Temporal Variability of Total Ozone in the Asian Region Inferred from Ground-Based and Satellite Measurement Data

This paper reports investigation data on the temporal variability of total ozone content (TOC) in the Central Asian and Tibet Plateau mountain regions obtained by conventional methods, as well as by spectral, cross-wavelet, and composite analyses. The data of ground-based observation stations located at Huang He, Kunming, and Lake Issyk-Kul, along with the satellite data obtained at SBUV/SBUV2 (SBUV merged total and profile ozone data, Version 8.6) for 1980–2013 and OMI (Ozone Monitoring Instrument) and TOU (Total Ozone Unit) for 2009–2013 have been used. The average relative deviation from the SBUV/SBUV2 data is less than 1% in Kunming and Issyk-Kul for the period of 1980–2013, while the Huang He Station is characterized by an excess of the satellite data over the ground-based information at an average deviation of 2%. According to the Fourier analysis results, the distribution of amplitudes and the periods of TOC oscillations within a range of over 14 months is similar for all series analyzed. Meanwhile, according to the cross-wavelet and composite analyses results, the phase relationships between the series may considerably differ, especially in the periods of 5–7 years. The phase of quasi-decennial oscillations in the Kunming Station is close to the 11-year oscillations of the solar cycle, while in the Huang He and Issyk-Kul stations the TOC variations go ahead of the solar cycle.     

Mapping of ice in the Odden by satellite and airborne remote sensing

A detailed analysis of the ice conditions in the Odden area of the Greenland Sea was carried out using data from active and passive microwave sensors, supplemented by airborne data. The study focuses on the 1992–1993 winter season, the only winter during the period 1993–1995 in which an Odden feature formed. The analysis is structured as a hierarchy of spatial resolutions where the overview is obtained by the DMSP SSM/I microwave radiometers having spatial resolutions in the 15–50 km range. Further details in cloud-free situations are obtained by data from the NOAA advanced very high resolution radiometer, which is a scanner in the visible, near-infrared and thermal infrared range with a resolution of 1.1 km. The finest resolution of 25 m per pixel is obtained from the synthetic aperture radar on the ERS-1 satellite.     

Bayesian classification of the ice cover of the Arctic seas

A classification of sea ice in the Arctic by age (multiyear; first-year; and first-year deformed ice, nilas, etc.) is developed based on the Bayesian approach using satellite radar data and taking into account regional peculiarities of these types of ice for different sectors of the Arctic. Estimations of a priori probabilities for each ice type, which are required for the use of the Bayesian classification, are obtained by the analysis of ice charts in the Arctic seas developed at the AARI in 2008–2013 using satellite data. A posterior probabilities are estimated visually by an expert. Types of sea ice distinguished by the expert on satellite images make it possible to create sample values of the radar-scattering cross section (RSCS). Examples of the proposed Bayesian classification of ice in the Laptev Sea according to Envisat satellite data are given.     

Brown Carbon and Black Carbon in the Smoky Atmosphere during Boreal Forest Fires

We have investigated the variability of smoke aerosol absorbing ability with variations in the content of brown carbon (BrC) and black carbon (BC). Using monitoring data on radiative characteristics of smoke aerosol at AERONET stations and the spatial distribution of aerosol optical depth (AOD) obtained by the MODIS spectrometer (Terra satellite), we have detected large-scale smokes during boreal forest fires in Russia and Canada (1995–2012). The spatial distribution (50°–70° N, 95°–125° W) and temporal variability (at AERONET station Fort McMurray) of AOD during the smoking of a part of Canada in July 2012 have been analyzed. AOD probability distributions for July 14–18, 2012, and an estimate of aerosol radiative forcing of smoke aerosol at the upper boundary of the atmosphere have been obtained. We have proposed a technique for the diagnostics of BrC and BC in smoke aerosol particles from the spectral dependence of the imaginary part of the refractive index. At a wavelength of 440 nm, the contributions of BrC and BC to the smokeaerosol absorbing abitity can be comparable in magnitude. In many cases, the absorption spectra of smoke aerosol can be adequately approximated by either power or exponential functions. The presence of BrC in smoke-aerosol particles highly extends the variety of observed absorption spectra in a smoky atmosphere and spectral dependences of single scattering albedo. In the spectral range of 440–1020 nm, the radiative characteristics of smoke aerosol are largely contributed by its fine mode.     

Determination of the chlorophyll <Emphasis Type="Italic">a</Emphasis> concentration by MODIS-Aqua and VIIRS satellite radiometers in Eastern Arctic and Bering Sea

The waters of the Bering and Chukchi seas, as well as the De Long Strait, are investigated based on the data obtained in August 2013 during the scientific expedition of the Far Eastern Floating University on the research vessel Professor Khlyustin. Chlorophyll a concentrations calculated from MODIS-Aqua and VIIRS satellite data by ocean color and obtained by means of shipboard flow-through fluorometric measurements are comparatively analyzed. Vessel data are corrected for standard spectrophotometric measurements and the vertical depth distribution of phytoplankton. It has been found that, in the waters of the Eastern Arctic, satellite radiometers showed overestimated chlorophyll a concentrations in the upper seawater layer visible from the satellite. This is associated with the additional contribution of colored dissolved organic matter in the sea surface color. In the De Long Strait, satellite measurements incorrectly estimate the depth integrated chlorophyll a concentration, since the bulk of phytoplankton cells at a chlorophyll a concentration of 10–20 g/L is at depths of 25–30 m with luminosity of 5%.     

Interannual Sea Level Variations in the South China Sea Over 1950–2009

Spatial patterns of interannual sea level variations in the South China Sea (SCS) are investigated by analyzing an EOF-based 2-dimensional past sea level reconstruction from 1950 to 2009 and satellite altimetry data from 1993 to 2009. Long-term tide gauge records from 14 selected stations in this region are also used to assess the quality of reconstructed sea levels and determine the rate of sea level along the coastal area. We found that the rising rate of sea levels derived from merged satellite altimetry data during 1993–2009 and past sea level reconstruction over 1950–2009 is about 3.9 ± 0.6 mm/yr and 1.7 ± 0.1 mm/yr, respectively. For the longer period, this rate is not significantly different from the global mean rate (of 1.8 ± 0.3 mm/yr). The interannual mean sea level of the SCS region appears highly correlated with Niño 4 indices (a proxy of El Niño-Southern Oscillation/ENSO), suggesting that the interannual sea level variations over the SCS region is driven by ENSO events. Interpolation of the reconstructed sea level data for 1950–2009 at sites where tide gauge records are of poor quality (either short or gapped) show that sea level along the Chinese coastal area is rising faster than the global mean rate of 1.8 mm/yr. At some sites, the rate is up to 2.5 mm/yr.     

Performance limitations in underwater acoustic telemetry

Performance limitations in digital acoustic telemetry are addressed. Increases in computational capabilities have led to a number of complex but practical solutions aimed at increasing the reliability of acoustic data links. These solutions range from ocean-basin scale data telemetry to video-image transmission at a few hundred yards' distance. The opportunity to implement highly complex tasks in real time on modest hardware is a common factor. The data rates range from 1 to 500 kb/s and are much slower than satellite channels, while acceptable system complexity is higher than virtually any other channel with comparable data throughput. The basic performance bounds are the channel phase stability, available bandwidth, and the channel impulse response fluctuation rate. Phase stability is of particular concern for long-range telemetry, channel fluctuation characteristics drive equalizer, and synchronizer design; the bandwidth limitation is a direct constraint on data rate for a given signaling method     

Monitoring the total atmospheric ozone content using data collected by the Elektro-L Russian geostationary meteorological satellite

The possibility of remotely monitoring the total atmospheric ozone content (TAOC) using data from the multichannel geostationary scanning instrument (MGSI) aboard the Elektro-L no. 1 Russian meteorological satellite is explored. In addition to the MGSI measurements in three channels (8.2–9.2, 9.2–10.2, and 10.2–11.2 μm), data on the vertical temperature distributions in the ozone layer and the temperature and pressure at the underlying terrain level (satellite sensing results or forecast data) are used as additional predictors in the process of TAOC estimation. The TAOC estimates are constructed with the use of a regularized regression algorithm (ridge regression). The learning and check samples are formed using independent TAOC estimates based on the data gathered by the OMI instrument aboard the EOS Aura satellite. Numerical experiments in processing the actual MGSI data gathered over certain periods within the interval from November 2011 to August 2012 reveal the possibility of arranging regular monitoring of the TAOC fields with high spatial and temporal resolutions and an acceptable precision: the absolute value of relative mean deviations and the relative root-mean-square deviations of the estimates based on the MGSI data from the estimates based on the OMI data lie within intervals of 1–2% and 5–7%, respectively, depending on the underlying terrain type.     

渤海海域多源遥感溢油风险评价与长序监测

渤海海域溢油事件频发,所以进行海洋溢油风险时空特征分析,对于开展卫星遥感溢油精确监测具有重要意义.作者采用多源高分辨率卫星遥感数据,提取渤海海域船舶及石油平台两类主要溢油风险源分布状况,结合2015—2020年间渤海海域海上溢油卫星遥感监测结果,分析多种传感器下不同类型溢油的成像特征,通过溢油风险源核密度分析方法,获得...     

Satellite Radiothermovision on Synoptic and Climatically Significant Scales

This paper is focused on the development of a methodological basis for the authors’ approach to the processing of large volumes of satellite radiothermal data, which is known as satellite radiothermovision. A closed scheme for calculating the latent heat flux (and other integral characteristics of the dynamics of geophysical fields) through arbitrary contours (boundaries) has been constructed and mathematically described. The opportunity for working with static, as well as movable and deformable boundaries of arbitrary shape, has been provided. The computational scheme was tested using the example of calculations of the atmospheric advection of the latent heat from the North Atlantics to the Arctic in 2014. Preliminary analysis of the results showed a high potential of the approach when applying it to the study of a wide range of synoptic and climatically significant atmospheric processes of the Earth. Some areas for the further development of the satellite radiothermovision approach are briefly discussed. It is noted that expanding the analysis of the available satellite data to as much data as possible is of considerable importance. Among the immediate prospects is the analysis of large arrays of data already accumulated and processed in terms of the satellite radiothermovision ideology, which are partially presented and continuously updated on a specialized geoportal.     

New Zealand wave climate from satellite observations

Wave data derived from radar altimeters carried on four satellite missions are combined into a wave climatology for New Zealand waters. These data provide extensive observations of wave conditions around New Zealand, where the paucity of measurements has previously hindered definition of the wave climate. The data span the period 1985 to the present with the exception of a 2‐year gap in 1989–91. The spatial distribution of the long‐term mean of significant wave heights (SWH) indicates a strong latitudinal variation in the south‐west Pacific, with values of over 4 m at latitudes of 50–60°S and under 2.5 m towards the tropics. The shadowing of New Zealand is quite marked; a result of the dominant contribution of south‐westerly wave events. The annual range of the mean SWH also varies over the region; within 0.6 m in the north and 1.3 m in the south. A principal component analysis of the monthly anomalies in mean SWH identifies spatial patterns of variation. Some components vary with the local wind more than others suggesting that some anomalies are associated with wind sea and some with swell. Some patterns also appear to vary with the Southern Oscillation Index and can be related to the wind anomalies associated with El Nino events. Frequency distributions of SWH are also determined, and it is noted that in the north of the region the spatial pattern of the high waves differs considerably from the means.     

A study of sea-wave spectra in a wide wavelength range from satellite and in-situ data

The results of studying sea-wave spectra in a wide wavelength range using high resolution (0.5–1.0 m) satellite optical imagery spectra and the results of measurements carried out from an oceanographic platform using string-wave recorders, stereo system, and drifting wave buoys are presented in this paper. The wave spectra retrieved from satellite imagery and sea-truth data have been compared. A comparison has shown the adequacy of the purposely developed retrieval methods. Power approximation indices for spatial spectra in the 0.04–5.0-m wavelength range have been found. It has been shown that the wave spectra measured experimentally by satellite-based and in-situ methods best approximate the Toba spectrum.     

Evaluation of vertical crustal movements and sea level changes around Greenland from GPS and tide gauge observations

To better monitor the vertical crustal movements and sea level changes around Greenland, multiple data sources were used in this paper, including global positioning system(GPS), tide gauge, satellite gravimetry, satellite altimetry, glacial isostatic adjustment(GIA). First, the observations of more than 50 GPS stations from the international GNSS service(IGS) and Greenland network(GNET) in 2007–2018 were processed and the common mode error(CME) was eliminated with using the principal component analysis(PCA). The results show that all GPS stations show an uplift trend and the stations in southern Greenland have a higher vertical speed. Second, by deducting the influence of GIA, the impact of current Gr IS mass changes on GPS stations was analysed, and the GIA-corrected vertical velocity of the GPS is in good agreement with the vertical velocity obtained by gravity recovery and climate experiment(GRACE). Third, the absolute sea level change around Greenland at 4 gauge stations was obtained by combining relative sea level derived from tide gauge observations and crustal uplift rates derived from GPS observations, and was validated by sea level products of satellite altimetry. The results show that although the mass loss of Gr IS can cause considerable global sea level rise, eustatic movements along the coasts of Greenland are quite complex under different mechanisms of sea level changes.     

Multispectral satellite imaging system aboard the Meteor-M No. 1 spacecraft: Three years in orbit

The multispectral satellite imaging system (MSIS) aboard the Meteor-M No. 1 spacecraft (SC) has surveyed the territory of Russia and neighboring countries in three-bands of the visible and near-IR ranges with a resolution of 60/120 m in a swath of more than 900 km for three years. The MSIS data, supple-mented by synchronous navigational information, are automatically received, pipeline processed, archived, and cataloged at ground-based receiving stations in Moscow, Novosibirsk, and Khabarovsk. These data are used to solve a wide range of land-use, environmental, and emergency monitoring problems; assess ice situations in seas, rivers, and lakes; etc. The further development of imaging instruments for operational monitoring is aimed at increasing its resolution to 20–30 m in a simultaneously expanded swath of 1600–1800 km, allowing for imaging of most of the territory of Russia with inter-orbit overlapping.     

Reconstruction of the surface temperature fields according to the fragmentary data of remote sensing

We propose a gap-filling method for the data of remote sensing of the hydrophysical and biological characteristics of the water surface. The proposed method of reconstruction is based on the representation of the fields of surface characteristics as the sums of certain numbers of empirical orthogonal functions (EOF) making the largest contributions to the total variance of the field. According to the fragmentary data obtained as a result of processing of the satellite images for the summer season, we construct estimates of the mean field and of the four-dimensional space covariance function of the surface temperature of the Black Sea. The coefficients of expansion are computed by the method of least squares or determined with the help of a genetic searching algorithm. The results of numerical experiments show that the proposed method is quite promising for applications in the problems of gap filling in the available satellite data.     

Inversion of the three-dimensional temperature structure of mesoscale eddies in the Northwest Pacific based on deep learning

Mesoscale eddies, which are mainly caused by baroclinic effects in the ocean, are common oceanic phenomena in the Northwest Pacific Ocean and play very important roles in ocean circulation, ocean dynamics and material energy transport. The temperature structure of mesoscale eddies will lead to variations in oceanic baroclinity, which can be reflected in the sea level anomaly (SLA). Deep learning can automatically extract different features of data at multiple levels without human intervention, and find the hidden relations of data. Therefore, combining satellite SLA data with deep learning is a good way to invert the temperature structure inside eddies. This paper proposes a deep learning algorithm, eddy convolution neural network (ECN), which can train the relationship between mesoscale eddy temperature anomalies and sea level anomalies (SLAs), relying on the powerful feature extraction and learning abilities of convolutional neural networks. After obtaining the temperature structure model through ECN, according to climatic temperature data, the temperature structure of mesoscale eddies in the Northwest Pacific is retrieved with a spatial resolution of 0.25° at depths of 0–1 000 m. The overall accuracy of the ECN temperature structure is verified using Argo profiles at the locations of cyclonic and anticyclonic eddies during 2015–2016. Taking 10% error as the acceptable threshold of accuracy, 89.64% and 87.25% of the cyclonic and anticyclonic eddy temperature structures obtained by ECN met the threshold, respectively.     

Intercomparison of satellite and ground-based ozone total column measurements

Ozone total column (OTC) measurements made in 2009–2012 near St. Petersburg by a Fourier Transform Infrared (FTIR) spectrometer (Peterhof, St. Petersburg State University (SPbSU)), an M-124 filter ozonometer, and a Dobson spectrophotometer (Voeikovo, MGO), as well as measurements made by a spectrometer ozone monitoring instrument (OMI) (onboard the AURA satellite) have been analyzed and compared. Comparisons have been performed both between ensembles of ground-based measurement data, as well as between ground-based and satellite data. It has been shown that the standard deviation for all devices is 2.5–4.5%; here, the FTIR and Dobson instruments measuring the direct sun are in better agreement with OMI than the M-124 ozonometer measuring the zenith-scattered solar radiation as well. A seasonal cycle in discrepancy with amplitude of 1.5% has been detected between two series of OTC measurements made by M-124 and OMI instruments for a total of 850 days. In fall and winter, the ground-based measurements underestimate the OTC values in comparison with satellite data; in spring and summer, the situation is reversed: ground-based data overestimate the OTC values. Also, it has been revealed that FTIR measurements systematically overestimate the OTC values in comparison with other instruments: from 1.4% (for Dobson) to 3.4% (for OMI). Taking into account the spatial and temporal discrepancy of independent ensembles of measurements and an analysis of standard deviations between ground-based and satellite measurement data, the FTIR spectrometer (SPbSU) can be recommended for OTC satellite data validation.     

半分析模型在近岸及河口水体透明度反演应用研究

Secchi depth(SD, m) is a direct and intuitive measure of water's transparency, which is also an indicator of water quality. In 2015, a semi-analytical model was developed to derive SD from remote sensing reflectance, thus able to provide maps of water's transparency in satellite images. Here an in-situ dataset(338 stations) is used to evaluate its potential ability to monitor water quality in the coastal and estuarine waters, with measurements covering the Zhujiang(Pearl) River Estuary, the Yellow Sea and the East China Sea where measured SD values span a range of 0.2–21.0 m. As a preliminary validation result, according to the whole dataset, the unbiased percent difference(UPD) between estimated and measured SD is 23.3%(N=338, R~2=0.89), with about 60% of stations in the dataset having relative difference(RD)≤20%, over 80% of stations having RD≤40%. Furthermore, by excluding the field data which with relatively larger uncertainties, the semi-analytical model yielded the UPD of 17.7%(N=132,R~2=0.92) with SD range of 0.2–11.0 m. In addition, the semi-analytical model was applied to Landsat-8 images in the Zhujiang River Estuary, and retrieved high-quality mapping and reliable spatial-temporal patterns of water clarity. Taking into account the uncertainties associated with both field measurements and satellite data processing, and that there were no tuning of the semi-analytical model for these regions, these findings indicate highly robust retrieval of SD from spectral techniques for such turbid coastal and estuarine waters. The results suggest it is now possible to routinely monitor coastal water transparency or visibility at high-spatial resolutions from measurements, like Landsat-8 and Sentinel-2 and newly launched Gaofen-5.     

A diagnostic stabilized finite-element ocean circulation model

A stabilized finite-element (FE) algorithm for the solution of oceanic large scale circulation equations and optimization of the solutions is presented. Pseudo-residual-free bubble function (RFBF) stabilization technique is utilized to enforce robustness of the numerics and override limitations imposed by the Babuška–Brezzi condition on the choice of functional spaces. The numerical scheme is formulated on an unstructured tetrahedral 3d grid in velocity–pressure variables defined as piecewise linear continuous functions. The model is equipped with a standard variational data assimilation scheme, capable to perform optimization of the solutions with respect to open lateral boundary conditions and external forcing imposed at the ocean surface. We demonstrate the model performance in applications to idealized and realistic basin-scale flows. Using the adjoint method, the code is tested against a synthetic climatological data set for the South Atlantic ocean which includes hydrology, fluxes at the ocean surface and satellite altimetry. The optimized solution proves to be consistent with all these data sets, fitting them within the error bars.The presented diagnostic tool retains the advantages of existing FE ocean circulation models and in addition (1) improves resolution of the bottom boundary layer due to employment of the 3d tetrahedral elements; (2) enforces numerical robustness through utilization of the RFBF stabilization, and (3) provides an opportunity to optimize the solutions by means of 3d variational data assimilation. Numerical efficiency of the code makes this a desirable tool for dynamically constrained analyses of large datasets.     

Variations in the chemical composition of the atmosphere from satellite measurements and their relation to fluxes of energetic particles of cosmic origin (Review)

New information about the chemical composition of the stratosphere and mesosphere is reviewed. This information was obtained in different seasons in both hemispheres with the use of the MIPAS (IR limb sounder), Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY; UV-visible and near-IR nadir and limb viewer), and Global Ozone Mapping Spectrometer (GOMOS) instruments installed on the European Envisat satellite launched in 2002. Measurements with the MIPAS instrument make it possible to retrieve information about the composition of the nighttime atmosphere. It should be noted that several powerful solar proton events (SPEs) occurred on the Sun in the period of satellite measurements. As is well known, the ionization of the polar atmosphere by SPEs is responsible for the intense interaction between ionic and neutral constituents below 100 km, which leads to the additional formation of nitrogen oxides and OH radicals destroying the ozone. Therefore, observations of the composition of the middle atmosphere in these periods are of great interest, because such situations serve as a unique test which makes it possible to check our knowledge not only about photochemical processes in the atmosphere but also about its interaction with cosmic plasma. The results of a comparison of model calculations with newly obtained data on the chemical composition, including those for SPE periods, are presented.