Analysis of atmospheric turbulence in the upper layers of sea fog

Atmospheric turbulence plays a vital role in the formation and dissipation of fog. However,studies of such turbulence are typically limited to observations with ultrasonic anemometers less than 100 m above ground. Thus,the turbulence characteristics of upper fog layers are poorly known. In this paper,we present 4-layers of data,measured by ultrasonic anemometers on a wind tower about 400 m above the sea surface; we use these data to characterize atmospheric turbulence atop a heavy sea fog. Large differences in turbulence during the sea fog episode were recorded. Results showed that the kinetic energy,momentum flux,and sensible heat flux of turbulence increased rapidly during the onset of fog. After onset,high turbulence was observed within the uppermost fog layer. As long as this turbulence did not exceed a critical threshold,it was crucial to enhancing the cooling rate,and maintaining the fog. Vertical momentum flux and sensible heat flux generated by this turbulence weakened wind speed and decreased air temperature during the fog. Towards the end of the fog episode,the vertical distribution of sensible heat flux reversed,contributing to a downward momentum flux in all upper layers. Spatial and temporal scales of the turbulence eddy were greater before and after the fog,than during the fog episode. Turbulence energy was greatest in upper levels,around 430 m and 450 m above mean sea level(AMSL),than in lower levels of the fog(390 m and 410 m AMSL); turbulence energy peaked along the mean wind direction. Our results show that the status of turbulence was complicated within the fog; turbulence caused fluxes of momentum and sensible heat atop the fog layer,affecting the underlying fog by decreasing or increasing average wind speed,as well as promoting or demoting air temperature stratification.     

Comparison study between observation and simulation for sea fog over the Yellow Sea in May 2009

In this paper, almost all available observational data and the latest 6.0 version of Regional Atmospheric Modeling System (RAMS) model were employed to investigate a heavy sea fog event occurring over the Yellow Sea from 2 to 5 May 2009. The evolutionary process of this event was documented by using Multifunctional Transport Satellites-1 (MTSAT-1) visible satellite imagery. The synoptic situation, sounding profiles at two selected stations were analyzed. The difference between the air temperature and sea surface temperature during the sea fog event over the entire sea region was also analyzed. In order to better understand this event, an RAMS modeling with a 15 km×15 km resolution was performed. The model successfully reproduced the main characteristics of this sea fog event. The simulated height of fog top and the area of lower atmospheric visibility derived from the RAMS modeling results showed good agreement with the sea fog area identified from the satellite imagery. Examinations of both observational data and RAMS modeling results suggested that advection cooling seemed to play an important role in the formation of this sea fog event.     

An analysis and modeling study of a sea fog event over the Yellow and Bohai Seas

In this study, a sea fog event which occurred on 27 March 2005 over the Yellow and Bohai Seas was investigated observationally and numerically. Almost all available observational data were used, including satellite imagery of Geostationary Operational Environmental Satellite (GOES)-9, three data sets from station observations at Dandong, Dalian and Qingdao, objectively reanalyzed data of final run analysis (FNL) issued by the National Center for Environmental Prediction (NCEP) and Regional Atmospheric Modeling System (RAMS) results. Synoptic conditions and fog characteristics were analyzed. The fog formed when warm,moist air was advected northwards over the cool water of the Yellow and Bohai Seas, and dissipated when a cold front brought northerly winds and cool, dry air. In order to better understand the fog formation mechanism, a high-resolution RAMS modeling with a 6km×6km grid, initialized and validated by FNL data, was designed. A 48h modeling that started from 12 UTC 26 March 2005reproduced the main characteristics of this sea fog event. The simulated lower visibility area agreed reasonably well with the sea fog region identified from the satellite imagery. Advection cooling effect seemed to play a significant role in the fog formation.     

On spatiotemporal characteristics of sea fog occurrence over the Northern Atlantic from 1909 to 2008

In this paper, the International Comprehensive Ocean and Atmosphere Data Set(ICOADS) is utilized to investigate the horizontal distribution of sea fog occurrence frequency over the Northern Atlantic as well as the meteorological and oceanic conditions for sea fog formation. Sea fog over the Northern Atlantic mainly occurs over middle and high latitudes. Sea fog occurrence frequency over the western region of the Northern Atlantic is higher than that over the eastern region. The season for sea fog occurrence over the Northern Atlantic is generally from April to August. When sea fogs occur, the prevailing wind direction in the study area is from southerly to southwesterly and the favorable wind speed is around 8 m s-1. It is most favorable for the formation of sea fogs when sea surface temperature(SST) is 5℃ to 15℃. When SST is higher than 25℃, it is difficult for the air to get saturated, and there is almost no report of sea fog. When sea fogs form, the difference between sea surface temperature and air temperature is mainly-1 to 3℃, and the difference of 0℃ to 2℃ is the most favorable conditions for fog formation. There are two types of sea fogs prevailing in this region: advection cooling fog and advection evaporating fog.     

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。     

顾及风向和风速的空气污染物浓度插值方法

随着经济的快速发展,中国大部分地区空气污染状况日趋严重。空气污染物浓度插值对于进一步分析污染物时空分布情况,估计不同地区人群的暴露风险,制定防范措施具有重要作用。然而,现有空间插值方法由于没有充分考虑风向和风速因素对于污染物扩散的影响,故直接应用于空气污染物浓度插值,会对插值结果造成不利的影响。因此,本文提出一种顾及风向和风速的空气污染物浓度插值方法（Direction-Velocity IDW,DVIDW）。该方法首先根据离散气象站点处的风向和风速数据建立风场表面,然后利用风场数据计算空气污染物的扩散距离,根据扩散距离计算风场中待求点与采样点间的最短路径距离,最后由最短路径距离替代欧式距离进行反距离加权插值。本文分别采用2组实际空气污染物浓度数据,对DVIDW方法和其他常用的空间插值方法进行实验对比分析,验证了本文方法的可行性和优越性。     

区域优化Peterson模型的气溶胶光学厚度估算分析

气溶胶光学厚度作为描述气溶胶光学特性的重要参数之一, 被广泛应用于空气质量监测及辐射传输模型的大气订正等研究中。卫星遥感可快速反演获取大范围气溶胶信息, 但其产品通常因云覆盖或暗目标算法等原因而存在空间覆盖率较低的问题, 且产品时相受限于卫星过境时间。水平能见度作为描述气溶胶光学特性的另一重要参数, 由分布广泛的气象台站一日8 次固定时间多次发布。建立水平能见度与气溶胶光学厚度的转换关系, 可实现对卫星反演气溶胶光学厚度的有益补充。本文利用2001-2009 年的MODIS气溶胶光学厚度产品与中国华东地区71 个气象台站的水平能见度数据, 对描述两者转换关系的Peterson 模型进行区域优化。采用分区域高斯曲线拟合的方法, 对影响转换精度的主要参数气溶胶标高随时间变化规律开展研究和模拟。利用2010 年数据对优化模型进行精度及区域适用性验证。结果表明, 优化后模型的气溶胶光学厚度估算均方根误差为0.31, 低于原模型误差;精度基本上与单站点优化模型一致, 但在实用性方面优于单站点优化模型。     

Retrieval of Atmospheric Horizontal Visibility by Statistical Regression from NOAA/AVHRR Satellite Data

Based on the atmospheric horizontal visibility data from forty-seven observational stations along the eastern coast of China near the Taiwan Strait and simultaneous NOAA/AVHRR multichannel satellite data during January 2001 to December 2002, the spectral characters associated with visibility were investigated. Successful retrieval of visibility from multichannel NOAA/AVHRR data was performed using the principal component regression （PCR） method. A sample of retrieved visibility distribution was discussed with a sea fog process. The correlation coefficient between the observed and retrieved visibility was about 0.82, which is far higher than the 99.9% confidence level by statistical test. The rate of successful retrieval is 94.98% of the 458 cases during 2001 2002. The error distribution showed that high visibilities were usually under-estimated and low visibilities were over-estimated and the relative error between the observed and retrieved visibilities was about 21.4%.     

基于机器学习的高精度高分辨率气象因子时空估计

气象变量常作为重要的影响因子出现在环境污染、疾病健康和农业等领域,而高分辨率的气象资料可作为众多研究的基础数据,对推进相关研究的发展意义重大。本文以中国大陆为研究区域,利用2015年824个气象站点的气温、相对湿度和风速3套数据,结合不同的解释变量组合,分别构建了各自的GAM和残差自编码器神经网络（简称残差网络）模型,以10倍交叉验证判断模型是否过拟合。研究结果表明：① GAM和残差网络方法都不存在过拟合问题,同GAM相比,残差网络显著提高了模型预测的精度（3个气象因素的交叉验证CV R²平均提高了0.21,CV RMSE平均降低了37%）,其中相对湿度模型的提升幅度最大（CV R²:0.85 vs. 0.52,CV RMSE:7.53% vs. 13.59%）;② 残差模型的结果较普通克里格插值结果和再分析资料更接近站点观测数据,表明残差网络可作为高分辨率气象数据研制的可靠方法。此外,研究还发现在相对湿度模型中加入臭氧浓度和气温、在风速模型中加入GLDAS风速再分析资料,可提升模型的性能。     

The climate background and synoptic situation of fog at Great Wall Station, Antarctica

Based on the observed and NCEP reanalysis data from 1985 to 2006,the climate background and synoptic situation of fog at Great Wall Station were analyzed. It is shown that the seasonal variation of fog is controlled by the change of general circulation and local pressure field. Three favorable typical synoptic situations for fog development are found, the Front-of-A-Depression type, the Saddle-Shaped-Field type and the Passing-Weak-Cyclone type. The first one is the most important situation. Advection cooling fog is dominant at Great Wall Station, but there are other kinds of fog as well. As a result, some helpful principles for local fog forecasting are given.     

Study of the Wind Conditions in the South China Sea and Its Adjacent Sea Area

An increasing number of marine structures have been built for coastal protection and marine development in recent years,and wind,which is crucial to marine structures,should be analyzed.Therefore,typhoon frequency,wind climate,wind energy assess-ment,and extreme wind speed in the South China Sea(SCS)are investigated in detail in this study.The data are obtained from the China Meteorological Administration,the European Centre for Medium-range Weather Forecasts,and the National Centers for Envi-ronmental Prediction.The offshore wind energy potential is analyzed at five sites near the coast.The spatial and monthly frequencies of tropical cyclones for different intensity categories are analyzed.The extreme wind speed is fitted by five distribution models,and the generalized extreme value(GEV)distribution is selected as the most suitable function according to the goodness of fit.The spa-tial distributions of extreme wind speeds in the SCS are plotted on the basis of the GEV distribution and ERA5 data sets.The influ-ences of the distribution models and data sets on the calculated results are discussed.Moreover,the monthly extreme wind speed and comparison with the results of previous studies are analyzed.This study provides a reference for the design of wind turbines.     

Comparison of wind data from ERA-Interim and buoys in the Yellow and East China Seas

We compared data of sea surface wind from the European Centre for Medium-Range Weather Forecasts Interim Reanalysis(ERA-Interim) with that collected from eight buoys deployed in the Yellow and East China seas.The buoy data covered a period from 2010 to 2011,during which the longest time series without missing data extended for 329 days.Results show that the ERA-Interim wind data agree well with the buoy data.The regression coefficients between the ERA-Interim and observed wind speed and direction are greater than 0.7 and 0.79,respectively.However,the ERA-Interim wind data overestimate wind speed at most of the buoy stations,for which the largest bias is 1.8 m/s.Moreover,it is found from scatter plots of wind direction that about 13%of the ERA-Interim wind data can be classified as bad for wind speeds below6 m/s.Overall,the ERA-Interim data forecast both the wind speed and direction well,although they are not very representative of our observations,especially those where the wind speed is below 6 m/s.     

Recent observations and modeling study about sea fog over the Yellow Sea and East China Sea

This review presents some of the latest achievements in sea fog research,including fog climatology,fog structure in the marine atmospheric boundary layer,and numerical simulations and forecasting of fog.With the development of atmospheric observational techniques and equipments,new facts about sea fog are revealed.The mechanisms involved in the formation,development and dissipation of sea fog are further explored with the help of advanced atmospheric models.     

SUT法偏差改正的Partial EIV模型方差分量估计及其精度评定

由于部分变量误差（partial errors-in-variables,Partial EIV）模型方差分量估计精度评定理论不完善,将SUT采样法应用于Partial EIV模型的最小范数二次无偏估计（the minimum norm quadratic unbiased estimator, MINQUE）,利用方差分量估计修正随机模型并以此作为先验信息对观测向量进行SUT法采样得到参数的加权均值和二阶精度信息。考虑到非线性模型的偏差,进行偏差改正,再通过SUT法对改正后的参数采样计算二阶精度信息。通过算例实验验证,结合SUT法和方差分量估计求解Partial EIV模型,能够有效地避免复杂的求导运算,并获得更为精确的参数估值和合理的二阶精度信息,表明偏差改正的必要性。     

雾霾对GPS天顶对流层延迟与精密单点定位影响研究

通过计算对流层延迟和精密单点定位的点位坐标,研究雾霾天气对GPS天顶对流层延迟和精密单点定位精度的影响。结果表明,当空气质量持续良好、没有雾霾发生时,空气质量指数(air quality index, AQI)与对流层延迟的相关性很小;当重度雾霾天气持续发生时,雾霾会对天顶对流层延迟产生40~60 mm的影响。但在精密单点定位中,通过对对流层延迟进行参数估计的方法可以消除绝大部分雾霾对定位精度的影响,因此无论重度雾霾天气是否发生,AQI指数与精密单点定位精度的相关性很小。     

重庆辐射雾的声雷达回波与大气污染特征

结合气象观测和大气边界层探测资料，分析了１９９０年１月２日重庆雾的声雷达回波特征，并与１９８９年１２月３０日雾的回波作了比较。结果表明，雾顶回波高度与逆温和相对湿度的转折高度一致；雾顶回波在雾的成熟期呈现波动，在消散期有一下降过程。上午大气污染物地面浓度的变化与逆温混合层状况有密切关系，混合层较薄且持续时间较长时，地面浓度较大     

“重庆雾”动力统计预报模型

本文首先对重庆雾1981～1987年159个例进行500hPa、700hPa、850hPa各气象要素的相关和合成分析,得到了影响重庆雾的主要因子和主要关键区以及雾发生时24小时以前各层要素场的异常特征。在此基础上,对重庆雾进行了分类,用关键区的因子作为自变量,利用逐步回归残差订正和模型集成,建立起重庆雾24小时预报模型,并设计成软件系统,在IBM机上自动预报。     

基于摄影测量的ASTER影像云顶高度解算模型与实验

云顶高度是天气预报、天气监测的重要因子,准确的云顶高度对提高天气分析和数值预报的质量,具有重要的科学意义。立体几何法是公认云顶高度解算精度较高的方法,目前,普遍采用卫星-球心-投影云-真云的平面和球面三角几何关系,以及影像匹配技术解算云顶高度,由于采用了理想椭球体和重投影技术,以及对云移动考虑不足,因此误差较大。本文将数字摄影测量理论与遥感技术相结合,首次将摄影测量共线方程用于云顶高度解算。本文利用ASTER影像,依据相关系数法解求云迹风,并将其引入到摄影测量共线方程中,建立了ASTER影像的云顶高度解算模型,进行了未考虑和考虑风速的云顶高度解算,通过地面点计算,本文解算误差为2个像元（30 m）左右,经与MISR云顶高度产品对比分析,认为该模型解算的考虑风速的云顶高度精度优于MISR解算结果。     

甘肃庆阳市雾的气候特点及其预报思路初探

通过统计甘肃庆阳市1971～2003年的历史资料，分析了庆阳市雾的气候特征：庆阳市年均雾日最大值出现在西峰、合水一带，雾日以秋季9月、10月和春季3月出现较多，夏季、冬季和春季4月、5月较少。对2000～2003年出现的101次雾天气条件做了分析，就形成雾的原因和环流特征做了初步探讨，并归纳提出了庆阳市雾预报的着眼点和一般的预报思路，辐射雾和平流雾分别对应两种截然相反的天气条件，要根据形成雾的天气系统环流典型场采取不同的预报思路，着重分析天气系统的演变，还要分析本地湿度、温度和风向风速等气象要素场的变化特征。     

广汉机场一次非典型辐射平流雾的天气诊断分析

为探索广汉机场雾发生发展的机制,确保飞行安全,提高预报准确率,利用广汉机场地面观测资料、Mi—caps系统下的常规观测资料、探空资料和NCEP／NCAR再分析资料,采用天气诊断分析方法,对2012年11月13日-15日广汉机场持续性的辐射平流雾进行分析。结果表明,雾是在稳定的天气背景下形成。夜间地面长波辐射冷却触发了这次雾的形成,而在轻雾转大雾期间,地面长波辐射冷却作用明显减弱,低层暖湿平流则起到了主要作用。与典型辐射平流雾不同的是成雾后,机场由脊前西北气流转为南支槽前西南气流控制,天空中云量的迅速增加使得雾进一步加强。