A comparison of atmospheric aerosol measurements by various satellite sensors

Investigations to measure the vertical optical thickness of aerosols over ocean surfaces has been conducted using several different satellite sensors. Landsat 1 and Landsat 2 data originally confirmed that a linear relationship exists between the upwelling visible radiance and the aerosol optical thickness (about 90% of this thickness is generally in the lowest 3 km of the atmosphere). Similar relationships have also been found for sensors on GOES-1, SMS-2, NOAA-5, and NOAA-6 satellites. The linear relationship has been shown theoretically to vary with the aerosol properties, such as size distribution and refractive index, although the Landsat data obtained at San Diego showed little variability in the relationship. The differences between the results found for the various satellite sensors are discussed, and are attributed mainly to uncertainties in the calibration of the sensors. To investigate the general applicability of the technique to different locations, a global-scale ground truth experiment was conducted with the AVHRR sensor on NOAA-6 to determine the relationship at eleven ocean sites around the globe. Analysis of the data shows good agreement between the satellite and ground truth values of the aerosol optical thickness, and indicates that the technique has global application. At two of the sites, multispectral radiometric measurements of the Junge aerosol size distribution parameter were made, and showed good agreement with a value inferred from the AVHRR Channels 1 and 2 radiances.     

Satellite measurements of tropospheric aerosols

The ability to measure tropospheric aerosols over ocean surfaces has been demonstrated using several different satellite sensors. Landsat data originally showed that a linear relationship exists between the upwelling visible radiance and the aerosol optical thickness (about 90% of this thickness is generally in the lowest 3 km of the atmosphere). Similar relationships have also been found for sensors on GOES, NOAA-5 and NOAA-6 satellites. The linear relationship has been shown theoretically to vary with the aerosol properties, such as size distribution and refractive index, although the Landsat data obtained at San Diego showed little variability in the relationship. To investigate the general applicability of the technique to different locations, a global-scale ground-truth experiment was conducted in 1980 with the AVHRR sensor on NOAA-6 to determine the relationship at ten ocean sites around the globe. The data for four sites have been analyzed, and show excellent agreement between the aerosol content measured by the AVHRR and by sunphotometers at San Diego, Sable Island and San Juan, but at Barbados, the AVHRR appears to overestimate the aerosol content. The reason for the different relationship at the Barbados site has not been definitely established, but is most likely related to problems in interpreting the sunphotometer data rather than to a real overestimation by the AVHRR. A preliminary analysis of AVHRR Channel 1 (0.65 μm) and Channel 2 (0.85 μm) radiances suggest that useful information on the aerosol size distribution may also be obtained from satellite observations.     

Improvements in broadband planetary albedo estimates from narrowband NOAA satellite observations

New and current algorithms for estimating the broadband planetary albedo from NOAA satellite narrowband observations are testes by applying them to retrospective NOAA-9 AVHRR (Advanced Very High Resolution) data of 2 July 1985. For comparison, broadband SW fluxes taken by the Earth Radiation Budget Experiment (ERBE) instrument, also on NOAA-9 are used as reference values. In contrast to the current scene-independent model, the new algorithms are all scene-dependent, but differ in the way they are classified by surface, cloud amount and albedo indices. The current operational model produces a global bias of magnitude 5 W/m² and a strong latitudinal dependence in error. The scene-dependent algorithms yield global biases of less than ±3 W/m² and have little latitudinal dependence over most of the globe.     

Analysis of the variability of temperature gradient in the ocean frontal zones based on satellite data

AVHRR MCSST data for the periods 1982–2000 (mean weekly data) were used to calculate mean gradient fields in the ocean for different periods of time. Three-month averaged sea surface temperature gradients (SSTG) and their mean seasonal variations have been studied for 25 points in the large-scale oceanic fronts zones. Major oceanic fronts in the Atlantic and Pacific have been identified and compared in literature. In the North Atlantic and Pacific, the areas under study were the North Polar Front and Subpolar Fronts. In the South Atlantic and Pacific we studied the region of the Antarctic Circumpolar Current (ACC) and the fronts formed by this current, known as the South Polar Front, and the Subantarctic Front. SSTG were also calculated for El Niño (Southeast Pacific) and Benguela Current (Southeast Atlantic).     

Development of digital interactive processing system for NOAA satellites AVHRR data

The paper discusses the digital image processing system for NOAA/AVHRR data including Land applications — configured around VAX 11/750 host computer supported with FPS 100 Array Processor, Comtal graphic display and HP Plotting devices; wherein the system software for relational Data Base together with query and editing facilities, Man-Machine Interface using form, menu and prompt inputs including validation of user entries for data type and range; preprocessing software for data calibration, Sun-angle correction, Geometric Corrections for Earth curvature effect and Earth rotation offsets and Earth location of AVHRR image have been accomplished. The implemented image enhancement techniques such as grey level stretching, histogram equalization and convolution are discussed. The software implementation details for the computation of vegetative index and normalized vegetative index using NOAA/AVHRR channels 1 and 2 data together with output are presented; scientific background for such computations and obtainability of similar indices from Landsat/MSS data are also included. The paper concludes by specifying the further software developments planned and the progress envisaged in the field of vegetation index studies.     

Seasonal-to-interannual variability of chlorophyll-a bloom timing associated with physical forcing in the Gulf of Cádiz

Seasonal-to-interannual variability of the winter-spring bloom in the Gulf of Cádiz, eastern North Atlantic, has been investigated using chlorophyll-a remote sensing (CHL). These data have been obtained from the GlobColour project; the temporal coverage extends from September 1997 to December 2010. In this study we develop a generic quantitative approach for describing the temporal variability in the shape of the winter-spring bloom within a region. Variability in both the timing and magnitude of the bloom in the basin has been evaluated as a function of physical properties in the water column such as Mixed Layer Depth (MLD, GODAS model), sea surface temperature (SST, from AVHRR radiometers), photosynthetically-active radiation (PAR, from ocean color data) and euphotic depth (Z_eu, from ocean color data). The analysis indicated that the timing, size and duration of the phytoplankton bloom in this area are largely controlled by both meteorological and oceanographic conditions at different scales; this means that it is likely to vary widely from one year to another.     

Robust extension of the simple sea-surface irradiance model to handle cloudy conditions for the global ocean using satellite remote sensing data

Sea-surface solar radiation (abbreviated as photosynthetically available radiation, PAR) in the visible wavelength (400–700 nm) is an essential parameter to estimate marine primary productivity and understanding phytoplankton dynamics, upper ocean physics and biogeochemical processes. Although many remote-sensing models were developed to estimate daily PAR (DPAR) from ocean colour data, these models often produce biases in the DPAR products under cloudy-sky and complex atmospheric conditions due to the lack of parameterization to deal with the cloud cover conditions and insufficient in-situ DPAR data. This study presents an Extended Sea-surface Solar Irradiance Model (ESSIM) for estimating DPAR over the global ocean. The ESSIM uses the direct and diffuse components from the Simple sea-surface Solar Irradiance Model (SSIM) along with a new parameter to handle cloudy conditions. The ESSIM produced DPAR products with greater accuracy under both clear and cloudy conditions. Its performance was tested on the time-series MODIS-Aqua images and compared with the concurrent in-situ data and the results from two global models. Results showed that the DPAR values produced by ESSIM agree with in-situ data better than the global models for all-sky conditions (with a mean relative error of 11.267 %; a root mean square error of 5.563 Em^?2day^?1; and a mean net bias of 2.917 Em^?2day^?1). The ESSIM performed slightly better than the SSIM for clear conditions and the Frouin's Operational Algorithm (FOA) for all-sky conditions. As the new parameterization accounts for cloudy conditions, the ESSIM produced more accurate results for cloud cover conditions across latitudes (up to 60°). The time-series Level-3 binned MODIS-Aqua data (global gridded) also demonstrated that the ESSIM improved the accuracy of DPAR products and produced spatially and temporally consistent DPAR products over the global ocean regardless of the seasons and sky conditions.     

Sea surface temperature measurement from satellites: Validation and accuracy

A review of the latest published results concerning the accuracy of satellite derived sea surface temperature (SST) estimation is presented. Two types of platforms are considered : orbiting satellites and geosynchronous satellites and the accuracies that may now be expected from such systems are reported. This review emphasizes the impressive improvement in global mapping of SST obtained from the Advanced Very High Resolution Radiometer (AVHRR) on NOAA's operational polar satellites. Tests of the AVHRR SST's against a high reliability data set consisting of buoys, bathythermographs and research ship reports indicate biases of < 0.1°C and RMS differences of < 0.75°C (McClain [1]). Particular attention is also paid to a method adding along track scanning capability to the present multichannel AVHRR technique. This method is demonstrated owing to the coupling of an orbiting satellite (TIROS-N) and a geosynchronous satellite (METEOSAT). Another type of coupling of two such platforms is also presented in connection with the advent of geostationary satellites equipped with a vertical sounding capability, such as GOES-4.     

Preliminary evaluation of the landsat-4 thematic mapper data for mineral exploration

Landsat-4 Thematic Mapper (TM) data recorded over an arid terrain were analyzed to determine the applicability of using of TM data for identifying and mapping hydrothermally altered, potentially mineralized rocks. Clays, micas, and other minerals bearing the OH anion in specific crystal lattice positions have absorption bands in the 2.2-μm region (TM channel 7, TM7) and commonly lack features in the 1.6-μm region (TM5). Channel ratios TM5/TM7, TM5/TM4, and TM3/TM1 were combined into a color-ratio-composite (CRC) image and used to distinguish hydrothermally altered rocks, unaltered rocks, and vegetation. These distinctions are made possible by using the TM5 and TM7, channels which are not available in the Landsat multispectral scanner (MSS). Digital masking was used to eliminate ambiguities due to water and shadows. However, some ambiguities in identification resulted between altered volcanic rocks and unaltered sedimentary deposits that contained clays, carbonates, and gypsum, and between altered volcanic rocks and volcanic tuffs diagenetically altered to zeolites. However, compared to MSS data, TM data should greatly improve the ability to map hydrothermally altered rocks in arid terrains.     

Detection and mapping vegetation cover based on the Spectral Angle Mapper algorithm using NOAA AVHRR data

Satellite data, taken from the National Oceanic and Atmospheric Administration (NOAA) have been proposed and used for the detection and the cartography of vegetation cover in North Africa. The data used were acquired at the Analysis and Application of Radiation Laboratory (LAAR) from the Advanced Very High Resolution Radiometer (AVHRR) sensor of 1 km spatial resolution. The Spectral Angle Mapper Algorithm (SAM) is used for the classification of many studies using high resolution satellite data. In the present paper, we propose to apply the SAM algorithm to the moderate resolution of the NOAA AVHRR sensor data for classifying the vegetation cover. This study allows also exploiting other classification methods for the low resolution. First, the normalized difference vegetation index (NDVI) is extracted from two channels 1 and 2 of the AVHRR sensor. In order to obtain an initial density representation of vegetal formation distribution, a methodology, based on the combination between the threshold method and the decision tree, is used. This combination is carried out due to the lack of accurate data related to the thresholds that delimit each class. In a second time, and based on spectral behavior, a vegetation cover map is developed using SAM algorithm. Finally, with the use of low resolution satellite images (NOAA AVHRR) and with only two channels, it is possible to identify the most dominant species in North Africa such as: forests of the Liege oaks, other forests, cereal’s cultivation, steppes and bar soil.     

A generalised methodology for estimating land surface temperature for non-urban areas of Greece through the combined use of NOAA–AVHRR data and ancillary information

The purpose of this study was twofold: to develop a methodology for the estimation of land surface temperature for non-urban areas and to analyze the sensitivity of the methodology. The key element of the methodology was the development of emissivity maps based on CORINE Land Cover and the ASTER spectral library. Land surface temperatures were derived from NOAA/AVHRR data and the methodology was applied at a national scale in Greece, with emphasis given to non-urban areas. A sensitivity analysis was performed in order to determine the variables that mainly affect the estimation of land surface temperature. A varying propagation error was identified depending on the temperature and humidity of the atmosphere, as well as the land cover type. The methodology was applied to a series of 25 AVHRR images and the results were compared to in-situ measurements from representative stations.     

基于QZSS L1信号的岸基GNSS-R码延迟海面测高

为了探究GNSS L1波段中信号不同调制方式的GNSS-R码相位延迟海面的测高性能，开展了双天线岸基GNSS-R海面测高实验，收集了采样率为40 MHz的原始中频数据。利用自主开发的GNSS-R测高软件接收机和反演软件对实验数据进行了处理分析，同时获得了基于QZSS L1C/A码和L1C码的GNSS-R海面测高结果，并分别与岸基同步观测的雷达高度计的测高值进行对比，以对反演结果进行精度评定。实验结果表明:基于QZSS L1C/A码和L1C码的海面测高精度最优可达0.63 m和0.4 m，L1C码的延迟GNSS-R测高精度明显高于L1C/A码。此外，GNSS-R测高精度会随着卫星高度角的增加而有所增加。      

Evaluation of thematic mapper data for mapping forest,agricultural and soil resources

Color composite TM film products which include TM5, TM4, and a visible band (TM1, TM2, or TM3) are superior to composites which exclude TM4 for discriminating most forest and agricultural cover types and estimating area proportions for inventory and sampling purposes. Clustering a subset of TM data results in a spectral class map which groups diverse forest cover types into spectrally and ecologically similar areas suitable for use as a stratification base in traditional forest inventory practices. Analysis of simulated Thematic Mapper data indicate that the location and number of TM spectral bands are suitable for detecting differences in major soil properties and characterizing soil spectral curve form and magnitude.     

The First Chinese Ocean Color Satellite HY-1A

HY-1A is China's first ocean color satellite, and was launched on 15 May 2002as a piggyback satellite on the FY-1D satellite using the Long March rocket.There are two sensors on the satellite: China's Ocean Color and Temperature Scanner (COCTS), and the CCD Coastal Zone Imager (CZI). In the report,first, the properties and characteristics of HY-1A are briefly introduced; Second, the quality and availability of the data are evaluated by the mean of the Complex Signal Noise Ratio (CSNR) which is simulated theoretically; Third,the received HY-1A data are compared with SeaSTAR data to understand the accuracy of radiance measurement by the HY-1A; Finally, the remote sensing products of ocean color and temperature are mapped by HY-1A to study its application potentiality. The results show that the HY-1A has a latent capability for the application of marine environment detection, the management and protection of marine resources, and the furthering of national rights and interests.Meanwhile, some modifications are proposed for the next ocean satellite, suchas adding the case of tilt scanning, modification of the CCD element uniformity,and adding more ocean satellite receiving stations.     

Environmental degradation analysis using NOAA/AVHRR data

This paper proposes a particular approach to assess information about soil degradation, based on a methodology to calculate soil color from NOAA/AVHRR data. As erosive processes change physical and chemical properties of the soil, altering, consequently, the superficial color, monitoring the change in color over time can help to identify and analyze those processes. A relationship among the soil color (described in the Munsell Color System, i.e., in terms of Hue, Value and Chroma), vegetation indices, surface temperature and emissivity has been established, which is based on the theoretical model. The methodology has three main phases: determination of the regression models among soil color and vegetation indices, emissivity and surface temperature; generation of digital soil color models; and statistical evaluation of the estimated color. The tests showed that the methodology is efficient in determining soil color using the various vegetation indices (i.e., Normalized vegetation index NDVI, Modified soil adjusted vegetation index MSAVI). One vegetation index, i.e., Purified adjusted vegetation index (PAVI) is proposed to subsidies the effect of vegetation over the soil. Best results were obtained for the Hue color component. To further test the methodology, the estimated digital color models were compared with the characteristic color of soil classes in the test area. The results of this application confirmed the methodology’s capacity to determine the soil color from NOAA/AVHRR data. This type of study is quite helpful to know the erosion of soil as well as some abrupt change in soil due to natural hazards by space borne or air-borne sensors.     

Quantifying barystatic sea-level change from satellite altimetry,GRACE and Argo observations over 2005–2016

Time-varying spherical harmonic coefficients determined from the Gravity Recovery and Climate Experiment (GRACE) data provide a valuable source of information about the water mass exchange that is the main contributor to the Earth’s gravity field changes within a period of less than several hundred years. Moreover, by measuring seawater temperature and salinity at different layers of ocean depth, Argo floats help to measure the steric component of global mean sea level (GMSL). In this study, we quantify the rate of barystatic sea-level change using both GRACE RL05 and RL06 monthly gravity field models and compare the results with estimates achieved from a GMSL budget closure approach. Our satellite altimetry-based results show a trend of 3.90 ± 0.14 mm yr⁻¹ for the GMSL rise. About 35% or 1.29 ± 0.07 mm yr⁻¹ of this rate is caused by the thermosteric contribution, while the remainder is mainly due to the barystatic contribution. Our results confirm that the choice of decorrelation filters does not play a significant role in quantifying the global barystatic sea-level change, and spatial filtering may not be needed. GRACE RL05 and RL06 solutions result in the barystatic sea-level change trends of 2.19 ± 0.13 mm yr⁻¹ and 2.25 ± 0.16 mm yr⁻¹, respectively. Accordingly, the residual trend, defined as the difference between the altimetry-derived GMSL and sum of the steric and barystatic components, amounts to 0.51 ± 0.51 and 0.45 ± 0.44 mm yr⁻¹ for RL05 and RL06-based barystatic sea-level changes, respectively, over January 2005 to December 2016. The exclusion of the halosteric component results in a lower residual trend of about 0.36 ± 0.46 mm yr⁻¹ over the same period, which suggests a sea-level budget closed within the uncertainty. This could be a confirmation on a high level of salinity bias particularly after about 2015. Moreover, considering the assumption that the GRACE-based barystatic component includes all mass change signals, the rather large residual trend could be attributed to an additional contribution from the deep ocean, where salinity and temperature cannot be monitored by the current observing systems. The errors from various sources, including the model-based Glacial Isostatic Adjustment signal, independent estimation of geocenter motion that are not quantified in the GRACE solutions, as well as the uncertainty of the second degree of zonal spherical harmonic coefficients, are other possible contributors to the residual trend.     

Towards development of a consistent orbit series for TOPEX,Jason-1, and Jason-2

The TOPEX/Poseidon, Jason-1 and Jason-2 set of altimeter data now provide a time series of synoptic observations of the ocean that span nearly 17 years from the launch of TOPEX in 1992. The analysis of the altimeter data including the use of altimetry to monitor the global change in mean sea level requires a stable, accurate, and consistent orbit reference over the entire time span. In this paper, we describe the recomputation of a time series of orbits that rely on a consistent set of reference frames and geophysical models. The recomputed orbits adhere to the IERS 2003 standards for ocean and earth tides, use updates to the ITRF2005 reference frame for both the SLR and DORIS stations, apply GRACE-derived models for modeling of the static and time-variable gravity, implement the University College London (UCL) radiation pressure model for Jason-1, use improved troposphere modeling for the DORIS data, and apply the GOT4.7 ocean tide model for both dynamical ocean tide modeling and for ocean loading. The new TOPEX orbits have a mean SLR fit of 1.79 cm compared to 2.21 cm for the MGDR-B orbits. These new TOPEX orbits agree radially with independent SLR/crossover orbits at 0.70 cm RMS, and the orbit accuracy is estimated at 1.5–2.0 cm RMS over the entire TOPEX time series. The recomputed Jason-1 orbits agree radially with the Jason-1 GDR-C orbits at 1.08 cm RMS. The GSFC SLR/DORIS dynamic and reduced-dynamic orbits for Jason-2 agree radially with independent orbits from the CNES and JPL at 0.70–1.06 cm RMS. Applying these new orbits, and using the latest altimeter corrections for TOPEX, Jason-1, and Jason-2 from September 1992 to May 2009, we find a global rate in mean sea level of 3.0 ± 0.4 mm/yr.     

Ocean Observation from Haiyang Satellites

In 2018, China successfully launched three new Haiyang (which means ocean in Chinese, referred to as HY) satellites which are an ocean color observation satellite HY-1C (operational), an ocean dynamics environment satellite HY-2B (operational) and the China-France ocean satellite CFOSAT (experimental). In 2019, all the three satellites had finished their commissioning phases and were declared operational. HY-2A satellite continues to operate in-orbit, and its operational status is basically normal. So in 2020, China has 4 Haiyang satellites in-orbit, China's ocean satellites enter into a new operational application phase. The operation of the ground application system of Chinese ocean satellites is stable. In 2019, Beijing, Hainan, Mudanjiang, and Hangzhou ocean satellite ground stations had received the data of HY-1C, HY-2A, HY-2B, and CFOSAT 5012 orbits and 26.46 TB data had been distributed to both domestic and international users. Chinese ocean satellite data has played an important role in marine disaster prevention and mitigation, development and management of marine resources, maintenance of marine rights and interests, marine environment protection, scientific researches, and blue economy development.      

General Relativity Accuracy Test (GReAT): New configuration for the differential accelerometer

We presents the results of an activity concerning the test of the Einstein Weak Equivalence Principle with an accuracy of about 5 × 10⁻¹⁵. The experiment will be performed in an “Einstein elevator” using a differential accelerometer with a final sensitivity of about 10⁻¹⁴ g_⊕/Hz^1/2. The differential accelerometer is spun about an horizontal axis at a frequency in the range 0.5–1 Hz in order to modulate, during the free fall, the signal from a possible violation of the Equivalence Principle. In the paper the perturbing effects with the same signature of the possible violation are analyzed and constrained. The experimental results obtained in the laboratory with a first prototype of the differential accelerometer are discussed, comparing this results with those obtained using a new prototype.     

Advances on Technology and Application of Ocean Color Remote Sensing in China (2004 - 2006)

China has great progress in the technology and application of ocean color remote sensing during 2004-2006. In this report, firstly, four major technical advances are displaying, including (1) the vector radiative transfer numerical model of coupled ocean-atmosphere system; (2) the atmospheric correction algorithm specialized on Chinese high turbid water; (3) systematical research of hyper-spectrum ocean color remote sensing; (4) local algorithms of oceanic parameters, like ocean color components, ocean primary productivity, water transparency, water quality parameters, etc. On the foundation of technical advances, ocean color remote sensing takes effect on ocean environment monitoring, with four major kinds of application systems, namely, (1) the automatic multi-satellites data receiving, processing and application system; (2) the shipboard satellite data receiving and processing system for fishery ground information; (3) Coastal water quality monitoring system, integrating satellite and airborne remote sensing technology and ship measurement; (4) the preliminary system of airborne ocean color remote sensing application system. Finally, the prospective development of Chinese ocean color remote sensing is brought forward. With Chinese second ocean color satellite (HY-1B) orbiting, great strides will take place in Chinese ocean color information accumulation and application.