Tracking typhoon-generated swell in the western North Pacific Ocean using satellite altimetry

This paper proposes a scheme for detecting the swell decay of a moving typhoon. We considered a typhoon that was neither far from a point source nor had a belt-like homogenous source,as previously studied. We tracked the swell close to the source during a typhoon in the western North Pacific Ocean. We used wind speed and significant wave height data derived from the Geophysical Data Record of the Jason-1 altimeter and the best-track information of the typhoon from the China Meteorological Administration tropical cyclone database. We selected three specific cases to reveal the decay characteristics of the swell generated by a moving typhoon. Based on an altimeter-based typhoon swell identification scheme and the dispersion relationship for deep water,we relocated the swell source for each altimeter measurement. The subsequent statistical decay coefficient was comparable to previous studies,and effectively depicted the swell propagation conditions induced by the typhoon. We hope that our results provide a new understanding of the characteristics and wave energy budget of the North Pacific Ocean,and significantly contribute to wave modeling in this region.     

Evaluating and correcting rain effects on dual-frequency altimeter Jason-1 wind measurements

Rain is one of the main sources of error in dual-frequency altimeter Jason-1 wind measurement. In this study, a new radar altimeter backscatter model is proposed and validated to eliminate rain effects. The model takes into account attenuation, volume backscattering, and sea surface perturbation by raindrops under rain conditions. A match-up dataset is built to evaluate rain effects, in combination with the Jason-1 normalized radar cross section, precipitation radar data from the Tropical Rainfall Measuring Mission, and sea surface wind reanalysis data from the European Centre for Medium-Range Weather Forecasts. The results show that rain-induced surface perturbation backscatter increases with rain rate at Ku-band, but their correlation at C-band is poor. In addition, rain surface perturbation and attenuation have major effects onradar altimeter wind measurements. Finally, a rain correction model for Jason-1 winds is developed and validation results prove its ability to reduce rain-induced inaccuracies in wind retrievals.     

Inversion of Evaporation and Water Vapor Transport Using HY-2 Multi-Sensor Data

HY-2 satellite is the first marine dynamic environment satellite of China.In this study,global evaporation and water vapor transport of the global sea surface are calculated on the basis of HY-2 multi-sensor data from April 1 to 30,2014.The algorithm of evaporation and water vapor transport is discussed in detail,and results are compared with other reanalysis data.The sea surface temperature of HY-2 is in good agreement with the ARGO buoy data.Two clusters are shown in the scatter plot of HY-2 and OAFlux evaporation due to the uneven global distribution of evaporation.To improve the calculation accuracy,we compared the different parameterization schemes and adopted the method of calibrating HY-2 precipitation data by SSM/I and Global Precipitation Climatology Project(GPCP)data.In calculating the water vapor transport,the adjustment scheme is proposed to match the balance of the water cycle for data in the low latitudes.     

Sea State Bias Estimation with Least Absolute Shrinkage and Selection Operator (LASSO)

With the sea-level rising, the measurement of sea surface height (SSH) is attracting more and more attention in the area of oceanography. Satellite radar altimeter is usually used to measure the SSH. However, deviation between the measured value and the actual one always exists. Among others, the sea state bias (SSB) is a main reason to cause the deviation. In general, one needs to estimate SSB first to correct the measured SSH. Currently, existing SSB estimation methods more or less have shortcomings, such as with many parameters, high prediction error and long training time. In this paper, we introduce an effective and efficient linear model called LASSO to the SSB estimation. The LASSO algorithm minimizes the residual sum of squares under the condition that the sum of the absolute values of each coefficient is less than a certain constant. In the implementation of LASSO, we use the significant wave height and wind speed to fit the LASSO model. Hence, the applied model has only 3 parameters, corresponding to the two inputs and a bias. Experimental results on the data of JASON-2, JASON-3, T/P and HY-2 radar altimetry show that LASSO performs better than geophysical data records (GDR) and ordinary least squares (OLS) estimator. Moreover, from the running time, we can see that LASSO is very efficient.     

A physics-based dual-frequency approach for altimeter wind speed retrieval

The altimeter normalized radar cross section(NRCS) has been used to retrieve the sea surface wind speed for decades, and more than a dozen of wind speed retrieval algorithms have been proposed. Despite the continuing efforts to improve the wind speed measurements, a bias dependence on wave state persists in all wind algorithms. On the basis of recent evidence that short waves are essentially modulated by local winds and much less affected by wave state, we proposed a physics-based approach to retrieve the wind speed from the dual-frequency difference in terms of the mean square slope of short waves. A collocated dataset of coincident altimeter/buoy measurements were used to develop and validate the approach. Validation against buoy measurements indicates that the approach is almost unbiased and has an overall root mean square error of 1.24 m s-1, which is 5.3% lower than the single-parameter algorithm in operational use(Witter and Chelton, 1991) and 2.4% lower than another dual-frequency approach(Chen et al., 2002). Furthermore, the results indicate that the new approach significantly improves the wave-dependent bias compared to the single-parameter algorithm. The capacity of altimeter to retrieve sea surface wind speed appears to be limited for the case of winds below 3 m s-1. The validity of the approach at high winds needs to be further examined in the future study.     

海洋卫星测高新技术-GPS测高

GPS测高是利用GPS测量技术以间接和直接的方式测量海平面到椭球面的高度.本文介绍GPS测高的概念,分别论述机载GPS测高和浮标GPS测高两种技术的基本原理及可能的应用范围,并阐述了我国开展GPS测高研究的重要意义和有利条件.     

Verification and recalibration of HY-2A microwave radiometer brightness temperature

HY-2A is the first one of the Chinese HY-2 ocean satellite series carrying a microwave radiometer(RM) to measure sea surface temperature,sea surface wind speed,atmospheric water vapor,cloud liquid water content, and rain rate. We verified the RM level 1B brightness temperature(T_B) to retrieve environmental parameters. In the verification, TB that simulated using the ocean-atmosphere radiative transfer model(RTM) was used as a reference. The total bias and total standard deviation(SD) of the RM level 1B T_B, with reference to the RTM simulation, ranged-20.6-4.38 K and 0.7-2.93 K, respectively. We found that both the total bias and the total SD depend on the frequency and polarization, although the values for ascending and descending passes are different. In addition, substantial seasonal variation of the bias was found at all channels. The verification results indicate the RM has some problems regarding calibration, e.g.,correction of antenna spillover and antenna physical emission, especially for the 18.7-GHz channel. Based on error analyses, a statistical recalibration algorithm was designed and recalibration was performed for the RM level 1B T_B. Validation of the recalibrated TB indicated that the quality of the recalibrated RM level 1B T_B was improved significantly. The bias of the recalibrated TB at all channels was reduced to 0.4 K, seasonal variation was almost eradicated, and SD was diminished(i.e., the SD of the 18.7-GHz channel was reduced by more than 0.5 K).     

Polar Sea Ice Identification and Classification Based on HY-2A/SCAT Data

In this paper,a Bayesian sea ice detection algorithm is first used based on the HY-2A/SCAT data,and a backpropagation(BP)neural network is used to classify the Arctic sea ice type.During the implementation of the Bayesian sea ice detection algorithm,linear sea ice model parameters and the backscatter variance suitable for HY-2A/SCAT were proposed.The sea ice extent obtained by the Bayesian sea ice detection algorithm was projected on a 12.5 km grid sea ice map and validated by the Advanced Microwave Scanning Radiometer 2(AMSR2)15%sea ice concentration data.The sea ice extent obtained by the Bayesian sea ice detection al-gorithm was found to be in good agreement with that of the AMSR2 during the ice growth season.Meanwhile,the Bayesian sea ice detection algorithm gave a wider ice edge than the AMSR2 during the ice melting season.For the sea ice type classification,the BP neural network was used to classify the Arctic sea ice type(multi-year and first-year ice)from January to May and October to De-cember in 2014.Comparison results between the HY-2A/SCAT sea ice type and Equal-Area Scalable Earth Grid(EASE-Grid)sea ice age data showed that the HY-2A/SCAT multi-year ice extent variation had the same trend as the EASE-Grid data.Classification errors,defined as the ratio of the mismatched sea ice type points between HY-2A/SCAT and EASE-Grid to the total sea ice points,were less than 12%,and the average classification error was 8.6%for the study period,which indicated that the BP neural network classification was a feasible algorithm for HY-2A/SCAT sea ice type classification.     

Comparison of sea surface wind field measured by HY-2A scatterometer and WindSat in global oceans

In this study, we present a comprehensive comparison of the sea surface wind ?eld measured by scatterometer(Ku-band scatterometer) aboard the Chinese HY-2 A satellite and the full-polarimetric radiometer WindSat aboard the Coriolis satellite. The two datasets cover a four-year period from October2011 to September 2015 in the global oceans. For the sea surface wind speed, the statistical comparison indicates good agreement between the HY-2 A scatterometer and WindSat with a bias of nearly 0 m/s and a root mean square error(RMSE) of 1.13 m/s. For the sea surface wind direction, a bias of 1.41° and an RMSE of 20.39° were achieved after excluding the data collocated with opposing directions. Furthermore,discrepancies in sea surface wind speed measured by the two sensors in the global oceans were investigated.It is found that the larger dif ferences mainly appear in the westerlies in the both hemispheres. Both the bias and RMSE show latitude dependence, i.e., they have signi?cant latitudinal ?uctuations.     

Interannual variability of SST,SLA and wind waves in the Hawaii area and their responses to ENSO

Time series of sea surface temperature (SST),wind speed and significant wave height (SWH) from meteorologicalbuoys of the National Data Buoy Center (NDBC) are useful for studying the interannual variability and trend of these quantities at the buoy areas.The measurements from 4 buoys (B51001,B51002,B51003 and B51004) in the Hawaii area are used to study theresponses of the quantities to EI Nino and Southern Oscillation (ENSO).Long-term averages of these data reflect precise seasonaland climatological characteristics of SST,wind speed and SWH around the Hawaii area.Buoy observations from B51001 suggest asignificant warming trend which is,however,not very clear from the other three buoys.Compared with the variability of SST andSWH,the wind speeds from the buoy observations show an increasing trend.The impacts of El Nifio on SST and wind waves arealso shown.Sea level data observed by altimeter during October 1992 to September 2006 are analyzed to investigate the variabilityof sea level in the Hawaii area.The results also show an increasing trend in sea level anomaly (SLA).The low-passed SLA in theHawaii area is consistent with the inverse phase of the low-passed Sol (Southern Oscillation Index).Compared with the low-passedSOl and PDO (Pacific Decadal Oscillation),the low-passed PNA (Pacific-North America Index) has a better correlation with thelow-passed SLA in the Hawaii area.     

Measurements of ocean wave and current field using dual polarized X-band radar

A new ocean wave and sea surface current monitoring system with horizontally-(HH) and vertically-(VV) polarized X-band radar was developed. Two experiments into the use of the radar system were carried out at two sites, respectively, for calibration process in Zhangzi Island of the Yellow Sea, and for validation in the Yellow Sea and South China Sea. Ocean wave parameters and sea surface current velocities were retrieved from the dual polarized radar image sequences based on an inverse method. The results obtained from dual-polarized radar data sets acquired in Zhangzi Island are compared with those from an ocean directional buoy. The results show that ocean wave parameters and sea surface current velocities retrieved from radar image sets are in a good agreement with those observed by the buoy. In particular, it has been found that the vertically-polarized radar is better than the horizontally-polarized radar in retrieving ocean wave parameters, especially in detecting the significant wave height below 1.0 m.     

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MEAN SEA LEVEL AND SEA SURFACE VARIABILITY OF NQRTHWEST PACIFIC OCEAN AND EASTERN CHINA SEAS FROM GEOSAT ALTIMETRY

Collinear analysis technique is widely used for determining sea surface variability with Geosat altimeterdata from its Exact Repeat Mission(ERM).But most of the researches have been only on global scaleor in oceans deeper than 2000 m.In shallow shelf waters this method is hampered by the inaccuracy ofocean tide data supplied with Geosat Geophysical Data Records(GDRs).This work uses a modified collinearanalysis technique characterized by simultaneous separation of mean sea level and ocean tide with theleast squares method,to compute sea surface variability in the Northwest Pacific Ocean and eastern ChinaSeas.The mean sea level map obtained contains not ouly bathymetric but also dynamic features such asamphidromes,indicating considerable improvement over previous works.Our sea surface variability mapsshow clearly the main current system,the well-known Zhejiang coastal upwelling,and a northern East Chi-na Sea meso-scale eddy in good agreement with satellite sea surface temperature(SST)observation and his-to     

HY-2B星载GPS数据质量及简化动力学精密定轨分析

对HY-2B卫星星载GPS数据进行质量检查,分析伪随机脉冲先验值对简化动力学精密定轨的影响。结果发现,在所有时间间隔中,先验标准差为1×10^-8 m/s²时定轨精度最高,最优伪随机脉冲时间间隔为6 min。估计天线相位中心变化（PCV）,分析不同分辨率（10°×10°、5°×5°）PCV模型对定轨结果的影响,并使用载波相位残差、重叠轨道比较和SLR检核对定轨结果进行检验。结果表明,99%以上的历元能观测到4颗以上GPS卫星,数据完整率达到99.65%,L1、L2波段的多路径误差RMS均值分别为15.7 cm、9.5 cm,证明HY2国产接收机性能良好。轨道内符合精度均达到cm级;未加PCV模型时,SLR检核RMS值为27.8 mm,加入10°×10°、5°×5° PCV模型后,SLR检核RMS值分别提高0.9 mm和1.2 mm,说明轨道外符合精度也达到cm级。     

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基于TRACK的GPS海浪测量方法

针对现有GPS海浪测量技术的不足,提出基于TRACK的GPS海浪测量方法,即利用TRACK解得海上载体高精度的垂向位移,经浪潮分离提取海浪信号,采用周期图法估计海浪信号的功率谱,计算海浪要素。利用实测数据进行实验,结果表明,平均波高和平均周期与测波仪结果差异分别小于2 cm和0.25 s,验证了本文方法的有效性。     

Jason-2测高卫星对湖泊水位的监测精度评价

湖泊水位是评估湖泊水量变化的重要指标。本文以洪泽湖、高邮湖及洞庭湖为研究对象,利用集中度的概率密度函数方法(CPDF)来提高Jason-2测高数据精度,分析了降水量与各个湖泊水位变化的相关性,并基于实测水位数据对比评价了Jason-2测高卫星原始GDR数据和CPDF方法处理后的卫星数据的精度。结果表明:①Jason-2原始GDR数据点的分布存在疏密之分,大部分数据分布相对集中,且有一定的周期变化,但评价结果显示精度较差,故原始GDR数据不能直接用于湖泊水位监测;②CPDF方法可以极大提高测高卫星的水位数据精度,洪泽湖与高邮湖的均方根误差分别由1.92 m与1.74 m减少到了0.32 m和0.36 m,相关系数由0.28和0.04提高到了0.85和0.72。对于南北宽度较窄且日水位变化较大的湖泊(如洞庭湖),CPDF方法提高原始GDR结果的精度有限;③洞庭湖降水与水位相关性最强,高邮湖次之,而洪泽湖降水与水位成不显著的负相关,是洪泽湖水利工程对于水位的调节导致了这一结果。本研究对于利用测高卫星获得湖泊水位值,进而对湖泊进行动态监控,特别是在填补资料匮乏地区湖泊水位数据方面具有重要意义。