Using sea surface temperature measurements from microwave and infrared satellite measurements

The Tropical Rainfall Mapping Mission Microwave Imager (TMI) instrument Sea Surface Temperature (SST) product (v1.0) is compared with in situ observations obtained in the Atlantic Ocean. The TMI SST has a mean warm bias of 0.25?K±0.7?K when compared to in situ SST at a depth of 7?m. When TMI SST are compared to in situ skin SST measurements, the bias is 0.6?K±0.5?K. A limited global comparison between TMI SST and co-incident ERS-2 Along-Track Scanning Radiometer (ATSR/2) skin SST demonstrates a bias of 0.6?K±0.6?K consistent with the result obtained using in situ observations. These results are consistent with the predicted accuracy of the TMI SST data products. Based on these results, a simple method to merge the TMI and ATSR data is proposed.     

Comparison of bathymetric estimation using different satellite images in coastal sea waters

Bathymetric estimation can be obtained from multispectral satellite images for shallow waters. The method is based on the rotation of a pair of spectral bands. One of the resulting images is depth-dependent. Therefore several pixels corresponding to different depths are required to numerically evaluate the linear relation between the pixel values and the real depth for a training area. The aim of this study is to compare, for one bathymetric estimation method and one mesotrophic site, the results of depth estimation with a large panel of satellite and aerial images: CASI, QUICKBIRD, CHRIS PROBA, ETM, HYPERION and MeRIS. For each image the pair of spectral bands chosen to compute the bathymetry has been optimized. Error on depth estimation has been computed on two regions of the image: the training area and a validation area. This comparison is discussed to identify the influence of image parameters (spectral bands, S/N ratio, spatial resolution, and quantization) on the bathymetric results and to propose the most adapted image parameters for bathymetric estimation. For validation purposes, we compared the results obtained with a CASI image matching the optimized parameters in an oligotrophic site in the Red Sea.     

Atmospheric boundary layer field measurements over coastal areas

This paper reviews the main field campaigns and their results, performed within the Greater Athens Area (GAA) during the last years in order to examine closely the emission and transport mechanisms in the Athens basin. In this respect the flows and the different circulation patterns of the wind combined with the dispersion of different pollutants emitted from various points, area or line sources, were studied. Various parameters such as the topographical effects, or local circulation patterns were examined in order to establish their contribution to the pollution levels in the different areas of the Athens basin.     

基于卫星云图的风矢场度量模型研究

以数学建模的方式对基于卫星云图的风矢场度量模型进行了研究.对卫星云图数据进行预处理分析,得到卫星云图数据的特征,结合卫星上传感器采集数据的过程,通过一些假设,建立了卫星-地球三维立体模型,结合半小时采样间隔的卫星云图数据,求解得到风矢场度量模型,通过三维绘图引擎编程对模型进行模拟实现.研究结果表明该模型可以很好的预测风矢场的变化趋势,计算高效,结果与实际相符,具有一定的实用价值.     

Comparison between satellite and ship measurements of sea surface temperature in the north-east Atlantic Ocean

Abstract

A comparison is made between in situ measurements of sea surface temperature (SST) in the north-east Atlantic Ocean, obtained during Cruise 145 of RRS Discovery, and SSTs derived from several overpasses of the Advanced Very High Resolution Radiometer on the NOAA-7 satellite during the same period in March 1984. The objective of the analysis was to test the ability of the satellite to map the detailed features of SST structure and to examine the performance of atmospheric correction and temperature calibration procedures in this context. Gross comparison between all the cloud-free ship and satellite data confirms agreement normally within 1 degC. More detailed comparison of SST structure along the cruise tracks shows that the satellite data are able to identify features with a resolution of 0.3°C.     

Validation of coastal sea and lake surface temperature measurements derived from NOAA/AVHRR data

An interactive validation monitoring system is being used at the NOAA/NESDIS to validate the sea surface temperature (SST) derived from the NOAA-12 and NOAA-14 polar orbiting satellite AVHRR sensors for the NOAA CoastWatch program. In 1997, we validated the SST in coastal regions of the Gulf of Mexico, Southeast US and Northeast US and the lake surface temperatures in the Great Lakes every other month. The in situ     

Structured neural network modelling of multi-valued functions for wind vector retrieval from satellite scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method for modelling conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.     

Efficient statistical classification of satellite measurements

Supervized statistical classification is a vital tool for satellite image processing. It is useful not only when a discrete result, such as feature extraction or surface type, is required, but also for continuum retrievals by dividing the quantity of interest into discrete ranges. Because of the high resolution of modern satellite instruments and because of the requirement for real-time processing, any algorithm has to be fast to be useful. Here we describe an algorithm based on kernel estimation called Adaptive Gaussian Filtering that incorporates several innovations to produce superior efficiency as compared to three other popular methods: k-nearest-neighbour (KNN), Learning Vector Quantisation (LVQ) and Support Vector Machines (SVM). This efficiency is gained with no compromises: accuracy is maintained, while estimates of the conditional probabilities are returned. These are useful not only to gauge the accuracy of an estimate in the absence of its true value, but also to re-calibrate a retrieved image and as a proxy for a discretized continuum variable. The algorithm is demonstrated and compared with the other three on a pair of synthetic test classes and to map the waterways of the Netherlands.     

Development of polarization ratio model for sea surface wind field retrieval from TerraSAR-X HH polarization data

In this article, the polarization ratio (PR) of TerraSAR-X (TS-X) vertical–vertical (VV) and horizontal–horizontal (HH) polarization data acquired over the ocean is investigated. Similar to the PR of C-band synthetic aperture radar (SAR), the PR of X-band SAR data also shows significant dependence on incidence angle. The normalized radar cross-section (NRCS) in VV polarization data is generally larger than that in HH polarization for incidence angles above 23°. Based on the analysis, two PR models proposed for C-band SAR were retuned using TS-X dual-polarization data. A new PR model, called X-PR hereafter, is proposed as well to convert the NRCS of TS-X in HH polarization to that in VV polarization. By using the developed geophysical model functions of XMOD1 and XMOD2 and the tuned PR models, the sea surface field is retrieved from the TS-X data in HH polarization. The comparisons with in situ buoy measurements show that the combination of XMOD2 and X-PR models yields a good retrieval with a root mean square error (RMSE) of 2.03 m s^–1 and scatter index (SI) of 22.4%. A further comparison with a high-resolution analysis wind model in the North Sea is also presented, which shows better agreement with RMSE of 1.76 m s^–1 and SI of 20.3%. We also find that the difference between the fitting of the X-PR model and the PR derived from TS-X dual-polarization data is close to a constant. By adding the constant to the X-PR model, the accuracy of HH polarization sea surface wind speed is further improved with the bias reduced by 0.3 m s^–1. A case acquired at the offshore wind farm in the East China Sea further demonstrates that the improvement tends to be more effective for incidence angles above 40°.     

Detecting wind disturbance severity and canopy heterogeneity in boreal forest by coupling high-spatial resolution satellite imagery and field data

Wind disturbance events can impact spatially heterogeneous patterns in vegetation structure and disturbance severity in forested landscapes. Characterizing these patterns in forested ecosystems with remote sensing data has been a persistent challenge as variation in severity may be heterogeneous at fine spatial scales. Yet the degree and pattern of disturbance severity are an important influence on successional dynamics. This study explored how spectral and textural characteristics of high-spatial resolution IKONOS imagery reflected patterns of disturbance severity across a windstorm damaged, 121-km² area of the Boundary Waters Canoe Area Wilderness (BWCAW) in northeastern Minnesota, USA. In this study, spectral and spatial features of high-spatial resolution (1-m panchromatic and 4-m multispectral) IKONOS satellite imagery from a single post-disturbance date are coupled with field observations of disturbance within 0.045-ha field plots to access the potential for empirically modeling disturbance severity across this heterogeneous landscape within the BWCAW. Combining textural and spectral features led to a multiple regression model that explained 68% of the variance, and predicted disturbance severity equally well for ground data not included in the model development. The results suggest the utility of combining spatial and spectral data for detecting differences in forest structure caused by ecological processes such as disturbance.     

Eddy-advective effects on the temperature and wind speed of the sea surface in the Northwest Pacific Subtropical Countercurrent area from satellite observations

In this study, satellite microwave and altimeter data from 1998 to 2007 are used to quantify the eddy-induced meridional heat advection (EMHA) in the Northwest Pacific Subtropical Countercurrent area. Generally, from March to May, the robust EMHA is formed at the point where meridional currents of eddies cross a zonal front of climatological background sea surface temperature (SST). The EMHA shifts westwards with eddies and varies seasonally with the SST front. It warms (cools) the sea surface west of anticyclonic (cyclonic) eddies, inducing noticeable SST anomalies (SSTAs), which are westwardly phase shifted from the eddy-induced sea surface height anomalies by about 90°. Surface wind subsequently varies with the induced SSTAs: it blows faster (slower) over the warm (cold) SST regions than the surroundings. The spatial variations of SST and sea surface wind due to the EMHA shift westwards with eddy motion. These findings from satellite observations give us the possibility of studying the role of oceanic eddies in ocean–atmosphere interaction at the timescale of weather systems in an open ocean.     

The use of optic and radar satellite data for coastal environments

The pressure of population and its demands for fuel, for heating or industrial usage, causes destruction of the natural environment. One of the clearest examples for the accelerated degradation of changes in the forest area and coastline is in the Kilyos–Karaburun coastline located in the northern part of Istanbul metropolitan city. The open‐pit mining activities in the region are threatening the balances of both sea and land ecosystems, and cause degradation of forest areas and changes along the coastline. In this paper, the changes are examined with multisensor satellite data such as Landsat Thematic Mapper (TM), SPOT Panchromatic (P), and RADARSAT images by using different image‐processing techniques. The degrees of changes in coastline length and coastal region area were calculated, and the effectiveness of the use of different image data sets was outlined for coastal environments.     

Provincial nature of chlorophyll and sea surface temperature observed by satellite

Monthly composite SeaWiFS derived chlorophyll, National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) derived sea surface temperature (SST) and QuikScat derived wind data of 2003–2005 (January–December) were analysed to study the provincial nature of chlorophyll‐a (chl‐a), SST and wind speed in the Arabian sea and Bay of Bengal. The study was confined to five provinces, three in the Arabian Sea and two in the Bay of Bengal. Results indicate provincial variability in the SST‐chl‐a relation. It suggests that the correlation between chlorophyll and SST is not always negative. A negative correlation was observed in provinces 1, 2 and 3 for all the seasons, whereas, except for the month of January–February, it was positively correlated for province 4. Analysis shows the provincial specific nature of chlorophyll variability to physical forcing and suggests that treatment of such a problem should not be undertaken on the basin scale.     

Assessment of satellite ocean color products at a coastal site

A comprehensive set of bio-optical measurements collected at the Acqua Alta Oceanographic Tower site in the northern Adriatic Sea is used to assess satellite derived optical properties and concentrations of optically significant constituents. These include normalized water leaving radiance spectra L_WN, absorption spectra due to phytoplankton, non-pigmented particles and chromophoric dissolved organic matter, back-scattering spectra, concentrations of chlorophyll a, Chla, and total suspended matter, TSM, and diffuse attenuation coefficients, K_d, obtained with a diverse set of algorithms. A total of 81 and 21 match-ups are found for SeaWiFS and MODIS L_WN, respectively. For both sensor products, the match-ups show mean absolute percentage differences of approximately 30% at 412 nm, 20% at 443 nm, and 14% from 490 to 555 nm. Some dependence of these differences has been found with respect to the aerosol optical thickness and the single scattering albedo associated with the in-water constituents. However, the performance of the atmospheric correction scheme appears relatively robust with respect to angular and environmental conditions. The different Chla products generally show quite large uncertainties whereas a TSM product shows encouraging results. Three algorithms produce K_d (490) with a RMS uncertainty of 0.13 for log-transformed data. The comparison between in situ data and satellite derived absorption values yields varying levels of uncertainties for the three bio-optical algorithms considered here and for the different wavelengths. Preliminary improvements could be reached by reducing biases affecting the total absorption coefficient at various wavelengths. Another general result is that the bio-optical models are able to represent a larger part of the observed variability for phytoplankton absorption than for the absorption by dissolved and non-pigmented particulate matter. The assumed spectral shape of the latter absorption term appears logically as a strong determinant of the partition of the total absorption. The three sets of satellite derived back-scattering spectra compare favorably with in situ optical measurements, with mean RMS differences between 0.12 and 0.18. Importantly, the uncertainties obtained here for satellite match-ups of absorption coefficients are comparable to published estimates of the inherent uncertainties associated with the bio-optical algorithms.     

随机风速场的数值模拟及高层建筑风振控制

根据Davenport脉动风速谱, 采用AR模型(auto-regressive)法, 考虑竖向相关性、平稳的多变量随机过程以及它的互谱密度矩阵, 模拟生成具有随机性的脉动风速时程曲线和风速谱的功率谱密度. AR法模拟风速的功率谱密度函数与Davenport目标谱的比较表明AR法具有很高的精度和效率. 采用了建筑结构振动控制第2代标准规定的76层306m高钢筋混凝土结构的风振控制模型, 研究了风荷载作用下高层建筑动力响应的控制方法, 给出了模拟脉动风荷载作用下, 被动调谐质量阻尼器(TMD, tuned mass damper)控制和主动线性二次型Gauss(LQG, linear quadratic Gaussian)控制的控制结果.     

Sea surface wind speed and sea state retrievals from dual-frequency altimeter and its preliminary application in global view of wind-sea and swell distributions

Altimeter radar backscatter intensity, in terms of the normalized radar cross section (NRCS), is known to be modulated by surface wind forcing and the state of wind-sea development. Based on a data set of collocated altimeters (including Topex/Poseidon, Jason-1 and Jason-2) and in situ measurements, different responses to various wind speeds and wave ages (i.e. the state of wind-sea development) were illustrated for altimeter dual-frequency NRCSs (K_u-band at 13.6 Hz and C band at 5.4 Hz), which can facilitate the retrieval of wind speed and wave age parameters. A statistical parametric algorithm was developed to retrieve the two dynamic parameters from the altimeter dual-frequency NRCSs using the neutral network method. The wind-sea significant wave height (SWH) was estimated from wind speed and wave age parameters, which partitions the swell SWH from the altimeter SWH measurement. All newly derived parameters were well validated by comparison against in situ buoy measurements. A preliminary application of the method in examining the swell or wind-sea contributions to global waves was performed; it was found the swell dominance in an open ocean, and the wind-sea dominance in marginal and semi-enclosed seas. The methods would benefit other applications such as studies of air–sea interactions, validation of wave model, determination of swell decay rate and studies of wave climate.     

Influence of wind on crop canopy reflectance measurements

Remote sensing techniques of measuring red and far-red crop canopy reflectance are frequently used to estimate crop canopy characteristics. The variability introduced in reflectance data from nonvegetative factors such as wind decreases the usefulness of the techniques. The objective of this study was to quantify and minimize the variability from wind on spectral reflectances. Red and far-red reflectances were acquired above wheat, barley, and alfalfa canopies throughout days of changing wind conditions. Periods of 312 s with little changes in irradiance values were used for the analysis. Wind had negligible effect on reflectances of a short canopy such as cut alfalfa, while it had a significant effect on reflectances from canopies with a higher vertical structure, particularly during gusty conditions. Within the windy and calm periods, extreme values of spectral reflectance differed by 60% and 12%, respectively, in the red, and by 40% and 8% in the far-red for the barley canopy. For the compact and dense canopy structure of alfalfa, these differences reached a maximum of 10% under windy conditions in both spectral regions. The plant canopy architecture, the wind conditions, and the spectral regions all affected the magnitude of the influence of wind on crop canopy spectral reflectances. The mean reflectance of a canopy overestimated the true reflectance by 2–4% while the use of the median reduced this overestimation. Sampling requirements for this sensor are evaluated, and the possibility of decreasing either the sampling rate or the sampling period is discussed.     

Inter-comparison of satellite sea ice motion with drifting buoy data

In this study, three low-resolution and three medium-resolution ice motion products were compared to ice-tethered profiler (ITP) global positioning system (GPS) data over a 2 year period. The ice motion products were the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), merged Advanced Scatterometer + Special Sensor Microwave/Imager (ASCAT + SSM/I), advanced synthetic aperture radar (ASAR), and Advanced Very High Resolution Radiometer (AVHRR) ice motion data. The results show that the data quality of six satellite products is better than or close to expected values. The error distributions of the satellite ice motion generally have high kurtosis and heavy tails and are not normally distributed. Low-resolution ice motion generally shows large errors in the Fram Strait. AVHRR summer ice motion shows a larger bias, probably affected by inaccurate cloud masking, while the large errors in ASAR ice motion mainly occur due to occasional geolocation errors of near-real-time ASAR images used for ice motion retrieval. Inter-comparison between satellite ice motion products with different time intervals is also discussed.