Improving the estimation of zenith dry tropospheric delays using regional surface meteorological data

Global Navigation Satellite Systems (GNSS) are emerging as possible tools for remote sensing high-resolution atmospheric water vapour that improves weather forecasting through numerical weather prediction models. Nowadays, the GNSS-derived tropospheric zenith total delay (ZTD), comprising zenith dry delay (ZDD) and zenith wet delay (ZWD), is achievable with sub-centimetre accuracy. However, if no representative near-site meteorological information is available, the quality of the ZDD derived from tropospheric models is degraded, leading to inaccurate estimation of the water vapour component ZWD as difference between ZTD and ZDD. On the basis of freely accessible regional surface meteorological data, this paper proposes a height-dependent linear correction model for a priori ZDD. By applying the ordinary least-squares estimation (OLSE), bootstrapping (BOOT), and leave-one-out cross-validation (CROS) methods, the model parameters are estimated and analysed with respect to outlier detection. The model validation is carried out using GNSS stations with near-site meteorological measurements. The results verify the efficiency of the proposed ZDD correction model, showing a significant reduction in the mean bias from several centimetres to about 5 mm. The OLSE method enables a fast computation, while the CROS procedure allows for outlier detection. All the three methods produce consistent results after outlier elimination, which improves the regression quality by about 20% and the model accuracy by up to 30%.     

Inversion of satellite gradiometry data using statistically modified integral formulas for local gravity field recovery

The satellite gravity gradiometric data can be used directly to recover the gravity anomaly at sea level using inversion of integral formulas. This approach suffers by the spatial truncation errors of the integrals, but these errors can be reduced by modifying the formulas. It allows us to consider smaller coverage of the satellite data over the region of recovery. In this study, we consider the second-order radial derivative (SORD) of disturbing potential (T_rr) and determine the gravity anomaly with a resolution of 1° × 1° at sea level by inverting the statistically modified version of SORD of extended Stokes’ formula. Also we investigate the effect of the spatial truncation error on the quality of inversion considering noise of T_rr. The numerical investigations show satisfactory results when the area of T_rr coverage is the same with that of the gravity anomaly and the integral formula is modified by the biased least-squares modification. The error of recovery will be about 6 mGal after removing the regularization bias in the presence of 1 mE noise in T_rr measured on the orbit.     

Fire risk assessment using satellite data

Forest fires are one of the most important sources of land degradation that lead to deforestation and desertification processes. Risk indexes obtained by means of satellite measurements have widely improved the forecasting and monitoring of fire and its impact over the global ecosystem in an operational manner. Using Advanced Very High Resolution Radiometer (AVHRR) data and the Normalized Difference Vegetation Index (NDVI) as a key variable, we have defined a new risk index in which a static map of fire probability is modulated with the NDVI values. Its usefulness to study the dynamic of fire risk over a test area that has been affected by fire in the past years is tested. The potential application of these tools for fire management and its suitability to be provided as an end product to the forest services and cooperators aiding in that sense is also assessed.     

Exploring for natural gas using reflectance spectra of surface soils

Reflectance spectra in the visible and near-infrared wavelengths provide a rapid and inexpensive means for determining the mineralogy of samples and obtaining information on chemical composition. Hydrocarbon microseepage theory establishes a cause-and-effect relation between oil and gas reservoirs and some special surface anomalies, which mainly include surface hydrocarbon microseepage and related alterations. Therefore, we can explore for oil, gas by determining reflectance spectra of surface anomalies. This idea has been applied to the R&D project of exploring for natural gas in Qinghai province of China using NASA EO-1 satellite with the Hyperion sensor (June 2005 to June 2006). In this project, in order to improve the accuracy of exploration targets of natural gas mapped in the field studied, an integrated practical system of exploration of oil and gas was built by the analysis of not only hyperspectral remote sensing data but also data provided from field work. In this paper, our efforts were focused on the analysis of the 799 reflectance spectra provided from the field work. In order to properly define the typical form of hydrocarbon microseepage with spectroscopy and fulfill the data analysis, it was necessary to build a spectral model. In this spectral model the most important features of hydrocarbon microseepage in the surface of our study area, i.e., diagnostic spectral macroscopic features and diagnostic spectral absorption features, were proposed and extracted, respectively. The distribution of coexisting anomalies, which results from both alteration minerals and hydrocarbons, is estimated by the diagnostic macroscopic features mainly using Spectral Angle Mapper (SAM) classifier. On the other hand, the diagnostic absorption features of two main absorption bands presented abundant local information, based on deep analysis of which, we are able to map the anomalies of alteration minerals and hydrocarbons, respectively. Additionally, a general framework of analysis and key classification algorithms applied to the Hyperion data have been introduced briefly. In our work, three exploration targets of natural gas were identified from the study area which covers 2100 km². In the three exploration targets, three wildcats have been drilled by China National Petroleum Corporation (CNPC) since July 2006, and all the three wells have been proven some industrial reserves.     

Modeling urban heat islands in heterogeneous land surface and its correlation with impervious surface area by using night-time ASTER satellite data in highly urbanizing city,Delhi-India

The present study is an assessment and identification of urban heat island (UHI) in the environment of one of the fastest urbanizing city of India, Delhi Metropolis, employing satellite image of ASTER and Landsat 7 ETM+ in the thermal infrared region 3–14 μm. Temporal (2001 and 2005) ASTER datasets were used to analyze the spatial structure of the thermal urban environment subsequently urban heat island (UHI) in relation to the urban surface characteristics and land use/land cover (LULC). The study involves derivation of parameters governing the surface heat fluxes, constructing statistics of ASTER thermal infrared images along with validation through intensive in situ measurements. The average images reveal spatial and temporal variations of land surface temperature (LST) of night-time and distinct microclimatic patterns. Central Business District (CBD) of Delhi, (Connaught Place, a high density built up area), and commercial/industrial areas display heat islands condition with a temperature greater than 4 °C compared to the suburbs. The small increase in surface temperature at city level is mainly attributed to cumulative impact of human activities, changes in LULC pattern and vegetation density. In this study the methodology takes into account spatially-relative surface temperatures and impervious surface fraction value to measure surface UHI intensity between the urban land cover and rural surroundings. Both the spatial and temporal variation in surface temperature associated with impervious surface area (ISA) has been evaluated to assess the effect of urbanization on the local climate.     

Comparison of ground reflectance measurement with satellite derived atmospherically corrected reflectance: A case study over semi-arid landscape

Atmospheric corrections to satellite data are important for comparing multitemporal data sets over tropical regions with variable aerosol loading. In this study, we evaluated the potential of 6S radiative transfer model for atmospheric corrections of IRS-P6 AWiFS satellite data sets, in a semi-arid landscape. Ground measurements of surface reflectance representing different land use/land cover categories were conducted to relate IRS-P6 AWiFS top of atmospheric reflectance. The 6S radiative transfer model was calibrated for local conditions using ground measurements for aerosol optical depth, water vapor and ozone with a sun photometer. Surface reflectance retrieved from 6S code was compared with top of atmosphere (TOA) reflectance and ground based spectroradiometer measurements. Accurate parameterization of the 6S model using measurements of aerosol optical depth, water vapor and ozone plays an important role while comparing ground and satellite derived reflectance measurements.     

Assessment of plant vitality detection through fluorescence and reflectance imagery

Recent studies of the vegetation fluorescence show that it can be successfully used as an intrinsic indicator of plant photosynthetic activity. With respect to the vegetation spectral reflectance, the chlorophyll (Chl) fluorescence is more specific as an observable of basic biophysical processes in the plant cells. Laser induced fluorescence is widely used in near range remote sensing, but it is not suitable for the global monitoring of vegetation. Decades of active fluorometry studies have collected useful information of leaf reaction to natural and anthropogenic stress. Still the passive fluorescence, the one that could be registered from satellite orbit has still to prove its advantage over widely used reflectance signature. The weakness of the signal and the lack of experience with passive fluorescence measurements require extensive technical, theoretical and experimental studies. New imaging fluorometres are to be designed for measuring steady state fluorescence in controlled and natural conditions.

In order to compare reflectance and steady state fluorescence sensitivity to stress impact, a set of experiments have been conducted under controlled illumination conditions in a bio-chamber, designed by the author’s team. The equipment allows plant vitality to be monitored both by passive fluorescence and spectral reflectance imaging. Different types of stress factors (heat and drought stress, acid impact) were investigated to demonstrate equipments ability in monitoring changes of fluorescence signal. Selected fluorescence images of foliage illustrate an early detection of plant dysfunction and the temporal and spatial spreading of the stress impact. Analysis shows that fluorescence imaging of green plants can be developed as a highly effective early warning remote sensing method, which could have application for an ecosystems’ monitoring along with high-spectral reflectance imagery.     

Sensing the Earth’s low ionosphere during solar flares using VLF signals and goes solar X-ray data

An analysis of D-region electron density height profile variations, induced by four isolated solar X-ray flares during period from September 2005 to December 2006, based on the amplitude and the phase delay perturbation of 22.1 kHz signal trace from Skelton (54.72 N, 2.88 W) to Belgrade (44.85 N, 20.38 E), coded GQD, was carried out. Solar flare data were taken from NOAA GOES12 satellite one-minute listings. For VLF data acquisition and recordings at the Institute of Physics, Belgrade, Serbia, the AbsPAL system was used. Starting from LWPCv21 code (Ferguson, 1998), the variations of the Earth-ionosphere waveguide characteristic parameters, sharpness and reflection height, were estimated during the flare conditions. It was found that solar flare events affected the VLF wave propagation in the Earth-ionosphere waveguide by changing the lower ionosphere electron density height profile, in a different way, for different solar flare events.     

Effect of solar activity on the repetitiveness of some meteorological phenomena

In this paper we research the relationship between solar activity and the weather on Earth. This research is based on the assumption that every ejection of magnetic field energy and particles from the Sun (also known as Solar wind) has direct effects on the Earth’s weather. The impact of coronal holes and active regions on cold air advection (cold fronts, precipitation, and temperature decrease on the surface and higher layers) in the Belgrade region (Serbia) was analyzed. Some active regions and coronal holes appear to be in a geo-effective position nearly every 27 days, which is the duration of a solar rotation. A similar period of repetitiveness (27–29 days) of the passage of the cold front, and maximum and minimum temperatures measured at surface and at levels of 850 and 500 hPa were detected. We found that 10–12 days after Solar wind velocity starts significantly increasing, we could expect the passage of a cold front. After eight days, the maximum temperatures in the Belgrade region are measured, and it was found that their minimum values appear after 12–16 days. The maximum amount of precipitation occurs 14 days after Solar wind is observed. A recurring period of nearly 27 days of different phases of development for hurricanes Katrina, Rita and Wilma was found. This analysis confirmed that the intervals of time between two occurrences of some particular meteorological parameter correlate well with Solar wind and A index.     

A surface reflectance correction model to improve the retrieval of MISR aerosol optical depth supported by MODIS data

Combined use of different satellite sensors are known to improve retrievals of aerosol optical depth (AOD). In this study, we propose a new method for retrieving Multi-angle Imaging SpectroRadiometer (MISR) AOD data supported by Moderate Resolution Imaging Spectroradiometer (MODIS) data in Jiangsu Province, China, over the period of 2016–2018 using MODIS L1B, bidirectional reflectance distribution function (BRDF), MISR 1B2T, and ground-measured AOD data. This method is based on the surface reflectance determined by the MODIS V5.2 algorithm. Through the observation angle and spectral conversion between different sensors, the MISR AOD can be obtained. The correlation coefficient (R) and root-mean-square error (RMSE) between the retrieved MISR and ground-measured AOD data varied between different seasons. The accuracy of the MISR AOD retrieval was notably improved after correcting the MISR surface reflectance. Therefore, the method proposed in this study is feasible for the retrieval of MISR AOD supported by MODIS data, and will be applicable to atmospheric environmental monitoring over large areas in the future.     

The atmospheric cosmic- and solar energetic particle radiation environment at aircraft altitudes

Galactic cosmic rays interact with the solar wind, the earth's magnetic field and its atmosphere to produce hadron, lepton and photon fields at aircraft altitudes. In addition to cosmic rays, energetic particles generated by solar activity bombard the earth from time to time. These particles, while less energetic than cosmic rays, also produce radiation fields at aircraft altitudes which have qualitatively the same properties as atmospheric cosmic rays. We have used a code based on transport theory to calculate atmospheric cosmic-ray quantities and compared them with experimental data. Agreement with these data is seen to be good. We have then used this code to calculate equivalent doses to aircraft crews. We have also used the code to calculate radiation doses from several large solar energetic particle events which took place in 1989, including the very large event that occurred on September 29^th and 30^th of that year. The spectra incident on the atmosphere were determined assuming diffusive shock theory.     

Variation of ionospheric electron and ion temperatures during periods of minimum to maximum solar activity by the SROSS-C2 satellite over Indian low and equatorial latitudes

To study the variation of ionospheric electron and ion temperatures with solar activity the data of electron and ion temperatures were recorded with the help of Retarding Potential Analyzer payload aboard Indian SROSS-C2 satellite at an average altitude of ∼500 km. The main focuses of the paper is to see the diurnal, seasonal and latitudinal variations of electron and ion temperatures during periods of minimum to maximum solar activity. The ionospheric temperatures in the topside show strong variations with altitude, latitude, season and solar activity. In present study, the temperature variations with latitude, season and solar activity have been studied at an average altitude ∼500 km. The peak at sunrise has been observed during all seasons, in both electron and ion temperatures. Further, the ionospheric temperatures vary with latitude in day time. The latitudinal variation is more pronounced for low solar activity than for high solar activity.     

Substitution of satellite-based land surface temperature defective data using GSP method

Land surface temperature (LST) as an important environmental variable provides valuable information for earth environmental system modelling. Currently, LST is obtained through satellite thermal sensors at various spatial and temporal resolutions. Although spatially continuous satellite-based LST measurements are intended to overcome the shortcomings of sparse ground-based LST measurements, LST images often contain anomalous values due to the existence of clouds or sensor malfunctioning. The problem becomes more serious where the users deal with high spatial resolution characterized by low temporal resolution. This study examines the capability of a newly developed graph signal processing (GSP) method using two-dimensional single-date thermal data. For this purpose, four Landsat/TIRS datasets are analyzed. The data of five elliptical regions on thermal images are eliminated and then reconstructed through the GSP method and using the LST values of the enclosing rectangles containing the ellipsoids. The results indicate that the temperature variation determined by the GSP method generally conforms to the original image LST values. According to a correlation test conducted on the original image LST and those obtained through the GSP method, the values vary from 58% to 95%, which is an above-the-average rate (RMSE from 0.69 to 2.27). The statistical analysis of the original image LST in both the elliptical regions and the enclosing rectangles containing the ellipsoids indicates that an increase in the variance of LST data causes an increased error in the calculation of temperature by the GSP method, and vice versa. The results of the analysis of variance (ANOVA) and Duncan test indicated that an increase in the number of the non-zero spectral bins would result in increased RMSE values for all the dates and the regions. Moreover, the model errors were significant at the 0.05 level across all the image date and five elliptical study regions. Based on the results, the use of this method is recommended for the reconstruction of LST missing values, where dissimilarity of atmospheric conditions limits the use of other methods that depend on the time series data of various dates and a great deal of data calculation.     

Use of data from meteorological satellites in long-range weather forecasting

In the Soviet Union experiments on obtaining meteorological information by means of man-made Earth's satellites were initiated in 1966 (the “Meteor” meteorological system).Starting with 1975 the launches of the “Meteor-2” updated meteorological satellites of the second generation were carried out. The detailed information about the Soviet meteorological satellite system can be found in [9].Below, the problems concerning the use of satellite data in schemes of long-range weather forecasts are considered. Particular attention is paid to the role of external sources of energy. The role of cloud cover over the oceans is emphasized as a heat influx regulator in the process of absorption radiant solar heat by the ocean. The dynamic and statistical method of ocean heat memory parameterization is stated.     

Investigations on temperature distribution of satellite surfaces affected by solar absorptivity

Based on the Monte Carlo ray-tracing method, the network coefficients of thermal network model describing the radiation heat transfer among satellite surfaces is solved by considering the surface material optical characters. It is superiority to the conventional Gebhart’s method in view of the grey body and the diffuse reflection assumptions. The zone leveling method is used to discrete the governing equations and the solar absorpivity is separated and considered to be an important correction parameter. Effects of the solar incidence round angle, the zenith angle and the ratio of absorpivity to emissivity (RAE) on temperature distribution are numerically simulated and discussed in detail. The higher or the lower the RAE may be lead to the alternative heating and cooling tend with a larger heating or cooling velocity of main body surfaces than the solar array surfaces. Furthermore, maximum temperature of main body is almost larger than solar arrays. Under the same RAE, solar incidence angle make a great effect on the uniform character of temperature distribution.     

Calculations and observations of solar particle enhancements to the radiation environment at aircraft altitudes.

Solar particle events can give greatly enhanced radiation at aircraft altitudes, but are both difficult to predict and to calculate retrospectively. This enhanced radiation can give significant dose to aircrew and greatly increase the rate of single event effects in avionics. Validation of calculations is required but only very few events have been measured in flight. The CREAM detector on Concorde detected the event of 29 September 1989 and also four periods of enhancement during the events of 19-24 October 1989. Instantaneous rates were enhanced by up to a factor ten compared with quiet-time cosmic rays, while flight-averages were enhanced by up to a factor six. Calculations are described for increases in radiation at aircraft altitudes using solar particle spectra in conjunction with Monte Carlo radiation transport codes. In order to obtain solar particle spectra with sufficient accuracy over the required energy range it is necessary to combine space data with measurements from a wide range of geomagnetically dispersed, ground-level neutron monitors. Such spectra have been obtained for 29 September 1989 and 24 October 1989 and these are used to calculate enhancements that are compared with the data from CREAM on Concorde. The effect of cut-off rigidity suppression by geomagnetic activity is shown to be significant. For the largest event on record on 23 February 1956, there are no space data but there are data from a number of ground-level cosmic-ray detectors. Predictions for all events show very steep dependencies on both latitude and altitude. At high latitude and altitude (17 km) calculated increases with respect to cosmic rays are a factor 70 and 500 respectively for 29 September 1989 and 23 February 1956. The levels of radiation for high latitude, subsonic routes are calculated, using London to Los Angeles as an example, and can exceed 1 mSv, which is significantly higher than for Concorde routes from Europe to New York. The sensitivity of the calculations to spectral fitting, geomagnetic activity and other assumptions demonstrates the requirement for widespread carriage of radiation monitors on aircraft.     

Comparison of ANN and MLR models for estimating solar radiation in Turkey using NOAA/AVHRR data

In this paper, the estimation capacities of MLR and ANN are investigated to estimate monthly-average daily SR over Turkey. The satellite data are used for 73 different locations over Turkey. Land surface temperature, altitude, latitude, longitude and month are offered as the input variables for modeling ANN and MLR to get SR. Estimations of SR are evaluated with the meteorological values by using the statistical bases. The obtained results indicated that the ANN model could achieve a satisfactory performance when compared to the MLR model. Moreover, it is understood that more accurate results in estimation of SR are obtained in the use of satellite data, rather than the use of meteorological station data. Finally, the built ANN model is used to estimate the yearly average of daily SR over Turkey. As a result, satellite-based SR map for Turkey is generated.