Atmospheric profile retrieval with AIRS data and validation at the ARM CART site

The physical retrieval algorithm of atmospheric temperature and moisture distribution from the Atmospheric InfraRed Sounder （AIRS） radiances is presented. The retrieval algorithm is applied to AIRS clear-sky radiance measurements. The algorithm employs a statistical retrieval followed by a subsequent nonlinear physical retrieval. The regression coefficients for the statistical retrieval are derived from a dataset of global radiosonde observations （RAOBs） comprising atmospheric temperature, moisture, and ozone profiles. Evaluation of the retrieved profiles is performed by a comparison with RAOBs from the Atmospheric Radiation Measurement （ARM） Program Cloud And Radiation Testbed （CART） in Oklahoma, U. S. A.. Comparisons show that the physically-based AIRS retrievals agree with the RAOBs from the ARM CART site with a Root Mean Square Error （RMSE） of 1K on average for temperature profiles above 850 hPa, and approximately 10% on average for relative humidity profiles. With its improved spectral resolution, AIRS depicts more detailed structure than the current Geostationary Operational Environmental Satellite （GOES） sounder when comparing AIRS sounding retrievals with the operational GOES sounding products.     

A solely radiance-based spectral angular distribution model and its application in deriving clear-sky spectral fluxes over tropical oceans

The radiation budget at the top of the atmosphere plays a critical role in climate research. Compared to the broadband flux, the spectrally resolved outgoing longwave radiation or flux(OLR), with rich atmospheric information in different bands,has obvious advantages in the evaluation of GCMs. Unlike methods that need auxiliary measurements and information, here we take atmospheric infrared sounder(AIRS) observations as an example to build a self-consistent algorithm by an angular distribution model(ADM), based solely on radiance observations, to estimate clear-sky spectrally resolved fluxes over tropical oceans. As the key step for such an ADM, scene type estimations are obtained from radiance and brightness temperature in selected AIRS channels. Then, broadband OLR as well as synthetic spectral fluxes are derived by the spectral ADM and validated using both synthetic spectra and CERES(Clouds and the Earth's Radiant Energy System) observations. In most situations, the mean OLR differences between the spectral ADM products and the CERES observations are within ±2 W m~(-2), which is less than 1% of the typical mean clear-sky OLR over tropical oceans. The whole algorithm described in this study can be easily extended to other similar hyperspectral radiance measurements.     

Assimilating All-sky Infrared Radiances from Himawari-8 Using the 3DVar Method for the Prediction of a Severe Storm over North China

Although radar observations capture storm structures with high spatiotemporal resolutions, they are limited within the storm region after the precipitation formed. Geostationary satellites data cover the gaps in the radar network prior to the formation of the precipitation for the storms and their environment. The study explores the effects of assimilating the water vapor channel radiances from Himawari-8 data with Weather Research and Forecasting model data assimilation system(WRFDA) for a severe storm case over north China. A fast cloud detection scheme for Advanced Himawari imager(AHI)radiance is enhanced in the framework of the WRFDA system initially in this study. The bias corrections, the cloud detection for the clear-sky AHI radiance, and the observation error modeling for cloudy radiance are conducted before the data assimilation. All AHI radiance observations are fully applied without any quality control for all-sky AHI radiance data assimilation. Results show that the simulated all-sky AHI radiance fits the observations better by using the cloud dependent observation error model, further improving the cloud heights. The all-sky AHI radiance assimilation adjusts all types of hydrometeor variables, especially cloud water and precipitation snow. It is proven that assimilating all-sky AHI data improves hydrometeor specifications when verified against the radar reflectivity. Consequently, the assimilation of AHI observations under the all-sky condition has an overall improved impact on both the precipitation locations and intensity compared to the experiment with only conventional and AHI clear-sky radiance data.     

THE IMPACT OF MOUNTAIN TO BASIN WINDS ON THE DIURNAL VARIATION IN FOG OVER THE SICHUAN BASIN, CHINA

There is an increased demand for the accurate prediction of fog events in the Sichuan Basin (SCB) using numerical methods. A dense fog event that occurred over the SCB on 22 December 2016 was investigated. The results show that this dense fog event was influenced by the southwest of a low pressure with a weak horizontal pressure gradient and high relative humidity. This fog event showed typical diurnal variations. The fog began to form at 1800 UTC on 21 December 2016 (0200 local standard time on 22 December 2016) and dissipated at 0600 UTC on 22 December 2016 (1400 local standard time on 22 December 2016). The Weather Research and Forecasting model was able to partially reproduce the main features of this fog event and the diurnal variation in the local mountain to basin winds. The simulated horizontal visibility and liquid water content were used to characterize the fog. The mountain to basin winds had an important role in the diurnal variation of the fog event. The positive feedback mechanism between the fog and mountain to basin winds was good for the formation and maintain of the fog during the night. During the day, the mountain to basin wind displayed a transition from downslope flows to upslope flows. Water vapor evaporated easily from the warm, strong upslope winds, which resulted in the dissipation of fog during the day. The topography surrounding the SCB favored the lifting and condensation of air parcels in the lower troposphere as a result of the low height of the lifting condensation level.     

Analysis and Modeling of a Long-Lasting Fog Event over Beijing in February 2007

The evolution characteristics of a long-lasting fog event over Beijing during 20-22 February 2007 are investigated using the 5-min automatic visibility data and conventional meteorological observations.Data analysis results reveal that there is a close relationship between the development/evolution of this fog event and the weather conditions such as high humidity,light wind,and low temperature in the lower troposphere. Furthermore,numerical simulations of this event are carried out by using the Advanced...     

COMPREHENSIVE ANALYSIS OF THE MACRO- AND MICRO-PHYSICAL CHARACTERISTICS OF DENSE FOG IN THE AREA SOUTH OF THE NANLING MOUNTAINS

Using the composite field observational data collected in the area south of the Nanling Mts. and numerical modeling, the seasonal features of dense fog and visibility, fog drop spectrum and physical concept of fog forming have been analyzed. The occurring frequency of low visibility（≤200 m） is very high with a mean of 24.7%, a maximum of 41.8% from the end of autumn to winter and next spring. The fog processes that occur in the area south of the Nanling Mts. in spring and winter result from the interactions of complicated micro-physical processes, the local terrain, water vapor transportation and the influencing weather system. The fog processes are arisen from advection or windward slope, which is much different from the radiation fog. Cooling condensation due to the air lifted by the local mountain plays an important role in fog formation. Windward slope of the mountain is favorable to the fog formation. Dense fog can occur at lower altitudes in the windward slope of mountain, resulting in the lower visibility. The fog is mainly of small-drop spectrum with smaller number-density than that of urban fog, and its drop spectrum has descending trend in the section of smaller diameter. The inverse relationship between fog water content and visibility is the best among several relationships of micro-variables. In addition to micro-physical processes of fog body itself, the motion of irregular climbing and crossing over hillside while the fog body is being transported by the wind are also important reasons for the fluctuation of micro-physical parameters such as fog water content.     

Derivation of Regression Coefficients for Sea Surface Temperature Retrieval over East Asia

Among the regression-based algorithms for deriving SST from satellite measurements, regionally optimized algorithms normally perform better than the corresponding global algorithm. In this paper,three algorithms are considered for SST retrieval over the East Asia region (15°-55°N, 105°-170°E),including the multi-channel algorithm (MCSST), the quadratic algorithm (QSST), and the Pathfinder algorithm (PFSST). All algorithms are derived and validated using collocated buoy and Geostationary Meteorological Satellite (GMS-5) observations from 1997 to 2001. An important part of the derivation and validation of the algorithms is the quality control procedure for the buoy SST data and an improved cloud screening method for the satellite brightness temperature measurements. The regionally optimized MCSST algorithm shows an overall improvement over the global algorithm, removing the bias of about -0.13℃ and reducing the root-mean-square difference (rmsd) from 1.36℃ to 1.26℃. The QSST is only slightly better than the MCSST. For both algorithms, a seasonal dependence of the remaining error statistics is still evident. The Pathfinder approach for deriving a season-specific set of coefficients, one for August to October and one for the rest of the year, provides the smallest rmsd overall that is also stable over time.     

Fog Detection over China’s Adjacent Sea Area by using the MTSAT Geostationary Satellite Data

A fog threshold method for the detection of sea fog from Multi-function Transport Satellite (MTSAT1R) infrared (IR) channel data is presented.This method uses principle component analysis (PCA),texture analysis,and threshold detection to extract sea fog information.A heavy sea fog episode that occurred over China’s adjacent sea area during 7 8 April 2008 was detected,indicating that the fog threshold method can effectively detect sea fog areas nearly 24 hours a day.MTSAT-1R data from March 2006,June 2007,and April 2008 were processed using the fog threshold method,and sea fog coverage information was compared with the meteorological observation report data from ships.The hit rate,miss rate,and false alarm rate of sea fog detection were 66.1%,27.3%,and 33.9%,respectively.The results show that the fog threshold method can detect the formation,evolution,and dissipation of sea fog events over period of time and that the method has superior temporal and spatial resolution relative to conventional ship observations.In addition,through MTSAT-1R data processing and a statistical analysis of sea fog coverage information for the period from 2006 to 2009,the monthly mean sea fog day frequency,spatial distribution and seasonal variation characteristics of sea fog over China’s adjacent sea area were obtained.     

Calibration and Validation of an All-Sky Imager

The automatic all-sky imager developed by the Institute of Atmospheric Physics, Chinese Academy of Sciences, provides all-sky visible images in the red, green, and blue channels. This paper presents three major calibration experiments of the all-sky imager, geometric angular calibration, optical calibration, and radiometric calibration, and then infers an algorithm to retrieve relative radiance from the all-sky images. Field experiments show that the related coefficient between retrieved radiance and measured radiance is about 0.91. It is feasible to use the algorithm to retrieve radiance from images. The paper sets up a relationship between radiance and the image, which is useful for using the all-sky image in numerical-simulations that predict more meteorological parameters.     

A Heavy Sea Fog Event over the Yellow Sea in March 2005： Analysis and Numerical Modeling

In this paper, a heavy sea fog episode that occurred over the Yellow Sea on 9 March 2005 is investigated. The sea fog patch, with a spatial scale of several hundred kilometers at its mature stage, reduced visibility along the Shandong Peninsula coast to 100 m or much less at some sites. Satellite images, surface observations and soundings at islands and coasts, and analyses from the Japan Meteorology Agency （JMA） axe used to describe and analyze this event. The analysis indicates that this sea fog can be categorized as advection cooling fog. The main features of this sea fog including fog area and its movement axe reasonably reproduced by the Fifth-generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model （MM5）. Model results suggest that the formation and evolution of this event can be outlined as： （1） southerly warm/moist advection of low-level air resulted in a strong sea-surface-based inversion with a thickness of about 600 m; （2） when the inversion moved from the warmer East Sea to the colder Yellow Sea, a thermal internal boundary layer （TIBL） gradually formed at the base of the inversion while the sea fog grew in response to cooling and moistening by turbulence mixing; （3） the sea fog developed as the TIBL moved northward and （4） strong northerly cold and dry wind destroyed the TIBL and dissipated the sea fog. The principal findings of this study axe that sea fog forms in response to relatively persistent southerly waxm/moist wind and a cold sea surface, and that turbulence mixing by wind shear is the primary mechanism for the cooling and moistening the marine layer. In addition, the study of sensitivity experiments indicates that deterministic numerical modeling offers a promising approach to the prediction of sea fog over the Yellow Sea but it may be more efficient to consider ensemble numerical modeling because of the extreme sensitivity to model input.     

Fog detection using geostationary satellite data: Temporally continuous algorithm

A fog detection algorithm that uses geostationary satellite data has been developed and tested. This algorithm focuses on continuous fog detection since temporal discontinuities, especially at dawn and dusk, are a major problem with current fog detection algorithms that use satellite imagery data. This is because the spectral radiance at 3.7 μm contains overlapping emissive and reflectance components. In order to determine the radiance at 3.7 μm under fog conditions, radiative transfer model simulations were performed. The results showed that the radiance at 3.7 μm obviously varies with the solar zenith angle, and the brightness temperature differences between 3.7 μm and 10.8 μm are completely dissimilar between day and night (positive and varying with the angle during the daytime, but negative and constant at night). In this algorithm, a dynamic threshold is used as a function of the solar zenith angle. Moreover, additional criteria such as infrared, split-window channels, and a water vapor channel are used to remove high-level clouds. Also, the visible reflectance (0.67 μm) channel is used in the daytime algorithm because visible channel images are very practical for confirming a fog area with the high reflectivity and the smooth texture. The clear-sky visible reflectance for the previous 15 days was also employed to eliminate the surface effect that appeared during dawn and dusk. As the results, fog areas were estimated continuously, allowing the lifecycle of the fog system, from its development to decline, to appear obviously in the resulting images. Moreover, the estimated fog areas matched well with surface observations, except in a high latitude region that was covered by thin cirrus clouds.     

雾的气象卫星遥感光谱特征

从大气辐射传输理论入手，用频谱分析方法研究了气象卫星遥感图像上云雾的可见光和红外光光谱特征，阐述了雾在NOAA各通道的光谱响应特征及相关指标。根据云雾的不同顶部结构，分析了云雾反射可见光的非朗伯特性。根据瑞利(Rayleigh)准则，解释了低太阳高度角时可见光对云雾具有更强的识别作用，指出雾与云相比，具有更强的方向性反射特点，当卫星处于云雾层的镜面反射方向时，雾区具有更强的亮度，即反射率高于云区；反之．雾区则相对较暗，指出可见光在云雾识别方面具有重要作用。通过分析云雾层的不同红外光谱特点，给出了一些云雾识别与分类的指标，说明了通道组合方法对云雾识别的重要作用，为云雾分类提供了依据。通过时间动态的频谱分析，给出了判断大雾成熟期的光谱特征，对判定大雾的发展与消散具有重要意义。     

FY-2A与GMS-5红外通道遥感数据的辐射定标

该文通过辐射传输模拟计算和匹配数据统计分析实现了FY-2A和GMS-5红外通道间的辐射定标.以辐射定标为基础将FY-2A红外通道和GMS-5红外A通道的遥感资料融合应用, 可以得到时间分辨率更高、空间视野更为广阔的静止卫星遥感资料.     

山西省大雾的中尺度数值模拟

利用中尺度模式MM5（The Fifth—Generation NCAR／Penn State Mesoscale Model）对山西省2009年发生的3场典型雾个例进行了数值模拟,探讨了物理过程参数化方案对雾数值模拟的影响,确定了基于模式模拟数据的雾判别指标,为该地区大雾数值预报系统的研制提供了理论基础。结果表明,综合考虑边界层方案和辐射方案对地表温度、高空温度、2m温度及相对湿度、10m风速、雾的空间分布、雾的生消过程、雾的发展高度等要素数值模拟的影响,边界层方案选用high-resolution planetary boundary layers cheme（HIR）方案、辐射方案选用Cloud方案时,雾数值模拟的结果与实况更为一致。综合分析多个典型雾个例的模拟结果,山西省境内雾的预报指标为：20m液态水含量为0．13～0．6g·kg^（-1）,20～1500m高度大气层存在逆温层,10m风速小于4m·s^（-1）。     

基于深度学习的卫星多通道图像融合的海雾监测处理方法

海雾无论在海上还是在沿岸地带，都因其恶劣的能见度对交通运输、海洋捕捞和海洋开发工程以及军事活动等造成不良影响，因此对于海雾的实时监测和预报就显得尤为重要。本文提出了基于深度学习的静止气象卫星多通道图像融合分割算法，使用D LinkNet深度卷积神经网络语义分割算法模型对黄渤海海域范围的16通道、空间分辨率为0.5 km的Himawari 8卫星数据进行研究。分别采用均交并比（mIOU）以及观测值检验作为评价指标，在测试集上的mIOU为0.9436，并且用卫星测试数据结果与海上观测数据结果进行对比，得出雾区准确率（检测有雾且真实有雾/检测有雾）为66.5%，雾区识别率（检测有雾且真实有雾/（真实有雾-云覆盖））为51.9%，检测正确率(检测正确/总样本)93.2%。本文提出的方法能为海雾监测提供一个可靠的参考。     

在NCEPGDAS中同化MSG和GOES资料

首次将MSG-2（Meteosat Second Generation-2）卫星上的旋转增强可见光及红外成像仪（Spin—ning Enhanced Visibleand Infrared Imager,SEVIRI）的观测资料同化到美国国家环境预报中心（Na—tional Centers for Environmental Prediction,NCEP）全球资料同化系统（globaldataassimilationsys—tern,GDAS）中。对当前的地球静止业务环境卫星（Geostationary Operational Environmental Satel—lite,GOES）成像仪资料的同化问题也进行了进一步探讨。利用CRTM（The Community Radiative Transfer Model）模式,对SEVIRI辐射率观测资料进行了模拟。为了对红外辐射率资料进行模拟,CRTM模式中的几个关键部分得到改进,例如：动态更新地面发射率资料以及采用了快速精确的气体吸收模块。为了改进对SEVIRI和GOES成像仪辐射率资料的模拟效果,采用了GSICS（The Global Space—Based Inter—Calibration System）标定订正。初步研究结果表明,包含对SEVIRI辐射率资料的水汽通道（6．25和7．35μm）和二氧化碳通道（13．40μm）的同化对GFS（Global Forecast System）6d预报具有显著的正影响;而对其他5个SEVIRI红外窗口通道资料的同化则减小了这种正影响。通过应用GSICS标定算法,订正了SEVIRI和GOES-12成像仪观测资料的偏差,提高了对GFS预报的影响。此外,还需作进一步研究来提高对SEVIRI红外窗口通道辐射率资料同化的有效性。     

FY 2F红外亮温资料模拟与偏差分析

为了实现西太平洋及东亚区域FY-2F可见红外自旋扫描辐射计(VISSR)资料的直接同化,本文利用飓风天气预报模式(WRF For Hurricane,HWRF)和快速辐射传输模式(Community Radiative Transfer Model,CRTM)对FY-2F的亮温资料进行了模拟。在有云情况下,中高纬度锋面云系模拟的相对较好,而低纬热带云团模拟偏差较大。对于晴空条件下模拟的红外1、2、4通道(IR1、2、4)亮温,受陆地下垫面发射率不均匀的影响模拟偏差较大,且辐射传输模式平均而言低估了地表发射率。海洋下垫面的资料模拟情况要明显好于陆地。IR4通道在白天受太阳短波影响观测亮温偏高。去除受云污染的资料仅保留晴空观测资料,通过格点统计插值(Community Gridpoint Statistical Interpolation,GSI)质量控制和偏差订正,IR2通道平均偏差减小约50%,IR3通道平均偏差从3.7 K减小到0.34 K。而IR1通道质量较好,偏差订正前后几乎没有变化。     

基于多灰度共生矩阵特征值的黄渤海白天海雾识别算法

本文基于多灰度共生矩阵特征值,即相关性、对比度、同质性和能量,进行联合海雾遥感判识,提出一种高准确率黄渤海白天海雾识别算法。采用第二代静止气象卫星FY-4A可见光、近红外和红外数据,将该算法应用于黄渤海区域白天海雾判识,并利用2019—2020年沿黄渤海气象站点能见度实测数据及CALIPSO卫星数据产品对本算法识别结果进行精度验证。结果表明：海雾识别平均检测率(POD)为92%,误报率(FAR)为27%,临近成功指数(CSI)为69%,可以实现对海雾的动态监测,为海上交通等领域提供较好的数据支持。