Evaluation of Vector Winds Observed by NSCAT in the Seas around Japan

In order to validate wind vectors derived from the NASA Scatterometer (NSCAT), two NSCAT wind products of different spatial resolutions are compared with observations by buoys and research vessels in the seas around Japan. In general, the NSCAT winds agree well with the wind data from the buoys and vessels. It is shown that the root-mean-square (rms) difference between NSCAT-derived wind speeds and the buoy observations is 1.7 ms^–1, which satisfies the mission requirement of accuracy, 2 ms^–1. However, the rms difference of wind directions is slightly larger than the mission requirement, 20°. This result does not agree with those of previous studies on validation of the NSCAT-derived wind vectors using buoy observations, and is considered to be due to differences in the buoy observation systems. It is also shown that there are no significant systematic trends of the NSCAT wind speed and direction depending on the wind speed and incidence angle. Comparison with ship winds shows that the NSCAT wind speeds are lower than those observed by the research vessels by about 0.7 ms^–1 and this bias is twice as large for data observed by moving ships than by stationary ships. This result suggests that the ship winds may be influenced by errors caused by ship's motion, such as pitching and rolling.     

Validation and accuracy analysis of wind products from scatterometer onboard the HY-2B satellite

The Chinese marine dynamic environment satellite HY-2B was launched in October 2018 and carries a Ku-band scatterometer. This paper focuses on the accuracies of HY-2B scatterometer wind data during the period from November 2018 to May 2021. The HY-2B wind data are validated against global moored buoys operated by the U.S. National Data Buoy Center and Tropical Atmosphere Ocean, numerical model data by the National Centers for Environmental Prediction, and the Advanced Scatterometer data issued b...     

使用参数化初猜测谱算法提取VV极化Sentinel-1 SAR图像的海浪要素并与ECMWF再分析数据以及浮标数据进行验证对比

The purpose is to study the accuracy of ocean wave parameters retrieved from C-band VV-polarization Sentinel-1Synthetic Aperture Radar(SAR) images, including both significant wave height(SWH) and mean wave period(MWP), which are both calculated from a SAR-derived wave spectrum. The wind direction from in situ buoys is used and then the wind speed is retrieved by using a new C-band geophysical model function(GMF) model,denoted as C-SARMOD. Continuously, an algorithm parameterized first-guess spectra method(PFSM) is employed to retrieve the SWH and the MWP by using the SAR-derived wind speed. Forty–five VV-polarization Sentinel-1 SAR images are collected, which cover the in situ buoys around US coastal waters. A total of 52 subscenes are selected from those images. The retrieval results are compared with the measurements from in situ buoys. The comparison performs good for a wind retrieval, showing a 1.6 m/s standard deviation(STD) of the wind speed, while a 0.54 m STD of the SWH and a 2.14 s STD of the MWP are exhibited with an acceptable error.Additional 50 images taken in China's seas were also implemented by using the algorithm PFSM, showing a 0.67 m STD of the SWH and a 2.21 s STD of the MWP compared with European Centre for Medium-range Weather Forecasts(ECMWF) reanalysis grids wave data. The results indicate that the algorithm PFSM works for the wave retrieval from VV-polarization Sentinel-1 SAR image through SAR-derived wind speed by using the new GMF C-SARMOD.     

The wind-speed measurement capability of spaceborne radar altimeters

This study represents an attempt to quantitatively assess the capability of a spaceborne radar altimeter to infer ocean surface wind speeds from a measurement of the backscattered power at vertical incidence. The study uses data acquired during 184 near overflights of NOAA data buoys with the GEOS-3 satellite radar altimeter and encompasses a wind-speed range from less than 1 to 18 m/s. An algorithm is derived from the data comparison for converting measurements of the normalized scattering cross section of the ocean surface at 13.9 GHz into estimates of the surface wind speed at the standard anemometer height of 10 m. The algorithm is straightforward and potentially useful for on-board processing of raw altimeter data for the purpose of providing real-time estimates of surface wind speed. For winds in the range of 1 to 18 m/s, the mean difference between the altimeter-inferred winds and the buoy measurements is negligible while the standard deviation of the difference is 1.74 m/s.     

近海工程环境应用中各种风资料的平均时间分析

本文从近海工程设计应用的需要出发，对于通常使用的不同来源的测风资料平均时间进行了分析，这些资料来源包括：岸边及近海探查与生产设施上的气象台站、天气观测船、浮标、商船气象报、从受灾情况估计出的极大风速以及动力诊断模型估计出的海面风速。     

HY-2B卫星散射计海面风场产品质量分析 *

星载微波散射计是获取全球海面风场信息的主要手段, HY-2B卫星散射计的成功发射为全球海面风场数据获取的持续性提供了重要保障。本文利用欧洲中期天气预报中心(European Center for Medium-Range Weather Forecasts, ECMWF)再分析风场数据、热带大气海洋观测计划(Tropical Atmosphere Ocean Array, TAO)和美国国家数据浮标中心(National Data Buoy Center, NDBC)浮标获取的海面风矢量实测数据, 对HY-2B散射计海面风场数据产品的质量进行统计分析。分析表明, HY-2B风场与ECMWF再分析风场对比, 在4~24m·s^-1风速区间内, 风速和风向均方根误差(root mean square error, RMSE)分别为1.58m·s^-1和15.34°; 与位于开阔海域的TAO浮标数据对比, 风速、风向RMSE分别为1.03m·s^-1和14.98°, 可见HY-2B风场能较好地满足业务化应用的精度要求(风速优于2m·s^-1, 风向优于20°)。与主要位于近海海域的NDBC浮标对比, HY-2B风场的风速、风向RMSE分别为1.60m·s^-1和19.14°, 说明HY-2B散射计同时具备了对近海海域风场的良好观测能力。本文还发现HY-2B风场质量会随风速、地面交轨位置等变化, 为用户更好地使用HY-2B风场产品提供参考。     

Spatio-temporal variability in sea surface wind stress near and off the east coast of Korea

Sea surface wind stress variabilities near and off the east coast of Korea, are examined using 7 kinds of wind datasets from measurements at 2 coastal (land) stations and 2 ocean buoys,satellite scatterometer (QuikSCAT), and global reanalyzed products (ECMWF,NOGAPS,and NCEP/NCAR). Temporal variabilities are analyzed at 3 frequency bands; synoptic (2-20 d), intra-seasonal (20-90 d),and seasonal (>90 d).Synoptic and intra-seasonal     

唐山近海海域波浪要素特征分析

本文基于唐山近海海域1#、2#浮标2017年4月至11 月实时海浪观测数据及部分风速风向数据, 对唐山近海海域波浪有效波高、有效波向、有效波周期等波参数特征进行了统计分析, 并利用origin 软件对波参数与风速、风向相关性进行了研究。研究结果表明： 1#、2# 浮标海域常浪向为SSW、SW、SSE, 常浪向有效波高均以0.2 ～ 0.4 m 小浪及3 ～ 4 s 短周期为主,有效波高1 m 以上较大波浪极少出现; 该海域波浪以风浪为主, 波浪破碎速度较快, 有效波高与风速相关性较强, 相关系数r 为0.71, 风向与波向、有效波高与周期基本无相关性, 该研究资料可为海上活动及防灾减灾提供技术依据。     

Impact of wind/wind-stress field in the North Pacific constructed by ADEOS/NSCAT data

Data sets of surface wind and wind-stress fields in the North Pacific from September 1996 to June 1997 have been constructed using NASA Scatterometer (NSCAT) data on-board ADEOS to investigate their variability and implications for the wind-driven oceanic circulation. Using a weighting function decreasing with the distance between each grid and data points, and of Gaussian type for time, daily, 10-day and monthly averages are calculated for each 1°×1° grid. Products are validated by comparison with those calculated from in-situ measurement data at oceanic buoys around Japan (JMA) and in the equatorial area (TAO). The RMS differences for wind direction and speed never exceed 20° and 2 ms⁻¹, respectively, for the TAO buyos. This does not hold for data taken by JMA buoys, suggesting that the reliability in the mid-latitudes is not good for time averages shorter than several days. Zonal integration of the Sverdrup transport in a zone of 28°–30°N calculated from the monthly-mean products ranges between 25 and 60×10⁶ m³s⁻¹ (Sv) around its mean of 38 Sv. These are not so different from the Kuroshio transport values calculated from oceanic measurements.     

Evaluation of reanalysis surface wind products with quality-assured buoy wind measurements along the north coast of the South China Sea

Three archived reanalysis wind vectors at 10 m height in the wind speed range of 2–15 m/s, namely, the second version of the National Centres for Environmental Prediction(NCEP) Climate Forecast System Reanalysis(CFSv2), European Centre for Medium-Range Weather Forecasting Interim Reanalysis(ERA-I) and NCEPDepartment of Energy(DOE) Reanalysis 2(NCEP-2) products, are evaluated by a comparison with the winds measured by moored buoys in coastal regions of the South China Sea(SCS). The buoy data are first quality controlled by extensive techniques that help eliminate degraded measurements. The evaluation results reveal that the CFSv2 wind vectors are most consistent with the buoy winds(with average biases of 0.01 m/s and 1.76°). The ERA-I winds significantly underestimate the buoy wind speed(with an average bias of –1.57 m/s), while the statistical errors in the NCEP-2 wind direction have the largest magnitude. The diagnosis of the reanalysis wind errors shows the residuals of all three reanalysis wind speeds(reanalysis-buoy) decrease with increasing buoy wind speed, suggesting a narrower wind speed range than that of the observations. Moreover, wind direction errors are examined to depend on the magnitude of the wind speed and the wind speed biases. In general, the evaluation of three reanalysis wind products demonstrates that CFSv2 wind vectors are the closest to the winds along the north coast of the SCS and are sufficiently accurate to be used in numerical models.     

Sea State and Rain: A Second Take on Dual-Frequency Altimetry

TOPEX and Jason were the first two dual-frequency altimeters in space, with both operating at K_u- and C-band. Thus, each gives two measurements of the normalized backscatter, σ⁰, (from which wind speed is calculated) and two estimates of wave height. Departures from a well-defined relationship between the K_u- and C-band σ⁰ values give an indication of rain. This study investigates differences between the two instruments using data from Jason's verification phase. Jason's K_u-band estimates of wave height are ∼1.8% less than TOPEX's, whereas its σ⁰ values are higher. When these effects have been removed the root mean square (rms) mismatch between TOPEX and Jason's K_u-band observations is close to that for TOPEX's observations at its two frequencies, and the changes in σ⁰ with varying wave height conditions are the same for the two altimeters. Rain flagging and quantitative estimates of rain rate are both based on the atmospheric attenuation derived from the σ⁰ measurements at the two frequencies. The attenuation estimates of TOPEX and Jason agree very well, and a threshold of-0.5 dB is effective at removing the majority of spurious data records from the Jason GDRs. In the high σ⁰ regime, anomalous data can be caused by processes other than rain. Consequently, for these low wind conditions, neither can reliable rain detection be based on altimetry alone, nor can a generic rain flag be expected to remove all suspect data.     

Aircraft measurement of sea surface temperature during the West Coast Experiment

During the West Coast Experiment in March 1977, a test was conducted to ascertain the effectiveness of using remote sensing techniques to estimate sea surface temperature (SST) from infrared (IR) emissions of the sea surface. Aircraft flights were made over three buoys moored in southern California coastal waters, and data was collected of sea surface emissions at thermal IR wavelengths (7.95-13.5 mum). SST obtained from the remote sensing measurements were compared with in situ SST measured with thermistors mounted on the buoys. The remotely determined SST were from1.4-2.9degC lower than the in situ measurements. Several factors are discussed that could account for the differences.     

台风“灿鸿”影响下海浪的数值模拟研究

台风是影响中国黄东海的强天气现象,其引起的强风、巨浪和台风增水严重威胁着沿海地区人民的生命与财产安全。本文以海浪模式SWAN（Simulating Waves Nearshore）与区域海洋模式ROMS（Regional Ocean Modeling System）为基础,构建了中国黄东海海域在201509号台风“灿鸿”影响下的海浪-海洋耦合模式。通过浮标与Jason-2高度计有效波高数据验证了模式结果的准确性。进行了敏感性实验分析,对比耦合（ROMS+SWAN）与非耦合（SWAN）下以及使用不同地形数据（ETOPO1、ETOPO2、GEBCO）、不同物理参数化方案（风能输入、白冠耗散、底摩擦耗散）下的模拟结果差异。结果发现在射阳与前三岛浮标处,使用GEBCO地形数据（15弧秒间隔）下的模拟效果更好且稳定。在空间分布上,台风中心附近的浪流相互作用显著,在其前进方向右侧表现为耦合的有效波高值低于非耦合有效波高值,差值最高可达1米。选择不同风输入与耗散项方案时的模拟差异主要发生在最大波高处,选择不同的风能输入与白冠耗散项方案带来的差异接近0.4米,而底摩擦项方案选择不同带来的差异接近1米。因而在模拟实际的海况时,需要综合考虑这些因素带来的影响,才能达到SWAN海浪模型最好的海浪模拟效果。     

Geophysical Model Function for Wind Speed Retrieval from SARAL/AltiKa

With the launch of SARAL/AltiKa altimeter, efforts have been made to develop wind speed retrieval algorithms. Here we present two algorithms for estimating and validating wind speed from AltiKa. The first method is based on a theoretical Geophysical Model Function (GMF) using forward model simulations for Ka band specifications. The second is the model function developed using the matched database of input and output vectors of Normalized Radar Cross Section (NRCS) from AltiKa and wind speed measurements from concurrent Jason-2 altimeters. Since the NRCS depends on both the surface roughness due to surface wind speed and on mean square slope of the surfaces, the significant wave height is used along with wind speed for model development as an proxy variable. Both the theoretical and empirical GMFs are evaluated for retrieval of wind speed from AltiKa and validated with NDBC buoys data. The empirical model provide wind speed retrieval accuracy of 1.4 m/s. The accuracy of wind retrievals from theoretical model is also in the similar range (1.6 m/s), indicating the sound physical basis applicable for the future altimeters with various incidence angles. The retrieved wind speed is applied for various case studies, bringing out all the regional and global features quite well.     

Surface currents derived from satellite-tracked buoys off Namibia

To study the flow field off Namibia (20–30°S, 10–15°E), 48 satellite-tracked buoys were deployed and tracked in six bimonthly batches between July 1994 to September 1995. In situ supporting wind information was collected from a weather buoy moored off Lüderitz, from coastal stations and from voluntary observing ships. Buoy drift tracks were compared with surface topography data from the TOPEX/POSEIDON satellite and satellite infrared images. Most of the buoys drifted in a northwesterly direction, the buoys deployed in the south generally moving faster and diverging more from the coast than the northern buoys. The overall maximum daily drift velocity was 72 cm s^-1, but typical speeds were 10–30 cm s^-1. In the proximity of the coast some buoys experienced transient southward sets associated with the effect of coastal trapped waves, while tracks north of 23°S showed inertial oscillations.     

卫星高度计海面风速的校准与验证

为了改善不同卫星高度计海面风速数据之间的一致性,以浮标数据为基准,对国内的HY-2A和国外的T/P、GFO、Jason-1、Envisat、Jason-2、CryoSat-2共7颗卫星高度计的海面风速数据进行了分析,给出了各个卫星高度计的海面风速校准公式,并对其校准效果进行了验证。验证结果表明:各个卫星高度计的海面风速在经过校准后,与浮标海面风速差异的均值和均方根都有所降低,其中HY-2A最为显著。经过校准后所有卫星高度计的海面风速与浮标海面风速差异的均值都在±0.2m/s以内。除了HY-2A、GFO和Jason-1,其余4颗卫星高度计校准后的海面风速与浮标海面风速差异的均方根都在1.6m/s以下。由此可以得出结论,利用本文的校准公式对各个卫星高度计(特别是HY-2A卫星高度计)的海面风速进行校准,可以有效减少其与浮标海面风速之间的差异。     

渤海重现期波高的数值计算

利用RAMS大气模式给出的20年风场资料,利用SWAN近海波浪模式对渤海海域的波浪进行了20 a数值计算.通过与一般过程和大风过程的实测资料的对比后发现.波浪模拟值与实潮值符合地较好,SWAN模式适合渤海海域波浪的计算。通过分析发现.辽东湾常浪向为SSW。强浪向为SSW;渤海中部常浪向为S,强浪向为NE;渤海海峡常浪向为NNW,强浪向为NNW;莱州湾常浪向为S,强浪向为NNE;渤海湾常浪向为S.强浪向为NE。渤中偏东南海域(38°～39°N,119.5°～120.5°E)多年一遇有效波高最大.其中百年一遇有效波高最大值达到6.7m。     

Comparing satellite and meteorological data on wind velocity over the Black Sea

Wind-velocity data obtained from in situ measurements at the Golitsyno-4 marine stationary platform have been compared with QuikSCAT scatterometer data; NCEP, MERRA, and ERA-Interim global reanalyses and MM5 regional atmospheric reanalysis. In order to adjust wind velocity measured at a height of 37 m above the sea surface to a standard height of 10 m with stratification taken into account, the Monin–Obukhov theory and regional atmospheric reanalysis data are used. Data obtained with the QuikSCAT scatterometer most adequately describe the real variability of wind over the Black Sea. Errors in reanalysis data are not high either: the regression coefficient varies from 0.98 to 1.06, the rms deviation of the velocity amplitude varies from 1.90 to 2.24 m/s, and the rms deviation of the direction angle varies from 26° to 36°. Errors in determining the velocity and direction of wind depend on its amplitude: under weak winds (<3 m/s), the velocity of wind is overestimated and errors significantly increase in determining its direction; under strong winds (>12 m/s), its velocity is underestimated. The influence of these errors on both spatial and temporal estimates of the characteristics of wind over the Black Sea is briefly considered.     

First six months quality assessment of HY-2A SCAT wind products using in situ measurements

The first Chinese microwave ocean environment satellite HY-2A, carrying a Ku-band scatteromenter （SCAT）, was successfully launched in August 2011. The first quality assessment of HY-2A SCAT wind products is presented through the comparison of the first 6 months operationally released SCAT products with in situ data. The in situ winds from the National Data Buoy Center （NDBC） buoys, R/V Polarstern, Aurora Australis, Roger Revelle and PY30-1 oil platform, were converted to the 10 m equivalent neutral winds. The temporal and spatial differences between the HY-2A SCAT and the in situ observations were limited to less than 5 min and 12.5 km. For HY-2A SCAT wind speed products, the comparison and analysis using the NDBC buoys yield a bias of-0.49 m/s, a root mean square error （RMSE） of 1.3 m/s and an increase negative bias with increasing wind speed observation above 3 m/s. Although less accurate of HY-2A SCAT wind direction at low winds, the RMSE of 19.19° with a bias of 0.92° is found for wind speeds higher than 3 m/s. These results are found consistent with those from R/Vs and oil platform comparisons. Moreover, the NDBC buoy comparison results also suggest that the accuracy of HY-2A SCAT winds is consistent over the first half year of 2012. The encouraging assessment results over the first 6 months show that wind products from HY-2A SCAT will be useful for scientific community.     

Real time wave forecasting using wind time history and numerical model

Operational activities in the ocean like planning for structural repairs or fishing expeditions require real time prediction of waves over typical time duration of say a few hours. Such predictions can be made by using a numerical model or a time series model employing continuously recorded waves. This paper presents another option to do so and it is based on a different time series approach in which the input is in the form of preceding wind speed and wind direction observations. This would be useful for those stations where the costly wave buoys are not deployed and instead only meteorological buoys measuring wind are moored. The technique employs alternative artificial intelligence approaches of an artificial neural network (ANN), genetic programming (GP) and model tree (MT) to carry out the time series modeling of wind to obtain waves. Wind observations at four offshore sites along the east coast of India were used. For calibration purpose the wave data was generated using a numerical model. The predicted waves obtained using the proposed time series models when compared with the numerically generated waves showed good resemblance in terms of the selected error criteria. Large differences across the chosen techniques of ANN, GP, MT were not noticed. Wave hindcasting at the same time step and the predictions over shorter lead times were better than the predictions over longer lead times. The proposed method is a cost effective and convenient option when a site-specific information is desired.