurnal cycle of the virtual FRP occurred within the same 15-minute timeslot as in the native SEVIRI fire product. Continental-scale ignition and extinction events, however, were detected on average 44 min earlier (standard deviation s.d. = 40 min) and 137 min later (s.d. = 92 min), respectively. It is anticipated that the methodology developed here can be used to cross-calibrate active fire products between a variety of different satellite platforms.

Influence of the convection electric field models on predicted plasmapause positions during magnetic storms

In the present work, we determine how three well documented models of the magnetospheric electric field, and two different mechanisms proposed for the formation of the plasmapause influence the radial distance, the shape and the evolution of the plasmapause during the geomagnetic storms of 28 October 2001 and of 17 April 2002. The convection electric field models considered are: McIlwain's E5D electric field model, Volland‐Stern's model, and Weimer's statistical model compiled from low‐Earth orbit satellite data. The mechanisms for the formation of the plasmapause to be tested are: (1) the MHD theory where the plasmapause should correspond to the last‐closed‐equipotential (LCE) or last‐closed‐streamline (LCS), if the E‐field distribution is stationary or time‐dependent respectively; (2) the interchange mechanism where the plasmapause corresponds to streamlines tangent to a Zero‐Parallel‐Force surface where the field‐aligned plasma distribution becomes convectively unstable during enhancements of the E‐field intensity in the nightside local time sector. The results of the different time dependent simulations are compared with concomitant EUV/IMAGE observations when available. The plasmatails or plumes observed after both selected geomagnetic storms are predicted in all simulations and for all E‐field models. However, their shapes are quite different depending on the E‐field models and the mechanisms that are used. Despite the partial success of the simulations to reproduce plumes during magnetic storms and substorms, there remains a long way to go before the detailed structures observed in the EUV observations during periods of geomagnetic activity can be accounted for very precisely by the existing E‐field models. Furthermore, it cannot be excluded that the mechanisms currently identified to explain the formation of “Carpenter's knee” during substorm events, will have to be revised or complemented in the cases of geomagnetic storms.