Comparison of two wind algorithms of ENVISAT ASAR at high wind

Two wind algorithms of ENVISAT advanced synthetic aperture radar (ASAR), i. e. CMOD4 model from the European Space Agency (ESA) and CMOD IFR2 model from Quilfen et al., are compared in this paper. The wind direction is estimated from orientation of low and linear signatures in the ASAR imagery. The wind direction has inherently a 180° ambiguity since only a single ASAR image is used. The 180° ambiguity is eliminated by using the buoy data from the NOAA (National Oceanic and Atmospheric Administration) buoys moored in the Pacific. Wind speed is obtained with the two wind algorithms using both estimated wind direction and normalized radar cross section (NRCS). The retrieved wind results agree well with the data from Quikscat. The root mean square error (RMSE) of wind direction is 2.80? The RMSEs of wind speed from CMOD4 model and CMOD_IFR2 model are 1.09 m/s and 0.60 m/s, respectively. The results indicate that the CMOD_IFR2 model is slight better than CMOD4 model at high wind.     

Comparison of remote sensing data with in-situ wind observation during the development of the South China Sea monsoon

Wind measurements derived from QuikSCAT data were compared with those measured by anemometer on Yongxing Island in the South China Sea (SCS) for the period from April 2008 to November 2009. The comparison confirms that QuikSCAT estimates of wind speed and direction are generally accurate, except for the extremes of high wind speeds (>13.8m/s) and very low wind speeds (<1.5m/s) where direction is poorly predicted. In-situ observations show that the summer monsoon in the northern SCS starts between May 6 and June 1. From March 13, 2010 to August 31, 2010, comparisons of sea surface temperature (SST) and rainfall from AMSR-E with data from a buoy located at Xisha Islands, as well as wind measurements derived from ASCAT and observations from an automatic weather station show that QuikSCAT, ASCAT and AMSR-E data are good enough for research. It is feasible to optimize the usage of remote-sensing data if validated with in-situ measurements. Remarkable changes were observed in wind, barometric pressure, humidity, outgoing longwave radiation (OLR), air temperature, rainfall and SST during the monsoon onset. The eastward shift of western Pacific subtropical high and the southward movement of continental cold front preceded the monsoon onset in SCS. The starting dates of SCS summer monsoon indicated that the southwest monsoon starts in the Indochinese Peninsula and forms an eastward zonal belt, and then the belt bifurcates in the SCS, with one part moving northeastward into the tropical western North Pacific, and another southward into western Kalimantan. This largely determined the pattern of the SCS summer monsoon. Wavelet analysis of zonal wind and OLR at Xisha showed that intra-seasonal variability played an important role in the summer. This work improves the accuracy of the amplitude of intra-seasonal and synoptic variation obtained from remote-sensed data.     

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.     

A new algorithm for sea-surface wind-speed retrieval based on the L-band radiometer onboard Aquarius

Aquarius is the second satellite mission to focus on the remote sensing of sea-surface salinity from space and it has mapped global sea-surface salinity for nearly 3 years since its launch in 2011. However,benefiting from the high atmospheric transparency and moderate sensitivity to wind speed of the L-band brightness temperature(TB),the Aquarius L-band radiometer can actually provide a new technique for the remote sensing of wind speed. In this article,the sea-surface wind speeds derived from TBs measured by Aquarius' L-band radiometer are presented,the algorithm for which is developed and validated using multisource wind speed data,including Wind Sat microwave radiometer and National Data Buoy Center buoy data,and the Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory wind field product. The error analysis indicates that the performance of retrieval algorithm is good. The RMSE of the Aquarius wind-speed algorithm is about 1 and 1.5 m/s for global oceans and areas of tropical hurricanes,respectively. Consequently,the applicability of using the Aquarius L-band radiometer as a near all-weather wind-speed measuring method is verified.     

Retrieval algorithm of sea surface wind vectors for WindSat based on a simple forward model

WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center (NDBC), root mean square errors are 1.2 m/s and 30° for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.     

Chaos particle swarm optimization combined with circular median filtering for geophysical parameters retrieval from Windsat

This paper established a geophysical retrieval algorithm for sea surface wind vector, sea surface temperature, columnar atmospheric water vapor, and columnar cloud liquid water from WindSat, using the measured brightness temperatures and a matchup database. To retrieve the wind vector, a chaotic particle swarm approach was used to determine a set of possible wind vector solutions which minimize the difference between the forward model and the WindSat observations. An adjusted circular median filtering function was adopted to remove wind direction ambiguity. The validation of the wind speed, wind direction, sea surface temperature, columnar atmospheric water vapor, and columnar liquid cloud water indicates that this algorithm is feasible and reasonable and can be used to retrieve these atmospheric and oceanic parameters. Compared with moored buoy data, the RMS errors for wind speed and sea surface temperature were 0.92 m s~(-1) and 0.88℃, respectively. The RMS errors for columnar atmospheric water vapor and columnar liquid cloud water were 0.62 mm and 0.01 mm, respectively, compared with F17 SSMIS results. In addition, monthly average results indicated that these parameters are in good agreement with AMSR-E results. Wind direction retrieval was studied under various wind speed conditions and validated by comparing to the Quik SCAT measurements, and the RMS error was 13.3?. This paper offers a new approach to the study of ocean wind vector retrieval using a polarimetric microwave radiometer.     

Observation and numerical experiments for drag coefficient under typhoon wind forcing

This paper presents a study on drag coefficients under typhoon wind forcing based on observations and numerical experiments. The friction velocity and wind speed are measured at a marine observation platform in the South China Sea. Three typhoons: SOULIK(2013), TRAMI(2013) and FITOW(2013) are observed at a buoy station in the northeast sea area of Pingtan Island. A new parameterization is formulated for the wind drag coefficient as a function of wind speed. It is found that the drag coefficient(Cd) increases linearly with the slope of 0.083′10~(-3) for wind speed less than 24 m s~(-1). To investigate the drag coefficient under higher wind conditions, three numerical experiments are implemented for these three typhoons using SWAN wave model. The wind input data are objective reanalysis datasets, which are assimilated with many sources and provided every six hours with the resolution of 0.125?×0.125?. The numerical simulation results show a good agreement with wave observation data under typhoon wind forcing. The results indicate that the drag coefficient levels off with the linear slope of 0.012′10~(-3) for higher wind speeds(less than 34 m s~(-1)) and the new parameterization improvese the simulation accuracy compared with the Wu(1982) default used in SWAN.     

Numerical simulation of wave field in the South China Sea using WAVEWATCH III

Wave fi elds of the South China Sea(SCS) from 1976 to 2005 were simulated using WAVEWATCH III by inputting high-resolution reanalysis wind fi eld datasets assimilated from several meteorological data sources. Comparisons of wave heights between WAVEWATCH III and TOPEX/Poseidon altimeter and buoy data show a good agreement. Our results show seasonal variation of wave direction as follows: 1. During the summer monsoon(April–September), waves from south occur from April through September in the southern SCS region, which prevail taking about 40% of the time; 2. During the winter monsoon(December–March), waves from northeast prevail throughout the SCS for 56% of the period; 3. The dominant wave direction in SCS is NE. The seasonal variation of wave height H s in SCS shows that in spring, H s ≥1 m in the central SCS region and is less than 1 m in other areas. In summer, H s is higher than in spring. During September–November, infl uenced by tropical cyclones, H s is mostly higher than 1 m. East of Hainan Island, H s 2 m. In winter, H s reaches its maximum value infl uenced by the north-east monsoon, and heights over 2 m are found over a large part of SCS. Finally, we calculated the extreme wave parameters in SCS and found that the extreme wind speed and wave height for the 100-year return period for SCS peaked at 45 m/s and 19 m, respectively, SE of Hainan Island and decreased from north to south.     

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.     

Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data

Synthetic aperture radar(SAR)is a suitable tool to obtain reliable wind retrievals with high spatial resolution.The geophysical model function(GMF),which is widely employed for wind speed retrieval from SAR data,describes the relationship between the SAR normalized radar cross-section(NRCS)at the copolarization channel(vertical-vertical and horizontal-horizontal)and a wind vector.SAR-measured NRCS at cross-polarization channels(horizontal-vertical and vertical-horizontal)correlates with wind speed.In this study,a semi-empirical algorithm is presented to retrieve wind speed from the noisy Chinese Gaofen-3(GF-3)SAR data with noise-equivalent sigma zero correction using an empirical function.GF-3 SAR can acquire data in a quad-polarization strip mode,which includes cross-polarization channels.The semi-empirical algorithm is tuned using acquisitions collocated with winds from the European Center for Medium-Range Weather Forecasts.In particular,the proposed algorithm includes the dependences of wind speed and incidence angle on cross-polarized NRCS.The accuracy of SAR-derived wind speed is around 2.10ms−1 root mean square error,which is validated against measurements from the Advanced Scatterometer onboard the Metop-A/B and the buoys from the National Data Buoy Center of the National Oceanic and Atmospheric Administration.The results obtained by the proposed algorithm considering the incidence angle in a GMF are relatively more accurate than those achieved by other algorithms.This work provides an alternative method to generate operational wind products for GF-3 SAR without relying on ancillary data for wind direction.     

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.     

Comparison and analysis of Envisat ASAR ocean wave spectra with buoy data in the northern Pacific Ocean

The validation and assessment of Envisat advanced synthetic aperture radar (ASAR) ocean wave spectra products are important to their application in ocean wave numerical predictions. Six-year ASAR wave spectra data are compared with one-dimensional (1D) wave spectra of 55 co-located moored buoy observations in the northern Pacific Ocean. The ASAR wave spectra data are firstly quality control filtered and spatio-temporal matched with buoy data. The comparisons are then performed in terms of 1D wave spectra, significant wave height (SWH) and mean wave period (MWP) in different spatio-temporal offsets respectively. SWH comparison results show the evident dependence of SWH biases on wind speed and the ASAR SWH saturation effect. The ASAR wave spectra tend to underestimate SWH at high wind speeds and overestimate SWH at low wind speeds. MWP comparison results show that MWP has a systematic bias and therefore it should be bias-modified before used. The comparisons of 1D wave spectra show that both wave spectra agree better at low frequencies than at high frequencies, which indicates the ASAR data cannot resolve the high frequency waves.     

郑州市市区风环境模拟研究

城市风环境是城市微气候研究的一个重要方向,对分析城市热岛效应、空气流通等具有重要意义。本文以郑州市市区为例,使用1971—2018年气象观测数据、2018年建筑分布数据（OSM）和2016年资源三号卫星数据作为数据源,通过运用气象学和GIS技术结合的方法,探究潜在通风廊道,科学量化城市形态对风环境的影响。研究首先借助WindNinja软件,对城市背景风环境进行模拟分析,该计算方法提高了风道定位的精度。然后利用卫星遥感数据制作了数字高程模型（DSM）,结合OSM计算下垫面地表粗糙度。进一步借助ArcGIS软件,利用最小成本路径法（LCP）确定城市潜在通风廊道的位置。结果表明：① 郑州市近年来平均风速缓慢下降,平均每10年下降0.26 m/s;全年主导风向东北风进入城市后受城市形态影响在京广铁路线附近以西逐渐转为东北偏东风,其中在京广快速路以东风速较高,在京广快速路以西风速较低;② 金水区西部、中原区、二七区以及管城区的地表粗糙度较高,通风环境较差;金水区东部和惠济区的地表粗糙度较低,通风环境较好;③根据盛行风向模拟的潜在通风廊道,其共同特点是趋向于低粗糙度的地区。     

基于静风期污染物的PM2.5排放清单空间精细化方法

有利气象条件之后的静风期,极大降低了PM_2.5跨区域传输的影响,能够揭示本地源的排放状况。本文尝试性引入了静风期污染物分布揭示本地源排放特征的概念,提出了一种基于遥感数据的PM_2.5排放清单空间精细化方法：首先,利用 MODIS MCD19A2反演的ChinaHighPM_2.5数据,构建高时空分辨率PM_2.5数据融合方法;然后,构建唐山市有利气象条件之后的静风期污染物遴选方法（合理风向和风速：有利气象条件为东风,地面10 m高度风速大于3 m/s,其他风向,持续的较大风力5~10 m/s;静风期风速小于1.5~2.0 m/s）;其次,基于遴选的静风期PM_2.5数据分配MEIC清单中的PM_2.5总排放量,同时对比传统插值方法：基于GDP、人口密度、路网、土地利用类型数据,实现清单各污染源PM_2.5的1 km×1 km空间分配;最后,利用WRF-CMAQ模拟数据和地面台站实测数据进行真实性检验。研究结果表明：① PM_2.5数据填补融合方法能够有效提高PM_2.5监测数据的时空分辨率,且与地面监测值显著相关（R²=0.94,RMSE=4.64 µg/m³,NMB=2%,NME=7%）;② 引入有利气象条件后的静风期概念,提出了静风期污染物的遴选方法,有效降低了PM_2.5跨区域传输的影响,更好地反映了本地源排放的空间分布特征;③ WRF-CMAQ模拟方法的精度验证结果表明,该方法较传统面积插值法NME降低7%,NMB降低10%,RMSE降低1.54 µg/m³,R²提高11%。该方法为排放清单的空间精细化提供了新的研究思路。     

Satellite retrieval of hurricane wind speeds using the AMSR2 microwave radiometer

The AMSR2 microwave radiometer is the main payload of the GCOM-W1 satellite,launched by the Japan Aerospace Exploration Agency in 2012. Based on the pre-launch information extraction algorithm,the AMSR2 enables remote monitoring of geophysical parameters such as sea surface temperature,wind speed,water vapor,and liquid cloud water content. However,rain alters the properties of atmospheric scattering and absorption,which contaminates the brightness temperatures measured by the microwave radiometer. Therefore,it is difficult to retrieve AMSR2-derived sea surface wind speeds under rainfall conditions. Based on microwave radiative transfer theory,and using AMSR2 L1 brightness temperature data obtained in August 2012 and NCEP reanalysis data,we studied the sensitivity of AMSR2 brightness temperatures to rain and wind speed,from which a channel combination of brightness temperature was established that is insensitive to rainfall,but sensitive to wind speed. Using brightness temperatures obtained with the proposed channel combination as input parameters,in conjunction with HRD wind field data,and adopting multiple linear regression and BP neural network methods,we established an algorithm for hurricane wind speed retrieval under rainfall conditions. The results showed that the standard deviation and relative error of retrievals,obtained using the multiple linear regression algorithm,were 3.1 m/s and 13%,respectively. However,the standard deviation and relative error of retrievals obtained using the BP neural network algorithm were better(2.1 m/s and 8%,respectively). Thus,the results of this paper preliminarily verified the feasibility of using microwave radiometers to extract sea surface wind speeds under rainfall conditions.     

广西山地风能资源开发利用可行性分析——以大容山为例

利用大容山自动观测站2004年8月～2006年7月气象观测资料和容县气象站1958～2006年7月测风资料,对大容山的风能资源各参数进行了详细计算和分析,并结合预选风电场的地形地貌、交通运输、联网条件、环境保护等状况对大容山风能资源开发利用进行了可行性分析评价.结果表明：大容山年平均风速为7.2m/s,年平均风功率密度为390.8W/m^2,其风能资源丰富,且交通运输、联网、工程地质等条件较好,可选择在坡度较小的山头或山腰建设风电场,预选风电场可布置750kW的风机45台,总装机容量约为34MW.     

Surface circulation patterns observed by drifters in the Yellow Sea in summer of 2001, 2002 and 2003

In summer of 2001, 2002 and 2003, ten, six and seventeen satellite-tracked surface drifters with drogues centered at 15 and 4 m were deployed, respectively, in the southern Yellow Sea (YS). 23 drifters of them transmitted useful data of at least 30 days. The wind-driven component of the drift was removed from the original drift velocity of drifters. The wind data used are from NCEP (National Center for Environmental Prediction), USA.Trajectories and drift velocities of the 23 drifters depicted the upper circulation structure in the southern YS. There exists an anti-cyclonic eddy with a mean speed and radius of 0.063 m/s and 50km in the central southern YS, whose center lingered within 35.3-36.0°N / 123.5-124.0°E. Showed by 6 drifters, a basin-scale elliptic cyclonic gyre with a mean speed of 0.114 m/s, long and short radius of 250 and 200 km surrounds the anti-cyclonic eddy. In the southwestern part of the southern YS has obvious frontal eddy activities within about 100 km with a mean speed about 0.076     

基于高斯曲线拟合-FFT方法的南海风场反演

海面风场是海洋学的基本参量,获取海面风场对了解海洋的物理过程以及海洋与大气之间的相互作用至关重要。宽阔的海域面积及复杂的海面状况通常使南海海面上的风场信息很难被及时获取。ENVISAT ASAR是一种全天候全天时监测海面的微波雷达传感器,可实时获取海面风场数据。本文基于已有ASAR数据对南海海面风场进行反演实验,首先将结合高斯曲线拟合的FFT风向反演方法应用于南海风向反演,并参考Cross-Calibrated Multi-Platform （CCMP）风场数据去除180o方向模糊获得海面风向。然后,将高斯曲线拟合-FFT风向与传统的峰值-FFT风向进行对比,最后将准确率较高的高斯曲线拟合-FFT风向分别输入CMOD4模型和CMOD5模型获得海面风速大小。实验结果与CCMP参考数据的比较结果表明,在风条纹不明显的情况下,利用结合高斯曲线的FFT风向反演方法和CMOD4模型风速反演方法可有效地进行南海海面风场反演。该成果对利用SAR数据实时获取南海大面积海面风场信息,尤其是观测点缺乏海域的风场信息,具有重要的指导意义。     

HY-2散射计风速降雨影响的神经网络校正

海洋二号搭载的笔形圆锥扫描微波散射计(HY2-scat)是国内第一个业务化运行的,可提供大量实时海面风场数据的微波传感器。由于Ku波段散射计测风原理和微波传输特性,受到降雨影响的散射计反演风场数据准确度降低。降雨导致的微波传播路径衰减,雨滴对微波直接后向散射导致的回波能量增加和雨滴对海表面毛细波的干扰等综合效应,使得降雨条件下散射计测风风速计算值偏高,风向计算值偏差较大。针对散射计反演风速受降雨影响的特点引入神经网络模型,使用准确度较高的NWP数值预报模式风场数据作为参考,对受降雨影响的HY-2散射计反演L2B级标准风场数据产品进行校正,改进HY-2散射计反演风矢量在降雨条件下的准确度。与受降雨影响的散射计反演风场风速偏差相比较,经过神经网络校正后的风速偏差减小,说明该方法适用于改善受降雨影响的HY-2散射计测风风速精度。     

Seasonal variations of the near surfacelayer parameters over the Antarctic ice sheet in Princess Elizabeth Land,East Antarctica

Analysis of sensible heat flux(Qh),latent heat flux(Qe),Richardson number(Ri),bulk transport coefficient(Cd) and katabatic winds are presented by using the meteorological data in the near surface layer from an automatic weather station(AWS) in Princess Elizabeth Land,East Antarctica ice sheet and the data of corresponding period at Zhongshan station in 2002.It shows that annual mean air temperature at LGB69 is-25.6°C,which is 16.4°C lower than that at Zhongshan,where the elevation is lower and located on the coast.The temperature lapse rate is about 1.0°C/110 m for the initial from coast to inland.The turbulence heat flux at LGB69 displays obvious seasonal variations with the average sensible heat flux-17.9 W/m2 and latent heat flux-0.9 W/m2.The intensity(Qh Qe) of coolling source is-18.8 W/m2 meaning the snow surface layer obtains heat from atmosphere.The near surface atmosphere is near-neutral stratified with bulk transport coefficients(Cd) around 2.8×10-3,and it is near constant when the wind speed higher than 8 m/s.The speed and the frequency of easterly Katabatic winds at LGB69 were higher than that at Zhongshan Station.