A study of multiyear ice concentration retrieval algorithms using AMSR-E data

In recent years, the rapid decline of Arctic sea ice area （SIA） and sea ice extent （SIE）, especially for the multiyear （MY） ice, has led to significant effect on climate change. The accurate retrieval of MY ice concentration retrieval is very important and challenging to understand the ongoing changes. Three MY ice concentration retrieval algorithms were systematically evaluated. A similar total ice concentration was yielded by these algorithms, while the retrieved MY sea ice concentrations differs from each other. The MY SIA derived from NASA TEAM algorithm is relatively stable. Other two algorithms created seasonal fluctuations of MY SIA, particularly in autumn and winter. In this paper, we proposed an ice concentration retrieval algorithm, which developed the NASA TEAM algorithm by adding to use AMSR-E 6.9 GHz brightness temperature data and sea ice concentration using 89.0 GHz data. Comparison with the reference MY SIA from reference MY ice, indicates that the mean difference and root mean square （rms） difference of MY SIA derived from the algorithm of this study are 0.65×10^6 km^2 and 0.69×10^6 km^2 during January to March, -0.06×10^6 km^2 and 0.14×10^6 km^2during September to December respectively. Comparison with MY SIE obtained from weekly ice age data provided by University of Colorado show that, the mean difference and rms difference are 0.69×10^6 km^2 and 0.84×10^6 km^2, respectively. The developed algorithm proposed in this study has smaller difference compared with the reference MY ice and MY SIE from ice age data than the Wang＇s, Lomax＇ and NASA TEAM algorithms.

Evaluation of ENVISAT ASAR data for sea surface wind retrieval in Hong Kong coastal waters of China

The C-band wind speed retrieval models, CMOD4, CMOD - IFR2, and CMOD5 were applied to retrieval of sea surface wind speeds from ENVISAT （European environmental satellite） ASAR （advanced synthetic aperture radar） data in the coastal waters near Hong Kong during a period from October 2005 to July 2007. The retrieved wind speeds are evaluated by comparing with buoy measurements and the QuikSCAT （quick scatterometer） wind products. The results show that the CMOD4 model gives the best performance at wind speeds lower than 15 m/s. The correlation coefficients with buoy and QuikSCAT winds are 0.781 and 0.896, respectively. The root mean square errors are the same 1.74 m/s. Namely, the CMOD4 model is the best one for sea surface wind speed retrieval from ASAR data in the coastal waters near Hong Kong.

An assessment of arctic sea ice concentration retrieval based on “HY-2” scanning radiometer data using field observations during CHINARE-2012 and other satellite instruments

A retrieval algorithm of arctic sea ice concentration （SIC） based on the brightness temperature data of “HY-2” scanning microwave radiometer has been constructed. The tie points of the brightness temperature were selected based on the statistical analysis of a polarization gradient ratio and a spectral gradient ratio over open water （OW）, first-year ice （FYI）, and multiyear ice （MYI） in arctic. The thresholds from two weather filters were used to reduce atmospheric effects over the open ocean. SIC retrievals from the “HY-2” radiom-eter data for idealized OW, FYI, and MYI agreed well with theoretical values. The 2012 annual SIC was calcu-lated and compared with two reference operational products from the National Snow and Ice Data Center （NSIDC） and the University of Bremen. The total ice-covered area yielded by the “HY-2” SIC was consistent with the results from the reference products. The assessment of SIC with the aerial photography from the fifth Chinese national arctic research expedition （CHINARE） and six synthetic aperture radar （SAR） images from the National Ice Service was carried out. The “HY-2” SIC product was 16% higher than the values de-rived from the aerial photography in the central arctic. The root-mean-square （RMS） values of SIC between “HY-2” and SAR were comparable with those between the reference products and SAR, varying from 8.57% to 12.34%. The “HY-2” SIC is a promising product that can be used for operational services.

Monitoring Carbon Dioxide from Space：Retrieval Algorithm and Flux Inversion Based on GOSAT Data and Using CarbonTracker-China

Monitoring atmospheric carbon dioxide（CO_2） from space-borne state-of-the-art hyperspectral instruments can provide a high precision global dataset to improve carbon flux estimation and reduce the uncertainty of climate projection. Here, we introduce a carbon flux inversion system for estimating carbon flux with satellite measurements under the support of ＂The Strategic Priority Research Program of the Chinese Academy of Sciences—Climate Change： Carbon Budget and Relevant Issues＂. The carbon flux inversion system is composed of two separate parts： the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing（IAPCAS）, and Carbon Tracker-China（CT-China）, developed at the Chinese Academy of Sciences. The Greenhouse gases Observing SATellite（GOSAT） measurements are used in the carbon flux inversion experiment. To improve the quality of the IAPCAS-GOSAT retrieval, we have developed a post-screening and bias correction method, resulting in 25%–30% of the data remaining after quality control. Based on these data, the seasonal variation of XCO_2（column-averaged CO_2dry-air mole fraction） is studied, and a strong relation with vegetation cover and population is identified. Then, the IAPCAS-GOSAT XCO_2 product is used in carbon flux estimation by CT-China. The net ecosystem CO_2 exchange is-0.34 Pg C yr^（-1）（±0.08 Pg C yr^（-1））, with a large error reduction of 84%, which is a significant improvement on the error reduction when compared with in situ-only inversion.

A COMPARISON OF THE RETRIEVAL OF ATMOSPHERIC TEMPERATURE PROFILES USING OBSERVATIONS OF THE 60 GHZ AND 118.75 GHZ ABSORPTION LINES

The Microwave Temperature Sounder-Ⅱ(MWTS-Ⅱ) and Microwave Humidity and Temperature Sounder(MWHTS) onboard the Fengyun-3 C(FY-3 C) satellite can be used to detect atmospheric temperature profiles. The MWTS-II has 13 temperature sounding channels around the 60 GHz oxygen absorption band and the MWHTS has 8 temperature sounding channels around the 118.75 GHz oxygen absorption line. The data quality of the observed brightness temperatures can be evaluated using atmospheric temperature retrievals from the MWTS-Ⅱ and MWHTS observations. Here, the bias characteristics and corrections of the observed brightness temperatures are described. The information contents of observations are calculated, and the retrieved atmospheric temperature profiles are compared using a neural network(NN) retrieval algorithm and a one-dimensional variational inversion(1 D-var) retrieval algorithm. The retrieval results from the NN algorithm show that the accuracy of the MWTS-Ⅱ retrieval is higher than that of the MWHTS retrieval, which is consistent with the results of the radiometric information analysis. The retrieval results from the 1 D-var algorithm show that the accuracy of MWTS-Ⅱ retrieval is similar to that of the MWHTS retrieval at the levels from 850-1,000 h Pa, is lower than that of the MWHTS retrieval at the levels from 650-850 h Pa and 125-300 h Pa, and is higher than that of MWHTS at the other levels. A comparison of the retrieved atmospheric temperature using these satellite observations provides a reference value for assessing the accuracy of atmospheric temperature detection at the 60 GHz oxygen band and 118.75 GHz oxygen line. In addition, based on the comparison of the retrieval results, an optimized combination method is proposed using a branch and bound algorithm for the NN retrieval algorithm, which combines the observations from both the MWTS-Ⅱand MWHTS instruments to retrieve the atmospheric temperature profiles. The results show that the optimal combination can further improve the accuracy of MWTS-Ⅱ retrieval and enhance the detection accuracy of atmospheric temperatures near the surface.

Sea surface wind speed retrieval under rain with the HY-2 microwave radiometer

As rain drops change the radiation and scattering characteristic of the oceans and the atmosphere, the wind speed measuring by spaceborne remote sensors under rainy conditions remains challenging for years. On the basis of a microwave radiometer（RM） loaded on HY-2 satellite, the sensitivity of some brightness temperature（TB）channels to a rain rate and the wind speed are analyzed. Consequently, two TB combinations which show minor sensitivity to rain are obtained. Meanwhile, the sensitivity of the TB combination to the wind speed is even better to the original TB channel. On the basis of these TB combinations, a wind speed retrieval algorithm is developed and compared with Wind Sat all-weather wind speed product, HY-2 RM original wind speed product and buoy in situ data. The wind speed retrieval accuracy is better than 2 m/s for rainy conditions, which is evidently superior to HY-2 RM original product. The applicability of this new algorithm is testified for the wind speed measuring in rainy weather with HY-2 RM.

Convolutional neural network for transient grating frequency-resolved optical gating trace retrieval and its algorithm optimization

A convolutional neural network is employed to retrieve the time-domain envelop and phase of few-cycle femtosecond pulses from transient-grating frequency-resolved optical gating(TG-FROG) traces.We use theoretically generated TGFROG traces to complete supervised trainings of the convolutional neural networks,then use similarly generated traces not included in the training dataset to test how well the networks are trained.Accurate retrieval of such traces by the neural network is realized.In our case,we find that networks with exponential linear unit(ELU) activation function perform better than those with leaky rectified linear unit(LRELU) and scaled exponential linear unit(SELU).Finally,the issues that need to be addressed for the retrieval of experimental data by this method are discussed.

A general phase retrieval algorithm based on a ptychographical iterative engine for coherent diffractive imaging

Coherent diffractive imaging （CDI） is a lensless imaging technique and can achieve a resolution beyond the Rayleigh or Abbe limit. The ptychographical iterative engine （PIE） is a CDI phase retrieval algorithm that uses multiple diffraction patterns obtained through the scan of a localized illumination on the specimen, which has been demonstrated successfully at optical and X-ray wavelengths. In this paper, a general PIE algorithm （gPIE） is presented and demonstrated with an He-Ne laser light diffraction dataset. This algorithm not only permits the removal of the accurate model of the illumination function in PIE, but also provides improved convergence speed and retrieval quality.

A Multi-stage Heuristic Algorithm for Matching Problem in the Modified Miniload Automated Storage and Retrieval System of E-commerce

E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.

Validation of MODIS ocean-colour products in the coastal waters of the Yellow Sea and East China Sea

An extensive study collected in situ data along the Yellow Sea(YS) and East China Sea(ECS) to assess the radiometric properties and the concentration of the water constituents derived from Moderate Resolution Imaging Spectroradiometer(MODIS). Thirteen high quality match-ups were obtained for evaluating the MODIS estimates of Rrs(λ), chlorophyll a(Chl a) and concentrations of suspended particulate sediment matter(SPM). For MODIS Rrs(λ), the mean absolute percentage difference(APD) was in the range of 20%–36%, and the highest uncertainty appeared at 412 nm, whereas the band ratio of Rrs(λ) at 488 nm compared with that at 547 nm was highly consistent, with an APD of 7%. A combination of near-infrared bands and shortwave infrared wavelengths atmosphere correction algorithm(NIR-SWIR algorithm) was applied to the MODIS data, and the estimation accuracy of Rrs were improved at most of the visible spectral bands except 645 nm, 667 nm and 678 nm. Two ocean-colour empirical algorithms for Chl a estimation were applied to the processed data, the results indicated that the accuracy of the derived Chl a values was obviously improved, the four-band algorithms outperformed the other algorithm for measured and simulated datasets, and the minimum APD was 35%. The SPM was also quantified. Two regional and two coastal SPM algorithms were modified according to the in situ data. By comparison, the modified Tassan model had a higher accuracy for the application along the YS and ECS with an APD of 21%. However, given the limited match-up dataset and the potential influence of the aerosol properties on atmosphere correction, further research is required to develop additional algorithms especially for the low Chl a coastal water.

A new algorithm of retrieving a petroleum substances absorption coefficient in sea water based on a remote sensing image

Establishing the remote sensing algorithm of retrieving the absorption coefficient of seawater petroleum substances is an efficient way to improve the accuracy of retrieving a seawater petroleum concentration using a remote sensing technology. A remote sensing reflectance is a basic physical parameter in water color remote sensing. Apply it to directly retrieve the absorption coefficient of seawater petroleum substances is of potential advantage. The absorption coefficient of waters containing petroleum [ACWCP, a_o（λ）], consists of the absorption coefficient of pure water [ACPW, a_w（λ）], plankton [ACP, a_（ph）（λ）], colored scraps [ACCS, a_（d,g）（λ）], and petroleum substance [ACPS, a_（oil）（λ）]. Among those, ACCS consists of the absorption coefficient of nonalgal particle [ACNP, a_d（λ）] and colored dissolved organic matter [ACCDOM, a_g（λ）]. For waters containing petroleum, the retrieved ACCS using the existing method is a combination absorption coefficient of ACNP,ACCDOM and ACPA [CAC, a_（d,g,oil）（λ）]. Therefore, the principle question is how to extract ACPS from CAC.Through the analysis of the three proportion tests conducted between the year of 2013 and 2015 and the corresponding remote sensing data, an algorithm of retrieving the absorption coefficient of petroleum substances is proposed based on remote sensing reflectance. First of all, ACPS and CAC are retrieved from the reflectance using the quasi-analytical algorithm（QAA）, with some parameter modified. Secondly, given the fact that the backscatter coefficient [BC, b_（bp）（555）] of total particles at 555 nm can be obtained completely from the reflectance, the relation between BC and ACNP in petroleum contaminated water can be established. As a result, ACNP can be calculated. Then, combining the remote sensing retrieving algorithm of a_g（440）, the method of achieving the spectral slope of the absorption coefficient can be established, from which ACCDOM,can be calculated. Finally, ACPS can be computed as the residual. The accuracy of ACPS based on this algorithm is 86% compared with the in situ measurements.

A New Global Solar-induced Chlorophyll Fluorescence(SIF)Data Product from TanSat Measurements

The Chinese Carbon Dioxide Observation Satellite Mission(TanSat)is the third satellite for global CO2 monitoring and is capable of detecting weak solar-induced chlorophyll fluorescence(SIF)signals with its advanced technical characteristics.Based on the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing(IAPCAS)platform,we successfully retrieved the TanSat global SIF product spanning the period of March 2017 to February 2018 with a physically based algorithm.This paper introduces the new TanSat SIF dataset and shows the global seasonal SIF maps.A brief comparison between the IAPCAS TanSat SIF product and the data-driven SVD(singular value decomposition)SIF product is also performed for follow-up algorithm optimization.The comparative results show that there are regional biases between the two SIF datasets and the linear correlations between them are above 0.73 for all seasons.The future SIF data product applications and requirements for SIF space observation are discussed.

Data Mining and Neural Network Techniques in Case Based System

This paper first puts forward a case based system framework based on data mining techniques. Then the paper examines the possibility of using neural networks as a method of retrieval in such a case based system. In this system we propose data mining algorithms to discover case knowledge and other algorithms.

Spatial heterodyne spectroscopy for space-based measurements of atmospheric CO_2

To reduce the error from measurement and retrieval process, a new technology of spatial heterodyne spectroscopy is proposed. The principle of this technology and the instrument spatial het- erodyne spectrometer （SHS） are introduced. The first application of this technology will be for CO2 measurements from space on a high spectral observation satellite. The outstanding measurement principle and the priority of combination of retrieval algorithm and three channels （ O2 A-band, CO2 1.58 μm and 2.06 μm bands） are theoretically analyzed and numerically simulated. Experiments u- sing SHS prototype with low spectral resolution of 0. 4 cm -1are carried out for preliminary valida- tion. The measurements show clear CO2 absorption lines and follow the expected signature with the- ory spectrum, and the retrievals agreed well with GOSAT CO2 products, except a small bias of about 4 × 10 ^-6. The results show that the ability of spatial heterodyne spectroscopy for CO2 detecting is ob- vious, and SHS is a competent sensor.

ACCURACY OF THE RETRIEVED TEMPERATURE AND HUMIDITY FIELDS FOR TYPHOON HAIYAN UTILIZING THE ADVANCED TECHNOLOGY MICROWAVE SOUNDER

One-dimensional retrieval was performed on Typhoon Haiyan utilizing the advanced technology microwave sounder onboard the satellite Suomi NPP to retrieve the temperature and water vapor profiles of the typhoon.Comparisons of the retrieved profiles and ECMWF reanalysis were made to assess the results. The main conclusions are as follows.(1) The results have high spatial resolution and therefore can precisely represent the temperature and humidity distribution of the typhoon.(2) The retrieved temperature is low in the areas of low temperature and high in the areas of high temperature; similar patterns are observed for humidity. This means that systematic revision may be needed during routine application.(3) The results of the retrieved temperature and humidity profiles are generally accurate, which is quite important for typhoon monitoring.

Deep-learning-based cryptanalysis of two types of nonlinear optical cryptosystems

The two types of nonlinear optical cryptosystems(NOCs)that are respectively based on amplitude-phase retrieval algorithm(APRA)and phase retrieval algorithm(PRA)have attracted a lot of attention due to their unique mechanism of encryption process and remarkable ability to resist common attacks.In this paper,the securities of the two types of NOCs are evaluated by using a deep-learning(DL)method,where an end-to-end densely connected convolutional network(DenseNet)model for cryptanalysis is developed.The proposed DL-based method is able to retrieve unknown plaintexts from the given ciphertexts by using the trained DenseNet model without prior knowledge of any public or private key.The results of numerical experiments with the DenseNet model clearly demonstrate the validity and good performance of the proposed the DL-based attack on NOCs.

Variation of Antarctic marginal ice zone extent (1989-2019)

The Antarctic marginal ice zone(MIZ)is the transition region between open water and consolidated pack ice,which is defined as an area with 15%-80%sea ice concentration.The MIZ represents the outer circle of Antarctic sea ice and the biological activity circle of Antarctic organisms,which provides a direct indication of the extent of Antarctic sea ice.In this study,the joint total variation and nonnegative constrained least square algorithm are applied to retrieve the Antarctic MIZ extent based on passive microwave data sets from 1989 to 2019.The spatial and temporal variations of the Antarctic MIZ extent and five regions are analyzed.The results show that the Antarctic MIZ extent follows a strong monthly variation pattern,decreasing from November to February and increasing from March to October.The annual MIZ extent is largest in the Weddell Sea and smallest in the Western Pacific Ocean.The edge of the sea ice begins to form a closed ring in May,which eventually closes near the Antarctic Peninsula.The ring width variation is large in summer,but generally stabilizes between 350 and 370 km in winter.The average latitude of the Antarctic MIZ is relatively stable in summer,but changes substantially in winter with a difference of approximately 3°.In October,the lowest mean latitude of the MIZ can reach 64.35°S.The sea surface pressure,2-m temperature,and 10-m wind speed are negatively correlated with the MIZ extent variation,among which the second-order partial correlation coefficient of the sea surface pressure and MIZ extent is−0.8773 in the Western Pacific Ocean.

Conditions Supporting Funnel Cloud Development in Alaska

The characteristics and climatology of funnel clouds in Alaska were examined using operational radiosondes, surface meteorological observations, and reanalysis data. Funnel clouds occurred under weak synoptic forcing between May and September between 11 am and 6 pm Alaska Daylight Time with a maximum occurrence in July. They occurred under Convective Available Potential Energy >500 J·kg-1 and strong low-level wind shear. Characteristic atmospheric profiles during funnel cloud events served to develop a retrieval algorithm based on similarity testing. Out of more than 129,000 soundings between 1971 and 2014, 2724, 442, and 744 profiles were similar to the profiles of observed funnel cloud events in the Interior, Alaska West Coast, and Anchorage regions. While the number of reported funnel clouds has increased since 2000, the frequency of synoptic situations favorable for such events has decreased.

Evaluation of regression algorithms for estimating leaf area index and canopy water content from water stressed rice canopy reflectance

Optical remote sensing(RS)with robust algorithms is needed for accurate assessment of crop canopy features.Despite intensive studies on algorithms,their performance using RS needs to be improved.We evaluated five different algorithms(partial-least-squares regression(PLSR),support vector regression(SVR),random forest regression(RFR),locally-weighted-PLSR(PLSRLW)and PLSR with feature selection(PLSRFS))for rapid assessment of leaf area index(LAI)and canopy water content(CWC)for rice canopies using canopy reflectance spectra over visible to short-wave infrared region.Two pooled datasets of LAI(600)and CWC(480)were collected from two replicated field experiments during 2014–15 and 2015–16 rice growing season.The performance of each algorithm was evaluated using coefficient of determination(R^(2)).Results showed that PLSRLW performed more accurately than other algorithms with R^(2) values 0.77 and 0.66 for LAI and CWC,respectively.We also used a bootstrapping approach to generate a kernel density estimator of root mean squared error values for each model.The results suggested that the improvement in prediction accuracy of LAI and CWC can be achieved if a suitable algorithm is selected by assigning higher weights to calibration samples,which has similar canopy structure as the test sample.Subsetting of the canopy spectral data results large error values in test dataset,therefore the use of entire season canopy spectral data should be used for model calibration.

A Retrieval Algorithm of Sheet Metal Parts Based on Relationships of Features

With the rapid increase in the number of three-dimensional （3D） models each year, to quickly and easily find the part desired has become a big challenge of enterprises. Meanwhile, many methods and algorithms have been proposed for part retrieval. However, most of the existing methods are designed lbr mechanical parts, and can not be well worked for sheet metal part re- trieval. An approach to feature-based retrieval of sheet metal parts is presented. Firstly, the features frequently used in sheet metal part design are chosen as the ＂＇key words＂ in retrieval. Based on those features, a relative position model is built to express the different relationships of the features in 3D space. Secondly, a description method of the model is studied. With the descrip- tion method the relative position of features in sheet metal parts can be expressed by four location description matrices. Thirdly, based on the relative position model and location description matrices, the equivalent definition of relationships of two feature groups is given which is the basis to calculate the similarity of two sheet metal parts. Next, the tbrmula of retrieval algorithm for sheet metal parts is given. Finally, a prototype system is developed to test and verify the effectiveness of the retrieval method suggested. Experiments verify that the new method is able to meet the requirements of searching sheet metal parts and possesses potentials in practical application.